The molecular signatures of lung adenocarcinoma (LUAD) are not well understood. Centromere protein F (CENPF) has been shown to promote oncogenesis in many cancers; however, its role in LUAD has not been illustrated. We explored the role of CENPF in LUAD. CENPF expression level was investigated in public online database firstly, the prognosis of CENPF in LUAD were also assessed by Kaplan-Meier analysis. Then quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed using 13 matched pairs of clinical LUAD tissue samples. Subsequently, the impact of CENPF expression on cell proliferation, cell cycle, apoptosis, colony formation was investigated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), flow cytometric analysis and colony formation assay, respectively. Finally, experimental xenograft lung cancer model of nude mice armpit of right forelimb to determine the effect of CENPF on LUAD tumorigenesis. CENPF mRNA expression was significantly elevated in LUAD tissues compared with adjacent non-tumor lung tissues in Gene Expression Profiling Interactive Analysis (GEPIA) ( < 0.001). Up-regulated CENPF was remarkably positively associated with pathological stage, relapse free survival (RFS) as well as overall survival (OS) of LUAD patients. Besides, CENPF knockdown greatly suppressed A549 cell proliferation, induced S phase arrest, promoted apoptosis and decreased colony numbers of LUAD cells. Furthermore, knockdown of CENPF significantly inhibited the tumor growth of the LUAD cells in an experimental xenograft lung cancer model of nude mice armpit of right forelimb. Taken together, these results demonstrated that CENPF may serve as a potential biomarker of prognostic relevance and a potential therapeutic target for LUAD.
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http://dx.doi.org/10.7150/ijms.49041 | DOI Listing |
PeerJ
July 2024
Department of Clinical Laboratory, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
Objective: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cancer-related deaths worldwide. This study is a review of three molecular biomarkers screened by machine learning that are not only important in the occurrence and progression of lung adenocarcinoma but also have the potential to serve as biomarkers for clinical diagnosis, prognosis evaluation and treatment guidance.
Methods: Differentially expressed genes (DEGs) were identified using comprehensive GSE1987 and GSE18842 gene expression databases.
Biomed Pharmacother
May 2024
Institute of Cancer, Xinqiao Hospital, Army Medical University, Chongqing 400037, China. Electronic address:
Oncol Lett
December 2023
The First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, P.R. China.
Lung adenocarcinoma (LUAD) is a clinically challenging disease due to its poor prognosis and limited therapeutic methods. The aim of the present study was to identify prognosis-related genes and therapeutic targets for LUAD. Raw data from the GSE32863, GSE41271 and GSE42127 datasets were downloaded from the Gene Expression Omnibus database.
View Article and Find Full Text PDFTransl Cancer Res
February 2023
Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background: Centromere proteins (CENPs) form a large protein family. Sixteen proteins in this family are positioned at the centromere throughout the cell cycle. The overexpression of CENPs is common in many cancers and predicts a poor prognosis.
View Article and Find Full Text PDFWorld J Clin Oncol
January 2023
Scientific Research Center, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China.
Background: Lung adenocarcinoma (LUAD) is the most common non-small-cell lung cancer, with a high incidence and a poor prognosis.
Aim: To construct effective predictive models to evaluate the prognosis of LUAD patients.
Methods: In this study, we thoroughly mined LUAD genomic data from the Gene Expression Omnibus (GEO) (GSE43458, GSE32863, and GSE27262) and the Cancer Genome Atlas (TCGA) datasets, including 698 LUAD and 172 healthy (or adjacent normal) lung tissue samples.
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