Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer.

Although immunotherapy with PD-(L)1 blockade is routine for lung cancer, little is known about acquired resistance. Among 1,201 patients with non-small cell lung cancer (NSCLC) treated with PD-(L)1 blockade, acquired resistance is common, occurring in >60% of initial responders. Acquired resistance shows differential expression of inflammation and interferon (IFN) signaling. Relapsed tumors can be separated by upregulated or stable expression of IFNγ response genes. Upregulation of IFNγ response genes is associated with putative routes of resistance characterized by signatures of persistent IFN signaling, immune dysfunction, and mutations in antigen presentation genes which can be recapitulated in multiple murine models of acquired resistance to PD-(L)1 blockade after in vitro IFNγ treatment. Acquired resistance to PD-(L)1 blockade in NSCLC is associated with an ongoing, but altered IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance may inform therapeutic strategies to effectively reprogram and reverse acquired resistance.

Cell-of-origin-specific proteomics of extracellular vesicles.

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.

Ovarian tumors orchestrate distinct cellular compositions.

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.

Copy number aberrations drive kinase rewiring, leading to genetic vulnerabilities in cancer.

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.

Promises and challenges of adoptive T-cell therapies for solid tumours.

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.

Integrated Multi-Tumor Radio-Genomic Marker of Outcomes in Patients with High Serous Ovarian Carcinoma.

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.

Multi-site clonality analysis uncovers pervasive heterogeneity across melanoma metastases.

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 evidence of diversification among metastatic lineages. UV-induced mutations dominate the trunk, whereas APOBEC-associated mutations are found in the branches of the evolutionary tree. Multi-sample analyses from a further seven patients confirmed that lineage diversification was pervasive, representing an important mode of melanoma dissemination. Our analyses demonstrate that joint analysis of cancer cell fraction estimates across multiple metastases can uncover previously unrecognised levels of tumour heterogeneity and highlight the limitations of inferring heterogeneity from a single biopsy.

Unraveling tumor-immune heterogeneity in advanced ovarian cancer uncovers immunogenic effect of chemotherapy.

In metastatic cancer, the degree of heterogeneity of the tumor microenvironment (TME) and its molecular underpinnings remain largely unstudied. To characterize the tumor-immune interface at baseline and during neoadjuvant chemotherapy (NACT) in high-grade serous ovarian cancer (HGSOC), we performed immunogenomic analysis of treatment-naive and paired samples from before and after treatment with chemotherapy. In treatment-naive HGSOC, we found that immune-cell-excluded and inflammatory microenvironments coexist within the same individuals and within the same tumor sites, indicating ubiquitous variability in immune cell infiltration. Analysis of TME cell composition, DNA copy number, mutations and gene expression showed that immune cell exclusion was associated with amplification of Myc target genes and increased expression of canonical Wnt signaling in treatment-naive HGSOC. Following NACT, increased natural killer (NK) cell infiltration and oligoclonal expansion of T cells were detected. We demonstrate that the tumor-immune microenvironment of advanced HGSOC is intrinsically heterogeneous and that chemotherapy induces local immune activation, suggesting that chemotherapy can potentiate the immunogenicity of immune-excluded HGSOC tumors.

Lack of detectable neoantigen depletion signals in the untreated cancer genome.

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.

Comprehensive Benchmarking and Integration of Tumor Microenvironment Cell Estimation Methods.

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.

UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma.

Although clonal neo-antigen burden is associated with improved response to immune therapy, the functional basis for this remains unclear. Here we study this question in a novel controlled mouse melanoma model that enables us to explore the effects of intra-tumor heterogeneity (ITH) on tumor aggressiveness and immunity independent of tumor mutational burden. Induction of UVB-derived mutations yields highly aggressive tumors with decreased anti-tumor activity. However, single-cell-derived tumors with reduced ITH are swiftly rejected. Their rejection is accompanied by increased T cell reactivity and a less suppressive microenvironment. Using phylogenetic analyses and mixing experiments of single-cell clones, we dissect two characteristics of ITH: the number of clones forming the tumor and their clonal diversity. Our analysis of melanoma patient tumor data recapitulates our results in terms of overall survival and response to immune checkpoint therapy. These findings highlight the importance of clonal mutations in robust immune surveillance and the need to quantify patient ITH to determine the response to checkpoint blockade.

Centriolar satellites are acentriolar assemblies of centrosomal proteins.

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.

Mutational Analysis Identifies Therapeutic Biomarkers in Inflammatory Bowel Disease-Associated Colorectal Cancers.

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.

Heterogeneous Tumor-Immune Microenvironments among Differentially Growing Metastases in an Ovarian Cancer Patient.

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+ and CD4+ T cells and exhibited oligoclonal expansion of specific T cell subsets. We also detected CD8+ T cell reactivity against predicted neoepitopes after isolation of cells from a blood sample taken almost 3 years after the tumors were resected. These findings suggest that multiple distinct tumor immune microenvironments co-exist within a single individual and may explain in part the heterogeneous fates of metastatic lesions often observed in the clinic post-therapy. VIDEO ABSTRACT.

Integrin-α10 Dependency Identifies RAC and RICTOR as Therapeutic Targets in High-Grade Myxofibrosarcoma.

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.

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.

MutationAligner: a resource of recurrent mutation hotspots in protein domains in cancer.

The MutationAligner web resource, available at http://www.mutationaligner.org, enables discovery and exploration of somatic mutation hotspots identified in protein domains in currently (mid-2015) more than 5000 cancer patient samples across 22 different tumor types. Using multiple sequence alignments of protein domains in the human genome, we extend the principle of recurrence analysis by aggregating mutations in homologous positions across sets of paralogous genes. Protein domain analysis enhances the statistical power to detect cancer-relevant mutations and links mutations to the specific biological functions encoded in domains. We illustrate how the MutationAligner database and interactive web tool can be used to explore, visualize and analyze mutation hotspots in protein domains across genes and tumor types. We believe that MutationAligner will be an important resource for the cancer research community by providing detailed clues for the functional importance of particular mutations, as well as for the design of functional genomics experiments and for decision support in precision medicine. MutationAligner is slated to be periodically updated to incorporate additional analyses and new data from cancer genomics projects.

Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer.

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.

Friends not foes: CTLA-4 blockade and mTOR inhibition cooperate during CD8+ T cell priming to promote memory formation and metabolic readiness.

During primary Ag encounter, T cells receive numerous positive and negative signals that control their proliferation, function, and differentiation, but how these signals are integrated to modulate T cell memory has not been fully characterized. In these studies, we demonstrate that combining seemingly opposite signals, CTLA-4 blockade and rapamycin-mediated mammalian target of rapamycin inhibition, during in vivo T cell priming leads to both an increase in the frequency of memory CD8(+) T cells and improved memory responses to tumors and bacterial challenges. This enhanced efficacy corresponds to increased early expansion and memory precursor differentiation of CD8(+) T cells and increased mitochondrial biogenesis and spare respiratory capacity in memory CD8(+) T cells in mice treated with anti-CTLA-4 and rapamycin during immunization. Collectively, these results reveal that mammalian target of rapamycin inhibition cooperates with rather than antagonizes blockade of CTLA-4, promoting unrestrained effector function and proliferation, and an optimal metabolic program for CD8(+) T cell memory.

Pan-Cancer Analysis of Mutation Hotspots in Protein Domains.

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.