Identification and Validation of a Six Immune-Related Genes Signature for Predicting Prognosis in Patients With Stage II Colorectal Cancer

Abstract

BackgroundImmune-related genes (IRGs) play important roles in the tumor immune microenvironment and can affect the prognosis of cancer. This study aimed to construct a novel IRG signature for prognostic evaluation of stage II colorectal cancer (CRC).MethodsGene expression profiles and clinical data for stage II CRC patients were collected from the Cancer Genome Atlas and Gene Expression Omnibus database. Univariate, multivariate Cox regression, and least absolute shrinkage and selection operator regression were used to develop the IRG signature, namely IRGCRCII. A nomogram was constructed, and the “Cell Type Identification by Estimating Relative Subsets of RNA Transcripts” (CIBERSORT) method was used to estimate immune cell infiltration. The expression levels of genes and proteins were validated by qRT-PCR and immunohistochemistry in 30 pairs of primary stage II CRC and matched normal tissues.ResultsA total of 466 patients with stage II CRC were included, and 274 differentially expressed IRGs were identified. Six differentially expressed IRGs were detected and used to construct the IRGCRCII signature, which could significantly stratify patients into high-risk and low-risk groups in terms of disease-free survival in three cohorts: training, test, and external validation (GSE39582). Receiver operating characteristics analysis revealed that the area under the curves of the IRGCRCII signature were significantly greater than those of the OncotypeDX colon signature at 1 (0.759 vs. 0.623), 3 (0.875 vs. 0.629), and 5 years (0.906 vs. 0.698) disease-free survival, respectively. The nomogram performed well in the concordance index (0.779) and calibration curves. The high-risk group had a significantly higher percentage of infiltrated immune cells (e.g., M2 macrophages, plasma cells, resting mast cells) than the low-risk group. Finally, the results of qRT-PCR and immunohistochemistry experiments performed on 30 pairs of clinical specimens were consistent with bioinformatics analysis.ConclusionThis study developed and validated a novel immune prognostic signature based on six differentially expressed IRGs for predicting disease-free survival and immune status in patients with stage II CRC, which may reflect immune dysregulation in the tumor immune microenvironment.

Identification of a Four-Gene Signature for Determining the Prognosis of Papillary Thyroid Carcinoma by Integrated Bioinformatics Analysis

“…The results of clinical practice based on gene-expression profiles have shown that high-throughput methods for identifying gene signatures might show promise in helping determine effective therapies. 20 , 21 Several studies have explored the prognostic roles of gene signatures in predicting THCA outcomes. 22–25 However, only a few studies focused specifically on the prognosis of PTC.…”

ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG May Serve as Diagnostic and Prognostic Biomarkers in Endometrial Carcinoma

“…UCEC therapy was not merely needed to keep a watchful eye on the intrinsic characteristics of UCEC cells but also needed to pay close attention to the dynamic communication with various components in its TME. It had been established that tumor-infiltrating immune cells played essential roles in the TME with their composition and distribution considered to be linked with tumorigenesis and development [32][33][34]. We discovered that the expression of the 6 hub genes was positively correlated with the abundance of 2 cells, and was all negatively correlated with the abundance of 17 cells, NK CD56bright cells, pDC, NK cells, cytotoxic cells, neutrophils, eosinophils, mast cells, T cells, Tfh.…”

“…Immune Infiltration. Tumor-infiltrating immune cells were the primary components of the tumor microenvironment (TME) and had been considered to exert important effects on the progression of the tumor [32][33][34].…”

Four methylation-driven genes detected by linear discriminant analysis model from early-stage colorectal cancer and their methylation levels in cell-free DNA

“…Recent studies have indicated that integrated analyses of DNA methylation and gene expression could better reveal the regulatory function of DNA methylation and effectively predict the prognosis of patients (19)(20)(21). The prognostic models of CRC based on methylation-driven genes (MDGs) detected by R package MethylMix from DNA methylation and gene expression data have been reported (22)(23)(24)(25). However, the above studies mainly focused on the prognosis values of DNA methylation, whereas the roles of gene methylation in colorectal carcinogenesis have not been analyzed based on integrated multi-omics data.…”