State of the art and future directions of pancreatic ductal adenocarcinoma therapy.

State of the art and future directions of pancreatic ductal adenocarcinoma therapy Cindy Neuzillet, Annemila¨ı Tijeras-Raballand, Philippe Bourget, Jérôme Cros, Anne Couvelard, Alain Sauvanet, Marie-Pierre Vullierme, Christophe Tournigand, Pascal Hammel PII: DOI: Reference:

S0163-7258(15)00164-3 doi: 10.1016/j.pharmthera.2015.08.006 JPT 6810

To appear in:

Pharmacology and Therapeutics

Please cite this article as: Neuzillet, C., Tijeras-Raballand, A., Bourget, P., Cros, J., Couvelard, A., Sauvanet, A., Vullierme, M.-P., Tournigand, C. & Hammel, P., State of the art and future directions of pancreatic ductal adenocarcinoma therapy, Pharmacology and Therapeutics (2015), doi: 10.1016/j.pharmthera.2015.08.006

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C. NEUZILLET et al., PDAC state of the art

P&T #22740

State of the art and future directions of pancreatic ductal adenocarcinoma therapy

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Cindy Neuzillet1,2,3, M.D., Annemilaï Tijeras-Raballand4, Ph.D., Philippe Bourget5, Pharm.D., Ph.D., Jérôme Cros1,6, M.D., Ph.D., Anne Couvelard1,6, M.D., Ph.D., Alain Sauvanet7, M.D., Ph.D., Marie-Pierre Vullierme8, M.D., Christophe Tournigand3, M.D., Ph.D., Pascal Hammel1,2, M.D., Ph.D.

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1. INSERM UMR1149, Bichat-Beaujon University Hospital (AP-HP – PRES Paris 7 Diderot), 46 rue Henri Huchard, 75018 Paris, and 100 boulevard du Général Leclerc, 92110 Clichy, France 2. Department of Digestive Oncology, Beaujon University Hospital (AP-HP – PRES Paris 7 Diderot), 100 boulevard du Général Leclerc, 92110 Clichy, France 3. Department of Medical Oncology, Henri Mondor University Hospital, 51 avenue du Maréchal de Lattre de Tassigny, 94010 Créteil, France 4. Department of Translational Research, AAREC Filia Research, 1 place Paul Verlaine, 92100 Boulogne-Billancourt, France 5. Department of Clinical Pharmacy, Necker-Enfants Malades University Hospital, 149 Rue de Sèvres, 75015 Paris, France 6. Department of Pathology, Bichat-Beaujon University Hospital (AP-HP – PRES Paris 7 Diderot), 46 rue Henri Huchard, 75018 Paris, and 100 boulevard du Général Leclerc, 92110 Clichy, France 7. Department of Biliary and Pancreatic Surgery, Beaujon University Hospital (AP-HP – PRES Paris 7 Diderot), 100 boulevard du Général Leclerc, 92110 Clichy, France 8. Department of Radiology, Beaujon University Hospital (AP-HP – PRES Paris 7 Diderot), 100 boulevard du Général Leclerc, 92110 Clichy, France

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Corresponding author: Dr. Cindy Neuzillet, M.D., Department of Medical Oncology, Henri Mondor University Hospital, 51 avenue du Maréchal de Lattre de Tassigny, 94010 Créteil, France. E-mail: [email protected]; fax: +33 1 49 81 25 79; tel.: +33 6 82 55 04 92. Disclosure/Conflict of Interest: The authors declare no conflict of interest. Running Title: PDAC state of the art. Key Words: chemotherapy, imaging, pancreatic cancer, pathology, radiotherapy, targeted therapy.

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Contents: 1. Introduction

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2. Development of pancreatic ductal adenocarcinoma

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2.1. Cell of origin (acinar vs ductal cell)

mucinous neoplasm, mucinous cystic neoplasm

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2.2. Precancerous lesions: pancreatic intraepithelial neoplasia, intraductal papillary and

2.3. Risk factors: nicotine, obesity/diabetes/insulin resistance, chronic pancreatitis and the role of inflammation

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2.4. Genetic and molecular cascade of events

2.5. Role of microenvironment: pancreatic stellate cells, immune cells, neural cells, abundance

2.6. Changes in metabolic pathways 3. Diagnosis and staging

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and composition of stroma

3.1. Clinical presentation and value of CA 19-9

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3.2. Evolution in imaging techniques: current standard of care (MDCT, MRI, EUS, and 18FDG-PET)

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3.3. Resectable, borderline resectable, locally advanced, and metastatic pancreatic ductal adenocarcinoma: classification as the framework for treatment strategy and pre-therapeutic

4. Therapeutics

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prognosis evaluation

4.1. Metastatic PDAC

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4.2. Resectable PDAC

4.3. Borderline resectable PDAC 4.4. Locally advanced PDAC 5. Unanswered clinical questions 6. Research pathways for the future of PDAC management 6.1. Challenges and advances in preclinical models 6.2. PDAC screening and early diagnosis 6.3. Inter- and intra-tumor heterogeneity: molecular subtypes and predictive markers 6.4. Current therapeutic research pathways 6.5. Innovative complementary interventions: quality of life and physical activity 7. General conclusion: from benchside to bedside

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Abstract Pancreatic ductal adenocarcinoma (PDAC) is expected to become the second cause of cancer-related

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death in 2030. PDAC is the poorest prognostic tumor of the digestive tract, with 80% of patients

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having advanced disease at diagnosis and 5-year survival rate not exceeding 7%.

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Until 2010, gemcitabine was the only validated therapy for advanced PDAC with a modest improvement in median overall survival as compared to best supportive care (5-6 vs 3 months). Multiple phase II-III studies have used various combinations of gemcitabine with other

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cytotoxics or targeted agents, most in vain, in attempt to improve this outcome. Over the past few years, the landscape of PDAC management has undergone major and rapid changes with the approval of the FOLFIRINOX and gemcitabine plus nab-paclitaxel regimens in

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patients with metastatic disease. These two active combination chemotherapy options yield an improved median overall survival (11.1 vs 8.5 months, respectively) thus making longer survival a

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reasonably achievable goal. This breakthrough raises some new clinical questions about the management of PDAC. Moreover, better knowledge of the environmental and genetic events that

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underpin multistep carcinogenesis and of the microenvironment surrounding cancer cells in PDAC

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has open new perspectives and therapeutic opportunities. In this new dynamic context of deep transformation in basic research and clinical management aspects of the disease, we gathered updated preclinical and clinical data in a multifaceted review encompassing the lessons learned from the past, the yet unanswered questions, and the most

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promising research priorities to be addressed for the next 5 years.

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Abbreviations: 18

FDG-PET: 18F-fluorodeoxyglucose-positron emission tomography

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5FU: 5-fluorouracil

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α-SMA: α-smooth muscular actin AA: amino acid APA: adapted physical activity

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ATP: adenosine triphosphate

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BCAA: branched-chain amino acid CA 19-9: carbohydrate antigen 19-9

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CRT: chemoradiotherapy

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dCK: deoxycytidine kinase

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ctDNA: circulating tumor DNA

Dclk1: doublecortin like kinase-1 DFS: disease-free survival

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ECM: extracellular matrix

ECOG: Eastern Cooperative Oncology Group EGF: epidermal growth factor ERCP: endoscopic retrograde cholangio-pancreatography EUS: endoscopic ultrasonography FDR: fixed dose rate GDH: glutamate dehydrogenase GOT: glutamic-oxaloacetic transaminase HE: hematoxylin and eosin

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hENT-1: human equilibrative nucleoside transporter 1 HRQoL: health-related quality of life

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IGF: insulin-like growth factor

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LDH: lactate dehydrogenase MDCT: multiple detector-computed tomography MRI: magnetic resonance imaging

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MSC: mesenchymal stem cells

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OS: overall survival PanIN: pancreatic intraepithelial neoplasia lesion

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PARP: poly-(ADP-ribose) polymerases

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PFS: progression-free survival PSC: pancreatic stellate cell RR: relative risk

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PDAC: pancreatic ductal adenocarcinoma

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TCA: tricarboxylic acid

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1. Introduction

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Pancreatic cancer is the 12th most frequent malignancy and the seventh leading cause of cancerrelated death in men and the eighth in women worldwide (Torre et al., 2015). In developed countries, it is the fourth cause of cancer-related death (Siegel, Miller, & Jemal, 2015). Its incidence is dramatically increasing worldwide; it is expected to become the second cause of cancer death in the United States in 2030 (Rahib et al., 2014).

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The vast majority of malignant pancreatic tumor cases (85%) are pancreatic ductal adenocarcinoma (PDAC). PDAC has the poorest prognostic among digestive tract malignancies with a 5-year survival rate of 5%-7%, with no significant change in death rate in 1997-2007 ("National Cancer Institute. Cancer Statistics," 1975-2007 (SEER 9)). Complete surgical resection is the only treatment that can provide prolonged survival. However, due to lack of initial symptoms at early stage and high invasive potential, diagnosis is made at an advanced stage in 80% of cases, when patients already have metastases or locoregional extension (Rhim et al., 2012; Ryan, Hong, & Bardeesy, 2014a). Moreover, most patients with an apparently localized disease who may undergo a curative-intent resection will promptly develop metastatic and/or local relapses. The median survival after curative resection is about 20-24 months, 9-15 months in patients with locally advanced PDAC, and 6-9 months in those with metastatic disease (Ryan et al., 2014a). Advanced PDAC remains a challenging, non-curable disease attracting attention of medical and surgical specialists, as well as pharmacologists. Over a decade (1997-2010), gemcitabine was the only validated chemotherapy regimen for advanced PDAC, yet the improvement obtained with this drug in terms of median overall survival (OS) was only of about 3 months as compared with best supportive care (BSC) (5-6 months vs 3 months). Several phase II and III studies have been designed as add-on benefit using various combinations of gemcitabine with other cytotoxics or targeted agents such as tyrosine kinase inhibitors and monoclonal antibodies. However, most of these doublets failed to demonstrate a superiority over gemcitabine monotherapy (Ryan et al., 2014a). The landscape of PDAC management has undergone major changes during the 5 past years with the approval of two active combinations of cytotoxics: the FOLFIRINOX (5-fluorouracil [5FU], irinotecan, and oxaliplatin) and the gemcitabine plus nab-paclitaxel regimens. These combination regimens were shown to be superior to gemcitabine in patients with metastatic PDAC, yielding median OS of 11.1 and 8.5 months, respectively (Conroy et al., 2011; Von Hoff et al., 2013). After advent of these chemotherapy regimens, longer survival for patients with advanced PDAC has turned to a reasonably achievable goal, while before median life expectancy rarely got beyond one year. This breakthrough has raised some new specific clinical questions about the management of PDAC patients. Moreover, better knowledge of the environmental etiological factors (particularly, obesity/insulin resistance and nicotine exposure), the molecular and genetic events that underpin multistep carcinogenesis, and the microenvironment surrounding cancer cells (pancreatic stellate cells [PSC], immune cells, neural cells, abundance and composition of stroma) has opened new perspectives of therapeutic opportunities in PDAC. Accumulation of preclinical data, especially in recent years, provides a strong rational for the development of news drugs and strategies aiming to better control disease progression. In this dynamic context of deep changes in both the basic research and clinical management aspects of a disease that is becoming a major health issue, it appears crucial to gather updated preclinical and clinical data on PDAC. In this review, we summarize the lessons learned from the past, the yet unanswered questions, and the most promising research pathways to draw up a state of the art and the future directions in PDAC management. 2. Development of pancreatic ductal adenocarcinoma 2.1. Cell of origin (acinar vs ductal cell)

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Activating KRAS mutations are present in more than 90% of PDAC and represent one of the earliest oncogenic events driving pancreatic carcinogenesis (Hezel, Kimmelman, Stanger, Bardeesy, & Depinho, 2006). It has long been a matter of controversy which pancreatic cell type(s) can give rise to PDAC when mutant KRAS is expressed. Although PDAC displays ductal characteristics, it may not necessarily emerge from the ductal compartment. Moreover, there is some preclinical evidence for its non-ductal origin, i.e. acinar, centroacinar, or insulin-positive cells (Morris, Wang, & Hebrok, 2010). Mouse models harboring mutant KRAS in specific populations of adult pancreatic cells showed that aberrant KRAS signaling can convert differentiated acinar pancreatic cells into duct-like lineages capable of progressing through pre-malignant pancreatic intraepithelial neoplasia (PanIN) to PDAC (Hezel et al., 2006). The process preceding PanIN formation is also known as acinar-to-ductal metaplasia (ADM): following pancreatic injury or KRAS activation acinar cells gradually lose their acinar features and acquire a ductal phenotype. Recent studies have unravelled the underlying mechanisms involved in this process. The ductal differentiation factor SOX9 has been identified as a critical mediator of ADM and tumor initiation in acinar cells (Kopp et al., 2012). Ectopic SOX9 induction promotes the expression of ductal genes in acinar cells and has been shown to be necessary for KRAS-mediated formation of PanIN. Moreover, rather than mimicking normal pancreatic ducts, metaplastic cells harboring oncogenic KRAS acquire a proliferative biliary progenitor phenotype and form tuft cells. Commonly found in the biliary tract, tuft cells are normally absent from murine pancreas, but have been identified as PanIN initiating cells. These are chemosensory cells and respond to signals from the extracellular environment by the production of effector molecules, leading to inflammation and collagen deposition (Delgiorno et al., 2014). Metaplastic cells co-express the transdifferentiation SOX17 promoter and PDX1 suppressor, which control tuft cell formation and early PDAC carcinogenesis (Takeuchi, Delgiorno, Halbrook, & Crawford, 2014). Co-expression of these developmental transcription factors with opposing roles may account for cellular heterogeneity within early pre-malignant pancreatic lesions (Lafaro, Hendley, Bailey, & Leach, 2014). By contrast, centroacinar-specific or ductal-specific activation of KRAS rarely results in PanIN formation, despite the histological resemblance of PanIN to pancreatic ducts. The refractory nature of ductal cells to KRAS activation suggests that tumor suppressive pathways may be active in these cells and that a cooperating “second hit” leading to the downregulation of these suppressor genes is required to induce cellular transformation. Indeed, conjunction of KRAS activation and reduced expression of the tumor suppressor gene PTEN induces malignant transformation through another type of premalignant lesion, intraductal papillary and mucinous neoplasm (IPMN) (Sander, Kopp, Dubois, & Stiles, 2014). Overall, preclinical models suggest that both acinar and ductal cells can initiate PDAC via distinct genetic events and carcinogenesis pathways. Alternatively, there is some preclinical evidence suggesting that stem cells are putative precursors of PDAC. Cancer cells may emerge from particular progenitor cells expressing doublecortin like kinase-1 (Dclk1) and regulated by adrenergic signaling. The microtubule regulator Dclk1 is a marker for radial glial cells in the central nervous system. It has been proposed as a marker of pancreatic stem cells and cancer-initiating cells (Bailey et al., 2014). In the normal pancreas, Dclk1+ cells are rare, longlived, and quiescent. However, following pancreatic injury such as pancreatitis, these get activated, expand and play a critical role in pancreatic tissue regeneration. Lineage tracing studies revealed that Dclk1+ cells could differentiate in both ductal and acinar cells. The presence of oncogenic KRAS in Dclk1+ cells leads to PDAC formation after pancreatitis induction (Westphalen et al., 2014). Dclk1+ cells are frequently observed in the early stage of murine IPMN development and may serve as part of an initiating niche for IPMN. In addition, Dclk1+ cells are in close interaction with nerves. During PDAC carcinogenesis, the increase in Dclk1+ cells is associated with an increase in nerve density. In in vitro and in vivo PDAC models, adrenergic receptors and signaling are upregulated and promote tumor formation (Westphalen et al., 2014). Then, Dclk1+ cells activation and tumor initiation may be related to stress and adrenergic signaling.

