The Immunoglobulin Superfamily Receptome Defines Cancer-Relevant Networks Associated with Clinical Outcome.

Cell surface receptors and their interactions play a central role in physiological and pathological signaling. Despite its clinical relevance, the immunoglobulin superfamily (IgSF) remains uncharacterized and underrepresented in databases. Here, we present a systematic extracellular protein map, the IgSF interactome. Using a high-throughput technology to interrogate most single transmembrane receptors for binding to 445 IgSF proteins, we identify over 500 interactions, 82% previously undocumented, and confirm more than 60 receptor-ligand pairs using orthogonal assays. Our study reveals a map of cell-type-specific interactions and the landscape of dysregulated receptor-ligand crosstalk in cancer, including selective loss of function for tumor-associated mutations. Furthermore, investigation of the IgSF interactome in a large cohort of cancer patients identifies interacting protein signatures associated with clinical outcome. The IgSF interactome represents an important resource to fuel biological discoveries and a framework for understanding the functional organization of the surfaceome during homeostasis and disease, ultimately informing therapeutic development.

Gremlin 1+ fibroblastic niche maintains dendritic cell homeostasis in lymphoid tissues.

Fibroblastic reticular cells (FRCs) are specialized stromal cells that define tissue architecture and regulate lymphocyte compartmentalization, homeostasis, and innate and adaptive immunity in secondary lymphoid organs (SLOs). In the present study, we used single-cell RNA sequencing (scRNA-seq) of human and mouse lymph nodes (LNs) to identify a subset of T cell-zone FRCs defined by the expression of Gremlin1 (Grem1) in both species. Grem1-CreERT2 knock-in mice enabled localization, multi-omics characterization and genetic depletion of Grem1+ FRCs. Grem1+ FRCs primarily localize at T-B cell junctions of SLOs, neighboring pre-dendritic cells and conventional dendritic cells (cDCs). As such, their depletion resulted in preferential loss and decreased homeostatic proliferation and survival of resident cDCs and compromised T cell immunity. Trajectory analysis of human LN scRNA-seq data revealed expression similarities to murine FRCs, with GREM1+ cells marking the endpoint of both trajectories. These findings illuminate a new Grem1+ fibroblastic niche in LNs that functions to maintain the homeostasis of lymphoid tissue-resident cDCs.

Selective autophagy of the adaptor TRIF regulates innate inflammatory signaling.

Defective autophagy is linked to diseases such as rheumatoid arthritis, lupus and inflammatory bowel disease (IBD). However, the mechanisms by which autophagy limits inflammation remain poorly understood. Here we found that loss of the autophagy-related gene Atg16l1 promoted accumulation of the adaptor TRIF and downstream signaling in macrophages. Multiplex proteomic profiling identified SQSTM1 and Tax1BP1 as selective autophagy-related receptors that mediated the turnover of TRIF. Knockdown of Tax1bp1 increased production of the cytokines IFN-ß and IL-1ß. Mice lacking Atg16l1 in myeloid cells succumbed to lipopolysaccharide-mediated sepsis but enhanced their clearance of intestinal Salmonella typhimurium in an interferon receptor-dependent manner. Human macrophages with the Crohn's disease-associated Atg16l1 variant T300A exhibited more production of IFN-ß and IL-1ß. An elevated interferon-response gene signature was observed in patients with IBD who were resistant to treatment with an antibody to the cytokine TNF. These findings identify selective autophagy as a key regulator of signaling via the innate immune system.

Homeostatic functions of monocytes and interstitial lung macrophages are regulated via collagen domain-binding receptor LAIR1.

Myeloid cells encounter stromal cells and their matrix determinants on a continual basis during their residence in any given organ. Here, we examined the impact of the collagen receptor LAIR1 on myeloid cell homeostasis and function. LAIR1 was highly expressed in the myeloid lineage and enriched in non-classical monocytes. Proteomic definition of the LAIR1 interactome identified stromal factor Colec12 as a high-affinity LAIR1 ligand. Proteomic profiling of LAIR1 signaling triggered by Collagen1 and Colec12 highlighted pathways associated with survival, proliferation, and differentiation. Lair1-/- mice had reduced frequencies of Ly6C- monocytes, which were associated with altered proliferation and apoptosis of non-classical monocytes from bone marrow and altered heterogeneity of interstitial macrophages in lung. Myeloid-specific LAIR1 deficiency promoted metastatic growth in a melanoma model and LAIR1 expression associated with improved clinical outcomes in human metastatic melanoma. Thus, monocytes and macrophages rely on LAIR1 sensing of stromal determinants for fitness and function, with relevance in homeostasis and disease.

