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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.

Supplementary Data from Entinostat Decreases Immune Suppression to Promote Antitumor Responses in a HER2+ Breast Tumor Microenvironment

Spatial transcriptomics (ST) is a powerful new approach to characterize the cellular and molecular architecture of the tumor microenvironment. Previous single-cell RNA-sequencing (scRNA-seq) studies of pancreatic ductal adenocarcinoma (PDAC) have revealed a complex immunosuppressive environment characterized by numerous cancer associated fibroblasts (CAFs) subtypes that contributes to poor outcomes. Nonetheless, the evolutionary processes yielding that microenvironment remain unknown. Pancreatic intraepithelial neoplasia (PanIN) is a premalignant lesion with potential to develop into PDAC, but the formalin-fixed and paraffin-embedded (FFPE) specimens required for PanIN diagnosis preclude scRNA-seq profiling. We developed a new experimental pipeline for FFPE ST analysis of PanINs that preserves clinical specimens for diagnosis. We further developed novel multi-omics analysis methods for threefold integration of imaging, ST, and scRNA-seq data to analyze the premalignant microenvironment. The integration of ST and imaging enables automated cell type annotation of ST spots at a single-cell resolution, enabling spot selection and deconvolution for unique cellular components of the tumor microenvironment (TME). Overall, this approach demonstrates that PanINs are surrounded by the same subtypes of CAFs present in invasive PDACs, and that the PanIN lesions are predominantly of the classical PDAC subtype. Moreover, this new experimental and computational protocol for ST analysis suggests a biological model in which CAF-PanIN interactions promote inflammatory signaling in neoplastic cells which transitions to proliferative signaling as PanINs progress to PDAC.SummaryPancreatic intraepithelial neoplasia (PanINs) are pre-malignant lesions that progress into pancreatic ductal adenocarcinoma (PDAC). Recent advances in single-cell technologies have allowed for detailed insights into the molecular and cellular processes of PDAC. However, human PanINs are stored as formalin-fixed and paraffin-embedded (FFPE) specimens limiting similar profiling of human carcinogenesis. Here, we describe a new analysis protocol that enables spatial transcriptomics (ST) analysis of PanINs while preserving the FFPE blocks required for clinical assessment. The matched H&E imaging for the ST data enables novel machine learning approaches to automate cell type annotations at a single-cell resolution and isolate neoplastic regions on the tissue. Transcriptional profiles of these annotated cells enable further refinement of imaging-based cellular annotations, showing that PanINs are predominatly of the classical subtype and surrounded by PDAC cancer associated fibroblast (CAF) subtypes. Applying transfer learning to integrate ST PanIN data with PDAC scRNA-seq data enables the analysis of cellular and molecular progression from PanINs to PDAC. This analysis identified a transition between inflammatory signaling induced by CAFs and proliferative signaling in PanIN cells as they become invasive cancers. Altogether, this integration of imaging, ST, and scRNA-seq data provides an experimental and computational approach for the analysis of cancer development and progression.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by a heterogeneous tumor microenvironment (TME) that is enriched with cancer associated fibroblasts (CAFs)1. Cell-cell interactions involving these CAFs promote an immunosuppressive phenotype with altered inflammatory gene expression. While single-cell transcriptomics provides a tool to dissect the complex intercellular pathways that regulate cancer-associated inflammation in human tumors, complementary experimental systems for mechanistic validation remain limited. This study integrated single-cell data from human tumors and novel organoid co-cultures to study the PDAC TME. We derived a comprehensive atlas of PDAC gene expression from six published human single-cell RNA sequencing (scRNA-seq) datasets2–7to characterize intercellular signaling pathways between epithelial tumor cells and CAFs that regulate the inflammatory TME. Analysis of the epithelial cell compartment identified global gene expression pathways that modulate inflammatory signaling and are correlated with CAF composition. We then generated patient-derived organoid-CAF co-cultures to serve as a biological model of the cellular interactions learned from human tissue in the atlas. Transfer learning analysis to additional scRNA-seq data of this co-culture system and mechanistic experiments confirmed the epithelial response to fibroblast signaling. This bidirectional approach of complementary computational andin vitroapplications provides a framework for future studies identifying important mechanisms of intercellular interactions in PDAC.

Recent advances in spatial transcriptomics (ST) 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 and its 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 occurs in tumor-immune interactions. We present SpaceMarkers, a novel bioinformatics algorithm to infer molecular changes from cell-cell interaction from latent space analysis of ST data. We apply this approach to infer 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.