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Figure 1 summarized the current knowledge about PDAC development.

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2.2. Precancerous lesions: pancreatic intraepithelial neoplasia, intraductal papillary and mucinous neoplasm, mucinous cystic neoplasm Pre-malignant pancreatic lesions include PanIN, IPMN, and mucinous cystic neoplasms (MCN) (Lennon et al., 2014). These three lesions follow a progressive evolution according to an adenoma-tocancer sequence (i.e. low-grade to high-grade dysplasia, also known as carcinoma in situ, then invasive carcinoma), similarly to the Vogelstein’s model for colon carcinogenesis (Vogelstein et al., 1988). PanIN are microscopic (< 0.5 cm), non-invasive epithelial proliferations within the pancreatic ducts (Hruban et al., 2004; Lennon et al., 2014) that can be flat or micropapillary, and are classified into four grades (i.e. PanIN-1A, -1B, -2, and -3) of increasing dysplasia in parallel with the accumulation of mutations, ultimately giving rise to PDAC (Hruban, Goggins, Parsons, & Kern, 2000). Of note, in human specimens, PanIN-3 is often found at the periphery of invasive adenocarcinoma; in this setting, the question whether PanIN-3 is the precursor or an intraductal extension of PDAC is still open. KRAS mutations are detected in early-stage PanIN and occur more frequently in advanced stages and PDAC, raising an unresolved question as to when deregulated K-Ras activity is necessary for disease progression (Morris et al., 2010). p16/CDKN2A gene alteration is also an early genetic event found in PanIN-1 and PanIN-2, while the higher grade PanIN-3 lesions and invasive adenocarcinoma often harbor additional mutations in TP53, BRCA2, and TGFβ/SMAD4 pathway genes (Hruban et al., 2000; Kanda et al., 2012). Genetically engineered PDAC mouse models consistently recapitulate this genetic and biological evolution (Mazur & Siveke, 2012; Morris et al., 2010). In addition, whole-exome sequencing studies revealed that mutations in DNA damage response genes are prevalent in both PanIN and PDAC and that genes encoding proteins involved in gap junctions, actin cytoskeleton, mitogen-activated protein kinase (MAPK) signaling pathway, axon guidance, and cell-cycle regulation are among the earliest targets of mutagenesis in PanIN that progress to PDAC (Murphy et al., 2013). IPMN is the second major PDAC precursor lesion (Hruban et al., 2004; Lennon et al., 2014). The growing use of sophisticated imaging techniques has led to a huge increase in incidental detection of pancreatic cystic lesions; these are found in about 3% of asymptomatic patients undergoing an abdominal multiple detector computed tomography (MDCT) and up to 15% of those undergoing abdominal magnetic resonance imaging (MRI) for other indications (Laffan et al., 2008; Vege, Ziring, Jain, Moayyedi, & Clinical Guidelines, 2015). The incidence of pancreatic cysts increases with age and may be about 25% in individuals older than 70 years (Vege et al., 2015). IPMN is the main cause of pancreatic cystic lesions, accounting for almost 50% of resected specimens (Valsangkar et al., 2012). These are macroscopic lesions (most of them ≥ 1.0 cm) that can arise from the main or branch pancreatic ducts; by far, branch duct IPMN are the most common (Hruban et al., 2004; Lennon et al., 2014). Typically, these types of tumors are papillary and often produce large amounts of mucin leading to ductal dilatation, and occasionally causing pancreatitis by transient obstruction of pancreatic ducts. The risk of malignant transformation is closely related to lesion location and phenotype. The 5-year risk of PDAC has been estimated at 10%-15% for branch duct IPMN and may exceed 50% for those of the main pancreatic duct; the risk of malignancy with a longer follow-up is still unknown (Levy et al., 2006). Four morphologic and histologic subtypes of IPMN have been described (i.e. the gastric, intestinal, pancreatobiliary, and oncocytic), which are differentially prone to malignant transformation (Fernandez-del Castillo & Adsay, 2010). Branch duct IPMN are mainly of gastric phenotype and most of these do not progress to invasive cancer; when they do progress, the carcinoma is of the tubular type. By contrast, main duct IPMN are mostly of intestinal type and progress into invasive cancer of colloid or tubular type. International consensus guidelines for the management of IPMN have defined “high-risk stigmata” (enhanced solid component and main pancreatic duct size of ≥ 10 mm) and “worrisome features” (cyst size ≥ 3 cm, thickened enhanced cyst walls, non-enhanced mural nodules, main pancreatic duct size of 5–9 mm, abrupt change in

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main pancreatic duct calibre with distal pancreatic atrophy, and lymphadenopathy) on imaging to stratify the risk of IPMN malignancy (Tanaka et al., 2012; Vege et al., 2015). Similarly to PanIN, lowgrade IPMN often harbor KRAS and p16/CDKN2A gene mutations, and high-grade IPMN harbor additional mutations in TP53 and SMAD4 genes (Lennon et al., 2014). Moreover, GNAS and RNF43 genes have been reported to be frequently mutated in these lesions (in 66% and 75% of IPMN, respectively) (Wu, Jiao, et al., 2011; Wu, Matthaei, et al., 2011). In addition, familial forms of IPMN have been described (Rebours et al., 2012). MCN are large mucin-producing pre-malignant lesions of the pancreas that almost always arise in the body or tail of the gland (90% of cases) and almost exclusively in women (sex ratio: 20:1); median age at diagnosis is 40-50 years (Lennon et al., 2014). They are less common than IPMN, accounting for 16% of resected pancreatic cysts in large surgical series (Valsangkar et al., 2012). Typically these are unique, and unilocular or paucilocular, with few septations. In contrast with IPMN, MCN are not connected with the pancreatic ductal system. They display a thick wall (> 2 mm) and the mucinous lining epithelium is surrounded by a pathognomonic ovarian-type stroma (Lennon et al., 2014). Similarly to IPMN, imaging criteria have been proposed to predict the risk of malignant transformation of MCN (presence of mural nodule, thick wall, and cyst size > 40 mm) but their natural history remains ill-defined (Le Baleur et al., 2011; Tanaka et al., 2012; Vege et al., 2015). Given that KRAS, p16/CDKN2A, RNF43, TP53, and SMAD4 genes, but not GNAS, are mutated in MCN, the latter has been proposed to distinguish between IPMN and MCN lesions (Lennon et al., 2014). Noticeably, MCN must be differentiated from serous cystadenoma, which are benign lesions with an anecdotal risk of malignant transformation (Jais et al., 2015).

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2.3. Risk factors: nicotine, obesity/diabetes/insulin resistance, chronic pancreatitis, and the role of inflammation PDAC risk increases with age and rarely affects individuals younger than 45; the median age at diagnosis is 71 years old (Ryan et al., 2014a). Increasing PDAC incidence in recent years may be related to population aging. Incidence rates vary by sex and race. The incidence is greater in developed countries, in males (sex ratio: 1.3:1), and in black individuals (14.8 per 100,000 in black males compared with 8.8 per 100,000 in the general population) (Ries et al., 2000). However, more recent data suggest that these racial differences may be diminishing (Ma, Siegel, & Jemal, 2013). Main environmental risk factors for PDAC include smoking (relative risk [RR]: 2-3), and more precisely nicotine exposure (Bosetti et al., 2012). In KRAS-mutated mice models, nicotine accelerates pancreatic carcinogenesis and tumor development via down-regulation of Gata6 to induce acinar cell dedifferentiation (Hermann et al., 2014). In addition, nicotine induces pancreatic cells to acquire a mesenchymal phenotype (i.e. epithelial-mesenchymal transition [EMT]), and gene expression patterns and functional characteristics of cancer stem cells. PDAC tumors developed in mice exposed to nicotine display more aggressive features, with increased number of circulating cancer cells and dissemination to the liver, compared with not-exposed mice. Moreover, these tumors are more resistant to gemcitabine chemotherapy (Banerjee, Al-Wadei, & Schuller, 2013). Obesity and abdominal fatness also increase PanIN and PDAC risks (RR: 2) (Aune et al., 2012; Rebours et al., 2015). Overweight (defined as body mass index [BMI] of 25 to 29.9 kg/m2) and obesity (BMI ≥ 30 kg/m2) are growing epidemic health problems, increasing the risk not only of cardiovascular disease and type 2 diabetes mellitus but also of various cancers, including PDAC (Renehan, Tyson, Egger, Heller, & Zwahlen, 2008). Obesity is strongly associated with changes in the physiological function of adipose tissue, leading to insulin resistance, chronic inflammation, and altered secretion of adipokines, all of which are involved in carcinogenesis and cancer progression through signaling pathway deregulations (e.g. the MAPK, PI3K/m-TOR, STAT3, and NFκB pathways) and DNA damage induced by reactive oxygen species (ROS) production (van Kruijsdijk, van der Wall, & Visseren, 2009). In mice, a high-fat diet leads to weight gain, increase in visceral fat, and development of hyperinsulinemia, hyperglycemia, and hyperleptinemia, as well as elevated levels of insulin-like

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growth factor (IGF)-1 (Eibl, 2014). Moreover, in mice with acinar cell-specific expression of mutant KRAS, high-fat diet induces activation of latent oncogenic KRAS signaling via COX2, causing pancreatic inflammation and fibrosis, and ultimately resulting in the development of PanIN and PDAC (B. Philip et al., 2013). Long-standing type 2 diabetes mellitus is also associated with increased PDAC risk (RR: 2) (Ben et al., 2011). In contrast, diabetes mellitus of recent onset (< 2-3 years) is rather considered as an early paraneoplastic manifestation of PDAC, caused by paracrine cancer-induced β‑ cell dysfunction and peripheral insulin resistance (Sah, Nagpal, Mukhopadhyay, & Chari, 2013). Overall, there is consistent evidence on the relationship between insulin resistance, insulin and IGF-1 secretions, and pancreatic carcinogenesis: (a) obesity and long-standing type 2 diabetes mellitus (i.e. metabolic syndrome) are risk factors for PDAC, and physical activity may have a protective effect (RR: 0.72); (b) metformin, a drug that decreases insulin resistance, reduces the risk of developing PDAC in in vivo preclinical models, and in observational clinical studies of type 2 diabetic patients; (c) insulin-receptor overexpression has been described in PDAC, and insulin and IGF-1 stimulate proliferation of PDAC cells in vitro; (d) some polymorphisms of IGF, IGF receptor, and IGF binding protein are associated with an increased risk of PDAC and shorter survival in PDAC patients; (e) weight loss, impaired glucose tolerance and diabetes mellitus, along with peripheral insulin resistance are frequently observed in PDAC patients (Agustsson, D'Souza M, Nowak, & Isaksson, 2011; Bao et al., 2011). Chronic inflammation, as typically seen in non-hereditary chronic pancreatitis, is another condition predisposing to PDAC (RR: 2-6). Inflammation is a well-known promoter of pancreatic carcinogenesis; induction of pancreatitis (e.g. using caerulein) is commonly used in mouse models in conjunction with genetic alterations to accelerate PanIN and PDAC development. Excessive alcohol consumption is the most frequent cause of chronic pancreatitis. Ethanol induces pancreatic inflammation and carcinogenesis through various mechanisms: (a) transcription of pro-inflammatory mediators and pancreatic cell necrosis; (b) non-oxidative metabolism of ethanol to fatty acid ethyl esters, which cause pancreatitis-like injury and increased levels of trypsinogen activation peptide; and (c) oxidative alcohol metabolism generating ROS and other free radicals (Greer & Whitcomb, 2009). Despite a RR of 15, screening in patients with non-hereditary chronic pancreatitis is not recommended because the absolute risk is limited (approximately 4% after 20 years of evolution) and tumor detection by imaging is challenging in a remodeled parenchyma (Malka et al., 2002). Finally, other factors such as chronic viral hepatitis B or C infection, Helicobacter pylori infection, and non-O blood groups have been suggested to increase PDAC risk, but further studies are needed to confirm these potential associations (Klein et al., 2013; Maisonneuve & Lowenfels, 2015; Risch, Yu, Lu, & Kidd, 2010; Xu et al., 2013). 2.4. Genetic and molecular cascade of events Although KRAS mutations play a crucial role in pancreatic carcinogenesis, they are not sufficient for full PDAC development (Hezel et al., 2006). For instance, about 10 % of patients with chronic pancreatitis harbor KRAS mutations without developing PDAC (Luttges et al., 1999). KRAS seems to drive early stages of pancreatic carcinogenesis, but accumulation of other cooperative genetic alterations is required for full oncogenic transformation (Neuzillet, Hammel, Tijeras-Raballand, Couvelard, & Raymond, 2013). As described above, studies of premalignant lesions, particularly PanIN, have allowed the identification of early vs late oncogenic events in PDAC carcinogenesis [Figure 1]. Recent data suggest that the switch to a metastatic behavior may be controlled by a cooperative relationship between expression levels of RUNX3 transcription factor and SMAD4 status to coordinately regulate the balance between cancer cell division and dissemination (Whittle et al., 2015). The study of familial cancer syndromes (5%-10% of PDAC) due to inherited mutations in specific genes has also provided precious data about key genetic events in pancreatic carcinogenesis (Ghiorzo, 2014; Hezel et al., 2006). Main genetic syndromes and associated genes are presented in Table 1 (Groen et al., 2008; Holter et al., 2015; Iqbal et al., 2012; Jones et al., 2009; Kastrinos et al., 2009; Rebours et al., 2008; Roberts et al., 2012; Ruijs et al., 2010; van Lier et al., 2010; Vasen et al.,

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2000; Walpole & Cullity, 1989). Cooperation of these genetic alterations with mutant KRAS has been demonstrated in genetically engineered mouse models (Mazur & Siveke, 2012; Morris et al., 2010). Besides well-described genetic syndromes, numerous cases of familial aggregation have been reported and led to the creation of family registries (Bartsch, Gress, & Langer, 2012; Klein, 2013). Familial pancreatic cancer is classically defined by at least two first-degree relatives with confirmed PDAC and absence of the criteria for other inherited tumor syndromes associated with increased risk of PDAC. The theoretical risk of PDAC in relatives increases depending on the number of cases in the family: it is multiplied by 4.6, 6.4, and 32.0, respectively, if there is one case, two cases, or three cases (Klein et al., 2004). BRCA2 and PALB2 gene mutations were found in 6%-17 % and 3%-4% of these families (Bartsch et al., 2012). Genetic testing of patients with suspected familial pancreatic cancer should include analysis of BRCA1/2, PALB2, p16/CDKN2A, and ATM (Syngal et al., 2015).

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Global genomic analyses have provided a new insight into PDAC genetic complexity. First studies revealed that a core set of 12 pathways and processes are commonly genetically deregulated in PDAC (Jones et al., 2008). More recently, additional studies using whole-exome sequencing and copy number analysis uncover novel mutated genes including genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM), axon guidance (SLIT/ROBO), and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4, and MAGEA6) (Biankin et al., 2012). Combining most recent technologies for deep whole-genome sequencing and analysis of structural rearrangement of chromosomes, Waddell et al. (Waddell et al., 2015) identified genetic alterations affecting genes already known to be important in pancreatic cancer (TP53, SMAD4, p16/CDKN2A, ARID1A, and ROBO2) and new candidate drivers of pancreatic carcinogenesis (KDM6A and PREX2). In addition, they showed that structural variation (i.e. variation in chromosomal structure) is an important mechanism of DNA damage in pancreatic carcinogenesis.

