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Tumor heterogeneity and personalized cancer medicine: are we being outnumbered? Geert A Cirkel1, Christa G Gadellaa-van Hooijdonk1, Marco J Koudijs1, Stefan M Willems2 & Emile E Voest*,3

ABSTRACT: Tumor heterogeneity is regarded as a major obstacle to successful personalized cancer medicine. The lack of reliable response assays reflective of in vivo tumor heterogeneity and associated resistance mechanisms hampers identification of reliable biomarkers. By contrast, oncogene addiction and paracrine signaling enable systemic responses despite tumor heterogeneity. This strengthens researchers in their efforts towards personalized cancer medicine. Given the fact that tumor heterogeneity is an integral part of cancer evolution, diagnostic tools need to be developed in order to better understand the dynamics within a tumor. Ultra-deep sequencing may reveal future resistant clones within a (liquid) tumor biopsy. On-treatment biopsies may provide insight into intrinsic or acquired drug resistance. Subsequently, upfront combinatorial treatment or sequential therapy strategies may forestall drug resistance and improve patient outcome. Finally, innovative response assays, such as organoid cultures or patient-derived tumor xenografts, provide an extra dimension to correlate molecular profiles with drug efficacy and control cancer growth. Background Owing to the lack of reliable biomarkers that can predict a favorable treatment outcome, the majority of patients are currently treated based on results from large prospective randomized trials in the general population of a specific tumor type. As a result, a considerable number of patients are exposed to often highly toxic treatment, with only a small subset of these patients having benefit. Global efforts towards treating cancer patients based on analysis of their individual genetic, epigenetic or proteomic tumor profile have brought hope and optimism among patients and physicians. Theoretically, this approach should result in more rationalized treatment strategies for individual patients. Believers in the concept of personalized cancer medicine (PCM) predict a shift towards molecular profile-based treatment that will allow a better selection of patients for a specific treatment within the upcoming decades. Critics of the concept of PCM bring tumor heterogeneity into contention as the main reason why this concept will fail. In this article, we will focus on tumor heterogeneity as a determinant of treatment outcome.

KEYWORDS 

• evolution • heterogeneity • innovation • metastases • personalized cancer medicine • selection • tumor

Tumor heterogeneity Tumor heterogeneity refers to variations at the level of the genome, epigenome, proteome, cell and tissue behavior found within an individual tumor, its metastases and associated stromal components. Darwinian selection caused by random variations of genetic traits has resulted in an overwhelmingly heterogeneous variety of species thriving in their specific habitat worldwide. This Department of Medical Oncology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands Department of Pathology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands 3 Department of Medical Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands *Author for correspondence: Tel.: +31 020 512 9111; [email protected] 1 2

10.2217/FON.13.214 © 2014 Future Medicine Ltd

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Perspective  Cirkel, Gadellaa-van Hooijdonk, Koudijs, Willems & Voest mechanism ensuring survival and offspring from the fittest has its downside in cancer progression. Disruption of cellular mechanisms protecting genomic integrity results in instability and consequently phenotypic diversity [1,2] . As a result, extensive heterogeneity is present within a single malignancy. In tumorigenesis, a continuous selection of cancer cells best equipped to survive in their specific microenvironment and escape endogenous antitumor surveillance occurs. Systemic anticancer treatment further selects cellular phenotypes highly specialized to survive toxic environments ultimately leading to therapy refractory disease. This is consistent with observations that chemotherapy increases genomic instability and thereby increases drug resistance [3–6] . It is commonly accepted that tumors originate from a single cell. Cancer is initiated and subsequently evolves by inactivating tumor suppressor genes and acquiring multiple mutations that activate oncogenic pathways [7] . These ‘driver mutations’ often occur among thousands of other somatic mutations in vivo. These so called ‘passenger mutations’ are unlikely to influence the cell’s phenotype, but are reflective of increased genomic instability or mismatch repair deficiency, and lead to extensive tumor heterogeneity at both the genomic and nucleotide level. Recent papers have provided a glimpse of the inter- and intra-individual heterogeneity of cancer [8–13] . In general, a considerable amount of somatic nonsynonymous mutations are not commonly shared between primary tumors and associated metastases. For instance, our group evaluated samples of primary and metastatic tumor sites of 21 colorectal cancer patients [9,14] . In line with other reports, significant genetic differences were observed between primary and metastatic sites. In addition, complex structural genomic rearrangements and chromothripsis clusters were observed within all samples. Several known cancer-related genes were shown to be affected by these structural rearrangements [14] . Gerlinger et al. reported data from two clear cell renal cell carcinoma patients biopsied at multiple primary and metastatic sites [11] . Approximately two-thirds of nonsynonymous mutations were not commonly shared, indicating that a single tumor biopsy does not reflect the complete somatic mutational make-up of a tumor. Yachida et al. collected primary tumors and associated metastases of seven stage IV pancreatic cancer patients via rapid postmortem autopsy [8] .

