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Supplementary Table S1, patient characteristics. Supplementary Table S2, genes in the signature distinguishing Cluster 1 and Cluster 2. Supplementary Table S3, genes associated with disease-specific survival. Supplementary Table S4, pathway modules identified by NetBox. Supplementary Table S5, functional annotation enrichment analysis. Supplementary Table S6, antibodies used. Supplementary Table S7, samples analyzed for ITGA10 mRNA in the comparison of primary and metastatic tissue.

Supplementary Figure Legends

Supplementary Figure S1, showing clustering of myxofibrosarcomas compared to normal tissue and showing the validation of the association of 5 genes with survival. Supplementary Figure S2, showing the effects of ITGA10 knockdown and overexpression. Supplementary Figure S3, showing the cell biology of integrin-alpha10 in myxofibrosarcoma cells. Supplementary Figure S4, showing the associations of TRIO and RICTOR amplification and overexpression with clinical outcomes. Supplementary Figure S5, showing that TRIO and RAC1 knockdown induce apoptosis in myxofibrosarcoma cells, but not in ASCs. Supplementary Figure S6, showing that RAPTOR knockdown does not induce apoptosis in myxofibrosarcoma cells. Supplementary Figure S7, showing the effects of RAC/PAK and mTOR inhibitors in myxofibrosarcoma cells and normal cells. Supplementary Figure S8, showing that mice treated with INK128 and/or EHop-016 maintain their weight.

The ability to assign cellular origin to low-abundance secreted factors in extracellular vesicles (EVs) would greatly facilitate the analysis of paracrine-mediated signaling. Here, we report a method, named selective isolation of extracellular vesicles (SIEVE), which uses cell type-specific proteome labeling via stochastic orthogonal recoding of translation (SORT) to install bioorthogonal reactive groups into the proteins derived from the cells targeted for labeling. We establish the native purification of intact EVs from a target cell, via a bioorthogonal tetrazine ligation, leading to copurification of the largely unlabeled EV proteome from the same cell. SIEVE enables capture of EV proteins at levels comparable with those obtained by antibody-based methods, which capture all EVs regardless of cellular origin, and at levels 20× higher than direct capture of SORT-labeled proteins. Using proteomic analysis, we analyze nonlabeled cargo proteins of EVs and show that the enhanced sensitivity of SIEVE allows for unbiased and comprehensive analysis of EV proteins from subpopulations of cells as well as for cell-specific EV proteomics in complex coculture systems. SIEVE can be applied with high efficiency in a diverse range of existing model systems for cell–cell communication and has direct applications for cell-of-origin EV analysis and for protein biomarker discovery.

Various computational approaches have been developed for estimating the relative abundance of different cell types in the tumor microenvironment (TME) using bulk tumor RNA data. However, a comprehensive comparison across diverse datasets that objectively evaluates the performance of these approaches has not been conducted. Here, we benchmarked seven widely used tools and gene sets and introduced ConsensusTME, a method that integrates gene sets from all the other methods for relative TME cell estimation of 18 cell types. We collected a comprehensive benchmark dataset consisting of pan-cancer data (DNA-derived purity, leukocyte methylation, and hematoxylin and eosin–derived lymphocyte counts) and cell-specific benchmark datasets (peripheral blood cells and tumor tissues). Although none of the methods outperformed others in every benchmark, ConsensusTME ranked top three in all cancer-related benchmarks and was the best performing tool overall. We provide a Web resource to interactively explore the benchmark results and an objective evaluation to help researchers select the most robust and accurate method to further investigate the role of the TME in cancer (www.consensusTME.org).Significance:This work shows an independent and comprehensive benchmarking of recently developed and widely used tumor microenvironment cell estimation methods based on bulk expression data and integrates the tools into a consensus approach.

Supplementary Table S1 Phenotypic characteristics of IBD-CRC cases. Supplementary Table S2A Selected somatic mutations in IBD-CRC hypermutators. Supplementary Table S2B Selected somatic mutations in IBD-CRC non-hypermutators. Supplementary Table S3 Cosine similarities of IBD-CRC signatures and Alexandrov signatures. Supplementary Table S4 Genes implicated in susceptibility to colorectal cancer. Supplementary Table S5 Selected germline variants. Supplementary Table S6 Estimated cellularity, ploidy and SCNAs in IBD-CRC samples.

Purpose: Inflammatory bowel disease–associated colorectal cancers (IBD-CRC) are associated with a higher mortality than sporadic colorectal cancers. The poorly defined molecular pathogenesis of IBD-CRCs limits development of effective prevention, detection, and treatment strategies. We aimed to identify biomarkers using whole-exome sequencing of IBD-CRCs to guide individualized management.Experimental Design: Whole-exome sequencing was performed on 34 formalin-fixed paraffin-embedded primary IBD-CRCs and 31 matched normal lymph nodes. Computational methods were used to identify somatic point mutations, small insertions and deletions, mutational signatures, and somatic copy number alterations. Mismatch repair status was examined.Results: Hypermutation was observed in 27% of IBD-CRCs. All hypermutated cancers were from the proximal colon; all but one of the cancers with hypermutation had defective mismatch repair or somatic mutations in the proofreading domain of DNA POLE. Hypermutated IBD-CRCs had increased numbers of predicted neo-epitopes, which could be exploited using immunotherapy. We identified six distinct mutation signatures in IBD-CRCs, three of which corresponded to known mechanisms of mutagenesis. Driver genes were also identified.Conclusions: IBD-CRCs should be evaluated for hypermutation and defective mismatch repair to identify patients with a higher neo-epitope load who may benefit from immunotherapies. Prospective trials are required to determine whether IHC to detect loss of MLH1 expression in dysplastic colonic tissue could identify patients at increased risk of developing IBD-CRC. We identified mutations in genes in IBD-CRCs with hypermutation that might be targeted therapeutically. These approaches would complement and individualize surveillance and treatment programs. Clin Cancer Res; 24(20); 5133–42. ©2018 AACR.

