Diana Miao

Genomic correlates of response to CTLA-4 blockade in metastatic melanoma

Is cancer immunotherapy a private affair? Immune checkpoint blockade, a relatively new cancer treatment, substantially extends the survival of a subset of patients. Previous work has shown that patients whose tumors harbor the largest number of mutations—and thus produce a large number of “neoantigens” recognized as foreign by the immune system—are most likely to benefit. Expanding on these earlier studies, Van Allen et al. studied over 100 patients with melanoma and found a similar correlation (see the Perspective by Gubin and Schreiber). There was no evidence, however, that specific neoantigen sequences were shared by patients who responded. Science, this issue p. 207, see also p. 158 Melanoma patients who respond to immunotherapy do not appear to share common tumor neoantigens. [Also see Perspective by Gubin and Schreiber ] Monoclonal antibodies directed against cytotoxic T lymphocyte–associated antigen-4 (CTLA-4), such as ipilimumab, yield considerable clinical benefit for patients with metastatic melanoma by inhibiting immune checkpoint activity, but clinical predictors of response to these therapies remain incompletely characterized. To investigate the roles of tumor-specific neoantigens and alterations in the tumor microenvironment in the response to ipilimumab, we analyzed whole exomes from pretreatment melanoma tumor biopsies and matching germline tissue samples from 110 patients. For 40 of these patients, we also obtained and analyzed transcriptome data from the pretreatment tumor samples. Overall mutational load, neoantigen load, and expression of cytolytic markers in the immune microenvironment were significantly associated with clinical benefit. However, no recurrent neoantigen peptide sequences predicted responder patient populations. Thus, detailed integrated molecular characterization of large patient cohorts may be needed to identify robust determinants of response and resistance to immune checkpoint inhibitors.

Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade

The cellular ancestry of tumor antigens One contributing factor in antitumor immunity is the repertoire of neoantigens created by genetic mutations within tumor cells. Like the corresponding mutations, these neoantigens show intratumoral heterogeneity. Some are present in all tumor cells (clonal), and others are present in only a fraction of cells (subclonal). In a study of lung cancer and melanoma, McGranahan et al. found that a high burden of clonal tumor neoantigens correlated with improved patient survival, an increased presence of tumor-infiltrating lymphocytes, and a durable response to immunotherapy. Science, this issue p. 1463 Analysis of the cellular ancestry of tumor neoantigens can predict which are most likely to induce an immune response. As tumors grow, they acquire mutations, some of which create neoantigens that influence the response of patients to immune checkpoint inhibitors. We explored the impact of neoantigen intratumor heterogeneity (ITH) on antitumor immunity. Through integrated analysis of ITH and neoantigen burden, we demonstrate a relationship between clonal neoantigen burden and overall survival in primary lung adenocarcinomas. CD8+ tumor-infiltrating lymphocytes reactive to clonal neoantigens were identified in early-stage non–small cell lung cancer and expressed high levels of PD-1. Sensitivity to PD-1 and CTLA-4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumors enriched for clonal neoantigens. T cells recognizing clonal neoantigens were detectable in patients with durable clinical benefit. Cytotoxic chemotherapy–induced subclonal neoantigens, contributing to an increased mutational load, were enriched in certain poor responders. These data suggest that neoantigen heterogeneity may influence immune surveillance and support therapeutic developments targeting clonal neoantigens.

In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target

Immunotherapy with PD-1 checkpoint blockade is effective in only a minority of patients with cancer, suggesting that additional treatment strategies are needed. Here we use a pooled in vivo genetic screening approach using CRISPR–Cas9 genome editing in transplantable tumours in mice treated with immunotherapy to discover previously undescribed immunotherapy targets. We tested 2,368 genes expressed by melanoma cells to identify those that synergize with or cause resistance to checkpoint blockade. We recovered the known immune evasion molecules PD-L1 and CD47, and confirmed that defects in interferon-γ signalling caused resistance to immunotherapy. Tumours were sensitized to immunotherapy by deletion of genes involved in several diverse pathways, including NF-κB signalling, antigen presentation and the unfolded protein response. In addition, deletion of the protein tyrosine phosphatase PTPN2 in tumour cells increased the efficacy of immunotherapy by enhancing interferon-γ-mediated effects on antigen presentation and growth suppression. In vivo genetic screens in tumour models can identify new immunotherapy targets in unanticipated pathways.

Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures.

BackgroundTumor-infiltrating immune cells have been linked to prognosis and response to immunotherapy; however, the levels of distinct immune cell subsets and the signals that draw them into a tumor, such as the expression of antigen presenting machinery genes, remain poorly characterized. Here, we employ a gene expression-based computational method to profile the infiltration levels of 24 immune cell populations in 19 cancer types.ResultsWe compare cancer types using an immune infiltration score and a T cell infiltration score and find that clear cell renal cell carcinoma (ccRCC) is among the highest for both scores. Using immune infiltration profiles as well as transcriptomic and proteomic datasets, we characterize three groups of ccRCC tumors: T cell enriched, heterogeneously infiltrated, and non-infiltrated. We observe that the immunogenicity of ccRCC tumors cannot be explained by mutation load or neo-antigen load, but is highly correlated with MHC class I antigen presenting machinery expression (APM). We explore the prognostic value of distinct T cell subsets and show in two cohorts that Th17 cells and CD8+ T/Treg ratio are associated with improved survival, whereas Th2 cells and Tregs are associated with negative outcomes. Investigation of the association of immune infiltration patterns with the subclonal architecture of tumors shows that both APM and T cell levels are negatively associated with subclone number.ConclusionsOur analysis sheds light on the immune infiltration patterns of 19 human cancers and unravels mRNA signatures with prognostic utility and immunotherapeutic biomarker potential in ccRCC.Tumor-infiltrating immune cells have been linked to prognosis and response to immunotherapy; however, the levels of distinct immune cell subsets and the signals that draw them into a tumor, such as the expression of antigen presenting machinery genes, remain poorly characterized. Here, we employ a gene expression-based computational method to profile the infiltration levels of 24 immune cell populations in 19 cancer types. We compare cancer types using an immune infiltration score and a T cell infiltration score and find that clear cell renal cell carcinoma (ccRCC) is among the highest for both scores. Using immune infiltration profiles as well as transcriptomic and proteomic datasets, we characterize three groups of ccRCC tumors: T cell enriched, heterogeneously infiltrated, and non-infiltrated. We observe that the immunogenicity of ccRCC tumors cannot be explained by mutation load or neo-antigen load, but is highly correlated with MHC class I antigen presenting machinery expression (APM). We explore the prognostic value of distinct T cell subsets and show in two cohorts that Th17 cells and CD8+ T/Treg ratio are associated with improved survival, whereas Th2 cells and Tregs are associated with negative outcomes. Investigation of the association of immune infiltration patterns with the subclonal architecture of tumors shows that both APM and T cell levels are negatively associated with subclone number. Our analysis sheds light on the immune infiltration patterns of 19 human cancers and unravels mRNA signatures with prognostic utility and immunotherapeutic biomarker potential in ccRCC.

Loss of PTEN Is Associated with Resistance to Anti-PD-1 Checkpoint Blockade Therapy in Metastatic Uterine Leiomyosarcoma

SUMMARY Response to immune checkpoint blockade in mesenchymal tumors is poorly characterized, but immunogenomic dissection of these cancers could inform immunotherapy mediators. We identified a treatment‐naive patient who has metastatic uterine leiomyosarcoma and has experienced complete tumor remission for >2 years on anti‐PD‐1 (pembrolizumab) monotherapy. We analyzed the primary tumor, the sole treatment‐resistant metastasis, and germline tissue to explore mechanisms of immunotherapy sensitivity and resistance. Both tumors stained diffusely for PD‐L2 and showed sparse PD‐L1 staining. PD‐1+ cell infiltration significantly decreased in the resistant tumor (p = 0.039). Genomically, the treatment‐resistant tumor uniquely harbored biallelic PTEN loss and had reduced expression of two neoantigens that demonstrated strong immunoreactivity with patient T cells in vitro, suggesting long‐lasting immunological memory. In this near‐complete response to PD‐1 blockade in a mesenchymal tumor, we identified PTEN mutations and reduced expression of genes encoding neoantigens as potential mediators of resistance to immune checkpoint therapy. Graphical Abstract Figure. No Caption available. HighlightsAnti‐PD‐1 monotherapy can induce complete tumor remission in uterine leiomyosarcomaLongitudinal profiling of patient tumors reveals response and resistance mechanismsTumor neoantigens are patient specific and can induce long‐term immunoreactivityBiallelic PTEN loss is associated with resistance to PD‐1 blockade in sarcoma &NA; George et al. report an exceptional responder to anti‐PD‐1 monotherapy in uterine leiomyosarcoma and propose mediators of treatment sensitivity and resistance. Neoantigen‐directed immunoreactivity was associated with sensitivity to anti‐PD‐1 monotherapy, whereas resistance was associated with reduction in neoantigen expression consistent with immune evasion, and biallelic PTEN loss was associated with induction of an immunosuppressive microenvironment.