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Sequencing analysis of separate sections of the primary tumors, as well as the metastases, revealed a genetic evolutionary path of pancreatic cancer. In total, 64% (range: 48–83%) of all mutations identified were present in all samples. These mutations were called ‘founder’ mutations. Acquisition of additional mutations resulted in seeding to distant sites. The other 36% (range: 17–52%) of all mutations identified were present in one or more subclones or metastasis. These were called ‘progressor’ mutations. Of each metastasis, an original, nonmetastatic, founder clone could be identified within the primary tumor. These data are illustrative for genetic heterogeneity in advanced pancreatic cancer, as well as of how an individual metastasis evolves from a distinct subclone within the primary tumor, and how tumor heterogeneity is reflected within the primary tumor. To further complicate matters, extensive epigenetic tumor heterogeneity has been observed in several tumor cell populations leading to different phenotypes [15,16] . In general, malignant cells are hypomethylated compared with nonmalignant cells, leading to potential upregulation of a broad range of genes. Although still controversial, tumor cells with a ‘stem cell’ or ‘tumor-initiating’ phenotype seem to be more drug resistant and crucial for tumor evolution in some but not all cases [17] . It has been proposed that, in analogy with epigenetically regulated phenotypic diversity of homogenous normal cells, epigenetic regulation plays a major role in cancer ‘stem’ or ‘drug-resistant’ cell differentiation [18] . In a majority of cases, development of drug resistance after an initial response is unlikely explained by genetic changes, but rather by epigenetic changes resulting in an altered expression profile [19] . Reversible epigenetic variations within the cancer genome appear to play crucial roles in tumor cell differentiation and survival [20] . A molecular profile obtained from a population of cells within a tumor biopsy specimen provides a snapshot of a continuous evolutionary process. Microenvironmental circumstances may change in time. Antineoplastic treatment, disease progression, clonal competition, metabolic changes or migration to a distant site will cause a different and dynamic selection process at a different time point selecting other clones to survive and expand. Therefore, a molecular profile should always be interpreted within its spatial and temporal context. Sequential pre-,

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Tumor heterogeneity & personalized cancer medicine: are we being outnumbered?  on- and post-treatment tumor biopsies (and, perhaps in the future, circulating markers) are of paramount importance to better understand tumor evolution and mechanisms of drug resistance during the course of treatment. Why tumor heterogeneity is considered to be a problem Tumor heterogeneity is often regarded as the major obstacle for successful implementation of PCM for a number of reasons. First, taking a biopsy from a single lesion may not reflect the mutational profile of that entire metastasis, nor may it reflect the genetic make-up of other metastases in that same patient. For example, in our study of 21 colorectal cancers, three patients showed dissimilarity in KRAS status [9] . In addition, several structural rearrangements affecting known cancer-related genes were also exclusively present in the primary tumor or a metastasis [14] . Heterogeneity within the primary tumor provides an explanation for discordance in most cases [21,22] . As a consequence, patients may not be treated with anti-EGF receptor (EGFR) antibodies simply because of the sampling site. A meta-analysis of 21 reports on KRAS mutation concordance between primary and metastatic colorectal tumor tissue was performed by Baas et al. [23] . In general, discordance in KRAS status is observed in less than 10%. Interestingly, discordance with the primary tumor appeared to be more frequent in lymph node metastases (16%). Possible explanations for discordance include occurrence of KRAS mutations after metastasizing, lack of sufficient sensitivity or specificity of KRAS testing, (chemotherapy induced) low tumor cell percentage in tumor samples, or tumor heterogeneity. After considering pros and cons of each explanation, Baas et al., in our opinion, justly conclude that tumor heterogeneity is the most plausible explanation for discordant cases observed. Unfortunately, obtaining multiple biopsies from multiple sites in an individual patient is usually not feasible due to practical and ethical considerations, and the oncologist will have to rely on a partial reflection of the total molecular make-up of a malignancy. Second, mutational data are considered less relevant if not combined with data from other potential levels of heterogeneity, such as epigenetic up- or down-regulation or structural variations of the genome. Finally, DNA extracted from a single biopsy consists of a mixture

