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Supplementary Figures S1-5

PDF file 1227K, This file contains Supplemental Figures 1-7, which provide additional supporting information for each of the main figures

Table S3

Tumor-associated macrophages (TAM) are regulators of extracellular matrix (ECM) remodeling and metastatic progression, the main cause of cancer-associated death. We found that disabled homolog 2 mitogen-responsive phosphoprotein (DAB2) is highly expressed in tumor-infiltrating TAMs and that its genetic ablation significantly impairs lung metastasis formation. DAB2-expressing TAMs, mainly localized along the tumor-invasive front, participate in integrin recycling, ECM remodeling, and directional migration in a tridimensional matrix. DAB2+ macrophages escort the invasive dissemination of cancer cells by a mechanosensing pathway requiring the transcription factor YAP. In human lobular breast and gastric carcinomas, DAB2+ TAMs correlated with a poor clinical outcome, identifying DAB2 as potential prognostic biomarker for stratification of patients with cancer. DAB2 is therefore central for the prometastatic activity of TAMs.Significance:DAB2 expression in macrophages is essential for metastasis formation but not primary tumor growth. Mechanosensing cues, activating the complex YAP–TAZ, regulate DAB2 in macrophages, which in turn controls integrin recycling and ECM remodeling in 3-D tissue matrix. The presence of DAB2+ TAMs in patients with cancer correlates with worse prognosis.This article is highlighted in the In This Issue feature, p. 1611

Table S8

Supplementary Information

Supplementary Figures, Tables, Methods

PDF file 146K, This file contains the legends to Supplementary Figures 1-7 and Supplementary methods

Marker genes for each cell type identified in tumor-infiltrating myeloid cells.Related to Fig.1A

S1 XLSX file 63K, This Supplementary Table contains the results of ORF screen to identify genes that can rescue the suppression of TBK1 in a KRAS-dependent cell line

Table S2

Table S7

Marker genes for macrophages clusters from WT and Dab2 KO samples. Related to Fig. 1C-D

Table S5

Table S4

Table S6

Description of the functional status of WT and Dab2 KO macrophages. Related to Fig. 1C-D

Cancer immunotherapy with immune checkpoint blockade (ICB) has transformed the treatment of melanoma, although intrinsic or acquired resistance develops in nearly half of patients. Tumor-infiltrating CD8+ T lymphocytes (TILs) are key determinants of anti-tumor immunity in melanoma and other cancers, and single-cell RNA-sequencing has identified T cell states associated with improved clinical response to ICB, as well as adoptive T cell therapy (ACT). Despite these advances, strategies to identify and analyze tumor-reactive TILs in ICB-resistant patients remain limited. Here, we demonstrate that TILs from ICB-resistant melanoma patients can recognize and eliminate autologous tumor cells independent of class I HLA-TCR interactions. TILs eliminated matched melanoma cells in a time and dose-dependent fashion associated with secretion of effector cytokines. Strikingly, the deletion of B2M (resulting in loss of class I HLA surface expression) did not alter the activity of these TILs. Immunophenotyping studies confirmed that TILs are largely (>95%) effector memory (Tem) CD8 T cells (CD45RA-CD45RO+CCR7-) and give rise to terminal effector cells after co-culture with matched melanoma cells. Further, the elimination of melanoma cells by TILs required intact JAK1/2 signaling, although interferon-gamma (IFNγ) was neither necessary nor sufficient for tumor cell elimination. Together, these findings demonstrate that expanded TILs from ICB-resistant melanoma patients are capable of eliminating melanoma cells via a novel, class I MHC-independent mechanism. Citation Format: Hongyan Xie, Aiping Jiang, Anne Jenney, Yi Sun, Tatyana Sharova, Moshe Sade-Feldman, Or-yam Revach, Angelina Cicerchia, Martin Q. Rasmussen, Nir Hacohen, Robert T. Manguso, Russell W. Jenkins. Class I HLA-independent lysis of immunotherapy-resistant melanoma by CD8 T cells. [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 4072.

Background: Immunologic tumor control involves coordination of multiple cell types, but the organization of these interactions in human tumors is poorly understood. We recently reported that immunogenic tumors contain spatially-localized multicellular immunity hubs characterized by expression of interferon-stimulated genes, including CXCL10/CXCL11 (T cell attracting chemokines), and the presence of IFNG+ T cells. This suggested a positive feedback loop where T cell-derived IFNγ stimulates production of CXCR3 ligands, thereby attracting more T cells. However, we did not know (1) whether these hubs predict response to immunotherapy and (2) how hubs intersect with the various CD8 T cell states which play central roles in anti-tumor immunity. Methods: To understand the composition of this immunity hub and its potential association with immunotherapy response, we performed multiplex RNA FISH to visualize hub components in NSCLC tissue from 68 patients prior to PD1-blockade. Cells were segmented and phenotyped automatically. We additionally imaged serial sections with a second panel for markers of CD8 T cell state. We then computationally registered sequential images, integrating our panels. To identify hubs in an unbiased manner, we employed kmeans clustering. Results: We found that the presence of the immunity hub is predictive of subsequent response to PD1-blockade. Image registration revealed that hubs are enriched for CD8 T cells in multiple states, confirming their role as key sites of anti-tumor T cell activity. Furthermore, immunity hubs in responders contained more activated CD8 T cells and IFNG+ cells than those in nonresponders. To determine how hub heterogeneity may influence hub functions, we subclustered hubs by phenotypic composition. This analysis uncovered a ‘hybrid hub’ subclass that spatially overlaps with structures containing stem-like TCF7+ CD8 T cells, resembling the interfollicular zone of lymph nodes. The presence of a single hybrid hub was strongly associated with RECIST response (p = 0.0005), found in 85% of responders and only 24% of non-responders. Hybrid hubs also showed a striking association with patient PFS (p = 0.0014). Using ultra-highplex RNA ISH technologies, we further explored the hybrid hubs and found they are enriched in macrophages that express CXCR3 ligands. Conclusions: Our study provides insight into the multicellular networks that underlie anti-tumor immunity. Immunity hubs are predictive of response to immunotherapy in human lung cancer and organize intratumoral CD8 T cell activity. Moreover, hybrid hubs may represent an active intratumoral niche for tumor-specific stem-like T cells that sustain anti-tumor immunity. These multicellular networks are excellent candidates for biomarker development and targets for immunotherapy. Citation Format: Jonathan Chen, Linda Nieman, Maxwell Spurrell, Justin Gainor, Nir Hacohen. Spatial clustering reveals immune hub interaction with reservoir of stem-like CD8 T cells and predicts immunotherapy response in lung cancer patients. [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 5784.

Despite the unprecedented success of immune checkpoint blockade (ICB) in melanoma and other cancers, therapeutic resistance remains a major challenge. CD38, an ecto-enzyme involved in NAD+ catabolism, is upregulated in dysfunctional/exhausted CD8+ T cells in human melanoma. As enrichment of dysfunctional CD8+ T cells is associated with lack of response to ICB, and NAD+ depletion via enhanced CD38 activity has been associated with diminished immune response, we hypothesized that CD38 might represent an attractive target to overcome resistance to ICB. While CD38 blockade has been shown to augment response to ICB in murine tumor models, the specific role of CD38 signaling in CD8 T cell exhaustion, and the therapeutic relevance of CD38 in human cancer have not been defined. Here, we confirm and extend previous observations that CD38 is enriched in exhausted CD8+ T cells during tumor progression and in response to ICB. Further, we demonstrate that disrupting CD38 signaling via neutralizing antibodies or pharmacological inhibition enhances response to ICB using established murine tumor models and patient-derived tumor explant models. Notably, we observed 54% response rate to combination PD-1/CD38 blockade using a cohort (n=35) of patient-derived organotypic tumor spheroids (PDOTS) from patients with ICB-refractory melanoma (11.4% response rate to single-agent PD-1 blockade). Supplementation of nicotinamide riboside (NR) to boost NAD+ levels mimicked the effects CD38 blockade/inhibition on PD-1 response, whereas FK866, an inhibitor of NAMPT a key step in NAD+ biosynthesis, blunted the response to combined PD-1/CD38 blockade, suggesting a major role for NAD+ in the efficacy of CD38 blockade/inhibition. Lastly, we demonstrate that in vitro CD38 inhibition/blockade in CD8+ T cells increases the levels of TCF7 (an effector/memory T cell transcription factor), decreases surface expression of co-inhibitory receptors (e.g., TIM-3, CD39, PD-1), and improves effector CD8 T cell function. Taken together, these data confirm a role for CD38 in CD8+ T cell exhaustion in melanoma and support further pre-clinical and clinical development of this novel therapeutic strategy to enhance anti-tumor immune responses. Citation Format: Or-Yam Revach, Angelina M. Cicerchia, Moshe Sade-Feldman, Seth Anderson, Robert T. Manguso, Nir Hacohen, Russell W. Jenkins. Targeting CD38 on exhausted T cells overcomes resistance to cancer immunotherapy [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 3250.

