Construction of prognostic model of lung cancer based on transcription factors and its clinical significance

doi:10.3877/cma.j.issn.1674-6902.2022.04.002

Abstract

Abstract:

Objective

To investigated the relationship between aberrant expression of transcription factor genes (TFGs) and tumor prognosis in lung adenocarcinoma (LUAD), and to explore potential tumor transcriptional therapeutic targets.

Methods

Bioinformatics was used to mine the transcriptome and clinical data of lung adenocarcinoma (LUAD) in the Cancer Genome Atlas program (TCGA) database. R language software was adopted to screen the differentially expressed TFGs between LUAD and paracancerous tissues. Then, GO and KEGG enrichment analyses were performed. COX regression was applied to construct a risk score model to predict the prognosis of LUAD patients.

Results

391 TFGs were differentially expressed in LUAD tissues. These TFGs are mainly involved in biological processes and signal pathways such as embryonic development, transcriptional regulation and pluripotent regulation of stem cells. Univariate COX regression analysis showed that 11 TFGs were associated with prognosis. Five TFGs (IRX4, ID3, CDX2, E2F7, NPAS2) were further selected via stepwise multivariate COX regression analysis to construct the risk score model. Survival analysis revealed that the overall survival time of low-risk group was significantly longer than that of high-risk group. Risk score could be used as a risk factor to predict the prognosis of LUAD (hazard ratio=1.906, P<0.01), but there was no correlation between age, gender and tumor stage and prognosis (P>0.05).

Conclusion

Lots of transcription factor genes in LUAD have abnormal expression, which is closely concern to the prognosis of patients. The risk score model based on the 5-TFGs could effectively predict the LUAD patients prognosis and provide a new reference for clinical diagnosis and treatment of lung cancer.

Key words: Bronchial lung cancer, Transcription factors, Prognostic model, Clinical significance

Xiaomei He, Xingmin Wang, Junzhi Xiong, Rongrong Chen, Qian Min, Kebin Zhang, Yuanyuan Li. Construction of prognostic model of lung cancer based on transcription factors and its clinical significance[J]. Chinese Journal of Lung Diseases(Electronic Edition), 2022, 15(04): 462-467.

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Figures/Tables 5

References 38

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