Intratumoral Phenotypic Heterogeneity Research Articles

Abstract 6946: Unravelling intra-tumor phenotypic heterogeneity in colorectal cancer organoids

Abstract Colorectal cancer (CRC) is one of the most diagnosed cancers worldwide. Though several treatment strategies are available today, around a million people die of this disease each year worldwide. Thus, there is still a pivotal need for new and more effective treatments. Genetic and non-genetic intra-tumor heterogeneity has emerged lately as an intrinsic feature of malignancies and as one of the factors responsible for therapy resistance or tolerance. In particular, the nature and role that phenotypically distinct, yet genetically indistinguishable, subpopulations have on tumor biology is far from being understood. Here we investigate phenotypic heterogeneity in CRC by identifying specific transcriptionally well defined cell subpopulations. We aim at deciphering the interactions between populations in terms of differentiation and plasticity, tumor growth and potentially exposed targetable vulnerabilities. To this end, we used patient-derived metastatic CRC (mCRC) organoids, including KRAS wild type (wt) and mutant (kras) models. We performed in total scRNAseq for 7 mCRC samples (4 wt; 3 kras) in different growth media: normal growth medium (supplemented with EGF) (n=1); medium without EGF (noEGF) (n=7); or treated with Cetuximab (CTX, a clinically approved monoclonal antibody against EGFR) (n=7). We found that the wt sample grown in EGF presents 2 distinct subpopulations: one with stemness characteristics (LGR5 high) and the other with a more differentiated phenotype (KRT20 high), in agreement with the current bibliography. Interestingly, in EGF deprived cultures new subpopulations appear. In particular, we were able to identify a subpopulation with distinct expression of WNT-related genes (APCDD1, WNT6, WIF1). This subpopulation is also present, and in cases increasing in fraction, when organoids are treated with CTX (in 3 out of 7 samples). Interestingly, a fraction of the WNT positive subpopulation seems to be able to proliferate under CTX treatment (Ki67 positive). We identified the negative regulator of the WNT pathway, APCDD1, as a potential marker to track this subpopulation. We took one wt and one kras sample as models to validate these findings by flow cytometry. Furthermore, sorting of APCDD1 positive and negative cells, and further RT-qPCR analysis, confirmed good correlation between antibody staining and gene expression. Moreover, we found that both types of cells are able to re-grow as organoids after re-culturing. This suggests that this WNT-associated subpopulation could be contributing, at least in part, to CTX tolerance or resistance. Our results show promising potential to help unravel basic features of intra-tumor heterogeneity both in basal conditions and upon treatment, and possibly to find new therapeutic targets. Citation Format: Sabrina J. Fletcher, Irene Catalano, Elena Grassi, Sofia Borgato, Barbara Peracino, Elena Piretto, Luca Alessandri, Raffaele Calogero, Luca Primo, Livio Trusolino, Andrea Bertotti, Alberto Puliafito. Unravelling intra-tumor phenotypic heterogeneity in colorectal cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6946.

Microscopy-based phenotypic monitoring of MDA-MB-231 spheroids allows the evaluation of phenotype-directed therapy

Breast cancer (BC) is the most commonly diagnosed cancer among women. Prognosis has improved over the years, to a large extent, owing to personalized therapy informed by molecular profiling of hormone receptors. However, there is a need for new therapeutic approaches for a subgroup of BCs lacking molecular markers, the Triple Negative Breast Cancer (TNBC) subgroup. TNBC is the most aggressive type of BC, lacks an effective standard of care, shows high levels of resistance and relapse is often inevitable. High resistance to therapy has been hypothesized to be associated with high intratumoral phenotypic heterogeneity. To characterize and treat this phenotypic heterogeneity, we optimized a whole-mount staining and image analysis protocol for three-dimensions (3D) spheroids.Applying this protocol to TNBC spheroids located in the outer region of the spheroid the cells with selected phenotypes: dividing, migrating, and high mitochondrial mass phenotypes. To evaluate the relevance of phenotype-based targeting these cell populations were targeted with Paclitaxel, Trametinib, and Everolimus, respectively, in a dose-dependent manner. Single agents cannot specifically target all phenotypes at the same time. Therefore, we combined drugs that should target independent phenotype. With this rationale we observed that combining Trametinib and Everolimus achieves the highest cytotoxicity at lower doses from all the tested combinations. These findings suggest a rational approach to design treatments can be evaluated in spheroids prior to pre-clinical models and potentially reduce adverse effects.

