ArticleCancer cell international2022
Identification and validation a costimulatory molecule gene signature to predict the prognosis and immunotherapy response for hepatocellular carcinoma.
Article in Cancer cell international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 11 citations in OpenAlex.
- Comprehensive bioinformatics analysis of MEX3 family genes in hepatocellular carcinoma.Scientific reports · 2025Article
- Machine learning-driven mast cell gene signatures for prognostic and therapeutic prediction in prostate cancer.Heliyon · 2024Article
- Comprehensive analysis of anoikis-related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma.IET systems biology · 2023Article
- Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma.International journal of molecular sciences · 2023Review
- Prognostic costimulatory molecule-related signature risk model correlates with immunotherapy response in colon cancer.Scientific reports · 2023Article
- Dysregulation of immune checkpoint proteins in hepatocellular carcinoma: Impact on metabolic reprogramming.Current opinion in pharmacology · 2022Review
- A Signature Based on Costimulatory Molecules for the Assessment of Prognosis and Immune Characteristics in Patients With Stomach Adenocarcinoma.Frontiers in immunology · 2022Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundHepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Costimulatory molecules have been proven to be the foundation of immunotherapy. However, the potential roles of costimulatory molecule genes (CMGs) in HCC remain unclear. Our study is aimed to develop a costimulatory molecule-related gene signature that could evaluate the prognosis of HCC patients.
methodsBased on The Cancer Gene Atlas (TCGA) database, univariate Cox regression analysis was applied in CMGs to identify prognosis-related CMGs. Consensus clustering analysis was performed to stratify HCC patients into different subtypes and compared them in OS. Subsequently, the LASSO Cox regression analysis was performed to construct the CMGs-related prognostic signature and Kaplan-Meier survival curves as well as ROC curve were used to validate the predictive capability. Then we explored the correlations of the risk signature with tumor-infiltrating immune cells, tumor mutation burden (TMB) and response to immunotherapy. The expression levels of prognosis-related CMGs were validated based on qRT-PCR and Human Protein Atlas (HPA) databases.
resultsAll HCC patients were classified into two clusters based on 11 CMGs with prognosis values and cluster 2 correlated with a poorer prognosis. Next, a prognostic signature of six CMGs was constructed, which was an independent risk factor for HCC patients. Patients with low-risk score were associated with better prognosis. The correlation analysis showed that the risk signature could predict the infiltration of immune cells and immune status of the immune microenvironment in HCC. The qRT-PCR and immunohistochemical results indicated six CMGs with differential expression in HCC tissues and normal tissues.
conclusionIn conclusion, our CMGs-related risk signature could be used as a prediction tool in survival assessment and immunotherapy for HCC patients.
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