Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Inflammation in Cancer Cells in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by an immunosuppressive tumor microenvironment enriched with cancer-associated fibroblasts (CAF). This study used a convergence approach to identify tumor cell and CAF interactions through the integration of single-cell data from human tumors with human organoid coculture experiments. Analysis of a comprehensive atlas of PDAC single-cell RNA sequencing data indicated that CAF density is associated with increased inflammation and epithelial-mesenchymal transition (EMT) in epithelial cells. Transfer learning using transcriptional data from patient-derived organoid and CAF cocultures provided in silico validation of CAF induction of inflammatory and EMT epithelial cell states. Further experimental validation in cocultures demonstrated integrin beta 1 (ITGB1) and vascular endothelial factor A (VEGFA) interactions with neuropilin-1 mediating CAF-epithelial cell cross-talk. Together, this study introduces transfer learning from human single-cell data to organoid coculture analyses for experimental validation of discoveries of cell-cell cross-talk and identifies fibroblast-mediated regulation of EMT and inflammation.

SIGNIFICANCE

Adaptation of transfer learning to relate human single-cell RNA sequencing data to organoid-CAF cocultures facilitates discovery of human pancreatic cancer intercellular interactions and uncovers cross-talk between CAFs and tumor cells through VEGFA and ITGB1.

Personalized neoantigen vaccine and pembrolizumab in advanced hepatocellular carcinoma: a phase 1/2 trial

Programmed cell death protein 1 (PD-1) inhibitors have modest efficacy as a monotherapy in hepatocellular carcinoma (HCC). A personalized therapeutic cancer vaccine (PTCV) may enhance responses to PD-1 inhibitors through the induction of tumor-specific immunity. We present results from a single-arm, open-label, phase 1/2 study of a DNA plasmid PTCV (GNOS-PV02) encoding up to 40 neoantigens coadministered with plasmid-encoded interleukin-12 plus pembrolizumab in patients with advanced HCC previously treated with a multityrosine kinase inhibitor. Safety and immunogenicity were assessed as primary endpoints, and treatment efficacy and feasibility were evaluated as secondary endpoints. The most common treatment-related adverse events were injection-site reactions, observed in 15 of 36 (41.6%) patients. No dose-limiting toxicities or treatment-related grade ≥3 events were observed. The objective response rate (modified intention-to-treat) per Response Evaluation Criteria in Solid Tumors 1.1 was 30.6% (11 of 36 patients), with 8.3% (3 of 36) of patients achieving a complete response. Clinical responses were associated with the number of neoantigens encoded in the vaccine. Neoantigen-specific T cell responses were confirmed in 19 of 22 (86.4%) evaluable patients by enzyme-linked immunosorbent spot assays. Multiparametric cellular profiling revealed active, proliferative and cytolytic vaccine-specific CD4+ and CD8+ effector T cells. T cell receptor β-chain (TCRβ) bulk sequencing results demonstrated vaccination-enriched T cell clone expansion and tumor infiltration. Single-cell analysis revealed posttreatment T cell clonal expansion of cytotoxic T cell phenotypes. TCR complementarity-determining region cloning of expanded T cell clones in the tumors following vaccination confirmed reactivity against vaccine-encoded neoantigens. Our results support the PTCV's mechanism of action based on the induction of antitumor T cells and show that a PTCV plus pembrolizumab has clinical activity in advanced HCC. ClinicalTrials.gov identifier: NCT04251117 .

Mimicking the breast metastatic microenvironment: characterization of a novel syngeneic model of HER2+ breast cancer

Preclinical murine models in which primary tumors spontaneously metastasize to distant organs are valuable tools to study metastatic progression and novel cancer treatment combinations. Here, we characterize a novel syngeneic murine breast tumor cell line, NT2.5-lung metastasis (-LM), that provides a model of spontaneously metastatic neu-expressing breast cancer with quicker onset of widespread metastases after orthotopic mammary implantation in immune-competent NeuN mice. Within one week of orthotopic implantation of NT2.5-LM in NeuN mice, distant metastases can be observed in the lungs. Within four weeks, metastases are also observed in the bones, spleen, colon, and liver. Metastases are rapidly growing, proliferative, and responsive to HER2-directed therapy. We demonstrate altered expression of markers of epithelial-to-mesenchymal transition (EMT) and enrichment in EMT-regulating pathways, suggestive of their enhanced metastatic potential. The new NT2.5-LM model provides more rapid and spontaneous development of widespread metastases. Besides investigating mechanisms of metastatic progression, this new model may be used for the rationalized development of novel therapeutic interventions and assessment of therapeutic responses targeting distant visceral metastases.

Systems immunology spanning tumors, lymph nodes, and periphery

The immune system defines a complex network of tissues and cell types that orchestrate responses across the body in a dynamic manner. The local and systemic interactions between immune and cancer cells contribute to disease progression. Lymphocytes are activated in lymph nodes, traffic through the periphery, and impact cancer progression through their interactions with tumor cells. As a result, therapeutic response and resistance are mediated across tissues, and a comprehensive understanding of lymphocyte dynamics requires a systems-level approach. In this review, we highlight experimental and computational methods that can leverage the study of leukocyte trafficking through an immunomics lens and reveal how adaptive immunity shapes cancer.

CD4 T cell-activating neoantigens enhance personalized cancer vaccine efficacy

Personalized cancer vaccines aim to activate and expand cytotoxic antitumor CD8+ T cells to recognize and kill tumor cells. However, the role of CD4+ T cell activation in the clinical benefit of these vaccines is not well defined. We previously established a personalized neoantigen vaccine (PancVAX) for the pancreatic cancer cell line Panc02, which activates tumor-specific CD8+ T cells but required combinatorial checkpoint modulators to achieve therapeutic efficacy. To determine the effects of neoantigen-specific CD4+ T cell activation, we generated a vaccine (PancVAX2) targeting both major histocompatibility complex class I- (MHCI-) and MHCII-specific neoantigens. Tumor-bearing mice vaccinated with PancVAX2 had significantly improved control of tumor growth and long-term survival benefit without concurrent administration of checkpoint inhibitors. PancVAX2 significantly enhanced priming and recruitment of neoantigen-specific CD8+ T cells into the tumor with lower PD-1 expression after reactivation compared with the CD8+ vaccine alone. Vaccine-induced neoantigen-specific Th1 CD4+ T cells in the tumor were associated with decreased Tregs. Consistent with this, PancVAX2 was associated with more proimmune myeloid-derived suppressor cells and M1-like macrophages in the tumor, demonstrating a less immunosuppressive tumor microenvironment. This study demonstrates the biological importance of prioritizing and including CD4+ T cell-specific neoantigens for personalized cancer vaccine modalities.

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells' characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual "thought experiments" that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.

Immune landscape of tertiary lymphoid structures in hepatocellular carcinoma (HCC) treated with neoadjuvant immune checkpoint blockade

Neoadjuvant immunotherapy is thought to produce long-term remissions through induction of antitumor immune responses before removal of the primary tumor. Tertiary lymphoid structures (TLS), germinal center-like structures that can arise within tumors, may contribute to the establishment of immunological memory in this setting, but understanding of their role remains limited. Here, we investigated the contribution of TLS to antitumor immunity in hepatocellular carcinoma (HCC) treated with neoadjuvant immunotherapy. We found that neoadjuvant immunotherapy induced the formation of TLS, which were associated with superior pathologic response, improved relapse free survival, and expansion of the intratumoral T and B cell repertoire. While TLS in viable tumor displayed a highly active mature morphology, in areas of tumor regression we identified an involuted TLS morphology, which was characterized by dispersion of the B cell follicle and persistence of a T cell zone enriched for ongoing antigen presentation and T cell-mature dendritic cell interactions. Involuted TLS showed increased expression of T cell memory markers and expansion of CD8+ cytotoxic and tissue resident memory clonotypes. Collectively, these data reveal the circumstances of TLS dissolution and suggest a functional role for late-stage TLS as sites of T cell memory formation after elimination of viable tumor.

Molecular signature incorporating the immune microenvironment enhances thyroid cancer outcome prediction

Genomic and transcriptomic analysis has furthered our understanding of many tumors. Yet, thyroid cancer management is largely guided by staging and histology, with few molecular prognostic and treatment biomarkers. Here, we utilize a large cohort of 251 patients with 312 samples from two tertiary medical centers and perform DNA/RNA sequencing, spatial transcriptomics, and multiplex immunofluorescence to identify biomarkers of aggressive thyroid malignancy. We identify high-risk mutations and discover a unique molecular signature of aggressive disease, the Molecular Aggression and Prediction (MAP) score, which provides improved prognostication over high-risk mutations alone. The MAP score is enriched for genes involved in epithelial de-differentiation, cellular division, and the tumor microenvironment. The MAP score also identifies aggressive tumors with lymphocyte-rich stroma that may benefit from immunotherapy. Future clinical profiling of the stromal microenvironment of thyroid cancer could improve prognostication, inform immunotherapy, and support development of novel therapeutics for thyroid cancer and other stroma-rich tumors.

Spatial transcriptomics analysis of neoadjuvant cabozantinib and nivolumab in advanced hepatocellular carcinoma identifies independent mechanisms of resistance and recurrence

BACKGROUND

Novel immunotherapy combination therapies have improved outcomes for patients with hepatocellular carcinoma (HCC), but responses are limited to a subset of patients. Little is known about the inter- and intra-tumor heterogeneity in cellular signaling networks within the HCC tumor microenvironment (TME) that underlie responses to modern systemic therapy.

METHODS

We applied spatial transcriptomics (ST) profiling to characterize the tumor microenvironment in HCC resection specimens from a prospective clinical trial of neoadjuvant cabozantinib, a multi-tyrosine kinase inhibitor that primarily blocks VEGF, and nivolumab, a PD-1 inhibitor in which 5 out of 15 patients were found to have a pathologic response at the time of resection.

RESULTS

ST profiling demonstrated that the TME of responding tumors was enriched for immune cells and cancer-associated fibroblasts (CAF) with pro-inflammatory signaling relative to the non-responders. The enriched cancer-immune interactions in responding tumors are characterized by activation of the PAX5 module, a known regulator of B cell maturation, which colocalized with spots with increased B cell marker expression suggesting strong activity of these cells. HCC-CAF interactions were also enriched in the responding tumors and were associated with extracellular matrix (ECM) remodeling as there was high activation of FOS and JUN in CAFs adjacent to the tumor. The ECM remodeling is consistent with proliferative fibrosis in association with immune-mediated tumor regression. Among the patients with major pathologic responses, a single patient experienced early HCC recurrence. ST analysis of this clinical outlier demonstrated marked tumor heterogeneity, with a distinctive immune-poor tumor region that resembles the non-responding TME across patients and was characterized by HCC-CAF interactions and expression of cancer stem cell markers, potentially mediating early tumor immune escape and recurrence in this patient.

CONCLUSIONS

These data show that responses to modern systemic therapy in HCC are associated with distinctive molecular and cellular landscapes and provide new targets to enhance and prolong responses to systemic therapy in HCC.

Informing virtual clinical trials of hepatocellular carcinoma with spatial multi-omics analysis of a human neoadjuvant immunotherapy clinical trial

Human clinical trials are important tools to advance novel systemic therapies improve treatment outcomes for cancer patients. The few durable treatment options have led to a critical need to advance new therapeutics in hepatocellular carcinoma (HCC). Recent human clinical trials have shown that new combination immunotherapeutic regimens provide unprecedented clinical response in a subset of patients. Computational methods that can simulate tumors from mathematical equations describing cellular and molecular interactions are emerging as promising tools to simulate the impact of therapy entirely in silico. To facilitate designing dosing regimen and identifying potential biomarkers, we developed a new computational model to track tumor progression at organ scale while reflecting the spatial heterogeneity in the tumor at tissue scale in HCC. This computational model is called a spatial quantitative systems pharmacology (spQSP) platform and it is also designed to simulate the effects of combination immunotherapy. We then validate the results from the spQSP system by leveraging real-world spatial multi-omics data from a neoadjuvant HCC clinical trial combining anti-PD-1 immunotherapy and a multitargeted tyrosine kinase inhibitor (TKI) cabozantinib. The model output is compared with spatial data from Imaging Mass Cytometry (IMC). Both IMC data and simulation results suggest closer proximity between CD8 T cell and macrophages among non-responders while the reverse trend was observed for responders. The analyses also imply wider dispersion of immune cells and less scattered cancer cells in responders' samples. We also compared the model output with Visium spatial transcriptomics analyses of samples from post-treatment tumor resections in the original clinical trial. Both spatial transcriptomic data and simulation results identify the role of spatial patterns of tumor vasculature and TGFβ in tumor and immune cell interactions. To our knowledge, this is the first spatial tumor model for virtual clinical trials at a molecular scale that is grounded in high-throughput spatial multi-omics data from a human clinical trial.

Profiling of syngeneic mouse HCC tumor models as a framework to understand anti-PD-1 sensitive tumor microenvironments

BACKGROUND AND AIMS

The treatment of hepatocellular carcinoma (HCC) has been transformed by the use of immune checkpoint inhibitors. However, most patients with HCC do not benefit from treatment with immunotherapy. There is an urgent need to understand the mechanisms that underlie response or resistance to immunotherapy for patients with HCC. The use of syngeneic mouse models that closely recapitulate the heterogeneity of human HCC will provide opportunities to examine the complex interactions between cancer cells and nonmalignant cells in the tumor microenvironment.

APPROACH AND RESULTS

We leverage a multifaceted approach that includes imaging mass cytometry and suspension cytometry by time of flight to profile the tumor microenvironments of the Hep53.4, Hepa 1-6, RIL-175, and TIBx (derivative of TIB-75) syngeneic mouse HCC models. The immune tumor microenvironments vary across these four models, and various immunosuppressive pathways exist at baseline in orthotopic liver tumors derived from these models. For instance, TIBx, which is resistant to anti-programmed cell death protein 1 therapy, contains a high proportion of "M2-like" tumor-associated macrophages with the potential to diminish antitumor immunity. Investigation of The Cancer Genome Atlas reveals that the baseline immunologic profiles of Hep53.4, RIL-175, and TIBx are broadly representative of human HCCs; however, Hepa 1-6 does not recapitulate the immune tumor microenvironment of the vast majority of human HCCs.

CONCLUSIONS

There is a wide diversity in the immune tumor microenvironments in preclinical models and in human HCC, highlighting the need to use multiple syngeneic HCC models to improve the understanding of how to treat HCC through immune modulation.

Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces

Recent advances in spatial transcriptomics (STs) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor as well as the tumor microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as it occurs in tumor-immune interactions. We present SpaceMarkers, a bioinformatics algorithm to infer molecular changes from cell-cell interactions from latent space analysis of ST data. We apply this approach to infer the molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantification of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.

Abstract 2873: Evolution of immune cell composition and functionality as pancreatic intraepithelial neoplasia progresses to pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is most often diagnosed at an advanced stage. Newly diagnosed patients therefore have a dismal five-year survival rate of 11%. However, PDAC progresses from pre-invasive pancreatic intraepithelial neoplasia (PanIN) over at least a decade. Throughout this transition, the tissue microenvironment becomes increasingly immunosuppressive. Early PanINs may therefore be more amenable to immune-based interception strategies; however, little is known about the pre-malignant lesion immune microenvironment in PDAC. We hypothesized that the identification of the immune landscape of PanINs will elucidate the immuno-dynamic changes that occur during PanIN-to-PDAC progression and identify novel strategies for intercepting PDAC. Here, we use an inducible mouse model to study the evolution of immunosuppression from PanINs to PDAC. We pair spatial molecular profiling of our mouse model with profiling of human tissue in a cohort of patients with normal tissue, chronic pancreatitis, PanIN, and PDAC. To examine the evolution of the immune microenvironment throughout PanIN-to-PDAC progression, we first optimized a tamoxifen-inducible Pdx1-CreERT2 mouse that controls KRASG12D expression and knocks out p53. The impact of KRASG12D expression on the immune cell landscape in PanIN and PDAC lesions was examined by immunohistochemistry (IHC) and RNA in situ hybridization on mouse pancreas. We used imaging mass cytometry (IMC) of 35 immune markers to better classify and quantify the immune cell subtypes. Our analyses thus far reveal increased Tregs as PanINs progress to PDAC. Furthermore, although CD3+ T cells are recruited to tumors, these immune cells are strictly restricted to the immediate edge of the tumor and predominantly consist of Tregs. For our human analyses, FFPE pancreas sections from treatment naïve patients who had undergone surgical resection without neoadjuvant chemotherapy were evaluated. Each section contained regions of normal tissue, chronic pancreatitis, PanIN and PDAC. These were evaluated using IHC, IMC, and spatial transcriptomics to allow us to spatially evaluate the immune populations associated with lesions and PDAC. The relative density and localization of myeloid and lymphoid cell types in both PanIN and PDAC regions revealed an initial influx of CD8+ and CD4+ T cells to PanINs and a progressively immunosuppressive microenvironment in subsequent stages. While PanINs and PDAC both recruited immune cells, the phenotypes of the immune infiltrates were distinct and revealed unique immune pathways that could contribute to immunosuppression as PanINs develop into PDACs. Our proteomic and transcriptomic data from mouse and human pancreas show that mutant KRAS driven premalignant lesions recruit an evolving immune response that readily becomes immunosuppressive as progression to PDAC occurs.

Citation Format: Melissa R. Lyman, Jacob T. Mitchell, Luciane T. Kagohara, Benjamin Barrett, Amanda Huff, Sarah Shin, Gabriella Longway, Anuj Gupta, Lalitya Andaloori, Todd D. Armstrong, Daniel Haldar, Robert Anders, Elizabeth Thompson, Nilo Azad, Won Jin Ho, Elizabeth Jaffee, Elana J. Fertig, Neeha Zaidi. Evolution of immune cell composition and functionality as pancreatic intraepithelial neoplasia progresses to pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2873.

Abstract 5076: Combination PancVAX neo-epitope vaccine with anti-CTLA-4 and anti-PD-1 antibodies enhances infiltration of cytotoxic T cells and mitigates T cell exhaustion in a murine model of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a deadly cancer with a low tumor mutational burden and therefore few neoantigen targets that can be recognized by cytotoxic T cells. Most PDACs are thus insensitive to either single or dual immune checkpoint inhibitor (ICI) therapy. Personalized neoantigen vaccines can expand the number and repertoire of anti-tumor T cells that infiltrate the tumor and mediate cytotoxicity. To model a personalized neoantigen vaccine treatment strategy in PDAC, we previously developed PancVAX, a peptide-based vaccine targeting 12 neoantigens expressed in the murine pancreatic cell line Panc02 (Kinkead et al, JCI Insight 2018). Although we observed increased T cell infiltration present in the tumor post-vaccination, these cells expressed high levels of exhaustion markers. We therefore hypothesized that sequential administration of anti-CTLA-4 and anti-PD-1 would enhance the pool of T cells primed by the neoantigen vaccine and maintain activation of antigen-experienced T cells, respectively, to yield optimal and durable neoantigen-specific anti-tumor immunity in PDAC. To address this, mice bearing subcutaneous Panc02 tumors were vaccinated with two rounds of the PancVAX neoantigen vaccine followed by anti-CTLA-4 and anti-PD-1 3 days later. Anti-PD-1 maintenance was given twice weekly beginning at the first vaccine dose. Twelve days after the last peptide vaccine dose, tumors were harvested and dissociated into single-cell suspensions for paired single-cell RNA-sequencing and TCR-sequencing. Mice that were untreated or given ICIs without PancVAX had the highest proportions of CD8+ T cells expressing exhaustion markers. PancVAX-treated mice had more intratumoral cycling CD8 T cells and effector CD8+ T cells with high cytotoxic gene expression. Among mice treated with PancVAX, tumors from mice treated with PancVAX + anti-PD1 or PancVAX + anti-PD1 + anti-CTLA-4 had the highest proportions of effector CD8+ T cells. Ongoing analyses include differential gene expression and pathway analysis between treatment conditions in the T cell compartment in mice treated with combination ICI and PancVAX. Additionally, we will assess changes in T cell clonality and diversity within the tumors when mice are treated with single or combination therapy. These results will define a transcriptional signature associated with the generation of a productive anti-tumor immune response when neoantigen vaccines and ICI are used in combination. This work demonstrates how the addition of ICIs to personalized neo-epitope vaccines for PDAC can further enhance the quality of vaccine-induced T cell effector function in an otherwise immunologically cold tumor type and supports their inclusion in neoantigen vaccination strategies for patients with PDAC.

