Deciphering and Targeting Oncogenic Mutations and Pathways in Breast Cancer.

Breast Cancer

Deciphering and Targeting Oncogenic Mutations and Pathways in Breast Cancer } RFFY,c BORBALA SZE´ KELY,d LAJOS PUSZTAIe ´ G YO LIBERO SANTARPIA,a GIULIA BOTTAI,a CATHERINE M. KELLY,b BALAZS a

Oncology Experimental Therapeutics, Istituto di Ricovero e Cura a Carattere Scientifico Humanitas Clinical and Research Institute, Milan, Italy; bMater Misericordiae University Hospital, Dublin, Ireland; c2nd Department of Pediatrics and d2nd Department of Pathology, Semmelweis University, Budapest, Hungary; eYale Cancer Center, School of Medicine, Yale University, New Haven, Connecticut, USA Disclosures of potential conflicts of interest may be found at the end of this article.

Key Words. Breast cancer molecular subtypes x Mutation-genomic landscape x Oncogenic signaling pathways x Biomarkers of response to therapy x Tumor heterogeneity x Drug resistance x Potential therapeutic targets

ABSTRACT Advances in DNA and RNA sequencing revealed substantially greater genomic complexity in breast cancer than simple models of a few driver mutations would suggest. Only very few, recurrent mutations or copy-number variations in cancercausing genes have been identified. The two most common alterations in breast cancer are TP53 (affecting the majority of triple-negative breast cancers) and PIK3CA (affecting almost half of estrogen receptor-positive cancers) mutations, followed by a long tail of individually rare mutations affecting ,1%–20% of cases. Each cancer harbors from a few dozen to a few hundred potentially high-functional impact somatic variants, along with a much larger number of potentially

high-functional impact germline variants. It is likely that it is the combined effect of all genomic variations that drives the clinical behavior of a given cancer. Furthermore, entirely new classes of oncogenic events are being discovered in the noncoding areas of the genome and in noncoding RNA species driven by errors in RNA editing. In light of this complexity, it is not unexpected that, with the exception of HER2 amplification, no robust molecular predictors of benefit from targeted therapies have been identified. In this review, we summarize the current genomic portrait of breast cancer, focusing on genetic aberrations that are actively being targeted with investigational drugs. The Oncologist 2016;21:1063–1078

Implications for Practice: Next-generation sequencing is now widely available in the clinic, but interpretation of the results is challenging, and its impact on treatment selection is often limited. This work provides an overview of frequently encountered molecular abnormalities in breast cancer and discusses their potential therapeutic implications. This review emphasizes the importance of administering investigational targeted therapies, or off-label use of approved targeted drugs, in the context of a formal clinical trial or registry programs to facilitate learning about the clinical utility of tumor target profiling.

INTRODUCTION Breast cancer represents a complex and heterogeneous disease, encompassing several molecularly and clinically distinct entities that can be classified according to gene expression profiles and clinicopathological features [1, 2]. Hereditary disease accounts only for a small percentage of all breast tumors, whereas the majority of breast cancers are sporadic, resulting from the accumulation of acquired somatic alterations [3]. Recent advances in sequencing-based technologies have increased our understanding of genetic aberrations and dysregulated oncogenic pathways, involving growth signaling, stress response,

metabolism, and cell-to-cell communication, which affect breast cancer development and progression. These somatic alterations, together with the host response to cancer, determine the clinical course of the disease. A large number of often individually rare, but potentially functionally important, molecular alterations are encountered in unique combinations in every cancer. How to best exploit the genomic anatomy of cancer for therapeutic advantage remains an important unanswered challenge [4–7]. In this review, we provide a portrait of currently known genomic alterations and related pathways in breast cancer.

Correspondence: Libero Santarpia, M.D., Ph.D., Oncology Experimental Therapeutics, Istituto di Ricovero e Cura a Carattere Scientifico Humanitas Clinical and Research Institute, Via Manzoni 113, 20089 Rozzano, Milan, Italy. Telephone: 39 02-82245173; E-Mail: libero.santarpia@ humanitasresearch.it or [email protected]; or Lajos Pusztai, M.D., Ph.D., Breast Medical Oncology, Yale Cancer Center, Yale School of Medicine, 333 Cedar Street, P.O. Box 208032, New Haven, Connecticut 06520-8032, USA. Telephone: 203-737-6858; E-Mail: lajos.pusztai@yale. edu Received September 15, 2015; accepted for publication April 16, 2016; published Online First on July 6, 2016. ©AlphaMed Press 1083-7159/ 2016/$20.00/0 http://dx.doi.org/10.1634/theoncologist.2015-0369

The Oncologist 2016;21:1063–1078 www.TheOncologist.com

©AlphaMed Press 2016

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Targeting Oncogenic Pathways in Breast Cancer

Figure 1. Major cancer susceptibility loci identified in breast cancer. Each breast cancer susceptibility locus is mapped on their chromosomal location. The risk conferred by each specific allele is indicated by color. Chromosomes are not drawn to scale.

MATERIALS AND METHODS We conducted a review of the literature using PubMed,Web of Science, and Embase databases from 2000 to May 2016 using the search terms “breast cancer,” “genetic mutations,” “genetic alterations,” “biomarkers,” “response to therapy,” “tumor heterogeneity,” and “targeted therapies.” Additional studies were identified through the references listed in review publications. Recent emerging clinical findings presented at scientific meetings in the form of abstracts were also reviewed and incorporated. We note that the reported frequency for gene-level mutations depends on platform, sequencing depth, sample size, and definition of actionability, which vary from study to study. In this review, we use the frequency numbers from the largest studies that we could identify. We also searched clinicaltrials.gov to identify relevant ongoing phase II–III clinical trials evaluating targeted agents in patients with breast cancer.