Responders to checkpoint blockade in Non Small Cell Lung Cancer (NSCLC) often feature an inflamed microenvironment prior to therapy. However, the complete set of molecular drivers connecting this histologic observation to enhanced tumor clearance remain enigmatic. In updated analysis of the Stand Up 2 Cancer-Mark Foundation (SU2C-MARK) Cohort - a collection of 393 patients with whole exome and/or RNA sequencing along with matched checkpoint blockade response annotation - we identify a prominent predictive role for inducible components of the immunoproteasome, a non-canonical peptide processing complex upstream of antigen presentation. Notably, these subunits are enriched as predictors relative to interferon-inducible genes as well as proteasome components in general, and are consistently associated with objective response, progression-free survival and overall survival. Expression of Immunoproteasome subunits associates positively with TCR (but not BCR) burden, supporting a mechanistic model in which enhanced immunoproteasome processivity leads to superior T-cell recognition. Furthermore, although they are known to be targets of interferon gamma (IFNɣ), we demonstrate that their expression is better modeled via a combination of IFNɣ and tumor necrosis factor-α (TNFα) levels, suggesting they may act as integrators of multiple cytokine cascades. Given the fact that the immunoproteasome can alter both antigen quantity as well as quality (including peptide cleavage site preference), the enhanced expression of this complex in the setting of checkpoint blockade response may have important implications for modeling of antigen presentation. These data also suggest novel strategies to enhance immune checkpoint blockade. Citation Format: Vivek Naranbhai, Arvind Ravi, Matthew Hellmann, Monica Arniella, Mark Holton, Samuel Freeman, Chip Stewart, Ignaty Leshchiner, Jaegil Kim, Yo Akiyama, Aaron Griffin, Natalie Vokes, Mustafa Sakhi, Vashine Kamesan, Hira Rizvi, Biagio Ricciuti, Patrick Forde, Valsamo Anagnostou, Jonathan Riess, Don Gibbons, Nathan Pennell, Vamsidhar Velcheti, Subba Digumarthy, Mari Mino-Kenudson, Andrea Califano, John Heymach, Roy Herbst, Julie Brahmer, Kurt Schalper, Victor Velculescu, Brian Henick, Naiyer Rizvi, Pasi Janne, Mark Awad, Andrew Chow, Benjamin Greenbaum, Marta Luksza, Alice Shaw, Jedd Wolchok, Nir Hacohen, Gad Getz, Justin Gainor. Immunoproteasome expression and checkpoint blockade response in advanced non-small cell lung cancer [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 3468.

Circulating tumor cells (CTC) are shed by cancer into the bloodstream, where a viable subset overcomes oxidative stress to initiate metastasis. We show that single CTCs from patients with melanoma coordinately upregulate lipogenesis and iron homeostasis pathways. These are correlated with both intrinsic and acquired resistance to BRAF inhibitors across clonal cultures of BRAF-mutant CTCs. The lipogenesis regulator SREBP2 directly induces transcription of the iron carrier Transferrin (TF), reducing intracellular iron pools, reactive oxygen species, and lipid peroxidation, thereby conferring resistance to inducers of ferroptosis. Knockdown of endogenous TF impairs tumor formation by melanoma CTCs, and their tumorigenic defects are partially rescued by the lipophilic antioxidants ferrostatin-1 and vitamin E. In a prospective melanoma cohort, presence of CTCs with high lipogenic and iron metabolic RNA signatures is correlated with adverse clinical outcome, irrespective of treatment regimen. Thus, SREBP2-driven iron homeostatic pathways contribute to cancer progression, drug resistance, and metastasis. Significance: Through single-cell analysis of primary and cultured melanoma CTCs, we have uncovered intrinsic cancer cell heterogeneity within lipogenic and iron homeostatic pathways that modulates resistance to BRAF inhibitors and to ferroptosis inducers. Activation of these pathways within CTCs is correlated with adverse clinical outcome, pointing to therapeutic opportunities. This article is highlighted in the In This Issue feature, p. 521

Despite the clinical success of targeted inhibitors, tumor responses to these agents are transient, and drug-tolerant residual cells seed resistance. Understanding the role of tumor-intrinsic mechanisms and effects of the tumor microenvironment in mediating drug tolerance will guide and optimize targeted therapies. Given similarities between drug tolerance and cellular dormancy, we studied the role of nuclear receptor subfamily 2 group F member 1 (NR2F1) in response to targeted therapy. We used BRAF-mutant cutaneous melanoma models treated with BRAF and MEK inhibitors (BRAFi + MEKi) since patients treated with this combination typically develop resistance. The aged tumor microenvironment has been shown to increase therapy resistance, and we find that melanoma cells in aged mice express higher levels of NR2F1 than when the same cells are injected into young animals. Transcriptomic analysis of melanoma patient samples treated with BRAFi + MEKi showed increased expression of NR2F1 post-treatment. Similarly, NR2F1 was highly expressed in minimal residual disease collected on BRAFi + MEKi treatment in patient- and xenograft-derived tumors. High expression of NR2F1 promotes tumor survival and invasion in the presence of BRAFi + MEKi in vitro leading to tolerance to BRAFi + MEKi efficacy in vivo. Depletion of NR2F1 in YUMM1.7 allografts grown in aged mice improved response to the combination therapy. Altogether, our findings suggest that NR2F1 promotes drug tolerance leading to minimal residual disease in melanoma and that NR2F1-high cells may be targeted with CDK4/6 inhibitors to improve targeted therapy outcomes in melanoma patients. Citation Format: Manoela Tiago, Timothy J. Purwin, Mitchell E. Fane, Yash Chhabra, Jessica L. F. Teh, Rama Kadamb, Weijia Cai, Inna Chervoneva, Sheera Rosenbaum, Vivian Chua, Nir Hacohen, Michael A. Davies, Jessie Villanieva, Ashani T. Weeraratna, Claudia Capparelli, Julio A. Aguirre-Ghiso, Andrew E. Aplin. The aged tumor microenvironment influences tolerance to targeted therapy via NR2F1 overexpression in BRAF-mutant melanoma [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr A005.

Pancreatic cancer is a lethal disease in part because tumor cells exist in distinct transcriptional phenotypes (e.g. basal and classical states), each with a selective ability to evade current chemotherapy regimens. Two major mechanisms have been suggested for treatment evasion: 1) intrinsic resistance of certain phenotypes to particular chemotherapy regimens and 2) plasticity of treatment sensitive phenotypes to adopt more resistant phenotypes. However, the relative contribution of these mechanisms to treatment resistance is still poorly understood. Whereas previous work has described the redistribution of tumor cell states under selective treatment pressure, there is no direct evidence that tumor cells exhibit phenotypic plasticity at steady state or with treatment. By leveraging technological advancements in single-cell methods, lineage tracing and functional genomics, we have now shown direct evidence of phenotypic state switching in human pancreatic cancer cell lines. By performing single-cell RNA-seq on 5 barcoded PDAC cell lines over a steady state timecourse and under chemotherapy selective pressure (>600k cells total), we identify unique plasticity phenotypes within these cell lines and infer regulators of these plastic states. We validate the role of several of these regulators using bulk phenotypic CRISPRi screens in these cell lines. We next perform CRISPRi perturbations along with lineage tracing and single-cell multiomics (>300k cells) to dissect the regulatory relationships that underlie these cell states. We identify several novel epithelial and mesenchymal biasing factors, including those with unique roles in the most plastic clones. Collectively, we nominate several regulators that bias PDAC cell states thus posing a paradigm whereby perturbations may be used to homogenize tumor populations towards treatment-sensitive phenotypes. We believe this approach combined with current chemotherapy regimens could benefit pancreatic cancer patients by targeting residual, resistant tumor cells in the localized and metastatic disease settings to improve patient survival. Citation Format: Arnav Mehta, Lynn Bi, Aziz Al'Khafaji, Martin Jankowiak, Milan Parikh, Mehrtash Babadi, Alex Bloemendal, Marc Schwartz, Glen Munson, Joeseph Chan, Cassandra Burdziak, Elisa Donnard, Ryan Park, Chen Lu, Philippe Rigollet, Andrew Aguirre, Vidya Subramanian, Ray Jones, Eric S. Lander, David T. Ting, Dana Pe'er, Nir Hacohen. Quantifying and dissecting pancreatic cancer cell phenotypic plasticity using lineage tracing, single-cell multiomics and CRISPR perturbations reveals novel regulators of plastic states [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B016.

Immune checkpoint blockade (ICB) has revolutionized the treatment of many cancers but has been ineffective for the treatment of microsatellite stable (MSS) PDAC. The lack of efficacy of immunotherapies in PDAC is due to: 1) a desmoplastic tumor microenvironment (TME); 2) the presence of suppressive cells, including myeloid derived suppressor cells and regulatory T cells; and 3) the lack of antigen-presenting dendritic cells (DCs) that are important in priming an effective immune response to generate functionally effective tumor antigen-specific T cells. We recently completed a pilot study of dual ICB (Ipilumamab and Nivolumab) with radiation therapy (SBRT 8Gy for 3 fractions) in a cohort of 25 metastatic PDAC patients that had progressed on conventional chemotherapy; this combination conferred an impressive 18% ORR and 29% disease control rate measured on non-irradiated lesions (historical 0% ORR with ICB in PDAC). This led to a phase 2 study in 30 metastatic PDAC patients using this dual modality treatment paradigm. To understand the role of radiation and ICB in altering the PDAC tumor microenvironment we performed single-cell RNA-sequencing and TCR-sequencing (>180k cells), and single-nucleus RNA-sequencing (>300k cells) on 36 tumor biopsies (23 pre-treatment, 13 paired on-treatment between day 10 and 21) from patients undergoing treatment in our phase 2 study. Tumor tissue was taken from distinct tissue sites, including primary tumors in the pancreas, and liver and abdominal wall metastases. We identified distinct tumor cell state distributions within different tissues, and a redistribution of cells from basal/mesenchymal states to classical states after radiation. We identified several state-specific interferon stimulated gene programs thus cataloging distinct responses of epithelial cells with different transcriptional states. Importantly, we found a redistribution of T cells states towards proliferating and exhausted T cells with unique clonality after radiation. Additionally, the myeloid compartment after radiation was enriched for C1QC+ and MHCII+ macrophage subsets, as well as infiltrating CD16/CD16 monocytes and CD14 monocytes, each showing induction of unique sets of interferon stimulated genes (ISGs). We next sought to better understand immunotherapy resistance mechanisms within these PDAC patients despite finding strong ISG induction in several subsets. We analyzed covarying gene programs and identified multicellular communities of cells before and after radiation that underlie interaction networks associated with radiation. Together our data provides the most comprehensive single-cell atlas of paired biopsies to study tumor and immune cell states in the context of radiation and ICB response. Citation Format: Arnav Mehta, Aparna Parikh, Milan Parikh, Ryan Park, Moshe Sade-Feldman, Lynn Bi, Nicole Carzo, Tarin M. Grillo, Islam Baiev, Olanike Asupoto, Irena Gushterova, Tom LaSalle, Anna Gonye, Emily Blaum, Sebastien Vigneau, Ronan Chaligne, Ana Lako, Thomas Lila, David Nelson, Caroline Porter, Orr Ashenberg, Karthik Jagadesh, William L. Hwang, Christopher Smillie, David P. Ryan, David T. Ting, Theodore Hong, Dana Pe'er, Nir Hacohen. Dissecting the reorganization of pancreatic tumor microenvironments after radiation and immunotherapy reveals insights into immunotherapy resistance [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr C012.