Supplementary Materials and Methods

Figure S1: Additional Analyses: A) Statistical framework benchmark results, each point represents the rank of that statistical framework when compared against the rest for each benchmarking experiment. ConsensusTME gene sets were used for all frameworks. B) Historical benchmark, each consecutive version of consensus contains signature/approach from an additional method, added chronologically. A) Kendall's correlation coefficients (Ï„) of xCell PBMC data based on CyTOF (top left: SDY311 n = 61, top right: SDY420 n = 104) and CIBERSORT PBMC data based on flow cytometry (bottom left, n = 20) vs RNA-derived cell type-specific estimates for the tested methods. The grey box represents correlation coefficients that have a q-value > 0.05 (B-H method). Box plots are sorted according to median correlation coefficient (left to right: decreasing performance).

Supplementary Table 1: A) TME cell estimation method information. B) Benchmarking dataset information. C) Cell type inclusion for multiple linear regression analyses. D) TME cell estimation method to ground truth cell type matching for cell type-specific benchmarking experiments.

Various computational approaches have been developed for estimating the relative abundance of different cell types in the tumor microenvironment (TME) using bulk tumor RNA data. However, a comprehensive comparison across diverse datasets that objectively evaluates the performance of these approaches has not been conducted. Here, we benchmarked seven widely used tools and gene sets and introduced ConsensusTME, a method that integrates gene sets from all the other methods for relative TME cell estimation of 18 cell types. We collected a comprehensive benchmark dataset consisting of pan-cancer data (DNA-derived purity, leukocyte methylation, and hematoxylin and eosin–derived lymphocyte counts) and cell-specific benchmark datasets (peripheral blood cells and tumor tissues). Although none of the methods outperformed others in every benchmark, ConsensusTME ranked top three in all cancer-related benchmarks and was the best performing tool overall. We provide a Web resource to interactively explore the benchmark results and an objective evaluation to help researchers select the most robust and accurate method to further investigate the role of the TME in cancer (www.consensusTME.org). Significance: This work shows an independent and comprehensive benchmarking of recently developed and widely used tumor microenvironment cell estimation methods based on bulk expression data and integrates the tools into a consensus approach.

Although cancer immunotherapy with PD-(L)1 blockade is now routine treatment for patients with lung cancer, remarkably little is known about acquired resistance. We examined 1,201 patients with NSCLC treated with PD-(L)1 blockade to clinically characterize acquired resistance, finding it to be common (occurring in more than 60% of initial responders), with persistent but diminishing risk over time, and with distinct metastatic and survival patterns compared to primary resistance. To examine the molecular phenotype and potential mechanisms of acquired resistance, we performed whole transcriptome and exome tumor profiling in a subset of NSCLC patients (n=29) with acquired resistance. Systematic immunogenomic analysis revealed that tumors with acquired resistance generally had enriched signals of inflammation (including IFNγ signaling and inferred CD8+ T cells) and could be separated into IFNγ upregulated and stable subsets. IFNγ upregulated tumors had putative routes of resistance with signatures of dysfunctional interferon signaling and mutations in antigen presentation genes. Transcriptomic profiling of cancer cells from a murine model of acquired resistance to PD-(L)1 blockade also showed evidence of dysfunctional interferon signaling and acquired insensitivity to in vitro interferon gamma treatment. In summary, we characterized clinical and molecular features of acquired resistance to PD-(L)1 blockade in NSCLC and found evidence of ongoing but dysfunctional IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance informs therapeutic strategies to effectively reprogram and reverse acquired resistance.

Summary The determinants of T cell infiltration in tumors remain largely unknown. In a recent issue of Cancer Cell, Hornburg et al. use single-cell RNA sequencing to characterize the cellular compartments of the ovarian cancer microenvironment and shed light on how tumor, immune, and stromal cells interact and shape T cell infiltration.

Summary Somatic DNA copy number variations (CNVs) are prevalent in cancer and can drive cancer progression, albeit with often uncharacterized roles in altering cell signaling states. Here, we integrate genomic and proteomic data for 5,598 tumor samples to identify CNVs leading to aberrant signal transduction. The resulting associations recapitulate known kinase-substrate relationships, and further network analysis prioritizes likely causal genes. Of the 303 significant associations we identify from the pan-tumor analysis, 43% are replicated in cancer cell lines, including 44 robust gene-phosphosite associations identified across multiple tumor types. Several predicted regulators of hippo signaling are experimentally validated. Using RNAi, CRISPR, and drug screening data, we find evidence of kinase addiction in cancer cell lines, identifying inhibitors for targeting of kinase-dependent cell lines. We propose copy number status of genes as a useful predictor of differential impact of kinase inhibition, a strategy that may be of use in the future for anticancer therapies., Graphical abstract, Highlights • Alterations in copy number and in signaling pathways are robustly associated in cancer • Differences in essentiality of phosphoproteins show evidence of kinase addiction • Copy number markers of dysregulated signaling suggest treatment stratification options, Memon et al. show that copy number alterations can be used as molecular fingerprints to predict the activity of signaling pathways in cancer. Kinase dependencies of cancer cells can be exploited for targeted anticancer therapy.