The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine

BackgroundThe diversity of clinical tumor profiling approaches (small panels to whole exomes with matched or unmatched germline analysis) may engender uncertainty about their benefits and liabilities, particularly in light of reported germline false positives in tumor-only profiling and use of global mutational and/or neoantigen data. The goal of this study was to determine the impact of genomic analysis strategies on error rates and data interpretation across contexts and ancestries.MethodsWe modeled common tumor profiling modalities—large (n = 300 genes), medium (n = 48 genes), and small (n = 15 genes) panels—using clinical whole exomes (WES) from 157 patients with lung or colon adenocarcinoma. We created a tumor-only analysis algorithm to assess germline false positive rates, the impact of patient ancestry on tumor-only results, and neoantigen detection.ResultsAfter optimizing a germline filtering strategy, the germline false positive rate with tumor-only large panel sequencing was 14 % (144/1012 variants). For patients whose tumor-only results underwent molecular pathologist review (n = 91), 50/54 (93 %) false positives were correctly interpreted as uncertain variants. Increased germline false positives were observed in tumor-only sequencing of non-European compared with European ancestry patients (p < 0.001; Fisher’s exact) when basic germline filtering approaches were used; however, the ExAC database (60,706 germline exomes) mitigated this disparity (p = 0.53). Matched and unmatched large panel mutational load correlated with WES mutational load (r2 = 0.99 and 0.93, respectively; p < 0.001). Neoantigen load also correlated (r2 = 0.80; p < 0.001), though WES identified a broader spectrum of neoantigens. Small panels did not predict mutational or neoantigen load.ConclusionsLarge tumor-only targeted panels are sufficient for most somatic variant identification and mutational load prediction if paired with expanded germline analysis strategies and molecular pathologist review. Paired germline sequencing reduced overall false positive mutation calls and WES provided the most neoantigens. Without patient-matched germline data, large germline databases are needed to minimize false positive mutation calling and mitigate ethnic disparities.

Somatic Mutations and Neoepitope Homology in Melanomas Treated with CTLA-4 Blockade

This is a reanalysis of data described in Snyder et al., N Eng J Med 2014;371:2189–99, that also provides an open-source tool for comparing epitopes. No predictor of response to anti–CTLA-4 therapy was more accurate than mutation burden. Immune checkpoint inhibitors are promising treatments for patients with a variety of malignancies. Toward understanding the determinants of response to immune checkpoint inhibitors, it was previously demonstrated that the presence of somatic mutations is associated with benefit from checkpoint inhibition. A hypothesis was posited that neoantigen homology to pathogens may in part explain the link between somatic mutations and response. To further examine this hypothesis, we reanalyzed cancer exome data obtained from our previously published study of 64 melanoma patients treated with CTLA-4 blockade and a new dataset of RNA-Seq data from 24 of these patients. We found that the ability to accurately predict patient benefit did not increase as the analysis narrowed from somatic mutation burden, to inclusion of only those mutations predicted to be MHC class I neoantigens, to only including those neoantigens that were expressed or that had homology to pathogens. The only association between somatic mutation burden and response was found when examining samples obtained prior to treatment. Neoantigen and expressed neoantigen burden were also associated with response, but neither was more predictive than somatic mutation burden. Neither the previously described tetrapeptide signature nor an updated method to evaluate neoepitope homology to pathogens was more predictive than mutation burden. Cancer Immunol Res; 5(1); 84–91. ©2016 AACR.