The introduction of checkpoint blockade therapy, specifically anti-PD-1/PD-L1 agents, has transformed the treatment landscape of advanced Non-Small Cell Lung Cancer (NSCLC). While our understanding of the biology underlying immunotherapy in NSCLC is still incomplete, studies to date have established central roles for Tumor Mutation Burden (TMB) and PD-L1 Tumor Proportion Score (PDL1-TPS). In order to expand our understanding of the molecular features underlying response in NSCLC, we describe here the first joint analysis of the Stand Up 2 Cancer-Mark Foundation (SU2C-MARK) Cohort, a collection of 393 patients with whole exome and/or RNA sequencing along with matched checkpoint blockade response annotation. We identify a number of significant associations between molecular features and response, including: 1) favorable and unfavorable genomic subgroups; 2) distinct immune infiltration signatures associated with wound healing (unfavorable) and immune activated (favorable) microenvironments; and 3) a novel de-differentiated tumor-intrinsic subtype characterized by high TMB, immune activation, and enhanced response rate. Taken together, results from this cohort extend our understanding of NSCLC-specific predictors, providing a rich set of molecular and immunologic hypotheses with which to further our understanding of the biology of checkpoint blockade in NSCLC. Citation Format: Arvind Ravi, Justin Gainor, Monica Arniella, Chip Stewart, Sam Freeman, Mark M. Awad, Patrick Forde, Valsamo Anagnostou, Brian Henick, Jonathan W. Riess, Don Gibbons, Nathan Pennell, Vamisdhar Velcheti, Ignaty Leshchiner, Jaegil Kim, Subba Digumarthy, Mari Mino-Kenudson, John Heymach, Natalie Vokes, Andrew Griffin, Biagio Ricciuti, Naiyer Rizvi, Roy Herbst, Victor Velculescu, Julie Brahmer, Kurt Schalper, Pasi Janne, Jedd Wolchok, Alice Shaw, Nir Hacohen, Gad Getz, Matthew D. Hellmann. Integrative genomics of checkpoint blockade response in advanced non-small cell lung cancer [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 3580.

Background: Although BRAF inhibitors combined with EGFR and/or MEK inhibitors have improved efficacy in BRAFV600E colorectal cancer (CRC), response rates remain low and clinical benefit is not durable. Preclinical studies suggest that BRAF-targeted therapy in combination with immune checkpoint blockade could enhance anti-tumor activity. We have previously reported on the efficacy from an ongoing phase 2 clinical trial of anti-PD-1 antibody spartalizumab in combination with BRAF inhibitor dabrafenib and MEK inhibitor trametinib in BRAFV600E CRC patients. Of 26 patients, overall response rate (ORR) was 38% (10/26) and compares favorably to the historical controls in BRAFV600E CRC, yet the mechanisms of patient response in this trial need further investigation. Methods: Single-cell RNA-seq (scRNA-seq) was performed on 23 paired baseline and day 15 tumor biopsies. Patient-derived organoids (PDOs) were generated from baseline tumor biopsies. Results: scRNA-seq of paired biopsies revealed increased CD8+ T cell infiltration after treatment in patients with better clinical outcome (PFS > 6 months, n=11). From the on- versus pre-treatment differentially expression analysis and gene set enrichment analysis in the tumor epithelial compartment, we observed greater induction and enrichment of immune gene signatures such as antigen processing and presentation, type I and II interferon response, chemokine activity, as well as superior MAPK pathway inhibition with therapy in patients with PFS > 6 months. In comparison, patients with PFS < 6 months (n=12) showed less immune gene upregulation and MAPK pathway inhibition in tumor cells. PDOs treated with dabrafenib and trametinib exhibited gene expression changes that mirrored the changes observed in scRNA-seq of tumor cells in the same patients from which they were derived. BRAF/ERKi treatment in PDOs produced greater MAPK pathway inhibition and immune genes induction than BRAF/MEKi. Conclusion: Correlative studies of combined anti-PD-1 and BRAF/MEK inhibition suggest that the tumor-intrinsic immune response induced by MAPK pathway inhibition might underlie cooperativity between BRAF-targeted therapy and immune checkpoint blockade. A greater degree of immune gene induction in tumor cells could be enhanced by superior MAPK pathway inhibition, which provides rationale for further clinical studies. Citation Format: Jun Tian, Jonathan H. Chen, Sherry X. Chao, Karin Pelka, Vjola Jorgji, Islam Baiev, William B. Bradford, Edmond Wong, Princy Sindurakar, Tomonori Oka, Shadmehr Demehri, Nir Hacohen, Ryan B. Corcoran. Combined BRAF, MEK, and PD-1 inhibition in BRAFV600E colorectal cancer patients: Correlative studies from a phase 2 trial [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 LB003.

Understanding the tumor microenvironment (TME) requires more than just a catalog of cell types and gene programs. It is critical to see the spatial organization of the cells are and where they form multicellular interaction networks. Here we present a single-cell spatially resolved transcriptomic analysis of human mismatch repair deficient (MMRd) and proficient (MMRp) colorectal cancer (CRC) specimens. High tumor mutational burden MMRd tumors are known to have an immune response characterized by higher cytolytic T cell infiltrates compared to MMRp tumors, making them an ideal system for spatial single-cell profiling and understanding how the immune-driven programs differ between these tumors. MERFISH is a massively multiplexed single molecule imaging technology which can simultaneously capture and measure the quantity and distribution of hundreds to thousands of RNA species within single cells across a tissue1. We designed a MERFISH library of over 450 genes including genes important to proliferation, apoptosis, immune signaling, immune cell type pathways and other critical pathways in CRC. Patient samples, obtained commercially or through MGH, were hybridized with the designed MERFISH library and stained with a cell boundary marker to delineate cells across the tissue. We performed unsupervised clustering to identify cell types and we calculated spatial statistics to characterize how the cell type distribution varied between MMRd and MMRp tumors. We identified the cellular composition of each tumor, including immune and stromal cells, and the spatial distribution of these cell types. We were able to readily identify all cell types and states previously discovered by single-cell RNA sequencing2 in intact patient specimens, thus providing an accurate map of the cellular composition and spatial organization of these cells in the tumor microenvironment. We transformed these cell types into neighborhoods and discovered a highly organized spatial distribution of most cell types throughout the tumor. While spatial organization was observed in both MMRp and MMRd CRC we saw a significant shift in spatial organization between these tumor classifications notably in the immune population. Further, previously predicted multicellular interaction networks2 appeared as spatially organized structures in the tissue and were distinct in MMRd versus MMRp tumor specimens. Our data provide a richness of concrete hypotheses about which cells are working together, how these cells function cooperatively, and where these cells are located which will be critical in advancing therapy in these immunologically distinct types of colorectal cancer. These cancer maps are critical to truly understand the biology of CRC as well as identify avenues for the development of future therapies for CRC patients. Citation Format: Colles Price, Jonathan H. Chen, Karin Pelka, Sherry Chao, Michael Therrien, Timothy Wiggin, Nicolas Fernandez, Jiang He, George Emanuel, Genevieve Boland, Nir Hacohen. A single-cell spatially resolved map of colorectal cancer identifies novel spatial relationships between cancer cells and the microenvironment [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 2030.