Chromatin Variants Reveal the Genetic Determinants of Oncogenesis in Breast Cancer.

Breast cancer presents as multiple distinct disease entities. Each tumor harbors diverse cell populations defining a phenotypic heterogeneity that impinges on our ability to treat patients. To date, efforts mainly focused on genetic variants to find drivers of inter- and intratumor phenotypic heterogeneity. However, these efforts have failed to fully capture the genetic basis of breast cancer. Through recent technological and analytical approaches, the genetic basis of phenotypes can now be decoded by characterizing chromatin variants. These variants correspond to polymorphisms in chromatin states at DNA sequences that serve a distinct role across cell populations. Here, we review the function and causes of chromatin variants as they relate to breast cancer inter- and intratumor heterogeneity and how they can guide the development of treatment alternatives to fulfill the goal of precision cancer medicine.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine.

Simple SummaryDespite the increased use of neoadjuvant chemotherapy in the early setting of breast cancer, there is a clinical need for predictive markers of response in daily practice. In the era of precision medicine and personalized treatment, new predictive markers that enable the better selection of patients for specific therapies are required. In this review, we describe the current knowledge about the molecular biomarkers used for clinical decision making for patients with breast cancer. We also report how microenvironment-driven intratumoral heterogeneity may influence the validation of biomarkers useful for precision medicine. We provide an overview of promising biomarkers, including pathological markers, genetic signatures, radiological techniques and liquid biopsies, with a great potential to be implemented in routine clinical practice. Finally, we discuss the use of relevant pre-clinical models of breast cancer to integrate microenvironmental specificities in order to identify and validate reliable biomarkers of (non-)response to neoadjuvant chemotherapy.Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

Beyond Genetics: Metastasis as an Adaptive Response in Breast Cancer

Metastatic disease represents the primary cause of breast cancer (BC) mortality, yet it is still one of the most enigmatic processes in the biology of this tumor. Metastatic progression includes distinct phases: invasion, intravasation, hematogenous dissemination, extravasation and seeding at distant sites, micro-metastasis formation and metastatic outgrowth. Whole-genome sequencing analyses of primary BC and metastases revealed that BC metastatization is a non-genetically selected trait, rather the result of transcriptional and metabolic adaptation to the unfavorable microenvironmental conditions which cancer cells are exposed to (e.g., hypoxia, low nutrients, endoplasmic reticulum stress and chemotherapy administration). In this regard, the latest multi-omics analyses unveiled intra-tumor phenotypic heterogeneity, which determines the polyclonal nature of breast tumors and constitutes a challenge for clinicians, correlating with patient poor prognosis. The present work reviews BC classification and epidemiology, focusing on the impact of metastatic disease on patient prognosis and survival, while describing general principles and current in vitro/in vivo models of the BC metastatic cascade. The authors address here both genetic and phenotypic intrinsic heterogeneity of breast tumors, reporting the latest studies that support the role of the latter in metastatic spreading. Finally, the review illustrates the mechanisms underlying adaptive stress responses during BC metastatic progression.

