Malini Manoharan

A cancer vaccine approach for personalized treatment of Lynch Syndrome

Lynch syndrome (LS) is a cancer predisposition disorder wherein patients have a 70–80% lifetime risk of developing colorectal cancers (CRC). Finding germline mutations in predisposing genes allows for risk assessment of CRC development. Here we report a germline heterozygous frame-shift mutation in the mismatch repair MLH1 gene which was identified in members of two unrelated LS families. Since defects in DNA mismatch repair genes generate frame-shift mutations giving rise to highly immunogenic neoepitopes, we postulated that vaccination with these mutant peptide antigens could offer promising treatment options to LS patients. To this end we performed whole-exome and RNA seq analysis on the blood and tumour samples from an LS-CRC patient, and used our proprietary neoepitope prioritization pipeline OncoPeptVAC to select peptides, and confirm their immunogenicity in an ex vivo CD8+ T cell activation assay. Three neoepitopes derived from the tumour of this patient elicited a potent CD8+ T cell response. Furthermore, analysis of the tumour-associated immune infiltrate revealed CD8+ T cells expressing low levels of activation markers, suggesting mechanisms of immune suppression at play in this relapsed tumour. Taken together, our study paves the way towards development of a cancer vaccine to treat or delay the onset/relapse of LS-CRC.

Molecular alterations associated with chronic exposure to cigarette smoke and chewing tobacco in normal oral keratinocytes.

ABSTRACT Tobacco usage is a known risk factor associated with development of oral cancer. It is mainly consumed in two different forms (smoking and chewing) that vary in their composition and methods of intake. Despite being the leading cause of oral cancer, molecular alterations induced by tobacco are poorly understood. We therefore sought to investigate the adverse effects of cigarette smoke/chewing tobacco exposure in oral keratinocytes (OKF6/TERT1). OKF6/TERT1 cells acquired oncogenic phenotype after treating with cigarette smoke/chewing tobacco for a period of 8 months. We employed whole exome sequencing (WES) and quantitative proteomics to investigate the molecular alterations in oral keratinocytes chronically exposed to smoke/ chewing tobacco. Exome sequencing revealed distinct mutational spectrum and copy number alterations in smoke/ chewing tobacco treated cells. We also observed differences in proteomic alterations. Proteins downstream of MAPK1 and EGFR were dysregulated in smoke and chewing tobacco exposed cells, respectively. This study can serve as a reference for fundamental damages on oral cells as a consequence of exposure to different forms of tobacco.

Abstract A17: Differential gene expression and tumor mutanome analysis reveal significantly enriched pathways associated with higher tumor burden of M1 and M2 macrophages

Many attributes of the tumor microenvironment, such as the level of CD8 T-cells in the tumor, higher levels of pro-inflammatory cytokine network dominated by interferon signaling, antigen processing and presentation correlate with superior efficacy of checkpoint control inhibitors. Tumors lacking CD8 T-cells are less responsive to checkpoint control blockade, and therefore other therapeutic modalities for treating these tumors need to be explored. In this study, we set out to identify a set of core pathways associated with the absence or presence of specific immune cell types in tumors. These core pathways can be modulated to alter the immune profile of these unresponsive tumors and sensitize them to checkpoint control blockade. To this end, we created a robust bioinformatic solution OncoPeptTUME, to systematically investigate the immune landscape of tumors from RNA-seq data, using a set of proprietary immune cell type-specific gene expression signatures. Using a scoring method derived from Single Cell Gene Set Enrichment Analysis (ssGSEA), we quantitated the relative abundance of different immune cell types present in 9345 tumors across 33 cancers available in the TCGA dataset. We first validated our approach by selecting high and low CD8 T-cell containing tumors across many different cancers. Differential gene expression analysis between these two sets of tumors identified upregulated genes in PD-1 signaling, IFN-α, β and γ pathways, TCR signaling, antigen processing and presentation as previously reported in multiple studies. Similarly, tumors with high infiltration of myeloid derived suppressor cells (MDSCs) showed high level expression of a large number of inhibitory receptors associated with innate immune cells, demonstrating potential mechanism of immunesuppression in these tumors. Few studies, however, have investigated tumor intrinsic and extrinsic factors that favor infiltration of macrophages and induce them to differentiate into M1 and M2 functional states. The M1 and M2 macrophages regulate the inflammatory state of the tumor microenvironment by producing cytokines, chemokines and growth factors thereby making them susceptible or resistant to immune-mediated elimination. We applied M1 and M2-specific gene expression signatures on CD8 T-cell depleted tumors and identified 236 tumors having high or low M1 or M2 macrophages. Differential gene expression analysis reveal that tumors containing high M1 macrophages have significant upregulation of IFN-α/β signaling, tryptophan catabolism, IL1-β processing and CASP1 inflammosome activity. By contrast, tumors with low M1 infiltrated macrophages have upregulation of FGFR1c-Klotho pathway genes. Since differentiation of macrophages into M1 or M2 occurs in the tissue microenvironment, FGFR1 signaling may regulate macrophage phenotype rather than their migration into the tumor. In support of this hypothesis, we detected higher level of M2 macrophages in tumors that are depleted of M1 macrophages. We also analyzed genetic alterations in tumor cells that favor higher levels of M2 macrophages by examining non-synonymous somatic mutations in the coding sequences of genes. We observed loss- of-function mutations in p53 gene across many different cancers (breast, glioblastoma, stomach adenocarcinoma and lung squamous cell carcinoma) showing higher burden of M2 macrophages compared to the M1 type. Our analysis demonstrate that combining expression signatures with tumor mutanome analysis can provide a powerful tool to assess the tumor microenvironment and identify pathways that promote, or exclude infiltration/differentiation of specific immune cells. Citation Format: Nitin Mandloi, Ashwini Patil, Rekha Sathian, Aparna Mohan, Malini Manoharan, Ravi Gupta, Hiranjith Govindamangalam, Amit Chaudhuri. Differential gene expression and tumor mutanome analysis reveal significantly enriched pathways associated with higher tumor burden of M1 and M2 macrophages. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr A17.