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2.5. Role of microenvironment: pancreatic stellate cells, immune cells, neural cells, abundance, and composition of stroma Over the last decade, research has increasingly focused on the microenvironment surrounding cancer cells and its role in tumor development and progression (Neesse, Algul, Tuveson, & Gress, 2015). PDAC displays the most prominent desmoplastic stromal reaction of all epithelial tumors, often greater than the epithelial component of the tumor itself (Erkan et al., 2012). Fibrotic focus (i.e. evidence of intratumoral fibroblast proliferation following focal necrosis) and stromal abundance and activity (evaluated by collagen deposition and α-smooth muscular actin [α-SMA] immunostaining) have been reported to be correlated with shorter survival in patients with resected PDAC, suggesting a prognostic role for desmoplasia in PDAC (Couvelard et al., 2005; Erkan et al., 2008). This desmoplastic stroma is a complex structure composed of ECM proteins (e.g. type I collagen, hyaluronic acid, fibronectin, laminin) and various cell types including PSC, endothelial cells, pericytes, neural cells, immune cells, and bone marrow-derived stem cells (Neesse et al., 2015). Activated PSC are related to cancer-associated fibroblasts (CAF) and are responsible for excess extracellular matrix (ECM) production in PDAC (Apte, Wilson, Lugea, & Pandol, 2013). PSC represent about 4% of pancreatic resident cells. These are quiescent in normal pancreas tissue and characterized by abundant vitamin-A-storing lipid droplets in their cytoplasm. They can be activated into myofibroblast-like cells, expressing α-SMA, by two major groups of extracellular factors: (a) growth factors and cytokines and (b) cellular stressors (ethanol and its metabolites, oxidant stress, and endotoxins) (Jaster, 2004). PDAC cells release mitogenic and fibrogenic stimulants, including transforming growth factor (TGF)-β, platelet-derived growth factor (PDGF), and sonic hedgehog, which activate surrounding PSC. In turn, activated PSC secrete various factors such as epidermal growth factor [EGF], IGF-1, fibroblast growth factor [FGF], connective tissue growth factor [CTGF], matrix metalloproteinases [MMP], and collagen type I that promote tumor growth, invasion, metastasis, and resistance to chemotherapy (Apte et al., 2013). PSC activation and fibrosis are early

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phenomenons in PDAC carcinogenesis that exist from the stage of precursor lesions and are driven by KRAS activating mutation (Collins, Yan, Sebolt-Leopold, & Pasca di Magliano, 2014). PSC not only create a fibrotic microenvironment but also contribute to make it hypoxic. Although activated PSC produce pro-angiogenic factors such as vascular endothelial growth factor [VEGF], they are dominantly anti-angiogenic, through (a) enhancing anti-angiogenic endostatin production by cancer cells, (b) compressing vessels by the dense and fibrotic stroma, and (c) high interstitial pressure, all of which result in low vascularization and tumor hypoxia (Erkan et al., 2012; Provenzano & Hingorani, 2013). As a result, PDAC are typically fibrotic and poorly vascularized tumors (Erkan et al., 2012). Moreover, hypoxia may drive a selective pressure over cancer cells toward a more aggressive phenotype (Guillaumond et al., 2013; Hashimoto et al., 2011). Overall, PSC appear as pro-tumoral “partners” of cancer cells in PDAC. However, recent studies showed that depleting PSC from the stroma modulates immunity within PDAC microenvironment and leads to undifferentiated, more invasive and aggressive tumors, uncovering a potential protective role of these cells in restraining PDAC progression (Ozdemir et al., 2014; Rhim et al., 2014).

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Mesenchymal stem cells (MSC) are another type of CAF-related cells. These are defined by the expression of stem cell markers (CD90, CD49a, CD73, and CD44), the functional capacity to differentiate into bone, cartilage, and adipose cells, and clonogenic ability (Waghray et al., 2014). These cells have been recently identified in the PanIN and PDAC stroma and demonstrated to have tumor-promoting properties, enhancing primary tumor growth and metastasis (Waghray, Yalamanchili, di Magliano, & Simeone, 2013). MSC have been shown to regulate the recruitment of macrophages in other cancer types. MSC associated to PDAC promote the polarization of macrophages into pro-tumoral, immunosuppressive M2-macrophages and have a specific paracrine profile, secreting granulocyte-macrophage colony-stimulating factor (GM-CSF) (Mathew, Zhang, Mendez, Bednar, & di Magliano, 2014; Waghray et al., 2014).

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The immune system is responsible for the early detection and destruction of cancer cells. Some cancer cells become immunologically invisible by passive avoidance of immune surveillance (i.e., cancer cell “hiding”). Another mechanism for escaping immune surveillance is to actively secrete cytokines that “blind” the immune system to the presence of abnormal antigens at the cancer cell surface. Interestingly, marked inflammatory syndrome and immunosuppression are commonly observed in patients with PDAC (von Bernstorff et al., 2001). Increasing evidence suggests that oncogenic KRAS drives a paracrine and endocrine (through circulating exosomes, which are membrane vesicles of endocytic origin enclosing tumor-derived material) inflammatory and immunosuppressive program establishing a pro-tumoral immune microenvironment in PDAC primary and metastatic sites (Costa-Silva et al., 2015; Miller, 2014; Ryan et al., 2014a; Vonderheide & Bayne, 2013). Several mechanisms that are involved are summarized in Figure 2. TGF-β and GM-CSF play crucial roles in these processes (Costa-Silva et al., 2015; Neuzillet, de Gramont, et al., 2014; PylayevaGupta, Lee, Hajdu, Miller, & Bar-Sagi, 2012). The importance of nerve-cancer interactions in PDAC carcinogenesis has been underestimated until recently. Nerves and cancer cells are involved in a bidirectional relationship (Bapat, Hostetter, Von Hoff, & Han, 2011; Demir, Friess, & Ceyhan, 2012). Nerves (a) modulate tumor growth, invasion, and metastasis, (b) chemoattract cancer cells and serve as physical paths of tumor spread, (c) mediate cancer-associated pain, (d) modulate peritumoral and systemic inflammation, and (e) increase tumor effects on mesenchymal cells. In turn, cancer cells (a) induce neuroplasticity and neuropathic pain, and (b) activate peripheral glia in early carcinogenesis. 2.6. Changes in metabolic pathways Cancer cells need large amounts of both energy (adenosine triphosphate [ATP]) and macromolecules (lipids, proteins, and nucleic acids) to support their proliferation. As a hallmark of cancer, metabolism reprogramming highlights the fact that changes in cell and whole-body metabolisms are necessary

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for tumor initiation and progression (Hanahan & Weinberg, 2011). Both oncogenes, with a driver role for oncogenic KRAS, and the tumor microenvironment are involved in this process (Cairns, Harris, & Mak, 2011; Cohen et al., 2015). The extensive and poorly vascularized desmoplastic stromal reactions in PDAC leads to tumor hypoxia and nutrient deprivation, yet without evidence of major cell death (Bergers & Hanahan, 2008). This suggests that pancreatic cancer cells adapt to metabolically challenging survival conditions in their microenvironment early in tumor development. Several changes occur in response to oxygen and nutrient deprivation: increased glycolysis even in aerobic conditions, as well as increased amino acid (AA) uptake derived from protein degradation, protein glycosylation, and fatty acid synthesis (Cohen et al., 2015; Ryan, Hong, & Bardeesy, 2014b). In addition, recycling and scavenging of cellular and extra-cellular components through autophagy and macropinocytosis have been shown to be applicable in PDAC (Cohen et al., 2015; Ryan et al., 2014b). These crucial and early adaptive mechanisms are referred to as the “metabolic switch”.

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Contrary to normal cells, cancer cells display increased glucose uptake and preferentially metabolize glucose-derived pyruvate to lactate even in the presence of oxygen, despite the fact that aerobic glycolysis is far less efficient than the oxidative phosphorylation via the mitochondrial tricarboxylic acid (TCA) cycle (or Krebs cycle) to produce energy (two ATP molecules instead of 36 ATP molecules per glucose unit) (Warburg, Wind, & Negelein, 1927). This “glycolytic switch”, also known as the “Warburg effect”, is an early phenomenon characterized by increased expression of lactate dehydrogenase (LDH, that converts pyruvate into lactate) and inactivation of pyruvate dehydrogenase (PDH, that converts pyruvate into acetyl-CoA for the TCA cycle). In addition, this allows intermediates of the TCA cycle to be redirected towards biosynthesis of cytoplasmic macromolecules (e.g. nucleotide, hexosamine) (Dell' Antone, 2012). The glycolytic switch is driven by the hypoxic tumor microenvironment through hypoxia-inducible factor (HIF)-1α activation, aberrant signaling due to oncogene activation (e.g., Ras, PI3K/mTOR, c-Myc), tumor suppressor gene inactivation (e.g., p53), or by mutations in the TCA enzymes (Cairns et al., 2011). Proteomic profiling and preclinical models showed that PDAC cells overexpress glycolytic enzymes including hexokinase (HK)-2, phosphoglycerokinase (PGK)-1, pyruvate dehydrogenase kinase (PDHK)-1, and LDH-A, as well as the glucose and lactate transporters GLUT-1 and MCT-4, especially in hypoxic tumor regions (Guillaumond et al., 2013; Zhou et al., 2011; Zhou et al., 2012).

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Although glutamine is a non-essential AA, most cancer cells exhibit glutamine addiction, using ten times more glutamine than any other AA with a dependence on exogenous supplementation for survival (Wise & Thompson, 2010). The metabolic fate of glutamine is multifaceted: it can be used for lipid biosynthesis, as a nitrogen donor for AA and nucleotide biosynthesis, as a carbonic substrate for the re-feeding of the mitochondrial TCA cycle through a phenomenon called “anaplerosis”, and as fuel for cell energy production through glutaminolysis (Cohen et al., 2015; DeBerardinis & Cheng, 2010). PDAC cells metabolize glutamine through a non-canonical pathway in which transaminases play a crucial role. Whereas most normal cells use glutamate dehydrogenase (GDH-1) to convert glutamine-derived glutamate into α-ketoglutarate to fuel the TCA cycle in the mitochondria, PDAC relies on a distinct pathway in which glutamine-derived aspartate is transported into the cytoplasm where it can be converted into oxaloacetate by glutamic-oxaloacetic transaminase (GOT-1), then into malate, and finally into pyruvate (Son et al., 2013). Conversion of malate to pyruvate by malic enzyme increases the NADPH/NADP+ ratio, providing the reducing power to maintain reduced glutathione pools to protect cancer cells against oxidative damage. Low expression of GDH-1 and overexpression of glutaminase, GOT-1, as well as enzymes using glutamine as a nitrogen donor (e.g. asparagine synthetase), are characteristic features of PDAC (Son et al., 2013; Zhou et al., 2012). Transcriptional reprogramming of key metabolic enzymes in the glutamine pathway (e.g. GDH-1, GOT-1) in cancer cells is driven by KRAS or MYC oncogenes (Son et al., 2013; Wise et al., 2008). Thus, more than an alternative fuel for the TCA cycle, glutamine is necessary to sustain biomass synthesis and maintain the redox balance in PDAC cells.

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Autophagy is a catabolic process that consists in degrading macromolecular complexes and cytoplasmic organelles into AA, lipids, and nucleosides that are then recycled. Autophagy is triggered by nutrient shortage, protein damage, or by oxidative stress occurring through inhibition of the AMP kinase (AMPK) and mTOR pathways (Cohen et al., 2015; Mazure & Pouyssegur, 2010). The role of autophagy in PDAC progression has been controversial since both pro- and anti-tumorigenic effects have been described (C. A. Iacobuzio-Donahue & Herman, 2014; Sousa & Kimmelman, 2014). Using genetically engineered mouse models of PDAC, Rosenfeldt et al. (Rosenfeldt et al., 2013) brought to light the role of p53 in this complex process. In a wild-type TP53 background, inhibition of autophagy resulted in decreased metabolism activity and blocked KRAS tumorigenicity; in contrast, in the context of a coexisting oncogenic KRAS mutation and embryonic homozygous TP53 deletion, it favored PanIN transformation into invasive PDAC. In tumors with loss of p53 function, autophagy inhibition induced an increase in glucose consumption for anabolic pathway activity, fueling cancer cell proliferation. PDAC cell dependence on autophagy may thus vary according to the genetic background of the tumor. However, more recently, using an alternative mouse model with stochastic loss of heterozygosity of TP53, cell lines, and genetically-characterized patient-derived xenografts, Yang et al. (Yang et al., 2014) showed that p53 status does not seem to affect response to autophagy inhibition. Alternatively, PDAC cells are also able to uptake and degrade extra-cellular components through an endocytic process called macropinocytosis. KRAS-dependent upregulation of macropinocytosis contributes to sustain the metabolic needs of PDAC cell lines, and macropinocytosis inhibition was demonstrated to reduce KRAS-transformed cell growth (Commisso et al., 2013; Kamphorst et al., 2013).

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To sum up, knowledge regarding PDAC development and biology has evolved toward increased complexity with the discovery and understanding of the various levels of genetic and phenotypic cancer heterogeneity and the diversity of stromal cells interacting with cancer cells within the tumor microenvironment.

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3. Diagnosis and staging 3.1. Clinical presentation and value of CA 19-9 The majority (75%) of PDAC occur in the pancreatic head, 15%-20% in the body, and 5%-10% in the tail of the pancreas (Seufferlein, Bachet, Van Cutsem, Rougier, & Group, 2012). PDAC primarily metastasize to lymph nodes, the liver, peritoneum, and lungs. The type and timing of clinical manifestations depend on primary tumor location (Modolell, Guarner, & Malagelada, 1999). Tumors located in the pancreatic body and tail tend to remain asymptomatic longer than those located in the head and, consequently, these are often diagnosed at a more advanced stage (Neuzillet, Sauvanet, & Hammel, 2011). Patients with PDAC commonly present with non-specific (e.g. asthenia) and heterogeneous symptoms. Intense abdominal and/or back pain is the most frequent inaugural symptom, and usually indicates neural invasion and poor prognosis (Modolell et al., 1999). Indeed, pain presence and intensity are not only predictive of nonresectability, but are also associated shorter survival (Kalser, Barkin, & MacIntyre, 1985). Jaundice may also be an early sign caused by biliary obstruction for tumors located in the pancreatic head, and PDAC presenting as inaugural painless jaundice have been reported to have a relatively more favorable prognosis, albeit debated (Modolell et al., 1999). Weight loss is a common finding in most patients, being usually associated with malabsorption (Modolell et al., 1999). Diabetes (either as a cause or a consequence of the disease) is present in at least 50% of patients with PDAC; longstanding diabetes, contrary to recent-onset diabetes, is associated with poor prognosis (Chari et al., 2005; Yuan et al., 2015). Less frequently, PDAC present as an acute pancreatitis episode, a gastrointestinal haemorrhage or intestinal obstruction, or may be revealed by venous thrombosis, mental disturbances, or skin manifestations (Weber-Christian disease, also known as idiopathic lobular panniculitis).

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Carbohydrate antigen 19-9 (CA 19-9) serum level does not meet the predictive value criteria to be a reliable diagnostic biomarker (Ballehaninna & Chamberlain, 2012). Its sensitivity and specificity for the diagnosis of PDAC in symptomatic patients is 79%-81% and 82%-90%, respectively, but its positive predictive value remains insufficient to be used for PDAC screening and diagnosis (Ballehaninna & Chamberlain, 2012; Ni et al., 2005). Alternatively, CA 19-9 at diagnostic provides useful prognostic information as patients with a CA 19-9 serum level of < 100 U/mL have likely resectable disease whereas levels > 100 U/mL suggest unresectable or metastatic disease (Ballehaninna & Chamberlain, 2012). Consistently, normalization or a decrease in post-treatment CA 19-9 serum level by ≥ 20%-50% from baseline following surgical resection or chemotherapy is associated with prolonged survival compared with failure to normalize or increase of CA 19-9 serum level (Ballehaninna & Chamberlain, 2012). Important limitations to CA 19-9 serum level evaluation in PDAC include false negative results in Lewis negative blood group (5%-10%) and increased false positivity in the presence of obstructive jaundice, decompensated diabetes mellitus, or in association with other adenocarcinoma (Ballehaninna & Chamberlain, 2012). Overall, CA 19-9 should be handled with care and should not be dosed without an accompanying imaging examination.