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of stromal, visceral and different tumor cell clones diluting aberrations, hampering the reliable detection of relevant somatic variants with potential clinical implications. The impact of tumor heterogeneity on translational cancer research is not new nor a surprise. Decades of biomarker research has generated over 150,000 articles claiming thousands of identified biomarkers. The estimated number of biomarkers implemented in daily clinical practice is less than 100 [24] . Tumor heterogeneity might very well, at least partly, explain this high failure rate. Promising preclinical research is mostly based on homogenous artificial tumor models, whereas correlative clinical studies are often based on data from a single biopsy and clinical outcome. In both settings, tumor heterogeneity is not adequately reflected potentially leading to false positive results. Treatment successes despite tumor heterogeneity Regardless of the aforementioned complexity of the biology of cancer, important advances in the treatment of cancer have been made. In spite of tumor heterogeneity, sometimes startling tumor responses are observed in patients treated with systemic anticancer treatment. Examples include the BRAF inhibitor vemurafenib in BRAF-mutant (V600E) unresectable or metastatic melanoma and crizotinib in EML4-ALK rearranged non-small-cell lung cancer (NSCLC), with response rates of approximately 81 and 55%, respectively [25,26] . These spectacular results, despite known tumor heterogeneity, can be explained by a phenomenon often referred to as ‘oncogene addiction’ or the ‘Achilles heel of Cancer’ [27,28] . Oncogene addiction refers to the dependence of a malignancy on a single oncogenic pathway or protein throughout its evolutionary course. As a consequence, the oncogenic aberration should be present in the ‘trunk’ of the clonal evolutionary tree. With regard to the oncogene addiction phenomenon, actionable mutations occurring early in tumorigenesis and persisting throughout evolution should result in consistent and significant overall responses. Various degrees of heterogeneity have been observed within treatment-naive melanomas [28] . BRAF (V600E) is considered to be a oncogenic ‘driver’ mutation in melanoma, which would result in addiction to the BRAF (V600E) mutation. Recently, Willmott et al. evaluated 58 melanoma samples stained with

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Perspective  Cirkel, Gadellaa-van Hooijdonk, Koudijs, Willems & Voest the monoclonal mouse antibody VE1, which is highly specific and sensitive for cells harboring a BRAF (V600E) mutation [29,30] . Indeed, in 71% of samples, all tumor cells stained positive, whereas only 12% of samples displayed less than 80% of tumor cells positive. The strong efficacy of drugs specifically targeting oncogenic germline mutations, such as BRCA or tuberous sclerosis complex (TSC), in patients harboring these aberrations is further supportive of the principle of oncogene addiction [31,32] . Unfortunately, known early driver mutations do not always occur early in tumorigenesis and may occur at a later stage in a clonal branch [10] . Tumor heterogeneity is not a new phenomenon. Tumor heterogeneity is something we already cope with in daily practice. Intratumor heterogeneity both in terms of histological features, as well as the (immunohistochemical) expression of predictive tumor markers is frequently observed in surgically resected breast tumors (Figure 1) . For instance, approximately 70% of all breast cancers are estrogen receptor (ER) positive. However, according to the American Society of Clinical Oncology guideline recommendations, a tumor sample is considered ER positive in the presence of at least 1% positive tumor nuclei [33] . Endocrine therapy is prescribed to these patients with significant clinical benefit, which seems paradoxical to the strong heterogeneity in ER expression often observed [34] . A possible explanation is provided by paracrine signaling observed between cancer cells. In the case of breast cancer cells, paracrine signaling by ER-positive cells increases the proportion of cells with a ‘drug-resistant’ or ‘cancer stem celllike’ phenotype through a paracrine FGF/FGF receptor/Tbx3 signaling pathway [35] . A similar paracrine mechanism has been observed within glioblastoma multiforme (GBM). Mutant EGFR cells activate wild-type EGFR neighboring cells by a cytokine-mediated paracrine mechanism. It was found that EGFR-mutant GBM cells release IL-6 or leukemia inhibitory factor. These factors stimulate neighboring wild-type GBM cells and maintain tumor heterogeneity through gp130 receptor signaling [36] . These examples illustrate that targeting a small subpopulation of cells may indeed have an impact on a larger proportion of tumor cells through paracrine or endocrine mechanisms. This bystander effect could, at least, partly explain the relative high incidence of overall ‘systemic’ responses observed in daily practice and the low incidence of mixed responses.

