Distinct expression pattern and prognostic values of pituitary tumor transforming gene family genes in non‑small cell lung cancer
Members of the pituitary tumor transforming gene (PTTG) family, including PTTG1, PTTG2 and PTTG3P, exhibit pivotal roles in the onset and progression of certain types of human cancer. However, to the best of our knowledge, a systematic study regarding the expression pattern and the prognostic values...
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Veröffentlicht in: | Oncology letters 2019-11, Vol.18 (5), p.4481-4494 |
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Zusammenfassung: | Members of the pituitary tumor transforming gene (PTTG) family, including PTTG1, PTTG2 and PTTG3P, exhibit pivotal roles in the onset and progression of certain types of human cancer. However, to the best of our knowledge, a systematic study regarding the expression pattern and the prognostic values of PTTG family genes in non-small cell lung cancer (NSCLC) remains to be performed. The expression levels of PTTG family genes in NSCLC were successively determined using the Gene Expression Profiling Interactive Analysis, UALCAN and Oncomine databases. Subsequently, the Kaplan-Meier plotter database was used to assess the prognostic value of the PTTG family genes in patients with NSCLC, and to determine the associations between PTTG expression levels and the prognosis of patients based on different clinicopathological features, including cancer stage, grade, chemotherapy, radiotherapy, lymph node status, smoking history, and sex. PTTG1 was identified to be significantly upregulated in NSCLC in all three databases, whereas PTTG2 and PTTG3P were significantly upregulated in NSCLC in only the UALCAN database. Patients with NSCLC with higher expression levels of the three PTTG genes demonstrated shorter overall survival times. In summary, the results of the present study suggested that increased expression of PTTG family genes may serve as promising prognostic biomarkers for patients with NSCLC. Key words: pituitary tumor transforming gene, non-small cell lung cancer, Kaplan-Meier plotter, prognosis, in silico analysis, Oncomine, UALCAN, gene expression profiling interactive analysis |
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ISSN: | 1792-1074 1792-1082 |
DOI: | 10.3892/ol.2019.10844 |