CTLA-4 blockade drives loss of Treg stability in glycolysis-low tumours.

Limiting metabolic competition in the tumour microenvironment may increase the effectiveness of immunotherapy. Owing to its crucial role in the glucose metabolism of activated T cells, CD28 signalling has been proposed as a metabolic biosensor of T cells1. By contrast, the engagement of CTLA-4 has been shown to downregulate T cell glycolysis1. Here we investigate the effect of CTLA-4 blockade on the metabolic fitness of intra-tumour T cells in relation to the glycolytic capacity of tumour cells. We found that CTLA-4 blockade promotes metabolic fitness and the infiltration of immune cells, especially in glycolysis-low tumours. Accordingly, treatment with anti-CTLA-4 antibodies improved the therapeutic outcomes of mice bearing glycolysis-defective tumours. Notably, tumour-specific CD8+ T cell responses correlated with phenotypic and functional destabilization of tumour-infiltrating regulatory T (Treg) cells towards IFNγ- and TNF-producing cells in glycolysis-defective tumours. By mimicking the highly and poorly glycolytic tumour microenvironments in vitro, we show that the effect of CTLA-4 blockade on the destabilization of Treg cells is dependent on Treg cell glycolysis and CD28 signalling. These findings indicate that decreasing tumour competition for glucose may facilitate the therapeutic activity of CTLA-4 blockade, thus supporting its combination with inhibitors of tumour glycolysis. Moreover, these results reveal a mechanism by which anti-CTLA-4 treatment interferes with Treg cell function in the presence of glucose.

TGFß attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

Therapeutic antibodies that block the programmed death-1 (PD-1)-programmed death-ligand 1 (PD-L1) pathway can induce robust and durable responses in patients with various cancers, including metastatic urothelial cancer. However, these responses only occur in a subset of patients. Elucidating the determinants of response and resistance is key to improving outcomes and developing new treatment strategies. Here we examined tumours from a large cohort of patients with metastatic urothelial cancer who were treated with an anti-PD-L1 agent (atezolizumab) and identified major determinants of clinical outcome. Response to treatment was associated with CD8+ T-effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden. Lack of response was associated with a signature of transforming growth factor ß (TGFß) signalling in fibroblasts. This occurred particularly in patients with tumours, which showed exclusion of CD8+ T cells from the tumour parenchyma that were instead found in the fibroblast- and collagen-rich peritumoural stroma; a common phenotype among patients with metastatic urothelial cancer. Using a mouse model that recapitulates this immune-excluded phenotype, we found that therapeutic co-administration of TGFß-blocking and anti-PD-L1 antibodies reduced TGFß signalling in stromal cells, facilitated T-cell penetration into the centre of tumours, and provoked vigorous anti-tumour immunity and tumour regression. Integration of these three independent biological features provides the best basis for understanding patient outcome in this setting and suggests that TGFß shapes the tumour microenvironment to restrain anti-tumour immunity by restricting T-cell infiltration.

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer.

Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies.

A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers.

Protein expression and post-translational modification levels are tightly regulated in neoplastic cells to maintain cellular processes known as 'cancer hallmarks'. The first Pan-Cancer initiative of The Cancer Genome Atlas (TCGA) Research Network has aggregated protein expression profiles for 3,467 patient samples from 11 tumor types using the antibody based reverse phase protein array (RPPA) technology. The resultant proteomic data can be utilized to computationally infer protein-protein interaction (PPI) networks and to study the commonalities and differences across tumor types. In this study, we compare the performance of 13 established network inference methods in their capacity to retrieve the curated Pathway Commons interactions from RPPA data. We observe that no single method has the best performance in all tumor types, but a group of six methods, including diverse techniques such as correlation, mutual information, and regression, consistently rank highly among the tested methods. We utilize the high performing methods to obtain a consensus network; and identify four robust and densely connected modules that reveal biological processes as well as suggest antibody-related technical biases. Mapping the consensus network interactions to Reactome gene lists confirms the pan-cancer importance of signal transduction pathways, innate and adaptive immune signaling, cell cycle, metabolism, and DNA repair; and also suggests several biological processes that may be specific to a subset of tumor types. Our results illustrate the utility of the RPPA platform as a tool to study proteomic networks in cancer.

OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks.

MOTIVATION: Reverse engineering of gene regulatory networks remains a central challenge in computational systems biology, despite recent advances facilitated by benchmark in silico challenges that have aided in calibrating their performance. A number of approaches using either perturbation (knock-out) or wild-type time-series data have appeared in the literature addressing this problem, with the latter using linear temporal models. Nonlinear dynamical models are particularly appropriate for this inference task, given the generation mechanism of the time-series data. In this study, we introduce a novel nonlinear autoregressive model based on operator-valued kernels that simultaneously learns the model parameters, as well as the network structure. RESULTS: A flexible boosting algorithm (OKVAR-Boost) that shares features from L2-boosting and randomization-based algorithms is developed to perform the tasks of parameter learning and network inference for the proposed model. Specifically, at each boosting iteration, a regularized Operator-valued Kernel-based Vector AutoRegressive model (OKVAR) is trained on a random subnetwork. The final model consists of an ensemble of such models. The empirical estimation of the ensemble model's Jacobian matrix provides an estimation of the network structure. The performance of the proposed algorithm is first evaluated on a number of benchmark datasets from the DREAM3 challenge and then on real datasets related to the In vivo Reverse-Engineering and Modeling Assessment (IRMA) and T-cell networks. The high-quality results obtained strongly indicate that it outperforms existing approaches. AVAILABILITY: The OKVAR-Boost Matlab code is available as the archive: http://amis-group.fr/sourcecode-okvar-boost/OKVARBoost-v1.0.zip. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOSBY enables multi-omic inference and spatial biomarker discovery from whole slide images.

The utility of deep neural nets has been demonstrated for mapping hematoxylin-and-eosin (H&E) stained image features to expression of individual genes. However, these models have not been employed to discover clinically relevant spatial biomarkers. Here we develop MOSBY (Multi-Omic translation of whole slide images for Spatial Biomarker discoverY) that leverages contrastive self-supervised pretraining to extract improved H&E whole slide images features, learns a mapping between image and bulk omic profiles (RNA, DNA, and protein), and utilizes tile-level information to discover spatial biomarkers. We validate MOSBY gene and gene set predictions with spatial transcriptomic and serially-sectioned CD8 IHC image data. We demonstrate that MOSBY-inferred colocalization features have survival-predictive power orthogonal to gene expression, and enable concordance indices highly competitive with survival-trained multimodal networks. We identify and validate (1) an ER stress-associated colocalization feature as a chemotherapy-specific risk factor in lung adenocarcinoma, and (2) the colocalization of T effector cell vs cysteine signatures as a negative prognostic factor in multiple cancer indications. The discovery of clinically relevant biologically interpretable spatial biomarkers showcases the utility of the model in unraveling novel insights in cancer biology as well as informing clinical decision-making.

Tumor-intrinsic expression of the autophagy gene Atg16l1 suppresses anti-tumor immunity in colorectal cancer.

Microsatellite-stable colorectal cancer (MSS-CRC) is highly refractory to immunotherapy. Understanding tumor-intrinsic determinants of immunotherapy resistance is critical to improve MSS-CRC patient outcomes. Here, we demonstrate that high tumor expression of the core autophagy gene ATG16L1 is associated with poor clinical response to anti-PD-L1 therapy in KRAS-mutant tumors from IMblaze370 (NCT02788279), a large phase III clinical trial of atezolizumab (anti-PD-L1) in advanced metastatic MSS-CRC. Deletion of Atg16l1 in engineered murine colon cancer organoids inhibits tumor growth in primary (colon) and metastatic (liver and lung) niches in syngeneic female hosts, primarily due to increased sensitivity to IFN-γ-mediated immune pressure. ATG16L1 deficiency enhances programmed cell death of colon cancer organoids induced by IFN-γ and TNF, thus increasing their sensitivity to host immunity. In parallel, ATG16L1 deficiency reduces tumor stem-like populations in vivo independently of adaptive immune pressure. This work reveals autophagy as a clinically relevant mechanism of immune evasion and tumor fitness in MSS-CRC and provides a rationale for autophagy inhibition to boost immunotherapy responses in the clinic.