Citation Format: Jacob T. Mitchell, Amanda Huff, Emily Davis-Marcisak, Fangluo Chen, Todd D. Armstrong, Luciane T. Kagohara, James Leatherman, Rulin Wang, Srinivasan Yegnasubramanian, Elizabeth M. Jaffee, Elana J. Fertig, Neeha Zaidi. Combination PancVAX neo-epitope vaccine with anti-CTLA-4 and anti-PD-1 antibodies enhances infiltration of cytotoxic T cells and mitigates T cell exhaustion in a murine model of pancreatic ductal adenocarcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5076.

Spatial transcriptomics analysis of neoadjuvant cabozantinib and nivolumab in advanced hepatocellular carcinoma identifies independent mechanisms of resistance and recurrence

Novel immunotherapy combination therapies have improved outcomes for patients with hepatocellular carcinoma (HCC), but responses are limited to a subset of patients and recurrence can also occur. Little is known about the inter- and intra-tumor heterogeneity in cellular signaling networks within the HCC tumor microenvironment (TME) that underlie responses to modern systemic therapy. We applied spatial transcriptomics (ST) profiling to characterize the tumor microenvironment in HCC resection specimens from a clinical trial of neoadjuvant cabozantinib, a multi-tyrosine kinase inhibitor that primarily blocks VEGF, and nivolumab, a PD-1 inhibitor in which 5 out of 15 patients were found to have a pathologic response. ST profiling demonstrated that the TME of responding tumors was enriched for immune cells and cancer associated fibroblasts (CAF) with pro-inflammatory signaling relative to the non-responders. The enriched cancer-immune interactions in responding tumors are characterized by activation of the PAX5 module, a known regulator of B cell maturation, which colocalized with spots with increased B cell markers expression suggesting strong activity of these cells. Cancer-CAF interactions were also enriched in the responding tumors and were associated with extracellular matrix (ECM) remodeling as there was high activation of FOS and JUN in CAFs adjacent to tumor. The ECM remodeling is consistent with proliferative fibrosis in association with immune-mediated tumor regression. Among the patients with major pathologic response, a single patient experienced early HCC recurrence. ST analysis of this clinical outlier demonstrated marked tumor heterogeneity, with a distinctive immune-poor tumor region that resembles the non-responding TME across patients and was characterized by cancer-CAF interactions and expression of cancer stem cell markers, potentially mediating early tumor immune escape and recurrence in this patient. These data show that responses to modern systemic therapy in HCC are associated with distinctive molecular and cellular landscapes and provide new targets to enhance and prolong responses to systemic therapy in HCC.

Abstract 2130: Uncovering the spatial landscape of tumor-immune interactions using latent spaces from spatial transcriptomics

Recent advances in spatial transcriptomics (ST) enable us to measure gene expression from cancer tissues while retaining their spatial context. We present a novel bioinformatics pipeline to infer molecular changes from tumor and immune cell interactions in the tumor microenvironment (TME) from ST data. Latent space methods enable inference of biological patterns from ST without the need for spot deconvolution into cell-based spatial features. While linear latent space methods yield interpretable biological patterns, interactions between tumor and immune cells can be nonlinear. To enable comprehensive inference of the pathways in the TME, we developed novel algorithms to characterize biological patterns from ST data using linear latent space methods and further nonlinear effects from their interactions. For any given set of genes, the patternSpotter tool visualizes the spatial variation in the relative contribution of individual patterns to the aggregate expression at each location in the tumor sample. Application of this tool to latent features identified using CoGAPS non-negative matrix factorization on a Visium ST (10x Genomics) data from a lymph node with pancreatic cancer metastasis confirms its known immune cell architecture. Furthermore, we develop a patternMarker algorithm to identify sets of coexpressed genes associated with the patterns, which help us to pinpoint the underlying biological processes and cell types. Further analyzing a breast cancer sample with invasive carcinoma and multiple precursor lesions demonstrates that this approach can uncover tumor and immune regions without prior reliance on pathology annotations from H&E imaging. In this case, an ensemble-based factorization of multiple dimensions enhances our resolution of intra-tumor heterogeneity and identifies distinct hormone receptor pathways in different precursor lesions with the patternMarker algorithm. Additional latent features are associated with immune cells, revealing further heterogeneity in immune infiltration between the invasive carcinoma and distinct precursor lesions. Still, the molecular interactions resulting from this infiltration induce a further non-linear alteration to transcription not captured through the inferred latent spaces. To resolve this, we develop a further interactionMarker statistic to identify regions of inter-pattern interaction and the associated genes. We apply this approach to detect additional intra-tumor heterogeneity in immune signaling from infiltration suggestive of differences in immune attack of invasive lesions. Altogether, our pipeline for latent space analysis of ST can identify the location and context-specific molecular interactions within the TME, broadly applicable to a better understanding of the key drivers of tumorigenesis and resistance to immune attack in cancer.

Citation Format: Atul Deshpande, Melanie Loth, Dimitrios Sidiropoulos, QingFeng Zhu, Genevieve Stein-O'Brien, NIkhil Rao, Cedric Uytingco, Stephen Williams, Cesar Santa-Maria, Daniele M. Gilkes, Lei Zhang, Elizabeth Jaffee, Robert Anders, Ludmila Danilova, Luciane T. Kagohara, Elana J. Fertig. Uncovering the spatial landscape of tumor-immune interactions using latent spaces from spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2130.

Abstract 3820: Spatial transcriptomics of advanced hepatocellular carcinomas distinguishes intercellular interactions in responders and non-responders to cabozantinib and nivolumab neoadjuvant therapy

The recent development of genome-wide spatial transcriptomics (ST) approaches enable near single-cell gene expression profiling to infer cellular composition and intercellular interactions that drive cancer development and responses to therapy. This study applied ST on 10 surgical biospecimens from a clinical trial with neoadjuvant therapy with cabozantinib (multi-kinase inhibitor) and nivolumab (anti-PD-1 monoclonal antibody) with advanced hepatocellular carcinoma (HCC). Within our cohort, 6 of the samples were obtained from non-responders and 4 with demonstrated pathological response were previously associated with immune infiltration using spatial proteomics technologies. Our analysis with ST was performed to determine the specific pathways that drive immune infiltration in responders and to map intercellular interactions relevant for response and resistance to the combined therapy.Analysis of these data uncovered three main differences between responders and non-responders. First, to better understand the tumor mechanisms of response and resistance, we performed differential expression and pathway analysis only in the subset of tumor clusters from responders versus non-responders. In responders, we observed enrichment for pathways associated with immune response (TNF-alpha, IFN-gamma, T cell differentiation), while in non-responders the deregulated pathways are associated with cell growth, transcriptional activity and hypoxia (Myc, E2F, oxidative phosphorylation). Second, the intercellular interaction analyses indicate that CD8-HLA interactions are more abundant in responders, while interactions activating VEGFR, the main target of cabozantinib, are enriched in non-responders. The interaction profiles are evidence that in responders the tumor cells express tumor specific antigens that are recognized by the cytotoxic cells which activity is enhanced by nivolumab. In non-responders, the activation of the VEGF pathway is an indication that the tumor cells have developed mechanism of resistance to cabozantinib. Third, responding tumors have higher densities of immune and stromal cells, and the immune cells are enriched with aggregates composed of both B and T cells. The regions surrounded by these immune aggregates are transcriptionally distinct from regions enriched for stromal cells, suggesting that tumor gene expression profile drives immune infiltration.Overall, the ST analysis of neoadjuvant HCC treated samples detects tumor induced immune cell immune infiltration in responders compared to non-responders with enrichment of cytotoxic interactions to eliminate the tumor cells. It also identifies intercellular interactions suggestive of resistance to anti-VEGF blockade.

Citation Format: Luciane T. Kagohara, Shuming Zhang, Long Yuan, Qingfeng Zhu, Robert Anders, Daniel Shu, Aleksander S. Popel, Elizabeth M. Jaffee, Mark Yarchoan, Elana J. Fertig. Spatial transcriptomics of advanced hepatocellular carcinomas distinguishes intercellular interactions in responders and non-responders to cabozantinib and nivolumab neoadjuvant therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3820.

Abstract 637: Spatial transcriptomics for FFPE characterizes the molecular and cellular architecture of malignant changes in pancreatic pre-malignant lesions

We have optimized an experimental and computational pipeline to adapt spatial transcriptomics (ST) approaches based upon the Visium (10x Genomics) technology to infer cellular composition and intercellular interactions of FFPE clinical specimens. We apply this technology to deliver an approach to examine pancreatic intraepithelial neoplasia (PanIN) to identify intrinsic and extrinsic mechanisms that are associated with the progression of these pre-malignant lesions to invasive carcinoma. Currently, most pancreatic cancers are diagnosed at an advanced stage that reflects in dismal survival rates and a better understanding of PanINs biology will provide valuable insights for early therapeutic interventions. Thus, we used PanINs as our model system to implement the FFPE ST workflow. Our workflow for FFPE ST analysis facilitates sectioning of small regions (5mm in diameter) from a paraffin block that are stained and imaged with H&E and concurrently measured for genome-wide transcriptional profiling. Subsequently, the image is used for automated cell annotation using an algorithm, CODA, trained to identify normal and neoplastic pancreatic cell types. CODA identified the normal pancreatic histological regions (ducts, acini, islets of Langerhans, stroma), as well as the neoplastic cells. This automated analysis enables isolation of specific spots for differential expression analysis to pinpoint the transcriptional changes that occur within neoplastic cells along ducts in PanIn and their changes between high-grade and low-grade lesions. The spatial gene expression analysis identified clusters that mapped to the cell types annotated by CODA and the marker genes of each cluster matched known markers for the correspondent cell type. Although PanINs are very small in size (< 1mm), we found specific clusters accurately mapped to these lesions in each sample. Overall, the spatial sequencing data presented enough depth and complexity to allow differential expression and pathway analysis. We observed a significant number of deregulated genes in PanINs compared to normal ducts. Some deregulated genes are known PanIN markers, but potential new markers were also identified. Moreover, the integration of CODA with gene expression changes enables us to verify that unique stromal regions annotated with CODA and associated with PanIns are in fact heterogeneous and formed by distinct cell subtypes. Altogether, our workflow combining automated cell annotation with STA from the same section provides a methodology to precisely examine the sample architecture while measuring heterogeneity at the transcriptional level. This combined approach can be applied to different FFPE tumor types to leverage the use of large bioarchives of samples not previously accessible to genome-wide spatial methods.

Citation Format: Alexander T. Bell, Kohei Fujikura, Jacob Stern, Rena Chan, James Chell, Stephen Williams, Ashley Kiemen, Elizabeth M. Jaffee, Denis Wirtz, Laura D. Wood, Elana J. Fertig, Luciane T. Kagohara. Spatial transcriptomics for FFPE characterizes the molecular and cellular architecture of malignant changes in pancreatic pre-malignant lesions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 637.

Entinostat decreases immune suppression to promote anti-tumor responses in a HER2+ breast tumor microenvironment

Therapeutic combinations to alter immunosuppressive, solid tumor microenvironments (TMEs), such as in breast cancer, are essential to improve responses to immune checkpoint inhibitors (ICIs). Entinostat, an oral histone deacetylase inhibitor (HDACi), has been shown to improve responses to ICIs in various tumor models with immunosuppressive TMEs. The precise and comprehensive alterations to the TME induced by entinostat remain unknown. Here, we employed single-cell RNA-sequencing on HER2-overexpressing breast tumors from mice treated with entinostat and ICIs in order to fully characterize changes across multiple cell types within the TME. This analysis demonstrates that treatment with entinostat induced a shift from a pro-tumor to an anti-tumor TME signature, characterized predominantly by changes in myeloid cells. We confirmed myeloid-derived suppressor cells (MDSCs) within entinostat-treated tumors associated with a less suppressive granulocytic (G)-MDSC phenotype and exhibited altered suppressive signaling that involved the NFkB and STAT3 pathways. In addition to MDSCs, tumor-associated macrophages were epigenetically reprogrammed from a pro-tumor M2-like phenotype toward an anti-tumor M1-like phenotype, which may be contributing to a more sensitized TME. Overall, our in-depth analysis suggests that entinostat-induced changes on multiple myeloid cell types reduce immunosuppression and increase anti-tumor responses, which, in turn, improve sensitivity to ICIs. Sensitization of the TME by entinostat could ultimately broaden the population of patients with breast cancer who could benefit from ICIs.

Implantation of a neoantigen-targeted hydrogel vaccine prevents recurrence of pancreatic adenocarcinoma after incomplete resection

Tumor involvement of major vascular structures limits surgical options in pancreatic adenocarcinoma (PDAC), which in turn limits opportunities for cure. Despite advances in locoregional approaches, there is currently no role for incomplete resection. This study evaluated a gelatinized neoantigen-targeted vaccine applied to a grossly positive resection margin in preventing local recurrence. Incomplete surgical resection was performed in mice bearing syngeneic flank Panc02 tumors, leaving a 1 mm rim adherent to the muscle bed. A previously validated vaccine consisting of neoantigen peptides, a stimulator of interferon genes (STING) agonist and AddaVax^TM (termed PancVax) was embedded in a hyaluronic acid hydrogel and applied to the tumor bed. Tumor remnants, regional lymph nodes, and spleens were analyzed using histology, flow cytometry, gene expression profiling, and ELISPOT assays. The immune microenvironment at the tumor margin after surgery alone was characterized by a transient influx of myeloid-derived suppressor cells (MDSCs), prolonged neutrophil influx, and near complete loss of cytotoxic T cells. Application of PancVax gel was associated with enhanced T cell activation in the draining lymph node and expansion of neoantigen-specific T cells in the spleen. Mice implanted with PancVax gel demonstrated no evidence of residual tumor at two weeks postoperatively and healed incisions at two months postoperatively without local recurrence. In summary, application of PancVax gel at a grossly positive tumor margin led to systemic expansion of neoantigen-specific T cells and effectively prevented local recurrence. These findings support further work into locoregional adjuncts to immune modulation in PDAC.

From bench to bedside: Single-cell analysis for cancer immunotherapy

Single-cell technologies are emerging as powerful tools for cancer research. These technologies characterize the molecular state of each cell within a tumor, enabling new exploration of tumor heterogeneity, microenvironment cell-type composition, and cell state transitions that affect therapeutic response, particularly in the context of immunotherapy. Analyzing clinical samples has great promise for precision medicine but is technically challenging. Successfully identifying predictors of response requires well-coordinated, multi-disciplinary teams to ensure adequate sample processing for high-quality data generation and computational analysis for data interpretation. Here, we review current approaches to sample processing and computational analysis regarding their application to translational cancer immunotherapy research.

Extracellular Vesicles Released by Tumor Endothelial Cells Spread Immunosuppressive and Transforming Signals Through Various Recipient Cells

Head and neck squamous cell carcinoma (HNSCC) has a high recurrence and metastatic rate with an unknown mechanism of cancer spread. Tumor inflammation is the most critical processes of cancer onset, growth, and metastasis. We hypothesize that the release of extracellular vesicles (EVs) by tumor endothelial cells (TECs) induce reprogramming of immune cells as well as stromal cells to create an immunosuppressive microenvironment that favor tumor spread. We call this mechanism as non-metastatic contagious carcinogenesis. Extracellular vesicles were collected from primary HNSCC-derived endothelial cells (TEC-EV) and were used for stimulation of peripheral blood mononuclear cells (PBMCs) and primary adipose mesenchymal stem cells (ASCs). Regulation of ASC gene expression was investigated by RNA sequencing and protein array. PBMC, stimulated with TEC-EV, were analyzed by enzyme-linked immunosorbent assay and fluorescence-activated cell sorting. We validated in vitro the effects of TEC-EV on ASCs or PBMC by measuring invasion, adhesion, and proliferation. We found and confirmed that TEC-EV were able to change ASC inflammatory gene expression signature within 24-48 h. TEC-EV were also able to enhance the secretion of TGF-β1 and IL-10 by PBMC and to increase T regulatory cell (Treg) expansion. TEC-EV carry specific proteins and RNAs that are responsible for Treg differentiation and immune suppression. ASCs and PBMC, treated with TEC-EV, enhanced proliferation, adhesion of tumor cells, and their invasion. These data indicate that TEC-EV exhibit a mechanism of non-metastatic contagious carcinogenesis that regulates tumor microenvironment and reprograms immune cells to sustain tumor growth and progression.

Abstract 1555: Single cell level treatment-specific characterization of HER2+ breast cancers treated with immune checkpoint inhibitors and entinostat

HER2+ breast cancers are known to be less-immunogenic and associated with low response rates to ICIs such as anti-PD-1, anti-PDL-1 or anti-CTLA-4. A combination of immunosuppressive signals that prevent cytotoxic T cells from infiltrating the tumor microenvironment (TME) and low tumor antigen expression contribute to immunotherapy resistance in this population. Epigenetic modulators can both reexpress tumor antigens and rewire the immunosuppressive environment. We previously used a benzamide histone deacetylase inhibitor, entinostat, in combination with ICIs to reverse the immunosuppressive TME and increase tumor antigen expression in a NeuN HER2+ mouse model of breast cancer. Our results showed that entinostat in combination with anti-PD-1, anti-CTLA-4, or both provided a significant survival benefit compared to either treatment alone. This current study employs single cell RNA-seq on whole tumor samples from mice treated with ICIs and entinostat to investigate the role of epigenetic inhibitors in rewiring the expression of tumor antigens and the cellular landscape of the TME. We generate single cell data of over 54,000 cells from 20 tumors treated with entinostat alone or in combination with anti-PD-1 and anti-CTLA-4 and their combination. Analysis of cells in the TME identifies consistent proportion of monocytes, macrophages, T-cells, Myeloid Derived Suppressor Cells (MDSCs) and Cancer Associated Fibroblasts (CAFs) before and after treatment. Differential expression analysis within the cell types identifies distinct subpopulations and we explore those that are either proportionally higher or lower in each treatment group. Notably, pathway analysis on differentially expressed genes of each cell type identified that combination entinostat and checkpoint treatment increased T cell activation, leukocyte proliferation, myeloid leukocyte and neutrophil migration, and decreased Wnt signaling and histone modifications in tumor cells. Further analysis of the tumor cells from these data and additional ATAC-seq data will enable us to further test the role of antigen reexpression in this TME of activated tumors. We also used the CoGAPS matrix factorization algorithm and RNA velocity analysis to identify transcriptional patterns that are enriched in response to combination treatment. Our current work provides insights into the transcriptional network within a breast tumor after treatment with entinostat. Our follow-up studies in patient samples from a corresponding clinical trial will allow us to map the role of epigenetic modulation in breast tumors. We predict our findings will bring us closer to identifying additional therapeutic targets and ultimately improve survival rates of patients with less-immunogenic tumors. NCT02453620.