The advent of PD-1/PD-L1 agents has transformed the therapeutic landscape of many advanced cancers, including non-small cell lung cancer (NSCLC). However, our understanding of the genomic biomarkers underlying effective treatment response remain limited. Here we provide updated results from our ongoing effort, the Stand Up To Cancer Lung (SU2C-Lung)/Mark Foundation EXTOLConsortium, a multi-institution collaboration to expand our understanding of the molecular determinants of immunotherapy response in NSCLC. Comprising a set of nearly 400 patients, this cohort enables evaluation of both genomic and transcriptomic factors associated with checkpoint blockade response. In addition to validating previously known associations including TMB and neoantigen burden, we examined transcriptional predictors associated with response. We generated a list of differentially expressed genes with respect to best overall response (BOR), and performed dimensionality reduction using semi-supervised Bayesian Non-Negative Factorization (ssBNMF). We identified 3 distinct clusters with strong sample membership. Characterization of these subtypes revealed varying levels of immune infiltrate, histologic composition, and response rates to checkpoint blockade. Of these three subtypes, two were associated with low response rates to PD-1/PD-L1 blockade, suggesting the existence of distinct avenues toward resistance. To further characterize these transcriptional subtypes, we used ssBNMF marker genes to classify publicly available NSCLC samples from The Cancer Genome Atlas (TCGA), along with gene expression from a smaller cohort of large-cell neuroendocrine (LCNE) samples. Histologic composition showed good concordance with our SU2C samples, and redemonstrated observations within our smaller SU2C cohort of distinct immuno-suppressive and immuno-depleted milieus associated with resistance. Citation Format: Monica B. Arniella, Arvind Ravi, Justin Gainor, Chip Stewart, Sam Freeman, Mark Awad, Patrick Forde, Valsamo Anagnostou, Brian Henick, Jonathan W. Riess, Don Gibbons, Nathan Pennell, Vamsidhar Velcheti, Ignaty Leshchiner, Jaegil Kim, Subba Digumarthy, Mari Mino-Kenudson, John Heymach, Nir Hacohen, Naiyer Rizvi, Roy Herbst, Victor E. Velculescu, Julie Brahmer, Kurt Schalper, Pasi Jänne, Jedd Wolchok, Alice Shaw, Gad Getz, Matthew D. Hellman. An SU2C-Mark Foundation Lung collaborative update: integrative genomics identifies distinct transcriptional states associated with checkpoint blockade resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB197.

Background: Despite recent successes with immune checkpoint blockade (ICB) in melanoma, the prognosis for most patients remains dire. Whereas a small fraction of patients are able to achieve disease control, most do not respond or are limited by immune-related adverse events. Robust non-invasive predictors of ICB response have the potential to guide clinical decision making and alter management of patients, however, no such predictors currently exist. Methods: We applied a highly-multiplex proximity extension assay (Olink Proteomics) to simultaneously detect >1000 proteins in the plasma of metastatic melanoma patients treated with anti-PD-1 antibodies. Our training cohort comprised of 116 patients, 66 of whom were classified as having treatment benefit (responders, R) and 50 having no benefit (non-responders, NR). An additional 58 patients comprised a validation cohort, including 44 R and 14 NR. Plasma samples were collected at baseline, and at 6-weeks and 6-months after starting treatment. A subset of patients additionally had single-cell RNA-seq performed on tumor tissue. Group differences and treatment effects were evaluated using a linear model with maximum likelihood estimation for model parameters and Benjamini and Hochberg multiple hypothesis correction. Results: At the baseline, 6 significantly differentially expressed (DE) proteins were identified between R and NR. In particular, we found elevated expression of ST2 and IL-6, two key immunoregulatory proteins, in NR. At the 6-week on-treatment time point, more dynamic changes occurred and 79 significantly DE proteins were identified between R and NR, including proteins implicated in primary or acquired resistance, such as IL-8, MIA, TNFR1 and potential novel targets as MCP-4/CCL13, ICOSLG and VEGF. Proteomic changes identified at baseline and 6-weeks were more profound at 6-months post-treatment, and moreover 238 DE proteins were confirmed significant between R and NR at this later time-point. Importantly, we were able to leverage these differences to build classifiers of R and NR subsets. We next looked at the mRNA expression of DE proteins within the tumor microenvironment by leveraging scRNAseq data from a subset of these patients. We uncovered enriched expression of these genes in certain myeloid and exhausted T cell subsets, thus shedding insight into the potential role of these cell subsets in ICB response. Conclusions: Whole plasma proteomic profiling of anti-PD1 treated patients identified important tumor and immune changes associated with R and NR. Advanced proteomic technologies enabling an easy and non-invasive means for the discovery of circulatory protein biomarkers may predict sensitivity to immunotherapy and uncover biological insights underlying primary resistance. Citation Format: Arnav Mehta, Marijana Rucevic, Emmett Sprecher, Lina H. Rosenberg, David Lieb, Gyulnara Kasumova, Michelle S. Kim, Xue Bai, Dennie T. Frederick, Keith Flaherty, Ryan J. Sullivan, Nir Hacohen, Genevieve Boland. The use of blood-based protein biomarkers to uncover determinants of immunotherapy response in melanoma [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 LB-260.

Cancer immunotherapy with checkpoint blockade has improved survival and outcomes in melanoma, but still a majority of patients do not respond. Both high tumor mutation burden (TMB) and high T cell infiltration have been associated with response, but integrative models based on DNA or RNA assays have not been comprehensively explored and validated. Focusing on melanomas from patients receiving checkpoint blockade, we generated new and aggregated existing datasets of whole exome sequencing (WES) (n = 189 total) and bulk RNA sequencing (n = 154 total) to derive genomic and transcriptomic factors that predict survival and response to immunotherapy in melanoma. We quantified T and B cell infiltrates using rearranged T cell receptor (TCR) and immunoglobulin (Ig) sequences, respectively, from DNA or RNA sequencing. High levels of rearranged TCR reads or rearranged Ig reads in RNA-seq were associated with survival (P = 0.0046, P = 0.015) and response (P = 0.0034, P = 0.047). We created RNA-based metrics of T and B cell burden (TCBRNA or BCBRNA) by normalizing the number of rearranged TCR reads by the total number of mapped reads. When we analyzed WES data in patients for whom DNA and RNA were extracted from the same region, we found that the TCBDNA correlated with TCBRNA (rho = 0.73) and BCBDNA with BCBRNA (rho = 0.41), demonstrating that the level of lymphocyte infiltration can be estimated using rearranged TCR or Ig reads from tumor WES alone. We found that TCBDNA and BCBDNA both associated with survival (P = 0.0023 and 0.0089). In a combined model, patients with high TMB and high TCB DNA survived longer (P = 2.4e-4, HR = 2.68) and had a higher response rate (Fisher P = 0.028). This combined model was superior to models with TMB or TCBDNA alone. Similarly, patients with high TMB and high BCBDNA had longer survival and higher response rates (log-rank P = 0.0029, HR = 2.64, Fisher P = 0.015). We reanalyzed stage III/IV melanomas from TCGA and found that the TMB high, TCBDNA high subgroup had increased survival (P = 0.007). Next, clustering of tumor transcriptomes identified 5 tumor subtypes based on melanocyte differentiation, immune infiltration and keratin levels. These melanoma subtypes were associated with survival outcomes after immunotherapy (P = 0.019). We found that TBX3, a tumor-expressed transcription factor enriched in poorly differentiated melanomas, was over-expressed among non-responders within the immune-infiltrated subtype and among all patients (P = 3.9e-4, P = 8.7e-5). Patients whose tumors had high immune infiltrate and low expression of TBX3 had longer survival (P = 1.6e-5, HR = 3.39), however this subgroup did not have longer survival in an independent cohort (n = 73, P = 0.10, HR = 2.63). In conclusion, we demonstrate both RNA-based (immune infiltrate and tumor subtype) and DNA-based metrics (TMB/TCB or TMB/BCB) can be used as pre-treatment predictors of survival after checkpoint blockade in melanoma. Citation Format: Samuel S. Freeman, Moshe Sade-Feldman, Jaegil Kim, Chip Stewart, Arvind Ravi, Monica Arniella, Keren Yizhak, Ignaty Leshchiner, Liudmila Elagina, Oliver Spiro, Dimitri Livitz, Daniel Rosebrock, François Aguet, Jian Carrot-Zhang, Anna Gonye, Gavin Ha, Ziao Lin, Jonathan H. Chen, Dennie T. Frederick, Michal Barzily-Rokni, Marc R. Hammond, Hans Vitzthum, Shauna M. Blackmon, Yunxin J. Jiao, Donald P. Lawrence, Lyn M. Duncan, Anat Stemmer-Rachamimov, Jennifer A. Wargo, Keith T. Flaherty, Genevieve M. Boland, Ryan J. Sullivan, Matthew Meyerson, Gad Getz, Nir Hacohen. Combined signals from tumor and immune cells predict outcomes of checkpoint inhibition in melanoma [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 6670.

PD-1/PD-L1 checkpoint blockade has been a landmark advance for many patients suffering from advanced non-small cell lung cancer (NSCLC). However, detailed biomarkers of response beyond tumor mutational burden (TMB) are still poorly understood. As part of the effort to elucidate these additional signatures, we describe our progress on the Stand Up to Cancer Lung (SU2C-Lung) cohort. Initial characterization of exomes recapitulates mutational and copy number profiles seen in The Cancer Genome Atlas (TCGA) project. To better define expression subtypes using RNA sequencing, we performed non-negative matrix factorization (NMF) across an aggregated set of publicly available NSCLC expression data (including adenocarcinoma, squamous cell carcinoma, and large cell neuroendocrine histologies), and demonstrate good concordance in the SU2C-Lung cohort between this expression-based classifier and clinically annotated histology. To gain further insight into how immune cell infiltrates vary across our cohort, we additionally tested two common deconvolution algorithms, EPIC and CIBERSORT. While these two methods agree for some prominent cell types, such as B cells and CD4 T cells, discrepancies in minor infiltrating components such as NK cells may suggest a limit to the inference of rare subpopulations from bulk sequencing data.Finally, we describe a novel approach for determining single-gene predictors of response. Using the method, which is based on comparison of top single transcriptional features identified from random bootstraps of the full cohort as compared to a set of background shuffles, we are able to show that we remain powered for discovery of RNA response biomarkers despite the typically burdensome toll of multiple hypothesis correction at genome wide scale. Acknowledgment: Supported by Stand Up To Cancer-American Cancer Society Lung Cancer Dream Team Translational Research Grant SU2C-AACR-DT17-15. Citation Format: Monica Arniella, Arvind Ravi, Chip Stewart, Sam Freeman, Mark Awad, Patrick Forde, Valsamo Anagnostou, Brian Henick, Jonathan Riess, Don Gibbons, Nathan Pennell, Vamsidhar Velcheti, Ignaty Leshchiner, Jaegil Kim, Subba Digumarthy, Mari Mino-Kenudson, John Heymach, Nir Hacohen, Naiyer Rizvi, Roy Herbst, Victor Velculescu, Julie Brahmer, Kurt Schalper, Pasi Jänne, Jedd Wolchok, Alice Shaw, Justin Gainor, Matthew Hellmann, Gad Getz. Integrative genomic analysis of checkpoint blockade in lung cancer: A multi-institution SU2C collaborative [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 5902.

