基于生物信息学构建肝癌免疫预后基因模型及初步验证OA北大核心CSTPCD

The Cancer Genome Atlas(TCGA)and the International Cancer Genome Consortium(ICGC)databases were used to collect RNA sequence information from patients with hepatocellular carcinoma(HCC).The key genes involved in the immune response mechanism to HCC were screened using the non-negative matrix factorization(NMF)clustering method and weighted gene co-expression network analysis(WGCNA).Prognostic gene models were constructed using the least absolute shrinkage and selection operator(LASSO)regression analysis,and biological functions were analyzed using gene set enrichment analysis(GSEA).Subsequently,to assess the immune infiltration and the related functional differences between the patients in two different risk groups,we used single-sample gene set enrichment analysis(ssGSEA).We constructed column line graphs in combination with independent risk factors to predict overall patient survival time using the"RMS"package in R.Finally,preliminary clinical validation was performed using the Human Protein Atlas(HPA)database with real-time quantitative fluorescent PCR(RT-qPCR).In conclusion,we integrated the clinical characteristics of patients based on risk scores to construct a verifiable and reproducible column line chart,providing a reliable reference for the precise treatment of patients in clinical oncology.