Yasin Senbabaoglu

Emerging landscape of oncogenic signatures across human cancers

Cancer therapy is challenged by the diversity of molecular implementations of oncogenic processes and by the resulting variation in therapeutic responses. Projects such as The Cancer Genome Atlas (TCGA) provide molecular tumor maps in unprecedented detail. The interpretation of these maps remains a major challenge. Here we distilled thousands of genetic and epigenetic features altered in cancers to ∼500 selected functional events (SFEs). Using this simplified description, we derived a hierarchical classification of 3,299 TCGA tumors from 12 cancer types. The top classes are dominated by either mutations (M class) or copy number changes (C class). This distinction is clearest at the extremes of genomic instability, indicating the presence of different oncogenic processes. The full hierarchy shows functional event patterns characteristic of multiple cross-tissue groups of tumors, termed oncogenic signature classes. Targetable functional events in a tumor class are suggestive of class-specific combination therapy. These results may assist in the definition of clinical trials to match actionable oncogenic signatures with personalized therapies.

Notch Reporter Activity in Breast Cancer Cell Lines Identifies a Subset of Cells with Stem Cell Activity

Developmental pathways such as Notch play a pivotal role in tissue-specific stem cell self-renewal as well as in tumor development. However, the role of Notch signaling in breast cancer stem cells (CSC) remains to be determined. We utilized a lentiviral Notch reporter system to identify a subset of cells with a higher Notch activity (Notch+) or reduced activity (Notch−) in multiple breast cancer cell lines. Using in vitro and mouse xenotransplantation assays, we investigated the role of the Notch pathway in breast CSC regulation. Breast cancer cells with increased Notch activity displayed increased sphere formation as well as expression of breast CSC markers. Interestingly Notch+ cells displayed higher Notch4 expression in both basal and luminal breast cancer cell lines. Moreover, Notch+ cells demonstrated tumor initiation capacity at serial dilutions in mouse xenografts, whereas Notch− cells failed to generate tumors. γ-Secretase inhibitor (GSI), a Notch blocker but not a chemotherapeutic agent, effectively targets these Notch+ cells in vitro and in mouse xenografts. Furthermore, elevated Notch4 and Hey1 expression in primary patient samples correlated with poor patient survival. Our study revealed a molecular mechanism for the role of Notch-mediated regulation of breast CSCs and provided a compelling rationale for CSC-targeted therapeutics. Mol Cancer Ther; 14(3); 779–87. ©2015 AACR.

Graph Curvature for Differentiating Cancer Networks

Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene co-expression networks derived from large-scale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks.

The landscape of T cell infiltration in human cancer and its association with antigen presenting gene expression

One sentence summary In silico decomposition of the immune microenvironment among common tumor types identified clear cell renal cell carcinoma as the most highly infiltrated by T-cells and further analysis of this tumor type revealed three distinct and clinically relevant clusters which were validated in an independent cohort. Abstract Infiltrating T cells in the tumor microenvironment have crucial roles in the competing processes of pro-tumor and anti-tumor immune response. However, the infiltration level of distinct T cell subsets and the signals that draw them into a tumor, such as the expression of antigen presenting machinery (APM) genes, remain poorly characterized across human cancers. Here, we define a novel mRNA-based T cell infiltration score (TIS) and profile infiltration levels in 19 tumor types. We find that clear cell renal cell carcinoma (ccRCC) is the highest for TIS and among the highest for the correlation between TIS and APM expression, despite a modest mutation burden. This finding is contrary to the expectation that immune infiltration and mutation burden are linked. To further characterize the immune infiltration in ccRCC, we use RNA-seq data to computationally infer the infiltration levels of 24 immune cell types in a discovery cohort of 415 ccRCC patients and validate our findings in an independent cohort of 101 ccRCC patients. We find three clusters of tumors that are primarily separated by levels of T cell infiltration and APM gene expression. In ccRCC, the levels of Th17 cells and the ratio of CD8+ T/Treg levels are associated with improved survival whereas the levels of Th2 cells and Tregs are associated with negative clinical outcome. Our analysis illustrates the utility of computational immune cell decomposition for solid tumors, and the potential of this method to guide clinical decision-making.