Cancer cell heterogeneity and plasticity: A paradigm shift in glioblastoma

Phenotypic plasticity has emerged as a major contributor to intra-tumoral heterogeneity and treatment resistance in cancer. Increasing evidence shows that glioblastoma (GBM) cells display prominent intrinsic plasticity and reversibly adapt to dynamic microenvironmental conditions. Limited genetic evolution at recurrence further suggests that resistance mechanisms also largely operate at the phenotypic level. Here we review recent literature underpinning the role of GBM plasticity in creating gradients of heterogeneous cells including those that carry cancer stem cell (CSC) properties. A historical perspective from the hierarchical to the nonhierarchical concept of CSCs towards the recent appreciation of GBM plasticity is provided. Cellular states interact dynamically with each other and with the surrounding brain to shape a flexible tumor ecosystem, which enables swift adaptation to external pressure including treatment. We present the key components regulating intra-tumoral phenotypic heterogeneity and the equilibrium of phenotypic states, including genetic, epigenetic, and microenvironmental factors. We further discuss plasticity in the context of intrinsic tumor resistance, where a variable balance between preexisting resistant cells and adaptive persisters leads to reversible adaptation upon treatment. Innovative efforts targeting regulators of plasticity and mechanisms of state transitions towards treatment-resistant states are needed to restrict the adaptive capacities of GBM.

Impact of cancer metabolism on therapy resistance – Clinical implications

Despite an increasing arsenal of anticancer therapies, many patients continue to have poor outcomes due to the therapeutic failures and tumor relapses. Indeed, the clinical efficacy of anticancer therapies is markedly limited by intrinsic and/or acquired resistance mechanisms that can occur in any tumor type and with any treatment. Thus, there is an urgent clinical need to implement fundamental changes in the tumor treatment paradigm by the development of new experimental strategies that can help to predict the occurrence of clinical drug resistance and to identify alternative therapeutic options. Apart from mutation-driven resistance mechanisms, tumor microenvironment (TME) conditions generate an intratumoral phenotypic heterogeneity that supports disease progression and dismal outcomes. Tumor cell metabolism is a prototypical example of dynamic, heterogeneous, and adaptive phenotypic trait, resulting from the combination of intrinsic [(epi)genetic changes, tissue of origin and differentiation dependency] and extrinsic (oxygen and nutrient availability, metabolic interactions within the TME) factors, enabling cancer cells to survive, metastasize and develop resistance to anticancer therapies. In this review, we summarize the current knowledge regarding metabolism-based mechanisms conferring adaptive resistance to chemo-, radio-and immunotherapies as well as targeted therapies. Furthermore, we report the role of TME-mediated intratumoral metabolic heterogeneity in therapy resistance and how adaptations in amino acid, glucose, and lipid metabolism support the growth of therapy-resistant cancers and/or cellular subpopulations. We also report the intricate interplay between tumor signaling and metabolic pathways in cancer cells and discuss how manipulating key metabolic enzymes and/or providing dietary changes may help to eradicate relapse-sustaining cancer cells. Finally, in the current era of personalized medicine, we describe the strategies that may be applied to implement metabolic profiling for tumor imaging, biomarker identification, selection of tailored treatments and monitoring therapy response during the clinical management of cancer patients.

Abstract 2653: Lineage plasticity in small cell lung cancer generates non- neuroendocrine cells primed for vascular mimicry

