Background Changes in DNA methylation of immunosuppressive checkpoints may impact express and consequently affect antigen processing and presentation by tumor cells and facilitates evasion of immunosurveillance and lead to colorectal cancer (CRC). This study is to investigate the effect of PDCD-1, LAG-3 methylation statuses in peripheral blood leukocytes on CRC risk. Methods GSE51032 dataset from Gene Expression Omnibus comprised of 166 CRC patients and 424 normal samples was used to identify significantly differentially methylated CpG sites of the two genes. A case–control study with 390 CRC patients and 397 cancer-free controls was carried out to validate the relationship between the methylation levels of the two genes and CRC susceptibility and then estimated their interactions with environmental factors on CRC risk. Results In the GSE51032 dataset, cg06291111 (PDCD-1) and cg10191002 (LAG-3) were screened as the candidate CpG sites for the following study. There were significant associations between hypermethylation of PDCD-1 and LAG-3 and lower risk of CRC (ORadj = 0.322, 95% CI 0.197–0.528; ORadj = 0.666, 95% CI 0.446–0.5996, respectively). Moreover, the results in case–control study showed similar trend, that hypermethylation of PDCD-1 and LAG-3 were associated with lower CRC risk (ORadj = 0.448, 95% CI 0.322–0.622; ORadj = 0.417, 95% CI 0.301–0.578, respectively). A synergistic interaction between LAG-3 hypermethylation and intake of eggs on CRC risk was observed. There were combination effects between hypermethylation of PDCD-1 and LAG-3 and environmental factors on CRC risk. Conclusions PDCD-1 and LAG-3 may potentially serve as blood-based predictive biomarkers for CRC risk.
Homogenous DNA methylation clearly affects clinical outcomes. However, less is known about the effects of heterogeneous methylation. We aimed to investigate the different effects between CASK promoter methylation heterogeneity and homogeneity on colorectal cancer (CRC) patients' prognosis. The methylation status of CASK in 296 tumor tissues and 255 adjacent normal tissues were evaluated using Methylation-sensitive high-resolution melting (MS-HRM). Digital MS-HRM (dMS-HRM) visualized heterogeneous methylation and subsequent sequencing provided exact patterns. Log-rank test and Cox regression model were adopted to assess the association between CASK methylation status and CRC prognosis with propensity score (PS) method to control confounding biases. Heterogeneous methylation was detected in both tumor (52.2%) and non-neoplastic tissue surrounding the tumor (62.4%). It occurred more frequently in lower levels of tumor invasion ( P = 0.002) and male patients ( P < 0.001). Compared with heterogeneous methylation, patients with CASK homogeneous methylation presented poorer overall survival (OS) (HR: 1.919, 95% CI: 1.146-3.212, P = 0.013) and disease-free survival (DFS) (HR: 1.913, 95% CI: 1.146-3.194, P = 0.013). This unfavorable effect still existed among older (≥ 50), Dukes staging C/D, and rectal cancer patients. MS-HRM and dMS-HRM when combined can assess the degree and complexity of heterogeneous methylation with a visible pattern.
The tumor immune microenvironment (TIME) of colon cancer (CC) has been associated with extensive immune cell infiltration (IMI). Increasing evidence demonstrated that plasma cells (PC) have an extremely important role in advance of antitumor immunity. Nonetheless, there is a lack of comprehensive analyses of PC infiltration in clinical prognosis and immunotherapy in CC. This study systematically addressed the gene expression model and clinical information of CC patients. Clinical samples were obtained from the TCGA (The Cancer Genome Atlas) databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), GSVA, and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were employed to research the potential mechanism and pathways. Immunophenoscore (IPS) was obtained to evaluate the immunotherapeutic significance of risk score. Half maximal inhibitory concentration (IC50) of chemotherapeutic medicine was predicted by employing the pRRophetic algorithm. A total of 513 CC samples (including 472 tumor samples and 41 normal samples) were collected from the TCGA-GDC database. Significant black modules and 313 candidate genes were considered PC-related genes by accessing WGCNA. Five pivotal genes were established through multiple analyses, which revealed excellent prognostic. The underlying correlation between risk score with tumor mutation burden (TMB) was further explored. In addition, the risk score was obviously correlated with various tumor immune microenvironment (TIME). Also, risk CC samples showed various signaling pathways activity and different pivotal sensitivities to administering chemotherapy. Finally, the biological roles of the CD177 gene were uncovered in CC.
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