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Third, there are types of cancer, such as testicular cancer or hematological malignancies, which can be cured by systemic antineoplastic treatment [37] . To our knowledge, no extensive analysis of intratumor heterogeneity in testicular cancer has been reported yet. However, analysis of genomic copy number alterations, expression patterns and methylation profiles have provided insight into a range of aberrations [38,39] . Since these aberrations result from genomic instability, the presence of intratumor heterogeneity, especially in advanced disease, is highly likely. An early age of onset seems to be a common feature of the current curable cancers. The current body of evidence at least suggests that tumor heterogeneity and molecular profiles within a younger patient differ distinctly from the older population, thereby possibly explaining beneficial treatment outcome for this group [17,40–41] . Normal stem cell properties change with age [40] . During oncogenesis, different oncogenic mutational spectra occur at different ages (reviewed in [17]) . Malignancies diagnosed at childhood or adolescence have less aberrations compared with the late-onset malignancies [41] . Although rather speculative, it might be that a more limited mutational spectrum with less ‘passenger mutations’ mediates a more rigid vulnerability to antineoplastic treatment leading to a possible final cure. Consequently, a broad mutational spectrum including a wide variety of ‘passenger mutations’ enhances the plasticity of a malignancy to deal with environmental stress and survive potentially toxic exposure to antineoplastic therapy. An initial response is observed in most malignancies when the right oncogene or ‘Achilles heel’ is targeted. Whether this initial response leads to a final cure might depend on the number of passenger mutations and associated chance on clonal survival. In summary, at first glance, tumor heterogeneity seems to be a major obstacle in cancer treatment. At closer look, phenomena such as paracrine signaling and maintenance of oncogenic driver mutations throughout tumor evolution allow significant treatment efficacy and provide a rationale to persist in efforts towards PCM. Impact of tumor heterogeneity on drug resistance Tumor heterogeneity does not only have an effect on the selection of patients for upfront treatment. Treatment itself is a major perturbation of the microcosmos of a tumor. It has

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Tumor heterogeneity & personalized cancer medicine: are we being outnumbered? 

HEE H

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ER

ER

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HER2

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Figure 1. Intratumor heterogeneity in breast cancer affects the expression of predictive biomarkers. Invasive ductal carcinoma consisting of at least two subclones (represented by the purple and green dot). (A) Tumor part consisting of poorly differentiated strands and ducts of atypical epithelial cells infiltrating desmoplastic stroma. The tumor cells are negative for ER, but show strong complete membraneous staining in >30% for HER2, corresponding with high-level amplification of HER2 in the CISH. (B) Tumor part consisting of well-differentiated ducts lined by epithelial cells with minimal nuclear atypia. The tumor cells strongly express ER, but are only cytoplasmic positive for HER without membraneous staining. CISH shows two copies of HER2 in the tumor cells (no amplification). CISH: Chromogenic in situ hybridization; ER: Estrogen receptor; HE: Hematoxylin and eosin staining.

impact on normal tissues, microenvironment, and drug-sensitive tumor clones. With the ability of tumors to rapidly adapt to treatment, our understanding of this process may significantly contribute to improving treatment outcome. Tumor heterogeneity has been shown to affect the efficacy of anticancer treatment. At a cellular level, patients with NSCLC consisting of a heterogeneous population of EGFR-mutated and nonmutated cells showed a reduced response to the EGFR inhibitor gefitinib compared with patients whose tumors contained EGFR-mutated cells only [42] . The level of genetic instability and thereby level of heterogeneity has been directly correlated with time to relapse and drug resistance in several malignancies [43,44] . For instance, breast cancer patients with relatively low levels of genetic instability in their tumor (luminal A)