Therapeutic combinations to alter immunosuppressive, solid tumor microenvironments (TME), such as in breast cancer, are essential to improve responses to immune checkpoint inhibitors (ICI). Entinostat, an oral histone deacetylase inhibitor, 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 to fully characterize changes across multiple cell types within the TME. This analysis demonstrates that treatment with entinostat induced a shift from a protumor to an antitumor TME signature, characterized predominantly by changes in myeloid cells. We confirmed myeloid-derived suppressor cells (MDSC) within entinostat-treated tumors associated with a less suppressive granulocytic (G)-MDSC phenotype and exhibited altered suppressive signaling that involved the NFκB and STAT3 pathways. In addition to MDSCs, tumor-associated macrophages were epigenetically reprogrammed from a protumor M2-like phenotype toward an antitumor 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 antitumor 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.

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.

Introduction: Pancreatic ductal adenocarcinomas (PDACs) are immunogenically “cold” tumors that lack effector T cell infiltration associated with immune checkpoint inhibitor (ICI) responsiveness. Neoadjuvant immunotherapy clinical trials facilitate understanding of the complexities of combination treatment strategies on immunosuppressive mechanisms. Our recent multi-omics analysis of a neoadjuvant trial comparing the GVAX vaccine alone or with nivolumab and supporting preclinical data uncovered crosstalk between CD8+CD137+ T cells and neutrophils as an axis for therapeutic intervention. These studies have formed the foundation for the addition of the CD137 agonist, urelumab, to our combination regimen to improve T cell activation in PDACs. Methods: Patients were enrolled on NCT02451982 and initiated treatment 2 weeks prior to surgical resection. We compared specimens from 3 treatment arms for downstream analysis: Arm A: an allogeneic whole cell vaccine, GVAX (n=7); Arm B: GVAX and nivolumab (n=4); Arm C: GVAX, nivolumab, and urelumab (n=4). Samples underwent dissociation and Percoll separation to enrich for immune cells, followed by single-cell RNA- and TCR-seq using 10X Genomics. Computational analysis was performed for cell type classification with Seurat, differential expression with DESeq2 of pseudobulk data, cell-cell communication with Domino, and TCR-seq analysis with scRepertoire. Results: Single-cell RNA-seq analysis identified changes in immune cell proportions and immune cell states across treatment arms. Alignment of scTCR-seq to RNA data showed greater CD8+ T cell expansion following triple agent therapy. Gene set enrichment identified changes in CD8+ T cell, tumor associated macrophage (TAM), and B cell responses to cytokine signaling, locomotion, amino acid metabolism, and cell adhesion pathways in Arm C. Domino analysis demonstrated increases in the naïve T cell signal CCR7 in Arm A and integrin ligand signal ICAM1 in Arm C between the CD8+ T cells and other cell types present in PDACs. CCR7 expression was significantly downregulated in CD8+ T cells in Arm C whereas CCL5, a T cell agonist cytokine, and LCP2, a TCR signaling activator and T cell receptor which is also required for integrin signaling, were significantly upregulated in CD8+ T cells in Arm C. The increased integrin ligand signaling via ICAM1 and LCP2 in Arm C is also associated with changes in CD8+ T cell motility observed from the differential expression analysis. Conclusions: Analysis of combination GVAX, PD-1 inhibition and CD137 agonist therapy demonstrated changes in multiple immune cell proportions and their functional pathways. These data provide new evidence that PDACs can become T cell rich and respond to combination immunotherapies. Citation Format: Joseph A. Tandurella, Jacob T. Mitchell, Janelle M. Montagne, Eric Christenson, Qingfeng Zhu, Ludmilla V. Danilova, Alexander V. Favorov, Won J. Ho, Luciane T. Kagohara, Melanie Loth, Su Jin Lim, Rui Zheng, Jessica Gai, Sarah Mitchell, Dimitrios N. Sidiropoulos, Wenpin Hou, Yao Xu, Hao Wang, Jacquelyn W. Zimmerman, Srinivasan Yegnasubramanian, Robert Anders, Elizabeth M. Jaffee, Lei Zheng, Elana J. Fertig. Single-cell RNA and TCR sequencing of tumor infiltrating lymphocytes identifies changes in pancreatic ductal adenocarcinomas following neoadjuvant treatment with combined anti-PD-1 blocking and anti-CD137 agonist therapy [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 3241.

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.