Cancer is a leading cause of death worldwide and, despite new targeted therapies and immunotherapies, many patients with advanced-stage- or high-risk cancers still die, owing to metastatic disease. Adoptive T-cell therapy, involving the autologous or allogeneic transplant of tumour-infiltrating lymphocytes or genetically modified T cells expressing novel T-cell receptors or chimeric antigen receptors, has shown promise in the treatment of cancer patients, leading to durable responses and, in some cases, cure. Technological advances in genomics, computational biology, immunology and cell manufacturing have brought the aspiration of individualised therapies for cancer patients closer to reality. This new era of cell-based individualised therapeutics challenges the traditional standards of therapeutic interventions and provides opportunities for a paradigm shift in our approach to cancer therapy. Invited speakers at a 2020 symposium discussed three areas—cancer genomics, cancer immunology and cell-therapy manufacturing—that are essential to the effective translation of T-cell therapies in the treatment of solid malignancies. Key advances have been made in understanding genetic intratumour heterogeneity, and strategies to accurately identify neoantigens, overcome T-cell exhaustion and circumvent tumour immunosuppression after cell-therapy infusion are being developed. Advances are being made in cell-manufacturing approaches that have the potential to establish cell-therapies as credible therapeutic options. T-cell therapies face many challenges but hold great promise for improving clinical outcomes for patients with solid tumours.

Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naïve patient and by leveraging the analytical power of multi-sample analyses, we reveal that metastatic cells may depart the primary tumour very early in the disease course and follow a branched pattern of evolution. Truncal UV-induced mutations that often swamp downstream analyses of heterogeneity, were found to be replaced by APOBEC-associated mutations in the branches of the evolutionary tree. Multi-sample analyses from a further 7 patients confirmed that branched evolution was pervasive, representing an important mode of melanoma dissemination. Our analyses illustrate that combining cancer cell fraction estimates across multiple metastases provides higher resolution phylogenetic reconstructions relative to single sample analyses and highlights the limitations of accurately inferring inter-tumoural heterogeneity from a single biopsy.

SUMMARYVascular endothelial cellsin vivoare exquisitely regulated by their local environment, which is absent or disrupted when using methods such as FACS orin vitrocell culture to study native signaling pathways. Here, we profile the gene expression patterns of undisturbed endothelial cells in living animals using a novel ‘AngioTag’ zebrafish transgenic line that permits isolation of actively translating mRNAs from endothelial cells in their native environment. This transgenic line uses the endothelial cell-specifickdrlpromoter to drive expression of an epitope tagged Rpl10a 60S ribosomal subunit protein, allowing for Translating Ribosome Affinity Purification (TRAP) of actively translating endothelial cell mRNAs. By performing TRAP-RNAseq on AngioTag animals, we demonstrate strong enrichment of endothelial specific genes and uncover novel endothelially expressed genes. Additionally, we generated a ‘UAS:RiboTag’ transgenic line to allow for the study of a wider array of zebrafish cell and tissue types using TRAP-RNAseq methods. This new tool offers an unparalleled resource to study cause and effect relationships in the context of gene loss or gain of functionin vivo.HIGHLIGHTSAn ‘AngioTag’ transgenic line permitsin vivoendothelial expression profilingThe AngioTag line is used for Translating Ribosome Affinity Purification - RNAseqA ‘UAS:RiboTag’ line enables profiling of any zebrafish cell and tissue type

Centrioles are core structural elements of both centrosomes and cilia. Although cytoplasmic granules called centriolar satellites have been observed around these structures, lack of a comprehensive inventory of satellite proteins impedes our understanding of their ancestry. To address this, we performed mass spectrometry (MS)‐based proteome profiling of centriolar satellites obtained by affinity purification of their key constituent, PCM1, from sucrose gradient fractions. We defined an interactome consisting of 223 proteins, which showed striking enrichment in centrosome components. The proteome also contained new structural and regulatory factors with roles in ciliogenesis. Quantitative MS on whole‐cell and centriolar satellite proteomes of acentriolar cells was performed to reveal dependencies of satellite composition on intact centrosomes. Although most components remained associated with PCM1 in acentriolar cells, reduced cytoplasmic and satellite levels were observed for a subset of centrosomal proteins. These results demonstrate that centriolar satellites and centrosomes form independently but share a substantial fraction of their proteomes. Dynamic exchange of proteins between these organelles could facilitate their adaptation to changing cellular environments during development, stress response and tissue homeostasis.

Approximately 20-40% of cancer patients who initially benefit from PD-1/L1 checkpoint blockade later develop progressive disease, which is associated with genetic and/or phenotypic changes in tumor cells that enable acquired resistance. Tumors from patients who have developed acquired resistance to checkpoint blockade (CPI-AR) typically demonstrate downregulation of specific antigens or proteins involved in antigen presentation on MHC class I, and dysregulation of interferon response pathways. With increasing CPI use across a large number of tumor types, the proportion of cancer patients with CPI-AR is increasing. Pre-clinical tumor models which mimic CPI-AR in humans are needed. We generated in vivo CPI-AR tumor models by serially passaging common CPI responsive murine syngeneic tumor cell lines (i.e. CT26) in vivo, followed by the excision and ex vivo expansion of the tumors that failed to respond to anti-PD1. This was repeated until passaged tumors no longer responded to anti-PD1 therapy. Transcriptomes of CT26 parental, CT26/CPI-AR, and B16.F10 melanoma (considered CPI primary resistant, CPI-PR) tumors were sequenced either under normal culture conditions or following 24 hour exposure to IFNg to assess interferon responsiveness. Here we present the genomic characterization of the CPI -PR and -AR models. Paradoxically, CPI-AR tumors maintain a state of type I/II IFN gene hyperactivation and increased expression of genes involved in MHC class I mediated antigen presentation/processing. Despite this transcriptional hyperactivity, CPI-AR tumor cells have a decreased capacity to translate and traffic these associated proteins to the cell membrane. Interestingly, upon challenge with IFNg, CPI-AR tumors down-regulate gene expression for PD-L1, TAP1, TAP2, β2M and other key pathways typically up-regulated by IFN stimulation. Collectively, the CPI-AR and -PR tumor models reflect many of the genomic and phenotypic changes reported in CPI-AR cancer patients. The CT26/CPI-AR tumors reproduce a state of IFN hypo-responsiveness and genetic/protein dysregulation. These clinically relevant models can be used to screen therapeutics that may translate to meaningful benefit for CPI-AR cancer patients. Citation Format: George J. Fromm, Danish Memon, Suresh de Silva, Kyung Jin Yoo, Kellsey Johannes, Casey Shuptrine, Jaya Miriyala, Arpita Patel, Fatima Rangwala, Zachary Opheim, Thuy-Ai Nguyen, Louis Gonzalez, Fatima Rangwala, Taylor H. Schreiber, Matthew D. Hellmann, Martin L. Miller, Taylor H. Schreiber. The development of an in vivo model of checkpoint acquired resistance, reveals a program of interferon hyperstimulation, resulting in dysregulation of MHC class I, protein translation/trafficking, and other unique pathways, that may be useful for guiding clinical strategy in patients with phenotypic similarities [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 1697.

