Dataset Information

Establishment of a novel gene panel as a biomarker of immune checkpoint inhibitor response.

ABSTRACT: Objective:Immune checkpoint inhibitors (ICIs) have become the standard of care in various cancers, although the predictive tool is still unknown. Methods:This study aimed to develop a novel gene panel by selecting DNA damage response (DDR) genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) databank and validating them in previously reported cohorts. This association between DDR gene mutations and tumor mutation burden or microsatellite status was analysed from The Cancer Genome Atlas (TCGA) databank. Furthermore, we made the gene panel clinically accessible and predicted the response in clinical patients receiving ICIs by using cell-free DNA. Results:The top 20 mutated DDR genes in various cancers (total 37 genes) were taken from the COSMIC databank, and the DDR genes found to individually predict a response rate > 50% in Van Allen's cohort were selected (Science, 350, 2015 and 207). Eighteen DDR genes were selected as the gene panel. The prevalence and predicted response rate were validated in the other three reported cohorts. Tumor mutational burden-high was positively associated with mutations of the 18 DDR genes for most cancers. We used cell-free DNA to test the DDR gene panel and validated by our patients receiving ICIs. This DDR gene panel accounted for approximately 30% of various cancers, achieving a predicted response rate of approximately 60% in patients with a mutated gene panel receiving ICIs. Conclusion:This gene panel is a novel and reliable tool for predicting the response to ICIs in cancer patients and guides the appropriate administration of ICIs in clinical practice.

SUBMITTER: Pan YR

PROVIDER: S-EPMC7326616 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Establishment of a novel gene panel as a biomarker of immune checkpoint inhibitor response.

Pan Yi-Ru YR Wu Chiao-En CE Wang Yu-Chao YC Yeh Yi-Chen YC Lu Meng-Lun ML Hung Yi-Ping YP Chao Yee Y Yeh Da-Wei DW Lin Chien-Hsing CH Hsieh Jason Chia-Hsun JC Chen Ming-Huang MH Yeh Chun-Nan CN

Clinical & translational immunology 20200630 7

<h4>Objective</h4>Immune checkpoint inhibitors (ICIs) have become the standard of care in various cancers, although the predictive tool is still unknown.<h4>Methods</h4>This study aimed to develop a novel gene panel by selecting DNA damage response (DDR) genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) databank and validating them in previously reported cohorts. This association between DDR gene mutations and tumor mutation burden or microsatellite status was analysed from The Ca ...[more]

PMID: 32617161

Similar Datasets

Project description:BackgroundImmune checkpoint inhibitor (ICI) therapy elicits durable antitumor responses in patients with many types of cancer. Genomic mutations may be used to predict the clinical benefits of ICI therapy. NOTCH homolog-4 (NOTCH4) is frequently mutated in several cancer types, but its role in immunotherapy is still unclear. Our study is the first to study the association between NOTCH4 mutation and the response to ICI therapy.MethodsWe tested the predictive value of NOTCH4 mutation in the discovery cohort, which included non-small cell lung cancer, melanoma, head and neck squamous cell carcinoma, esophagogastric cancer, and bladder cancer patients, and validated it in the validation cohort, which included non-small cell lung cancer, melanoma, renal cell carcinoma, colorectal cancer, esophagogastric cancer, glioma, bladder cancer, head and neck cancer, cancer of unknown primary, and breast cancer patients. Then, the relationships between NOTCH4 mutation and intrinsic and extrinsic immune response mechanisms were studied with multiomics data.ResultsWe collected an ICI-treated cohort (n = 662) and found that patients with NOTCH4 mutation had better clinical benefits in terms of objective response rate (ORR: 42.9% vs 25.9%, P = 0.007), durable clinical benefit (DCB: 54.0% vs 38.1%, P = 0.021), progression-free survival (PFS, hazard ratio [HR] = 0.558, P < 0.001), and overall survival (OS, HR = 0.568, P = 0.006). In addition, we validated the prognostic value of NOTCH4 mutation in an independent ICI-treated cohort (n = 1423). Based on multiomics data, we found that NOTCH4 mutation is significantly associated with enhanced immunogenicity, including a high tumor mutational burden, the expression of costimulatory molecules, and activation of the antigen-processing machinery, and NOTCH4 mutation positively correlates activated antitumor immunity, including infiltration of diverse immune cells and various immune marker sets.ConclusionsOur findings indicated that NOTCH4 mutation serves as a novel biomarker correlated with a better response to ICI therapy.

Project description:Somatostatin receptor 2 (SSTR2), the most abundant receptor of somatostatin (SST), possesses immunoreactivity and is altered in many cancers. However, the association between SSTR2 and efficacy of immune checkpoint inhibitors (ICIs) has not yet been reported. Immunohistochemistry (IHC) information across 20 cancers was collected from the Human Protein Atlas (HPA) and used to analyze the expression of SSTR2. Immune signatures collected from public databases, such as BioCarta or Reactome, were used to investigate the association between SSTR2 and the tumor microenviroment in the Cancer Genome Atlas (TCGA). Data from cohorts treated with ICIs were collected to assess whether SSTR2 is associated with benefits from ICIs treatment. In the HPA, we found the SSTR2 IHC-positive rate of 13 cancers to be above 50%. Five types of cancer express SSTR2 mildly (positive rate: 25%-50%), while the remaining two types of cancer barely stained SSTR2-positive (positive rate: 0%-24%). In TCGA analysis, immune cell signatures and immune function pathways were enriched in high SSTR2 expression groups in most cancers. In each ICIs treated cohort, patients with high SSTR2 expression experienced numerically superior objective response rate (Braun: 14.8% vs 13.4%, p = 0.85; Gide: 69.4% vs 40.5%, p = 0.025; Mariathasan: 22.4% vs 16.7%, p = 0.233; Miao: 37.5% vs 11.8%; Riaz: 32.0% vs 7.7%, p = 0.067) and overall survival (Braun: HR (95%CI): 0.80 [0.62-1.04], p = 0.80; Gide: HR (95%CI): 0.61 [0.29-1.30], p = 0.20; Mariathasan: HR (95%CI): 0.83 [0.64-1.08], p = 0.16; Miao: HR (95%CI): 0.24 [0.086-0.65], p = 0.0028; Nathanson cohort: HR (95%CI): 0 [0-inf], p = 0.18; Riaz: HR (95%CI): 0.24 [0.086-0.65], p = 0.028) than patients with low SSTR2 expression. In pooled cohort, we found these differences were significant (Pool: 24.6% vs 16.7%, p = 0.0077; HR (95% CI): 0.77 [0.65-0.91], p = 0.0018). Our results suggest that SSTR2 is a potential predictive biomarker for response to ICIs.

Dataset Information

Establishment of a novel gene panel as a biomarker of immune checkpoint inhibitor response.

Publications

Establishment of a novel gene panel as a biomarker of immune checkpoint inhibitor response.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets