ARID1A mutations confer intrinsic and acquired resistance to cetuximab treatment in colorectal cancer.

Most colorectal (CRC) tumors are dependent on EGFR/KRAS/BRAF/MAPK signaling activation. ARID1A is an epigenetic regulator mutated in approximately 5% of non-hypermutated CRC tumors. Here we show that anti-EGFR but not anti-VEGF treatment enriches for emerging ARID1A mutations in CRC patients. In addition, we find that patients with ARID1A mutations, at baseline, are associated with worse outcome when treated with cetuximab- but not bevacizumab-containing therapies; thus, this suggests that ARID1A mutations may provide both an acquired and intrinsic mechanism of resistance to anti-EGFR therapies. We find that, ARID1A and EGFR-pathway genetic alterations are mutually exclusive across lung and colorectal cancers, further supporting a functional connection between these pathways. Our results not only suggest that ARID1A could be potentially used as a predictive biomarker for cetuximab treatment decisions but also provide a rationale for exploring therapeutic MAPK inhibition in an unexpected but genetically defined segment of CRC patients.

Transcriptomic profiling of adjuvant colorectal cancer identifies three key prognostic biological processes and a disease specific role for granzyme B.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer-related deaths, with a 5% 5-year survival rate for metastatic disease, yet with limited therapeutic advancements due to insufficient understanding of and inability to accurately capture high-risk CRC patients who are most likely to recur. We aimed to improve high-risk classification by identifying biological pathways associated with outcome in adjuvant stage II/III CRC. METHODS AND FINDINGS: We included 1062 patients with stage III or high-risk stage II colon carcinoma from the prospective three-arm randomized phase 3 AVANT trial, and performed expression profiling to identify a prognostic signature. Data from validation cohort GSE39582, The Cancer Genome Atlas, and cell lines were used to further validate the prognostic biology. Our retrospective analysis of the adjuvant AVANT trial uncovered a prognostic signature capturing three biological functions-stromal, proliferative and immune-that outperformed the Consensus Molecular Subtypes (CMS) and recurrence prediction signatures like Oncotype Dx in an independent cohort. Importantly, within the immune component, high granzyme B (GZMB) expression had a significant prognostic impact while other individual T-effector genes were less or not prognostic. In addition, we found GZMB to be endogenously expressed in CMS2 tumor cells and to be prognostic in a T cell independent fashion. A limitation of our study is that these results, although robust and derived from a large dataset, still need to be clinically validated in a prospective study. CONCLUSIONS: This work furthers our understanding of the underlying biology that propagates stage II/III CRC disease progression and provides scientific rationale for future high-risk stratification and targeted treatment evaluation in biomarker defined subpopulations of resectable high-risk CRC. Our results also shed light on an alternative GZMB source with context-specific implications on the disease's unique biology.

Indication-specific tumor evolution and its impact on neoantigen targeting and biomarkers for individualized cancer immunotherapies.

BACKGROUND: Individualized neoantigen-specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. It is assumed that clonal neoantigens are preferred targets for immunotherapy, but the distributions of clonal neoantigens are not well characterized across cancer types. METHODS: We combined multiregion sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients in order to characterize their globally clonal neoantigen content and factors that would impact neoantigen targeting. RESULTS: Branching evolution in colorectal cancer and renal cell carcinoma led to fewer clonal neoantigens and to clade-specific neoantigens (those shared across a subset of tumor regions but not fully clonal), with the latter not being readily distinguishable in single tumor samples. In colorectal, renal, and bladder cancer, most tumors had few globally clonal neoantigens. Prioritizing mutations with higher purity-adjusted and ploidy-adjusted variant allele frequency enriched for globally clonal neoantigens (those found in all tumor regions), whereas estimated cancer cell fraction derived from clustering-based tools, surprisingly, did not. Neoantigen quality was associated with loss of neoantigen expression in the bladder cancer case, and HLA-allele loss was observed in the renal and non-small cell lung cancer cases. CONCLUSIONS: We show that tumor type, multilesion sampling, neoantigen expression, and HLA allele retention are important factors for iNeST targeting and patient selection, and may also be important factors to consider in the development of biomarker strategies.

Single-cell dissection of cellular components and interactions shaping the tumor immune phenotypes in ovarian cancer.