Citation Format: Dimitrios N. Sidiropoulos, Emily Davis-Marcisak, Christine Rafie, Luciane T. Kagohara, Gaurav Sharma, Roisin M. Connolly, Vered Stearns, Srinivasan Yegnasubramanian, Elizabeth M. Jaffee, Elana J. Fertig, Evanthia T. Roussos Torres. Single cell level treatment-specific characterization of HER2+ breast cancers treated with immune checkpoint inhibitors and entinostat [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1555.

Abstract 3024: Transcriptional and epigenetic regulation of resistance markers in cetuximab sensitive HNSCC cells

Acquired resistance is pervasive in cancers treated with targeted therapies. The understanding of resistance mechanisms and the timing of the driver molecular changes are crucial for alternative interventions while tumors are sensitive. In this study, we focus on cetuximab, the only targeted therapeutic approved to treat head and neck cancers (HNSCC). We and others have shown that signatures of resistance arise in early sensitive states of treatment, including notably EMT and TFAP2 activation. Because TFAP2 regulates both EMT genes and compensatory growth factor receptors and resistance is associated with epigenetic alterations, we hypothesized that epigenetic regulation of TFAP2 is a master regulator of future mechanisms of resistance.To test our central hypothesis, we treated three HNSCC cell lines (SCC1, SCC6 and SCC25) with CTX for 5 days, a time frame that cells are known to be sensitive. We performed RNA-seq and ATAC-seq to understand the global molecular changes induced by CTX. To verify the role of TFAP2A in cell growth and EMT control in response to CTX, we used siRNA for gene silencing and measured cell proliferation and migration ability (scratch assay). In order to identify a potential combination therapy, we also treated the cells with JQ1, a bromodomain inhibitor with a major impact in delaying acquired CTX resistance.RNA-seq analysis shows that CTX sensitive cells up-regulate growth factor receptors and EMT genes. Chromatin changes were also evident in the same cells. Enrichment of accessible chromatin areas for genes from the TFAP2A and EMT pathways suggests epigenetic regulation of CTX resistance associated genes as an early response to therapy. In both, RNA-seq and ATAC-seq analysis, we observed alterations in different sets of genes for each of the cell lines, indicating that resistance signatures vary in the cell models as observed in patients. TFAP2A plays a pivotal role in cell growth. Lack of TFAP2A results in lower proliferation rates in untreated cells and a synergistic effect is observed with CTX, JQ1 and CTX + JQ1 therapies. TFAP2A loss reflected in increased migration ability in SCC1 and SCC25, while in SCC6 we observed less cell motility. However, in all cell lines EMT markers were up-regulated and suggests EMT development, due to down-regulation of TFAP2A, is a cell type and time dependent mechanism with specific cell types requiring more time to translate the transcriptional changes.Overall, we demonstrate that resistance-associated genes in HNSCC sensitive cells are epigenetically regulated. These mechanisms are also cell type and time dependent reflecting observations from patients’ cohorts. We show that TFAP2A regulates growth factor receptors and EMT genes in CTX sensitive cells and could be a potential target for drug development. We also show that the CTX + JQ1 combined therapy is a potential alternative and more effective approach while patients are sensitive to therapy.

Citation Format: Luciane T. Kagohara, Fernando Zamuner, Michael Considine, Genevieve Stein-O'Brien, Thomas Sherman, Daria A. Gaykalova, Elana J. Fertig. Transcriptional and epigenetic regulation of resistance markers in cetuximab sensitive HNSCC cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3024.

Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer

Motivation

Current bioinformatics methods to detect changes in gene isoform usage in distinct phenotypes compare the relative expected isoform usage in phenotypes. These statistics model differences in isoform usage in normal tissues, which have stable regulation of gene splicing. Pathological conditions, such as cancer, can have broken regulation of splicing that increases the heterogeneity of the expression of splice variants. Inferring events with such differential heterogeneity in gene isoform usage requires new statistical approaches.

Results

We introduce Splice Expression Variability Analysis (SEVA) to model increased heterogeneity of splice variant usage between conditions (e.g. tumor and normal samples). SEVA uses a rank-based multivariate statistic that compares the variability of junction expression profiles within one condition to the variability within another. Simulated data show that SEVA is unique in modeling heterogeneity of gene isoform usage, and benchmark SEVA's performance against EBSeq, DiffSplice and rMATS that model differential isoform usage instead of heterogeneity. We confirm the accuracy of SEVA in identifying known splice variants in head and neck cancer and perform cross-study validation of novel splice variants. A novel comparison of splice variant heterogeneity between subtypes of head and neck cancer demonstrated unanticipated similarity between the heterogeneity of gene isoform usage in HPV-positive and HPV-negative subtypes and anticipated increased heterogeneity among HPV-negative samples with mutations in genes that regulate the splice variant machinery. These results show that SEVA accurately models differential heterogeneity of gene isoform usage from RNA-seq data.

Availability and implementation

SEVA is implemented in the R/Bioconductor package GSReg.

Contact

bahman@jhu.edu or favorov@sensi.org or ejfertig@jhmi.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer

Bioinformatics techniques to analyze time course bulk and single cell omics data are advancing. The absence of a known ground truth of the dynamics of molecular changes challenges benchmarking their performance on real data. Realistic simulated time-course datasets are essential to assess the performance of time course bioinformatics algorithms. We develop an R/Bioconductor package, CancerInSilico, to simulate bulk and single cell transcriptional data from a known ground truth obtained from mathematical models of cellular systems. This package contains a general R infrastructure for running cell-based models and simulating gene expression data based on the model states. We show how to use this package to simulate a gene expression data set and consequently benchmark analysis methods on this data set with a known ground truth. The package is freely available via Bioconductor: http://bioconductor.org/packages/CancerInSilico/

Epigenetic regulation of gene expression in cancer: techniques, resources and analysis

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in even individual malignant cells. Epigenetic changes are critical mediators of these functional changes that drive and maintain the malignant phenotype. Changes in DNA methylation, histone acetylation and methylation, noncoding RNAs, posttranslational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations were once thought to be crucial only for the malignant phenotype maintenance. Now, epigenetic alterations are also recognized as critical for disrupting essential pathways that protect the cells from uncontrolled growth, longer survival and establishment in distant sites from the original tissue. In this review, we focus on DNA methylation and chromatin structure in cancer. The precise functional role of these alterations is an area of active research using emerging high-throughput approaches and bioinformatics analysis tools. Therefore, this review also describes these high-throughput measurement technologies, public domain databases for high-throughput epigenetic data in tumors and model systems and bioinformatics algorithms for their analysis. Advances in bioinformatics data that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer. These integrative algorithms are also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations during tumor initiation and progression. This deeper understanding is essential to future studies with epigenetics biomarkers and precision medicine using emerging epigenetic therapies.

Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance

Background

Targeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients’ treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors.

Methods

To determine the dynamics of these molecular changes, we obtained high throughput omics data (RNA-sequencing and DNA methylation) weekly during the development of cetuximab resistance in a head and neck cancer in vitro model. The CoGAPS unsupervised algorithm was used to determine the dynamics of the molecular changes associated with resistance during the time course of resistance development.

Results

CoGAPS was used to quantify the evolving transcriptional and epigenetic changes. Applying a PatternMarker statistic to the results from CoGAPS enabled novel heatmap-based visualization of the dynamics in these time course omics data. We demonstrate that transcriptional changes result from immediate therapeutic response or resistance, whereas epigenetic alterations only occur with resistance. Integrated analysis demonstrates delayed onset of changes in DNA methylation relative to transcription, suggesting that resistance is stabilized epigenetically.

Conclusions

Genes with epigenetic alterations associated with resistance that have concordant expression changes are hypothesized to stabilize the resistant phenotype. These genes include FGFR1, which was associated with EGFR inhibitors resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. This understanding of the time course progression of molecular changes in acquired resistance is important for the development of alternative treatment strategies that would introduce appropriate selection of new drugs to treat cancer before the resistant phenotype develops.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0545-2) contains supplementary material, which is available to authorized users.

CoGAPS matrix factorization algorithm identifies transcriptional changes in AP-2alpha target genes in feedback from therapeutic inhibition of the EGFR network

Patients with oncogene driven tumors are treated with targeted therapeutics including EGFR inhibitors. Genomic data from The Cancer Genome Atlas (TCGA) demonstrates molecular alterations to EGFR, MAPK, and PI3K pathways in previously untreated tumors. Therefore, this study uses bioinformatics algorithms to delineate interactions resulting from EGFR inhibitor use in cancer cells with these genetic alterations. We modify the HaCaT keratinocyte cell line model to simulate cancer cells with constitutive activation of EGFR, HRAS, and PI3K in a controlled genetic background. We then measure gene expression after treating modified HaCaT cells with gefitinib, afatinib, and cetuximab. The CoGAPS algorithm distinguishes a gene expression signature associated with the anticipated silencing of the EGFR network. It also infers a feedback signature with EGFR gene expression itself increasing in cells that are responsive to EGFR inhibitors. This feedback signature has increased expression of several growth factor receptors regulated by the AP-2 family of transcription factors. The gene expression signatures for AP-2alpha are further correlated with sensitivity to cetuximab treatment in HNSCC cell lines and changes in EGFR expression in HNSCC tumors with low CDKN2A gene expression. In addition, the AP-2alpha gene expression signatures are also associated with inhibition of MEK, PI3K, and mTOR pathways in the Library of Integrated Network-Based Cellular Signatures (LINCS) data. These results suggest that AP-2 transcription factors are activated as feedback from EGFR network inhibition and may mediate EGFR inhibitor resistance.