The Genomic Landscape of Breast Cancers The genetic basis of susceptibility to breast cancer is related to multiple germline variations at different loci.These alleles have broadly variable frequencies and confer different levels of risk,

leading to a classification as high-, moderate-, and lowpenetrance alleles (Fig. 1). Even though the major rare highpenetrance genes, BRCA1 and BRCA2, which are involved in DNA repair processes, account for approximately 50% and 30% of familial breast cancers, respectively, further efforts are needed to unravel the impact of variants of unknown pathological significance or other susceptibility genes [3]. Sporadic breast cancers develop through the acquisition of novel malignant traits that confer a selective advantage to tumor cells. Although the accumulation of such genomic alterations is a requisite for the expansion and progression of a transformed cell population, recent insights that have emerged from comprehensive genomic studies have revealed additional heterogeneity in the genomic landscape of breast cancer [8–12]. The diversity of genetic pattern among breast tumors may explain the wide differences in biological features, clinical behavior, and response to therapies. The analysis of primary breast tumors has demonstrated that missense mutations are more common in estrogen receptor (ER)positive/luminal and human epidermal growth factor receptor 2 (HER2)-positive subtypes, whereas triple-negative breast cancers (TNBCs) are enriched for nonsense, frameshift, and

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Figure 2. Mutation spectrum in breast cancer subtypes. (A): Percentage of somatic mutations types in breast cancer overall and molecular subtypes according to COSMIC database. The ER-positive/luminal group includes luminal A and B subtypes. (B): Frequencies of the most commonly mutated cancer-related genes across breast cancer subtypes, according to the Cancer Genome Atlas [9]. Abbreviations: ER, estrogen receptor; HER2, human epidermal growth factor receptor 2.

complex mutations (Fig. 2A) [13]. Similarly, a higher rate of genomic rearrangements was found in HER2-positive breast cancers and TNBCs [14]. Breast cancer subtypes also differ regarding the pattern of copy-number alterations (CNAs) (Table 1) [11]. Novel data on genomic spectra, signaling pathways, and gene expression profiles are leading to the refinement of the molecular classification of breast cancer (Fig. 2B; Table 1) [8–12, 14–18].

Estrogen Receptor-Positive/Luminal Breast Cancers ER-positive/luminal breast cancers have the highest number of recurrent mutations (Fig. 2B; Table 1) [9, 14]. In luminal A cancers, the most frequently mutated gene is PIK3CA (45%), followed by GATA3 (14%), MAP3K1 (13%), TP53 (12%), CDH1 (9%), MLL3 (8%), MAP2K4 (7%), NCOR1 (5%), and RUNX1 (5%) [9]. The PIK3CA and GATA3 mutations appear mutually exclusive, with the much rarer mutations in AKT1 (4%) and FOXA1 (2%), respectively [9, 19]. Luminal B tumors have a lower frequency of PIK3CA mutations (29%) and a slightly

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higher frequency of GATA3 mutations (15%) (Fig. 2B; Table 1) [9]. Conversely, the frequency of TP53 mutations (29%) is higher in luminal B cancers and is associated with worse outcome [20].There is also higher frequency of ATM loss and CCND1, CDK4, CDK6, and MDM2 amplifications in luminal B cancers [9]. ER-positive cancers have relatively few recurrent CNAs compared with TNBCs (Table 1) [9, 10, 21, 22]. A common and potentially clinically relevant event in luminal B tumors is the amplification of fibroblast growth factor receptors (FGFRs) [9, 22].

HER2-Positive Breast Cancers A core set of genomic regions consistently affected by CNAs has been identified in HER2-positive breast cancers (Table 1) [23]. In addition to the common amplification at 17q12 (containing the HER2 oncogene), other recurrent CNAs included a large number of gains, losses, and amplifications [24]. A source of genomic heterogeneity within HER2-positive tumors is dependent on the size of the HER2 amplicon, because multiple ©AlphaMed Press 2016


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Table 1. Most common gene mutations and copy number alterations in different molecular subtypes of primary breast cancer Luminal A

Luminal B

HER2-positive

Triple negative

PIK3CA, GATA3, MAP3K1, TP53, CDH1, MLL3, MAP2K4, AKT1, FOXA1, CDH1, and RUNX1 —

PIK3CA, GATA3, and TP53

PIK3CA, and TP53

TP53 and PIK3CA

loss of ATM; amplification of CCND1, CDK4, CDK6, and MDM2

Amplification of multiple genes based on the HER2 amplicon size

loss of INPP4B, PTEN, and RB1; amplification of BRAF, CCNE1, EGFR, and KRAS

Copy number alterations Gains

1q and 16p

1q, 8q, 17q, and 20q

Losses

16q

1p, 3q, 8p, 13q, 16q, 17p, and 22q

1q12-q41, 3q, 6p12-p25, 7p12, 7q22-q36, 8q23.2-24.3, 10p12-p15, 12p, 17q25, and 21q22 3p, 3q12, 4p15-p32, 4q31-q35, 5q11-q31, 8p, 12q14-23, 13q, 14q22-q23, and 15q

Amplifications

8p11-12, 8q, 11q13-14, 12q13-14, 17q11-12, 17q21-24, and 20q13

7p22, 8p11-12, 8q11-24, 11q13-14, 17q23, 19q13, and 20q13

1p36.33-p36.32, 4q13.3, 5p15-p12, 8q23.3-q24.21, 11q13.5-q14.1, 14q11.1-q11.2, 17q23-q24, and 19q12 1p39, 1p36, 1p35, 1p32, 4p16.3, 7q21-q22, 7p22.3, 7q34, 7q36.1-q36.3, 8p23.3-p23.2, 8p11.23-p11.22, 9p21.3, 9q34.3, 10q26.3, 11q13.5, 11p15.5, 14q32.33, 15q11.2, 16p13.3, and 19p13.3 4q13.3, 8q23.3-q24.21, 11q13.5-q14.1, 14q11.1-q11.2, 17q12-q21, and 19q12

Gene mutations

Gene gains, losses and amplifications

—

Abbreviation: HER2, human epidermal growth factor receptor 2.

genes can be coamplified with HER2 [11]. Beyond the core of the amplicon, which includes at least HER2-C17orf37-GRB7 genes, coamplifications of other genes have been described [24, 25]. Particularly, the amplification of the HER2/TOP2A region has been correlated with the overexpression of several additional genes, such as CASC3, CDC6, RARA, and SMARCE1 [26]. It is worth noting that 20%–40% of HER2-positive cancers are TOP2A-deleted and that alterations in other growth factor receptors have been associated with the HER2 status, including EGFR, FGFR, and HER3 [9, 17, 27].

Triple-Negative Breast Cancers TNBCs represent a molecularly highly heterogeneous group with substantial transcriptional and DNA copy number variability [28]. These cancers have the highest frequency of TP53 disabling mutations (up to 80%) [9, 20]. Mutations and/or deletions in RB1 (retinoblastoma 1; 20%) and mutations in PIK3CA (9%), MLL3 (5%), and GATA3 (2%), as well as amplification of the CCNE1 gene (9%), occur at relatively low frequencies (Fig. 2B) [9]. Other repeatedly observed, but rather rare, genetic aberrations include mutations in ATR, COL6A3, FBXW7, MYO3A, PARK2, SYNE1/2, and USH2A genes [17, 29]. Despite the overall low prevalence of PIK3CA mutations, the activation of the phosphatidylinositol 3-kinase (PI3K) signaling has been found in specific TNBC subtypes, especially because of loss of PTEN and INPP4B, or PIK3R1 mutations [9, 30]. The genomic landscape of TNBCs is characterized by frequent and numerous DNA copy number losses and gains, suggesting a form of genomic instability (Table 1) [9, 11, 31–33]. Gains/ amplifications and overexpression of BRAF, CDK6, CDKN2A, CCNE1, E2F, EGFR, FGFR1, FGFR2, IGFR1, KIT, MET, MYC,

PDGFRA, and PIK3CA are also often encountered in TNBC [9, 32, 33].