Distinct T cell infiltration patterns, i.e., immune infiltrated, excluded, and desert, result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these tumor immune phenotypes remain elusive. Here, we provide a high-resolution dissection of the entire tumor ecosystem through single-cell RNA-sequencing analysis of 15 ovarian tumors. Immune-desert tumors are characterized by unique tumor cell-intrinsic features, including metabolic pathways and low antigen presentation, and an enrichment of monocytes and immature macrophages. Immune-infiltrated and -excluded tumors differ markedly in their T cell composition and fibroblast subsets. Furthermore, our study reveals chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumor cell-T cell cross talk via CXCL16-CXCR6 and stromal-immune cell cross talk via CXCL12/14-CXCR4. Our data highlight potential molecular mechanisms that shape the tumor immune phenotypes and may inform therapeutic strategies to improve clinical benefit from cancer immunotherapies.

Cross-tissue organization of the fibroblast lineage.

Fibroblasts are non-haematopoietic structural cells that define the architecture of organs, support the homeostasis of tissue-resident cells and have key roles in fibrosis, cancer, autoimmunity and wound healing1. Recent studies have described fibroblast heterogeneity within individual tissues1. However, the field lacks a characterization of fibroblasts at single-cell resolution across tissues in healthy and diseased organs. Here we constructed fibroblast atlases by integrating single-cell transcriptomic data from about 230,000 fibroblasts across 17 tissues, 50 datasets, 11 disease states and 2 species. Mouse fibroblast atlases and a DptIRESCreERT2 knock-in mouse identified two universal fibroblast transcriptional subtypes across tissues. Our analysis suggests that these cells can serve as a reservoir that can yield specialized fibroblasts across a broad range of steady-state tissues and activated fibroblasts in disease. Comparison to an atlas of human fibroblasts from perturbed states showed that fibroblast transcriptional states are conserved between mice and humans, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. In summary, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution has identified key organizing principles of the fibroblast lineage in health and disease.

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

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

Activation of NF-κB and p300/CBP potentiates cancer chemoimmunotherapy through induction of MHC-I antigen presentation.

Many cancers evade immune rejection by suppressing major histocompatibility class I (MHC-I) antigen processing and presentation (AgPP). Such cancers do not respond to immune checkpoint inhibitor therapies (ICIT) such as PD-1/PD-L1 [PD-(L)1] blockade. Certain chemotherapeutic drugs augment tumor control by PD-(L)1 inhibitors through potentiation of T-cell priming but whether and how chemotherapy enhances MHC-I-dependent cancer cell recognition by cytotoxic T cells (CTLs) is not entirely clear. We now show that the lysine acetyl transferases p300/CREB binding protein (CBP) control MHC-I AgPPM expression and neoantigen amounts in human cancers. Moreover, we found that two distinct DNA damaging drugs, the platinoid oxaliplatin and the topoisomerase inhibitor mitoxantrone, strongly up-regulate MHC-I AgPP in a manner dependent on activation of nuclear factor kappa B (NF-κB), p300/CBP, and other transcription factors, but independently of autocrine IFNγ signaling. Accordingly, NF-κB and p300 ablations prevent chemotherapy-induced MHC-I AgPP and abrogate rejection of low MHC-I-expressing tumors by reinvigorated CD8+ CTLs. Drugs like oxaliplatin and mitoxantrone may be used to overcome resistance to PD-(L)1 inhibitors in tumors that had "epigenetically down-regulated," but had not permanently lost MHC-I AgPP activity.

BCL2 Expression in First-Line Diffuse Large B-Cell Lymphoma Identifies a Patient Population With Poor Prognosis.

