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  • Title: Survival prediction for patients with lung adenocarcinoma: A prognostic risk model based on gene mutations.
    Author: Geng H, Li S, Guo Y, Yan F, Han Y, Xu M, Cui Y.
    Journal: Cancer Biomark; 2020; 27(4):525-532. PubMed ID: 32083571.
    Abstract:
    BACKGROUND: Lung adenocarcinoma is the most common type of lung cancer, and it is one of the most aggressive and rapidly fatal tumor types. OBJECTIVE: To identify a signature mutation genes for prognostic prediction of lung adenocarcinoma. METHODS: Four hundred and sixty-two lung adenocarcinoma cases were screened out and downloaded from TCGA database. Mutation data of 18 targeted genes were detected by MuTect. LASSO-COX model was used to screen gene loci, and then a prognosis model was established. Afterwards, 40 clinical patients of lung adenocarcinoma were collected to verify the mutation features and the predictive function of the above prognostic model. The mutations of above 18 genes were sequenced with targeted next generation sequencing (NGS) and analyzed with GATK and MuTect. RESULTS: TP53 (282, 32.38%), NF1 (82, 9.41%) and EGFR (80, 9.18%) were the top 3 most frequent mutation genes. A total of 7 variables were screened out after lasso-COX analysis (tumor stage, age, diagnostic type, SMARCA4, GNAS, PTCH2, TSC2). SMARCA4, GNAS and TSC2 were a gene mutation signature to predict a poor prognosis. CONCLUSIONS: We established a prognostic model for lung adenocarcinoma, and further concluded that SMARCA4, GNAS and TSC2 were a gene signature which plays a prognostic role.
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