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have a better prognosis and lower relapse rate when compared with tumors with relatively high levels of instability (e.g., basal-like) [44] . A similar difference is observed in chronic-phase chronic myeloid leukemia (CML) versus blastphase CML [45] . Chronic-phase CML is characterized by a BCR-ABL translocation and a low level of genetic instability. A durable response can be achieved on imatinib in these cases. By contrast, in blast-phase CML, a high level of genetic instability and thereby heterogeneity is present. As a consequence, duration of response is substantially reduced. Phenotypically distinct subpopulations of cells have been identified in several tumor cell lines derived from human primary tumors. Recent studies suggest that tumor cells stochastically change between phenotypically different

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Perspective  Cirkel, Gadellaa-van Hooijdonk, Koudijs, Willems & Voest states. Gupta et al. analyzed the dynamics of stem-like, luminal and basal subpopulations in breast cancer cell lines [20] . It was found that the likelihood of a cell with a specific phenotype to change to another phenotype results in fixed proportions of subpopulations, including a population with cells expressing a stem-like phenotype, within a malignancy. Expansion of a single subpopulation of cancer cells in fixed conditions resulted in rapid return to equilibrium of proportions within 6 days. Chemotherapy increased the relative proportion of stem-like cells who subsequently gave rise to an increased proportion of basal cells. It was also found that a stem-like subpopulation can arise de novo from a nonstem-like population, implicating that a future therapy that targets stem cells solely will probably not provide a final cure [19,20] . Several alternative extrinsic and intrinsic pathways of resistance have been identified [19,46–52] . Here, we will highlight two examples: programmed survival responses and clonal outgrowth (Figure 2) . Programmed survival responses The ability of a tumor cell to withstand a certain kind of treatment is known as resistance. Selective treatment pressure may also activate survival pathways. These compensatory survival programs may differ from tissue to tissue. A detailed analysis of these survival pathways may lead to novel combinatorial approaches. For instance, the lack of efficacy of BRAF inhibitors on BRAF-mutated colorectal cancer compared with BRAF-mutant melanomas puzzled researchers and prompted extensive pathway analysis into these tumors. It was found that BRAF inhibition of BRAF-mutant colorectal cancer causes a strong activation of the EGFR signaling pathway, resulting in resistance to BRAF inhibition. Coadministration of a BRAF and EGFR inhibitor abolished resistance, resulting in marked tumor response in vitro and in vivo [49,53] . Clinical trials are now underway to further validate this concept in patients. Validation of this finding will provide a conceptual framework for future combinatorial treatment approaches. Systemic treatment may trigger a programmed survival response either systemically, within the tumor’s microenvironment or within the tumor cell. In the majority of cases, development of resistance cannot be explained by genetic changes [19,54] . Epigenetic modulation provides an often

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rapid survival response to therapy-induced stress. Several recent papers have reported on nonmutational mechanisms of resistance and associated treatment opportunities [55–58] . A nonmutational mechanism of drug resistance of various cell lines on various tyrosine kinase inhibitors (TKIs) was described by Sharma et al. [19] . An EGFR–TKI sensitive, EGFR-mutant, NSCLC-derived cell line was exposed to an EGFR–TKI. The vast majority of cells was killed within a few days, but a small proportion (0.3%) survived. These were called drug-tolerant persisters (DTPs). Frequently observed mutational changes were ruled out as an explanation of drug resistance. Without TKI exposure, these DTPs resumed growth and gained drug sensitivity within nine doublings. A comparative genome-wide geneexpression analysis was performed on both drug-sensitive cell colonies as DTPs. Global chromatin changes were observed in the DTPs. Further analysis revealed that histone demethylase KDM5A/RPB2/JARID1A is required to acquire a drug-tolerant state. A rapid epigenetic survival response could help cancer cells to survive an initial assault and buy time to acquire further resistance by slower mutational mechanisms. Clinical trials with intermittent treatment regimens to further explore this concept are underway. Clonal outgrowth Systemic treatment of a heterogeneous tumor may provide a survival benefit to a resistant subclone, which will overgrow more sensitive clonal variants. Mathematical analyses suggests that drug-resistant subclones are present within each individual metastasis before initiation of treatment [8,47,59] . In KRAS-wild type colorectal cancer treated with panitumumab, the interval needed for resistant subclones to outgrow the sensitive clones and become clinically manifest was calculated to be 5–6 months, which is the relapse interval after initiation of treatment commonly observed in the clinic [59] . This therapyinduced recomposition of heterogeneous tumors can be quantified by sequential on-treatment biopsies or even by analysis of circulating tumor DNA (ctDNA) [60] . Ultra-deep sequencing may reveal the presence of low frequency genetic aberrations that confer resistance to treatment within a tumor already at the start of treatment. In other words, ultra-deep sequencing may identify the future resistant clone that will outgrow its neighbors. Consequently, this may provide a

