Identification of a Novel 4-gene Prognostic Model Related to Neutrophil Extracellular Traps for Colorectal Cancer.

Abstract

Background/aims: Colorectal cancer (CRC) is a significant global health concern, and understanding the molecular mechanisms underlying CRC progression and prognosis is crucial. Neutrophil extracellular traps (NETs) have been implicated in various cancers, but their role in CRC and its clinical implications remain to be elucidated.

Materials and methods: Transcriptomic data from TCGA of CRC patients were analyzed to assess NETs enrichment and "NETs formation" pathway scores in NETs_high and NETs_low groups. Univariate Cox regression was used to identify prognosis-associated genes with the Log-Rank test for selection. Patients in the TCGA database were randomly split into training and testing sets to build a prognostic model with LASSO Cox regression. Model diagnostic performance was evaluated using Kaplan-Meier curves and receiver operating characteristic analysis. Single-sample gene set enrichment analysis (ssGSEA) was used to determine the abundance of 23 immune cells. ESTIMATE was used to calculate ImmuneScore and ESTIMATEScore, characterizing immune features of CRC samples.

Results: The NETs_high group in CRC showed significantly better survival than the NETs_low group. A robust prognostic model based on PRKRIP1, SERTAD2, ELFN1, and LINC00672 accurately predicted patient outcomes. NETs_high samples exhibited a more enriched immune environment with higher immune cell infiltration levels, as well as ImmuneScore and ESTIMATEScore. PRKRIP1, SERTAD2, ELFN1, and LINC00672 were significantly correlated with key immune cell types. Additionally, 18 drugs displayed differential sensitivity between NETs_high and NETs_low groups, with Daporinad and Selumetinib as potential therapeutic options.

Conclusion: Our findings may catalyze the development of personalized treatment modalities and bestow invaluable insights into the intricate dynamics governing CRC progression.