Background Identifying potential resistance mechanisms while tumour cells still respond to therapy is critical to delay acquired resistance. Methods We generated the first comprehensive multi-omics, bulk and single-cell data in sensitive head and neck squamous cell carcinoma (HNSCC) cells to identify immediate responses to cetuximab. Two pathways potentially associated with resistance were focus of the study: regulation of receptor tyrosine kinases by TFAP2A transcription factor, and epithelial-to-mesenchymal transition (EMT). Results Single-cell RNA-seq demonstrates heterogeneity, with cell-specific TFAP2A and VIM expression profiles in response to treatment and also with global changes to various signalling pathways. RNA-seq and ATAC-seq reveal global changes within 5 days of therapy, suggesting early onset of mechanisms of resistance; and corroborates cell line heterogeneity, with different TFAP2A targets or EMT markers affected by therapy. Lack of TFAP2A expression is associated with HNSCC decreased growth, with cetuximab and JQ1 increasing the inhibitory effect. Regarding the EMT process, short-term cetuximab therapy has the strongest effect on inhibiting migration. TFAP2A silencing does not affect cell migration, supporting an independent role for both mechanisms in resistance. Conclusion Overall, we show that immediate adaptive transcriptional and epigenetic changes induced by cetuximab are heterogeneous and cell type dependent; and independent mechanisms of resistance arise while tumour cells are still sensitive to 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.

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.

Summary 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.

Understanding how novel therapeutic combinations alter solid tumor microenvironments (TME) in immunosuppressive tumors such as breast cancer is essential to improve their 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, but the precise alterations induced by entinostat and mechanisms of synergy with ICIs remain unknown. Here, we employ single-cell RNA-sequencing on HER2 overexpressing breast tumors from mice treated with entinostat + ICIs to characterize these changes across cell types in the TME. This analysis demonstrates that treatment with entinostat induces a shift from a pro-tumor to an anti-tumor TME signature characterized predominantly by changes in the myeloid cells. Notably, myeloid-derived suppressor cells (MDSCs) are shifted toward the less suppressive granulocytic phenotype in association with reduced signaling through the STAT3 pathway. In addition, tumor-associated macrophages are shifted toward an anti-tumor M1 phenotype by epigenetic reprogramming. Overall, these entinostat-induced TME changes reduce immunosuppression and increase mechanisms of tumor cell killing to improve ICI responses and broaden the population of patients who could potentially benefit from immunotherapy.

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.

Identifying potential mechanisms of resistance while tumor cells still respond to therapy is critical to delay acquired resistance. We generated the first comprehensive multi-omics, bulk and single cell data in sensitive head and neck squamous cell carcinoma (HNSCC) cells to identify immediate responses to cetuximab. Two pathways potentially associated with resistance were focus of the study: regulation of receptor tyrosine kinases through the transcription factor TFAP2A, and epithelial-to-mesenchymal transition (EMT) process. Single cell RNA-seq demonstrates heterogeneity, with cell specific TFAP2A and VIM expression profiles in response to treatment. RNA-seq and ATAC-seq reveal global changes within five days of cetuximab therapy, suggesting early onset of mechanisms of resistance; and corroborates cell line heterogeneity, with different TFAP2A targets or EMT markers affected by therapy. Lack of TFAP2A reduces HNSCC growth and is enhanced by cetuximab and JQ1. Regarding the EMT process, short term cetuximab therapy has the strongest effect on inhibiting migration. TFAP2A silencing does not affect cell migration, supporting an independent role for both mechanisms in resistance. Overall, we show that immediate adaptive transcriptional and epigenetic changes induced by cetuximab are heterogeneous and cell type dependent; and independent mechanisms of resistance arise while tumor cells are still sensitive to therapy.

Current clinical tests for prostate cancer (PCa), such as the PSA test, are not fully capable of discerning patients that are highly likely to develop metastatic prostate cancer (MPCa). Hence, more accurate prediction tools are needed to provide treatment strategies that are focused on the different risk groups. Cancer/testis antigens (CTAs) are expressed during embryonic development and present aberrant expression in cancer making them ideal tumor specific biomarkers. Here, the potential use of a panel of CTAs as a biomarker for PCa detection as well as metastasis prediction is explored. We initially identified eight CTAs (CEP55, NUF2, PAGE4, PBK, RQCD1, SPAG4, SSX2andTTK) that are differentially expressed in MPCa when compared to local disease and used this panel to compare the gene and protein expression profiles in paired PCa and normal adjacent prostate tissue. We identified differential expression of all eight CTAs at the protein level when comparing 80 paired samples of PCa and the adjacent non-cancer tissue. Using multiple logistic regression we also show that a panel of these CTAs present high accuracy to discriminate normal from tumor samples. In summary, this study provides evidence that a panel of CTAs, differentially expressed in aggressive PCa, is a potential biomarker for diagnosis and prognosis to be used in combination with the current clinically available tools and is also a potential target for immunotherapy development.

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.

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.

e15061 Background: HER2+ breast cancers are known to be less-immunogenic and associated with low response rates to immune checkpoint inhibitors (ICIs). 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 histone deacetylase inhibitor, entinostat (ENT), 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 ENT in combination with anti-PD-1, anti-CTLA-4, provided a significant survival benefit compared to either treatment alone. Methods: This current study employs single cell RNA-sequencing 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 over 54,000 cells from 20 tumors treated with entinostat alone or in combination with anti-PD1 and anti-CTLA4 and their combination. Results: 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. These results are being corroborated in patient samples from a parallel clinical trial to provide translational relevance. Conclusions: Our current work provides insights into the transcriptional network within a breast tumor after treatment with ENT+ICIs. We predict our findings will bring us closer to identifying additional therapeutic targets and ultimately improve survival rates of patients with less-immunogenic tumors.

Background: Immune checkpoint inhibitors (ICIs) provide benefit for immunogenic cancers that naturally attract T cell infiltration, but have limited benefit for patients with tumors that lack natural T cells in the tumor microenvironment (TME) including many breast cancers. Suboptimal and inconsistent immune responsiveness in many cancers is likely the result of a lack of tumor antigen expression and/or recognition together with multiple suppressive signals within the TME that provide a formidable barrier to T cell infiltration. Emerging data suggest that these factors can be overcome by combining epigenetic modulation that reprograms myeloid-derived suppressor cells (MDSCs) and upregulate T cell-attracting signals within the TME, with ICIs. Our paralleled preclinical and clinical trial investigates the mechanisms and efficacy of the epigenetic modulator, entinostat (ENT) to reprogram the immune suppressive cells within the TME. Methods: We conducted a multicenter phase 1 clinical trial (NCT02453620) of entinostat combined with nivolumab +/- ipilimumab in patients with advanced cancers including hormone-receptor positive or triple-negative breast cancer (TNBC). Mandatory tumor samples are being obtained pre-treatment, post-treatment with 2 weeks of entinostat, and 8 weeks post combination therapy with ICIs. We used immunohistochemical (IHC) for CD8 and FoxP3 to determine a ratio representative of immune infiltration in response to therapy. Preclinical studies utilize mouse models of breast cancer (NeuN and 4T1) and mirror the treatment scheme used in the clinical trial. We employed multiparameter flow cytometry, single cell RNA sequencing, bulk RNA sequencing of tumor specimens and patient samples to specifically interrogate the role of ENT in modulating STAT3 as a master regulator of downstream inflammatory pathways. Results: With regard to the clinical trial, out of 35 patients enrolled, 11 were diagnosed with breast cancer. We observed 4 partial responses, 2 responses in patients with breast cancer, with an ORR of 12%. We have almost completed accrual of our expansion cohort of 15 patients with advanced HER2 negative breast cancer. The primary outcomes of the clinical trial will be reported elsewhere, here we are focusing on important correlative findings which suggest a combination of ENT with ICIs alters CD8/FoxP3 ratios in certain patients. Bulk-RNA sequencing or patient samples is underway. Preliminary data from animal models obtained using scRNA-seq has begun to elucidate altered MDSC signaling pathways, and to identify gene expression changes in immune, stromal, and tumor cells following treatment with ENT. These data are also expected to identify new targets for ICI sensitization. Conclusions: Preliminary results with IHC staining suggests increased immune infiltration with combination therapy. Sequencing analysis will likely provide deeper insight into mechanisms driving response. The mechanisms of response to ICIs in patients with breast cancer have yet to be elucidated. These studies will provide the necessary scientific evidence to uncover mechanisms behind the transformation of the immunosuppressive TME and provide new targets that could improve clinical response to ICIs to maximize patient survival. The core biological themes explored will likely have a broad impact in the field of breast cancer and affect the paradigm of therapies available to patients in the clinic. These findings will help determine how treatment with ICIs will be successful to obtain durable responses for breast cancer patients. Citation Format: Evanthia T Roussos Torres, Luciane Tsukamoto Kagohara, Emily Davis, Christine Rafie, Brian Christmas, Qingfeng Zhu, Chenguang Wang, David Lim, Robert Anders, Elana Fertig, Vincent Chung, Patricia Lorusso, Adam Brufsky, Elizabeth M Jaffee, Vered Stearns, Roisin Connolly. Reprogramming the suppressive tumor microenvironment of breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-04-06.

