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A novel 4-gene signature for overall survival prediction in lung adenocarcinoma patients with lymph node metastasis.
Wang, Yanfang; Zhang, Quanli; Gao, Zhaojia; Xin, Shan; Zhao, Yanbo; Zhang, Kai; Shi, Run; Bao, Xuanwen.
Afiliação
  • Wang Y; 1Ludwig-Maximilians-Universität München (LMU), 80539 Munich, Germany.
  • Zhang Q; Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing, 210009 China.
  • Gao Z; 3Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, 213000 China.
  • Xin S; 1Ludwig-Maximilians-Universität München (LMU), 80539 Munich, Germany.
  • Zhao Y; 4Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany.
  • Zhang K; 5Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016 China.
  • Shi R; 5Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016 China.
  • Bao X; 1Ludwig-Maximilians-Universität München (LMU), 80539 Munich, Germany.
Cancer Cell Int ; 19: 100, 2019.
Article em En | MEDLINE | ID: mdl-31015800
ABSTRACT

BACKGROUND:

Lung adenocarcinoma (LUAD) patients experiencing lymph node metastasis (LNM) always exhibit poor clinical outcomes. A biomarker or gene signature that could predict survival in these patients would have a substantial clinical impact, allowing for earlier detection of mortality risk and for individualized therapy.

METHODS:

With the aim to identify a novel mRNA signature associated with overall survival, we analysed LUAD patients with LNM extracted from The Cancer Genome Atlas (TCGA). LASSO Cox regression was applied to build the prediction model. An external cohort was applied to validate the prediction model.

RESULTS:

We identified a 4-gene signature that could effectively stratify a high-risk subset of these patients, and time-dependent receiver operating characteristic (tROC) analysis indicated that the signature had a powerful predictive ability. Gene Set Enrichment Analysis (GSEA) showed that the high-risk subset was mainly associated with important cancer-related hallmarks. Moreover, a predictive nomogram was established based on the signature integrated with clinicopathological features. Lastly, the signature was validated by an external cohort from Gene Expression Omnibus (GEO).

CONCLUSION:

In summary, we developed a robust mRNA signature as an independent factor to effectively classify LUAD patients with LNM into low- and high-risk groups, which might provide a basis for personalized treatments for these patients.
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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: Cancer Cell Int Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancer Cell Int Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Alemanha