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Tumor heterogeneity & personalized cancer medicine: are we being outnumbered?  rationale for upfront combinatorial treatment as illustrated in Figure 2, addition of a second agent at progression or even an adaptive approach. The latter approach, the adaptive treatment, is based on the assumption that drug-resistant clones have less survival benefit compared with sensitive clones in the absence of antineoplastic therapy. This leads, by definition, to a minority of resistant clones within the untreated population. Aggressive eradication of sensitive clones by high-dose chemotherapy or prolonged targeted therapy exposure is thought to disturb clonal homeostasis resulting in an outgrowth of cells with a more drug-resistant phenotype [4, 48] . Supporters of this concept argue that treatment should be aimed at maintaining a manageable drug-sensitive population, which suppresses the aggressive drug-resistant subclones [61] . Recent findings in patient-derived BRAF-mutated melanoma xenografts treated with vemurafenib support this adaptive theory [48] . A significant delay in the development of resistance was observed in mice treated with intermittent vemurafenib dosing compared with continuous dosing with a similar cumulative drug dose. The authors suggest a new treatment approach with a high initiation dose to achieve rapid tumor regression followed by a ‘drug holiday’ to recover from toxicities. Afterwards, an intermittent treatment schedule at a lower dose is initiated to balance resistant clones with a survival deficit in the absence of therapy, with sensitive clones having a survival deficit in the presence of therapy. This interesting concept warrants further clinical studies. Regardless, the mechanism of resistance and changes in molecular profiles between sequential on-treatment biopsies provide valuable information on the dynamic changes within a tumor during the course of treatment and provide valuable insight into the development of drug resistance. Conclusion Tumor heterogeneity is an integral part of tumor progression. Tumor heterogeneity has not prevented the implementation of some powerful biomarkers determined in a single tumor biopsy and predictive for response. However, the existence of tumor heterogeneity and evolutionary and dynamic changes within a tumor should be taken into account in designing treatment strategies to control tumor growth and in-depth analysis of tumors. Technological advances and innovative response assays may further assist these approaches.

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Outgrowth of pre-existing clones with genetic aberrations

Activation of programmed survival response

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Ultra-deep sequencing of pretreatment tumor biopsy or ctDNA

Analyzing on treatment biopsy

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Figure 2. Cancer may relapse while on treatment after initial response. Analysis of pre- or on-treatment biopsies may reveal or predict mechanisms of resistance, such as clonal outgrowth or a programmed survival response providing a rationale for upfront combinatorial treatment or add-on therapy. ctDNA: Circulating tumor DNA.

Future perspective ●●Innovative response assays reflecting

heterogeneity

A disappointing low number of preclinical findings is eventually validated and adopted in daily clinic [62 , 63] . Among other reasons, shortcomings of artificial tumor models, such as limited or no tumor heterogeneity, are important contributors to this high failure rate. Obviously, preclinical tumor models and functional response assays should ideally be a complete mimic of the human in vivo situation, including the representation of tumor heterogeneity. In this context, patient-derived tumor xenografts (PDTXs) and organoid cultures are important new developments because they are a next step towards individualization of cancer treatment. ●●Patient-derived tumor xenografts

PDTXs are established by engrafting fresh patient-derived tumor tissue in immunocompromised rodents. Maintenance of histopathology