Myxofibrosarcoma is a common mesenchymal malignancy with complex genomics and heterogeneous clinical outcomes. Through gene-expression profiling of 64 primary high-grade myxofibrosarcomas, we defined an expression signature associated with clinical outcome. The gene most significantly associated with disease-specific death and distant metastasis was ITGA10 (integrin-α10). Functional studies revealed that myxofibrosarcoma cells strongly depended on integrin-α10, whereas normal mesenchymal cells did not. Integrin-α10 transmitted its tumor-specific signal via TRIO and RICTOR, two oncoproteins that are frequently co-overexpressed through gene amplification on chromosome 5p. TRIO and RICTOR activated RAC/PAK and AKT/mTOR to promote sarcoma cell survival. Inhibition of these proteins with EHop-016 (RAC inhibitor) and INK128 (mTOR inhibitor) had antitumor effects in tumor-derived cell lines and mouse xenografts, and combining the drugs enhanced the effects. Our results demonstrate the importance of integrin-α10/TRIO/RICTOR signaling for driving myxofibrosarcoma progression and provide the basis for promising targeted treatment strategies for patients with high-risk disease. Significance: Identifying the molecular pathogenesis for myxofibrosarcoma progression has proven challenging given the highly complex genomic alterations in this tumor type. We found that integrin-α10 promotes tumor cell survival through activation of TRIO–RAC–RICTOR–mTOR signaling, and that inhibitors of RAC and mTOR have antitumor effects in vivo, thus identifying a potential treatment strategy for patients with high-risk myxofibrosarcoma. Cancer Discov; 6(10); 1148–65. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 1069

Simple Summary Clinical responses to the initial treatment of high grade serous ovarian cancer (HGSOC) vary greatly. Widespread intra-site and inter-site genomic heterogeneity presents significant challenges for the development of predictive biomarkers based on pre-treatment sampling of select individual tumors. Non-invasive stratification of patients with HGSOC by risk of outcome could facilitate a higher level of intervention for those with the highest risk of a poor outcome. We developed and validated a machine learning-based integrated marker of HGSOC outcomes to standard chemotherapy that combines a previously developed intra-site and inter-site CT radiomics measure called cluster dissimilarity (cluDiss) with clinical and genomic measures using two retrospective cohorts of internal and external institution datasets. Our approach was more accurate than conventional clinical and average radiomics measures for prognosticating progression-free survival and platinum resistance. Abstract Purpose: Develop an integrated intra-site and inter-site radiomics-clinical-genomic marker of high grade serous ovarian cancer (HGSOC) outcomes and explore the biological basis of radiomics with respect to molecular signaling pathways and the tumor microenvironment (TME). Method: Seventy-five stage III-IV HGSOC patients from internal (N = 40) and external factors via the Cancer Imaging Archive (TCGA) (N = 35) with pre-operative contrast enhanced CT, attempted primary cytoreduction, at least two disease sites, and molecular analysis performed within TCGA were retrospectively analyzed. An intra-site and inter-site radiomics (cluDiss) measure was combined with clinical-genomic variables (iRCG) and compared against conventional (volume and number of sites) and average radiomics (N = 75) for prognosticating progression-free survival (PFS) and platinum resistance. Correlation with molecular signaling and TME derived using a single sample gene set enrichment that was measured. Results: The iRCG model had the best platinum resistance classification accuracy (AUROC of 0.78 [95% CI 0.77 to 0.80]). CluDiss was associated with PFS (HR 1.03 [95% CI: 1.01 to 1.05], p = 0.002), negatively correlated with Wnt signaling, and positively to immune TME. Conclusions: CluDiss and the iRCG prognosticated HGSOC outcomes better than conventional and average radiomic measures and could better stratify patient outcomes if validated on larger multi-center trials.

Little is known regarding the relationship between intra-tumor heterogeneity (ITH) and immune response in melanoma. Here, we explored the role of ITH in tumor rejection by establishing a melanoma mouse model and inducing UVB-derived mutations that increase both ITH and mutational load. This induction gives rise to highly aggressive tumors and decreased cytotoxic activity of tumor infiltrating lymphocytes (TILs). Conversely, single cell-derived melanoma clones with reduced ITH are swiftly rejected. Tumor rejection is accompanied by increased TIL reactivity and increased infiltration into the tumor core. Using phylogenetic tree analyses and mixing experiments of 20 single cell clones that lie along the phylogenetic tee we show that tumor rejection is strongly affected by number of injected clones and genetic diversity. We have, thus set up a novel, highly controlled system that enables us to study the interphase between the immune system and different layers of intra-tumor heterogeneity. Finally, the analysis of melanoma patient data identifies parallel observations, supporting the importance of ITH in determining patient survival and response to checkpoint blockade. Citation Format: Osnat Bartok, Sushant Patkar, Sapir Cohen, Kevin Litchfield, Hiren Karathia, Joo Sang Lee, Alejandro Jiménez-Sánchez, Chi-Ping Day, Lea Eisenbach, Martin Miller, Glenn Merlino, Eli Pikarsky, Arie Admon, Charles Swanton, Eytan Ruppin, Yardena Samuels, Yochai Wolf. UVB-induced tumor heterogeneity directs immune response in melanoma [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA07.