Joint estimation of DNA copy number from multiple platforms.

MOTIVATION: DNA copy number variants (CNVs) are gains and losses of segments of chromosomes, and comprise an important class of genetic variation. Recently, various microarray hybridization-based techniques have been developed for high-throughput measurement of DNA copy number. In many studies, multiple technical platforms or different versions of the same platform were used to interrogate the same samples; and it became necessary to pool information across these multiple sources to derive a consensus molecular profile for each sample. An integrated analysis is expected to maximize resolution and accuracy, yet currently there is no well-formulated statistical method to address the between-platform differences in probe coverage, assay methods, sensitivity and analytical complexity. RESULTS: The conventional approach is to apply one of the CNV detection ('segmentation') algorithms to search for DNA segments of altered signal intensity. The results from multiple platforms are combined after segmentation. Here we propose a new method, Multi-Platform Circular Binary Segmentation (MPCBS), which pools statistical evidence across platforms during segmentation, and does not require pre-standardization of different data sources. It involves a weighted sum of t-statistics, which arises naturally from the generalized log-likelihood ratio of a multi-platform model. We show by comparing the integrated analysis of Affymetrix and Illumina SNP array data with Agilent and fosmid clone end-sequencing results on eight HapMap samples that MPCBS achieves improved spatial resolution, detection power and provides a natural consensus across platforms. We also apply the new method to analyze multi-platform data for tumor samples. AVAILABILITY: The R package for MPCBS is registered on R-Forge (http://r-forge.r-project.org/) under project name MPCBS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The neutrophil protein CD177 is a novel PDPN receptor that regulates human cancer-associated fibroblast physiology.

The cancer-associated fibroblast (CAF) marker podoplanin (PDPN) is generally correlated with poor clinical outcomes in cancer patients and thus represents a promising therapeutic target. Despite its biomedical relevance, basic aspects of PDPN biology such as its cellular functions and cell surface ligands remain poorly uncharacterized, thus challenging drug development. Here, we utilize a high throughput platform to elucidate the PDPN cell surface interactome, and uncover the neutrophil protein CD177 as a new binding partner. Quantitative proteomics analysis of the CAF phosphoproteome reveals a role for PDPN in cell signaling, growth and actomyosin contractility, among other processes. Moreover, cellular assays demonstrate that CD177 is a functional antagonist, recapitulating the phenotype observed in PDPN-deficient CAFs. In sum, starting from the unbiased elucidation of the PDPN co-receptome, our work provides insights into PDPN functions and reveals the PDPN/CD177 axis as a possible modulator of fibroblast physiology in the tumor microenvironment.

Multiplexed proteomics of autophagy-deficient murine macrophages reveals enhanced antimicrobial immunity via the oxidative stress response.

Defective autophagy is strongly associated with chronic inflammation. Loss-of-function of the core autophagy gene Atg16l1 increases risk for Crohn's disease in part by enhancing innate immunity through myeloid cells such as macrophages. However, autophagy is also recognized as a mechanism for clearance of certain intracellular pathogens. These divergent observations prompted a re-evaluation of ATG16L1 in innate antimicrobial immunity. In this study, we found that loss of Atg16l1 in myeloid cells enhanced the killing of virulent Shigella flexneri (S.flexneri), a clinically relevant enteric bacterium that resides within the cytosol by escaping from membrane-bound compartments. Quantitative multiplexed proteomics of murine bone marrow-derived macrophages revealed that ATG16L1 deficiency significantly upregulated proteins involved in the glutathione-mediated antioxidant response to compensate for elevated oxidative stress, which simultaneously promoted S.flexneri killing. Consistent with this, myeloid-specific deletion of Atg16l1 in mice accelerated bacterial clearance in vitro and in vivo. Pharmacological induction of oxidative stress through suppression of cysteine import enhanced microbial clearance by macrophages. Conversely, antioxidant treatment of macrophages permitted S.flexneri proliferation. These findings demonstrate that control of oxidative stress by ATG16L1 and autophagy regulates antimicrobial immunity against intracellular pathogens.