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Perspective  Cirkel, Gadellaa-van Hooijdonk, Koudijs, Willems & Voest characteristics, intratumor heterogeneity and human stromal components, at least in the early passages, are considered key assets compared with cancer cell lines [64,65] . However, sequencing data also suggest that human tumor stroma is substituted by murine stroma in PDTXs during serial propagation in vivo, thereby altering an important factor in tumor resistance [64] . A first report on PDTX-guided PCM shows encouraging results. A pilot study was performed by Hidalgo et al. [66] . Primary or metastatic tumor samples were obtained from 14 patients with advanced solid tumors and propagated in immunodeficient mice. Subsequently, these mice were exposed to 232 different single-agent or combination treatment regimens and an effective treatment regimen was identified for 12 patients. An impressive response rate of 88% was achieved. ●●Organoid cultures

Culture conditions have been established in which both mouse-derived intestinal epithelium and patient-derived human colon cancer tissue can be expanded over long periods. Cells grow into tissue-like collections of cells referred to as ‘organoid cultures’ [67,68] . The ability to culture and expand organoids provides major opportunities to study tissue biology [69] . Compared with cancer cell lines and spheroids, tumor organoids highlight the contribution of cancer stem cells and preserve the individual genetic make-up of a tumor. Limitations are the absence of stromal cells and exposure to the immune system. Culturing tumor organoids provides an opportunity to expose patient-derived tumor organoids to a broad panel of antineoplastic agents within a reasonable short time frame. Organoid cultures can be established in 7–10 days [68] . For comparison, establishment of PDTXs takes several months [70] . Although promising, the real translational relevance of organoids and PDTXs needs to be established within the upcoming years. ●●Liquid biopsies to detect heterogeneity

Obtaining and analyzing free ctDNA or tumor cells is a relatively new and exciting area of research with great potential. Tumor DNA isolated from these ‘liquid biopsies’ provides several opportunities such as tumor monitoring, clonal tracking or even PCM [71] . As sequencing technology further develops, low frequency aberrations can be detected within these so-called ‘liquid biopsies’ with sufficient coverage and

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sensitivity. Implementation of highly sensitive sequencing analysis on ctDNA or circulating tumor cells provides an opportunity to obtain an overall view of tumor clones, and thus heterogeneity, present within a patient. From a clinical perspective, a liquid biopsy is obviously far less invasive and can be obtained without any risk of complications. Currently, malignancies with a metastasizing pattern to sites that are difficult or dangerous to approach (e.g., brain lesions or bone metastases) are less frequently biopsied. As a consequence, less scientific progress is achieved in these tumor types. Liquid biopsies may circumvent this problem. In the past years, several papers have described methods to isolate circulating tumor cells from a blood sample, with increasing quality and efficacy [72 ,73] . Parallel to these advancements single cell sequencing techniques have further evolved resulting in first reports on tumor heterogeneity at single cell level and clonal tracking [74,75] . Several reports describe methods to detect ctDNA based on a limited number of genetic aberrations found within the primary tumor [76–78] . For instance, in colorectal cancer patients, ctDNA levels with specific mutations identified in the primary tumor (e.g., APC, KRAS and TP53) were reflective of tumor dynamics influenced by surgery or chemotherapy [78] . Advanced ultra-deep sequencing technology enables identification of actionable mutations in ctDNA. As technology progresses, more variants will be identified with sufficient coverage. The feasibility of this technique was demonstrated by Forshew et al., who showed that known cancer-related mutations were found with high sensitivity and specificity in ctDNA at allele frequencies as low as 2% [60] . That liquid biopsies may at least partly overcome the sampling bias problems associated with tumor heterogeneity was demonstrated by an actionable EGFR mutation in ctDNA not present in the initial histological biopsy. The ability to identify and measure levels of ctDNA containing actionable mutations provides an opportunity to adjust treatment decisions accordingly in line with the concept of dynamic response assessments as depicted in Figure 2 . ●●Future challenges

In the upcoming decades, large databases will be prospectively filled with thousands of molecular profiles, clinical data and responses to therapy administered. It is essential that data

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Tumor heterogeneity & personalized cancer medicine: are we being outnumbered? 

Perspective

EXECUTIVE SUMMARY Background ●●

Owing to a lack of reliable biomarkers, a considerable number of patients are treated with expensive, highly toxic, nonefficacious treatment.