INTRODUCTION: The prognostic value of B-cell lymphoma 2 (BCL2) expression in de novo diffuse large B-cell lymphoma (DLBCL) treated with immunochemotherapy is of interest to define a target patient population for clinical development of BCL2 inhibitors. We aimed to develop a reproducible immunohistochemistry algorithm and assay to determine BCL2 protein expression and assess the prognostic value of BCL2 in newly diagnosed DLBCL cohorts. PATIENTS AND METHODS: The prospectively defined algorithm incorporated BCL2 staining intensity and percentage of BCL2-positive cells. Functionally relevant cutoffs were based on the sensitivity of lymphoma cell lines to venetoclax. This assay was highly reproducible across laboratories. The prognostic impact of BCL2 expression was assessed in DLBCL patients from the phase 3 MAIN (n = 230) and GOYA (n = 366) trials, and a population-based registry (n = 310). RESULTS: Approximately 50% of tumors were BCL2 positive, with a higher frequency in high International Prognostic Index (IPI) and activated B-cell-like DLBCL subgroups. BCL2 expression was associated with poorer progression-free survival in the MAIN study (hazard ratio [HR], 1.66; 95% confidence interval [CI], 0.81-3.40; multivariate Cox regression adjusted for IPI and cell of origin). This trend was confirmed in the GOYA and registry cohorts in adjusted multivariate analyses (GOYA: HR, 1.72; 95% CI, 1.05-2.82; registry: HR, 1.89; 95% CI, 1.29-2.78). Patients with BCL2 immunohistochemistry-positive and IPI-high disease had the poorest prognosis: 3-year progression-free survival rates were 51% (GOYA) and 37% (registry). CONCLUSION: Findings support use of our BCL2 immunohistochemistry scoring system and assay to select patients with BCL2-positive tumors for future studies.

Integrated digital pathology and transcriptome analysis identifies molecular mediators of T-cell exclusion in ovarian cancer.

Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what controls the spatial distribution of T cells in the tumour microenvironment is not well understood. Here we couple digital pathology and transcriptome analysis on a large ovarian tumour cohort and develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFß and activated stroma. Furthermore, we identify TGFß as an important mediator of T cell exclusion. TGFß reduces MHC-I expression in ovarian cancer cells in vitro. TGFß also activates fibroblasts and induces extracellular matrix production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFß might be a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

Development of a gene expression-based prognostic signature for IDH wild-type glioblastoma.

BACKGROUND: We aimed to develop a gene expression-based prognostic signature for isocitrate dehydrogenase (IDH) wild-type glioblastoma using clinical trial datasets representative of glioblastoma clinical trial populations. METHODS: Samples were collected from newly diagnosed patients with IDH wild-type glioblastoma in the ARTE, TAMIGA, EORTC 26101 (referred to as "ATE"), AVAglio, and GLARIUS trials, or treated at UCLA. Transcriptional profiling was achieved with the NanoString gene expression platform. To identify genes prognostic for overall survival (OS), we built an elastic net penalized Cox proportional hazards regression model using the discovery ATE dataset. For validation in independent datasets (AVAglio, GLARIUS, UCLA), we combined elastic net-selected genes into a robust z-score signature (ATE score) to overcome gene expression platform differences between discovery and validation cohorts. RESULTS: NanoString data were available from 512 patients in the ATE dataset. Elastic net identified a prognostic signature of 9 genes (CHEK1, GPR17, IGF2BP3, MGMT, MTHFD1L, PTRH2, SOX11, S100A9, and TFRC). Translating weighted elastic net scores to the ATE score conserved the prognostic value of the genes. The ATE score was prognostic for OS in the ATE dataset (P < 0.0001), as expected, and in the validation cohorts (AVAglio, P < 0.0001; GLARIUS, P = 0.02; UCLA, P = 0.004). The ATE score remained prognostic following adjustment for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and corticosteroid use at baseline. A positive correlation between ATE score and proneural/proliferative subtypes was observed in patients with MGMT non-methylated promoter status. CONCLUSIONS: The ATE score showed prognostic value and may enable clinical trial stratification for IDH wild-type glioblastoma.

Peripheral T cell expansion predicts tumour infiltration and clinical response.

Despite the resounding clinical success in cancer treatment of antibodies that block the interaction of PD1 with its ligand PDL11, the mechanisms involved remain unknown. A major limitation to understanding the origin and fate of T cells in tumour immunity is the lack of quantitative information on the distribution of individual clonotypes of T cells in patients with cancer. Here, by performing deep single-cell sequencing of RNA and T cell receptors in patients with different types of cancer, we survey the profiles of various populations of T cells and T cell receptors in tumours, normal adjacent tissue, and peripheral blood. We find clear evidence of clonotypic expansion of effector-like T cells not only within the tumour but also in normal adjacent tissue. Patients with gene signatures of such clonotypic expansion respond best to anti-PDL1 therapy. Notably, expanded clonotypes found in the tumour and normal adjacent tissue can also typically be detected in peripheral blood, which suggests a convenient approach to patient identification. Analyses of our data together with several external datasets suggest that intratumoural T cells, especially in responsive patients, are replenished with fresh, non-exhausted replacement cells from sites outside the tumour, suggesting continued activity of the cancer immunity cycle in these patients, the acceleration of which may be associated with clinical response.

