The cGAS-STING-related signature affects the prognosis of colorectal cancer through its regulation of multiple immune cells

Abstract

The cGAS-STING signaling pathway has emerged as a critical player in the immune response against cancer, including colorectal adenocarcinoma (COAD). Understanding the impact of this pathway on COAD at multiple omics levels is crucial for advancing cancer immunotherapy and precision medicine. This study aimed to investigate the relationship between cGAS-STING-related genes and COAD, analyzing gene mutations, copy number variations, DNA methylation, and gene expression to uncover the pathway's influence on COAD prognosis. Utilizing multi-omics sequencing data from TCGA and GEO databases, key core genes in the cGAS-STING pathway were identified and further validated through PCR and Western blot analysis. Mutations and copy number variations in the CASP8 and RIPK1 genes, differential DNA methylation patterns, and mRNA expression levels of specific genes were assessed to determine their impact on COAD prognosis. Validation through tissue samples highlighted NLRC3, CASP1, AIM2, and CXCL10 as core genes in the cGAS-STING pathway. Our findings demonstrate that mutations and copy number variations in CASP8 and RIPK1, differential DNA methylation patterns, and altered gene expression levels significantly influence the prognosis of COAD. The identification of core genes in the cGAS-STING pathway, particularly NLRC3, CASP1, AIM2, and CXCL10, has led to the development of a prognostic model predicting poor tumor outcomes through immune cell infiltration. This study provides valuable insights into the mechanisms of the cGAS-STING pathway in COAD and offers potential directions for future research in cancer immunotherapy and precision medicine.

Keywords: cGAS‐STING; colorectal adenocarcinoma; multiple immune cells; prognosis.

FIGURE 1

Basic information analysis of cGAS‐STING‐related genes. (A) Protein interaction analysis between cGAS‐STING‐related genes; (B) functional enrichment analysis of cGAS‐STING‐related genes in GO and KEGG. The size of the bubbles in the figure represents the number of genes included, and the darker the color, the more significant the result.

FIGURE 2

Relationship between cGAS‐STING signaling pathway gene mutations and colorectal adenocarcinoma (COAD). (A) Waterfall plot of gene mutations related to the cGAS‐STING signaling pathway; (B) specific locations of PRKDC and CREBBP gene mutations; (C) mutual occurrence/exclusion analysis of gene mutations in the cGAS‐STING signaling pathway; (D) relationship between cGAS‐STING signaling pathway mutations in COAD patients and MSI; (E) effect of CASP8 and RIPK1 gene mutations on the prognosis of COAD.*means p less than 0.05.

FIGURE 3

Relationship between cGAS‐STING signaling pathway gene copy number changes and colorectal adenocarcinoma (COAD). (A) Top 10 genes ranked by copy number changes; (B) effect of CREBBP gene copy number changes on the prognosis of COAD patients; (C) survival analysis of IFNA16 gene copy number changes; (D) relationship between CREBBP and stage, N stage, and M stage; (E) relationship between MSI and gene copy number changes in COAD patients.

FIGURE 4

Relationship between cGAS‐STING signaling pathway gene methylation and colorectal adenocarcinoma (COAD). (A) Volcano plot of differential methylation analysis; (B) functional enrichment analysis of differentially methylated genes in GO and KEGG. The size of the bubbles in the figure represents the number of genes included, and the darker the color, the more significant the result; (C) effect of gene methylation levels on the prognosis of COAD; (D) relationship between CTNNB1, CCL5, and CASP8 methylation and MSI.

FIGURE 5

Relationship between mRNA expression of cGAS‐STING signaling pathway genes and colorectal adenocarcinoma (COAD). (A) Volcano plot of differential expression analysis of TCGA‐COAD; (B) volcano plot of differential expression analysis of GSE8671, where blue bubbles represent low‐expression genes, red bubbles represent high‐expression genes, and black bubbles represent genes without differential expression; (C) Venn diagram of cross‐analysis of differential genes in TCGA‐COAD and GSE8671; (D) functional enrichment analysis of stably differentially expressed genes; (E) Venn diagram of cross‐analysis of significant prognostic genes in TCGA‐COAD and GSE39582; (F) KEGG pathway enrichment analysis of significant prognostic genes; (G) upset plot of cross‐analysis of TCGA‐COAD, GSE8671, and GSE39582, where the upper part of the figure represents the genes from the combination of the four datasets, and the red labels represent the number of significant genes in the four datasets; (H), effect of core genes on clinical stage; (I) KEGG pathway enrichment analysis of the four core genes; (J) relationship between core genes and immune cell infiltration, where red represents positive correlation and blue represents negative correlation, and the larger the size of the pie chart, the more significant the correlation.

FIGURE 6

Tissue sample validation results of cGAS core genes. (A) Differential expression validation of cGAS core genes using PCR on tissue samples. (B) Tissue sample validation of cGAS core genes using Western blot.

FIGURE 7

Prediction of potential regulatory functions of core genes. (A) Analysis of the correlation between NLRC3 and methylation sites; (B) analysis of the correlation between CASP1 and methylation sites; (C) analysis of the correlation between AIM2 and methylation sites; (D) relationship between CASP1 and AIM2 gene expression and copy number.

FIGURE 8

Construction of cGAS‐STING prognostic model. (A) Construction of cGAS‐STING prognostic model; (B) effect of the cGAS prognostic model on the prognosis of TCGA‐ colorectal adenocarcinoma (COAD) patients; (C) effect of the cGAS prognostic model on the prognosis of new data; (D) DCA curve indicates that the prognostic model has certain clinical usefulness; (E) construction of a nomogram based on the cGAS prognostic model and whether radiotherapy was performed.

FIGURE 9

The impact of the cGAS‐STING prognostic model on immune cell function. (A) Heatmap of differential analysis between the cGAS‐STING prognostic model and immune cells. (B) Differences in various types of T cells exist in the cGAS‐STING prognostic model. (C) Pathways including apoptosis exhibit differential expression in different prognostic groups.

FIGURE 10

NLRC3 affects tumor proliferation and apoptosis. (A) NLRC3 overexpression inhibits cell motility. (B) NLRC3 overexpression is associated with increased apoptosis in tumor cells. (C) The NLRC3‐expressing group showed significantly higher levels of TP53AIP1 expression, which promotes cell apoptosis.