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Whole-exome sequencing of cell-free DNA (cfDNA) could enable comprehensive profiling of tumors from blood but the genome-wide concordance between cfDNA and tumor biopsies is uncertain. Here we report ichorCNA, software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers. In the earliest tested sample for each patient, 34% of patients have ≥10% tumor-derived cfDNA, sufficient for standard coverage whole-exome sequencing. Using whole-exome sequencing, we validate the concordance of clonal somatic mutations (88%), copy number alterations (80%), mutational signatures, and neoantigens between cfDNA and matched tumor biopsies from 41 patients with ≥10% cfDNA tumor content. In summary, we provide methods to identify patients eligible for comprehensive cfDNA profiling, revealing its applicability to many patients, and demonstrate high concordance of cfDNA and metastatic tumor whole-exome sequencing. Identifying the mutational landscape of tumours from cell-free DNA in the blood could help diagnostics in cancer. Here, the authors present ichorCNA, software that quantifies tumour content in cell free DNA, and they demonstrate that cell-free DNA whole-exome sequencing is concordant with metastatic tumour whole-exome sequencing.

Therapeutic blockade of the PD-1/PD-L1 axis is recognized as an effective treatment for numerous cancer types. However, only a subset of patients respond to this treatment, warranting a greater understanding of the biological mechanisms driving immune evasion via PD-1/PD-L1 signaling and other T-cell suppressive pathways. We previously identified a head and neck squamous cell carcinoma with human papillomavirus integration in the PD-L1 locus upstream of the transmembrane domain-encoding region, suggesting expression of a truncated form of PD-L1 (Parfenov et al., Proc Natl Acad Sci USA111(43):15544–15549, 2014). In this study, we extended this observation by performing a computational analysis of 33 other cancer types as well as human cancer cell lines, and identified additional PD-L1 isoforms with an exon 4 enrichment expressed in 20 cancers and human cancer cell lines. We demonstrate that cancer cell lines with high expression levels of exon 4-enriched PD-L1 generate a secreted form of PD-L1. Further biochemical studies of exon 4-enriched PD-L1 demonstrated that this form is secreted and maintains the capacity to bind PD-1 as well as to serve as a negative regulator on T cell function, as measured by inhibition of IL-2 and IFNg secretion. Overall, we have demonstrated that truncated forms of PD-L1 exist in numerous cancer types, and have validated that truncated PD-L1 can be secreted and negatively regulate T cell function.

Deciphering individual cell phenotypes from cell-specific transcriptional processes requires high dimensional single cell RNA sequencing. However, current dimensionality reduction methods aggregate sparse gene information across cells, without directly measuring the relationships that exist between genes. By performing dimensionality reduction with respect to gene co-expression, low-dimensional features can model these gene-specific relationships and leverage shared signal to overcome sparsity. We describe GeneVector, a scalable framework for dimensionality reduction implemented as a vector space model using mutual information between gene expression. Unlike other methods, including principal component analysis and variational autoencoders, GeneVector uses latent space arithmetic in a lower dimensional gene embedding to identify transcriptional programs and classify cell types. In this work, we show in four single cell RNA-seq datasets that GeneVector was able to capture phenotype-specific pathways, perform batch effect correction, interactively annotate cell types, and identify pathway variation with treatment over time. In single-cell RNA-seq analyses, it would be critical to measure the relationships between genes. Here, the authors develop a framework for single-cell dimensionality reduction that incorporates gene-specific relationships - GeneVector -, and use it for tasks such as annotating cell types and analysing pathway variation after treatment.

Within the tumour microenvironment, CD4 + T cells can promote or suppress antitumour responses through the recognition of antigens presented by human leukocyte antigen (HLA) class II molecules 1 , 2 , but how cancers co-opt these physiologic processes to achieve immune evasion remains incompletely understood. Here we performed in-depth analysis of the phenotype and tumour specificity of CD4 + T cells infiltrating human melanoma specimens, finding that exhausted cytotoxic CD4 + T cells could be directly induced by melanoma cells through recognition of HLA class II-restricted neoantigens, and also HLA class I-restricted tumour-associated antigens. CD4 + T regulatory (T Reg ) cells could be indirectly elicited through presentation of tumour antigens via antigen-presenting cells. Notably, numerous tumour-reactive CD4 + T Reg clones were stimulated directly by HLA class II-positive melanoma and demonstrated specificity for melanoma neoantigens. This phenomenon was observed in the presence of an extremely high tumour neoantigen load, which we confirmed to be associated with HLA class II positivity through the analysis of 116 melanoma specimens. Our data reveal the landscape of infiltrating CD4 + T cells in melanoma and point to the presentation of HLA class II-restricted neoantigens and direct engagement of immunosuppressive CD4 + T Reg cells as a mechanism of immune evasion that is favoured in HLA class II-positive melanoma. A survey of the CD4 + T cells in human melanomas indicates that immune evasion is mediated through direct stimulation of neoantigen-specific tumour-reactive regulatory T cells by HLA class II-positive melanoma cells.

The immune system can eliminate tumors, but checkpoints enable immune escape. Here, we identify immune evasion mechanisms using genome-scale in vivo CRISPR screens across cancer models treated with immune checkpoint blockade (ICB). We identify immune evasion genes and important immune inhibitory checkpoints conserved across cancers, including the non-classical major histocompatibility complex class I (MHC class I) molecule Qa-1b/HLA-E. Surprisingly, loss of tumor interferon-γ (IFNγ) signaling sensitizes many models to immunity. The immune inhibitory effects of tumor IFN sensing are mediated through two mechanisms. First, tumor upregulation of classical MHC class I inhibits natural killer cells. Second, IFN-induced expression of Qa-1b inhibits CD8+ T cells via the NKG2A/CD94 receptor, which is induced by ICB. Finally, we show that strong IFN signatures are associated with poor response to ICB in individuals with renal cell carcinoma or melanoma. This study reveals that IFN-mediated upregulation of classical and non-classical MHC class I inhibitory checkpoints can facilitate immune escape.Here, the authors use genome-scale in vivo CRISPR screens to look at immune evasion mechanisms across cancer models, showing that IFN-mediated upregulation of classical and non-classical MHC class I inhibitory checkpoints facilitate immune escape.

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts. Genomic and transcriptomic analysis of 393 non-small cell lung cancer patients treated with checkpoint inhibitors identifies molecular features associated with response.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular ‘immunity hubs’ defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7 + PD-1 + CD8 + T cells, activated CCR7 + LAMP3 + dendritic cells and CCL19 + fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10 + macrophages and TCF7 − CD8 + T cells as well as between mature regulatory dendritic cells and TCF7 + CD4 + and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes. The spatial organization of cells in solid tumors is considered to be important for immune response and response to therapy. Here the authors use multiomics including spatial transcriptomics of human lung tumors prior to patients being treated and show among other things an association of stem-immunity hubs rich in stem-like CD8 + T cells with positive response to anti-PD-1 therapy.