Mutation position is an important determinant for predicting cancer neoantigens.

Tumor-specific mutations can generate neoantigens that drive CD8 T cell responses against cancer. Next-generation sequencing and computational methods have been successfully applied to identify mutations and predict neoantigens. However, only a small fraction of predicted neoantigens are immunogenic. Currently, predicted peptide binding affinity for MHC-I is often the major criterion for prioritizing neoantigens, although little progress has been made toward understanding the precise functional relationship between affinity and immunogenicity. We therefore systematically assessed the immunogenicity of peptides containing single amino acid mutations in mouse tumor models and divided them into two classes of immunogenic mutations. The first comprises mutations at a nonanchor residue, for which we find that the predicted absolute binding affinity is predictive of immunogenicity. The second involves mutations at an anchor residue; here, predicted relative affinity (compared with the WT counterpart) is a better predictor. Incorporating these features into an immunogenicity model significantly improves neoantigen ranking. Importantly, these properties of neoantigens are also predictive in human datasets, suggesting that they can be used to prioritize neoantigens for individualized neoantigen-specific immunotherapies.

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

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

Transposable element expression in tumors is associated with immune infiltration and increased antigenicity.

Profound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observe increased expression of over 400 TE subfamilies, of which 262 appear to result from a proximal loss of DNA methylation. The most recurrent TEs are among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent results in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing inflammation and the display of potentially immunogenic neoantigens.

Genomic Alterations Associated with Recurrence and TNBC Subtype in High-Risk Early Breast Cancers.

The identification of early breast cancer patients who may benefit from adjuvant chemotherapy has evolved to include assessment of clinicopathologic features such as tumor size and nodal status, as well as several gene-expression profiles for ER-positive, HER2-negative cancers. However, these tools do not reliably identify patients at the greatest risk of recurrence. The mutation and copy-number landscape of triple-negative breast cancer (TNBC) subtypes defined by gene expression is also largely unknown, and elucidation of this landscape may shed light on novel therapeutic opportunities. The USO01062 phase III clinical trial of standard chemotherapy (with or without capecitabine) enrolled a cohort of putatively high-risk patients based on clinical features, yet only observed a 5-year disease-free survival event rate of 11.6%. In order to uncover genomic aberrations associated with recurrence, a targeted next-generation sequencing panel was used to compare tumor specimens from patients who had a recurrence event with a matched set who did not. The somatic mutation and copy-number alteration landscapes of high-risk early breast cancer patients were characterized and alterations associated with relapse were identified. Tumor mutational burden was evaluated but was not prognostic in this study, nor did it correlate with PDL1 or CD8 gene expression. However, TNBC subtypes had substantial genomic heterogeneity with a distinct pattern of genomic alterations and putative underlying driver mutations. IMPLICATIONS: The present study uncovers a compendium of genomic alterations with utility to more precisely identify high-risk patients for adjuvant trials of novel therapeutic agents.

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

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

APPLICATIONS OF GENETICS, GENOMICS AND BIOINFORMATICS IN DRUG DISCOVERY.

As the impact of genetics, genomics, and bioinformatics on drug discovery has been increasingly recognized, this session of the 2018 Pacific Symposium on Biocomputing (PSB) aims to facilitate scientific discussions between academia and pharmaceutical industry on how to best apply genetics, genomics and bioinformatics to enable drug discovery. The selected papers focus on developing and applying computational approaches to understand drug mechanisms of action and develop drug combination strategies, to enable in silico drug screening, and to further delineate disease pathways for target identification and validation.

High-Throughput and Sensitive Quantification of Circulating Tumor DNA by Microfluidic-Based Multiplex PCR and Next-Generation Sequencing.