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The goal of personalized cancer medicine (PCM) is a shift to molecular profile-based treatment. Tumor heterogeneity is considered a major obstacle towards successful implementation of PCM.

Tumor heterogeneity ●●

Owing to tumor heterogeneity, a single tumor biopsy only partially reflects the total genetic make-up of a malignancy and only at that particular moment in time.

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Sequential pre-, on- and post-treatment tumor biopsies (and, perhaps in the future, circulating markers) are of

paramount importance to better understand tumor evolution and mechanisms of drug resistance during the course of treatment. Why tumor heterogeneity is considered to be a problem ●●

Sampling bias caused by tumor heterogeneity is regarded as the major obstacle for successful implementation of PCM or biomarker identification.

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Inadequate reflection of tumor heterogeneity in most tumor models might very well explain the poor validation rate of preclinical findings in daily clinical practice.

Treatment successes despite tumor heterogeneity ●●

Phenomena such as ‘oncogene addiction’ and paracrine signaling at least partly explain the relative high incidence of overall ‘systemic’ responses despite tumor heterogeneity.

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Hematological malignancies and advanced testicular cancer can be cured in spite of tumor heterogeneity.

Malignancies diagnosed at young age exhibit a more limited mutational spectrum with less ‘passenger mutations’ possibly generating a more rigid vulnerability to antineoplastic treatment. Impact of tumor heterogeneity on drug resistance ●●

Cancer may survive antineoplastic treatment by activation of compensatory survival programs or outgrowth of

resistant clones. Systemic treatment may trigger a programmed survival response either systemically, within the tumor’s microenvironment or within the tumor cell at several molecular levels. ●●

Balancing drug-resistant tumor clones with a survival deficit in the absence of a drug, with sensitive clones with a survival deficit in the presence of a drug provides a rationale for intermittent dosing regimens.

Future perspective ●●

Patient-derived tumor xenografts (PDTXs) and organoid cultures mimic to some extent tumor heterogeneity dynamics and are a promising next step towards individualization of cancer treatment.

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Analysis of circulating tumor DNA from ‘liquid biopsies’ provides an opportunity to obtain an overall view of tumor clones, and thus heterogeneity, within a single malignancy obtained without any risk of complications.

Future challenges ●●

Large initiatives such as the Cancer Genome Atlas of the US NIH enable a collaborative approach which is essential to allow large correlative analyses of molecular profiles and clinical outcome data.

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Due to pharmacoeconomic factors and limited patient resources it is very likely that there will be a misbalance between potential drug targets identified and corresponding drugs to target them.

Conclusion ●●

Tumor heterogeneity is an integral part of tumor progression and should be taken into account when designing

treatment strategies. Technological advances and innovative response assays may increase the number of biomarkers implemented in daily practice.

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Perspective  Cirkel, Gadellaa-van Hooijdonk, Koudijs, Willems & Voest sets containing molecular profiles and clinical outcome data will be shared. Large initiatives such as The Cancer Genome Atlas of the US NIH have been undertaken to facilitate a collaborative approach and enable large correlative analyses. In The Netherlands, the largest cancer centers have decided to collaborate and create a large biobank and database containing clinical and genetic data of individual cancer patients. For this reason, they have established the Center for Personalized Cancer Treatment [79] , which may serve as a model for others. Large correlative studies will be possible and concomitantly an increasing amount of new potential targets may be identified. But will there be a drug for every promising target identified? Drug research and development towards approval and marketing authorization is a very expensive process with a high risk of preliminary failure. In the year 2000, preapproval costs for drug research and development were estimated to be over US$800,000,000, with a yearly increasing trend of 7.4% above inflation [80] . Beside pharmacoeconomic considerations, large cohorts of patients are required References Papers of special note have been highlighted as: of interest of considerable interest l

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Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.

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in Phase I, II and III trials in order to obtain approval and marketing authorization. Limited patient resources worldwide force researchers to strictly prioritize clinical trials and innovative response assays, with less or no patients involved are highly demanded [81] . The above-mentioned facts clearly illustrate that not tumor heterogeneity, but development and clinical introduction of newly developed drugs will be the future ratelimiting step towards effective PCM. Reliable functional response assays or tumor models such as PDTXs or organoid cultures will partially resolve this bottleneck but their real value remains to be determined.

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