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/

Widespread characterization of the genomic landscape of tumors has enabled precision treatment strategies. Despite significant advances in development of targeted therapies, patients with tumors sensitive to inhibitors often acquire resistance and succumb to their tumors. The timing and function of gene regulation responsible for resistance remain unknown. Clinical gains from the use of the anti-EGFR antibody, cetuximab, in head and neck squamous cell carcinoma (HNSCC) lead to FDA approval. However, cetuximab is not curative for HNSCC patients and a significant proportion acquire resistance to the treatment. A comprehensive characterization of the mechanisms resulting in acquired cetuximab resistance is critical to delineate new strategies to overcome resistance. To this end, we developed a novel time course analysis to study the in vitro progression of the molecular mechanisms resulting in acquired cetuximab resistance in HNSCC. Specifically, we collected multiple experimentally equivalent cultures over several generations in order to measure changes in gene expression, DNA methylation, and proliferation as resistance developed. This new long-term treatment protocol models the progression of acquired therapeutic resistance, including controls for clonal selection unrelated to treatment. The epigenetic regulation of FGFR1 expression emerged as the dominant mechanism of acquired therapeutic resistance in this system and was confirmed in primary tumors from The Cancer Genome Atlas (TCGA). The association of FGFR1 overexpression with cetuximab resistance is consistent with previous studies. Even in a subset of cetuximab stable resistant clones presenting substantial epigenetic heterogeneity, FGFR1 up-regulation in response to loss of promoter methylation emerged as a key regulator of resistance corroborating our pooled time course epigenetics data. Therefore, we hypothesize that alternative molecular mechanisms giving rise to EGFR inhibitor resistance could be overcome with the introduction of combined FGFR1 inhibition. Taken together, our time course profiling of DNA methylation and gene expression data provide a significant contribution to the characterization of mechanisms involved in acquired cetuximab resistance in HNSCC and provides new insights to alternative options for targeted therapy in this tumor type.

Recent advances in sequencing technology have enabled unprecedented genome-wide characterization of head and neck squamous cell carcinoma (HNSCC). Integrated analyses of publicly available multiplatform high-throughput data have uncovered the vast genomic, epigenetic, and transcriptional diversity of HNSCC. Recognition of human papillomavirus (HPV) involvement in HNSCC carcinogenesis has resulted in the categorization of two HNSCC subtypes (HPV-driven and HPV-negative) with distinct etiologies, molecular properties, clinical features, and prognostic outcomes. Differences in the molecular landscapes of HPV-driven and HPV-negative HNSCC occur genome-wide and encompass changes in genomic, epigenetic, and transcriptional landscapes. Even within each subtype, HNSCC tumors have substantial inter-tumor and intra-tumor molecular heterogeneity. Improving the understanding of the underlying biological function of these complex molecular landscapes through emerging cross-platform genomic analyses is essential to developing more effective diagnostic and therapeutic strategies for HNSCC.

ABSTRACT Aim: The aim of the study was to evaluate the use of global and gene-specific DNA methylation changes as potential biomarkers for gallbladder cancer (GBC) in a cohort from Chile. Material & methods: DNA methylation was analyzed through an ELISA-based technique and quantitative methylation-specific PCR. Results: Global DNA Methylation Index (p = 0.02) and promoter methylation of SSBP2 (p = 0.01) and ESR1 (p = 0.05) were significantly different in GBC when compared with cholecystitis. Receiver curve operator analysis revealed promoter methylation of APC, CDKN2A, ESR1, PGP9.5 and SSBP2, together with the Global DNA Methylation Index, had 71% sensitivity, 95% specificity, a 0.97 area under the curve and a positive predictive value of 90%. Conclusion: Global and gene-specific DNA methylation may be useful biomarkers for GBC clinical assessment.

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, non-coding RNAs, post-translational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations, once thought to be crucial only for the malignant phenotype maintenance, are now recognized as critical also 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. While associated with 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 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 integration techniques that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer, and are therefore also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations to cause tumorigenesis initiation and progression. This deeper understanding is essential to future studies that will precisely infer patients’ prognosis and select patients who will be responsive to emerging epigenetic therapies.

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. Supplementary information Supplementary data are available at Bioinformatics online.