Abstract Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine (NE) cancer with rapid and widespread metastasis and a dismal prognosis measurable only in months. The inherent lack of tumor biopsies has limited our understanding of SCLC phenotypic heterogeneity, and except for the addition of Immune Checkpoint Inhibitors the therapeutic strategy has remained largely unchanged for decades. We are investigating Vascular Mimicry (VM) in SCLC, which is linked to poor prognosis and may provide a novel therapeutic opportunity1. VM describes the ability of aggressive tumor cells to undergo trans-endothelial differentiation, enabling angiogenesis-independent tumor vascularization. We hypothesize that, via extracellular matrix (ECM) remodeling, VM provides a favorable tumor microenvironment (TME) to support tumor progression and metastasis. We explored SCLC VM competency and molecular mechanisms underpinning this using histopathology and transcriptomic and proteomic analyses of NE and non-NE SCLC cells in patient faithful Circulating Tumor Cell (CTC)-Derived eXplant (CDX)2,3 models and genetically-engineered mouse models (GEMMs). We demonstrate that within human and murine SCLC tumors in vivo and ex vivo the non-NE cells, unlike NE cells, are VM competent. NE SCLC cells in an ASCL1-expressing CDX model undergo a Notch-driven transition to a non-NE phenotype. We show that non-NE cells are transcriptionally primed to undergo VM and express gene signatures consistent with pseudohypoxia, blood vessel development and extracellular matrix (ECM) organization. These cells undergo post-translational modification of proteins involved in cell-cell and cell-ECM adhesion including a VM-specific glycosylation of integrin β1. On Matrigel VM-primed non-NE cells remodeled the ECM forming tubular networks, an established surrogate assay for VM competence. Integrin β1 blockade impedes VM in vitro by inhibiting non-NE cell collagen adhesion and thus ECM remodeling. This previously unrecognized functional intratumoral heterogeneity in SCLC supports therapeutic co-targeting of NE and non-NE cells to curtail VM-supported tumor growth and metastasis. The ultimate aim is to identify targetable therapeutic options with which to inhibit VM to improve outcomes for patients with SCLC. References 1S. C. Williamson et al., Vasculogenic mimicry in small cell lung cancer. Nat Commun 7, 1 (2016). 2C. L. Hodgkinson et al., Tumorigenicity and genetic profiling of circulating tumor cells in small-cell lung cancer. Nature medicine 20, 897 (2014). 3K. L. Simpson et al., A biobank of small cell lung cancer CDX models elucidates inter-and intratumoral phenotypic heterogeneity. Nature Cancer 1, 4 (2020). Citation Format: Sarah M. Pearsall, Stuart C. Williamson, Fernando García Marqués, Sam Humphrey, Ellyn Hughes, Ian Cannell, Kristopher K. Frese, Melanie Galvin, Mathew Carter, Lynsey Priest, Alastair Kerr, Martin J. Humphries, Jonathon D. Humphries, Fiona Blackhall, Gregory Hannon, Julien Sage, Sharon J. Pitteri, Kathryn L. Simpson, Caroline Dive. Lineage plasticity in small cell lung cancer generates non- neuroendocrine cells primed for vascular mimicry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2653.

A Mathematical Study of the Influence of Hypoxia and Acidity on the Evolutionary Dynamics of Cancer

Hypoxia and acidity act as environmental stressors promoting selection for cancer cells with a more aggressive phenotype. As a result, a deeper theoretical understanding of the spatio-temporal processes that drive the adaptation of tumour cells to hypoxic and acidic microenvironments may open up new avenues of research in oncology and cancer treatment. We present a mathematical model to study the influence of hypoxia and acidity on the evolutionary dynamics of cancer cells in vascularised tumours. The model is formulated as a system of partial integro-differential equations that describe the phenotypic evolution of cancer cells in response to dynamic variations in the spatial distribution of three abiotic factors that are key players in tumour metabolism: oxygen, glucose and lactate. The results of numerical simulations of a calibrated version of the model based on real data recapitulate the eco-evolutionary spatial dynamics of tumour cells and their adaptation to hypoxic and acidic microenvironments. Moreover, such results demonstrate how nonlinear interactions between tumour cells and abiotic factors can lead to the formation of environmental gradients which select for cells with phenotypic characteristics that vary with distance from intra-tumour blood vessels, thus promoting the emergence of intra-tumour phenotypic heterogeneity. Finally, our theoretical findings reconcile the conclusions of earlier studies by showing that the order in which resistance to hypoxia and resistance to acidity arise in tumours depend on the ways in which oxygen and lactate act as environmental stressors in the evolutionary dynamics of cancer cells.

Heterogeneity in Signaling Pathway Activity within Primary and between Primary and Metastatic Breast Cancer.

