Background: Aging is a well-studied concept, but no studies have comprehensively analyzed the association between aging-related genes (AGs) and hepatocellular carcinoma (HCC) prognosis.Methods: Gene candidates were selected from differentially expressed genes and prognostic genes in The Cancer Genome Atlas (TCGA) database. A gene risk score for overall survival prediction was established using the least absolute shrinkage and selection operator (LASSO) regression analysis, and this was validated using data from the International Cancer Genome Consortium (ICGC) database. Functional analysis was conducted using gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis, and immune microenvironment and tumor stemness analyses.Results: Initially, 72 AGs from the TCGA database were screened as differentially expressed between normal and tumor tissues and as genes associated with HCC prognosis. Then, seven AGs (POLA1, CDK1, SOCS2, HDAC1, MAPT, RAE1, and EEF1E1) were identified using the LASSO regression analysis. The seven AGs were used to develop a risk score in the training set, and the risk was validated to have a significant prognostic value in the ICGC set (p < 0.05). Patients with high risk scores had lower tumor differentiation, higher stage, and worse prognosis (all p < 0.05). Multivariate Cox regression analyses also confirmed that the risk score was an independent prognostic factor for HCC in both the TCGA and ICGC sets (all p < 0.05). Further analysis showed that a high risk score was correlated with the downregulation of metabolism and tumor immunity.Conclusion: The risk score predicts HCC prognosis and could thus be used as a biomarker not only for predicting HCC prognosis but also for deciding on treatment.
BackgroundTransient receptor potential channels (TRPC) play critical regulatory functions in cancer occurrence and progression. However, knowledge on its role in colorectal cancer (CRC) is limited. In addition, neoadjuvant treatment and immune checkpoint inhibitors (ICIs) have increasing roles in CRC management, but not all patients benefit from them. In this study, a TRPC related signature (TRPCRS) was constructed for prognosis, tumor immune microenvironment (TIME), and treatment response of CRC.MethodsData on CRC gene expression and clinical features were retrospectively collected from TCGA and GEO databases. Twenty-eight TRPC regulators (TRPCR) were retrieved using gene set enrichment analysis. Different TRPCR expression patterns were identified using non-negative matrix factorization for consensus clustering, and a TRPCRS was established using LASSO. The potential value of TRPCRS was assessed using functional enrichment analysis, tumor immune analysis, tumor somatic mutation analysis, and response to preoperative chemoradiotherapy or ICIs. Moreover, an external validation was conducted using rectal cancer samples that received preoperative chemoradiotherapy at Fujian Cancer Hospital (FJCH) via qRT-PCR.ResultsAmong 834 CRC samples in the TCGA and meta-GEO cohorts, two TRPCR expression patterns were identified, which were associated with various immune infiltrations. In addition, 266 intersected genes from 5564 differentially expressed genes (DEGs) between two TRPC subtypes, 4605 DEGs between tumor tissue and adjacent non-tumor tissue (all FDR< 0.05, adjusted P< 0.001), and 1329 prognostic related genes (P< 0.05) were identified to establish the TRPCRS, which was confirmed in the TCGA cohort, two cohorts from GEO, and one qRT-PCR cohort from FJCH. According to the current signature, the high-TRPC score group had higher expressions of PD-1, PD-L1, and CTLA4, lower TIDE score, and improved response to anti-PD-1 treatment with better predictive ability. Compared to the high-TRPC score group, the low-TRPC score group comprised an immunosuppressive phenotype with increased infiltration of neutrophils and activated MAPK signaling pathway, but was more sensitive to preoperative chemoradiotherapy and associated with improved prognosisConclusionsThe current TRPCRS predicted the prognosis of CRC, evaluated the TIME in CRC, and anticipated the response to immune therapy and neoadjuvant treatment.
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