Ex Vivo Profiling of PD-1 Blockade Using Organotypic Tumor Spheroids

Ex vivo systems that incorporate features of the tumor microenvironment and model the dynamic response to immune checkpoint blockade (ICB) may facilitate efforts in precision immuno-oncology and the development of effective combination therapies. Here, we demonstrate the ability to interrogate ex vivo response to ICB using murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). MDOTS/PDOTS isolated from mouse and human tumors retain autologous lymphoid and myeloid cell populations and respond to ICB in short-term three-dimensional microfluidic culture. Response and resistance to ICB was recapitulated using MDOTS derived from established immunocompetent mouse tumor models. MDOTS profiling demonstrated that TBK1/IKKε inhibition enhanced response to PD-1 blockade, which effectively predicted tumor response in vivo Systematic profiling of secreted cytokines in PDOTS captured key features associated with response and resistance to PD-1 blockade. Thus, MDOTS/PDOTS profiling represents a novel platform to evaluate ICB using established murine models as well as clinically relevant patient specimens.Significance: Resistance to PD-1 blockade remains a challenge for many patients, and biomarkers to guide treatment are lacking. Here, we demonstrate feasibility of ex vivo profiling of PD-1 blockade to interrogate the tumor immune microenvironment, develop therapeutic combinations, and facilitate precision immuno-oncology efforts. Cancer Discov; 8(2); 196-215. ©2017 AACR.See related commentary by Balko and Sosman, p. 143See related article by Deng et al., p. 216This article is highlighted in the In This Issue feature, p. 127.

Mutational patterns in chemotherapy resistant muscle-invasive bladder cancer

Despite continued widespread use, the genomic effects of cisplatin-based chemotherapy and implications for subsequent treatment are incompletely characterized. Here, we analyze whole exome sequencing of matched pre- and post-neoadjuvant cisplatin-based chemotherapy primary bladder tumor samples from 30 muscle-invasive bladder cancer patients. We observe no overall increase in tumor mutational burden post-chemotherapy, though a significant proportion of subclonal mutations are unique to the matched pre- or post-treatment tumor, suggesting chemotherapy-induced and/or spatial heterogeneity. We subsequently identify and validate a novel mutational signature in post-treatment tumors consistent with known characteristics of cisplatin damage and repair. We find that post-treatment tumor heterogeneity predicts worse overall survival, and further observe alterations in cell-cycle and immune checkpoint regulation genes in post-treatment tumors. These results provide insight into the clinical and genomic dynamics of tumor evolution with cisplatin-based chemotherapy, suggest mechanisms of clinical resistance, and inform development of clinically relevant biomarkers and trials of combination therapies.The impact of cisplatin-based chemotherapy on tumor genomes is complex. Here, the authors study matched pre- and post-chemotherapy primary samples in muscle-invasive bladder cancer, finding a cisplatin-based mutational signature, and highlighting the impact of intratumor heterogeneity on survival.

Tumor Mutational Load and Immune Parameters across Metastatic Renal Cell Carcinoma Risk Groups

mRCC patients were assessed for mutational load and expression of active tumor microenvironment markers to find correlates with MSKCC risk prognostic classifications. No correlations were found; thus, patients who would benefit most from immunotherapy are not yet identifiable. Patients with metastatic renal cell carcinoma (mRCC) have better overall survival when treated with nivolumab, a cancer immunotherapy that targets the immune checkpoint inhibitor programmed cell death 1 (PD-1), rather than everolimus (a chemical inhibitor of mTOR and immunosuppressant). Poor-risk mRCC patients treated with nivolumab seemed to experience the greatest overall survival benefit, compared with patients with favorable or intermediate risk, in an analysis of the CheckMate-025 trial subgroup of the Memorial Sloan Kettering Cancer Center (MSKCC) prognostic risk groups. Here, we explore whether tumor mutational load and RNA expression of specific immune parameters could be segregated by prognostic MSKCC risk strata and explain the survival seen in the poor-risk group. We queried whole-exome transcriptome data in renal cell carcinoma patients (n = 54) included in The Cancer Genome Atlas who ultimately developed metastatic disease or were diagnosed with metastatic disease at presentation and did not receive immune checkpoint inhibitors. Nonsynonymous mutational load did not differ significantly by the MSKCC risk group, nor was the expression of cytolytic genes—granzyme A and perforin—or selected immune checkpoint molecules different across MSKCC risk groups. In conclusion, this analysis revealed that mutational load and expression of markers of an active tumor microenvironment did not correlate with MSKCC risk prognostic classification in mRCC. Cancer Immunol Res; 4(10); 820–2. ©2016 AACR.