The purpose of this study is to identify how the epigenetic modulator entinostat reprograms myeloid derived suppressor cells (MDSCs) to prime the tumor microenvironment (TME) and modulate immunotherapy response. Early trials investigating single agent ICIs, anti-CTLA-4 and anti-PD-1/PD-L1, resulted in overall response rates of 5-20% in patients with metastatic HER2 positive breast cancer but little is understood about use of these therapies in patients with early stage/ primary disease. Suboptimal and inconsistent immune responsiveness is likely the result of multiple suppressive signals within the TME that provide a formidable barrier to T cell infiltration leading to an opportunity for TME modulation to potentially improve response. We and others have shown that immunosuppressive factors can be overcome by adding the class 1 histone deacetylase inhibitor, entinostat, to ICIs to reprogram MDSCs and upregulate T cell attracting signals within the TME. We hypothesize that gene expression signatures of reprogrammed MDSCs are predictive of response with subsequent immunotherapy treatment. To test this hypothesis, we used the neu-N syngeneic mouse model of HER2 positive breast cancer. We investigated differences in survival and tumor burden in response to combinations of entinostat with anti-PD-1 and anti-CTLA-4. Having previously identified MDSCs as important targets of entinostat that modulate response to ICIs, we used methods we developed to study MDSC function. Given the broad effects of entinostat on global gene expression including that of MDSCs, we used single cell RNA-seq (scRNA-seq) on primary tumors and isolated intratumoral MDSCs to determine what is driving changes in MDSC function in primary tumors. We plan to use data obtained from scRNA-seq to develop signatures of response and identify changes in responders vs. non-responders to help develop biomarkers of response in primary disease. Our results thus far show that treatment with entinostat + ICIs improves survival, and decreases tumor burden in primary tumors. Ex-vivo studies of MDSCs demonstrate changes in immunosuppressive capabilities of MDSCs and show differences in infiltration and function of granulocytic vs. monocytic MDSCs. We expect that evaluation of the ongoing sequencing data will identify more specific immune targets within primary TME and help us understand the importance of targeting MDSCs in early disease. We predict this work will identify additional candidate targets for therapeutic testing to convert breast cancers into immune responsive tumors, and that this will facilitate improved response to ICIs that will ultimately translate into improved survival of patients with breast cancer. Citation Format: Evanthia T. Roussos Torres, Christine Rafie, Emily Davis, Luciane T. Kagohara, Elana J. Fertig, Elizabeth M. Jaffee. Sequencing the tumor microenvironment and myeloid derived suppressor cells to understand response to immunotherapy in primary HER2 positive breast cancer [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 5027.

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.

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 shown 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 (TIL), 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) showed a geographic association with immune infiltrates. Among specimens with moderate-severe TIL intensities, 100% (29/29) showed 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 [HR 3.12; 95% confidence interval, 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. Cancer Immunol Res; 1(1); 54–63. ©2013 AACR.

O6-Methyguanine-DNA methyltransferase (MGMT) repairs DNA damage and acts as a tumor suppressor in normal cells by preventing DNA mutations. Several antibodies against MGMT are used for immunohistochemical assessment of this marker and no universal standard is adopted. We evaluated the immunohistochemical expression of MGMT with 5 commercially available primary antibodies in 59 invasive breast carcinomas. A tissue microarray was constructed using 59 invasive breast carcinoma samples. Five primary antibodies against MGMT were used for immunohistochemistry, including clones MT3.1, SPM287, and MT23.2. Heat-induced antigen retrieval and polymer-based immunohistochemistry were performed. Stains were analyzed by microscopy and automated digital slide technology. qRT-PCR was performed for all tumors. Clone SPM287 had the highest sensitivity (p0.001), and clone MT3.1 had the lowest sensitivity (p0.001). Clone MT23.2 generated higher levels of cytoplasmic staining, which was not observed with the other antibodies (p0.001). Fifty-six samples (94.9%) showed hypoexpression of MGMT compared with normal breast, as measured by qRT-PCR (p0.001). Only clone SPM287 correlated significantly with the qRT-PCR results (p=0.027). Antibody clone SPM287 is the most sensitive and specific antibody for the immunohistochemical evaluation of MGMT, rendering it a reliable and effective reagent for research and clinical practice in breast cancer.

