AUTHOR=Chen Liang , Peng Tianchen , Luo Yongwen , Zhou Fenfang , Wang Gang , Qian Kaiyu , Xiao Yu , Wang Xinghuan 

TITLE=ACAT1 and Metabolism-Related Pathways Are Essential for the Progression of Clear Cell Renal Cell Carcinoma (ccRCC), as Determined by Co-expression Network Analysis

JOURNAL=Frontiers in Oncology

VOLUME=Volume 9 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2019.00957

DOI=10.3389/fonc.2019.00957

ISSN=2234-943X

ABSTRACT=Kidney cancer ranks as one of the top ten cause of cancer deaths; this cancer is difficult to detect, difficult to treat and poorly understood. The most common subtype of kidney cancer is clear cell renal cell carcinoma (ccRCC) and its progression is influenced by complex gene interactions. Few clinical have investigated molecular markers associated with the progression of ccRCC. In this study, we collected microarray profiles of 72 ccRCC and matched normal samples to identify differentially expressed genes (DEGs). Then a weighted gene coexpression network analysis (WGCNA) was conducted to identify coexpressed gene modules. By relating all coexpressed modules to clinical features, we found that the brown module and Fuhrman grade had the highest correlation (r = -0.8, p = 1e-09). Thus, the brown module was regarded as a clinically significant module and analyzed subsequently. Functional annotation showed that the brown module focused on metabolism-related biological process and pathway, such as fatty acid oxidation and amino acid metabolism. Then, we performed a protein-protein interaction (PPI) network to identify the hub nodes in the brown module. It is worth noting that only one candidate, acetyl-CoA acetyltransferase (ACAT1), was considered to be the final target most relevant to the Fuhrman grade of ccRCC by applying the intersection of hub genes in the coexpressed network and the PPI network. ACAT1 was subsequently validated using another two external microarray datasets and the TCGA dataset. Intriguingly, validation results indicated that ACAT1 was negatively correlated with four grades of ccRCC, which was also consistent with our results from qRT-PCR analysis and immunohistochemistry staining of clinical samples. Overexpression of ACAT1 inhibited the proliferation and migration of human ccRCC cells in vitro. In addition, the Kaplan-Meier survival curve showed that patients with lower expression of ACAT1 showed a significantly lower overall survival rate and disease-free survival rate, indicating that ACAT1 could act as a prognostic and recurrence/progression biomarker of ccRCC. In summary, we found and confirmed that ACAT1 might help to identify the progression of ccRCC, which might have important clinical implications for enhancing risk stratification, therapeutic decision and prognosis prediction in ccRCC patients.