Neoantigen-based therapies hold the promise of being safe, personalized anti-cancer therapies for a broad range of cancers. A crucial step for the development of effective neoantigen therapies is the identification of putative tumor specific neoantigens typically achieved through in silico analyses. In silico-based approaches have the benefit of being fast, modular and reproducible. A wide range of tools are available for variant calling, determining peptide-HLA binding affinity, peptide foreignness, agritopicity and more, and researchers are continuously adding to the lot. However, there does not currently exist a common reference data set with which these different approaches can be compared, and the key parameters for effective neoantigen identification remain elusive. Here we introduce a consortium-based initiative, the Tumor nEoantigen SeLection Alliance (TESLA), to address these needs and describe straight-forward strategies through which the sensitivity and ranking ability of neoantigen prediction methods can be improved. TESLA participants were provided with whole exome and RNA sequencing from six tumors (3 melanoma and 3 NSCLC) and in turn submitted predictions for immunogenic peptides. Twenty-five groups from academia, pharma and biotech participated to this challenge. Peptides identification and ranking across the teams were assessed and showed little overlap. The limited overlap could not be explained simply by differences in variant calling. From these predictions, 608 peptides regrouping the teams' highly ranked epitopes plus epitopes frequently called and ranked across the teams, were assessed for T-cell recognition in patient-matched samples as well as for in-vitro MHC binding affinity. Analyses showed that peptides recognized by T-cells had significantly stronger MHC binding affinity and were derived from genes with significantly higher gene expression. Concomitantly, neoantigen pipelines which prioritized epitopes with strong binding affinity and/or which filtered out those originating from genes with low tumor variant allele fraction or low gene expression were associated with improved ability to identify and rank neoantigens. Direct interventions on participant predictions using these identified traits demonstrated substantial improvement in the performance of the neoantigen predictions. Pipeline analysis indicated that there are a range of approaches to neoantigen prediction and improving upon an existing neoantigen pipeline requires assessing that pipeline for a range of characteristics, including variant detection ability, peptide filtering ability, and peptide ranking ability, and improving those areas where the pipeline performance is sub-optimal. TESLA data will be continually available and serve as a living benchmark to improve neoantigen prediction. Citation Format: Daniel K. Wells, Kristen Dang, Vanessa M. Hubbard-Lucey, Kathleen C. Sheehan, Andrew Lamb, Jeffrey P. Ward, John Sidney, Ana B. Blazquez, Andrew J. Rech, Jesse Zaretsky, Begonya Comin-Anduix, Alphonsus H. Ng, William Chour, Thomas V. Yu, Hira Rizvi, Jia Chen, Patrice Manning, Taha Merghoub, Justin Guinney, Adam Kolom, Cheryl Selinsky, Antoni Ribas, Matthew D. Hellmann, Ton N. Schumacher, Nir Hacohen, Pia Kvistborg, Alessandro Sette, James R. Heath, Nina Bhardwaj, Fred Ramsdell, Robert D. Schreiber, Nadine A. Defranoux, TESLA Consortium. Strategies to improve the sensitivity and ranking ability of neoantigen prediction methods: Report on the results of the Tumor nEoantigen SeLection Alliance (TESLA) [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 3210.

How the genomic landscape of a tumor shapes and is shaped by anti-tumor immunity has not been systematically explored. Using large-scale genomic datasets of solid tissue tumor biopsies, we quantified the cytolytic activity of the local immune infiltrate and identified associated properties across 18 tumor types. The number of predicted MHC Class I-associated neoantigens was correlated with cytolytic activity and was lower than expected in colorectal and other tumors, suggesting immune-mediated elimination. We identified recurrently mutated genes that showed positive association with cytolytic activity, including beta-2-microglobulin (B2M), HLA-A, -B and -C and Caspase 8 (CASP8), highlighting loss of antigen presentation and blockade of extrinsic apoptosis as key strategies of resistance to cytolytic activity. Genetic amplifications were also associated with high cytolytic activity, including immunosuppressive factors such as PDL1/2 and ALOX12B/15B. Our genetic findings thus provide evidence for immunoediting in tumors and uncover mechanisms of tumor-intrinsic resistance to cytolytic activity. Citation Format: Nir Hacohen. Genetics of immune escape. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr SY11-04. doi:10.1158/1538-7445.AM2015-SY11-04

Cancer genome sequencing has enabled the rapid identification of the complete repertoire of coding sequence mutations within a patient's tumor and facilitated their use as personalized immunogens. Although a variety of techniques are available to assist in the selection of mutation-defined epitopes to be included within the tumor vaccine, the ability of the peptide to bind to patient MHC is a key gateway to peptide presentation. With advances in the accuracy of predictive algorithms for MHC class I binding, choosing epitopes on the basis of predicted affinity provides a rapid and unbiased approach to epitope prioritization. We show herein the retrospective application of a prediction algorithm to a large set of bona fide T cell–defined mutated human tumor antigens that induced immune responses, most of which were associated with tumor regression or long-term disease stability. The results support the application of this approach for epitope selection and reveal informative features of these naturally occurring epitopes to aid in epitope prioritization for use in tumor vaccines. Cancer Immunol Res; 2(6); 522–9. ©2014 AACR.

Immune checkpoint blockade (ICB) has revolutionized the treatment of metastatic melanoma, however, cases of resistance have now begun to emerge. We report here a case of acquired resistance by melanoma phenotypic transformation in a patient treated on a Phase 1b/2 clinical trial (NCT02437136) with anti-PD1 (Pembrolizumab) and a histone deacetylase (HDAC) inhibitor (Entinostat). The patient presented to MGH with metastatic melanoma confirmed by core-needle biopsy of a liver lesion. A PET/CT scan one month after starting the trial revealed interval regression of liver and bone lesions, however, four months later the patient presented with disease progression. A tumor debulked from the L2 vertebral body at that time revealed the presence of a pleomorphic rhabdomyosarcoma. The patient was started on anti-CTLA4 (Ipilumimab) with further disease progression, and surgical specimens thereafter revealed either melanoma or rhabdomyosarcoma. Tumor tissue was evaluated for markers by immunohistochemistry. All tumors (5 specimens in total) were subjected to whole exosome sequencing (WES), RNA-sequencing (RNAseq) and epigenomic sequencing (ATACseq). WES revealed 844 mutations were shared between all tumors, suggesting a common ancestor including driver mutations in NRAS (G13D), NF1 (E1121* and W1314*) and the TERT2 promoter, among others. The pre-treatment melanoma biopsy had positive staining for S100 and MART-1, nuclear staining patterns for SOX10 and MITF, and were BRAF V600E negative. Importantly, 80% of the tumor cells had strong staining for PD-L1 expression and CD8 CTL infiltration was associated with 25% of the tumor. The post-treatment rhabdomyosarcoma biopsy was notable for diffusely positive staining for Desmin and MyoD1, and multifocal positivity for myogenin. The tumor stained negative for S100 and SOX10, and there was no PD-L1 staining and less than 5% tumor CD8 CTL infiltration. Gene expression analysis revealed distinct expression patterns between melanoma and rhabdomyosarcoma samples, with 150 differentially expressed genes implicated in processes such as antigen presentation, T cell activation, cell death and protein metabolism. In addition, each tumor was found to have a unique immune cell composition and T-cell receptor repertoire, suggesting an interplay between phenotypic transformation and immune response. Results from epigenomic sequencing are pending, but may shed light on the mechanisms of transformation leading to resistance. These data therefore elucidate a previously undescribed mechanism of acquired resistance to ICB through melanoma phenotypic transformation to a rhabdomyosarcoma. Whereas these tumors were genetically similar, they expressed distinct gene expression patterns suggestive of underlying epigenomic differences in the setting of an HDAC inhibitor. Citation Format: Arnav Mehta, David Liu, Alvin Shi, Dennie T. Frederick, Li-Lun Ho, Ana B. Larque, Benchun Miao, Rumya S. Raghavan, Tatyana Sharova, John H. Shin, Nicola Rinaldi, Ivan A. Chebib, Manolis Kellis, Eliezer Van Allen, Nir Hacohen, Keith T. Flaherty, Genevieve M. Boland, Ryan J. Sullivan. Acquired resistance to immune checkpoint inhibition by melanoma phenotypic transformation [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 3013.