Epigenetic regulation of gene expression in cancer: techniques, resources and analysis

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in even individual malignant cells. Epigenetic changes are critical mediators of these functional changes that drive and maintain the malignant phenotype. Changes in DNA methylation, histone acetylation and methylation, noncoding RNAs, posttranslational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations were once thought to be crucial only for the malignant phenotype maintenance. Now, epigenetic alterations are also recognized as critical for disrupting essential pathways that protect the cells from uncontrolled growth, longer survival and establishment in distant sites from the original tissue. In this review, we focus on DNA methylation and chromatin structure in cancer. The precise functional role of these alterations is an area of active research using emerging high-throughput approaches and bioinformatics analysis tools. Therefore, this review also describes these high-throughput measurement technologies, public domain databases for high-throughput epigenetic data in tumors and model systems and bioinformatics algorithms for their analysis. Advances in bioinformatics data that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer. These integrative algorithms are also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations during tumor initiation and progression. This deeper understanding is essential to future studies with epigenetics biomarkers and precision medicine using emerging epigenetic therapies.

Abstract 05: Untangling the gene-epigenome networks: Timing of epigenetic regulation of gene expression in acquired cetuximab resistance gene programs

The current study performs time course RNA-seq and DNA methylation profiling to determine the complex interactions between gene expression and epigenetic changes in acquired therapeutic resistance. The genomics era provides widespread characterization of the genomic landscape of tumors and has enabled precision treatment strategies. Currently, epidermal growth factor receptor (EGFR) inhibitors are the only FDA-approved targeted therapy for clinical use in head and neck squamous cell carcinoma (HNSCC). EGFR inhibitors are only effective in a subset of each of these tumors. Moreover, patients with de novo sensitivity to EGFR inhibitors often subsequently acquire resistance and succumb to their tumors. Numerous genetic and epigenetic alterations occur in tumors with acquired resistance. However, their timing and function remain unknown. Therefore, we develop new computational techniques to find gene programs associated with the acquisition of resistance.

High-throughput transcriptional profiling enables unprecedented characterization of individual genes during cancer treatment. However, identifying and targeting mechanisms of EGFR resistance from these high-throughput data requires novel systems biology techniques that can discriminate altered cellular signaling pathways in response to cancer treatment. Therefore, we developed a new bioinformatics algorithm Coordinated Gene Activity in Pattern Sets (CoGAPS) to quantify multiplexed regulation and gene reuse in oncogenic signaling. To test this algorithm, we modified the HaCaT keratinocyte cell line model of premalignancy to simulate cancer cells with constitutive overexpression of wild-type EGFR and with activating mutations in HRAS and PIK3CA in a controlled genetic background. We apply CoGAPS to gene expression data from these models. This algorithm quantified relative changes in cellular signaling pathway activity in these data, not accessible to standard gene comparisons. Increases in CoGAPS pathway signatures from HRAS also occurred in gene expression data from the cetuximab resistant HNSCC cell line (1CC8) relative to its parental, sensitive cell line (UMSCC1).

Investigation of the mechanisms of acquired resistance has previously been limited by reliance on case-control comparisons between sensitive and resistant cells, such as the UMSCC1 and 1CC8 cell lines. Since activity in cellular signaling pathways evolves during cetuximab resistance, it is essential to extend these case-control paradigms to quantify the dynamics responsible for resistance. Therefore, we developed a novel time course analysis to determine the molecular mechanisms of acquired cetuximab resistance in HNSCC. Specifically, we treated the cetuximab sensitive SCC25 HNSCC cell line over generations with both cetuximab and PBS. This long-term treatment protocol models the progression of acquired therapeutic resistance, including controls for clonal selection unrelated to treatment. Overexpression of the previous HRAS gene program also occurs in gene expression data measured during acquired cetuximab resistance in SCC25. We also measure DNA methylation during this time course to find the driver of this aberrant signaling associated with resistance. We apply CoGAPS analysis to the time course data for both DNA methylation and gene expression. This analysis distinguished early gene expression changes from cetuximab treatment from longer-term epigenetic alterations to gene expression during acquired resistance. Epigenetic regulation of FGFR1 expression emerged as the dominant mechanism of acquired therapeutic resistance in this system. Thus, our integration of time course DNA methylation and gene expression data enables unprecedented inference of the timing of targetable gene-epigenome programs responsible for acquired resistance.

Citation Format: Genevieve Stein-O'Brien, Luciane T. Kagohara, Sijia Li, Manjusha Thakar, Ruchira Ranaweera, Michael Considine, Ludmila V. Danilova, Hiroyuki Ozawa, Joseph A. Califano, Daria A. Gaykalova, Michael F. Ochs, Christine H. Chung, Elana J. Fertig. Untangling the gene-epigenome networks: Timing of epigenetic regulation of gene expression in acquired cetuximab resistance gene programs [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; April 23-25, 2017; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(23_Suppl):Abstract nr 05.

KRAS mutation status is highly homogeneous between areas of the primary tumor and the corresponding metastasis of colorectal adenocarcinomas: one less problem in patient care

Background: Mutations in KRAS are negative predictors of the response to anti-EGFR therapies in the treatment of metastatic colorectal cancer. Yet, the ideal tissue to test for KRAS mutation-primary or metastatic-remains unknown, as is the validity of testing only 1 area of the primary tumor. The aim of this study was to determine the heterogeneity of KRAS mutational status between areas of the primary lesion and between paired primary CRC and the corresponding lymph node (LN), liver, and lung metastasis with a high-sensitivity sequencing method. Design: DNA from 2 or 3 areas from the primary tumor and 1 area of metastatic tissue was obtained from formalin-fixed paraffin-embedded specimens from 102 metastatic CRC patients. Mutations in KRAS codons 12, 13, and 61 were analyzed by pyrosequencing.

RESULTS

Ninety-one cases had DNA extracted from more than 1 area of the primary tumor. Only 1 patient showed intratumor heterogeneity, which involved KRAS mutation type, not KRAS mutational status. We examined KRAS mutations in 97 primaries and matched metastatic samples, recording 2 discordant cases, representing 2.1% of our cohort of matched samples. Conclusion:KRAS status is highly homogeneous throughout primary CRC tumor areas and consistent between the primary tumor and metastatic tissue in the same patient. Our data suggest that testing KRAS mutations in only 1 area of the primary or metastatic tissue is suitable for predicting the response to anti-EGFR treatment and guiding clinical decisions.

Abstract 86: Time course analysis of gene expression and epigenetic interactions in acquired cetuximab resistance in head and neck squamous cell carcinoma

The current study performs time course genomics and epigenomics profiling to determine the complex dynamics of interactions between gene expression and epigenetic changes that alter cellular signaling and drive acquired therapeutic resistance. Targeted therapeutic agents block the activity of specific molecules critical for tumor progression. Cetuximab is a monoclonal antibody against EGFR currently used in the treatment of head and neck squamous cell carcinoma (HNSCC) and metastatic colorectal cancers. Similar to many targeted therapeutics, cetuximab improves survival for a brief period of two years, after which most patients acquire resistance resulting in tumor progression or recurrence. The mechanisms that alter cellular signaling pathways and cause resistance are poorly understood. We hypothesize that the molecular alterations that precede the resistance phenotype are more likely to be responsible for the resistance than the widespread alterations observed once the resistance is established. To test this hypothesis, we develop a novel time course experimental and bioinformatics model of acquired resistance. Specifically, this protocol enables weekly profiling of RNA, DNA, and proliferation as cetuximab resistance developed in vitro. We apply the CoGAPS bioinformatics algorithm to perform integrated analysis of gene expression and DNA methylation. This analysis distinguishes signatures of sustained activation of cellular pathways in response to treatment from signatures of clonal expansion associated with acquired cetuximab resistance. Despite identifying massive changes in gene expression driven by therapeutic response, only the expression changes associated with the acquired resistance, and not response to treatment, have corresponding epigenetic signatures. The genomic signature associated with acquired resistance is enriched for gene targets of the AP-2 family of transcription factors. In a previous study, we found that these gene targets were overexpressed after short-term treatment in cetuximab sensitive cell lines and HNSCC tumors. Our data suggest that this family of transcription factors serves as a feedback mechanism to maintain homeostasis to growth factors receptor signaling. As a result, AP-2 transcription factors serve as a natural mechanism to cause subsequent therapeutic resistance without addition of genetic alterations. Further investigation is needed to determine the role of AP-2 transcription factors in acquired cetuximab resistance.

Citation Format: Luciane T. Kagohara, Genevieve Stein-O'Brien, Sijia Li, Manjusha Thakar, Ruchira Ranaweera, Michael Considine, Joseph A. Califano, Christine H. Chung, Daria Gaykalova, Elana J. Fertig. Time course analysis of gene expression and epigenetic interactions in acquired cetuximab resistance in head and neck squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 86. doi:10.1158/1538-7445.AM2017-86

Comparative mutational landscape analysis of patient-derived tumour xenografts

Background:

Screening of patients for cancer-driving mutations is now used for cancer prognosis, remission scoring and treatment selection. Although recently emerged targeted next-generation sequencing-based approaches offer promising diagnostic capabilities, there are still limitations. There is a pressing clinical need for a well-validated, rapid, cost-effective mutation profiling system in patient specimens. Given their speed and cost-effectiveness, quantitative PCR mutation detection techniques are well suited for the clinical environment. The qBiomarker mutation PCR array has high sensitivity and shorter turnaround times compared with other methods. However, a direct comparison with existing viable alternatives are required to assess its true potential and limitations.

Methods:

In this study, we evaluated a panel of 117 patient-derived tumour xenografts by the qBiomarker array and compared with other methods for mutation detection, including Ion AmpliSeq sequencing, whole-exome sequencing and droplet digital PCR.

Results:

Our broad analysis demonstrates that the qBiomarker's performance is on par with that of other labour-intensive and expensive methods of cancer mutation detection of frequently altered cancer-associated genes, and provides a foundation for supporting its consideration as an option for molecular diagnostics.