Intratumor Genomic Heterogeneity and Implications for Treatment Tumor heterogeneity creates a potential framework to explain several clinical features of cancer [34–38]. Clinicians have long noticed variable tumor responses in different metastatic sites, suggesting variable treatment sensitivity in different locations. Within-tumor clonal heterogeneity and variable clonal composition of different metastatic lesions provide a simple explanation for this clinical phenomenon and is supported by recent results from tumor sequencing of metastatic sites and matching primary tumors. Clonal selection in response to therapy has also been demonstrated in several different cancer types and provides explanation for the development of treatment resistance over time [37, 39–41]. The evolutionary relatedness of primary tumors and multiple metastases from the same patient suggests multiple different ways that metastasis can arise (Fig. 3A) [42, 43]. Most metastatic lesions show large degrees of similarity to the primary tumor, indicating direct seeding from the primary tumor followed by modest genetic drift, whereas other lesions are more similar to one or more other metastatic lesions, suggesting that a metastatic site could give rise to further metastatic lesions (Fig. 3A) [42, 43]. Our understanding of how clinical drug resistance emerges during therapy has also evolved (Fig. 3B; Table 2) [44]. Some forms of resistance emerge through selection of intrinsically resistant subclones present in the cancer as a minority clone from the beginning (Fig. 3B) [12, 69, 73–75]. Other forms of resistance arise through de novo

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Figure 3. Biological and clinical consequences of tumor heterogeneity. (A): Tumor dissemination may occur at earlier stages of cancer progression, resulting in substantial divergences between primary and metastatic lesions. Alternatively, cell subpopulations in the primary tumor evolve by acquiring multiple genetic aberrations and aggressive phenotypes, ultimately leading to a late-stage metastatic dissemination. (B): Distinct subclones may harbor constitutive alterations that confer different drug sensitivity. Cancer therapy may trigger clonal evolution and increase intratumoral heterogeneity, allowing for the selection of cells with advantageous genetic aberrations. Further evolution of the resistant clone in response to therapy may lead to relapse after initial treatment response.

mutations that create new clones with drug resistance, not originally present in the cancer (Fig. 3B) [74, 76]. Several studies showed that appearance of new mutations, undetectable in the primary tumor, can arise after neoadjuvant chemotherapy (PTEN and TP53), HER2-targeted therapies (PIK3CA), and during endocrine therapy (ESR1) for metastatic breast cancer [50–54, 77–79]. Even though the relative proportion of drug-resistant subclones is generally higher in the post-treatment specimens, retreating cancers with drugs on which they previously progressed often continues to produce tumor response. Selectively removing a drug-sensitive subpopulation can lead to a temporary collapse of the entire


population, but eventual recovery happens through new subclones stepping in to provide the critical function for the entire population [80]. Considering cancer as a societyof neoplastic cells will allow for exploring new therapeutic strategies that could target between-cell communication or interrupt the complementary functions cells provide to each another.

The evolutionary relatedness of primary tumors and multiple metastases from the same patient suggests multiple different ways that metastasis can arise.



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Table 2. The most relevant and frequent gene mutations associated with therapy response and biological mechanisms in different breast cancer subtypes Gene symbol

Breast cancer subtypea

Therapeutic agentb

Molecular mechanism

References

BRCA1/2

Hereditary BRCA1-mutant breast cancer, TNBC

Dysfunction of DNA-damage response; regulation of the EMT

[45–49]

ESR1

ER-positive/luminal

DNA-damaging agents, PARPi, platinum compounds, spindle poisons Endocrine therapies

[50–54]

FGFR1/2 GATA3 HER2

ER-positive/luminal ER-positive/luminal HER2-positive breast cancer

Endocrine therapies Endocrine therapies Trastuzumab, lapatinib, pertuzumab

PIK3CA

ER-positive/luminal, HER2-positive breast cancer

PTEN

HER2-positive breast cancer ER-positive/luminal, TNBC

DNA damaging agents, everolimus, lapatinib, spindle poisons, tamoxifen, trastuzumab Everolimus, lapatinib, trastuzumab 5-fluorouracil, aromatase inhibitors, cyclophosphamide, DNA damaging agents, spindle poisons

Constitutive ligand-independent activation of the ER Activation of the PI3K pathway — Activation of downstream pathways; crosstalk with other growth factor receptors; intrinsic HER2 alterations Activation of the PI3K pathway; regulation of antitumor immunity; regulation of the EMT

TP53

Activation of the PI3K pathway; regulation of the EMT Dysfunction of DNA-damage response, Regulation of cell cycle and cell death, Regulation of the EMT

[55] [56] [57]

[58–67]

[58–64, 68, 69] [70–72]

a

Mutations mainly represented in the following breast cancer subtypes. Most relevant therapeutic agents. Abbreviations: EMT, epithelial-to-mesenchymal transition; ER, estrogen receptor; ESR1, estrogen receptor 1; HER2, human epidermal growth factor receptor 2; PARPi, poly(ADP-ribose) polymerase 1 inhibitors; PI3K, phosphatidylinositol 3-kinase; TNBC, triple-negative breast cancer.

b

Molecular Predictors of Response to Targeted Therapy in Breast Cancer Subtypes The fundamental premise behind “precision medicine” and tumor target profiling is that the targetable molecular abnormalities that are detected in a cancer will serve as predictors of treatment response to the appropriate targeted therapy. Several clinical trials suggest that the relationship between benefit from targeted therapies and molecular defects is more complex than hoped for. For example, the predictive value of the PI3K pathway activation (i.e., PIK3CA mutations and loss of PTEN) in HER2overexpressing tumors has been analyzed in different neoadjuvant clinical trials, generating variable results, leaving HER2 amplification as the only biomarker associated with antiHER2 therapies benefit [64–68, 81, 82]. It is noteworthy that recent data have demonstrated the presence of HER2 mutations in nonamplified HER2 tumors, potentially advancing the development of novel anti-HER2 drugs in this clinical setting [83]. ER-positive tumors are also highly dependent on the PI3K signaling for cell growth and survival [84]. Everolimus, an mTOR (mammalian target of rapamycin) inhibitor that interrupts the PI3K-mediated signaling, is approved in combination with exemestane for the treatment of advanced postmenopausal ER-positive/HER2-negative breast cancer patients, but results from the BOLERO-2 trial showed that PIK3CA mutations did not predict benefit from everolimus. However, the PI3K assessment was performed on primary tumors rather than metastatic biopsies [85]. Conversely, in the same trial, circulating ESR1 mutations showed a potential predictive efficacy of the addition of everolimus to standard endocrine therapy [54, 85]. The addition of theAKT inhibitor MK-2206 to anastrozole also did not confer significant benefit to ER-positive/HER2-negative patients with PIK3CA mutations [86]. However, preliminary results from