Immune checkpoint blockade (ICB) has revolutionized the treatment of many solid tumors, including metastatic melanoma. Despite recent successes, many patients fail to respond or are overcome by severe toxicities that limit further treatment. To date, there are no non-invasive predictors of response and toxicity that can guide treatment decisions. In this work, we perform whole plasma and exosome proteomic profiling to construct a predictive model of immunotherapy response and toxicity, and to glean further biologic insight into the mechanisms underlying resistance to ICB. Whole plasma was analyzed in a cohort of 150 melanoma patients receiving anti-PD1 antibodies (MGH IRB #11-181) at baseline, and on-treatment at 6 week and 6 month time-points. Exosomes were analyzed in 15 of these patients for all time-points. Proteomic analysis was performed using a multiplex proximity extension assay that enabled detection of more than 1000 proteins simultaneously. A linear mixed model with maximum likelihood estimation for model parameters was used to analyze differences between patient groups, and significant differences were determined after Benjamini and Hochberg multiple hypothesis correction. Between plasma baseline and on-treatment time-points, 67 differentially expressed proteins were identified including markers of inflammation such as PD1, CXCL9, CXCL10, CXCL11, IL10, CCL3 and TNFR2. Exosome samples had a distinct protein signature over the treatment period compared to plasma, including differential expression of CXCL16, CCL18, CCL20, and IL6, among others. 41 proteins were differentially expressed in plasma between ICB responders and non-responders including several inflammatory proteins such as CD28, TNFb, MCSFRa and IL8, and others implicated in melanoma resistance, such as MIA and ERBB2. Again, exosome samples had a distinct protein signature between responders and non-responders compared to plasma samples, consisting of CXCL9, CXCL13, CXCL16, CCL19, CD8a, GZMA and CD5 expression. Whereas plasma proteins reflected a myeloid signature, exosome proteins reflected a lymphoid signature, suggesting that the two compartments may capture elements of different immune processes. Integrating data from both plasma and exosome proteomics, we applied machine learning tools to build a predictor of response. Further analysis to look for predictors of toxicity is also currently underway. Overall, our work suggests that plasma and exosome protein signatures are distinct and may reflect unique immunological processes. Proteomic analysis of these compartments may be an effective way for non-invasive liquid biopsy to predict ICB response. Citation Format: Arnav Mehta, Gyulnara Kasumova, Alvin Shi, Marijana Rucevic, Markus Sallman-Almen, Lina Hultin Rosenberg, Emmett Sprecher, Jacqueline Ohmura, Michelle Kim, David Lieb, Xue Bai, Dennie T. Frederick, Manolis Kellis, Ryan J. Sullivan, Keith T. Flaherty, Nir Hacohen, Genevieve M. Boland. Plasma and exosome proteomic profiling for prediction of immunotherapy response and toxicity [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 4533.

Somatic mutations in cancer cells can generate neoantigens which can be recognized by immune cells and trigger an immune response. Patients vaccinated with neoantigen-based peptides display expanded neoantigen-specific T cells, suggesting that this could be a promising avenue for cancer treatment. Currently, neoantigen predictions are based on mutations detected by whole exome sequencing, which covers a pre-determined set of annotated exons, and often falls short for cancers with few somatic mutations. Ribosome profiling (Ribo-seq), which allows to monitor mRNA translation, has predicted a plethora of translated novel unannotated ORFs (nuORFs). Here we hypothesized that nuORFs can provide another source of neoantigens in cancer cells. In particular, we focused on nuORFs in the following categories: 1) nuORFs expressed in healthy and cancer cells, that have acquired tumor-specific somatic mutations; 2) nuORFs upregulated in or specific to cancer cells. To explore this hypothesis, we performed Ribo-seq on primary healthy and cancer cells and cell lines from melanoma, glioblastoma, colon carcinoma and chronic lymphocytic leukemia. Using this extensive dataset, we performed hierarchical ORF prediction analysis to build a database of highest confidence predicted translated nuORFs across healthy and cancer cell types. To determine if peptides from nuORFs can be a source of antigens, we searched our collection of mono-allelic MHC class I immunopeptidome mass spectrometry (MS) spectra from 94 common HLA alleles against our pan-tissue nuORF database. Additionally, we performed MHC class I immunoprecipitation followed by MS on the same cells used for Ribo-seq. We found HLA-presented unmutated peptides derived from thousands of nuORFs, found within, but out-of-frame with annotated protein-coding ORFs, within 5’ and 3’ untranslated regions of annotated protein-coding transcripts, long non-coding RNAs (lncRNAs), pseudogenes, and other RNA species. The HLA-binding motifs of peptides from nuORFs correspond to the expected motifs for given HLA types, indicating that 1) nuORFs are translated and 2) nuORF-derived peptides are presented on MHC I. To identify tumor-specific somatic mutations in nuORFs, we performed whole genome sequencing on patient-matched healthy and cancer cells and mapped somatic mutations to annotated ORFs and nuORFs. Finally, to identify nuORFs upregulated in or specific to cancer cells, we compared translation levels of nuORFs between healthy and cancer cells of the same origin. We found translated nuORFs with cancer-specific somatic mutations and nuORFs highly upregulated in and specific to cancer cells, suggesting that they can give rise to neoantigens. In conclusion, nuORFs are translated, contribute peptides to MHC I presentation, acquire somatic mutations, are expressed in tissue- and cancer-dependent manner and should be considered in the search for neoantigens in cancer. Citation Format: Tamara Ouspenskaia, Travis E. Law, Karl R. Clauser, Susan Klaeger, Derin B. Keskin, Bo Li, Elena Christian, Yuen Ting Chow, Phuong M. Le, Joshua Gould, Zhe Ji, Wandi Zhang, Pavan Bachireddy, Siranush Sarkizova, Nir Hacohen, Steven A. Carr, Catherine J. Wu, Aviv Regev. Neoantigens from translated unannotated open reading frames in 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 566.

Background: Cytotoxic T cell markers, PD-L1, and mutational burden have been identified as biomarkers of response to immune checkpoint blockade (ICB). However, there is a growing appreciation of B cells as biomarkers and mediators of response. We recently conducted a phase II trial of neoadjuvant ICB (NCT02519322) in patients with resectable melanoma, and found increased B cell infiltration in responders (R) versus non-responders (NR). Methods: We further investigated our B cell findings through whole transcriptomic profiling in samples with high tumor purity and also targeted immune profiling with deconvolution algorithm MCP counter. Spatial organization of the B cells was assessed with singlet and multiplex immunohistochemistry (IHC). Additionally, B cell phenotype was queried through mass cytometry. B cell gene expression signatures were validated in a cohort of renal cell carcinoma (RCC) patients (NCT02210117), and B cell phenotype in a metastatic melanoma cohort, both treated with ICB. Results: Whole transcriptomic analysis of the neoadjuvant melanoma ICB cohort identified that the most differentially expressed genes by response in baseline (b/l) samples were related to B cells and antibody production (MZB1, JCHAIN, IGLL5, FCRL5, p Conclusion: Together, these data suggest that B cells, more specifically those with activated effector phenotypes, and TLS predict response to ICB and may also be contributing mechanistically to response. Citation Format: Sangeetha M. Reddy, Beth Helmink, Jianjun Gao, Shaojun Zhang, Keren Yizhak, Moshe Sade-Feldman, Rafet Basar, Jorge Blando, Guangchun Han, Vancheswaran Gopalakrishnan, Hao Zhao, Wenbin Liu, Hussein Tawbi, Rodabe Amaria, Michael Davies, Jeffrey Gershenwald, Elizabeth M. Burton, James Allison, Michael Tetzlaff, Katy Rezvani, Nir Hacohen, Padmanee Sharma, Linghua Wang, Jennifer Wargo. Effector B cells and tertiary lymphoid structures predict response to immune checkpoint blockade in solid tumors [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 4488.