Conclusions:

This large-scale direct comparison and validation of currently available mutation detection approaches is extremely relevant for the current scenario of precision medicine and will lead to informed choice of screening methodologies, especially in lower budget conditions or time frame limitations.

Abstract 452: MIC-1 and Endoglin are protein serum biomarkers capable of increasing the clinical diagnostic specificity of the PSA test

PSA test and digital rectal examination have been routinely used to screen for prostate cancer (PCa). PSA screening revolutionized the management of PCa, especially with regards to early detection. Before the PSA test was available, ∼20% of men were diagnosed with PCa that had already spread to the bone. Today, that number is around 4%. However, it is estimated that 56% of the cases are overdiagnosed resulting in overtreatment and exposing the patients to serious unnecessary treatment morbidities. Also the rate of false-positives is incredibly high (60-80%), since PSA is not cancer specific. It is critical to discriminate clinically significant PCa patients requiring definitive treatment from those who would safely undergo active surveillance monitoring.

The aim of this project is to identify and incorporate multiple serum protein biomarkers into an assay that will enhance the clinical diagnostic specificity of the PSA screening test. Using ELISA, we analyzed protein serum levels of Endoglin, IL-8 and MIC-1 in samples obtained from 50 PCa patients and 50 non-cancer individuals. ROC curve analysis was used to determine if these biomarkers were capable of separating the 2 groups. Multivariate logistic regression (MLR) was used to identify a panel of biomarkers that combined to PSA would increase the test specificity.

MIC-1 was the only biomarker capable of discriminating PCa from normal cases (AUC = 0.76; p<0.0001). Endoglin protein levels were significantly different (p = 0.0010) between the groups, although the AUC was borderline (AUC = 0.69) to our cut-off (AUC>0.7) it suggests a good potential for this protein as a biomarker in PCa diagnosis. IL-8 did not show significant differences (p = 0.1828) in the levels detected between cancer and normal samples. The expression of these proteins were also evaluated for their prognostic association with clinical-pathological features: Gleason Score (GS), T and N stage. MIC-1 protein levels was capable to separate GS 3+3 and 3+4 from those 4+3 or higher (AUC = 0.73), suggesting that this biomarker might be associated with more aggressive cases. Using MLR, we identified Endoglin, MIC-1 and PSA as a multiple biomarker panel that enhanced specificity of the PSA screening test. The panel resulted in an assay with 88% specificity and 86% sensitivity that is slightly higher than PSA alone (82% specificity; 84% sensitivity). Our results suggest that MIC-1 is a strong candidate as a biomarker for cancer screening and disease aggressiveness. We also showed that when PSA test is combined with the presence of MIC-1 and Endoglin in serum, it resulted in an assay with higher specificity and sensitivity than when these biomarkers are evaluated alone. To validate these results, protein serum levels of Endoglin, MIC-1 and IL-8 will be determined in a bigger cohort of normal and PCa patients. Other biomarkers are also being evaluated.

Citation Format: Luciane T. Kagohara, Ji Li, Christian P. Pavlovich, Christine Davis, Leslie Mangold, Guangjing Zhu, Colm Morrissey, Alan W. Partin, Wlodeck Mandecki, Robert W. Veltri. MIC-1 and Endoglin are protein serum biomarkers capable of increasing the clinical diagnostic specificity of the PSA test. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 452.

Targeted sequencing reveals clonal genetic changes in the progression of early lung neoplasms and paired circulating DNA

Lungs resected for adenocarcinomas often harbour minute discrete foci of cytologically atypical pneumocyte proliferations designated as atypical adenomatous hyperplasia (AAH). Evidence suggests that AAH represents an initial step in the progression to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and fully invasive adenocarcinoma. Despite efforts to identify predictive markers of malignant transformation, alterations driving this progression are poorly understood. Here we perform targeted next-generation sequencing on multifocal AAHs and different zones of histologic progression within AISs and MIAs. Multiregion sequencing demonstrated different genetic drivers within the same tumour and reveal that clonal expansion is an early event of tumorigenesis. We find that KRAS, TP53 and EGFR mutations are indicators of malignant transition. Utilizing droplet digital PCR, we find alterations associated with early neoplasms in paired circulating DNA. This study provides insight into the heterogeneity of clonal events in the progression of early lung neoplasia and demonstrates that these events can be detected even before neoplasms have invaded and acquired malignant potential.

Atypical adenomatous hyperplasia is thought to be a precursor lesion for lung adenocarcinoma. Here, using targeted deep sequencing, the authors demonstrate that hyperplastic lesions contain somatic mutations associated with malignant disease and that these can be detected in circulating tumour cells.

Abstract 4826: Cancer/testis antigen expression pattern is a potential biomarker for prostate cancer aggressiveness

Introduction: The prostate-specific antigen (PSA) test has improved the early detection of PCa and also recurrence after radical prostatectomy (RP). However, it is estimated that 35% of patients submitted to RP that progress with detectable PSA levels will never present metastatic disease. Thus, there is a need to distinguish localized curable disease from a subset of patients at risk for progression. Currently, the D’Amico Stratification System defines high risk PCa as any combination of the following factors: PSA >20ng/ml, a Gleason score (GS) of 8-10, or clinical stage T2c or greater. As some aggressive PCa did not fit these criteria, a more accurate test to classify high risk patients is crucial.

Objective: The objective of this study is to identify a cancer/testis antigen (CTA)-based biomarker to discern PCa patients with potentially aggressive disease. The CTAs are a unique group of genes whose expression is normally confined to germ cells in normal testis and placenta, but aberrantly expressed in several types of cancers.

Methods and results: Using Nanostring multiplex approach, we screened the expression of 22 CTA genes in 20 localized (LPCa) and 20 metastatic prostate cancer (MPCa) samples, obtained from University of Washington. Using ROC curve analysis we ranked the CTAs capable of discriminating LPCa and MPCa. We found one under-expressed CTA (PAGE4) and seven over-expressed (CEP55, NUF2, PBK, RQCD1, SPAG4, SSX2 and TTK) in MPCa, considering AUC>0.70. qRT-PCR was used to validate Nanostring results in the same set of samples and to identify the candidate CTA biomarkers. The eight CTAs selected showed significant expression changes and were also capable of separating LPCa and MPCa cases (AUC>0.70). A multivariate logistic regression model (MLR) showed that combined expression patterns of CEP55, NUF2, PBK and TTK was capable of discriminating MPCa from LPCa with AUC = 0.95 (pr = 0.15), sensitivity = 80%, specificity = 90%. Using this model 85% of the PCa cases were correctly classified. We then evaluated, by q-RT-PCR, if CTA expression profile is associated with GS using the same 20 LPCa samples and a new set of 25 PCa samples. The PCa cases were separated in two groups according to GS: (1) 3+3/3+4 and (2) other GS. The expression pattern of the CTA panel CEP55, NUF2 and RQCD1 correctly separated 83% of the samples according to the GS with AUC = 0.89 (pr = 0.05), sensitivity = 88%, specificity 75%.

Conclusion: The results of the study are clinically and biologically relevant, since little is known about the role of CTAs in PCa. The CTA expression pattern was shown to be different between two extreme pathologic phenotypes and also among samples of different GS. The CTA profile may be useful to identify high risk LPCa patients and to stratify patients according to GS, which may guide treatment strategies for the different groups of patients.

Citation Format: Luciane T. Kagohara, Prakash Kulkarni, Takumi Shiraishi, Guangjing Zhu, Robert Vessella, Robert Veltri. Cancer/testis antigen expression pattern is a potential biomarker for prostate cancer aggressiveness. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4826. doi:10.1158/1538-7445.AM2015-4826

Abstract 527: Analysis of the interaction between microRNAs and Notch pathway members in HNSCC (head and neck squamous cell carcinoma)

Head and neck squamous cell carcinomas (HNSCC) have poor prognosis due in part to diagnosis in advanced stages. Also, little progress on treatment modalities has been observed in the last decades. Identification of early detection molecular markers and new targets for therapy can bring important benefits for HNSCC patients’ survival. Recently, inactivating mutations in the NOTCH1 gene were described as the most frequent after TP53, suggesting an important role of this gene as a tumor suppressor in HNSCC. Another important alteration for HNSCC tumorigenesis is the de-regulated expression of microRNAs (miRs), small molecules known to negatively regulate their target mRNAs. Many studies trying to understand the biogenesis and mechanisms of miRs on gene expression regulation have proved this class of nucleic acids to be a good target for the identification of new biomarkers. In this study, we evaluate possible interactions between miR and the Notch pathway in HNSCC. To identify differentially expressed genes from Notch pathway and those miRs predicted to target components from this pathway, we performed mRNA and miR expression profiling of 44 HNSCC samples and 25 normal samples. Expression patterns were then validated in an independent cohort of 55 HNSCC tumors and 18 normal samples, using qRT-PCR. Microarray data analysis showed significant altered expression of 3 Notch pathway components: up-regulation of JAG1 and MAML1, and down-regulation of NUMBL. After identification of differentially expressed miRs, using online prediction tools, we selected the miRs expected to regulate these genes: miR-23a (MAML1), miR-26a (JAG1, MAML1), miR-146a (NUMBL), and let-7g (NUMBL). All four miRs were down-regulated in the 20 HN cell lines evaluated. Expression analysis in the independent cohort confirmed up-regulation of JAG1 in tumors. miRs expression evaluation confirmed miR-23a up-regulation in HNSCC samples. Forced expression of miR-23a (mimic) resulted in reduced cell proliferation in HN cancer cell lines. Our results suggest that miR-23a plays an important role in HNSCC and may be participating in Notch pathway regulation. To assess this interaction, mRNA expression analysis of members of Notch pathway before and after miR-23a overexpression on the cell lines is ongoing. We are also underway of comparing all the molecular changes observed in the HNSCC samples to demographic and clinicopathological variables to further evaluate Notch pathway alterations as well as miRs as potential HNSCC molecular markers.

