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GNPNAT1 Predicts Poor Prognosis and Cancer Development in Non-Small Cell Lung Cancer.

AbstractBackground:
Glucosamine-phosphate N-acetyltransferase 1 (GNPNAT1) is a key enzyme in the biosynthetic pathway of uridine diphosphate-N-acetylglucosamine and is upregulated in multiple malignancies. However, its function in cancer biology remains unclear.
Methods:
Using TCGA dataset, this study analysed GNPNAT1 expression in non-small cell lung cancer (NSCLC) and assessed the correlation between GNPNAT1 and NSCLC patient prognosis. MTT and transwell assays were performed to determine the effect of GNPNAT1 on the growth and metastatic ability of lung cancer cells. GNPNAT1 expression was detected using immunohistochemistry in 78 NSCLC patients, and we analysed the correlation among clinicopathological parameters, overall survival (OS) and GNPNAT1 levels. Transcription factors that potentially regulate GNPNAT1 were explored using database analysis. RNF2 expression was verified using immunohistochemistry in NSCLC tissues.
Results:
The results indicated that GNPNAT1 was upregulated in NSCLC, and patients with high GNPNAT1 levels had a poor prognosis. GNPNAT1 overexpression promoted the proliferative and metastatic ability of lung cancer cells, whereas GNPNAT1 knockdown showed the opposite effect. GNPNAT1 expression was upregulated in NSCLC tissues compared to matched normal tissues as assessed by immunohistochemistry. Moreover, GNPNAT1 levels were positively correlated with histological type and pathological stage. The negative correlation between GNPNAT1 levels and OS was confirmed in 78 NSCLC patients. Aberrant RNF2 partly contributed to the upregulation of GNPNAT1 expression in NSCLC.
Conclusion:
These findings suggested that GNPNAT1 was upregulated and played an important role in NSCLC. GNPNAT1 is expected to represent an effective prognostic biomarker for NSCLC patients.
AuthorsYong Feng, Na Li, Yi Ren
JournalCancer management and research (Cancer Manag Res) Vol. 14 Pg. 2419-2428 ( 2022) ISSN: 1179-1322 [Print] New Zealand
PMID35975106 (Publication Type: Journal Article)
Copyright© 2022 Feng et al.

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