Prognosis analysis of necroptosis-related genes in colorectal cancer based on bioinformatic analysis

Abstract

Background: Colorectal cancer (CRC) is one gastrointestinal malignancy, accounting for 10% of cancer diagnoses and cancer-related deaths worldwide each year. Therefore, it is urgent to identify genes involved in CRC predicting the prognosis.Methods: CRC’s data were acquired from the Gene Expression Omnibus (GEO) database (GSE39582 and GSE41258 datasets) and The Cancer Genome Atlas (TCGA) database. The differentially expressed necroptosis-related genes (DENRGs) were sorted out between tumor and normal tissues. Univariate Cox regression analysis and least absolute shrinkage and selectionator operator (LASSO) analysis were applied to selected DENRGs concerning patients’ overall survival and to construct a prognostic biomarker. The effectiveness of this biomarker was assessed by the Kaplan–Meier curve and the receiver operating characteristic (ROC) analysis. The GSE39582 dataset was utilized as external validation for the prognostic signature. Moreover, using univariate and multivariate Cox regression analyses, independent prognostic factors were identified to construct a prognostic nomogram. Next, signaling pathways regulated by the signature were explored through the gene set enrichment analysis (GSEA). The single sample gene set enrichment analysis (ssGSEA) algorithm and tumor immune dysfunction and exclusion (TIDE) were used to explore immune correlation in the two groups, high-risk and low-risk ones. Finally, prognostic genes’ expression was examined in the GSE41258 dataset.Results: In total, 27 DENRGs were filtered, and a necroptosis-related prognostic signature based on 6 DENRGs was constructed, which may better understand the overall survival (OS) of CRC. The Kaplan–Meier curve manifested the effectiveness of the prognostic signature, and the ROC curve showed the same result. In addition, univariate and multivariate Cox regression analyses revealed that age, pathology T, and risk score were independent prognostic factors, and a nomogram was established. Furthermore, the prognostic signature was most significantly associated with the apoptosis pathway. Meanwhile, 24 immune cells represented significant differences between two groups, like the activated B cell. Furthermore, 32 immune checkpoints, TIDE scores, PD-L1 scores, and T-cell exclusion scores were significantly different between the two groups. Finally, a 6-gene prognostic signature represented different expression levels between tumor and normal samples significantly in the GSE41258 dataset.Conclusion: Our study established a signature including 6 genes and a prognostic nomogram that could significantly assess the prognosis of patients with CRC.

Experimental prognostic model integrating N6-methyladenosine-related programmed cell death genes in colorectal cancer

“… 10 , 41 It has been reported that m6A plays an increasingly important role in various physiological and pathological processes in various cancers, 42 including pancreatic cancer, 43 breast cancer, 44 and our published CRC study. 45 While the roles of various programmed cell death (PCD) modes in CRC prognosis have been explored in the literature, these models have primarily focused on individual modes of cell death, such as the apoptosis-related prognostic signature, 46 autophagy-related signature, 47 , 48 , 49 , 50 , 51 cuproptosis-related signature, 52 , 53 , 54 ferroptosis-related signature, 55 , 56 , 57 necroptosis-related signature, 58 , 59 and pyroptosis-related prognostic signature. 60 , 61 , 62 , 63 , 64 , 65 However, the interplay between m6A modification and PCD in CRC prognosis remains unexplored, representing a gap in the existing literature.…”

The role of HMGA2 in activating the IGFBP2 expression to promote angiogenesis and LUAD metastasis via the PI3K/AKT/VEGFA signaling pathway

“…html). Furthermore, the "clusterProfiler", "org.Hs.eg.db", "enrichplot", "DOSE", and "ggplot2" packages in R language were employed for conducting GO and KEGG pathway analysis [13,14].…”