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Comprehensive analysis of cuproptosis-related immune biomarker signature to enhance prognostic accuracy in gastric cancer

Jie Li, Tian Yu, Juan Sun, Ziyang Zeng, Zhen Liu, Mingwei Ma, Zicheng Zheng, Yixuan He, Weiming Kang

Aging(2023)

Cited 0|Views13
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Abstract
Background: Gastric cancer (GC) is a malignant tumor with high prevalence and fatality. Cuproptosis is a recently identified copper-dependent programmed cell death mechanism. Multiple studies have demonstrated the profound impact of the immune microenvironment on tumor development. Hence, we decided to excavate the potential functional roles of cuproptosis-related immune genes (CRIGs) in GC and their values as biomarkers. Methods: Cuproptosis-and immune-related genes were curated from top published studies on cell cuproptosis and cellular immunity. Transcriptome data and clinical information were obtained from TCGA, GTEx, and GEO databases. Cox and LASSO analyses were used to establish a prognostic signature for GC. Long-term prognosis, immune infiltration, immune checkpoint, and drug response were compared between signature groups. CRIG expression in GC scRNA-seq was analyzed. Immunohistochemistry was used to evaluate CRIG and cuproptosis regulator FDX1 in GC tissues. Results: Seven CRIGs (ANOS1, CTLA4, ITGAV, CXCR4, NRP1, FABP3, and LGR6) were selected to establish a potent signature to forecast the long-term prognosis of patients. GC patients had worse prognosis and poor responses to chemotherapeutic drugs (5-Fluorouracil and paclitaxel) in the high-risk group. scRNA-seq revealed that CTLA4, ITGAV, CXCR4, and NRP1 enrichment in specific cell types regulated the progression of GC. Moreover, NRP1, CXCR4, LGR6, CTLA4, and FDX1 were elevated in GC tissues, with a positive correlation between their expression and FDX1. Conclusions: To conclude, this study first provides insights into the functions of CRIGs in GC. Furthermore, a robust cuproptosis-related immune biomarker signature was established to forecast the long-term survival of GC patients accurately.
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Key words
gastric cancer,cuproptosis,immune infiltration,prognostic signature,bioinformatics
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