the phase III BELLE-2 trial indicated that only patients with circulating PIK3CA mutations benefited from a combination of the PI3K inhibitor BKM120 and fulvestrant [87]. Several larger phase II and III trials with a-specific PIK3CA inhibitors are still under way to further define the predictive function, and therapeutic target value, of PIK3CA mutations [88–90]. The CDK4/6 inhibitor PD-0332991 (palbociclib) was recently approved for the treatment of metastatic ER-positive breast cancer in combination with endocrine therapy, and several other CDK-targeted drugs are in clinical trials [91, 92]. Amplification of CDK4/6 and CCND1 and loss of the CDK4/6 inhibitors CDKN2A and CDKN2C are often detected in ERpositive cancers [9]. However, results from the PALOMA-1 trial showed that these genetic aberrations are not predictive for the efficacy of treatment with palbociclib [93]. For TNBC, there are no targeted therapies specifically approved [47]. However, recent data suggest a significant clinical activity of poly(ADP-ribose) polymerase (PARP) inhibitors in germline BRCA mutant breast cancer with dysfunctional homologous recombination DNA repair [47–49].

Potential New Therapeutic Targets and Treatment Strategies Derived From Genomic Analysis of Breast Cancer Despite very rare driver mutations that have been found in directly targetable genes (e.g., kinase genes), limiting the development of genotype targeted-therapies in breast cancer, several agents are currently used in the clinic, whereas others are not yet approved for clinical practice or are still under evaluation (Table 3). Furthermore, results derived from nextgeneration sequencing (NGS) studies have demonstrated

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Table 3. Targeted anticancer agents under investigation for breast cancer currently in phase II/III clinical trials Compound (company)

Direct target

Study name

Study design

Population

Arms

Study IDa

GDC-0810 (Genentech)

ER

HydranGea

Randomized, open label, phase II study

Postmenopausal women with advanced or metastatic ER-positive/ HER2-negative breast cancer

Experimental: GDC-0810 comparator: fulvestrant

NCT02569801

—

Open label, phase II study

Locally advanced or metastatic ER-positive/ HER2-negative breast cancer patients

Experimental: GDC-0810

NCT01823835

Randomized, open Early ER-positive/ label, phase III study HER2-negative breast cancer patients

Experimental: palbociclib 1 endocrine therapy

NCT02513394

Randomized, open label, neoadjuvant, phase II study

Experimental: palbociclib 1 letrozole

Palbociclib (Pfizer)

CDK4/6 PALLAS

PALLET

PENELOPE-B

LEE011 (Novartis)

LY2835219 (Eli Lilly)

Postmenopausal women with primary ER-positive/ HER2-negative breast cancer

Randomized, Primary ER-positive/ double-blind, phase HER2-negative breast III study cancer patients

Comparator: endocrine therapy NCT02296801

Comparator: letrozole Experimental: palbociclib

NCT01864746

Comparator: placebo

MONALEESA-2 Randomized, Postmenopausal women double-blind, phase with ER-positive/ III study HER2-negative advanced breast cancer

Experimental: LEE011 1 letrozole

MONALEESA-3 Randomized, Postmenopausal women double-blind, phase with ER-positive/ III study HER2-negative advanced breast cancer

Experimental: LEE011 1 fulvestrant NCT02422615

MONALEESA-7 Randomized, Premenopausal women double-blind, phase with ER-positive/ III study HER2-negative advanced breast cancer

Experimental: LEE011 1 tamoxifen

MONARCH 1


Experimental: LY2835219

NCT02102490

MONARCH 2

Randomized, Locally advanced or double-blind, phase metastatic ER-positive/ HER2-negative breast III study cancer patients

Experimental: LY2835219 1 fulvestrant

NCT02107703

ER-positive/ HER2-negative metastatic breast cancer patients

MONARCH 3

Randomized, Postmenopausal women double-blind, phase with advanced or III study metastatic ER-positive/ HER2-negative breast cancer neoMONARCH Randomized, open Postmenopausal women label, neoadjuvant, with ER-positive/ phase II study HER2-negative breast cancer

NCT01958021

Comparator: placebo 1 letrozole

Comparator: placebo 1 fulvestrant NCT02278120

Comparator: placebo 1 tamoxifen

Comparator: placebo 1 fulvestrant Experimental: LY2835219 1 anastrozole 1 letrozole

NCT02246621

Comparator:placebo1 anastrozole1 letrozole Experimental: LY2835219 1 anastrozole

NCT02441946

Experimental: LY2835219 Comparator: anastrozole

BKM120 (Novartis)

PI3K

NeoPHOEBE

Randomized, double-blind, neoadjuvant, phase II study

HER2-positive primary breast cancer patients

Experimental: BKM120 1 trastuzumab 1 paclitaxel

NCT01816594

Comparator: placebo 1 trastuzumab 1 paclitaxel

BELLE-2

Randomized, Locally advanced or double-blind, phase metastatic HER2-negative III study breast cancer patients

Experimental: BKM120 1 fulvestrant

BELLE-3

Randomized, double-blind, phase III study Randomized, double-blind, phase II/III study

Locally advanced or metastatic HER2-negative breast cancer patients HER2-negative locally advanced or metastatic breast cancer patients

Experimental: BKM120 1 fulvestrant


Postmenopausal women with hormone receptor-positive HER2-negative breast cancer

Experimental: BKM120 1 letrozole


ER-positive/ HER2-negative locally advanced or metastatic breast cancer patients

Experimental: BKM120 1 tamoxifen NCT02404844

BELLE-4 —

PIKTAM

NCT01610284

Comparator: placebo 1 fulvestrant NCT01633060

Comparator: placebo 1 fulvestrant Experimental: BKM120 1 paclitaxel NCT01572727 Comparator: placebo 1 paclitaxel NCT01923168


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Table 3. (continued) Compound (company)

Direct target

Study name —

Study design Open label, phase II study

Population Patients with metastatic TNBC

Arms Experimental: BKM120

Study IDa NCT01629615

—


TNBC patients with brain metastases

Experimental: BKM120 1 capecitabine

NCT02000882

PIKNIC


Advanced breast cancer patients

Experimental: BYL719

NCT02506556

—


Postmenopausal women with hormone receptors-positive/ HER2-negative breast cancer

Experimental: BYL719 1 letrozole

NCT01923168

NCT01790932

BYL719 (Novartis)