Single-Cell RNA Sequencing Reveals Stromal Evolution into LRRC15+ Myofibroblasts as a Determinant of Patient Response to Cancer Immunotherapy.

With only a fraction of patients responding to cancer immunotherapy, a better understanding of the entire tumor microenvironment is needed. Using single-cell transcriptomics, we chart the fibroblastic landscape during pancreatic ductal adenocarcinoma (PDAC) progression in animal models. We identify a population of carcinoma-associated fibroblasts (CAF) that are programmed by TGFß and express the leucine-rich repeat containing 15 (LRRC15) protein. These LRRC15+ CAFs surround tumor islets and are absent from normal pancreatic tissue. The presence of LRRC15+ CAFs in human patients was confirmed in >80,000 single cells from 22 patients with PDAC as well as by using IHC on samples from 70 patients. Furthermore, immunotherapy clinical trials comprising more than 600 patients across six cancer types revealed elevated levels of the LRRC15+ CAF signature correlated with poor response to anti-PD-L1 therapy. This work has important implications for targeting nonimmune elements of the tumor microenvironment to boost responses of patients with cancer to immune checkpoint blockade therapy. SIGNIFICANCE: This study describes the single-cell landscape of CAFs in pancreatic cancer during in vivo tumor evolution. A TGFß-driven, LRRC15+ CAF lineage is associated with poor outcome in immunotherapy trial data comprising multiple solid-tumor entities and represents a target for combinatorial therapy.This article is highlighted in the In This Issue feature, p. 161.

Genomic and Transcriptomic Characterization of Papillary Microcarcinomas With Lateral Neck Lymph Node Metastases.

CONTEXT: Most papillary microcarcinomas (PMCs) are indolent and subclinical. However, as many as 10% can present with clinically significant nodal metastases. OBJECTIVE AND DESIGN: Characterization of the genomic and transcriptomic landscape of PMCs presenting with or without clinically important lymph node metastases. SUBJECTS AND SAMPLES: Formalin-fixed paraffin-embedded PMC samples from 40 patients with lateral neck nodal metastases (pN1b) and 71 patients with PMC with documented absence of nodal disease (pN0). OUTCOME MEASURES: To interrogate DNA alterations in 410 genes commonly mutated in cancer and test for differential gene expression using a custom NanoString panel of 248 genes selected primarily based on their association with tumor size and nodal disease in the papillary thyroid cancer TCGA project. RESULTS: The genomic landscapes of PMC with or without pN1b were similar. Mutations in TERT promoter (3%) and TP53 (1%) were exclusive to N1b cases. Transcriptomic analysis revealed differential expression of 43 genes in PMCs with pN1b compared with pN0. A random forest machine learning-based molecular classifier developed to predict regional lymph node metastasis demonstrated a negative predictive value of 0.98 and a positive predictive value of 0.72 at a prevalence of 10% pN1b disease. CONCLUSIONS: The genomic landscape of tumors with pN1b and pN0 disease was similar, whereas 43 genes selected primarily by mining the TCGA RNAseq data were differentially expressed. This bioinformatics-driven approach to the development of a custom transcriptomic assay provides a basis for a molecular classifier for pN1b risk stratification in PMC.

Non-conventional Inhibitory CD4+Foxp3-PD-1hi T Cells as a Biomarker of Immune Checkpoint Blockade Activity.

