Identification of genes associated with cancer prognosis in glioma: In silico data analyses of Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA),Journal of Bioinformatics and Computational Biology

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Identification of genes associated with cancer prognosis in glioma: In silico data analyses of Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA)
Journal of Bioinformatics and Computational Biology ( IF 0.9 ) Pub Date : 2021-05-11 , DOI: 10.1142/s0219720021400047
Junjie Lv ₁ , Fubin Ren ₂ , Zhengyu Lv ₁ , Zhiqiang Chang ₁ , Wan Li ₁ , Yuehan He ₁ , Lina Chen ₁

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Glioma is one particular type of brain malignancy which is highly complex and usually has a poor prognosis. Despite the limited diagnostic level of glioma, the survival time of affected patients broadly varies. Here, we conducted a detailed analysis, regarding the differences in patient survival time, to discover potential survival-related genes in glioma as well as their putative regulatory mechanisms. To contextualize the acquisition of these potential prognosis markers in large populations, particularly in China, we combined CGGA and The Cancer Genome Atlas (TCGA) databases to properly identify genes that are significantly related to survival. Our workflow combined a series of analytical approaches, including differential analysis, survival time, co-expression, clinical correlation analysis, ROC curve evaluation and prediction ability. Our results indicate that the four particular genes - PLAT, IGFBP2, BCAT1, SERPINH1 could be used as independent prognostic marker genes. These genes have also shown good prognostic ability in distinct populations, reiterating the robustness and value of these prognostic markers.

更新日期：2021-05-11

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