Everolimus (Novartis)


mTOR

PI3K/ mTOR

AZD5363 (AstraZeneca)

SOLAR-1

Randomized, Men and postmenopausal Experimental: BYL719 1 fulvestrant NCT02437318 double-blind, phase women with hormone Comparator: placebo 1 fulvestrant 3 study receptors-positive/ HER2-negative advanced breast cancer

SANDPIPER

Randomized, Postmenopausal women double-blind, phase with ER-positive/ 3 study HER2-negative, PIK3CA-mutant, locally advanced or metastatic breast cancer

AKT

NCT02340221

Comparator: placebo 1 fulvestrant

Postmenopausal women Experimental: GDC-0032 1 with ER-positive/ letrozole HER2-negative, early stage Comparator: placebo 1 letrozole breast cancer


—

Randomized, ER-positive/ Experimental: GDC-0941 1 NCT01437566 double-blind, phase HER2-negative advanced fulvestrant II study or metastatic breast cancer Comparator: placebo 1 fulvestrant patients

—

Randomized, Patients with locally single-blind, phase II recurrent or metastatic study breast cancer

Experimental: GDC-0941 1 paclitaxel

BOLERO-1

Randomized, Locally advanced or double-blind, phase metastatic HER2-positive III study breast cancer patients

Experimental: everolimus 1 paclitaxel 1 trastuzumab

—

STAKT —

MK2206 (Merck)

Experimental: GDC-0032 1 fulvestrant

LORELEI

—

BEZ235 (Novartis)


I-SPY 2

Randomized, ER-positive/ double-blind, phase HER2-negative advanced II study or metastatic breast cancer patients Randomized, open ER-positive/ label, phase II study HER2-negative metastatic breast cancer patients Randomized, ER-positive breast cancer double-blind, phase patients II study Randomized, Triple negative advanced double-blind, phase or metastatic breast cancer II study patients Randomized, open Invasive breast cancer label, phase II study patients

NCT02273973

NCT01740336

Comparator: placebo 1 paclitaxel NCT00876395

Comparator: placebo 1 paclitaxel 1 trastuzumab Experimental: GDC-0980 1 fulvestrant

NCT01437566

Comparator: placebo 1 fulvestrant Experimental: BEZ235

NCT01288092

Experimental: AZD5363

NCT02077569

Comparator: placebo Experimental: AZD5363 1 paclitaxel NCT02423603 Comparator: placebo 1 paclitaxel Experimental: MK-2206 with/ without trastuzumab

NCT01042379

Comparator: standard therapy

GSK2141795 (Novartis) GSK1120212 (Novartis)

MEK

—


Advanced breast cancer patients with a PIK3CA mutation, or an AKT mutation, and/or PTEN loss/mutation

—


Women with clinical stage Experimental: MK2206 1 II or III, PIK3CA mutant, anastrozole ER-positive/ HER2-negative invasive breast cancer

—


Advanced TNBC patients

Experimental: GSK2141795 1 GSK1120212

NCT01964924

—


Advanced TNBC patients

Experimental: GSK1120212 1 GSK2141795

NCT01964924

Experimental: MK2206

NCT01277757

NCT01776008

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Direct target

AZD6244 (AstraZeneca) Dovitinib (Novartis)

FGFR

Lucitanib (Clovis)

AZD4547 (AstraZeneca) Afatinib (Gilotrif)

EGFR

Gefitinib (AstraZeneca)

Arms

Study IDa

Randomized, Advanced breast cancer double-blind, phase patients II study

Experimental: AZD6244 1 fulvestrant

NCT01160718

—


Patients with stage IV HER2-negative inflammatory breast cancer

Experimental: dovitinib

NCT01262027

—


FGF aberrant metastatic breast cancer patients

Experimental: lucitanib

NCT02202746

—


Patients with FGFR1-amplified or nonamplified ER-positive metastatic breast cancer

Experimental: lucitanib

NCT02053636

—


Patients with FGFR1 or FGFR2 amplified tumors

Experimental: AZD4547

NCT01795768

—

Open label, neoadjuvant, phase II study

TNBC patients

Experimental: afatinib

NCT02511847

—


TNBC patients

Experimental: gefitinib

NCT01732276

—

Randomized, Patients with metastatic double-blind, phase breast cancer and II study hormone receptors-positive tumors

Experimental: gefitinib 1 tamoxifen NCT00229697

Randomized, ER-positive, double-blind, phase endocrine-resistant, II study metastatic breast cancer patients Open label, phase II Patients with stage IV study breast cancer

Experimental: erlotinib 1 fulvestrant Experimental: erlotinib 1 bevacizumab

NCT00054132

—

Open label, neoadjuvant, phase II study

Experimental: erlotinib 1 standard chemotherapy

NCT00491816

—

Randomized, single Triple negative breast blind, phase II study cancer patients

Experimental: cetuximab

NCT00232505

ICE


TNBC patients

Experimental: cetuximab 1 ixabepilone

—


Metastatic breast cancer patients

Experimental: cetuximab 1 irinotecan 1 carboplatin

Study name

Study design

—

—

Erlotinib (Genentech)

—

Cetuximab (BristolMyers Squibb)

Neratinib (Puma Biotechnology)

EGFR/ HER2

NALA

TNBC patients


Comparator: placebo 1 tamoxifen NCT00570258


Experimental: cetuximab 1 carboplatin NCT01097642

Comparator: ixabepilone

Randomized, open Metastatic HER2-positive label, phase III study breast cancer patients

Comparator: irinotecan 1 carboplatin Experimental: neratinib 1 capecitabine

NCT00248287

NCT01808573

Comparator: lapatinib 1 capecitabine NEFERTT

ExteNET —

—

RO4929097 (Roche)

Population


Advanced HER2-positive breast cancer patients

Randomized, Early stage HER2-positive double-blind, phase breast cancer patients III study Randomized, open label, neoadjuvant, phase II study

Advanced HER2-positive breast cancer patients

Experimental: neratinib 1 paclitaxel NCT00915018 Comparator: trastuzumab 1 paclitaxel Experimental: neratinib

NCT00878709

Comparator: placebo Experimental: neratinib 1 paclitaxel NCT01008150 Experimental: neratinib 1 paclitaxel 1 trastuzumab Comparator: paclitaxel 1 trastuzumab Experimental: neratinib

NCT01670877


Metastatic HER2-non amplified but HER2-mutant breast cancer patients

NOTCH —


Advanced, metastatic, or recurrent TNBC patients

—

Open label, phase I study

Patients with clinical stage Experimental: RO4929097 1 II-III TNBC paclitaxel 1 carboplatin

Experimental: neratinib 1 fulvestrant Experimental: RO4929097

NCT01151449 NCT01238133

(continued)