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3.2. Evolution in imaging techniques: current standard of care (MDCT, MRI, EUS, and 18FDG-PET) Once the diagnosis of PDAC is clinically suspected or a pancreatic mass is detected (e.g. by transparietal abdominal ultrasonography), thoraco-abdomino-pelvic MDCT - with thin sections (< 1 mm), both non-enhanced and late arterial (at 40-50 sec), so called “pancreatic”, plus portal venous (at 65-70 sec) phases after contrast injection and reconstructions - is the imaging modality of choice for the initial staging and management discussion (Al-Hawary et al., 2014). PDAC lesions, both primary tumor and metastasis, classically appear classically appear as hypoattenuating at arterial phase, then poorly enhanced/isoattenuating tumors at portal phase [Figure 3]. Tumor appearance, size, and location, presence of a biliary or pancreatic duct narrowing, vascular involvement, and extra-pancreatic extension (suspicious lymph nodes and liver, peritoneal, and lung metastasis) should be precisely evaluated, as staging is one of the most important steps for optimal patient management (Al-Hawary et al., 2014). Regarding resectability evaluation, MDCT has a diagnostic accuracy of 85%-95%, but most studies have reported a nearly 100% specificity for diagnosis of unresectability, limiting the risk of palliative treatment in case of actually resectable PDAC (Diehl, Lehmann, Sadick, Lachmann, & Georgi, 1998; Lu, Reber, Krasny, Kadell, & Sayre, 1997). Obtaining timely, recent diagnostic imaging (< 3-4 weeks) is crucial since long imaging-to-management interval has been reported to be associated with a higher risk of unanticipated metastasis (20% when > 3 weeks) in patients with presumably resectable tumors (Glant et al., 2011). Thoracic sections should be carefully reviewed so that not to ignore pulmonary extension (6% of patients at diagnosis) (AlHawary et al., 2014). MRI has been shown to be equally sensitive and specific as MDCT in staging locoregional extension of PDAC, but is not widely used due to its cost and limited availability (Bipat et al., 2005). In most centers, MRI is predominantly dedicated to characterization of poorly or not visible isoattenuating pancreatic lesions or indeterminate liver lesions identified at prior MDCT examinations. Magnetic resonance cholangiopancreatography (MRCP) sequences must be included in the pancreatic MRI protocol to search for main pancreatic duct stenosis, which frequently allows to suspect PDAC diagnosis and to locate the tumor. A recent prospective French study (the PANDA study) has suggested that diffusion MRI is more sensitive than MDCT to detect small hepatic, peritoneal, or lymph node metastasis and can avoid futile laparotomy in 12% of patients with presumably resectable PDAC; it was mainly related to the discovery of liver metastases that were not detectable with MDCT nor 18F-fluorodeoxyglucose-positron emission tomography (18FDG-PET) (Marion-Audibert et al., 2014). Endoscopic ultrasonography (EUS) with fine-needle aspiration has an established role in morphological description and pathologic confirmation of PDAC before treatment initiation (De Angelis, Brizzi, & Pellicano, 2013). Its sensitivity and specificity can be increased by specific contrast

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injection to better detect and characterize pancreatic tumors, in particular in cases of small or isoattenuating lesion (Gincul et al., 2014). EUS is mainly used in four clinical situations: (a) in negative cross-sectional evaluation with MDCT or MRI when the suspicion of PDAC is high (e.g. adenocarcinoma of unknown primary with a pancreatobiliary immunophenotype), especially when a main pancreatic duct stenosis is described, the biopsy being performed downstream to the stenosis, (b) to characterize ambiguous pancreatic lesions identified at MDCT and MRI (e.g. differential diagnosis with pseudo-tumoral autoimmune pancreatitis or with a pancreatitis focus in case of chronic pancreatitis), (c) to obtain pathologic confirmation of PDAC when it is required and no other tumor site of easier access is available (i.e. mostly for locally-advanced PDAC or before neoadjuvant treatment of resectable/borderline resectable tumors), or (d) during combined procedures with endoscopic retrograde cholangio-pancreatography (ERCP) when a biliary drainage is indicated (De Angelis et al., 2013). Of note, ERCP has a role only to relieve bile duct obstruction (Seufferlein et al., 2012). It is indicated in patients with obstructive jaundice caused by an unresectable tumor; in patients with a resectable tumor, ERCP and biliary stenting before surgery should only be performed in selected cases (i.e. angiocholitis, bilirubin level > 250 μmol/l or 150 mg/l, when a neoadjuvant treatment is planned, or if surgery cannot be done expeditiously) as an increased rate of complications is observed in patients undergoing preoperative biliary drainage (van der Gaag et al., 2010). 18 FDG-PET is playing an increasing role in the diagnosis, staging, and prognosis of gastrointestinal malignancies. However, it is inconstantly positive in case of PDAC (particularly, in mucin-producing variants) and recent prospective studies (including the PANDA study) and meta-analyses concluded that 18FDG-PET has no obvious advantage for PDAC diagnosis and staging compared to currently available diagnostic tools (Marion-Audibert et al., 2014; Rijkers, Valkema, Duivenvoorden, & van Eijck, 2014; Tang et al., 2011; Z. Wang, Chen, Liu, Qin, & Huang, 2013). Finally, laparoscopy may detect small peritoneal and liver metastases changing the therapeutic strategy in < 15% of patients (Seufferlein et al., 2012). It can be proposed before resection in case of large tumors developed in the body or the tail of the pancreas and/or in case of high CA 19-9 levels, or when neoadjuvant treatment is considered.

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3.3. Resectable, borderline resectable, locally advanced, and metastatic pancreatic ductal adenocarcinoma: classification as the framework for treatment strategy and pre-therapeutic prognosis evaluation Based on the results of the pre-therapeutic imaging assessment, PDAC are classified as resectable, borderline resectable, locally advanced, or metastatic (Tempero et al., 2014). The degree of vascular involvement is often difficult to determine. It must be discussed in a multidisciplinary conference by radiologists, surgeons, and oncologists/gastroenterologists experienced in pancreatic and biliary malignant diseases. Criteria for PDAC staging are summarized in Table 2. This classification is the framework for PDAC treatment strategy and also guides the clinician on how to obtain PDAC cytologic/histologic diagnostic confirmation [Table 2]. Pre-therapeutic pathological proof of malignancy is only required in patients with unresectable tumor or when a neoadjuvant strategy is planned (Seufferlein et al., 2012). In patients with metastatic disease, tumor site of easier access should be biopsied in priority (either percutaneously under ultrasound or MDCT guidance or during EUS). For patients who will undergo a straightforward radical surgery, a previous biopsy is not mandatory (Seufferlein et al., 2012). Biopsy in this setting should be restricted to selected cases, e.g. in which imaging results of a pancreatic lesion are ambiguous. Particularly, in case of isolated atypical pancreatic mass, differential diagnosis with pseudo-tumoral autoimmune pancreatitis may be challenging (Levy, Hammel, & Ruszniewski, 2008). Imaging features and atypical clinical and biochemical findings may be helpful in arousing suspicion that a pancreatic mass is not a PDAC (e.g. young age of onset, absence of risk factors such as smoking, presence of associated autoimmune disease[s], elevated IgG4 level, and absence of weight loss, pain, or CA 19-9 elevation). Diagnostic test with steroids should only be performed in these specific situations when autoimmune

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pancreatitis is suspected and if at least two core biopsies devoid of cancer cells have been obtained by experienced specialists. Steroid treatment should not exceed 15 days and its efficacy should be assessed after a short delay not to miss the diagnosis and the curative therapeutic window of PDAC (Moon et al., 2008).

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In patients with resectable tumor, prognosis is mainly determined by tumor-related factors (i.e. tumor diameter, differentiation grade, lymph node status and ratio, and involvement of surgical margins) and adjuvant chemotherapy (Neuzillet et al., 2011). Surgical procedure-related and patientrelated factors are of minimal prognostic value. In contrast, in unresectable cases, patient-related factors and metastatic burden play a major prognostic role. Altered performance status (Eastern Cooperative Oncology Group [ECOG] ≥ 2), age of more than 65 years, low baseline albumin level (< 35 g/L), altered health-related quality of life (HRQoL), synchronous and hepatic metastases, and number of metastatic sites have been reported to be adversely associated with survival in large phase III clinical trials (Conroy et al., 2011; Gourgou-Bourgade et al., 2013; Lo Re et al., 2015; Vernerey et al., 2015). Evidence for the role of baseline CA 19-9 serum level is less consistent.

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4. Therapeutics 4.1. Metastatic PDAC About 50% of PDAC are diagnosed at a metastatic stage requiring systemic treatment. An important feature of PDAC is its high resistance to most of systemic therapies. Drug resistance in PDAC is driven by various mechanisms including aberrant gene expression (such as high ABC transporters expression [MDR phenotype], low human equilibrative nucleoside transporter [hENT]-1 expression or ribonucleotide reductase M1/2 [RRM1/2] and deoxycytidine kinase [dCK] leading to limited intracellular uptake and processing of gemcitabine, or high level of cytidine deaminase [CDA] leading to gemcitabine degradation), mutations, deregulation of key signaling pathways (such as NFκB, Notch, mTOR, and apoptosis pathways), EMT, and the presence of cancer stem cells that are intrinsically chemo-resistant (Long et al., 2011). Moreover, as described above, PDAC is characterized by a dense stroma resulting from the cancer cells and activated PSC interactions (Apte et al., 2013). This stroma is a barrier for diffusion of most of the drugs and the cross talk between cancer cells and stromal cells promotes tumor progression and resistance to therapies. Until 1997, there was no validated treatment for advanced PDAC. 5FU-based chemotherapy compared with BSC alone improved OS by approximately 3 months (Sultana et al., 2007). In 1997, gemcitabine was demonstrated to be superior to 5FU and became the cornerstone of first-line PDAC treatment. In a phase III study, Burris et al. (Burris et al., 1997) compared gemcitabine (1,000 mg/m2 once weekly for 7 out of 8 weeks, then once weekly for 3 out of 4 weeks) to 5FU (600 mg/m2 once weekly). In this study, gemcitabine was associated with higher clinical benefit (the primary endpoint; 23.8% vs 4.8%, p = 0.0022) and also improved OS (5.6 months vs 4.4 months, p = 0.0025). Then, over more than a decade (1997-2010), multiple phase II and III studies attempted to improve gemcitabine results either by pharmacokinetic modulation or by combining it with other agents (Ryan et al., 2014a; Vaccaro et al., 2015). The first approach was based on the observation that dCK, the enzyme that catalyzes the conversion of gemcitabine to its active triphosphate metabolite, is rapidly saturated at plasma concentrations achieved with the standard 30-minute infusion. Infusion of the same gemcitabine dose over a prolonged period at a fixed dose rate (FDR) of 10 mg/m2/minute allows to avoid dCK saturation and greater intracellular accumulation, possibly increasing antitumor activity. However, in a randomized phase III trial, although FDR-gemcitabine (1,500 mg/m2 over 150 min weekly) showed a trend towards increased OS compared to standard gemcitabine infusion and proved equivalent to gemcitabine plus oxaliplatin (GEMOX) combination (gemcitabine 1,000 mg/m2 over 100 min at day 1, and oxaliplatin 100 mg/m2 at day 2, every 14 days) (median OS of 4.9 months with standard gemcitabine, of 6.2 months with FDR-gemcitabine, and 5.7 months with GEMOX), it failed to meet the pre-specified criteria for significance (Poplin et al., 2009). Other chemically modified forms of gemcitabine have been tested. As gemcitabine relies on transporter proteins,

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including hENT-1, to cross cell membranes, CO-101, a lipid-drug conjugate of gemcitabine, was rationally designed to enter cells independently of hENT-1. However, in a randomized phase II study in patients with metastatic PDAC, CO-101 was not superior to gemcitabine and hENT-1 expression did not predict gemcitabine outcome (Poplin et al., 2013). Recently, NUC-1031, a gemcitabine analog avoiding resistance mechanisms mediated by hENT-1 and CDA, and allowing 10-fold higher intracellular concentrations of active form compared to gemcitabine, showed interesting results in a phase I study and may be active in tumors resistant to gemcitabine (Blagden et al., 2015). Alternatively, various combinations of gemcitabine with other drugs, either cytotoxics or targeted agents, have been tested. Large meta-analyses of randomized clinical trials comparing gemcitabine alone vs gemcitabine plus other cytotoxic combinations showed no benefit on OS with combination therapy (Bria et al., 2007; Ciliberto et al., 2013; Heinemann, Boeck, Hinke, Labianca, & Louvet, 2008; Sultana et al., 2007; Xie et al., 2010). The OS benefit for gemcitabine-based doublets (particularly, with platinum salts or capecitabine) seemed to be restricted to patients with good performance status (ECOG 0-1). In addition, combination therapy was associated with increased treatment-related toxicity. Thus, the routine use of gemcitabine-based cytotoxic doublets with either platinum salts or capecitabine in metastatic PDAC cannot be recommended based on available evidence. Targeted agents (including antiangiogenics, EGF and IGF receptor targeting agents, Hedgehog, MEK, and mTOR pathway inhibitors) alone or in combination with gemcitabine have also been evaluated, most in vain [Table 3] (Bodoky et al., 2012; Bramhall et al., 2002; Goncalves et al., 2012; Harder et al., 2012; Infante et al., 2014; Javle et al., 2010; Kindler et al., 2011; Kindler et al., 2010; D.T. Le et al., 2015; McCaffery et al., 2013; Moore et al., 2007; Ozdemir et al., 2014; P. A. Philip et al., 2010; P. A. Philip et al., 2014; Rinehart et al., 2004; Safran et al., 2011; Tolcher et al., 2015; Van Cutsem et al., 2004; Van Cutsem et al., 2009; Wolpin et al., 2009). No significant OS benefit was found as compared to gemcitabine alone, except for the combination of gemcitabine plus EGF receptor inhibitor erlotinib, which resulted in a modest but significant improvement in OS (6.2 months vs 5.9 months, p = 0.038) (Moore et al., 2007). Evidence suggests that clinical benefit of this combination may be limited to patients who develop skin toxicity under treatment. Two large clinical trials recently changed the standard of care from single-agent gemcitabine to combination chemotherapy. In 2011, the FOLFIRINOX regimen combining 5FU (400 mg/m2 as a bolus, then 2,400 mg/m2 given as a 46-hour continuous infusion), leucovorin (400 mg/m2), oxaliplatin (85 mg/m2), and irinotecan (180 mg/m2) was shown to be superior to weekly gemcitabine (median OS: 11.1 months vs 6.8 months, p < 0.001) in selected patients - those with a performance status ECOG 01 and absence of cholestasis (Conroy et al., 2011). Of note, modified FOLFIRINOX (no bolus 5FU) seems to have an improved safety and maintained efficacy in retrospective studies in patients with metastatic PDAC (Mahaseth et al., 2013). The question of how and when the FOLFIRINOX regimen and doses can be deescalated after a period of tumor response/stability (i.e. maintenance therapy) remains to be answered. In 2013, the combination of gemcitabine (1,000 mg/m2 weekly, 3 weeks/4) with nanoparticles of albumin-bound paclitaxel (nab-paclitaxel, 125 mg/m2 weekly, 3 weeks/4) demonstrated a statistically significant increase in OS compared with weekly gemcitabine alone (median OS: 8.5 months vs 6.7 months, p < 0.001) (Von Hoff et al., 2013). Studies directly comparing these two regimens are lacking. At present, the FOLFIRINOX or gemcitabine plus nab-paclitaxel combinations are standard first-line treatment for patients with good performance status (ECOG 0-1 for FOLFIRINOX and up to 2 for gemcitabine plus nab-paclitaxel) with no coexisting conditions. However, in routine clinical practice, only about 25% and 45% of patients with metastatic PDAC would be eligible for FOLFIRINOX and for gemcitabine plus nab-paclitaxel, respectively (D'Alpino Peixoto, Renouf, Lim, & Cheung, 2014). Patients treated with FOLFIRINOX with at least one exclusion criteria have significantly shorten PFS and OS compared with patients fulfilling the eligibility criteria of the pivotal Conroy’s study (median PFS: 4.1 months vs 6.5 months, p = 0.0107; median OS: 7.0 months vs 10.9 months, p = 0.0166) (Metges et al., 2014). Single-agent gemcitabine remains indicated in patients with poor performance status, limiting comorbidities, or age > 75 years. In a recent phase III study in an Asian population, monotherapy with S-1 demonstrated non-inferiority

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compared to gemcitabine in OS with good tolerability and may be an oral alternative for advanced PDAC (Ueno et al., 2013).