Simple SummaryPersonalized breast cancer treatment with targeted therapy (e.g., tamoxifen or PI3K inhibitors) requires identification of responder patients. Phenotypical heterogeneity within the primary, and between primary tumor and metastases, may however interfere with response to therapy, if based on a single primary tumor biopsy. In this study, we investigated this heterogeneity, using novel assays to measure activity of tumor-driving signal transduction pathways, e.g., estrogen receptor and PI3K pathways, in multiple samples distributed across the tumor and in metastases. Within the primary tumor, heterogeneity was dominant at microscale (biopsy block) and not at macroscale (across tumor), suggesting that a single biopsy is generally representative for the whole primary tumor. The differences found between pathway activity in primary tumor and metastases suggests that it is recommendable to analyze pathway activity in metastatic samples for treatment selection for late stage patients.Targeted therapy aims to block tumor-driving signaling pathways and is generally based on analysis of one primary tumor (PT) biopsy. Tumor heterogeneity within PT and between PT and metastatic breast lesions may, however, impact the effect of a chosen therapy. Whereas studies are available that investigate genetic heterogeneity, we present results on phenotypic heterogeneity by analyzing the variation in the functional activity of signal transduction pathways, using an earlier developed platform to measure such activity from mRNA measurements of pathways’ direct target genes. Statistical analysis comparing macro-scale variation in pathway activity on up to five spatially distributed PT tissue blocks (n = 35), to micro-scale variation in activity on four adjacent samples of a single PT tissue block (n = 17), showed that macro-scale variation was not larger than micro-scale variation, except possibly for the PI3K pathway. Simulations using a “checkerboard clone-size” model showed that multiple small clones could explain the higher micro-scale variation in activity found for the TGFβ and Hedgehog pathways, and that intermediate/large clones could explain the possibly higher macro-scale variation of the PI3K pathway. While within PT, pathway activities presented a highly positive correlation, correlations weakened between PT and lymph node metastases (n = 9), becoming even worse for PT and distant metastases (n = 9), including a negative correlation for the ER pathway. While analysis of multiple sub-samples of a single biopsy may be sufficient to predict PT response to targeted therapies, metastatic breast cancer treatment prediction requires analysis of metastatic biopsies. Our findings on phenotypic intra-tumor heterogeneity are compatible with emerging ideas on a Big Bang type of cancer evolution in which macro-scale heterogeneity appears not dominant.

Selection-driven tumor evolution with public goods leads to patterns of clonal expansion consistent with neutral growth.

SummaryCancers are the result of eco-evolutionary processes fueled by heritable phenotypic diversification and driven by environmentally dependent selection. Space represents a key growth-limiting ecological resource, the ability to explore this resource is likely under strong selection. Using agent-based modeling, we explored the interplay between phenotypic strategies centered on gaining access to new space through cell-extrinsic degradation of extracellular matrix barriers and the exploitation of this resource through maximizing cell proliferation. While cell proliferation is a cell-intrinsic property, newly accessed space represents a public good, which can benefit both producers and non-producers. We found that this interplay results in ecological succession, enabling emergence of large, heterogeneous, and highly proliferative populations. Even though in our simulations both remodeling and proliferation strategies were under strong positive selection, their interplay led to sub-clonal architecture that could be interpreted as evidence for neutral evolution, warranting cautious interpretation of inferences from sequencing of cancer genomes.

Abstract IA26: Tumor evolution: From Darwin’s finches to breast cancer

Abstract Tumor evolution is driven by heterogeneity for heritable traits in combination with environmental selection forces including cancer therapies. We have been investigating intratumor cellular genetic and phenotypic heterogeneity in breast tumors and described that higher heterogeneity is associated with poor clinical outcomes. We have also developed experimental models of intratumor subclonal heterogeneity and demonstrated that more heterogeneous tumors grow faster and develop heterogeneous distant metastases. By analyzing the underlying mechanisms we defined that intratumor heterogeneity is maintained by non-cell-autonomous factors and clonal cooperation drives metastases by modulating the local and systemic microenvironments. Lastly, we have identified epigenetic enzymes as regulators of cellular transcriptomic heterogeneity and showed that by modulating the activity of these enzymes, we can decrease cellular heterogeneity and therapeutic resistance. Overall, our studies demonstrate the need to study cancer patients as a whole and to apply a combination of molecular profiling, including single cell assays, and mathematical modeling to understand how tumors evolved and to develop more effective cancer therapeutic strategies based on this knowledge. Citation Format: Kornelia Polyak. Tumor evolution: From Darwin’s finches to breast cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA26.

