Identification of the collagen family as prognostic biomarkers and immune-associated targets in gastric cancer.

2020 
Abstract Background Gastric cancer has extremely high morbidity and mortality. Currently, it is lack of effective biomarkers and therapeutic targets for guiding clinical treatment. In this study, we aimed to identify novel biomarkers and therapeutic targets for gastric cancer. Methods Differentially expressed genes (DEGs) between gastric cancer and normal tissues were obtained from Gene Expression Omnibus (GEO). Core genes were identified by constructing protein-protein interaction network of DEGs. The expression of core genes was verified in Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN and clinical samples. Further, the mutation, DNA methylation, prognostic value, and immune infiltration of core genes were validated by cBioPortal, MethSurv, Kaplan-Meier plotter, and Tumor Immune Estimation Resource (TIMER) databases. Additionally, drug response analysis was performed by Cancer Therapy Response Portal (CTRP). Results A total of seven collagen family members were identified as core genes among upregulated genes. And copy number amplification may be involved in the upregulation of COL1A1 and COL1A2. Importantly, the collagen family was associated with the poor prognosis of patients with metastasis. Among them, COL1A1 had a higher hazard ratio (HR) for overall survival than other members (HR = 2.33). The correlation between DNA methylation levels at CpG sites of collagen family members and the prognosis was verified in gastric cancer. Besides, collagen family expression was positively correlated with macrophages infiltration and the expression of M2 macrophages markers. Further, collagen expression was related to the sensitivity and resistance of gastric cancer cell lines to certain drugs. Conclusions The collagen family, especially COL1A1, COL1A2, and COL12A1, may act as potential prognostic biomarkers and immune-associated therapeutic targets in gastric cancer.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    71
    References
    6
    Citations
    NaN
    KQI
    []