9621 Background: Although durability is the trademark characteristic of response to PD-1 blockade, acquired resistance can occur. The frequency, patterns, and survival outcomes of patients with acquired resistance to PD-1 blockade are unknown. Methods: All patients with NSCLC treated with PD-1 blockade at MSKCC were examined. Acquired resistance was defined as initial CR/PR (by RECIST) followed by progression/death. Oligo vs systemic patterns of acquired resistance were defined as progression in ≤ 2 sites of disease or ≥ 3 sites of disease, respectively. Results: Of 1201 patients treated with PD-1 blockade, 243 (20%) achieved initial response and 189 (78%, 95% CI 72-83%) eventually developed acquired resistance (AR). Onset of AR was variable and decreased with longer duration of response (53% within 1 year, 37% 1-2 years, 10% > 2 years). Patients with PD-L1 expression < 50% and TMB < 8mut/Mb were more likely to develop resistance compared those with PD-L1 expression ≥50% and TMB ≥8mut/Mb (OR 5.5, p = 0.02). Unlike organ sites of primary refractory disease, AR commonly occurred in lymph nodes (41%) and infrequently in the liver (6%). Patterns of AR were most commonly oligo rather than systemic (79/141 [56%], 39/141 [28%]); some patients died without radiographic progression (23/141 [16%]). Oligo-AR occurred later (median onset 13 vs 5.6 mo) and associated with improved post-progression survival (median OS 55.2 vs 9.2 mo, HR 6.0, p < 0.001) compared to systemic-AR. Post-progression survival was highest in patients with AR compared to those with initial SD or PD to PD-1 blockade (median 18.9 vs 12.5 vs 4.4, p < 0.001). Of 49 patients treated initially with locally-directed therapy for AR, 28 (57%) remain alive and systemic therapy-free. Conclusions: Acquired resistance to PD-1 blockade is common in NSCLC. Risk of acquired resistance is lower in biomarker-enriched patients and with increased duration of response. Patterns of acquired resistance is commonly oligo in nature, which is amenable to locally-directed therapy and can be associated with improved survival. Differences in organ-site distribution and post-progression survival suggest distinct biology associated with acquired resistance vs primary refractory disease.

BackgroundHigh grade serous ovarian carcinoma shows marked intra-tumoral heterogeneity which is associated with decreased survival and resistance to platinum-based chemotherapy. Pre-treatment quantification of spatial tumor heterogeneity by multiple tissue sampling is not clinically feasible. Using standard-of-care CT imaging to non-invasively quantify heterogeneity could have high clinical utility and would be highly cost-effective. Texture analysis measures local variations in computed tomography (CT) image intensity. Haralick texture methods are typically used to capture the heterogeneity of entire lesions; however, this neglects the possible presence of texture habitats within the lesion, and the differences between metastatic sites. The primary aim of this study was to develop texture analysis of intra-site and inter-site spatial heterogeneity from standard-of-care CT images and to correlate these measures with clinical and genomic features in patients with HGSOC.Methods and findingsWe analyzed the data from a retrospective cohort of 84 patients with HGSOC consisting of 46 patients from Memorial Sloan Kettering Cancer Center (MSKCC) and 38 non-MSKCC cases selected from The Cancer Imaging Archive (TCIA). Inclusion criteria consisted of FIGO stage II–IV HGSOC, attempted primary cytoreductive surgery, intravenous contrast-enhanced CT of abdomen and pelvis performed prior to surgery and availability of molecular tumor data analysed as per the Cancer Genome Atlas (TCGA) Research Network ovarian cancer project. Manual segmentation and image analysis was performed on 463 metastatic tumor sites from 84 patients. In the MSKCC cohort the median number of tumor sites was 7 (interquartile range 5–9) and 4 (interquartile range 3–4) in the TCIA patients. Sub-regions were produced within each tumor site by grouping voxels with similar Haralick texture using the Kernel K-means method. We derived statistical measures of intra- and inter-site tumor heterogeneity (IISTH) including cluster sites entropy (cSE), cluster sites standard deviation (cluDev) and cluster sites dissimilarity (cluDiss) from sub-regions identified within and between individual tumor sites. Unsupervised clustering was used to group patient IISTH measures into low, medium, high, and ultra-high heterogeneity clusters from each cohort.The IISTH measure cluDiss was an independent predictor of progression-free survival (PFS) in multivariable analysis in both datasets (MSKCC hazard ratio [HR] 1.04, 95% CI 1.01–1.06, P = 0.002; TCIA HR 1.05, 95% CI 1.00–1.10, P = 0.049). Low and medium IISTH clusters were associated with longer PFS in multivariable analysis (MSKCC HR 2.94, 90% CI 1.29–6.70, P = 0.009, TCIA HR 5.94, 95% CI 1.05–33.6, P = 0.044). IISTH measures were robust to differences in the CT imaging systems. Average Haralick textures contrast (TCIA HR 1.08, 95% CI 1.01–1.10, P = 0.019) and homogeneity (TCIA HR 1.09, 95% CI 1.02–1.16, P = 0.008) were associated with PFS in mutivariate analysis only in the TCIA dataset. All other average Haralick textures and total tumor volume were not associated with PFS in either dataset.ConclusionsTexture measures of intra- and inter-site tumor heterogeneity from standard of care CT images are correlated with shorter PFS in HGSOC patients. These quantitative methods are independent of the CT imaging system and can thus be applied in clinical practice. The methodology proposed here enables the non-invasive quantification of intra-tumoral heterogeneity and disease stratification for future experimental medicine studies and clinical trials, particularly in cases where total tumour volume and averaged textures have low predictive power.Author summaryWhy was this study done?Tumor heterogeneity is a feature of many solid malignancies including ovarian cancer.Recent genomic research suggests that intra-site tumor heterogeneity (heterogeneity within a single tumor site) and inter-site tumor heterogeneity (heterogeneity between different metastatic sites in the same patient) correlate with clinical outcome in HGSOC.What did the researchers do and find?We developed quantitative and non-invasive image-analysis based measures for predicting outcome in HGSOC patients by combining image-based information from within and between multiple tumor sites.Using datasets from two sources, we demonstrate that these image-based tumor heterogeneity measures predict progression free survival in patients with HGSOC.What do these findings mean?Non-invasive measures of CT image heterogeneity may predict outcomes in HGSOC patients.Wider application of these CT image heterogeneity measures could prove useful for stratifying patients to different therapies given that total tumour volume and averaged textures have low predictive power.