Cancer vaccines have been envisioned as a key tool for generating effective cancer therapy. Tumor neoantigens are ideal targets because of their exquisite tumor-specific expression (arising from somatic mutations of the tumor) and high level of immunogenicity (lacking of central tolerance against them). Recently, we and others have demonstrated that personalized neoantigen-targeting vaccines are safe, feasible and highly immunogenic in phase I trials of stage III/IV resected high-risk melanoma (Ott & Hu, Nature 2017; Sahin, Nature 2017). Our neoantigen vaccine (NeoVax), consisting of up to 20 long peptides and poly-ICLC, induced strong polyfunctional neoantigen-specific T-cells that recognized patient tumor in vitro. In addition, 2 patients who were vaccinated and received anti-PD1 checkpoint blockade (CPB) therapy upon relapse had durable complete responses (CRs). Thus far, these vaccine studies have been performed in the adjuvant setting, preventing direct assessment of on-target tumor killing in vivo due to the lack of evaluable tumor. On the other hand, the detection of epitope spreading (the broadening of the immune response from the initially targeted epitope to others) would indirectly suggest therapy-induced tumor lysis, whereby the release of additional tumor antigens leads to further tumor-specific T-cell activation. To explore the hypothesis that NeoVax+/- CPB generates epitope spreading, we evaluated the T-cell responses against neoantigens and tumor associated antigens (TAAs) that were not included in the original vaccine in 3 patients. We performed experiments for a patient with stage III melanoma who has remained disease-free (Pt.3) after vaccination and 2 patients with resected stage IV disease who recurred but achieved CR after CPB (Pts. 2&6). For the assessment of CD8+ T-cell responses, we designed 9-10 aa epitope length peptides (predicted by NetMHCpan and/or a mass spectrometry [MS]-based prediction algorithm (Abelin, Immunity 2017) or detected physically on the tumor’s surface class I complexes by MS) arising from 3 categories of antigens: (i) neoantigen peptides; (ii) TAA peptides based on high tumor gene expression; (iii) TAA peptides, detected on the tumor by MS (available for 2 of the 3 patients). For testing of CD4+ T-cell responses, we designed 15-16 aa peptides that spanned predicted neoepitopes from category i. Per patient, we designed peptides against up to 70 genes (~20 for each category). PBMCs from pre- , week 16 post-vaccination and post-CPB were stimulated with peptide pools (~10 peptides/pool) for 2 weeks, followed by restimulation with individual peptides in IFN-γ ELISPOT assays to deconvolute the peptides. Thus far, we have tested CD8+ T-cells against 71 neoantigens (category i) and 22 TAAs (ii) from Pts. 2 and 6, and CD4+ T-cells against 30 neoantigens from all 3 patients. We identified CD4+ T-cells specific for 3 peptides (mut-AGAP3 [Pt.2], -EYA3 and -P2RY4 [Pt.3]) in the week 16 samples that were not included in the original respective vaccines; these populations were expanded only post, but not pre-vaccination. For Pt.2, an additional CD4+ T-cell response against a different neoantigen peptide derived from mut-AGAP3 was detected only after CPB therapy. Lastly, all four lines of CD4+ T-cells reactive against these identified neoantigens were able to discriminate between the mutated and wild-type forms of the peptides, suggesting tumor specificity and lack of cross reactivity with normal tissues. Therefore, our results demonstrate that epitope spreading occurred in 2 patients after vaccination, and further spreading was detected in one of the two following CPB therapy. Ongoing studies are focused on screening additional peptides and investigating the association of epitope spreading and any residual tumor burden. The newly activated antigen-specific T-cells can target additional tumor antigens provided by epitope spreading, thus potentially enhancing therapeutic efficacy. Citation Format: Zhuting Hu, Donna Leet, Siranush Sarkizova, Rebecca Holden, Jing Sun, Susan Klaeger, Karl R. Clauser, Sachet A. Shukla, Wandi Zhang, Steven A. Carr, Edward F. Fritsch, Bradley L. Pentelute, Nir Hacohen, Derin B. Keskin, Patrick A. Ott, Catherine J. Wu. Personalized neoantigen-targeting vaccines for high-risk melanoma generate epitope spreading [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr A010.

Introduction: Cancer vaccine therapies rely on accurate personalized selection of immunizing peptides in order to potentiate tumor-specific immune responses against neoepitopes derived from somatic mutations. Given the unique accumulation of mutations in each tumor as well as the patient’s particular complement of HLA class I alleles, the ability to accurately predict which epitopes will be presented by tumor cells is a fundamental prerequisite for successful vaccine design. By utilizing a mono-allelic mass spectrometry (MS) strategy for profiling the endogenous HLA class I peptidome, we recently showed that prediction of endogenous presentation can be drastically improved when model training integrates peptide sequence along with intracellular signals such as likelihood of proteasomal processing and peptide abundance. Yet the limited set of mono-allelic data did not allow for deep comparative analysis across HLA- A, B, and C alleles, which can better inform pan-allele predictor design. Moreover, the significant variability in per-allele model performance remains unexplained. Methods: We recently developed a scalable mono-allelic MS technique to profile naturally presented peptides on HLA molecules, whereby the HLA class I deficient B721.221 cell line is transfected with HLA expression vectors coding for a single allele of interest and eluted HLA peptides are analyzed by LC-MS/MS. In addition, endogenously presented antigens on primary tumor-derived cell lines from 4 melanoma patients were also identified via MS. To extract knowledge from this unique dataset, we implemented computational tools to summarize, visualize, and compare the characteristics of HLA- A, B, C, and G alleles and developed a novel approach to define allele similarity that takes into account the collection of sub-motifs per allele. We trained neural network prediction models, validated their performance on internal and external datasets, and analyzed the variability in performance across alleles. Results: To date, we have generated binding data for 92 HLA- A, B, C and G alleles, identifying more than 190,000 peptides and covering the most frequent alleles in the population. Extensive mono-allelic profiling revealed that some alleles present non-9-mer peptides with high frequency. The availability of large number of non-9-mer peptides allowed us to build length-specific models that often performed better than the corresponding non-length-specific models currently used. We observe that HLA- A and B alleles present more peptides of length 10 and 11 than C alleles, while C alleles have a higher propensity for 8-mers. Correlation-based analysis of binding motifs revealed that HLA-A and B motifs are more specific whereas C motifs are less stringent and thus share more overlapping binders. Since binding data are available only for a fraction of all known alleles, pan-allele models implicitly embed allele similarity to predict for uncharacterized alleles based on the sequence of the binding pocket. By clustering allele-specific peptides into sub-motifs, we propose a novel explicit approach to delineate allele similarity at finer granularity that can improve pan-allele model design. We show that our allele-specific models are better at discriminating tumor-presented epitopes than state of the art predictors and investigate the relationship between false discovery rate and natural abundance of anchor residues to better understand differences in model accuracy amongst alleles. Finally, deconvolution of tumor-presented peptides demonstrated that ~10% of peptides are presented on HLA-C, which has been historically understudied. Conclusions: We have vastly expanded the collection of endogenous HLA-specific peptides deriving biologic insights into the principles of epitope presentations and valuable considerations for prediction model design and epitope selection for tumor vaccines. Citation Format: Siranush Sarkizova, Susan Klaeger, Derin B. Keskin, Karl Clauser, Hasmik Keshishian, Christina R. Hartigan, Nir Hacohen, Steven A. Carr, Catherine J. Wu. Broad analysis and more accurate predictions of HLA class I epitope binding in 92 common HLA alleles profiled by mono-allelic mass spectrometry [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B042.

Treatment of solid tumors has been revolutionized by immune checkpoint blockade therapies; yet even for melanoma, for which high response rates are observed, the majority of tumors continue to grow after therapy. To identify immune cell states associated with success or failure of immunotherapy, we profiled the single-cell transcriptomes of immune cells from tumor samples obtained from melanoma patients treated with checkpoint inhibitors. We defined specific activation states of CD8+ T cells that associate with tumor growth post-therapy, delineated their epigenetic landscape and clonality, and demonstrated enhanced immunity by targeting a novel combination of T cell factors. We also found that expression of a single T cell gene was predictive of tumor regression in response to therapy. Our study thus reveals immune cell states and molecules that help explain effective immunotherapy in humans. Citation Format: Nir Hacohen. Determinants of effective tumor immunity [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr IA35.

Despite years of preclinical efforts and hundreds of clinical studies, therapeutic cancer vaccines with the routine ability to limit or eliminate tumor growth in humans have been elusive. With advances in genome sequencing, it is now possible to identify a new class of tumor-specific antigens derived from mutated proteins that are present only in the tumor. These “neoantigens” should provide highly specific targets for antitumor immunity. Although many challenges remain in producing and testing neoantigen-based vaccines customized for each patient, a neoantigen vaccine offers a promising new approach to induce highly focused antitumor T cells aimed at eradicating cancer cells. Cancer Immunol Res; 1(1); 11–15. ©2013 AACR.

Obtaining paired alpha- and beta-chain information of the T cell receptor (TCR) enables identification of which TCR binds to a particular antigen, providing critical knowledge for understanding how a tumor interacts with its immune microenvironment and for monitoring responses to immunotherapy. We have developed a rapid, cost-effective single-cell TCR sequencing protocol (scTCRseq) that processes single T cells flow sorted into 384-well plates. Exploiting the added specificity provided by RNase H-dependent PCR (rhPCR; Dobosy et al., BMC Biotechnology 11:80, 2011), our scTCRseq protocol mixes primers for all known productive alpha and beta TCR alleles and obtains specific amplification of only the alleles present in a single-cell lysate (typically one alpha allele and one beta allele) without the use of nested PCR. Applying this protocol to T cell samples from normal donors, we detect TCRs arising from all productive TRAV and TRBV genes, and observe the expected highly diverse repertoires. Our method also includes targeted sequencing of 96 (or more) marker transcripts in order to obtain cell phenotype information. Our scTCRseq protocol has been adapted to analyze low-input samples (100 pg-10 ng) of PBMC RNA for characterization of the TCR repertoire and to improve the sensitivity of paired TCR detection in Smart-seq2 libraries prepared from single-cell RNA. We recently applied this approach to analyze T cell clonality in the T cell infiltrate from a glioblastoma patient receiving neoantigen-specific peptide vaccination. Fresh tumor obtained post-vaccination at the time of recurrence was dissociated and single CD3+ T cells were isolated by flow cytometry. Smart-seq2 analysis suggested the presence of clones, but this was based largely on inference from one-chain data. Using our scTCRseq protocol to re-amplify the TCR segments, paired alpha- and beta-chain information was obtained from 277 of 363 (76%) single cells that passed quality control. Out of 231 distinct clonotypes detected, 25 were identified as clones, where a clone is defined as two or more cells with identical alpha- and beta-CDR3 segments. GLIPH analysis (Glanville et al., Nature 547:94-98, 2017) was used to cluster infiltrate TCRs by specificity. A representative TCR from each specificity cluster was cloned in a TCR-negative Jurkat cell line. Cellular assays were used to determine which specificity groups react with epitopes from peptides used in the vaccination. TCRs specific for neoantigens included in the vaccine were detected. We have demonstrated a robust workflow that combines sensitive detection of paired alpha- and beta-chain TCR sequences with TCR cloning and expression to determine which TCRs in a tumor infiltrate have neoantigen specificity. Citation Format: Shuqiang Li, Jing Sun, Annabelle Anandappa, Oliver Spiro, Ignaty Leshchiner, Krishnalekha Datta, Yun Bao, Zhuting Hu, Nir Hacohen, Nathan D. Mathewson, Itay Tirosh, Kai Wucherpfennig, Aviv Regev, Mario Suva, Derin B. Keskin, Catherine J. Wu, Kenneth J. Livak. Novel targeted single-cell TCR sequencing method used for analysis of a T cell infiltrate from a glioblastoma patient [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 5387.