Abstract 3579: A novel algorithm to identify TCR-binding somatic mutations from human cancers

A large number of pre-clinical and clinical studies have strongly implicated that combining cancer-derived neo-antigen vaccines with checkpoint control inhibitors will enhance priming and expansion of tumor-specific naive and memory T-cells resulting in superior efficacy and durability of response. The neo-antigens, derived from somatic mutations are prime candidates for cancer vaccines, not subjected to host’s central and peripheral tolerance. Identifying potential T-cell engaging neo-epitopes among a large number of somatic mutations is like finding a specific needle in a stack of needles. Currently, the available T-cell neo-epitope prioritization pipelines rely primarily on two attributes - the class-I HLA-binding affinity of the mutant peptide compared to the wild-type counterpart, and the level of expression of the mutated gene in tumor cells. The higher the binding differential, and higher the expression level of the mutant allele, the greater is the likelihood for the peptide to be presented on antigen-presenting cells. These approaches however fall short of predicting whether the HLA-bound peptide will engage T-cells by binding to T-cell receptors (TCRs). We have developed a novel algorithm to predict the binding of HLA-peptide complexes to TCRs by analyzing the physico-chemical composition of the amino acids and their positional biases in the 9-mers from crystal structures of HLA-peptide-TCR complex. We applied machine learning approach to build a classification model that can predict whether a given 9-mer peptide is a TCR-binder or not by identifying whether an amino acid at a given position carries key features that will facilitate interaction with the TCR. We applied this approach to positive and negative TCR interactions selected from Immune Epitope data base (IEDB). We tested multiple classification approaches and found that Random Forest and ClassificationviaRegression methods provided the best performance. We achieved more than 99% accuracy at 10-fold cross validation on both training and unseen test datasets. We further validated our model using positive and negative peptides curated from published papers reporting clinical trial results of checkpoint control inhibitors. The performance of the two classification models was evaluated on two different TCR-binding assays - dextramer binding and IFN-γ release. The ClassificationviaRegression method showed a higher positive predictive value for the dextramer-binding assay, whereas the Random Forest method showed a higher positive predictive value for the IFN-γ ELISPOT assay, suggesting subtle differences between the two classification methods. The inclusion of the TCR binding step to our T-cell neo-epitope prioritization pipeline increased accuracy of prediction, reduced false positives and selected potential neo-epitopes to a manageable number for testing in cell-based assays. Citation Format: Priyanka Shah, Kiran V. Paul, Malini Manoharan, Amitabha Chaudhuri, Ravi Gupta. A novel algorithm to identify TCR-binding somatic mutations from human cancers [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 3579. doi:10.1158/1538-7445.AM2017-3579

Abstract A121: Analysis of tumor microenvironment identifies pathways predicting response to checkpoint control inhibitors: A case study comparing the immune microenvironment of uveal melanoma vs skin cutaneous melanoma

The remarkable success of checkpoint control inhibitors in treating a variety of different cancers has necessitated a deeper assessment of the tumor and its microenvironment at the genetic and phenotypic level. Data from recent clinical trials have unequivocally established that the tumor microenvironment significantly impacts the efficacy of immune-oncology drugs. We have taken a gene expression signature-based approach to qualitatively and quantitatively assess the epithelial, stromal and immune content of tumors from RNA-seq data. The immune cell content of the tumors was further stratified to determine the infiltration pattern of nine different immune cell types including CD8+/CD4+ T-cells, Treg cells, NK cells, dendritic cells, B-cells, myeloid-derived suppressor cells (MDSC) and M1/M2 macrophages in the tumors using gene signatures specific to each immune cell type. We applied these signatures singly, or in combination on the TCGA RNA-seq data from 33 cancers. Our analysis supports that there is an underlying molecular symmetry in tumors with higher CD8+ T-cell infiltration across most cancers characterized by the upregulation of a common set of genes that mapped to interferon signaling, antigen presentation and a pro-inflammatory cytokine network pathways. The upregulated genes were strongly correlated with patient survival in skin cutaneous melanoma (SKCM) and other cancers providing a framework for identifying biomarkers of patient response to checkpoint control inhibitors. We present a case study to support the idea that gene expression signatures can address a critical unmet need in the immuno-oncology space, which is to create a framework for treating tumors that carry less mutation burden combined with poor T-cell infiltration. As an example, we analyzed 476 skin cutaneous melanoma (SKCM) and 80 uveal melanoma (UVM) samples from TCGA. The UVM melanoma has ∼10-fold lower median mutational burden compared to SKCM, which correlates with a lower ( Based on our findings, we propose that therapies targeting MDSC cells, or those that can shift the balance towards increased M1 macrophage content over M2 are likely to show efficacy in UVM melanoma, which are largely unresponsive to checkpoint inhibitor molecules. Citation Format: Ravi Gupta, Nitin Mandloi, Ashwini Patil, Malini Manoharan, Rekha Sathian, Kiran V. Paul, Amitabha Chaudhuri. Analysis of tumor microenvironment identifies pathways predicting response to checkpoint control inhibitors: A case study comparing the immune microenvironment of uveal melanoma vs skin cutaneous melanoma [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A121.