Somatic DNA copy number variations (CNVs) are prevalent in cancer and can drive cancer progression albeit with often uncharacterized roles in altering cell signaling states. Here, we integrated genomic and proteomic data for 5598 tumor samples to identify CNVs leading to aberrant signal transduction. The resulting associations recapitulated known kinase-substrate relationships and further network analysis prioritized likely driver genes. A total of 44 robust pan-cancer gene-phosphosite associations were replicated in cell line samples. Of these, ARHGEF17, a predicted regulator of hippo-signaling, was further studied through (phospho)proteomics analysis where ARHGEF17 knockdown cells showed dys-regulation of hippo- and p38 signaling as well as immune related pathways. Using, RNAi, CRISPR and drug screening data we find evidence of kinase addiction in cancer cell lines identifying inhibitors for targeting of ‘kinase-dependent’ cell lines. We propose copy number status of genes as useful predictors of differential impact of kinase inhibition, a strategy that may be of use in the future for anticancer therapies.

Somatic mutations can result in the formation of neoantigens, immunogenic peptides that are presented on the tumor cell surface by HLA molecules. These mutations are expected to be under negative selection pressure, but the extent of the resulting neoantigen depletion remains unclear. On the basis of HLA affinity predictions, we annotated the human genome for its translatability to HLA binding peptides and screened for reduced single nucleotide substitution rates in large genomic data sets from untreated cancers. Apparent neoantigen depletion signals become negligible when taking into consideration trinucleotide-based mutational signatures, owing to lack of power or to efficient immune evasion mechanisms that are active early during tumor evolution.

Somatic mutations in cancer can result in the presentation of mutated peptides on the cell surface, eliciting an immune response. Mutant peptides are presented via HLA molecules and are known as neoantigens. It has been suggested that selection acts against the underlying mutations, leading to neoantigen depletion. Knowing the extent of this specific form of immunoediting may provide fundamental insights into tumour-immune interactions during tumour evolution. Here, we quantified the extent of neoantigen depletion in a wide range of human cancers by studying somatic mutations in the HLA-binding annotated exome, i.e. genomic regions that can be translated into presented peptides. We initially observed reduced non-synonymous mutation rates in presented regions, suggestive of neoantigen depletion. However, when compared to the expected mutation rates from a trinucleotide-based mutational signature model, depletion signals were negligible. This is explained by correlative relationships between the likelihood of mutagenesis in different nucleotide sequences and predicted HLA affinities for corresponding peptides. Our results suggest that signals of immunogenic negative selection are weak or absent in cancer genomics data and that other mechanisms to escape immune responses early during tumour evolution might be more efficient.

In metastatic cancer, the role of heterogeneity at the tumor-immune microenvironment, its molecular underpinnings and clinical relevance remain largely unexplored. To understand tumor-immune dynamics at baseline and upon chemotherapy treatment, we performed unbiased pathway and cell type-specific immunogenomics analysis of treatment-naive (38 samples from 8 patients) and paired chemotherapy treated (80 paired samples from 40 patients) high-grade serous ovarian cancer (HGSOC) samples. Whole transcriptome analysis and image-based quantification of T cells from treatment-naive tumors revealed ubiquitous variability in immune signaling and distinct immune microenvironments co-existing within the same individuals and within tumor deposits at diagnosis. To systematically explore cell type composition of the tumor microenvironment using bulk mRNA, we derived consensus immune and stromal cell gene signatures by intersecting state-of-the-art deconvolution methods, providing improved accuracy and sensitivity when compared to HGSOC immunostaining and leukocyte methylation data sets. Cell-type deconvolution and pathway analyses revealed that Myc and Wnt signaling associate with immune cell exclusion in untreated HGSOC. To evaluate the effect of chemotherapy on the intrinsic tumor-immune heterogeneity, we compared site-matched and site-unmatched tumors before and after neoadjuvant chemotherapy. Transcriptomic and T-cell receptor sequencing analyses showed that site-matched samples had increased cytotoxic immune activation and oligoclonal expansion of T cells after chemotherapy, which was not seen in site-unmatched samples where heterogeneity could not be accounted for. These results demonstrate that the tumor-immune interface in advanced HGSOC is intrinsically heterogeneous, and thus requires site-specific analysis to reliably unmask the impact of therapy on the tumor-immune microenvironment.