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Direct target

Study name

Study design

Population

Olaparib (AstraZeneca)

PARP

—


Patients with known BRCA Experimental: Olaparib mutations or TNBC

OlympiAD

Randomized, open Metastatic breast cancer label, phase III study patients with germline BRCA1/2 mutations

Experimental: Olaparib

Randomized, Patients with germline double-blind, phase BRCA1/2 mutations III study and high risk HER2 -negative primary breast cancer

Experimental: Olaparib

OlympiA

Iniparib (Sanofi)

BMN 673 (BioMarin)

Study IDa NCT00679783 NCT02000622

Comparator: physician’s choice chemotherapy NCT02032823

Comparator: placebo

ICEBERG 1


Advanced BRCA1 or BRCA2 Experimental: Olaparib associated breast cancer patients

SOLTI NEOPARP


Patients with stage II-IIIa TNBC

Experimental: Iniparib 1 paclitaxel

ABRAZO


Locally advanced and metastatic breast cancer patients with germline BRCA1/2 mutations

Experimental: BMN 673

NCT02034916

EMBRACA

Randomized, open Locally advanced and label, phase III study metastatic breast cancer patients with germline BRCA1/2 mutations Randomized, open Patients with stage IV label, phase II study BRCA-associated breast cancer

Experimental: BMN 673

NCT01945775

—

Veliparib (AbbVie)

Arms

NCT00494234

NCT01204125

Comparator: paclitaxel

Comparator: physician’s choice Experimental: Veliparib Experimental: Veliparib 1 carboplatin Experimental: Veliparib 1 cyclophospharmide

NCT01149083

—


—

Randomized, BRCA-associated double-blind, phase HER2-negative metastatic III study or locally advanced breast cancer patients

Experimental: Veliparib 1 carboplatin 1 paclitaxel

—


TNBC or hormone receptors-positive/ HER2-negative patients with known BRCA1/2 mutations

Experimental: Rucaparib 1 cisplatin NCT01074970 Comparator: cisplatin

Patients with germline BRCA1/2 mutations or TNBC

Experimental: LY2606368

TNBC patients

NCT01306032

Comparator: carboplatin

Rucaparib (Clovis)

LY2606368 (Eli Lilly)

CHEK1

—


CC-486 (Celgene)

DNMT

—


Entinostat (Syndax)

HDAC

—

Postmenopausal women with ER-positive/ HER2-negative metastatic breast cancer Randomized, Advanced ER-positive double-blind, phase breast cancer patients III study

NCT02163694

Comparator: placebo 1 carboplatin 1 paclitaxel

NCT02203513

Experimental: CC-486 1 fulvestrant NCT02374099 Comparator: fulvestrant Experimental: Entinostat 1 exemestane

NCT02115282

Comparator: placebo 1 exemestane

a

ClinicalTrials.gov identifier. Abbreviations: EGFR, epidermal growth factor receptor; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; TNBC, triple-negative breast cancer.

novel genetic aberrations and pathways dysregulation that may represent future therapeutic targets (Table 4). ESR1 mutations, leading to ligand-independent signaling, commonly arise under the selective pressure of endocrine therapy during the treatment of metastatic disease [53]. Several novel selective estrogen receptor degraders are in phase I (i.e., GDC0927, AZD9496, and RAD1901) and phase II (GDC0810) clinical trials that may turn out to be effective new therapies for these ESR1 mutant cancers (Table 3). Similar mutations conferring ligand-independent activity to HER2, in the absence

of HER2 amplification, were also reported, and several clinical trials are testing the efficacy of HER2 kinase inhibitors in these patients, who are currently considered “HER2 normal” by immunohistochemistry of fluorescence in situ hybridization assay. It is also increasingly recognized that PIK3CA inhibitors alone may be not sufficient to keep this important pathway inhibited because of redundancies, feedback loops, and simultaneous mutations in downstream pathway members. Indeed, concurrent perturbations of the PI3K/AKT/mTOR and the mitogenactivated protein kinase (MAPK) cascades are frequently

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Santarpia, Bottai, Kelly et al. observed in tumors. Several inhibitors of the Raf/MEK/ERK pathway are currently under clinical evaluation alone and in combination with PIK3CA/mTOR inhibitors (Table 3) [9, 58, 94, 95]. Furthermore, PI3K inhibition has been shown to boost the ERK pathway through the enhancement of the epidermal growth factor receptor (EGFR)/HER2/human epidermal growth factor receptor 3 (HER3) signaling, and HER3 may in turn promote the reactivation of the PI3K/AKT and MAPK pathways [96, 97].The modest activity of EGFR inhibitors in TNBC may also be due to crosstalk between signaling pathways and compensatory feedback loops [98–101]. Thus, combination trials with other drugs, including NOTCH and AXL inhibitors, warrant further clinical investigation [99–101]. Amplifications of FGFR1 and the activation of related pathways have been observed in TNBC [9]. Dovitinib and lucitanib showed antitumor activity, and clinical trials in fibroblast growth factor (FGF)-deregulated breast cancer are ongoing (Table 3). However, the therapeutic potential of FGFR inhibition in breast cancer requires further evaluation, in lightofuncertain clinical results, andthe keyrole of FGFRs in ordinary cell physiology [102]. An emerging success story in targeted therapies is the significant clinical activity of PARP inhibitors in germline BRCA mutant breast cancer [45, 103, 104]. Several trials showed single-agent activity in BRCA mutant breast cancers, and numerous trials, including a large adjuvant trial with olaparib, are under way (Table 3). APOBEC mutations can lead to instability and mutagenesis in breast cancer [105, 106]. The APOBEC3-mediated mutagenesis results in a specific pattern of nucleic acid changes, called APOBEC mutation signature, which has been found to be enriched in HER2overexpressed, basal-like, and luminal B subtypes.This evidence suggests that APOBECs could be crucial factors for targeted therapies aiming to block mechanisms producing widespread genomic alterations that drive tumor development, progression, and likely therapy resistance [105, 106]. Besides APOBEC enzymes, other mutational processes involving specific DNA repair pathways (i.e., mismatch repair and homologous recombination) lead to distinctive DNA damage [107, 108]. The identification of different genomic signatures arising from distinct defective pathways can provide a powerful means of revealing the somatic mutational basis of breast cancer [107, 108]. Recurrent mutations of TP53 make this gene a target of particular interest in TNBC. Considering that the direct targeting of TP53 is challenging, an alternative option may be to focus on activated signaling molecules downstream of TP53. For instance, CHEK1/2, ATM, and ATR are emerging as promising targets (Tables 3,4)[109].TP53-deficientcellsrelyonATR/CHEK1toarrestcell-cycle progression after DNA-damaging chemotherapy. Thus, the inhibition of CHEK1 and/or ATR in TP53-deficient cancers may lead to mitotic catastrophe and apoptosis [103, 104]. Several other TP53-associated kinases, such as polo-like kinases, aurora kinases, and, recently, the MPS1 kinase, have shown promising results in vitro and in vivo, suggesting their potential as suitable candidates for further development toward clinical studies (Table 4) [110].The TP53-associated pathway is also defective in an important quote of luminal B tumors because of TP53 mutations, amplification of MDM2, or ATM loss [9]. Several molecules that inhibit the ubiquitin ligase MDM2, or that disrupt the MDM2-TP53 interaction, are currently in early clinical


