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Prognostic significance of sites of extrathoracic metastasis in patients with non-small cell lung cancer.

ABSTRACT: Metastatic non-small cell lung cancer (NSCLC) continues to have a poor prognosis despite recent advances in both targeted radiotherapy methodologies such as stereotactic body radiotherapy (SBRT) and immunotherapies. The impact of location of metastatic disease in patients with NSCLC has not been investigated; we aimed to investigate this using the Surveillance, Epidemiology, and End Results (SEER) database.We included 39,910 patients from the SEER database treated for M1b NSCLC from 2010-2013. We identified patients with metastatic disease in the brain, lung, liver, and bone. We used Kaplan-Meier analyses and Cox proportional hazards models to assess the impact of varying sites of metastatic disease on overall survival (OS).Patients with disease coded as in the brain without other disease in the lung, liver, or bone had improved OS relative to all other comers with M1b disease (HR =0.84, 95% CI, 0.84-0.90, P<0.001). Likewise, patients with disease coded as in the bone without other disease in the lung, liver, or brain had improved OS relative to all other comers with M1b disease (HR =0.89, 95% CI, 0.86-0.92, P<0.001).This hypothesis-generating analysis suggests that patients with limited metastatic NSCLC to the bone or brain may particularly benefit from aggressive upfront therapies.

SUBMITTER: Bates JE

PROVIDER: S-EPMC5543004 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Project description:Background:Lung cancer has been a common malignant tumor with a leading cause of morbidity and mortality, current molecular targets are woefully lacking comparing to the highly progressive cancer. The study is designed to identify new prognostic predictors and potential gene targets based on bioinformatic analysis of Gene Expression Omnibus (GEO) database. Methods:Four cDNA expression profiles GSE19188, GSE101929, GSE18842 and GSE33532 were chosen from GEO database to analyze the differently expressed genes (DEGs) between non-small cell lung cancer (NSCLC) and normal lung tissues. After the DEGs functions were analyzed, the protein-protein interaction network (PPI) of DEGs were constructed, and the core gene in the network which has high connectivity degree with other genes was identified. We analyzed the association of the gene with the development of NSCLC as well as its prognosis. Lastly we explored the conceivable signaling mechanism of the gene regulation during the development of NSCLC. Results:A total of 92 up regulated and 214 down regulated DEGs were shared in four cDNA expression profiles. Based on their PPI network, TOP2A was connected with most of other genes and was selected for further analysis. Kaplan-Meier overall survival analysis (OS) revealed that TOP2A was associated with worse NSCLC patients survival. And both GEPIA analysis and immunohistochemistry experiment (IHC) confirmed that TOP2A was aberrant gain of expression in cancer comparing to normal tissues. The clinical significance of TOP2A and probable signaling pathways it involved in were further explored, and a positive correlation between TOP2A and TPX2 expression was found in lung cancer tissues. Conclusion:Using bioinformatic analysis, we revealed that TOP2A could be adopted as a prognostic indicator of NSCLC and it potentially regulate cancer development through co-work with TPX2. However, more detailed experiments are needed to clarify its drug target role in clinical medical use.

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Prognostic significance of sites of extrathoracic metastasis in patients with non-small cell lung cancer.

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