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Updated: Oct 4, 2025

Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression
Published on: March 17, 2020
The roles of risk model based on the 3-XRCC genes in lung adenocarcinoma progression
Qun-Xian Zhang1, Ye Yang2, Heng Yang1,3
1Department of Cardiothoracic Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
Background:
The abnormal expression of deoxyribonucleic acid (DNA) repair genes might be the cause of tumor development and resistance of malignant cells to chemotherapeutic drugs. A risk model based on the X-ray repair of cross-complementary (XRCC) genes was constructed to improve the diagnosis and treatment of lung adenocarcinoma (LUAD) patients.
Methods:
The expression levels, diagnostic values, and prognostic values of XRCC genes were identified, and the roles and regulatory mechanisms of the risk model based on the XRCC4/5/6 in LUAD progression was explored via The Cancer Genome Atlas (TCGA) and Oncomine databases.
Results:
XRCC1/2/3/4/5/6, XRCC7 (PRKDC), and XRCC9 (FANCG) were overexpressed, and had diagnostic value for LUAD. The XRCC genes were involved in DNA repair, and participated in the regulation of non-homologous end-joining, homologous recombination, etc. The overall survival (OS), tumor (T) stage, and survival status of patients were significantly different between the Cluster1 and Cluster2 groups. XRCC4/5/6 were independent risk factors affecting the prognosis of LUAD patients. The risk score was related to the prognosis, sex, clinical stage, T, lymph node (N), and metastasis (M) stage, as well as the survival status of LUAD patients. The clinical stage and risk score were independent risk factors for poor prognosis in LUAD patients. The risk model was involved in RNA degradation, cell cycle, basal transcription factors, DNA replication etc. The risk scores were significantly correlated with the expression levels of TGFBR1, CD160, TNFSF4, TNFRSF14, IL6R, CXCL16, TNFRSF25, TAPBP, CCL16, and CCL14.
Conclusions:
The risk model based on the XRCC4/5/6 genes could predict the progression of LUAD patients.
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