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Beyond progression under first-line treatment, about half of metastatic PDAC patients remain in good clinical condition and thus may receive subsequent line(s) of chemotherapy (Walker & Ko, 2014). A retrospective series evaluated the feasibility and benefits of second- and third-line chemotherapies in patients with metastatic PDAC after failure of gemcitabine (Bachet et al., 2009). Forty-five percent of patients received two and 21% received three or more lines of treatment. Median time to progression was 2.3 months and OS from the beginning of the second line was 4.7 months. Combinations of 5FU with platinum salts (oxaliplatin or cisplatin) or with irinotecan (standard or nanoliposomal form) have shown interesting activity after progression under gemcitabine (Chen et al., 2015; Dahan et al., 2010; Neuzillet et al., 2012; Oettle et al., 2014; Yoo et al., 2009; Zaanan et al., 2014). Noticeably, only patients remaining in good performance status (ECOG 0-1) seem to benefit from second or further line of treatment. In the era of the FOLFIRINOX and gemcitabine plus nab-paclitaxel combinations, data in patients with metastatic PDAC progressing under these new regimens are scarce and there is no validated strategy to date. Second-line gemcitabine plus nab-paclitaxel after progression or toxicity under first-line FOLFIRINOX has been studied in a retrospective work from the French Association of Gastroenterologists Oncologists (AGEO) involving 57 patients (Portal et al., 2015). Tumor control was achieved in 58% of cases. Median progression-free survival (PFS) and OS from the start of second line treatment in this selected patient population were 5.1 months and 8.8 months, respectively, which was comparable to the results of first-line gemcitabine plus nab-paclitaxel in the pivotal phase III study (Von Hoff et al., 2013). Similarly, retrospective series reported median OS of about 8.5 months with FOLFIRINOX as second-line treatment after progression under gemcitabine-based regimen (Assaf et al., 2011; M. G. Lee et al., 2013). Prospective studies are warranted.

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4.2. Resectable PDAC As described above, localized PDAC tumors are classified on a continuum from “resectable” to “unresectable, locally advanced”, according to vascular involvement (Tempero et al., 2014). The only curative treatment of pancreatic cancer is radical surgery. The major goal of surgery is to achieve R0 resection (Seufferlein et al., 2012). After careful pre-therapeutic evaluation, only 15%20% of PDAC patients are candidates for surgical resection, and many of them are found to have microscopically positive margins (R1) at the time of surgery (Ryan et al., 2014b). The proportion of patients with R1 resection has been underestimated until the 2010ies due to a lack of standardization in the quality of histopathological protocols; a careful examination of resection margins including multicolor inking by the surgeon of the three resection margins (the portal veinsuperior mesenteric vein, superior mesenteric artery, and posterior margins) should be performed for a reliable evaluation of R0/R1 status since it has a clinically relevant impact on disease-free survival (DFS) prediction (J. R. Delpero et al., 2014). Age is not a criterion to select patients for a surgical approach. Indeed, surgery has been shown feasible in elderly patients (> 70 years) and these patients do benefit from radical surgery (Turrini et al., 2013). However, comorbidity can justify abstention from an otherwise technically possible resection in this setting. Over the last 20 years, the perioperative morbidity and mortality of surgery for PDAC have declined significantly, thanks to advances in pre-operative imaging and to improvements in surgical and anaesthetic procedures. Operative mortality rate is now < 5% in major centers (compared with 20% in the 1980ies), morbidity is about 20%-30% (mainly represented by post-operative pancreatic fistula and pulmonary infections), and the average hospital stay has been reduced to less than two weeks (J.R. Delpero, Paye, & Bachellier, 2010). The experience of the center and surgical team (i.e. case volume) has a significant impact on post-operative morbidity and mortality, and on long-term patient survival as well (Fong, Gonen, Rubin, Radzyner, & Brennan, 2005). The type of surgical resection (pancreaticoduodenectomy, distal splenopancreatectomy, or total pancreatectomy) is determined by

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the location and size of the tumor; no major difference in outcome has been observed with the type of pancreatic resection (J.R. Delpero et al., 2010). The benefit of pylorus preservation has not been demonstrated (Diener et al., 2014). In addition, more extensive surgery, including extended lymphadenectomy and arterial en bloc resection does not result in significantly improved long-term survival and is not recommended (Martin et al., 2009). Mini-invasive laparoscopy is increasingly used for the resection of distal tumors (Tran Cao et al., 2014). About 80% of patients treated by « curative » resection alone for localized PDAC will develop metastastic (most frequent) and/or local recurrence (Hishinuma et al., 2006). Based on this observation, the role of adjuvant therapy has been extensively explored. The Pancreatic Cancer Meta-analysis Group published in 2005 a meta-analysis of five randomized controlled trials evaluating adjuvant chemotherapy or chemoradiotherapy (CRT) with individual data from 875 patients (Stocken et al., 2005). The administration of chemotherapy reduced the risk of death by 25% (p = 0.001). Median post-resection OS with adjuvant chemotherapy was 19 months vs 13.5 months in the observation group. Based on the results of the CONKO-001 study (Oettle et al., 2013) (comparing observation vs weekly gemcitabine: Hazard Ratio [HR] for DFS: 0.55, p < 0.001; HR for OS: 0.76, p = 0.01) and the ESPAC-3 (Neoptolemos et al., 2010) (gemcitabine vs 5FU: no significant difference in PFS, OS, or global HRQoL; more treatment-related serious adverse events with 5FU : 14% vs 7.5%, p < 0.001), six months of adjuvant chemotherapy with either gemcitabine or 5FU is recommended after curative resection for PDAC. Gemcitabine transporter hENT-1 expression level by immunochemistry has been proposed as a predictive biomarker of response to gemcitabine and may be useful to guide the choice between these two adjuvant regimens (Marechal et al., 2012). However, it remains unvalidated for routine practice due to discordant results according to the antibody origin (mouse vs rabbit) and tumor setting (adjuvant vs metastatic) (Svrcek et al., 2015). Recently, oral S-1, a fluoropyrimidine derivative was shown to be non-inferior, and furthermore, even superior to gemcitabine in a randomized phase III trial in a Japanese population (JASPAC-01) (HR for DFS: 0.56, p < 0.0001; HR for OS: 0.56, p < 0.0001) (Fukutomi et al., 2013). Low mRNA levels of dihydropyrimidine dehydrogenase (DPD) and high mRNA levels of thymidylate synthase (TS) might be predictive of S-1 benefit (Shimoda, Kubota, Shimizu, & Katoh, 2015). S-1 is now considered as the new standard treatment for patients with resected PDAC in Japan. Given the differences in S-1 metabolism in Asian vs non-Asian patients, the question of the potential translation of these results in a Western patient population remains unanswered. The patient’s ability to tolerate adjuvant chemotherapy appears to be an important prognostic factor in view of the natural history of pancreatic resection without adjuvant treatment (5-year OS of 10%) and outcome of patients who were unable to complete all planned cycles of chemotherapy (due to the deterioration of their condition, for example) (Valle et al., 2014). Conversely, the role of adjuvant radiotherapy is still a matter of debate with a controversy between the results of North American studies (favoring the use of CRT for local control) and European experience (showing no benefit of radiation therapy) (Corsini et al., 2008; Hsu et al., 2010; Klinkenbijl et al., 1999; Neoptolemos et al., 2004). The RTOG-0848 randomized trial aiming to provide answers to this question is ongoing in the United States (NCT01013649). In the Pancreatic Cancer Meta-analysis Group publication, there appeared to be a benefit of adjuvant CRT for the subgroup of patients whose resection was incomplete (R1) (Stocken et al., 2005). CRT is considered as an alternative to chemotherapy in cases with positive margins (R1 or R2 resection). Patients with positive lymph nodes (N+) may also benefit from adjuvant CRT (Liu et al., 2015; McDonald et al., 2015). The role of combination chemotherapy, targeted therapies, and immune therapies in the adjuvant setting of PDAC remains to be explored. The ongoing ESPAC-4 phase III study investigates the combination of gemcitabine plus capecitabine compared to gemcitabine alone. The use of the FOLFIRINOX and gemcitabine plus nab-paclitaxel combination regimens is not defined to date; two phase III studies comparing these regimens to standard gemcitabine are ongoing (NCT01526135, NCT01964430). Recently, two randomized studies, the phase III CONKO-005 (after R0 resection) and phase IIb CONKO-006 (after R1 resection), evaluating the addition of erlotinib or sorafenib, respectively, to adjuvant gemcitabine failed to improve DFS and OS in patients with resected PDAC

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(Sinn et al., 2015; Sinn et al., 2014). Studies exploring the role of immunotherapies are ongoing (NCT01072981). About 20%-30% of patients with resected PDAC, even those who received adjuvant chemotherapy, develop early relapse and die within the year following surgery. This lack of benefit from the surgery plus adjuvant chemotherapy sequence strategy is mainly observed in patients with R1 or N+ tumors (J. R. Delpero et al., 2014; Strobel et al., 2015). This observation has led to the exploration of neoadjuvant therapy (i.e. chemotherapy and/or radiotherapy before surgical resection) as an alternative strategy. Neoadjuvant therapy aims to: (a) test the chemosensitivity of the tumor, and also patient’s tolerance to the treatment; (b) give a time of observation (4-6 months) to identify patients with aggressive, early metastatic tumor who are not good candidates for surgery (about 30%); and (c) obtain a tumor downstaging and increase the chances of obtaining R0 resection. According to the results of the meta-analysis conducted by Gillen et al. (Gillen, Schuster, Meyer Zum Buschenfelde, Friess, & Kleeff, 2010) in 2010, neoadjuvant strategies (chemotherapy or CRT) do not appear to provide benefit to patients with resectable PDAC at the time of diagnosis: resection rates were similar with or without neoadjuvant treatment and the median OS achieved with these strategies was not different to that achieved in patients who underwent initial resection followed by adjuvant therapy (23.3 months vs 20.1-23.6 months). However, this meta-analysis displayed many biases (mixing studies with various chemotherapy and radiotherapy protocols and with no or unclear definition of resectability in more than 50% of studies) and was performed before the advent of the FOLFIRINOX and gemcitabine plus nab-paclitaxel combination regimens, which may yield higher antitumor activity. Phase II/III clinical trials testing these regimens in patients with resectable tumors are currently ongoing (NCT01298011, NCT02243007, NCT02047513, NCT02172976, NCT01560949). The results of the NEOPAC phase III study (NCT01521702) comparing adjuvant gemcitabine vs neoadjuvant GEMOX plus adjuvant gemcitabine in patients with resectable PDAC are pending. The PACT-15 phase II/III study (NCT01150630) investigates the PEXG combination (cisplatin and epirubicin 30 mg/m2, gemcitabine 800 mg/m2, every 14 days, and capecitabine 1250 mg/m2/day continuously). A French trial (PANACH) will compare upfront surgery vs FOLFOX or FOLFIRINOX then surgery in the setting of resectable PDAC.

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4.3. Borderline resectable PDAC The term “borderline resectable” has been increasingly used in recent years, with fluctuating anatomic definitions according to centers and surgeons and the greatest points of contention revolving around the extent of venous mesentericoportal axis involvement. A consensus has emerged for the use of the National Comprehensive Cancer Network (NCCN) classification (Bockhorn et al., 2014; Tempero et al., 2014). Given the technical options of vascular reconstruction, resection of these tumors is technically feasible, but at the cost of a high risk of R1 surgical margins (Bockhorn et al., 2014; J. R. Delpero et al., 2015). Based on the historically poor outcome for patients with R1 resected PDAC alternative strategies for this specific patient group have been considered, and particularly, the use of neoadjuvant therapy before surgery. In the meta-analysis of Gillen et al. (Gillen et al., 2010), contrary to resectable tumors, neoadjuvant treatments seemed to have an interesting role in the management of patients with initially nonresectable PDAC (borderline resectable and locally advanced tumors), converting certain tumors to a resectable stage and yielding long survival. The median OS in patients undergoing tumor resection after neoadjuvant treatment was comparable to that of patients who were resectable from the outset (20.5 months), vs 6-11 months with palliative therapy. Although disputable due to the abovementioned biases, this study suggested that with the help of neoadjuvant strategies, indications for resection can be enlarged to include certain patients with borderline resectable and even locally advanced tumors at diagnosis. Besides this meta-analysis, multiple investigators reported their single-center experience of neoadjuvant treatment in patients with borderline resectable PDAC (Heestand, Murphy, & Lowy, 2015). The results of these studies are also difficult to interpret due to (a) various definitions of borderline resectability, (b) the use of different chemotherapy regimens, (c)

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the combination or not with radiotherapy, (c) small sample size, and (d) retrospective design. In a French multicenter survey involving 1,399 patients who underwent pancreatectomy with or without venous resection for PDAC, long-term survival after surgery was significantly altered when up-front venous resection was performed (median OS: 21 months vs 29 months, p = 0.0002), and venous resection was a significant poor prognostic factor in multivariate analysis (HR: 1.75, p = 0.0005); neoadjuvant treatment was significantly associated with improved long-term survival in patients with venous resection (HR: 0.52, p = 0.031) (J. R. Delpero et al., 2015). This observation indicates that neoadjuvant treatment may be a better strategy than up-front resection in patients with preoperative suspicion of venous involvement. However, there is not enough evidence to date to recommend neoadjuvant therapy regimens in patients with borderline resectable PDAC (Bockhorn et al., 2014). Therefore, evaluation of neoadjuvant therapeutic options is only recommended in the setting of prospective trials at high-volume centers. It can be assumed that the regimens most active in the treatment of metastatic disease would offer the best chance of achieving tumor downstaging and systemic disease control. The FOLFIRINOX (NCT01688336, NCT01661088 NCT01397019, NCT01591733, NCT01560949, NCT01897454) and the gemcitabine plus nab-paclitaxel combinations (NCT02124369, NCT02241551, NCT02427841, NCT01470417), with or concurrent radiotherapy, are currently being investigated in patients with borderline resectable PDAC. The FOLFIRINOX regimen will also be evaluated in this setting in a French intergroup neoadjuvant trial (PANDAS) and in the international ESPAC-5 study (upfront surgery vs FOLFIRINOX or gemcitabine plus capecitabine or chemoradiotherapy with capecitabine then surgery). The role of immunotherapy (algenpantucel-L) will be explored in two trials (NCT01836432, NCT02405585).