In cancer genomics, recurrence of mutations in independent tumor samples is a strong indicator of functional impact. However, rare functional mutations can escape detection by recurrence analysis owing to lack of statistical power. We enhance statistical power by extending the notion of recurrence of mutations from single genes to gene families that share homologous protein domains. Domain mutation analysis also sharpens the functional interpretation of the impact of mutations, as domains more succinctly embody function than entire genes. By mapping mutations in 22 different tumor types to equivalent positions in multiple sequence alignments of domains, we confirm well-known functional mutation hotspots; identify uncharacterized rare variants in one gene that are equivalent to well-characterized mutations in another gene; detect previously unknown mutation hotspots; and provide hypotheses about molecular mechanisms and downstream effects of domain mutations. With the rapid expansion of cancer genomics projects, protein domain hotspot analysis will likely provide many more leads linking mutations in proteins to the cancer phenotype.

Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. To unravel the genomic determinants of response to this therapy, we used whole-exome sequencing of non–small cell lung cancers treated with pembrolizumab, an antibody targeting programmed cell death-1 (PD-1). In two independent cohorts, higher nonsynonymous mutation burden in tumors was associated with improved objective response, durable clinical benefit, and progression-free survival. Efficacy also correlated with the molecular smoking signature, higher neoantigen burden, and DNA repair pathway mutations; each factor was also associated with mutation burden. In one responder, neoantigen-specific CD8+ T cell responses paralleled tumor regression, suggesting that anti–PD-1 therapy enhances neoantigen-specific T cell reactivity. Our results suggest that the genomic landscape of lung cancers shapes response to anti–PD-1 therapy.

Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src.

To address limitations of current high-throughput methods for studying cell-cell communication and determining the cell-of-origin of proteins in multicellular environments, we have developed a technique that selectively and continuously labels the proteome of individual cell types in co-culture. Through transgenic expression of exogenous amino acid biosynthesis enzymes, vertebrate cells overcome their dependence on essential amino acids and can be selectively labeled through metabolic incorporation of amino acids produced from heavy isotope-labeled precursors. We have named this method Type specific labeling with Amino acid Precursors (CTAP). Testing CTAP in several human and mouse cell lines, we were able to differentially label the proteome of distinct cell populations in co-culture and determine the relative expression of proteins by quantitative mass spectrometry. In addition, CTAP successfully identified the cell-of-origin of extracellular proteins in co-culture, highlighting its potential use in biomarker discovery for linking secreted factors to their cellular source.

Purpose: Inflammatory bowel disease–associated colorectal cancers (IBD-CRC) are associated with a higher mortality than sporadic colorectal cancers. The poorly defined molecular pathogenesis of IBD-CRCs limits development of effective prevention, detection, and treatment strategies. We aimed to identify biomarkers using whole-exome sequencing of IBD-CRCs to guide individualized management. Experimental Design: Whole-exome sequencing was performed on 34 formalin-fixed paraffin-embedded primary IBD-CRCs and 31 matched normal lymph nodes. Computational methods were used to identify somatic point mutations, small insertions and deletions, mutational signatures, and somatic copy number alterations. Mismatch repair status was examined. Results: Hypermutation was observed in 27% of IBD-CRCs. All hypermutated cancers were from the proximal colon; all but one of the cancers with hypermutation had defective mismatch repair or somatic mutations in the proofreading domain of DNA POLE. Hypermutated IBD-CRCs had increased numbers of predicted neo-epitopes, which could be exploited using immunotherapy. We identified six distinct mutation signatures in IBD-CRCs, three of which corresponded to known mechanisms of mutagenesis. Driver genes were also identified. Conclusions: IBD-CRCs should be evaluated for hypermutation and defective mismatch repair to identify patients with a higher neo-epitope load who may benefit from immunotherapies. Prospective trials are required to determine whether IHC to detect loss of MLH1 expression in dysplastic colonic tissue could identify patients at increased risk of developing IBD-CRC. We identified mutations in genes in IBD-CRCs with hypermutation that might be targeted therapeutically. These approaches would complement and individualize surveillance and treatment programs. Clin Cancer Res; 24(20); 5133–42. ©2018 AACR.

Introduction Inflammatory bowel disease-associated colorectal cancers (IBD-CRCs) occur infrequently but are associated with a higher mortality than sporadic CRCs. The poorly defined genetic and molecular pathogenesis of IBD-CRCs limits our ability to develop effective prevention, detection and treatment strategies. Since molecular changes identified at the time of surgery are most likely to represent informative biomarkers we elected to study primary IBD-CRC. Method 6The study was approved by the Lothian NHS Research Scotland BioResource (ref:15/ES/0094). Whole-exome sequencing and a comprehensive mutational analysis was performed on 35 FFPE IBD-CRCs and matched normal lymph node pairs from 32 patients (16 CD). Two of the patients had synchronous cancers. Results Ten (29%) of 35 IBD-CRCs were hypermutated and had a significantly higher 10 year survival than the non-hypermutator cancers (p=0.04). All hypermutator cancers were in the proximal colon; seven had loss of expression of MLH1, of which 5 had MLH1 promoter methylation. Two had somatic mutations in the proof-reading domain of DNA POLE. The hypermutated IBD-CRCs had a predicted increased neo-epitope load suggesting that these cancers may benefit from immune checkpoint blockade. Six distinct IBD-CRC mutational signatures were identified with four corresponding to known mutational mechanisms. Five genes including TP53, APC, PIK3CA, and KRAS were significantly mutated in the non-hypermutator IBD-CRCs and fourteen genes in the hypermutator IBD-CRCs, including RNF43 and AIM2, which are clinically actionable. Eleven of the 32 patients (34%) had germline mutations that may confer an inherited susceptibility to colorectal cancer; only two of these specific variants have a clinical pathogenic effect. Conclusion The hypermutated IBD-CRCs are associated with defects in MMR and DNA POLE; with a predicted higher neo-epitope load, which could be exploited using immunotherapies. Loss of MLH1 expression could be evaluated in potential colonic dysplastic or cancerous lesions detected in IBD patients. The identification of novel significantly mutated genes in hypermutated IBD-CRCs could be used to stratify therapy. These approaches would complement and individualise current surveillance and treatment programs for IBD-CRC. Disclosure of Interest None Declared