Evolutionary Dynamics in Vascularised Tumours under Chemotherapy: Mathematical Modelling, Asymptotic Analysis and Numerical Simulations

We consider a mathematical model for the evolutionary dynamics of tumour cells in vascularised tumours under chemotherapy. The model comprises a system of coupled partial integro-differential equations for the phenotypic distribution of tumour cells, the concentration of oxygen and the concentration of a chemotherapeutic agent. In order to disentangle the impact of different evolutionary parameters on the emergence of intra-tumour phenotypic heterogeneity and the development of resistance to chemotherapy, we construct explicit solutions to the equation for the phenotypic distribution of tumour cells and provide a detailed quantitative characterisation of the long-time asymptotic behaviour of such solutions. Analytical results are integrated with numerical simulations of a calibrated version of the model based on biologically consistent parameter values. The results obtained provide a theoretical explanation for the observation that the phenotypic properties of tumour cells in vascularised tumours vary with the distance from the blood vessels. Moreover, we demonstrate that lower oxygen levels may correlate with higher levels of phenotypic variability, which suggests that the presence of hypoxic regions supports intra-tumour phenotypic heterogeneity. Finally, the results of our analysis put on a rigorous mathematical basis the idea, previously suggested by formal asymptotic results and numerical simulations, that hypoxia favours the selection for chemoresistant phenotypic variants prior to treatment. Consequently, this facilitates the development of resistance following chemotherapy.

A biobank of small cell lung cancer CDX models elucidates inter- and intratumoral phenotypic heterogeneity.

Although small cell lung cancer (SCLC) is treated as a homogeneous disease, biopsies and preclinical models reveal heterogeneity in transcriptomes and morphology. SCLC subtypes were recently defined by neuroendocrine transcription factor (NETF) expression. Circulating-tumor-cell-derived explant models (CDX) recapitulate donor patients' tumor morphology, diagnostic NE marker expression and chemotherapy responses. We describe a biobank of 38 CDX models, including six CDX pairs generated pretreatment and at disease progression revealing complex intra- and intertumoral heterogeneity. Transcriptomic analysis confirmed three of four previously described subtypes based on ASCL1, NEUROD1 and POU2F3 expression and identified a previously unreported subtype based on another NETF, ATOH1. We document evolution during disease progression exemplified by altered MYC and NOTCH gene expression, increased 'variant' cell morphology, and metastasis without strong evidence of epithelial to mesenchymal transition. This CDX biobank provides a research resource to facilitate SCLC personalized medicine.

The single-cell pathology landscape of breast cancer.

Single-cell analyses have revealed extensive heterogeneity between and within human tumours1-4, but complex single-cell phenotypes and their spatial context are not at present reflected in the histological stratification that is the foundation of many clinical decisions. Here we use imaging mass cytometry5 to simultaneously quantify 35 biomarkers, resulting in 720 high-dimensional pathology images of tumour tissue from 352 patients with breast cancer, with long-term survival data availablefor 281 patients. Spatially resolved, single-cell analysis identified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity, and enabled the cellular architecture of breast cancer tissue to be characterized on the basis of cellular composition and tissue organization. Our analysis reveals multicellular features of the tumour microenvironment and novel subgroups of breast cancer that are associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intratumour phenotypic heterogeneity in a disease-relevant manner, with the potential to inform patient-specific diagnosis.

Solid pseudopapillary neoplasia of the pancreas: a review.