1073

evaluation in patients with advanced malignancies other than breast cancer [111]. Other proteins involved in the ubiquitinproteasome system, such as the tumor suppressor FBXW7 and the SKP1 ligase, have been found to be mutated or dysregulated in breast cancer (especially TNBC/basal-like), affecting a complex network of oncogenic processes, including cell differentiation and genomic stability [17, 112, 113]. In particular, loss of SKP1 has been shown to deregulate multiple targets, including EGFR and SRC tyrosine kinase in basal-like breast cancer [113]. An integrated genomic-proteomic approach has recently allowed the identification of novel phosphosite markers in PIK3CA- (i.e., EIF2AK4 and RPS6KA5) and TP53- (i.e., CHEK2, EEF2K, and MASTL) mutated tumors, and other important amplicon-associated phosphorylated kinases (i.e., CDK12, PAK1, PTK2, RIPK2 and TLK2) (Table 4) [113]. Overall, the analysis of activated pathways and the understanding of dysregulated signaling circuitries can provide novel insights into the functional consequences of somatic mutations and help identify novel therapeutic targets in breast cancer.

Overall, the analysis of activated pathways and the understanding of dysregulated signaling circuitries can provide novel insights into the functional consequences of somatic mutations and help identify novel therapeutic targets in breast cancer. Genes identified as oncogenic drivers in other tumor types may also represent potential therapeutic targets. For instance, tumors carrying activating mutations and amplification in BRAF, KRAS, and MET genes might be sensitive to specific inhibitors. Furthermore, other potential driver mutations in genes that are involved in chromatin remodeling and epigenetic regulation of gene expression have been reported in breast cancer [8, 9, 17, 114]. Patients with such mutations may be potentially enrolled in clinical trials using drugs that target epigenetic modifications, particularly DNA methyltransferase and histone deacetylase inhibitors (Tables 3, 4). Tumor cells dynamically interact with a heterogeneous microenvironment through a bidirectional signaling network. An outstanding ability of the immune system, especially adaptive immunity, is to recognize tumor-specific antigen. Different gene mutations generate new antigenic peptides that could be recognized by T lymphocytes and trigger antitumor immune responses [115].The identification of specific antigens resulting from mutations in driver genes, as well as chromosomal translocations and gene amplifications, could provide the rationale for the development of novel immunotherapeutic strategies for patients with breast cancers [116]. Remarkably, the majority of mutated antigens contributing to the immunogenicity of human tumors results from alterations in nonrecurrent genes, suggesting that infrequent mutations identified from large-scale sequencing studies may represent tumor-specific antigens and hold promise for use in cancer immunotherapy (Table 4) [115].

DISCUSSION Identifying the functional relevance of individually often-rare variants is a daunting challenge for laboratory investigators and clinical trialists. Studying the functional interaction between the multiple somatic alterations and inherited germline polymorphisms is going to be key for the formulation of a more ©AlphaMed Press 2016


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Table 4. Potential therapeutic gene targets in breast cancer Target gene

Pathways and biological processes

Therapeutic strategies

CCND1/CCNE1 MDM2 MPS1 AURKA/AURKAB EEF2K MASTL PLK1 RIPK2 TLK2 CHEK1/2 FBXW7 FBXO7 PARK2 UBE2C SKP1/2 ARID1B BAP1 IDH1/2 MLL3 NCOR1 SETD2 SMARCD1 APOBEC3 ATM/ATR CDK12 NOTCH1 FGFRs MET HER2 amplicon genes AXL BRAF HER3 EIF2AK4 RPS6KA5 KIT PAK1 PTK2 KRAS MYC NF1

Cell cycle, mitotic spindle assembly,TP53-associated pathway

Agents targeting cyclins-interacting proteins or protein-protein interaction; direct inhibition; promotion of selective degradation; immunotherapeutic approaches

Ubiquitin-proteasome system

Agents targeting the protein-protein interaction; direct inhibition; synthetic lethality approaches

Chromatin remodeling and epigenetic regulation of gene expression

Inhibition of DNA methyltransferases and histone deacetylases

DNA damage response, genomic stability

Direct inhibition

NOTCH pathway

Inhibition of g-secretase

FGF signaling MET signaling HER signaling, PI3K/AKT/mTOR, EGFR, and Raf/MEK/ ERK pathways

Direct inhibition Direct inhibition Agents targeting the protein-protein interaction or chromatin adaptors; direct inhibition; immunotherapeutic approaches

comprehensive model of carcinogenesis. The importance of interaction between the host immune system and the cancer is also increasingly recognized as an important determinant of clinical outcome. Somatic mutations, even without functional impact on biological pathways, can represent novel antigens that could activate adaptive immunity in the tumor microenvironment. A major challenge in the implementation of molecular target-directed therapeutic trials is the rarity and diversity of potentially actionable mutations in breast cancer, so that very large numbers of patients need to be screened to

find the 20–100 patients required for a typical phase II trial [117–119]. The presence of multiple potentially targetable alterations in most cancers suggests that individualized combination therapies may be the most effective strategy, which presents a fundamental challenge to any traditional clinical trial design and raises unprecedented regulatory issues. Furthermore, the repertoire ofbiologicallyandtherapeuticallyimportantmutationsmaychange during the evolution of a cancer or perhaps even from metastatic site to site. Although several studies have demonstrated the

