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A methylation-driven gene panel predicts survival in patients with colon cancer.

ABSTRACT: The accumulation of various genetic and epigenetic changes in colonic epithelial cells has been identified as one of the fundamental processes that drive the initiation and progression of colorectal cancer (CRC). This study aimed to explore functional genes regulated by DNA methylation and their potential utilization as biomarkers for the prediction of CRC prognoses. Methylation-driven genes (MDGs) were explored by applying the integrative analysis tool (methylmix) to The Cancer Genome Atlas CRC project. The prognostic MDG panel was identified by combining the Cox regression model with the least absolute shrinkage and selection operator regularization. Gene set enrichment analysis was used to determine the pathways associated with the six-MDG panel. Cluster of differentiation 40 (CD40) expression and methylation in CRC samples were validated by using additional datasets from the Gene Expression Omnibus. Methylation-specific PCR and bisulfite sequencing were used to confirm DNA methylation in CRC cell lines. A prognostic MDG panel consisting of six gene members was identified: TMEM88, HOXB2, FGD1, TOGARAM1, ARHGDIB and CD40. The high-risk phenotype classified by the six-MDG panel was associated with cancer-related biological processes, including invasion and metastasis, angiogenesis and the tumor immune microenvironment. The prognostic value of the six-MDG panel was found to be independent of tumor node metastasis stage and, in combination with tumor node metastasis stage and age, could help improve survival prediction. In addition, the expression of CD40 was confirmed to be regulated by promoter region methylation in CRC samples and cell lines. The proposed six-MDG panel represents a promising signature for estimating the prognosis of patients with CRC.

SUBMITTER: Peng Y

PROVIDER: S-EPMC8409306 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAbnormal methylation is associated with the survival of colon cancer. This study intended to discover a significant model based on methylation-driven genes (MDGs) and screen relative risk loci to assist with determining the prognoses of colon cancer patients.MethodsWe downloaded transcriptome expression profiles and 450K methylation data from the TCGA database. We then collected the two normalized profiles and utilized the MethylMix package to identify a significant signature showing the aberrantly methylated events highly correlated with expression levels. Also, functional enriched pathway analysis based on the ConsensusPathDB database was conducted to further explore the underlying cancer-related crosstalk among the identified MDGs. To find the significant MDGs for prognosis, we applied a univariate Cox regression model, and the hub signature was identified based on the stepwise regression method. A risk model based on MDGs was constructed from the multivariate Cox analysis, and a receiver operating characteristic (ROC) curve was drawn to assess the predictive value of the MDG signature. Additionally, the Kruskal-Wallis (K-W) test was conducted to compare differential distributions of risk scores across groups of clinical variables. Furthermore, the methylation sites relating to the hub genes were screened out and the prognostic genes were searched using the Cox regression method. Last, we carried out gene set enrichment analysis (GSEA) with the risk score levels serving as the phenotype base on the JAVA platform.ResultsA total of 514 colon cancer samples with transcriptome profiles, including 473 tumor samples and 41 matched normal samples, were downloaded. We also obtained 351 methylation profiles comprising 314 tumor samples and 37 normal samples. The 320 MDGs identified by MethylMix were enriched in the generic transcription pathway, RNA polymerase II transcription, activation of SMO, or glutathione metabolism. Furthermore, a 10-MDGs signature was selected as the hub prognostic marker, and the risk model was constructed from the multivariate Cox regression results. We also discovered multiple specific methylated sites that were highly associated with survival. Finally, the GSEA results suggested that several enriched pathways were associated with the identified risk drivers, including extracellular matrix (ECM) receptor interaction, chemokine receptor interaction, and pathways in cancer, as well as calcium signaling pathways.ConclusionsWe conducted a comprehensive investigation of the molecular mechanisms in colon cancer by discovering the risk methylation-driven signature combined with relative methylated sites and constructing a risk model to predict prognosis.

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A methylation-driven gene panel predicts survival in patients with colon cancer.

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