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Noticeably, the assessment of tumor response to neoadjuvant therapy using current imaging techniques is challenging. Perivascular infiltration persists after chemotherapy and/or radiotherapy and it is hard to distinguish fibro-inflammatory changes from tumoral infiltration (Kim et al., 2009). However, partial regression of the contact between tumor and vessels indicates a likely R0 resection, and thus suitability for surgical exploration (Cassinotto et al., 2014). Another important efficacy criterion is then the absence of apparition of distant metastases. A decrease in the level of CA 19-9 may help in decision-making, but only intra-operative biopsy and/or examination of the resected specimen permits conclusions as to the efficacy of neoadjuvant therapy (Bockhorn et al., 2014; Takahashi et al., 2010). Furthermore, there is no consensual agreement on the pathological criteria for defining response (damaged cells, necrosis, fibrosis) and their prognostic value remains controversial; the College of American Pathologists (CAP) score is the most widely used tumor regression grading system but further validation studies are needed (Verbeke, Lohr, Karlsson, & Del Chiaro, 2015; Washington et al., 2014). 4.4. Locally advanced PDAC Locally advanced PDAC displays an intermediate prognosis between resectable and metastatic stages. Gemcitabine remains the best-validated standard chemotherapy regimen in this setting, based on the results of past studies in “advanced PDAC”, pooling patients with metastatic and locally advanced tumors. The results of the FOLFIRINOX and gemcitabine plus nab-paclitaxel combinations in the metastatic setting, the latter shown to be superior regimen, have raised increasing interest in evaluating these regimens in patients with locally advanced disease. Retrospective studies using FOLFIRINOX or modified FOLFIRINOX with or without radiotherapy showed promising results with conversion to resectability in 20%-40% of cases (Ferrone et al., 2015; Mahaseth et al., 2013; Marthey et al., 2015; Petrelli et al., 2015). The NCCN guidelines include these two regimens among the recommendations for patients with locally advanced PDAC based on extrapolations from randomized trials in patients with metastatic disease. Prospective studies with these intensified regimens in the locally advanced setting are ongoing (NCT02125136, NCT02043730). Of note, the same concerns as for resectable PDAC regarding tumor evaluation by imaging and pathology examination after neoadjuvant treatment have been raised for locally advanced PDAC (Ferrone et al., 2015; Verbeke et

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al., 2015). As for resectable PDAC, the role of radiotherapy in the management of locally advanced PDAC has been a matter of debate for more than 20 years. Two randomized prospective studies comparing chemotherapy plus radiotherapy vs gemcitabine alone showed contradictory results, while two retrospective studies were in favor of the use of CRT after a course of chemotherapy (Chauffert et al., 2008; Huguet et al., 2007; Krishnan et al., 2007; Loehrer et al., 2011). The randomized LAP07 and SCALOP studies prospectively tested this second strategy and recently provided key results about radiation therapy in locally advanced PDAC. In the English SCALOP phase II study patients with locally advanced PDAC with stable/responding disease after induction chemotherapy by three cycles of gemcitabine plus capecitabine (GEMCAP) combination (gemcitabine 1,000 mg/m2 weekly, and capecitabine 830 mg/m2/day for 3 weeks, every 28 days), received a further cycle of GEMCAP and then radiation therapy (50.4 Gy) associated with either capecitabine (1,660 mg/m2/day weekdays only) or gemcitabine (300 mg/m2 weekly) (Mukherjee et al., 2013). Capecitabine demonstrated significantly better OS (median OS 15.2 months vs 13.4 months, HR: 0.39, p = 0.012) and less haematological and non-haematological toxicity compared to gemcitabine. CRT with capecitabine should then form the template regimen for radiation therapy in locally advanced PDAC. The international LAP07 phase III study used the same study plan with weekly gemcitabine with or without erlotinib (100 mg/day) as induction chemotherapy (first randomization) (Hammel et al., 2013). Patients whose tumor was controlled after four months of treatment were randomized to continuation of the same chemotherapy or CRT (54 Gy) with capecitabine (1,600 mg/m2/day) (second randomization). Thirty-nine percent of patients were excluded before the second randomization, mainly due to metastatic progression, which was similar to the proportion of exclusions observed after chemotherapy in the SCALOP study (35%). Erlotinib failed to improve OS and superiority of radiotherapy was not confirmed. Noticeably, the OS of patients who completed the entire protocol were significantly longer than the statistical hypothesis (16.4 and 15.2 months vs 9 and 12 months for chemotherapy and chemoradiotherapy arms, respectively). Neither the deviations observed in the radiotherapy protocol or toxicity, which was moderate, explained the lack of superiority of CRT. Even though the OS was not improved with CRT, a secondary analysis showed that patients in the CRT group had a longer time without treatment with significantly less local tumor progression, which could translate into a better HRQoL (Huguet et al., 2014). Then, although early results of the LAP07 study have lessened the enthusiasm for the use of CRT for locally advanced PDAC, radiation therapy may be an option for selected patients following an adequate course of chemotherapy, especially those wishing a chemotherapy break. Current trials aim to study the role of CRT in the setting of more active induction chemotherapy regimens. In the phase III CONKO-007 study (NCT01827553), patients with locally advanced PDAC will be randomly assigned to induction FOLFIRINOX or gemcitabine followed by second randomization to further chemotherapy or CRT. In the phase II LAPACT study (NCT02301143) patients who complete six cycles of gemcitabine plus nabpaclitaxel without disease progression or unacceptable toxicities will receive additional treatment according to the investigator’s choice: more chemotherapy with gemcitabine plus nab-paclitaxel, CRT, or surgery. In addition, the recently opened phase I/II SCALOP-2 trial (NCT02024009) will treat patients with induction gemcitabine plus nab-paclitaxel followed by random assignment to further chemotherapy or to CRT with capecitabine with or without nelfinavir, a HIV protease inhibitor with radiosensitizing properties. The role of immunotherapy is also being explored. Optimization of radiation modalities is another research direction in locally advanced PDAC. Recent advances in imaging as well as radiotherapy planning and delivery techniques have made it possible to target tumors more accurately while sparing normal tissues (Hajj & Goodman, 2015). Ongoing randomized trials are investigating the contribution of intensity-modulated radiotherapy (NCT01921751) and stereotactic body radiotherapy (NCT01926197). The role of other locoregional therapy, including ablative therapies and intratumoral gene transfer, in locally advanced PDAC remains to be defined (Buscail et al., 2015; Rombouts et al., 2015).

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5. Unanswered clinical questions Currently unanswered clinical questions in the management of PDAC are summarized in Table 4.

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6. Research pathways for the future of PDAC management 6.1. Challenges and advances in preclinical models A key issue in the development of therapies for PDAC is the establishment of appropriate preclinical models that are able to reproduce the complexity of human PDAC microenvironment and to reliably predict treatment efficacy in the clinical setting. Indeed, many of the drugs designed based on preclinical studies have failed to demonstrate a clinically relevant benefit for patients with PDAC. 6.1.1. In vitro cell-based assays The advantage of preclinical testing in cell lines is that they represent a homogeneous population of cancer cells that can be molecularly characterized at the genetic and phenotypic levels. Studying the response profiles in different cell lines may be helpful to identify beneficial new therapies based on molecular targets and determine the mechanisms of action of new drugs. However, such cell systems studying PDAC cells alone in a flat 2D culture plate does not represent the complexity of the in vivo situation. First, PDAC cells in vivo, in a 3D space, considerably differ in their morphology and differentiation and their cell-cell and cell-matrix interactions. Second, cell line models ignore the contribution of the stroma and stem cells to tumor biology and drug response. Different types of 3D in vitro models have been developed, including “spheroids” and “organoids” in which cancer cells are grown suspended in an appropriate medium in order to mimic the ECM (Kimlin, Kassis, & Virador, 2013). More sophisticated 3D co-cultures mixing multiple cell types, e.g. cancer cells and PSC (so called “organotypic cultures”), have been exploited to investigate different cancer types including PDAC (Coleman et al., 2014). Such systems may be closer to the in vivo reality and may display higher predictive value for therapeutic agent testing. 6.1.2. In vivo tumor models using cell-line xenografts Subcutaneous xenograft models using implantation of PDAC cell lines in immunocompromised mice offer a 3D microenvironment and enable the exploration of distant disease progression (Qiu & Su, 2013). However, the major challenge is that a single cell line-based xenograft grows as a homogeneous mass of cancer cells with minimal stromal infiltration. Thus, it cannot mimic the heterogeneity of a whole tumor and the architecture and biology of human PDAC, both regarding the primary site and metastases. Due to the low abundance of desmoplastic reaction, intratumoral perfusion is quite preserved as compared to human PDAC and therefore such model may overestimate the diffusion and antitumor effect of chemotherapeutic agents. Moreover, other specific local paracrine factors within the pancreas (e.g. insulin levels, other cellular components) may not be replicated in subcutaneous xenograft systems. Orthotopic xenograft models (i.e. implantation of PDAC cell lines within the pancreas of immunocompromised mice) may be more relevant but are more difficult to monitor than subcutaneous xenografts (Qiu & Su, 2013). New imaging technologies adapted to small animals (including fluorescence and bioluminescence optical imaging, ultrasound, microPET, MRI, and MDCT) have been developed but are still of limited access due to their costs. Finally, both hetero- and orthotopic xenografts are limited by the lack of host immune response in immunocompromised mice. 6.1.3. Genetically engineered mouse models Genetically engineered mouse models have been developed based on the main driving genetic alterations seen in human PDAC (Mazur & Siveke, 2012; Morris et al., 2010). Many of these models appear to better recapitulate the clinical, histopathologic (including the marked stromal reaction), and molecular features of human tumors, with the advantage of generating the disease in the native organ and in the setting of an intact immune system. However, mouse tumors do not exhibit exactly the same biology and do not reflect the wide genetic heterogeneity of human tumors. Moreover, correlative studies between human and murine tissues are often hampered by different antibody affinities. 6.1.4. Patient-derived tumor xenografts (“xenopatients”)

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Emerging data supports the potential of primary patient-derived tumor xenografts as a platform for drug screening and biomarker development (Tentler et al., 2012). Surgically resected tumor samples are engrafted directly into immunocompromised mice. The advantage of such system over cell linebased xenografts is that it enables the maintenance of tumor heterogeneity and architecture observed in patients, although the human stroma is replaced by murine stroma with sequential passages. Xenopatients retain a greater proportion of stromal components and develop distant metastases. This system may be of better predictive value for clinical activity of new drugs (Garralda et al., 2014). However, the development of such approach is limited by the availability of fresh tumor tissues, the delay required for tumor “take”, and take rates. Time-to-engraftment depends on cancer type, implantation site, and recipient strain but is in general about four to six months. Take rates can be enhanced in selected recipient strains such as NOD/SCID mice. The advantages and disadvantages of the different mouse models are summarized in Table 5. 6.1.5. Ex vivo models Ex vivo models have been initially developed using cancer cells isolated from patients (primary cell cultures) either from surgical resection specimens or fine-needle aspiration biopsy samples (Michalski et al., 2008; Rubio-Viqueira et al., 2007). In this system, cancer cells are cultured in vitro and exposed to therapeutic agents. The cellular effects were shown to correlate with antitumor activity in vivo, and ex vivo testing was therefore proposed as a new tool to predict therapeutic benefit. However, here again, this model ignores the contribution of the stroma. Alternatively, tissue slicer is an innovative ex vivo model that consists in culture of fresh tissue slices (250-300 m) obtained from fresh human tumors (de Graaf et al., 2010; van Geer et al., 2009). It allows the growth of cancer cells in their own supportive human microenvironment. This strategy enables the study of stromal and cancer cells interactions, architecture, and local invasion although it is limited by the short time of observation (a few days) and the impossibility to study distant disease progression. This approach is a potent and useful tool to evaluate ex vivo the effects of novel anticancer drugs, either as monotherapy or in combination, on whole tumors, i.e. both cancer cells and surrounding stroma. Specific pharmacodynamic biomarkers may be monitored directly on tumor tissue, using selected concentrations of drugs and time points, to identify concentrations associated with biological activities (Neuzillet et al., 2015). Therefore, this assay is a promising model to guide the clinical development of novel drugs by validating active drug concentrations and biomarkers for patient selection prior launching clinical trials. Overall, optimization of PDAC preclinical models to improve their therapeutic predictive value is one of the main challenges for future PDAC therapy in terms of minimization of the risk of failure of large clinical trials involving large numbers of patients and high costs. The aims are to select the best candidate drugs to enter clinical trials and to identify biomarkers to guide patient selection. To date, no preclinical assay is perfect and the choice of adequate preclinical model should be determined by the specific scientific question asked. 6.2. PDAC screening and early diagnosis As PDAC is potentially curable only when detected at a resectable stage, screening and early diagnosis are crucial issues in the battle against PDAC. International expert consortium considers it appropriate to screen for PDAC in high-risk individuals (i.e. in case of genetic predisposition or familial aggregation) (Canto et al., 2013; Klein, 2013). To be successful, screening should allow detection and treatment of T1N0M0R0 PDAC and high-grade dysplastic precursor lesions (PanIN and IPMN). As discussed above, CA 19-9 predictive value is insufficient for PDAC early diagnosis and screening is currently based on imaging only (Ballehaninna & Chamberlain, 2012; Ni et al., 2005). Screening programs should include initial EUS and/or MRI, not CT or ERCP (Canto et al., 2013). Data has demonstrated that precursor lesions can be identified by these imaging modalities. No consensus exists regarding the age to initiate or stop screening and the optimal intervals for follow-up (Canto et al., 2013). More evidence is needed, particularly for how to

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manage patients with detected lesions. Timing and extent of surgery (i.e. partial vs total pancreatectomy) for familial pancreatic cancer are debated (Canto et al., 2013). Screening and subsequent management should be performed at high-volume centers with multidisciplinary teams, preferably within research protocols. The knowledge of genetic alterations occurring in precursor lesions through pancreatic carcinogenesis offers sensitive and specific markers that could be exploited for the early diagnosis of PDAC. These genetic alterations (especially, KRAS mutations) can be detected in the pancreatic juice collected at endoscopy or in the blood. Next-generation DNA sequencing technologies have deeply changed the speed and cost at which genetic alterations can be analyzed (Damodaran, Berger, & Roychowdhury, 2015). These recent advances have offered new applications for cancer diagnosis. Circulating tumor DNA (ctDNA) are cell-free fragments of DNA shed into the bloodstream by cells undergoing apoptosis or necrosis. The load of ctDNA has been shown to correlate with tumor stage and prognosis, and ctDNA can be genotyped to search for somatic genomic alterations found in the tumor (Diaz & Bardelli, 2014; Kinugasa et al., 2015). ctDNA has been shown to be present in the blood of more than 75% of patients with advanced PDAC and 50% of patients with localized tumor, even in patients without detectable circulating tumor cells (Bettegowda et al., 2014). Although its sensitivity appears to be insufficient to be used for PDAC screening yet, such a non-invasive method may have great potential as a new strategy for the diagnosis of PDAC, even before a tumor is detectable on imaging, as well as for predicting survival and for guiding therapeutic decision. For example, it would allow clinicians to decide whether or not to perform potentially debilitating surgery. Other circulating tumor-derived materials are currently being investigated for early PDAC detection; circulating micro-RNA (miRNA) and exosomes stand as the most promising ones (Melo et al., 2015a; Sun, Kong, Du, & Li, 2014). Using mass spectrometry analysis, Melo et al. (Melo et al., 2015b) recently identified a membrane-anchored proteoglycan molecule, glypican-1, that is specifically enriched at the surface of on PDAC-cell-derived exosomes. This team clearly demonstrated that glypican-1 positive circulating exosomes were detected in the bloodstream of patients with PDAC using flow cytometry with absolute specificity and sensitivity, distinguishing healthy subjects and patients with a benign pancreatic disease from patients with early- and latestage PDAC. In addition, serum levels of glypican-1 positive circulating exosomes correlated with tumor burden, and were a prognostic marker associated with the survival of pre- and post-surgical patients. Furthermore, in a mouse model of genetically induced PDAC, Melo's test gave positive results before a tumor was detectable by MRI. Although these findings require further validation in a larger cohort, this work demonstrates for the first time that circulating vesicles in blood can be a source of specific and reliable diagnostic biomarkers for PDAC. Alterations in whole-body metabolism could also be detected in patients with PDAC prior to diagnosis, with potential utility for PDAC screening. Among metabolic constraints caused by low tumor vascularization, PDAC cells face AA shortage, which can have a critical impact on cell survival especially for essential AA (Cohen et al., 2015). It has been suggested that the increased AA requirement for cancer cells is a very early phenomenon in PDAC development. Mayers et al. (Mayers et al., 2014) suggested that metabolic reprogramming to provide cancer cells with branched-chain AA (BCAA) may announce future diagnosis of PDAC. Indeed, elevated plasma levels of all three essential BCAA (isoleucine, leucine, and valine) were shown to precede PDAC diagnosis by about five years. BCAA elevations are derived from a long-term pool of AA of muscular origin. The mechanisms underlying this protein breakdown are still under investigation. This study reveals that metabolism alterations clearly predate PDAC diagnosis and circulating metabolites may be exploited as a high-risk or early-detection marker for PDAC. 6.3. Inter- and intra-tumor heterogeneity: molecular subtypes and predictive markers The concept of distinct biological subsets of PDAC derives from observations that tumors characterized by TP53 wild-type/SMAD4 wild-type profile have indolent behavior, improved response to therapy, and low metastatic efficiency, while TP53 mutant/SMAD4 wild-type tumors

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display aggressive features and high metastatic potential, and TP53 mutant/SMAD4 mutant tumors are among the most aggressive and widespread metastatic PDAC (C. Iacobuzio-Donahue, 2014; C. A. Iacobuzio-Donahue et al., 2009). Many immunohistochemical biomarkers have been proposed to identify prognostic subgroups of patients with PDAC (Ansari, Rosendahl, Elebro, & Andersson, 2011). However, none of these molecular markers can be recommended for routine clinical use as they were identified in small retrospective cohorts and were inconsistencies across studies. Prospective multicenter studies in larger patient populations are required to validate their prognostic and predictive value. More than a single marker, a panel of molecular markers may be useful in predicting individual patient outcome. Recently, based on data from deep whole-genome sequencing and analysis of structural rearrangement of chromosomes, Waddell et al. (Waddell et al., 2015) proposed a new classification of PDAC into four subtypes based on structural variation profiles (i.e. stable, locally rearranged, scattered, and unstable), with distinct therapeutic response profile to platinum salts and poly-(ADP-ribose) polymerases (PARP) inhibitors.