The aim of the current study was to identify a panel of cancer/testis antigens (CTAs) with the potential to be used as a complementary test to the prostate-specific antigen (PSA) test for prostate cancer (PCa) screening. PSA test is capable of identifying men under risk of PCa before the presence of symptoms. However, this screening has been considered a controversy assessment since many men presenting benign lesions (benign prostate hyperplasia or other inflammatory conditions) can also present increased PSA levels. Hence, the great current dilemma in PCa screening is to develop a test that in combination with PSA assay could present higher accuracy for PCa early diagnosis. CTAs constitute an important class of potential cancer biomarkers that are poorly studied in PCa. CTAs are normally expressed in testis and germ cells and are aberrantly over-expressed in cancers. This unique pattern of expression makes these genes potential candidates as specific tumor biomarkers. CTA aberrant expression in malignant tumors is associated with phenotypic changes that confer the cancer cells essential advantages for proliferation and survival. Our hypothesis is that a panel of CTAs differentially expressed in PCa compared to normal prostate tissue would be useful to develop a diagnostic biomarker panel to be used in combination with the PSA test. We initially evaluated the expression of 22 CTAs, using the Nanostring approach, in localized and metastatic PCa to identify those genes associated with more aggressive tumors. After validation by qRT-PCR, we verified that 8 genes were differentially expressed between indolent and aggressive tumors. Using immunohistochemistry and a quantitative image analysis to measure protein expression, we evaluated CTA protein levels in PCa and adjacent normal tissue paired samples. The CTAs CEP55, NUF2, PAGE4, PBK, RQCD1, SPAG4, SSX2 and TTK presented increased protein levels in PCa when compared to normal prostate tissue from the same patient. Increased levels of PAGE4, PBK, RQCD1, SPAG4 and SSX2 were more frequent among patients with Gleason Score 4+3 or higher. In an attempt to identify a panel of CTAs with increased expression in PCa vs. prostate normal samples, we used multiple logistic regression analysis (MLR). MLR analysis showed that a panel that includes all 8 CTAs analyzed correctly classified 88.9% of the cases (AUC=0.96; sensitivity=88.5%; specificity=89.2%). For the MLR analysis, we considered the intensity and the frequency of the cancer cells with positive CTA expression. The intensity of all 8 CTAs was significant in the analysis, while the frequency of staining was only relevant for NUF2, PBK, SSX2 and TTK. Our findings suggest that our 8 CTAs panel represent a potential biomarker with high accuracy to discriminate normal prostate from PCa. Further studies to evaluate their expression in bodily fluids will determine their potential as a non-invasive PCa screening test to be used in combination with PSA. Citation Format: Luciane T. Kagohara, Prakash Kulkarni, Takumi Shiraishi, Robert Vessella, Robert W. Veltri, Elana J. Fertig. Cancer/testis antigens: A biomarker panel for prostate cancer screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4525.

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.

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.

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

// Masamichi Hayashi 1,* , Heike Bernert 1,2,* , Luciane Tsukamoto Kagohara 1 , Leonel Maldonado 1,3 , Mariana Brait 1 , Mark Schoenberg 4 , Trinity Bivalacqua 4 , George J Netto 4,5,6 , Wayne Koch 1 , David Sidransky 1 , Mohammad O. Hoque 1,4,6 1 Department of Otolaryngology-Head and Neck Surgery, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 2 Department of Pathobiology, The University of Tennessee, The College of Veterinary Medicine, Knoxville, Tennessee, USA. 3 Department of Gynecology and Obstetrics-Gynecologic Specialties, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 4 Department of Urology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 5 Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 6 Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * The Authors Contributed equally Correspondence: Mohammad Obaidul Hoque, email: // Keywords : UCC, Epigenetics, Biomarker, Methylation Received : February 28, 2014 Accepted : May 6, 2014 Published : May 7, 2014 Abstract Background: To identify new epigenetic markers and further characterize Urothelial Cell Carcinoma (UCC), we tested the promoter methylation (PM) status of 19 genes previously identified as cancer specific methylated genes in other solid tumors. Methods: We used bisulfite sequencing, methylation specific PCR and quantitative methylation specific PCR (QMSP) to test the PM status of 19 genes in urothelial cancer cell lines. Results: Among the 19 genes tested, VGF was found to be completely methylated in several UCC cell lines. VGF QMSP analysis showed that methylation values of almost all the primary 19 UCC tissues were higher than the paired normal tissues (P=0.009). In another cohort, 12/35 (34.3%) of low grade UCC cases displayed VGF methylation. As a biomarker for non-invasive detection of UCC, VGF showed a significantly higher frequency of methylation in urine from UCC cases (8/20) compared to controls (1/20) (P=0.020). After treatment of cell lines with 5-Aza-2’-deoxycytidine, VGF was robustly re-expressed. Forced expression of VGF in bladder cancer cell lines inhibited cell growth. Conclusion: Selection of candidates from genome-wide screening approach in other solid tumors successfully identified UCC specific methylated genes.

Although specific mutations in the tyrosine kinase domain of epidermal growth factor receptor (EGFR) identify tumors that are responsive to EGFR tyrosine kinase inhibitors (TKI), these genetic alterations are present in only a minority of patients. Patients with tumors expressing wild-type EGFR lack reliable predictive markers of their clinical response to EGFR TKIs. Although epithelial–mesenchymal transition (EMT) has been inversely correlated with the response of cancers to EGFR-targeted therapy, the precise molecular mechanisms underlying this association have not been defined and no specific EMT-associated biomarker of clinical benefit has been identified. Here, we show that during transforming growth factor β (TGFβ)–mediated EMT, inhibition of the microRNAs 200 (miR200) family results in upregulated expression of the mitogen-inducible gene 6 (MIG6), a negative regulator of EGFR. The MIG6-mediated reduction of EGFR occurs concomitantly with a TGFβ-induced EMT-associated kinase switch of tumor cells to an AKT-activated EGFR-independent state. In a panel of 25 cancer cell lines of different tissue origins, we find that the ratio of the expression levels of MIG6 and miR200c is highly correlated with EMT and resistance to erlotinib. Analyses of primary tumor xenografts of patient-derived lung and pancreatic cancers carrying wild-type EGFR showed that the tumor MIG6(mRNA)/miR200 ratio was inversely correlated with response to erlotinib in vivo. Our data demonstrate that the TGFβ–miR200–MIG6 network orchestrates the EMT-associated kinase switch that induces resistance to EGFR inhibitors, and identify a low ratio of MIG6 to miR200 as a promising predictive biomarker of the response of tumors to EGFR TKIs. Cancer Res; 74(14); 3995–4005. ©2014 AACR.