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existence of “private” mutations (i.e., mutations unique to a particular tumor site while absent in other sites), the biological and therapeutic relevance of these observations is unknown. Molecular alterations are also being investigated as response predictors to targeted therapies. However, no single gene alterations emerged as clinically useful predictors to any therapy (other than HER2 amplification for HER2-targeted therapies). There is only weak, or no, association between PIK3CA mutations and response to mTOR or PI3K inhibitors in clinical trials. Similarly, amplifications in the CDK genes were not predictive of benefit from CDK4/6 inhibitors, and FGFR inhibitors also had only modest activity in FGFR1amplified tumors. Conversely, activating mutations in HER2 emerged as a potential new marker and target to extend the use of anti-HER2 kinase inhibitor therapy. Several ongoing clinical trials are examining the therapeutic target value of this abnormality. ESR1 mutations that render the receptor constitutively active are also frequently encountered in metastatic biopsies, whereas this mutation is very rare in primary cancers. Efforts are under way to develop therapies that target the mutant ER. Some, but not all, of the somatic mutations present in a cancer can also be detected as circulating-free tumor DNA. It is hoped that sequencing of circulating tumor DNA that can easily be obtained from blood may provide a tool to monitor risk of recurrence after potentially curative therapy, detect early recurrence, and monitor response to therapy [120–124]. Besides the importance of variants in protein-coding regions, the majority of the alterations occur in noncoding portions of the genome [125]. Different noncoding sequence variants, ranging from single-nucleotide variants to small insertions and deletions, to large structural variants have been demonstrated in human cancer [125–127]. Somatic variations can lead to gain of transcription factor-binding sites responsible of tumorigenesis. Fusion events because of genomic rearrangements, variations in noncoding RNAs and their binding sites, and variants in pseudogenes modulating gene expression have been linked to cancer [125]. Like somatic variants, germline noncoding affects gene expression through several mechanisms (e.g., promoter mutations, single-nucleotide polymorphisms in enhancers and noncoding RNAs and their binding sites, and variants in introns) [125]. Recently, recurrent mutations have been found in the promoter of TBC1D12 and WDR74, as well as in the long noncoding RNAs MALAT1 and NEAT1 in breast cancer [108]. However, the identification of noncoding drivers is complex

and requires additional studies. Overall, it is evident that cancer results from a more complex interplay of inherited germline and acquired somatic variants, including also noncoding region alterations. As for breast cancer, which seems to harbor more alterations in the noncoding regions compared with other tumors, the identification of noncoding driver mutations/alterations remains crucial to enable therapeutic approaches that target the specific linked proteins. The constant evolution of technologies allows the ever-increasing identification of novel mutated cancer genes (e.g., FOXP1, MED23, MLLT4, XBP1, and ZFP36L1) [108]. This ongoing update of cancer genes and noncoding regions’ alterations progresses toward a comprehensive understanding of the source and consequences of somatic mutations, ultimately enabling the development of novel targeted therapies for breast cancer.

CONCLUSION Recent insights from comprehensive genomic characterizations of cancer revealed large-scale heterogeneity in the genomic landscape of breast cancers. The diversity of genomic aberrations and the resulting dysregulation of a broad range of biological pathways help to explain the varied clinical behavior of breast tumors. Better understanding the biological effects of these aberrations remains a major focus of research and may pave the way for rational combination targeted therapies.

ACKNOWLEDGMENTS This work was supported by Associazione Italiana per la Ricerca sul Cancro Grant 6251 to L.S.; Fondazione Italiana per la Ricerca sul Cancro Fellowship 18328 to G.B.; and the Breast Cancer Research Foundation to L.P.

AUTHOR CONTRIBUTIONS Conception/Design: Libero Santarpia, Lajos Pusztai Provision of study material or patients: Libero Santarpia, Giulia Bottai, Catherine M. Kelly, Balázs Gy} orffy, Borbala Székely, Lajos Pusztai Collection and/or assembly of data: Libero Santarpia, Giulia Bottai, Catherine M. Kelly, Balázs Gy} orffy, Lajos Pusztai Data analysis and interpretation: Libero Santarpia, Giulia Bottai, Catherine M. ´ Kelly, Balázs Gy} orffy, Borbala Szekely, Lajos Pusztai Manuscript writing: Libero Santarpia, Lajos Pusztai Final approval of manuscript: Libero Santarpia, Giulia Bottai, Catherine M. ´ Kelly, Balázs Gy} orffy, Borbala Szekely, Lajos Pusztai

DISCLOSURES The authors indicated no financial relationships.

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For Further Reading: Juliann Chmielecki, Jeffrey S. Ross, Kai Wang et al. Oncogenic Alterations in ERBB2/HER2 Represent Potential Therapeutic Targets Across Tumors From Diverse Anatomic Sites of Origin. The Oncologist 2015;20:7–12. Implications for Practice: Tumors with amplification or overexpression of ERBB2/HER2 have a high likelihood of being sensitive to ERBB2/HER2 inhibitors, based on evidence from published studies. Current clinical practice investigates amplification or overexpression of ERBB2/HER2 in breast, gastric, and gastroesophageal cancers. However, recent studies suggest that mutations can also activate this gene, and these alterations may be similarly sensitive to ERBB2/HER2 inhibitors. Our data identified activation of ERBB2/HER2 (either amplification or activating mutation) in 27 different tumor types. Consequently, more comprehensive molecular profiling of multiple tumor types has the potential to identify additional patients who may derive clinical benefit from ERBB2/HER2 inhibitors.

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CXCR4 in breast cancer: oncogenic role and therapeutic targeting.

Deciphering oncogenic drivers: from single genes to integrated pathways.

Co-targeting estrogen receptor and HER2 pathways in breast cancer.

Combined phosphoproteomics and bioinformatics strategy in deciphering drug resistant related pathways in triple negative breast cancer.

Targeting oncogenic vulnerabilities in triple negative breast cancer: biological bases and ongoing clinical studies.

Activation of diverse signalling pathways by oncogenic PIK3CA mutations.

Targeting cancer stem cells and signaling pathways by phytochemicals: Novel approach for breast cancer therapy.

Targeting Oncogenic Mutant p53 for Cancer Therapy.

KLK6-regulated miRNA networks activate oncogenic pathways in breast cancer subtypes.

Comparative epigenetic analyses reveal distinct patterns of oncogenic pathways activation in breast cancer subtypes.

Deciphering hepatocellular responses to metabolic and oncogenic stress.

Defining and Targeting the Oncogenic Drivers of Neuroendocrine Prostate Cancer.

Analysis of PIK3CA Mutations and Activation Pathways in Triple Negative Breast Cancer.

AHNAK suppresses tumour proliferation and invasion by targeting multiple pathways in triple-negative breast cancer.

Targeting the Twist and Wnt signaling pathways in metastatic breast cancer.

Prostate cancer stem cells: deciphering the origins and pathways involved in prostate tumorigenesis and aggression.

MDM2 antagonists synergize broadly and robustly with compounds targeting fundamental oncogenic signaling pathways.

2 mutations?

Oncogenic PIK3CA mutations reprogram glutamine metabolism in colorectal cancer.

Molecular Pathways: Isocitrate Dehydrogenase Mutations in Cancer.

The oncogenic potential of human cytomegalovirus and breast cancer.

Molecular targeting of obesity pathways in cancer.

Targeting RTK Signaling Pathways in Cancer.

Targeting apoptosis pathways in cancer with alantolactone and isoalantolactone.