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BACKGROUND The aim of this study was to explore the expression levels of family with sequence similarity 83, member A (FAM83A) in lung adenocarcinoma (LUAD) and investigate its clinical prognostic value. MATERIAL AND METHODS Bioinformatics mining methods were used to predict the differential expression levels of FAM83A mRNA in LUAD and normal lung tissues based on the TCGA and Oncomine databases. Immunohistochemical staining was performed to demonstrate the FAM83A protein expression levels in 83 cases of LUAD combined with paired normal lung tissues. The correlation between clinicopathologic factors and FAM83A differential expression levels in LUAD was explored by the chi-square test. Kaplan-Meier univariate and Cox multivariate survival analyses were performed to investigate the clinical prognostic value of FAM83A expression in LUAD patients. RESULTS Results from TCGA and Oncomine databases revealed that FAM83A mRNA expression level was significantly higher in LUAD than that in normal lung tissues (both P<0.05). Immunohistochemical findings demonstrated that the high positive rate of FAM83A in LUAD was 73.49% (61/83), while that of matched normal lung tissues was only 22.89% (19/83). Moreover, LUAD patients with FAM83A mRNA or high protein levels had dramatically lower OS times than those with FAM83A mRNA or low protein levels (All P<0.05). Lastly, Cox multivariate survival analysis showed that FAM83A differential expression level (low vs. high) was the only independent factor predicting the prognosis of LUAD patients (P=0.001). CONCLUSIONS FAM83A was overexpressed in LUAD, and FAM83A overexpression could be used as an independent factor of poor prognosis in LUAD patients.
Pubmed ID: 31175804
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View all literature mentionsOncomine Research Platform is a partially-commercial suite of products for online cancer gene expression analysis dedicated to the academic and non-profit research community. Oncomine combines a rapidly growing compendium of 20,000+ cancer transcriptome profiles with a sophisticated analysis engine and a powerful web application for data-mining and visualization. Oncomine facilitates rapid and reliable biomarker and therapeutic target discovery, validation and prioritization. Oncomine was developed by physicians, scientists, and software engineers at the University of Michigan and is now fully supported for the academic and non-profit research community by Compendia Bioscience.
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