Literature DB >> 35066671

ACC2 is under-expressed in lung adenocarcinoma and predicts poor clinical outcomes.

Fei-Yuan Yu1, Qian Xu1,2, Qi-Yao Wei1, Hai-Ying Mo1, Qiu-Hua Zhong1, Xiao-Yun Zhao1, Andy T Y Lau3, Yan-Ming Xu4.   

Abstract

PURPOSE: Acetyl-CoA Carboxylases (ACCs) are key fatty acid metabolic enzymes responsible for catalyzing the carboxylation of acetyl-CoA to malonyl-CoA. The role of ACC1 has been associated with tumor biology, but the role of ACC2 in cancer remains largely uncharacterized.
METHODS: We conducted a transcriptomic analysis using GEPIA and Oncomine to study the expression of ACC2 in different cancers. Immunohistochemistry was used to examine the expression of ACC2 in lung cancer tissue microarray, and the correlation between ACC2 expression and clinical parameters was analyzed. Following ACC2 knockdown by RNA interference in A549 and HCC827 cells, Cell Counting Kit‑8 and transwell assays were used to detect cell proliferation and migration. Real-time PCR was used to detect cell cycle-related genes in A549 cells. GEO dataset and KM-plotter database were used to analyze the relationship between ACC2 expression and the prognosis in lung cancer patients.
RESULTS: We found that ACC2 is under-expressed in cancerous tissue and the expression of ACC2 is negatively correlated with tumor size, regional lymph-node metastases, and clinical stage of lung adenocarcinoma patients. In addition, knocking down ACC2 in A549 cells and HCC827 cells can promote cell proliferation and migration, and cell cycle-related genes MAD2L1 and CCNB2 were up-regulated after ACC2 was knockdown in A549 cells. Finally, we found that lung adenocarcinoma patients with under-expressed ACC2 have a worse prognosis.
CONCLUSIONS: Our results suggest that ACC2 is a potential diagnostic and prognostic marker that negatively correlated with clinical outcomes in lung adenocarcinoma.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  ACC2; Acetyl-CoA carboxylase; Lung adenocarcinoma; Prognosis

Year:  2022        PMID: 35066671     DOI: 10.1007/s00432-021-03910-1

Source DB:  PubMed          Journal:  J Cancer Res Clin Oncol        ISSN: 0171-5216            Impact factor:   4.322


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