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Prognostic model of AU-rich genes predicting the prognosis of lung adenocarcinoma.
Liu, Yong; Pang, Zhaofei; Zhao, Xiaogang; Zeng, Yukai; Shen, Hongchang; Du, Jiajun.
Afiliação
  • Liu Y; Institute of Oncology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
  • Pang Z; Institute of Oncology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
  • Zhao X; Institute of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, China.
  • Zeng Y; Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, China.
  • Shen H; Department of Thoracic Surgery, The Second Hospital of Shandong University, Jinan, Shandong Province, China.
  • Du J; Institute of Oncology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
PeerJ ; 9: e12275, 2021.
Article em En | MEDLINE | ID: mdl-34707942
ABSTRACT

BACKGROUND:

AU-rich elements (ARE) are vital cis-acting short sequences in the 3'UTR affecting mRNA stability and translation. The deregulation of ARE-mediated pathways can contribute to tumorigenesis and development. Consequently, ARE-genes are promising to predict prognosis of lung adenocarcinoma (LUAD) patients.

METHODS:

Differentially expressed ARE-genes between LUAD and adjacent tissues in TCGA were investigated by Wilcoxon test. LASSO and Cox regression analyses were performed to identify a prognostic genetic signature. The genetic signature was combined with clinicopathological features to establish a prognostic model. LUAD patients were divided into high- and low-risk groups by the model. Kaplan-Meier curve, Harrell's concordance index (C-index), calibration curves and decision curve analyses (DCA) were used to assess the model. Function enrichment analysis, immunity and tumor mutation analyses were performed to further explore the underlying molecular mechanisms. GEO data were used for external validation.

RESULTS:

Twelve prognostic genes were identified. The gene riskScore, age and stage were independent prognostic factors. The high-risk group had worse overall survival and was less sensitive to chemotherapy and radiotherapy (P < 0.01). C-index and calibration curves showed good performance on survival prediction in both TCGA (1, 3, 5-year ROC 0.788, 0.776, 0.766) and the GSE13213 validation cohort (1, 3, 5-year ROC 0.781, 0.811, 0.734). DCA showed the model had notable clinical net benefit. Furthermore, the high-risk group were enriched in cell cycle, DNA damage response, multiple oncological pathways and associated with higher PD-L1 expression, M1 macrophage infiltration. There was no significant difference in tumor mutation burden (TMB) between high- and low-risk groups.

CONCLUSION:

ARE-genes can reliably predict prognosis of LUAD and may become new therapeutic targets for LUAD.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PeerJ Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PeerJ Ano de publicação: 2021 Tipo de documento: Article