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Identification of CircRNA signature associated with tumor immune infiltration to predict therapeutic efficacy of immunotherapy.

ABSTRACT: Circular RNAs (circRNAs) play important roles in the regulation of cancer. However, the clinical implications and regulatory networks of circRNAs in cancer patients receiving immune checkpoint blockades (ICB) have not been fully elucidated. Here, we characterize circRNA expression profiles in two independent cohorts of 157 ICB-treated advanced melanoma patients and reveal overall overexpression of circRNAs in ICB non-responders in both pre-treatment and early during therapy. Then, we construct circRNA-miRNA-mRNA regulatory networks to reveal circRNA-related signaling pathways in the context of ICB treatment. Further, we construct an ICB-related circRNA signature (ICBcircSig) score model based on progression-free survival-related circRNAs to predict immunotherapy efficacy. Mechanistically, the overexpression of ICBcircSig circTMTC3 and circFAM117B could increase PD-L1 expression via the miR-142-5p/PD-L1 axis, thus reducing T cell activity and leading to immune escape. Overall, our study characterizes circRNA profiles and regulatory networks in ICB-treated patients, and highlights the clinical utility of circRNAs as predictive biomarkers of immunotherapy.

SUBMITTER: Dong Y

PROVIDER: S-EPMC10156742 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Identification of CircRNA signature associated with tumor immune infiltration to predict therapeutic efficacy of immunotherapy.

Dong Yu Y Gao Qian Q Chen Yong Y Zhang Zhao Z Du Yanhua Y Liu Yuan Y Zhang Guangxiong G Li Shengli S Wang Gaoyang G Chen Xiang X Liu Hong H Han Leng L Ye Youqiong Y

Nature communications 20230503 1

Circular RNAs (circRNAs) play important roles in the regulation of cancer. However, the clinical implications and regulatory networks of circRNAs in cancer patients receiving immune checkpoint blockades (ICB) have not been fully elucidated. Here, we characterize circRNA expression profiles in two independent cohorts of 157 ICB-treated advanced melanoma patients and reveal overall overexpression of circRNAs in ICB non-responders in both pre-treatment and early during therapy. Then, we construct c ...[more]

PMID: 37137884

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Project description:BackgroundLung cancer is a highly aggressive disease and the leading cause of cancer-related deaths. Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer. As a type of programmed cell death, anoikis serves a key role in tumor metastasis. However, as few studies have focused on anoikis and prognostic indicators in LUAD, in this study, we constructed an anoikis-related risk model to explore how anoikis could influence the tumor microenvironment (TME), clinical treatment, and prognosis in LUAD patients; we aimed to provide new insight for future research.MethodsUsing patient data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), we utilized the 'limma' package to select differentially expressed genes (DEGs) associated with anoikis and then they were divided into 2 clusters with consensus clustering. Risk models were constructed with least absolute shrinkage and selection operator (LASSO) Cox regression (LCR). Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC) curves were performed to assess the independent risk factors for different clinical characteristics, including age, sex, disease stage, grade, and their associated risk scores. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed to explore the biological pathways in our model. The effectiveness of clinical treatment was detected according to tumor immune dysfunction and exclusion (TIDE), The Cancer Immunome Atlas (TCIA), and IMvigor210.ResultsOur model was found to divide LUAD patients into high- and low-risk groups well, in which high risk groups had poor overall survival (OS), indicating that risk score could be an independent risk factor to predict the prognosis of LUAD patients. Interestingly, we found that anoikis could not only influence the extracellular organization but also play great roles in immune infiltration and immunotherapy, which might provide a new insight for future research.ConclusionsThe risk model constructed in this study can benefit to predict patient survival. Our results provided new potential treatment strategies.

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Identification of CircRNA signature associated with tumor immune infiltration to predict therapeutic efficacy of immunotherapy.

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Identification of CircRNA signature associated with tumor immune infiltration to predict therapeutic efficacy of immunotherapy.

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