To review the literature and the diagnosis of conventional histopathological routine and immunohistochemistry of the cases diagnosed with Solid Pseudopapillary Neoplasm of the Pancreas (SPNP). The review of the literature was done using the Pubmed and solid Google-Scholar databases, through the historical, clinical aspects and diagnostic methods of SPNP. The review of SPNP cases diagnosed in the University Hospital Clementino Fraga Filho was carried out from 1977 to 2018. Intratumoral phenotypic heterogeneity of SPNP was evidenced in the cases studied, taking into account macroscopic, microscopic, and immunohistochemical patterns. The results show the importance of the examination of several fragments obtained from different regions of the neoplasia since not all of them present the same molecular alterations.

STEM-09. INTRINSIC TUMOR PLASTICITY IN GLIOBLASTOMA ALLOWS FOR RECREATION OF STEM LIKE-STATES AND EFFICIENT TUMOR CELL ADAPTATION TO NEW MICROENVIRONMENTS

Abstract BACKGROUND Cellular heterogeneity is a hallmark of numerous cancer types, including Glioblastoma (GBM). Cancer stem cells (CSC) have been accounted for the generation of phenotypic heterogeneity and tumor progression in GBM. Recent data, however, suggest that CSCs may not represent a stable entity and intrinsic plasticity plays a key role in tumor adaptation to changing microenvironments. The question arises whether CSCs are a defined subpopulation of GBM or whether they represent a cellular state that any cancer cell can adopt. METHODS We interrogated intra-tumoral phenotypic heterogeneity at the single cell transcriptomic and proteomic level in GBM biopsies, patient-derived stem-like cultures and orthotopic xenografts (PDOXs). Tumor cell subpopulations, classified based on their expression of four proposed stem cell markers (CD133, CD15, A2B5 and CD44), were FACS isolated and functionally characterized under various microenvironmental conditions. Mathematical Markov modelling was applied to calculate state transitions. RESULTS GBM patient biopsies, PDOXs and stem-like cell cultures displayed remarkable stem cell-associated intra-tumoral heterogeneity. However independent of marker expression, all analysed tumor subpopulations carried stem-cell properties and recreated phenotypic heterogeneity. Mathematical modeling revealed a different propensity in reforming heterogeneity over time, which was independent of the proliferation index but linked to in vivo tumorigenic potential. Although GBM subpopulations varied in their potential to adapt to new environments, all were able to reach a steady state microenvironment-specific equilibrium. CONCLUSIONS Our results suggest that phenotypic heterogeneity in GBM results from intrinsic plasticity allowing tumor cells to adapt to changing microenvironmental conditions. Cellular states are non-hierarchical, reversible and occur via stochastic state transitions, striving towards a microenvironment-instructed equilibrium. Our data provides evidence that CSCs do not represent a defined clonal entity, but rather a cellular state determined by environmental conditions, which has implications for the design of treatment strategies targeting CSC-like states.

Tracking tumor evolution one-cell-at-a-time

ABSTRACTAccumulating evidence suggests that intra-tumor heterogeneity (ITH) within tumor sub-populations is a major contributor to therapy resistance, with genomically distinct clonal populations exhibiting different therapeutic vulnerabilities. Here we employed single-cell transcriptomics in patient-derived primary cells to understand the impact of phenotypic intra-tumor heterogeneity on drug-induced tumor evolution in oral squamous cell carcinoma.

Abstract GS5-05: Resistance to neoadjuvant chemotherapy in triple negative breast cancer mediated by a reversible drug-tolerant state

Abstract Approximately 50% of patients with localized triple negative breast cancer (TNBC) have substantial residual cancer burden following treatment with neoadjuvant chemotherapy (NACT), resulting in distant metastasis and death for most of these patients. While genomic and phenotypic intra-tumor heterogeneity are pervasive features of TNBCs at the time of diagnosis, the functional contributions of heterogeneous tumor cell populations to chemoresistance have not been elucidated. To investigate tumor evolution accompanying NACT, we employed orthotopic patient-derived xenograft (PDX) models of treatment-naïve TNBC, which retain intra-tumor heterogeneity characteristic of human TNBC. We discovered that some PDX models initially exhibited partial sensitivity to standard front-line NACT (Adriamycin plus Cytoxan, AC). Following AC, residual tumors were resistant to chemotherapy but repopulated tumors with chemo-sensitive cells if left untreated, indicating that tumor cells possessed inherent plasticity. To identify the tumor cell subpopulation(s) conferring chemoresistance, we conducted barcode-mediated clonal tracking in three independent PDX models by introducing a high-complexity pooled lentiviral barcode library into PDX tumor cells which were then orthotopically engrafted into recipient mice. Strikingly, residual tumors maintained the same heterogeneous clonal architecture as naïve tumors. Concordantly, whole-exome sequencing revealed conservation of genomic subclonal architecture throughout treatment. These results were corroborated by genomic sequencing of serial biopsies pre- and post-AC obtained directly from TNBC patients enrolled on an ongoing clinical trial at MD Anderson (ARTEMIS; NCT02276443). Together, these studies revealed that genomically distinct pre-treatment subclones were equally capable of surviving AC to reconstitute tumors after treatment. To identify functional addictions of residual tumor cells, we conducted histologic and transcriptomic profiling. Residual tumors following AC-treatment exhibited extensive fibrotic desmoplasia and tumor cell pleomorphism in both PDX models and in serial biopsies obtained from TNBC patients enrolled on the ARTEMIS trial. Strikingly, these AC-induced features were reverted upon regrowth of residual tumors in PDXs and in patients' tumors. Similarly, residual tumors exhibited unique transcriptomic features, many of which are also de-regulated in cohorts of human TNBCs undergoing chemotherapy treatment. These features were nearly completely reverted after tumors regrew, suggesting that the residual tumor state may be a unique and transient therapeutic window. Gene set enrichment analyses revealed that residual tumors had increased activation of oxidative phosphorylation and decreased glycolytic signaling. Pharmacologic targeting of oxidative phosphorylation with a small-molecule inhibitor of mitochondrial electron transport chain complex I (IACS-010759) significantly delayed the regrowth of AC-treated residual tumors in three independent PDX models. Collectively, these studies reveal that a reversible phenotypic state can confer chemoresistance in the absence of genomic selection and that the residual tumor state is a novel therapeutic window for chemo-refractory TNBC. Citation Format: Echeverria GV, Ge Z, Seth S, Jeter-Jones SL, Zhang X, Zhou X, Cai S, Tu Y, McCoy A, Peoples M, Lau R, Shao J, Sun Y, Bristow C, Carugo A, Ma X, Harris A, Wu Y, Moulder S, Symmans WF, Marszalek JR, Heffernan TP, Chang JT, Piwnica-Worms H. Resistance to neoadjuvant chemotherapy in triple negative breast cancer mediated by a reversible drug-tolerant state [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS5-05.

Longitudinal single-cell RNA sequencing of patient-derived primary cells reveals drug-induced infidelity in stem cell hierarchy

Chemo-resistance is one of the major causes of cancer-related deaths. Here we used single-cell transcriptomics to investigate divergent modes of chemo-resistance in tumor cells. We observed that higher degree of phenotypic intra-tumor heterogeneity (ITH) favors selection of pre-existing drug-resistant cells, whereas phenotypically homogeneous cells engage covert epigenetic mechanisms to trans-differentiate under drug-selection. This adaptation was driven by selection-induced gain of H3K27ac marks on bivalently poised resistance-associated chromatin, and therefore not expressed in the treatment-naïve setting. Mechanistic interrogation of this phenomenon revealed that drug-induced adaptation was acquired upon the loss of stem factor SOX2, and a concomitant gain of SOX9. Strikingly we observed an enrichment of SOX9 at drug-induced H3K27ac sites, suggesting that tumor evolution could be driven by stem cell-switch-mediated epigenetic plasticity. Importantly, JQ1 mediated inhibition of BRD4 could reverse drug-induced adaptation. These results provide mechanistic insights into the modes of therapy-induced cellular plasticity and underscore the use of epigenetic inhibitors in targeting tumor evolution.