Citation Format: Myriam Loyo, Luciane T. Kagohara, Wenyue Sun, Marietta Tan, Elana Fertig, Michael Ochs, Evgeny Izumchenko, Mariana Brait, Joseph Califano, David Sidransky. Analysis of the interaction between microRNAs and Notch pathway members in HNSCC (head and neck squamous cell carcinoma). [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 527. doi:10.1158/1538-7445.AM2014-527

Abstract 4284: Evaluation of cancer-related mutations in tumorgraft models

Personalized TumorGraft models are generated from tumor fragments resected from patients with refractory advanced cancers that are implanted and propagated in immunodeficient mice. They maintain the genetic characteristics of the original tumor and can potentially be used for individualized therapy selection.

We used samples from 120 TumorGrafts to analyze genetic changes (353 mutations and 31 copy number assays) with a customized Qiagen qBiomarker Somatic mutation PCR array. We chose the alterations to be analyzed based on the recent and classic literature data on significant known somatic mutations in cancer, either with biological or therapy response relevance in different cancer types (prioritizing lung and colorectal tumors). Our models consisted of: 39 colorectal cancer samples, 30 pancreatic cancers, 25 non-small cell lung cancers (NSCLC), 11 melanomas, 7 ovarian cancers, 4 breast cancers, and 4 small cell lung cancers. Among our 120 samples, 22% (26) did not show any of the analyzed mutations or deletions, 78% (94) showed at least one mutation, and of those: 56 had 2 or more mutations (44%). In colorectal tumors, the most frequently observed mutation was Kras, followed by p53, and PIK3CA. Among NSCLC: p53, PIK3CA, deletion of p16 and mutation of Kras. In melanoma: Braf and deletion of p16. All 30 cases of pancreatic cancer showed mutations, being Kras the most frequent, followed by p16 deletion and p53 mutation. On the other tumor types, not more than three samples displayed the same mutation. A subgroup of the samples (95) was validated for mutations with other two techniques: conventional Sanger sequencing and/or IonAmpliseq Cancer panel (a panel of key cancer related genes, Life Technologies). 56/69 (81%) cases had the same mutation(s) detected by two or three techniques simultaneously. Three samples were concordantly wild type for the evaluated genes by three or two techniques. Comparison of the genetic alterations with the demographic and clinicopathological data available for these samples (including tumor stage, therapy response, patient's gender and age) is underway to evaluate possible correlations among these parameters and the molecular changes.

With the recent massive data produced by next generation sequencing, and with our growing knowledge on the applicability of genetic alterations in the clinic, it is important to have cost-effective, easy straight- forward to perform and to analyze techniques in order to profile the tumors for relevant mutations on the era of personalized medicine.

In the present work, we assess a quick and simple, real time PCR based method with selected targets for mutation detection and compare with two other widely used methods. Moreover we aim to profile tumors and uncover their possible genetic targets to best utilize our powerful investigational method of TumorGrafts.

Further studies with larger cohorts and alternative mutation detection techniques are needed to validate and expand the present results.

Citation Format: Mariana Brait, Luciane T. Kagohara, Evgeny Izumchenko, Samuel Long, Tin Khor, Elizabeth Bruckheimer, David Sidransky. Evaluation of cancer-related mutations in tumorgraft models. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4284. doi:10.1158/1538-7445.AM2014-4284

PD-L1 expression in the Merkel cell carcinoma microenvironment: association with inflammation, Merkel cell polyomavirus and overall survival

Merkel cell carcinoma (MCC) is a lethal, virus-associated cancer that lacks effective therapies for advanced disease. Agents blocking the PD-1/PD-L1 pathway have demonstrated objective, durable tumor regressions in patients with advanced solid malignancies and efficacy has been linked to PD-L1 expression in the tumor microenvironment. To investigate whether MCC might be a target for PD-1/PD-L1 blockade, we examined MCC PD-L1 expression, its association with tumor-infiltrating lymphocytes (TILs), Merkel cell polyomavirus (MCPyV), and overall survival. Sixty-seven MCC specimens from 49 patients were assessed with immunohistochemistry for PD-L1 expression by tumor cells and TILs, and immune infiltrates were characterized phenotypically. Tumor cell and TIL PD-L1 expression were observed in 49% and 55% of patients, respectively. In specimens with PD-L1(+) tumor cells, 97% (28/29) demonstrated a geographic association with immune infiltrates. Among specimens with moderate-severe TIL intensities, 100% (29/29) demonstrated PD-L1 expression by tumor cells. Significant associations were also observed between the presence of MCPyV DNA, a brisk inflammatory response, and tumor cell PD-L1 expression: MCPyV(-) tumor cells were uniformly PD-L1(-). Taken together, these findings suggest that a local tumor-specific and potentially MCPyV-specific immune response drives tumor PD-L1 expression, similar to previous observations in melanoma and head and neck squamous cell carcinomas. In multivariate analyses, PD-L1(-) MCCs were independently associated with worse overall survival (hazard ratio 3.12; 95% CI, 1.28-7.61; p=0.012). These findings suggest that an endogenous immune response promotes PD-L1 expression in the MCC microenvironment when MCPyV is present, and provide a rationale for investigating therapies blocking PD-1/PD-L1 for patients with MCC.

Abstract 1165: Evaluation of HPV infection in penile cancer and its association with p16 and MGMT protein expression levels and pathologic variables

INTRODUCTION: Penile carcinoma is an infrequent tumor. However, in developing countries it is a common disease and in specific regions it may represents the most frequent tumor among men. The most important prognostic clinical factor is the presence of lymph node metastasis, which is associated with significant reduced survival to the penile carcinoma patients. Nevertheless, until the present date it was not possible to establish clinical or molecular prognostic markers. Various factors are associated with increased risk for de development of this disease, such as poor hygienic habits, lack of circumcision and HPV infection. HPV DNA can be detected in 20% to 80% of penile squamous cell carcinomas (PSCC). However, the role of HPV on patients’ prognosis is still uncertain. METHODS: We evaluated the frequency of HPV infection in 189 PSCC samples. The presence or absence of HPV DNA was established using generic primers (GP5+/GP6+) specific for the L1 gene of several HPVs. Specimens positive for HPV DNA were genotyped by dot blot hybridization using radioactive probes. We also evaluated the expression levels of the proteins p16 and MGMT through immunohistochemistry. These two proteins show aberrant levels in a wide range of tumors. Protein expression was quantified using an automated image system (ScanScope XT - Aperio), which determined the percentage and intensity of positive cells. The quantification was used to determine if there was loss of expression or normal (positive) expression. RESULTS: HPV infection, characterized by detection of viral DNA on the samples, was observed in 19.6% (37) of the cases. Among the positive HPV samples, 51.3% were infected by HPV16, 21.6% by HPV18 and 2.7% by both HPV16 and 18 concomitantly. The presence of HPV infection was more frequent among tumors with thickness lower than 5mm, suggesting that PSCC with HPV are less aggressive. This finding is in agreement with some studies that showed better prognosis of tumors with HPV infection. The immunohistochemistry assays showed reduced p16 expression in 35.4% (63) and loss of MGMT in 90.1% (146) cases. None association was observed between HPV infection and p16 protein expression. It is well established that the presence of HPV is associated with p16 positive expression. One interesting observation was that MGMT positive expression was associated with positive viral infection. Until this moment, there is no study describing this association in PSCC neither in other tumor types. It was observed an association between p16 reduced levels and poor differentiated tumors, this pathologic variable is associated with bad prognosis. MGMT loss of expression was associated with the presence of lymph node metastasis, suggesting that expression status of this protein can be a molecular marker for PSCC.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1165. doi:1538-7445.AM2012-1165

Abstract 4807: P16 and MGMT hypermethylation status evaluation in squamous cell penile carcinomas by pyrosequencing

Penile carcinoma is an uncommon disease and the most frequent subtype is squamous cell carcinoma. This cancer represents less than 1% of all cases in developed countries. However, in some regions of developing countries it represents 20% of all male cancers. The main risk factors associated to this tumor are poor hygienic habits, low quality of life, HPV infections and high number of sexual partners. Very little is known about penile carcinoma, including its pathogenesis, etiology and molecular biology features. In this study, we evaluated the hypermethylation status of two genes that present high frequencies of methylation in various tumor types. P16 plays an important role in cell cycle control. It encodes the protein p16 that binds to CDK proteins and inhibits pRB phosphorilation, blocking cell cycle progression. MGMT encodes a DNA repair protein that removes alkyl groups from guanines. The protein mgmt is peculiar once it acts alone and not in complexes like other DNA repair proteins. Hypermethylation of these genes is already described in a large variety of tumors, leads to gene silencing and has an important role in tumoregenesis. Here, we determined the frequency of hypermethylation among penile carcinoma samples and the percentage of aberrant methylation for each sample. The samples were submitted to bisulfite conversion, amplification and sequencing employing the pyrosequencing methodology, which is a quantitative methodology allowing percentage determination of each CpG dinucleotide analyzed. The hypermethylation status and methylation levels were evaluated in 33 squamous cell penile carcinoma samples. We observed P16 hypermethylation in 9% of the samples and MGMT was methylated in 27%, with levels of methylation varying from 10.71% to 35.43% and 12.20% to 62.60%, respectively. The low frequency of samples showing P16 hypermethylation could be explained by the presence of HPV infection, which is described in approximately 70.00% to 80.00% of penile carcinomas. It is well known that in the presence of HPV there is no P16 DNA methylation, suggesting that the HPV E7 protein influences the Rb pathway in these samples. MGMT hypermethylation frequency is in accordance with what was described by other groups and that showed no association to clinical characters of the samples analysed. Little is known about the influence of DNA hypermethylation on penile carcinoma tumorigenesis but our results show that the epigenetic alteration of P16 and MGMT genes are not tumor markers for penile carcinoma. To our knowledge it is the first study describing the epigenetic status of penile carcinomas in the Brazilian population.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4807. doi:10.1158/1538-7445.AM2011-4807