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 (NGS) - based approaches provide accurate results and offer promising diagnostic capabilities, there are still limitations which impede their adoption for large-scale population-based screening. There is a pressing clinical need for a well-validated, rapid, cost-effective and accurate mutation profiling system with optimal analytical performance in patient specimens. Given their speed, and cost-effectiveness, real-time, quantitative qPCR mutation detection techniques are well suited for the clinical environment. The novel qBiomarker somatic mutation PCR array has high sensitivity and shorter turnaround times compared to other methods. However a direct comparison to existing viable alternatives is required to assess its true potential and limitations. In this study, we extensively evaluated a panel of 117 patient-derived tumor xenografts (PDX) by the qBiomarker array and directly compared its efficacy with that of other routinely used methods for mutation detection, including Ion AmpliSeq sequencing, whole exome sequencing (WES), and ultra-sensitive droplet digital PCR (ddPCR) genotyping. Our comprehensive analysis demonstrates that qBiomarker's performance is on par with that of other routinely used but more complex, labor-intensive and expensive methods of cancer mutation detection, and provides a foundation for advancing the adoption of qBiomarker assay for cancer driving mutation profiling in clinical diagnostics. Furthermore, a large-scale direct comparison of different mutation detection approaches will lead to informed choice of screening methodologies, especially in lower budget conditions or timeframe limitations. Citation Format: Mariana Brait, Evgeny Izumchenko, Luciane Kagohara, Samuel Long, Piotr Wysocki, Brian Faherty, Elana Fertig, Tin Khor, Elizabeth Bruckheimer, Gilson Baia, Daniel Ciznadija, Ido Sloma, Ido Ben-Zvi, Keren Paz, David Sidransky. Validation of qBiomarker as an accurate and efficient mutation detection method in a comprehensive analysis of patient-derived tumor xenografts. [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 3640.

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; p0.7) 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.

Prostate-associated gene 4 (PAGE4) is an intrinsically disordered cancer/testis antigen that is typically restricted to the normal testis but is aberrantly expressed in prostate cancer (PCa). Furthermore, PAGE4 is developmentally regulated with dynamic expression patterns in the fetal prostate and is also a stress-response protein that is up-regulated in response to cellular stress. PAGE4 interacts with c-Jun and plays an important role in the development and pathology of the prostate gland. HIPK1, a component of the stress-response pathway, and CLK2, a dual specificity kinase are kinases that phosphorylate PAGE4 at predominantly at T51 and at multiple S/T residues, respectively. While phosphorylation at T51 is critical in potentiating c-Jun, the functional significance of the multisite phosphorylation by CLK2 is not known. The aim of this study was to determine the expression levels of HIPK1 and CLK2 in PCa cell lines, and in a set of 80 paired cases of PCa and benign adjacent tissue. Protein levels of HIPK1 and CLK2 were evaluated in cell lines and tissue samples by Western Blotting (WB) and immunohistochemistry (IHC), respectively. WB was performed with whole cell lysates from BPH1, DU145, LNCAP and PC3 cells using a fluorescence approach. IHC was performed with TMAs containing paired tumor and benign samples and after scanning (Aperio ScanScope), data were quantified using the ImageScope software. WB showed that HIPK1 is expressed in all cell lines selected with no significant changes in expression levels, while CLK2 was expressed only in BPH1 and LNCAP, suggesting this protein is expressed in cells displaying a less aggressive phenotype. Protein expression analysis by IHC in PCa and benign samples showed that CLK2 is more commonly expressed in PCa than HIPK1 when compared to non-cancer cases. CLK2 expression was positive in 81.7% of the cancer cases and HIPK1 was expressed in 72.2%. When compared to benign cases these differences are significant with p Citation Format: Luciane T. Kagohara, Steven Mooney, Yihong Chen, John Orban, Prakash Kulkarni, Robert W. Veltri. Phosphorylation of the intrinsically disordered cancer/testis antigen PAGE4 by HIPK1 and CLK2 in prostate cancer. [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 4970.