Personalized neoantigen therapies for cancer require accurate epitope selection. However, most Class I prediction algorithms in common use today are based on biochemical binding assays that are difficult to scale and do not address processing steps upstream of peptide-MHC binding. Here we present an alternative approach based on the LC-MS/MS identification of MHC Class I-bound peptides. While MS-based profiling is not new, we optimized the system for rule learning by focusing on cell lines expressing only a single HLA-A or HLA-B allele and by collecting parallel transcriptomic and proteomic measurements. Identifying over 24,000 peptides across 16 individual alleles, we were able to discover novel binding motifs, which were validated biochemically, and develop novel neural network algorithms. Furthermore, we systematically interrogated processing rules - discovering a novel motif conserved across multiple cell types - and developed a principled framework for integrating epitope cleavability, expression, and MHC binding potential into an overall ranking. Validating on external datasets, we saw a doubling in positive predictive value with respect to standard approaches. We thus demonstrate a scalable strategy for systematically learning the rules of endogenous antigen presentation that can be deployed for the optimal selection of patient-specific cancer neoantigens. Citation Format: Michael S. Rooney, Jenn Abelin, Siranush Sarkizova, Derin Keskin, Christine Hartigan, Wandi Zhang, John Sidney, William Lane, Jonathan Stevens, Guang L. Zhang, Karl Clauser, Nir Hacohen, Steve Carr, Cathy Wu. Next-generation epitope prediction using mass spectrometry and integrative genomics [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 LB-179. doi:10.1158/1538-7445.AM2017-LB-179

The role of tumor cell-derived immune factors in the development of cancer and tumor immunity remains poorly understood. We hypothesized that tumors express recurrent and stable immunoregulatory programs that impact cancer growth and immunity. To identify these programs, we performed an unbiased integrative analysis of chromosomal copy number aberrations and gene expression analysis on 775 primary solid tumor cell lines, derived from 23 different tissues of origin. Using modified versions of GISTIC 2.0 and CONEXIC, a Bayesian module network method, we identified cancer drivers that correlated with specific transcriptional regulatory programs across multiple cell lines (after considering confounding variables, including histology, sub-histology, ethnicity, gender, center of collection, experimental batches and unknown variables using Surrogate Variable Analysis). We identified a total of 60 amplified and 222 deleted somatic regions, of which 52% contained a candidate driver gene whose expression was associated with the expression of a target module. The driver genes consisted of putative novel and known cancer drivers, including deletions in CDKN2A-CDKN2B (q< 4.2E-176), WWOX (q< 5.3E-100), and amplifications in MYC (q< 2.1E-81) and CCND1 (q< 1.4E-44) genes. The target modules were enriched for known cancer-dysregulated processes, including cell cycle (q< 2.1E-91) and DNA damage/repair (q< 9.3E-50), validating the analysis. We identified and focused on immune programs common to several tissues of origin, including a type I interferon-related program (q Note: This abstract was not presented at the conference. Citation Format: Alexandra-Chloe Villani, Ye Chun, Raktima Raychowdhury, Weibo Li, Thomas Eisenhaure, Aviv Regev, Nir Hacohen. Integrative genomic and transcriptomic analysis of 775 human cancer cell lines reveals tumor-derived immune programs and their regulators. [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 B13.

Neoantigens arise from somatic tumor mutations and can encode amino acid changes, generating peptides with the potential to bind to HLA molecules. Since these neoepitopes provide exquisite tumor specificity and are expected to be highly immunogenic as they are not subject to central tolerance, they were long-envisioned as highly valuable tumor antigens. Growing evidence has supported tumor neoepitopes as key antigens triggering immune-mediated tumor killing in vivo across settings of effective cancer immunotherapy, including checkpoint blockade and adoptive transfer with tumor-infiltrating lymphocytes. Vaccination is a potentially effective approach for inducing tumor-specific immune responses, but has been limited by the lack of a sufficiently potent vaccine immunogen. By leveraging next-generation sequencing technologies and new analytical pipelines to systematically identify personal tumor neoantigens, in a phase 1 trial we tested the feasibility, safety, and immunogenicity of a multi-epitope cancer vaccine targeting personal tumor neoantigens in patients with high-risk melanoma. Mutations were identified by DNA and RNA sequencing; epitopes were selected based on class I HLA binding prediction algorithms. The vaccines, comprised of up to 20 long peptides spanning mutated tumor epitopes and admixed with the Toll-Like Receptor 3 agonist poly-ICLC, were administered using a prime-boost approach. Of 12 patients enrolled, the initial 6 patients who received the full set of priming and booster vaccinations experienced only minimal adverse events, consisting of mild and transient injection site reaction, flu-like symptoms, and rash. We identified strong, polyfunctional CD4+ and CD8+ T cell responses against multiple neoepitopes in all dosed patients. Processing and presentation of neoantigens on autologous tumors was confirmed by mass spectrometry and recognition of autologous tumor by vaccine-induced neoantigen-specific T cells was verified. These studies show that a personalized neoantigen vaccine is safe, feasible, and strongly immunogenic in cancer patients. The data should reinvigorate the field of cancer vaccines, providing a rational path for the building of combinatorial approaches to extend their efficacy. Citation Format: Patrick A. Ott, Zhuting Hu, Derin B. Keskin, Sachet A. Shukla, Jing Sun, Ed Fritsch, Nir Hacohen, Catherine J. Wu. A personalized neoantigen vaccine in patients with high risk 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 PR02.

Cancer mutations yield neo-antigens, which are instrumental to immune-mediated recognition and control of cancer. Vaccine-based therapies targeting neo-antigens will require accurate prediction of which mutations yield peptides presented on polymorphic HLA class I. While in vitro methods have produced increasingly accurate predictors of peptide:MHC binding, there remains a need to define rules for endogenous antigen presentation. Here, we use rapid, high-resolution liquid chromatography mass spectrometry (LC-MS/MS) to identify >24,000 peptides associated with 16 HLA alleles in B cell lines that each express a single HLA allele. The elution of peptides from single HLA alleles allowed us to develop improved rules for endogenous peptide presentation based on the physicochemical properties of binding peptides, patterns of peptide cleavage and abundance of cognate transcripts. Finally, we trained models that integrated MS-derived peptide data and gene expression and demonstrate improved prediction of endogenous peptide presentation in independent datasets. Our strategy thus improves the performance of current predictive algorithms and provides a rapid and scalable method to generate rules for the massive and diverse set of human HLA alleles. Citation Format: Michael S. Rooney, Jennifer G. Abelin, Derin B. Keskin, Siranush Sarkizova, Christina Hartigan, Wandi Zhang, John Sidney, Jonathan Stevens, William J. Lane, Guang L. Zhang, Karl R. Clauser, Nir Hacohen, Steven A. Carr, Catherine J. Wu. High-throughput profiling of HLA allele-specific peptides by MS for improved epitope prediction [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 B089.

T cells play a critical role in antitumor immunity and are the primary targets in many immunotherapies. However, the study of tumor-infiltrating T cells has been complicated by the extremely diverse repertoire of T cell receptors, characterized by the complementarity determining region 3 (CDR3). Here using our newly developed algorithm, we studied the CDR3 sequences of tumor infiltrating T cells in 9,142 RNA-seq samples across 29 diseases. In total, we assembled over 600 thousands CDR3 sequences, covering the α, β, γ, δ chains. TRBV genes usage, CDR3 sequence length and conservation of infiltrating T cells resembled those in the peripheral blood of healthy donors in many tumors, except brain and kidney cancers. About 20% of the CDR3 calls were shared in multiple individuals. T cell clonotypes carrying these CDR3 sequences are known as the ‘public T cells’. In this work, we found that public T cell CDR3 amino acid (AA) sequences are shorter compared to the private ones and the middle 3 positions of the private CDR3 sequences were enriched for hydrophobic AAs. This finding potentially suggests that private T cell clonotypes in the tumors have greater potential to recognize neoantigens. We defined clonotype per kilo-reads (CPK) to measure the diversity of T cell repertoire and identified a strong positive association between CPK and tumor mutation load, implying that neoantigens may diversify the infiltrating T cell population. In addition, we predicted SPAG5 and TSSK6 as putative immunogenic cancer/testis antigens in multiple cancers based on their strong associations with CPK. Finally, we identified 3 potential immunogenic somatic mutations based on their co-occurrence with CDR3 sequences. One of them, PRAMEF4 F300V, was predicted to bind strongly to both MHC-I and MHC-II, with matched HLA types in its carriers. Our analyses have the potential to simultaneously identify immunogenic neoantigen and the tumor-reactive T-cell clonotype. Citation Format: Bo Li, Taiwen Liu, Binbin Wang, Jinzeng Wang, Sachet Shukla, Ruoxu Dou, Stephen Hodi, Catherine Wu, Nir Hacohen, Jun Liu, X. Shirley Liu. Landscape of tumor-infiltrating T-cell repertoire of human cancers. [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 LB-264.