Expression profiles analysis identifies the values of carcinogenesis and the prognostic prediction of three genes in adrenocortical carcinoma

Abstract

Adrenocortical carcinoma (ACC) is a rare disease associated with a poor prognosis. Furthermore, the underlying molecular mechanism of carcinogenesis is poorly understood, and prognostic prediction of ACC has low accuracy. In the present study, a bioinformatics approach was used to investigate the molecular mechanisms and prognosis of ACC. Samples of adrenal tumors were collected from patients undergoing adrenalectomy at the Department of Urology, the First Hospital of China Medical University. The analyzed gene datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database. Following this, the differentially expressed genes (DEGs) were included in Gene Ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction network and survival analyses. MTT colorimetric assays, colony formation assays and 5-ethynyl-20-deoxyuridine incorporation assays were also conducted to evaluate ACC cell proliferation. The identified DEGs included 20 downregulated genes and 51 upregulated genes, which were highly associated with the cell cycle, organelle fission, chromosome segregation, cell division and spindle stability. The top 14 hub genes were subsequently confirmed by reverse transcription-quantitative polymerase chain reaction in ACC and adrenocortical adenoma samples. It was identified that the nuclear division cycle 80, cyclin B2 and topoisomerase 2-α may serve important roles in adrenocortical tumor development. Furthermore, these three genes predicted overall survival and recurrence-free survival in patients with ACC from the TCGA cohort. The findings identified three novel genes that have important roles in carcinogenesis and in the prognostic prediction of ACC.

Identification and Validation of a Novel Prognosis Prediction Model in Adrenocortical Carcinoma by Integrative Bioinformatics Analysis, Statistics, and Machine Learning

“…Two m6A-related signatures, which might be used as independent prognostic factors in evaluating the prognosis of ACC patients, were also established (Jin et al, 2021;Shen et al, 2021). Among the six hub genes we identified, two, including ASPM (Yuan et al, 2018) and CCNB2 (Gao et al, 2019;Guo et al, 2020), were already regarded as prognostic biomarkers in previous studies. Yuan et al screened out 12 hub genes including ASPM, which were associated with the progression and prognosis of ACC.…”

“…Yuan et al screened out 12 hub genes including ASPM, which were associated with the progression and prognosis of ACC. Two recent studies proved that CCNB2 was associated with worse OS of ACC ( Gao et al, 2019 ; Guo et al, 2020 ). As for the rest of the four genes, the relationship between them and prognosis of ACC has never been reported by previous studies, which might be novel prognostic biomarkers for ACC.…”

A Hypoxia Signature for Predicting Prognosis and Tumor Immune Microenvironment in Adrenocortical Carcinoma

“…It is reported that tumors with the expression of Ki67 higher than 10% have significantly poor prognosis than those with lower than 10% in ACC patients [ 12 ]. The nuclear division cycle 80, cyclin B2, and miRNAs have been reported to involve in carcinogenesis and progression of ACC, predicting OS in patients with ACC [ 13 , 14 ]. Additionally, PTTG1 and GLUT1 had been proven as a marker of poor survival in ACC [ 15 , 16 ].…”

The Role of Biomarkers in Adrenocortical Carcinoma: A Review of Current Evidence and Future Perspectives

“…Results have accentuated twelve hub genes (ANLN, ASPM, CDCA5, CENPF, FOXM1, KIAA0101, MELK, NDC80, PRC1, RACGAP1, SPAG5, TPX2) which have good distinctive power for malignancy and correlate with unfavorable prognosis and tumor stages [169]. With bioinformatics analysis highly associated with the cell cycle, organelle fission, chromosome segregation, cell division and spindle stability, 71 genes were reported [170]. Beside the abovementioned, these are BIRC5, CDK1, EZH2, MAD2L1, NCAPG, PBK, RRM2 and TOP2A [170].…”

“…With bioinformatics analysis highly associated with the cell cycle, organelle fission, chromosome segregation, cell division and spindle stability, 71 genes were reported [170]. Beside the abovementioned, these are BIRC5, CDK1, EZH2, MAD2L1, NCAPG, PBK, RRM2 and TOP2A [170]. The nuclear division cycle 80, cyclin B2 and topoisomerase 2-α are possibly included in tumor development, predict overall survival and recurrence-free survival in patients with ACC [170].…”