Abstract PR06: Overcoming intratumor T-cell exclusion by modulation of lactate metabolism to improve immune checkpoint therapies in aggressive breast cancer

Background: Breast cancer (BC) has historically been considered immunologically silent; however, several observations indicate that potentiation of immune functions can benefit BC patients. Intratumor T-cell infiltration has prognostic significance in patients with BC across different molecular and histological categories. In addition, PD-L1 can be overexpressed in BC, in particular in the highly aggressive triple negative BC (TNBC) subtype. This is associated with poor prognosis specifically in patients with luminal B and basal-like phenotypes, thus making these subtypes rational targets of PD-1/PD-L1 axis blockade treatments. However, initial results from early-phase clinical trials show a modest activity of immune checkpoint blockade monotherapy against BC, with 19% TNBC and 3-12% hormone receptor-positive patients achieving a clinical response to anti-PD-1/PD-L1 therapies. Lack of inflammation and T-cell infiltration at the tumor site are characteristic features of tumors that do not respond to checkpoint blockade. Since BC is typically poorly infiltrated by T cells, having strategies that reverse this immune exclusion as well as non-invasive modalities to predict this effect are crucial to improve the clinical efficacy of immune checkpoint blockade. Experimental Design: Our working model is that tumor glycolysis (lactate) and T-cell infiltration are mechanistically interdependent, since we reasoned that a highly glycolytic tumor microenvironment (due to lactate production) could hamper survival, expansion and effector functions of T cells in BC lesions, thus explaining T-cell exclusion. Therefore, we tested whether genetic and/or pharmacologic inhibition of lactate production/consumption could restore intratumor T-cell infiltration and immune function in BC models, thus favoring tumor responsiveness to checkpoint blockade. Results: By interrogating a compendium of 4 BC patient gene expression datasets, we found that patients harboring tumors with high expression of lactate dehydrogenase A (LDH-A) or the lactate transporters MCT-1/4 have a significantly higher risk to develop metastases (p −16 ), whereas those having tumors with increased expression of CD3 and CD8 transcripts experience a better prognosis (p −16 ). Gene expression data from MSKCC9s cBio Portal showed an inverse correlation between glycolysis- and immune-related gene expression signatures in BC patients, which was in agreement with our hypothesis. To mechanistically demonstrate the impact of lactate metabolism on intratumor T-cell infiltration in BC, we generated an LDH-A-knocked-down variant (LDH-A KD) of the metastatic TNBC murine model 4T1, and studied its growth and immune infiltrate in vivo in comparison with the control 4T1 tumor. Animals implanted with LDH-A KD 4T1 showed a 5-fold increase in tumor-infiltrating CD3 + T cells and a 4-fold reduction in tumor-associated macrophages, and experienced a significantly prolonged survival. LDH-A KD tumors could be completely eradicated in immunocompetent but not in immunodeficient mice, further supporting the immunologic basis of the antitumor effects of LDH-A inhibition. In vitro analyses showed that proliferation, activation and pro-inflammatory cytokine release of activated CD8 T cells were significantly hampered when they were co-cultured with 4T1 cells. Of note, blocking lactate transport with two new MCT-1/4 small-molecule inhibitors promoted immune functions of CD8 T cells cultured with 4T1, without showing significant toxicity in cultures of T cells alone. Citation Format: Roberta Zappasodi, Arnab Ghosh, Inna Serganova, Ivan Cohen, Yasin Senbabaoglu, Masahiro Shindo, Mayuresh M. Mane, Avigdor Leftin, Ellen Ackerstaff, Jason A. Koutcher, Jedd D. Wolchok, Ronald G. Blasberg, Taha Merghoub. Overcoming intratumor T-cell exclusion by modulation of lactate metabolism to improve immune checkpoint therapies in aggressive breast cancer [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 PR06.