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

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. DOI: http://dx.doi.org/10.7554/eLife.10769.001, eLife digest Within each cell of your body lie hundreds or thousands of mitochondria. These structures are perhaps best known for making energy, but mitochondria also play roles in processes like the immune response and cell signaling. However, in the mutant cells that form cancerous tumors, these roles can be subverted and altered. Mitochondria contain their own DNA, which is distinct from the DNA stored in the nucleus of the cell, and codes for the proteins that the mitochondria need to produce energy. Reznik et al. used next-generation DNA sequencing data produced by The Cancer Genome Atlas consortium to estimate the number of copies of mitochondrial DNA in tumor cells and the adjacent normal tissue. This revealed that in many types of cancer, tumor cells have fewer copies of mitochondrial DNA than the cells that make up normal tissue. In many cases, the depletion of mitochondrial DNA was accompanied by a reduction of the expression of mitochondrial genes, suggesting that mitochondrial activity may be suppressed in these tumor types. Reznik et al. also found that the number of copies of mitochondrial DNA in certain tumor types is related to the incidence of key 'driver' mutations that cause cells to become cancerous. This knowledge may help to develop new treatments for these tumors. DOI: http://dx.doi.org/10.7554/eLife.10769.002

Transfection of small RNAs (such as small interfering RNAs (siRNAs) and microRNAs (miRNAs)) into cells typically lowers expression of many genes. Unexpectedly, increased expression of genes also occurs. We investigated whether this upregulation results from a saturation effect--that is, competition among the transfected small RNAs and the endogenous pool of miRNAs for the intracellular machinery that processes small RNAs. To test this hypothesis, we analyzed genome-wide transcript responses from 151 published transfection experiments in seven different human cell types. We show that targets of endogenous miRNAs are expressed at significantly higher levels after transfection, consistent with impaired effectiveness of endogenous miRNA repression. This effect exhibited concentration and temporal dependence. Notably, the profile of endogenous miRNAs can be largely inferred by correlating miRNA sites with gene expression changes after transfections. The competition and saturation effects have practical implications for miRNA target prediction, the design of siRNA and short hairpin RNA (shRNA) genomic screens and siRNA therapeutics.

There is ample evidence for the involvement of protein phosphorylation on serine/threonine/tyrosine in bacterial signaling and regulation, but very few exact phosphorylation sites have been experimentally determined. Recently, gel-free high accuracy MS studies reported over 150 phosphorylation sites in two bacterial model organisms Bacillus subtilis and Escherichia coli. Interestingly, the analysis of these phosphorylation sites revealed that most of them are not characteristic for eukaryotic-type protein kinases, which explains the poor performance of eukaryotic data-trained phosphorylation predictors on bacterial systems. We used these large bacterial datasets and neural network algorithms to create the first bacteria-specific protein phosphorylation predictor: NetPhosBac. With respect to predicting bacterial phosphorylation sites, NetPhosBac significantly outperformed all benchmark predictors. Moreover, NetPhosBac predictions of phosphorylation sites in E. coli proteins were experimentally verified on protein and site-specific levels. In conclusion, NetPhosBac clearly illustrates the advantage of taxa-specific predictors and we hope it will provide a useful asset to the microbiological community.

Advances in mass spectrometry-based proteomics have yielded a substantial mapping of the tyrosine phosphoproteome and thus provided an important step toward a systematic analysis of intracellular signaling networks in higher eukaryotes. In this study we decomposed an uncharacterized proteomics data set of 481 unique phosphotyrosine (Tyr(P)) peptides by sequence similarity to known ligands of the Src homology 2 (SH2) and the phosphotyrosine binding (PTB) domains. From 20 clusters we extracted 16 known and four new interaction motifs. Using quantitative mass spectrometry we pulled down Tyr(P)-specific binding partners for peptides corresponding to the extracted motifs. We confirmed numerous previously known interaction motifs and found 15 new interactions mediated by phosphosites not previously known to bind SH2 or PTB. Remarkably, a novel hydrophobic N-terminal motif ((L/V/I)(L/V/I)pY) was identified and validated as a binding motif for the SH2 domain-containing inositol phosphatase SHIP2. Our decomposition of the in vivo Tyr(P) proteome furthermore suggests that two-thirds of the Tyr(P) sites mediate interaction, whereas the remaining third govern processes such as enzyme activation and nucleic acid binding.

We present an exceptional case of a patient with high-grade serous ovarian cancer, treated with multiple chemotherapy regimens, who exhibited regression of some metastatic lesions with concomitant progression of other lesions during a treatment-free period. Using immunogenomic approaches, we found that progressing metastases were characterized by immune cell exclusion, whereas regressing and stable metastases were infiltrated by CD8

In cancer, mitochondrial dysfunction, through mutations, deletions, and changes in copy number of mitochondrial DNA (mtDNA), contributes to the malignant transformation and progression of tumors. Here, we report the first large-scale survey of mtDNA copy number variation across 21 distinct solid tumor types, examining over 13,000 tissue samples profiled with next-generation sequencing methods. We find a tendency for cancers, especially of the bladder and kidney, to be significantly depleted of mtDNA, relative to matched normal tissue. We show that mtDNA copy number is correlated to the expression of mitochondrially-localized metabolic pathways, suggesting that mtDNA copy number variation reflect gross changes in mitochondrial metabolic activity. Finally, we identify a subset of tumor-type-specific somatic alterations, including IDH1 and NF1 mutations in gliomas, whose incidence is strongly correlated to mtDNA copy number. Our findings suggest that modulation of mtDNA copy number may play a role in the pathology of cancer.