Peer Review #3 of "Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA (v0.2)"

Abstract

Background. Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. Methods. Gene TPM (transcripts per million) data were downloaded from the UCSC Xena database, which included ACC (The Cancer Genome Atlas (TCGA), n = 77) and normal samples (Genotype Tissue Expression (GTEx), n = 128). We used weighted gene co-expression network analysis (WGCNA) to identify gene connections. Overall survival (OS) was determined using the univariate Cox model. A protein-protein interaction (PPI) network was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING). Results. To determine the critical genes involved in ACC progression, we obtained 2,953 significantly differentially expressed genes (DEGs) and nine modules. Among them, the blue module demonstrated significant correlation with the "Stage" of ACC. Enrichment analysis revealed that genes in the blue module were mainly enriched in cell division, cell cycle, and DNA replication. Combined with the PPI and co-expression networks, we identified four hub genes (i.e., TOP2A, TTK, CHEK1, and CENPA) that were highly expressed in ACC and negatively correlated with OS. Thus, these identified genes may play important roles in the progression of ACC and serve as potential biomarkers for future diagnosis.