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Better definition of PDAC molecular classification may allow optimization of therapeutic strategy. For example, as SMAD4 mutation may predict further polymetastatic evolution of locally advanced PDAC, local treatment (CRT) might be sufficient to control the disease in patients with intact SMAD4, while patients with mutated SMAD4 might require more intensive systemic chemotherapy (C. A. Iacobuzio-Donahue et al., 2009). The role of SMAD4 status in the pattern of disease progression will be addressed in ancillary studies of ongoing clinical trials in unresectable PDAC (NCT01921751, NCT01972919, NCT02241551). One of the main pitfalls in current PDAC therapy is the lack of reliable predictive biomarkers of response to treatment. Molecular markers associated with gemcitabine transport and metabolism in human PDAC cells (mainly, hENT-1) have been associated with inconsistent findings and remain unvalidated for routine practice (Marechal et al., 2012; Svrcek et al., 2015). The secreted protein acidic and rich in cystein (SPARC) protein has been suggested to predict response to nab-paclitaxel in preclinical and phase II clinical studies (Neuzillet, Tijeras-Raballand, et al., 2013; Von Hoff et al., 2011). However, this hypothesis was not confirmed in the phase III study, which showed that SPARC status did not influence the response to this treatment (M. Hidalgo et al., 2014). Conversely, consistent preclinical and clinical data have demonstrated hypersensitivity of BRCA or PALB2-deficient PDAC to DNA cross-linking agents, including mitomycin-C and platinum salts and to PARP inhibitors (Lowery et al., 2011; Villarroel et al., 2011; Vyas et al., 2015; Waddell et al., 2015). PARP enzymes are key components of the cellular DNA repair machinery for single-strand breaks and nucleoside base damage. Inhibition of PARP in cells with pre-existing defects in homologous recombination, such as BRCA-deficient PDAC cells, leads to the formation of doublestrand breaks that cannot be repaired, then causing cancer cell death (J. M. Lee, Ledermann, & Kohn, 2014). This effect of synthetic lethality has displayed efficacy in clinical trials in BRCA1/2-mutated ovarian carcinoma and gives a rationale to the therapeutic development of PARP inhibitors (e.g. olaparib, veliparib) for PDAC associated with BRCA1, BRCA2, and PALB2 mutations (NCT01296763, NCT02184195, NCT01585805, NCT01489865) (Kaufman et al., 2015). Overall, contrary to other cancer types such as breast, colorectal, or non-small cell lung cancer, in which molecular classification has allowed delineating patient groups with distinct treatment strategies, PDAC molecular splitting is still at an embryonic stage and not validated yet to guide PDAC treatment. Moreover, data are accumulating to support the concept of intratumor genetic and phenotypic, spatial and temporal, heterogeneity and clonal evolution in PDAC, as described in other cancer types (Gerlinger et al., 2012; C. A. Iacobuzio-Donahue, 2012). Data from whole genome sequencing of treatment naïve PDAC and matched metastases provide evidence for clonal evolution within the primary site preceding metastasis formation and for the divergence and heterogeneity between metastatic sites, through Darwinian selection (Makohon-Moore et al., 2015). Intratumor heterogeneity can lead to underestimation of the tumor genomic landscape depicted from a single biopsy sample by introducing tumor-sampling bias. In addition, it is one of the main causes of

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treatment failure by selection of treatment-resistant clones under treatment. This may then represent major challenges to personalized-medicine and biomarker development. Alternatively, considering tumor growth as a Darwinian tree with the trunk representing ubiquitous mutations and the branches representing heterogeneous mutations may help defining the most relevant therapeutic targets for drug discovery (Yap, Gerlinger, Futreal, Pusztai, & Swanton, 2012).

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6.4. Current therapeutic research pathways

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A summary of current therapeutic research pathways for PDAC in connection with their molecular and biological abnormalities is displayed in Table 6 (Abou-Alfa et al., 2011; Beatty et al., 2013; BekaiiSaab et al., 2014; Benson et al., 2014; Borad et al., 2015; Galluzzi, Kepp, Vander Heiden, & Kroemer, 2013; M. Hidalgo et al., 2014; Hingorani et al., 2015; Hurwitz et al., 2014; Ko, 2015; Kordes et al., 2015; Le et al., 2013; D. T. Le, J. N. Uram, et al., 2015; D. T. Le, A. Wang-Gillam, et al., 2015; Middleton et al., 2014; Neesse et al., 2015; Neuzillet, Tijeras-Raballand, et al., 2014; Oettle et al., 2012; Ostrem, Peters, Sos, Wells, & Shokat, 2013; Ozdemir et al., 2014; J. Wang, Reiss, Khatri, Jaffee, & Laheru, 2015; Wang-Gillam et al., 2015; Weden et al., 2011; Wolpin et al., 2014; Zimmermann et al., 2013; Zorde Khvalevsky et al., 2013).

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6.5. Innovative complementary interventions: quality of life and physical activity Palliative and supportive care holds a major place in PDAC management. It aims to prevent and ameliorate suffering while ensuring optimal HRQoL. It includes the treatment of biliary and gastric outlet obstructions, tumor-associated pain, depression, malnutrition, and pancreatic insufficiency, as well as thromboembolic disease treatment and prevention in high-risk patients (Pelzer et al., 2015; Tempero et al., 2014). HRQoL has been reported to be a prognostic indicator of survival in various cancers, including PDAC (Bonnetain et al., 2010; Quinten et al., 2009). Interventions aiming to improve HRQoL and, ultimately, survival in PDAC patients are an innovative complementary approach for PDAC therapy that is receiving growing interest. There is accumulating evidence that physical activity may provide benefit to cancer patients, by reducing disease- and/or treatment-induced symptoms, decreasing fatigue, and improving HRQoL (Ballard-Barbash et al., 2012; Cramp & Byron-Daniel, 2012; Mishra et al., 2012). Deconditioning i.e., the loss of physical (cardiorespiratory function and muscle strength) and psychological fitness resulting from reduction of physical activity is one of the main causes of cancer-related fatigue. As an appearing paradox, rest may be deleterious for these patients, while physical exercise is the best way to reduce it (Cramp & Byron-Daniel, 2012). In contrast, no specific drug has shown efficacy for the treatment of fatigue in palliative care patients (Mucke et al., 2015). A beneficial effect of physical activity on survival has also been reported in the most frequent cancers (breast, colon, and prostate) (Ballard-Barbash et al., 2012). It should be explained by a reduction of the circulating levels of estrogen and sex hormone binding globulin (SHBG) for sex hormone-dependent cancers, insulin and insulin-related pathways including IGF-1, inflammation, and by improving immunity (Ballard-Barbash et al., 2012). Moreover, physical activity, coupled with nutritional intervention, is one of the pillars of tumor-related cachexia (Fearon, Arends, & Baracos, 2013). Finally, physical activity may improve survival through its impact on HRQoL (Bonnetain et al., 2010; Mishra et al., 2012; Quinten et al., 2009). Adapted physical activity (APA) during chemotherapy is an original and promising nonpharmaceutical strategy in the field of supportive care to reduce fatigue and improve HRQoL. It has been shown to be both feasible and efficient in various cancers. The effects of an APA intervention in patients with advanced PDAC have never been explored. The APACaP study (NCT02184663) is a French national multicenter study that aims to assess the efficacy and feasibility of an APA program in advanced PDAC patients. Such intervention in patients with PDAC may appear challenging because of multiple cancer-related symptoms (fatigue, depression, pain, jaundice, and denutrition) that are usually considered as barrier to perform physical exercise. On the contrary, we hypothesize that an APA program, taking into account PDAC specificities, may be beneficial in these patients and may

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improve both these symptoms and HRQoL. If such intervention proves to be feasible and effective in that population, implementing standardized APA programs in association with anti-tumoral treatment of advanced PDAC will be the logical next step. Finally, data provided by this research may also have implications for the treatment of other digestive cancers.

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7. General conclusion: from benchside to bedside

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These are exciting times in both preclinical and clinical PDAC research. Better knowledge of the fundamental aspects of PDAC development, progression, and biology has translated into slow but significant therapeutic advances. Progress has been made during the past decade in the management of PDAC in all its forms, from precancerous lesions to advanced cancer stages and from anti-tumor treatments to the management of symptoms. If the 5-year OS has not (yet) changed in PDAC patients, it is likely to increase in the next few years, at any stage of the disease. Besides the identification of new pathways and therapeutic agents, improving the timeliness of access to care, the expertise of the teams, the therapeutic strategy based on individual data and identification of prognostic and predictive biomarkers, and supportive care with a constant concern for the HRQoL of patients will be the cornerstones of further advances.

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Tables Table 1. Main genetic syndromes predisposing to pancreatic ductal adenocarcinoma. Altered gene

Relative risk for PDAC

Frequency of gene alteration in sporadic PDAC

Biological effect

Genetic pancreatitis (Rebours et al., 2008)

PRSS1 (hereditary pancreatitis), CFTR

PRSS1: 50

PRSS1: not mutated

Premature activation of trypsin within the pancreas (PRSS1) and abnormal thickness and stickiness of pancreatic fluid (CFTR) causing inflammation

10-20

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Senescence evasion

Hereditary breast and ovarian cancer syndromes (Holter et al., 2015; Iqbal et al., 2012; Jones et al., 2009)

BRCA1, BRCA2, PALB2

2-3.5

5%-10%

Genetic instability

Lynch syndrome (Kastrinos et al., 2009)

MLH1, MSH2, MSH6, PMS2

9

< 2%

Genetic instability (microsatellites)

Peutz–Jeghers syndrome (van Lier et al., 2010)

STK11/LKB1

130

< 2%

Loss of differentiation and proliferation control leading to hamartomatous polyps and cancers

ATM

Unknown

5%

Genetic instability

Familial adenomatous polyposis (Groen et al., 2008)

APC

Unknown

< 2%

Loss of differentiation and proliferation control, leading to adenomatous polyps and cancers

Juvenile polyposis (Walpole & Cullity, 1989)

SMAD4

Unknown

50%-60%

TGFβ switch from antitumoral into protumoral effects

Li-Fraumeni (Ruijs et al., 2010)

TP53

Unknown

60%-70%

Genetic damage tolerance

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Ataxia-telangiectasia (Roberts et al., 2012)

PDAC: pancreatic ductal adenocarcinoma

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p16/CDKN2A

CFTR: < 2%

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CFTR: 5

Familial atypical multiple mole and melanoma syndrome (Vasen et al., 2000)

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Syndrome

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RI PT

Table 2. Pancreatic ductal adenocarcinoma staging (adapted from the National Comprehensive Cancer Network (Tempero et al., 2014)) and principles of management. Arterial involvement

Venous involvement

Distant organ involvement

Cytohistologic evidence

Current standard treatment strategy

Resectable

Clear fat planes around CA, SMA, and HA

No SMV/PV distortion

None

Not mandatory if straightforward radical surgery is planned, except in case of atypical clinical, biochemical, and/or imaging findings

Surgery + adjuvant chemotherapy

Borderline resectable

Gastroduodenal artery encasement up to the HA with either short segment encasement or direct abutment of the HA without extension to the CA

Venous involvement of the SMV or PV with distortion, narrowing or occlusion of the vein with suitable vessel proximal and distal, allowing for safe resection and replacement

None

Primary tumor biopsy under EUS

Prospective trials for neoadjuvant treatment (chemotherapy  radiotherapy) + surgery

None

Primary tumor biopsy under EUS

Chemotherapy  radiotherapy  surgery

Present (including metastases to lymph nodes beyond the field of resection)

Tumor site of easier access, either percutaneously under ultrasound or MDCT guidance or during EUS

Chemotherapy

Based on tumor location: 1) Pancreatic head: > 180° SMA encasement, any CA abutment, IVC

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Unreconstructible SMV/PV occlusion

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Aortic invasion or encasement.