Whole-exome sequencing and analysis of 115 cervical carcinoma–normal paired samples, in addition to transcriptome and whole-genome sequencing for a subset of these tumours, reveal novel genes mutated at significant levels within this cohort and provide evidence that HPV integration is a common mechanism for target gene overexpression; results also compare mutational landscapes between squamous cell carcinomas and adenocarcinomas. A genomic survey of cervical cancer To provide an overview of the genomic aberrations that contribute to cervical cancer these authors performed whole-exome sequencing and analysis of 115 cervical cancer–normal pairs, transcriptome sequences of 79 cervical carcinomas and whole-genomes from 14 cervical cancer–normal pairs. Analyses identify MAPK1 , HLA-B and ELF3 as novel significantly mutated genes and provide evidence that human papilloma virus integration is a common mechanism for target gene overexpression in cervical cancer. The results also provide a comparison of the mutational landscapes of squamous cell carcinomas and adenocarcinomas. Cervical cancer is responsible for 10–15% of cancer-related deaths in women worldwide 1 , 2 . The aetiological role of infection with high-risk human papilloma viruses (HPVs) in cervical carcinomas is well established 3 . Previous studies have also implicated somatic mutations in PIK3CA , PTEN , TP53 , STK11 and KRAS 4 , 5 , 6 , 7 as well as several copy-number alterations in the pathogenesis of cervical carcinomas 8 , 9 . Here we report whole-exome sequencing analysis of 115 cervical carcinoma–normal paired samples, transcriptome sequencing of 79 cases and whole-genome sequencing of 14 tumour–normal pairs. Previously unknown somatic mutations in 79 primary squamous cell carcinomas include recurrent E322K substitutions in the MAPK1 gene (8%), inactivating mutations in the HLA-B gene (9%), and mutations in EP300 (16%), FBXW7 (15%), NFE2L2 (4%), TP53 (5%) and ERBB2 (6%). We also observe somatic ELF3 (13%) and CBFB (8%) mutations in 24 adenocarcinomas. Squamous cell carcinomas have higher frequencies of somatic nucleotide substitutions occurring at cytosines preceded by thymines (Tp*C sites) than adenocarcinomas. Gene expression levels at HPV integration sites were statistically significantly higher in tumours with HPV integration compared with expression of the same genes in tumours without viral integration at the same site. These data demonstrate several recurrent genomic alterations in cervical carcinomas that suggest new strategies to combat this disease.

Adenocarcinoma in situ and minimally invasive adenocarcinoma are the pre-invasive forms of lung adenocarcinoma. The genomic and immune profiles of these lesions are poorly understood. Here we report exome and transcriptome sequencing of 98 lung adenocarcinoma precursor lesions and 99 invasive adenocarcinomas. We have identified EGFR , RBM10 , BRAF , ERBB2 , TP53 , KRAS , MAP2K1 and MET as significantly mutated genes in the pre/minimally invasive group. Classes of genome alterations that increase in frequency during the progression to malignancy are revealed. These include mutations in TP53 , arm-level copy number alterations, and HLA loss of heterozygosity. Immune infiltration is correlated with copy number alterations of chromosome arm 6p, suggesting a link between arm-level events and the tumor immune environment. The genomic and immune landscape of pre-invasive lung adenocarcinoma is poorly understood. Here, the authors perform exome and transcriptome sequencing on precursor legions and invasive lung adenocarcinomas, identifying recurrently mutated genes in pre/minimally invasive cases, and arm level alteration events linked to immune infiltration.

To systematically define molecular features in human tumor cells that determine their degree of sensitivity to human allogeneic natural killer (NK) cells, we quantified the NK cell responsiveness of hundreds of molecularly annotated ‘DNA-barcoded’ solid tumor cell lines in multiplexed format and applied genome-scale CRISPR-based gene-editing screens in several solid tumor cell lines, to functionally interrogate which genes in tumor cells regulate the response to NK cells. In these orthogonal studies, NK cell–sensitive tumor cells tend to exhibit ‘mesenchymal-like’ transcriptional programs; high transcriptional signature for chromatin remodeling complexes; high levels of B7-H6 ( NCR3LG1 ); and low levels of HLA-E /antigen presentation genes. Importantly, transcriptional signatures of NK cell–sensitive tumor cells correlate with immune checkpoint inhibitor (ICI) resistance in clinical samples. This study provides a comprehensive map of mechanisms regulating tumor cell responses to NK cells, with implications for future biomarker-driven applications of NK cell immunotherapies. The use of natural killer (NK) cells in immunotherapy as an alternative to allogeneic T cells is gaining ground. Here, two genome-scale high-throughput platforms are used to identify genes that modulate the sensitivity of multiple solid tumor cell lines to NK-mediated killing.