Circulating tumor DNA (ctDNA) has potential to serve as a biomarker for noninvasive monitoring of treatment response and disease progression. However, broad clinical applicability of ctDNA has been limited by the low sensitivity, throughput, and patient coverage offered by existing ctDNA detection methods. Herein, we report the adaptation and characterization of the microfluidics multiplex PCR sequencing technology for high-throughput and sensitive quantitation of ctDNA. A multiplex PCR preamplification step was developed and incorporated into the microfluidics multiplex PCR sequencing work flow to enable low-input ctDNA analysis with enhanced sensitivity. An empirical bayesian model was developed to characterize both position and substitution-associated system errors specific to this platform and provided a tailored approach to greatly enhance the confidence and accuracy of variant calling for ctDNA analysis. Clinical validation of this platform for ctDNA mutation detection demonstrated an overall sensitivity of 92% and specificity of 100% when using mutation calls in the matched tumor tissues as a benchmark. Finally, we established an early proof of concept of clinical utility of this ctDNA work flow for monitoring disease progression using clinical trial samples. Our novel ctDNA work flow provides a high-throughput and sensitive platform that can be implemented in clinical trials for mutation detection and disease monitoring from plasma ctDNA.

Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial.

BACKGROUND: First-line chemotherapy for patients with cisplatin-ineligible locally advanced or metastatic urothelial carcinoma is associated with short response duration, poor survival, and high toxicity. This study assessed atezolizumab (anti-programmed death-ligand 1 [PD-L1]) as treatment for metastatic urothelial cancer in cisplatin-ineligible patients. METHODS: For this single-arm, multicentre, phase 2 study, in 47 academic medical centres and community oncology practices in seven countries in North America and Europe, we recruited previously untreated patients with locally advanced or metastatic urothelial cancer who were cisplatin ineligible. Patients were given 1200 mg intravenous atezolizumab every 21 days until progression. The primary endpoint was independently confirmed objective response rate per Response Evaluation Criteria in Solid Tumors version 1.1 (central review), assessed in prespecified subgroups based on PD-L1 expression and in all patients. All participants who received one or more doses of atezolizumab were included in the primary and safety analyses. This study was registered with ClinicalTrials.gov, number NCT02108652. FINDINGS: Between June 9, 2014, and March 30, 2015, we enrolled 123 patients, of whom 119 received one or more doses of atezolizumab. At 17·2 months' median follow-up, the objective response rate was 23% (95% CI 16 to 31), the complete response rate was 9% (n=11), and 19 of 27 responses were ongoing. Median response duration was not reached. Responses occurred across all PD-L1 and poor prognostic factor subgroups. Median progression-free survival was 2·7 months (2·1 to 4·2). Median overall survival was 15·9 months (10·4 to not estimable). Tumour mutation load was associated with response. Treatment-related adverse events that occurred in 10% or more of patients were fatigue (36 [30%] patients), diarrhoea (14 [12%] patients), and pruritus (13 [11%] patients). One treatment-related death (sepsis) occurred. Nine (8%) patients had an adverse event leading to treatment discontinuation. Immune-mediated events occurred in 14 (12%) patients. INTERPRETATION: Atezolizumab showed encouraging durable response rates, survival, and tolerability, supporting its therapeutic use in untreated metastatic urothelial cancer. FUNDING: F Hoffmann-La Roche, Genentech.

Mutation load and an effector T-cell gene signature may distinguish immunologically distinct and clinically relevant lymphoma subsets.

Identifying follicular lymphoma (FL) patients with preexisting antitumor immunity will inform precision medicine strategies for novel cancer immunotherapies. Using clinical and genomic data from 249 FL patients, we determined the clinical impact of mutation load and an effector T-cell (Teff) gene signature as proxies for the likelihood of a functional immune response. The FL mutation load estimate varied between 0 and 33 mutations per Mb (median, 6.6), and 92% of FL patients with a high mutation load had high Teff gene expression (P = .001). The mutation load was associated with a benefit from rituximab maintenance: FL patients with low mutation loads experienced a profound benefit from rituximab maintenance (hazard ratio [HR], 0.29; 95% confidence interval [CI], 0.15-0.54; P < .001). The Teff gene signature was prognostic as a continuous predictor (P = .008), and was used to separate FL patients into 2 groups, an "inflamed" subset (Teff-high; n = 74) and an "uninflamed" subset (Teff-low; n = 75), with longer progression-free survival (PFS) in the inflamed FL subset (PFS HR, 0.39; 95% CI, 0.21-0.70; P = .002). Furthermore, the subset of inflamed FL tumors demonstrated high expression of other T-cell signatures and counterregulatory genes, which also correlate with PFS. Mutation load and Teff gene expression may help identify immunologically distinct lymphoma subsets relevant for modern immunotherapies.