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Tumor abutment of the SMA ≤ 180° of the circumference of the vessel wall

Unresectable/Locally advanced*

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Stage

2) Pancreatic body/tail: SMA or CA encasement > 180° Metastatic

Irrespective

Irrespective

CA: celiac axis, EUS: endoscopic ultrasound, HA: hepatic artery, IVC: inferior vena cava, MDCT: multiple detector computed tomography, PV : portal vein, SMA: superior mesenteric artery, SMV: superior mesenteric vein


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* Extension to adjacent structures such as transverse colon or mesocolon, stomach, spleen, adrenal gland, or kidney is not a definite contraindication to surgical resection since these structures can be resected along with the primary tumor

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Table 3. Summary of main negative studies (i.e. studies that do not have statistically significant results) evaluating targeted agents in advanced pancreatic ductal adenocarcinoma. Molecule [Ref]

Type

Phase

Endpoint

Result

Antiangiogenesis inhibitors

Bevacizumab (Kindler et al., 2010; Van Cutsem et al., 2009)

mAb

III

OS

Negative

SMI

III

OS

SMI

III

PFS

III

Marimastat (Bramhall et al., 2002)

SMI

EGF and HER2 receptor inhibitors

Cetuximab (P. A. Philip et al., 2010)

mAb

RI P Negative

Poor selectivity of MMP inhibitors, poor target validation, and complexity of MMP biological effects

III

OS

Negative

III

OS

Positive*

Frequent (> 90%) activating KRAS mutations downstream of the receptor driving resistance, as described in colorectal cancer

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SMI mAb

II

PFS

Negative

SMI

II

OS

Negative

mAb

II

PFS

Negative

mAb

III

OS

Negative (stopped)

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Trastuzumab (Harder et al., 2012)

Negative

OS

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MMP inhibitors

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Sorafenib (Goncalves et al., 2012)

Erlotinib (Moore et al., 2007)

Negative

PDAC avascular hypoxic microenvironment selecting anaerobic cancer cells that are intrinsically resistant to hypoxiainduced apoptosis and, consequently, to antiangiogenics

SC

Axitinib (Kindler et al., 2011)

Hypothesis for failure

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Class

IGF receptor inhibitors

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Lapatinib (Safran et al., 2011)

Cixutumumab (P. A. Philip et al., 2014) Ganitumab (NP: NCT01231347)

Crosstalk with other signalling pathways, benefit maybe restricted to a subset of patients with high levels of circulating factors of the IGF axis (McCaffery et al., 2013)

Farnesyltransferase inhibitors (K-Rasdirected agents)

Tipifarnib (Van Cutsem et al., 2004)

SMI

III

OS

Negative

Existence of other Ras isoforms (e.g. N-Ras) that do not rely on farnesylation and geranylgeranylation, working as an alternative pathway for K-Ras membrane attachment when farnesylation is inhibited

MEK inhibitors

CI-1040 (Rinehart et al., 2004)

SMI

II

Response

Negative

SMI

II

OS

Negative

SMI

II

OS

Negative

Crosstalk with other signalling pathways, particularly with the mTOR pathway, potential activity of dual MEK/mTOR pathway inhibition (Tolcher et al., 2015)

Selumetinib (Bodoky et al., 2012) Trametinib (Infante et al., 2014)

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mTOR inhibitors

Everolimus (Wolpin et al., 2009)

SMI

II

PFS

Negative

SMI

II

OS

Negative

SMI

II

PFS

Negative

SMI

II

OS

Crosstalk with other signalling pathways, particularly with the MAPK pathway

Vismodegib (NP: NCT01064622)

Negative (stopped)

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Saridegib (NP: NCT01130142)

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Hedgehog inhibitors

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Temsirolimus (Javle et al., 2010) Stroma depletion may enhance cancer cell invasion and accelerate PDAC progression (Ozdemir et al., 2014; Rhim et al., 2014)

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EGF: epidermal growth factor; IGF: insulin-like growth factor; mAb: monoclonal antibody; MAPK: mitogen-activated protein kinase; MMP: matrix metalloproteinase; NP: not published; OS: overall survival; PFS: progression-free survival; SMI: small molecule inhibitor *marginal overall survival benefit (14 days)

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Table 4. Currently unanswered clinical questions in the management of pancreatic ductal adenocarcinoma. Unanswered questions

Predisposition to PDAC and precancerous lesions

Familial pancreatic cancer: Validation of screening program: time intervals and modality Definition of indications, timing, and extent of surgery Precancerous lesions: Molecular and imaging predictive markers of malignant transformation Large cohorts to describe the natural history of precancerous lesions (e.g. TEAM-P cohort for branchduct IPMN in France, www.teamp.org) Role of endoscopic treatments

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Cancer stage

-

Best perioperative strategy (adjuvant vs neoadjuvant) Role of intensified chemotherapy regimens (FOLFIRINOX, gemcitabine plus nab-paclitaxel) Identification of prognostic and predictive biomarkers to guide the choice of chemotherapy regimen

Borderline resectable

-

Role of the intensified neoadjuvant chemotherapy regimens (FOLFIRINOX, gemcitabine plus nabpaclitaxel) Role and modalities of radiotherapy

Unresectable/Locally advanced

-

Best chemotherapy regimen (FOLFIRINOX, gemcitabine plus nab-paclitaxel) Role and modalities of radiotherapy Identification of prognostic biomarkers to select patients for radiotherapy (e.g. SMAD4) Role of other locoregional therapies (e.g. ablative therapies and gene therapy)

Metastatic

-

Sequential chemotherapy strategy (FOLFIRINOX then gemcitabine plus nab-paclitaxel vs the reverse sequence) Role of targeted therapies, stroma-directed therapies, and immunotherapy Place for therapeutic step-down, maintenance therapy, and chemo-breaks in responders Local treatment (radiofrequency, surgery) of pauci-metastatic disease in long responders Impact of HRQoL-directed interventions (e.g. physical activity) on survival

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-

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Resectable

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HRQoL: health-related quality of life; IPMN: intraductal papillary and mucinous neoplasm; PDAC: pancreatic ductal adenocarcinoma

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Table 5. Summary of the relative strengths and weaknesses of the currently available mouse models of pancreatic ductal adenocarcinoma. Tumor heterogeneity

Stroma abundance

Paracrine factors

-

-

-

-

-

++

Immune system

Comments

Cell-line xenografts - subcutaneous

-

Patient-derived tumor xenografts

++

++

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+

+

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Genetically engineered*

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- orthotopic

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Mouse model

Most widely used (quick and easy to manage) More difficult to monitor vs subcutaneous xenografts

++

++

Correlative studies between human and murine tissues may be hampered by different antibody affinities

+/-

-

Use limited by the availability of fresh tumor tissues, timeto-engraftment, and take rates

(highly depending on the anatomical site of implantation)

Relative scale for relevance of the mouse models for each PDAC feature: -: low; +: moderate; ++: high LSL.G12D/+

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*Molecular identity of most widely used genetically engineered mouse models: KC mice (K-Ras ; Pdx1LSL.G12D/+ R172H/+ LSL.G12D/+ Cre), KPC mice (K-Ras ; p53 ; Pdx1-Cre), TGF-β pathway alterations (K-Ras ; p48-Cre; flox/flox LSL.G12D/+ flox/flox LSL.G12D/+ flox/flox Tgfbr2 , K-Ras ; Pdx1-Cre; Smad4 , p48-Cre; K-Ras ; Smad4 )


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Rational

The pretended "undruggable" Ras • Activating KRAS mutations are present in > 90% of PDAC

Cancer cell metabolism

Tumor-stroma interactions

• Important needs of cancer cells for energy (ATP) and macromolecules (proteins, lipids, glucose) to support their proliferation • PDAC microenvironment constraints (hypovascularization, hypoxia, nutrient deprivation)

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• Key-role in pancreatic carcinogenesis

• PDAC is characterized by an abundant, dense and fibrous desmoplastic stroma

SC

Target

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Table 6. Current therapeutic research pathways for pancreatic ductal adenocarcinoma in relation to molecular and biological abnormalities.

• Small molecules targeting specific pockets of Ras or interaction domains with binding partners: preclinical development (Ostrem et al., 2013; Zimmermann et al., 2013) • Virotherapy: Reolysin® (phase II with negative results) (Bekaii-Saab et al., 2014), adenovirus and other virus under development (NCT00638612, NCT02446093)

• Signalling pathways involved in tumor-stroma interactions = potential therapeutic targets • Strategies of modulation of the abundance and/or activity of the stroma

• TGF-β pathway inhibitors (trabedersen, LY2157299): phase I with encouraging results (Oettle et al., 2012), phase II ongoing (NCT01373164)

• L-asparaginase (asparagine deprivation critical for cells with low ASN expression): phase II ongoing (GRASPANC study, NCT01523808)

• Notch/DLL4 pathway inhibitors (demcizumab, OMP-59R5): phase Ib with encouraging results (M. Hidalgo et al., 2014), phase Ib/II ongoing (NCT01647828), phase II in preparation

• Hydroxychloroquin (autophagy and macropinocytosis inhibitor): clinical trials ongoing (NCT01978184; NCT01128296; NCT01506973; NCT01494155; NCT01273805) (Wolpin et al., 2014)

• Wnt/β-catenin pathway inhibitors (OMP54F28, PRI-724): phase Ib ongoing (NCT02050178, NCT01764477)

• Agents targeting specific glycolysis enzymes (PKM2, LDH-A): preclinical development

• Lysyl-oxidase inhibitor (simtuzumab, action on collagen remodelling): preclinical study with contradictory results, phase II with negative results (Benson et al., 2014)

• Hypoxia-activated prodrug (TH-302): phase II

• PDAC is associated with local and systemic immunosuppression and inflammation that promote cancer cell evasion from the immune system and tumor progression • Role of immune checkpoints (CTLA-4, PD1/PDL-1) in T cell inactivation • Activity of anti-CTLA4 and anti-PD-1/PDL-1 potentially enhanced in tumors with low stroma content (Ozdemir et al., 2014) and/or dMMR status (D. T. Le, J. N. Uram, et al., 2015) • Vaccine-based strategies aiming to restore anti-tumoral immunity

• Metformin (action on mitochondria and mTOR pathway): observational data, phase II with negative results (Kordes et al., 2015), clinical trials ongoing

EP

• Small interfering RNA targeting KRASG12D: well tolerated in phase I (Zorde Khvalevsky et al., 2013), phase II ongoing (NCT01676259)

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Molecules

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• Adaptative cellular mechanisms to these metabolic constraints = potential therapeutic targets

• Cancer cells-stromal cells interactions, particularly with PSC, promotes tumor growth, invasion and metastatic dissemination, and resistance to chemotherapy

Immunity and inflammation

• GVAX (allogeneic PDAC cells transfected with GM-CSF gene, administered with low-dose cyclophosphamide): interesting activity in combination with CRS-207 (live-attenuated Listeria monocytogenes expressing mesothelin) in phase II (D. T. Le, A. Wang-Gillam, et al., 2015), phase IIb ongoing (NCT02004262) • Anti-CTLA-4 antibodies (ipilimumab): insufficient activity as monotherapy, potential efficacy in combination with vaccine-therapy using GVAX (Le et al., 2013) • Anti-PD-1/PDL-1 antibodies (nivolimumab, pembrolizumab): clinical trials ongoing in combination with chemotherapy (NCT02309177, NCT02331251), radiotherapy (NCT02305186, NCT02303990), or GVAX


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• Recombinant human hyaluronidase (PEGPH20, degrading hyaluronic acid of the ECM): phase II ongoing (NCT01959139, NCT01839487) with promising interim results (Hingorani et al., 2015), phase III in preparation

MA

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SC

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with encouraging results (Borad et al., 2015), combination phase Ib/II ongoing (NCT02047500), phase III ongoing (NCT01746979)

TE D (Cohen et al., 2015; Galluzzi et al., 2013)

• Anti-CD40 antibodies (CP-870,893): phase I (Beatty et al., 2013) • Anti-CCR2 antibodies (PF-04136309): phase Ib with encouraging results (Wang-Gillam et al., 2015), to be explored in phase II • Jak/Stat signaling pathway inhibitors (ruloxitinib): active in patients with elevated CRP levels in phase II (Hurwitz et al., 2014), phase III ongoing in this patient population (NCT02117479, NCT02119663) • Adoptive T-cell transfer (anti-mesothelin CAR): phase I ongoing (NCT01897415, NCT01583686) • Vaccines: phase I/II completed with a vaccine directed against mutated RAS (adjuvant setting) (Abou-Alfa et al., 2011; Weden et al., 2011); anti-telomerase tested in phase III with negative results (Middleton et al., 2014)

EP (Neuzillet, Tijeras-Raballand, et al., 2014)

AC C

Review in

(NCT02243371)

(Neesse et al., 2015)

(J. Wang et al., 2015)

ASN: asparagine synthase; ATP: adenosine triphosphate; CAR: chimeric antigen receptor; CCR2: C-C chemokine receptor type 2; CRP: C-reactive protein; CTLA-4: cytotoxic T-lymphocyte-associated protein 4; dMMR: deficient mismatch repair system; ECM: extra-cellular matrix; GM-CSF: granulocyte-macrophage colony-stimulating factor; Jak/Stat: Janus kinase/signal transducer and activator of transcription; LDH-A: lactate dehydrogenase type A; PKM2: pyruvate kinase isoform 2; PD/PDL: programmed death receptor/ligand; PDAC: pancreatic ductal adenocarcinoma; PSC: pancreatic stellate cell; RNA: ribonucleic acid; TGF-β: transforming growth factor-β

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Figure legends

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Figure 1. Summary of current hypotheses for pancreatic ductal adenocarcinoma development.

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Figure 2. Summary of paracrine immune signaling in pancreatic ductal adenocarcinoma microenvironment.

MA

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(1) The T-helper (Th) balance is turned toward the Th2 immune phenotype; (2) M2-type macrophages (M2) exert pro-tumoral activity mediated by secretion of immunosuppressive (e.g. IL10, TGF-β) and pro-inflammatory cytokines (e.g. IL-6, TNFα, IL-1), pro-angiogenic factors (e.g. VEGF, MMP-9, CXC chemokines), and tumor growth factors, and generate ROS with genotoxic activity; (3) CD4+CD25+ T-regulatory cells (T-reg) and Gr1+CD11b+ myeloid-derived suppressor cells (MDSC) are recruited suppress activity of other lymphocyte populations; (4) cytotoxic CD8+ T-lymphocytes (CTL), natural killer lymphocytes (NK) and dendritic cells (DC) functions are inhibited; (5) anti-tumoral Th1type responses and M1-type macrophages (M1) are inhibited; (6) Toll-like receptor (TLR) expression and activation are enhanced and induce tumor-promoting inflammation through NFκB.

Figure 3. Typical features of pancreatic ductal adenocarcinoma on imaging.

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Fig 3a. Multiple detector computed tomography (MDCT) at the arterial phase showing a hypoattenuating mass (arrow) with upstream parenchymal atrophy and main pancreatic duct dilatation.

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Fig 3b. Magnetic resonance imaging (MRI) showing a hyperintensity of the mass (arrow) at diffusionweighted sequence.

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Fig 3c. Magnetic resonance cholangiopancreatography (MRCP) sequence showing main pancreatic duct stenosis (arrow) with upstream chronic obstructive pancreatitis.

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References

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Abou-Alfa, G. K., Chapman, P. B., Feilchenfeldt, J., Brennan, M. F., Capanu, M., Gansukh, B., . . . O'Reilly, E. M. (2011). Targeting mutated K-ras in pancreatic adenocarcinoma using an adjuvant vaccine. Am J Clin Oncol, 34(3), 321-325. doi: 10.1097/COC.0b013e3181e84b1f Agustsson, T., D'Souza M, A., Nowak, G., & Isaksson, B. (2011). Mechanisms for skeletal muscle insulin resistance in patients with pancreatic ductal adenocarcinoma. Nutrition, 27(7-8), 796801. doi: S0899-9007(10)00303-5 [pii]

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Challenges and future directions in therapeutics for pancreatic ductal adenocarcinoma.

Nonintubated thoracoscopic surgery: state of the art and future directions.

Current management and future directions in metastatic pancreatic adenocarcinoma.

Perioperative Therapy of Oesophagogastric Adenocarcinoma: Mainstay and Future Directions.

State of the art of ICD programming: Lessons learned and future directions.

Dengue therapeutics, chemoprophylaxis, and allied tools: state of the art and future directions.

Renal denervation for treatment of cardiac arrhythmias: state of the art and future directions.

Mathematical Models for Immunology: Current State of the Art and Future Research Directions.

Radiofrequency ablation of pancreatic ductal adenocarcinoma: The past, the present and the future.

3D Biomaterial Microarrays for Regenerative Medicine: Current State-of-the-Art, Emerging Directions and Future Trends.

Minimally invasive aortic valve surgery: state of the art and future directions.

Trauma signature analysis: State of the art and evolving future directions.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Macrophages and pancreatic ductal adenocarcinoma.

Genetics and biology of pancreatic ductal adenocarcinoma.

Precision therapy for lymphoma--current state and future directions.

Novel approaches in the management of pancreatic ductal adenocarcinoma: potential promises for the future.

Interventional Nanotheranostics of Pancreatic Ductal Adenocarcinoma.

Lin28B facilitates the progression and metastasis of pancreatic ductal adenocarcinoma.

The many faces of wnt and pancreatic ductal adenocarcinoma oncogenesis.

Association of pancreatic Fatty infiltration with pancreatic ductal adenocarcinoma.

Imaging and targeted therapy of pancreatic ductal adenocarcinoma using the theranostic sodium iodide symporter (NIS) gene.

Management of the pregnant inflammatory bowel disease patient on anti-tumour necrosis factor: state of the art and future directions.

Application of bladder acellular matrix in urinary bladder regeneration: the state of the art and future directions.