Despite impressive durable responses, immune checkpoint inhibitors do not provide a long-term benefit to the majority of patients with cancer. Understanding genomic correlates of response and ...resistance to checkpoint blockade may enhance benefits for patients with cancer by elucidating biomarkers for patient stratification and resistance mechanisms for therapeutic targeting. Here we review emerging genomic markers of checkpoint blockade response, including those related to neoantigens, antigen presentation, DNA repair, and oncogenic pathways. Compelling evidence also points to a role for T cell functionality, checkpoint regulators, chromatin modifiers, and copy-number alterations in mediating selective response to immune checkpoint blockade. Ultimately, efforts to contextualize genomic correlates of response into the larger understanding of tumor immune biology will build a foundation for the development of novel biomarkers and therapies to overcome resistance to checkpoint blockade.
PD-1 blockade has transformed the management of advanced clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of the PD-1 response remain incompletely elucidated. Here, we analyzed ...592 tumors from patients with advanced ccRCC enrolled in prospective clinical trials of treatment with PD-1 blockade by whole-exome and RNA sequencing, integrated with immunofluorescence analysis, to uncover the immunogenomic determinants of the therapeutic response. Although conventional genomic markers (such as tumor mutation burden and neoantigen load) and the degree of CD8
T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations associated with response or resistance to PD-1 blockade. These advanced ccRCC tumors were highly CD8
T cell infiltrated, with only 27% having a non-infiltrated phenotype. Our analysis revealed that infiltrated tumors are depleted of favorable PBRM1 mutations and enriched for unfavorable chromosomal losses of 9p21.3, as compared with non-infiltrated tumors, demonstrating how the potential interplay of immunophenotypes with somatic alterations impacts therapeutic efficacy.
The management of advanced-stage renal cell carcinoma (RCC) has been transformed by the development of immune-checkpoint inhibitors (ICIs). Nonetheless, most patients do not derive durable clinical ...benefit from these agents. Importantly, unlike other immunotherapy-responsive solid tumours, most RCCs have only a moderate mutational burden, and paradoxically, high levels of tumour CD8
T cell infiltration are associated with a worse prognosis in patients with this disease. Building on the successes of antibodies targeting the PD-1 and CTLA4 immune checkpoints, multiple innovative immunotherapies are now in clinical development for the treatment of patients with RCC, including ICIs with novel targets, co-stimulatory pathway agonists, modified cytokines, metabolic pathway modulators, cell therapies and therapeutic vaccines. However, the successful development of such novel immune-based treatments and of immunotherapy-based combinations will require a disease-specific framework that incorporates a deep understanding of RCC immunobiology. In this Review, using the structure provided by the well-described cancer-immunity cycle, we outline the key steps required for a successful antitumour immune response in the context of RCC, and describe the development of promising new immunotherapies within the context of this framework. With this approach, we summarize and analyse the most encouraging targets of novel immune-based therapies within the RCC microenvironment, and review the landscape of emerging antigen-directed therapies for this disease.
Immune checkpoint inhibitors targeting the programmed cell death 1 receptor (PD-1) improve survival in a subset of patients with clear cell renal cell carcinoma (ccRCC). To identify genomic ...alterations in ccRCC that correlate with response to anti-PD-1 monotherapy, we performed whole-exome sequencing of metastatic ccRCC from 35 patients. We found that clinical benefit was associated with loss-of-function mutations in the
gene (
= 0.012), which encodes a subunit of the PBAF switch-sucrose nonfermentable (SWI/SNF) chromatin remodeling complex. We confirmed this finding in an independent validation cohort of 63 ccRCC patients treated with PD-1 or PD-L1 (PD-1 ligand) blockade therapy alone or in combination with anti-CTLA-4 (cytotoxic T lymphocyte-associated protein 4) therapies (
= 0.0071). Gene-expression analysis of PBAF-deficient ccRCC cell lines and
-deficient tumors revealed altered transcriptional output in JAK-STAT (Janus kinase-signal transducers and activators of transcription), hypoxia, and immune signaling pathways.
loss in ccRCC may alter global tumor-cell expression profiles to influence responsiveness to immune checkpoint therapy.
As a result of multiple technological and practical advances, high-throughput sequencing, known more commonly as "next-generation" sequencing (NGS), can now be incorporated into standard clinical ...practice. Whereas early protocols relied on samples that were harvested outside of typical clinical pathology workflows, standard formalin-fixed, paraffin-embedded specimens can more regularly be used as starting materials for NGS. Furthermore, protocols for the analysis and interpretation of NGS data, as well as knowledge bases, are being amassed, allowing clinicians to act more easily on genomic information at the point of care for patients. In parallel, new therapies that target somatically mutated genes identified through clinical NGS are gaining US Food and Drug Administration (FDA) approval, and novel clinical trial designs are emerging in which genetic identifiers are given equal weight to histology. For clinical oncology providers, understanding the potential and the limitations of DNA sequencing will be crucial for providing genomically driven care in this era of precision medicine.
The determination of molecular features that mediate clinically aggressive phenotypes in prostate cancer remains a major biological and clinical challenge
. Recent advances in interpretability of ...machine learning models as applied to biomedical problems may enable discovery and prediction in clinical cancer genomics
. Here we developed P-NET-a biologically informed deep learning model-to stratify patients with prostate cancer by treatment-resistance state and evaluate molecular drivers of treatment resistance for therapeutic targeting through complete model interpretability. We demonstrate that P-NET can predict cancer state using molecular data with a performance that is superior to other modelling approaches. Moreover, the biological interpretability within P-NET revealed established and novel molecularly altered candidates, such as MDM4 and FGFR1, which were implicated in predicting advanced disease and validated in vitro. Broadly, biologically informed fully interpretable neural networks enable preclinical discovery and clinical prediction in prostate cancer and may have general applicability across cancer types.
We present an in silico approach to identifying neoepitopes derived from intron retention events in tumor transcriptomes. Using mass spectrometry immunopeptidome analysis, we show that retained ...intron neoepitopes are processed and presented on MHC I on the surface of cancer cell lines. RNA-derived neoepitopes should be considered for prospective personalized cancer vaccine development.
Immune-checkpoint blockade (ICB) has demonstrated efficacy in many tumor types, but predictors of responsiveness to anti-PD1 ICB are incompletely characterized. In this study, we analyzed a ...clinically annotated cohort of patients with melanoma (n = 144) treated with anti-PD1 ICB, with whole-exome and whole-transcriptome sequencing of pre-treatment tumors. We found that tumor mutational burden as a predictor of response was confounded by melanoma subtype, whereas multiple novel genomic and transcriptomic features predicted selective response, including features associated with MHC-I and MHC-II antigen presentation. Furthermore, previous anti-CTLA4 ICB exposure was associated with different predictors of response compared to tumors that were naive to ICB, suggesting selective immune effects of previous exposure to anti-CTLA4 ICB. Finally, we developed parsimonious models integrating clinical, genomic and transcriptomic features to predict intrinsic resistance to anti-PD1 ICB in individual tumors, with validation in smaller independent cohorts limited by the availability of comprehensive data. Broadly, we present a framework to discover predictive features and build models of ICB therapeutic response.
Cancer genomes contain large numbers of somatic mutations but few of these mutations drive tumor development. Current approaches either identify driver genes on the basis of mutational recurrence or ...approximate the functional consequences of nonsynonymous mutations by using bioinformatic scores. Passenger mutations are enriched in characteristic nucleotide contexts, whereas driver mutations occur in functional positions, which are not necessarily surrounded by a particular nucleotide context. We observed that mutations in contexts that deviate from the characteristic contexts around passenger mutations provide a signal in favor of driver genes. We therefore developed a method that combines this feature with the signals traditionally used for driver-gene identification. We applied our method to whole-exome sequencing data from 11,873 tumor-normal pairs and identified 460 driver genes that clustered into 21 cancer-related pathways. Our study provides a resource of driver genes across 28 tumor types with additional driver genes identified according to mutations in unusual nucleotide contexts.
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.
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