A significant proportion of cancer patients do not respond to immune checkpoint blockade. To better understand the molecular mechanisms underlying these treatments, we explored the role of CD4+Foxp3- T cells expressing PD-1 (4PD1hi) and observed that 4PD1hi accumulate intratumorally as a function of tumor burden. Interestingly, CTLA-4 blockade promotes intratumoral and peripheral 4PD1hi increases in a dose-dependent manner, while combination with PD-1 blockade mitigates this effect and improves anti-tumor activity. We found that lack of effective 4PD1hi reduction after anti-PD-1 correlates with poor prognosis. Mechanistically, we provide evidence that mouse and human circulating and intra-tumor 4PD1hi inhibit T cell functions in a PD-1/PD-L1 dependent fashion and resemble follicular helper T cell (TFH)-like cells. Accordingly, anti-CTLA-4 activity is improved in TFH deficient mice.

Pan-cancer analysis of intratumor heterogeneity as a prognostic determinant of survival.

As tumors accumulate genetic alterations, an evolutionary process occurs in which genetically distinct subclonal populations of cells co-exist, resulting in intratumor genetic heterogeneity (ITH). The clinical implications of ITH remain poorly defined. Data are limited with respect to whether ITH is an independent determinant of patient survival outcomes, across different cancer types. Here, we report the results of a pan-cancer analysis of over 3300 tumors, showing a varied landscape of ITH across 9 cancer types. While some gene mutations are subclonal, the majority of driver gene mutations are clonal events, present in nearly all cancer cells. Strikingly, high levels of ITH are associated with poorer survival across diverse types of cancer. The adverse impact of high ITH is independent of other clinical, pathologic and molecular factors. High ITH tends to be associated with lower levels of tumor-infiltrating immune cells, but this association is not able to explain the observed survival differences. Together, these data show that ITH is a prognostic marker in multiple cancers. These results illuminate the natural history of cancer evolution, indicating that tumor heterogeneity represents a significant obstacle to cancer control.

The head and neck cancer immune landscape and its immunotherapeutic implications.

Recent clinical trials have demonstrated a clear survival advantage in advanced head and neck squamous cell carcinoma (HNSCC) patients treated with immune checkpoint blockade. These emerging results reveal that HNSCC is one of the most promising frontiers for immunotherapy research. However, further progress in head and neck immuno-oncology will require a detailed understanding of the immune infiltrative landscape found in these tumors. We leveraged transcriptome data from 280 tumors profiled by The Cancer Genome Atlas (TCGA) to comprehensively characterize the immune landscape of HNSCC in order to develop a rationale for immunotherapeutic strategies in HNSCC and guide clinical investigation. We find that both HPV+ and HPV- HNSCC tumors are among the most highly immune-infiltrated cancer types. Strikingly, HNSCC had the highest median Treg/CD8+ T cell ratio and the highest levels of CD56dim NK cell infiltration, in our pan-cancer analysis of the most immune-infiltrated tumors. CD8+ T cell infiltration and CD56dim NK cell infiltration each correlated with superior survival in HNSCC. Tumors harboring genetic smoking signatures had lower immune infiltration and were associated with poorer survival, suggesting these patients may benefit from immune agonist therapy. These findings illuminate the immune landscape of HPV+ and HPV- HNSCC. Additionally, this landscape provides a potentially novel rationale for investigation of agents targeting modulators of Tregs (e.g., CTLA-4, GITR, ICOS, IDO, and VEGFA) and NK cells (e.g., KIR, TIGIT, and 4-1BB) as adjuncts to anti-PD-1 in the treatment of advanced HNSCC.

Mitochondrial DNA copy number variation across human cancers.

Mutations, deletions, and changes in copy number of mitochondrial DNA (mtDNA), are observed throughout cancers. Here, we survey mtDNA copy number variation across 22 tumor types profiled by The Cancer Genome Atlas project. We observe a tendency for some cancers, especially of the bladder, breast, and kidney, to be depleted of mtDNA, relative to matched normal tissue. Analysis of genetic context reveals an association between incidence of several somatic alterations, including IDH1 mutations in gliomas, and mtDNA content. In some but not all cancer types, mtDNA content is correlated with the expression of respiratory genes, and anti-correlated to the expression of immune response and cell-cycle genes. In tandem with immunohistochemical evidence, we find that some tumors may compensate for mtDNA depletion to sustain levels of respiratory proteins. Our results highlight the extent of mtDNA copy number variation in tumors and point to related therapeutic opportunities.