Dataset Information

Promising diagnostic and prognostic value of six genes in human hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Ample data have been reported to unravel the carcinogenesis over the past decades. Although pinpointing the cause of the HCC is challenging, this in and of itself may not be an insuperable problem. Indeed, the emergence of novel molecular targets has given rise to targeted therapy for HCC. Compared to traditional treatments, drugs with molecularly targeted agents are considered an optimal way to treat HCC. However, targeted approaches are currently limited among HCC patients. In our work, we explored more potential genes for targeted treatment of HCC. Initially, differentially expressed genes (DEGs) were identified in gene expression profiling interactive analysis (GEPIA) and NetworkAnalyst. Subsequently, 10 key genes were selected through enrichment analysis and PPI network construction. Based on the GEPIA and Oncomine databases, six upregulated genes were selected. High protein expression of these six genes were confirmed through the Human Protein Atlas database. In addition, these six genes were associated with unfavorable overall survival and progression-free survival based on Kaplan-Meier plotter bioinformatics. Moreover, gene expression was closely related to the tumor stages and pathological grades, as determined with UALCAN. More importantly, PTTG1, UBE2C, and ZWINT were identified as potential targets of anti-cancer drugs using cBioPortal. qPCR and western blot assays were used to show the high expression levels of the latter three genes in HCC cell lines. Collectively, these findings are expected to provide a theoretical basis for and give novel insights into clinical research of HCC.

SUBMITTER: Zhang G

PROVIDER: S-EPMC7191178 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Promising diagnostic and prognostic value of six genes in human hepatocellular carcinoma.

Zhang Guanqi G Kang Zhengchun Z Mei Hongliang H Huang Zhiyuan Z Li Hanjun H

American journal of translational research 20200415 4

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Ample data have been reported to unravel the carcinogenesis over the past decades. Although pinpointing the cause of the HCC is challenging, this in and of itself may not be an insuperable problem. Indeed, the emergence of novel molecular targets has given rise to targeted therapy for HCC. Compared to traditional treatments, drugs with molecularly targeted agents are considered an optimal way to treat HCC. However, t ...[more]

PMID: 32355538

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Project description:Background: Mitophagy has been found to play a significant part in the cancer process in a growing number of studies in recent years. However, there is still a lack of study on mitophagy-related genes' (MRGs) prognostic potential and clinical significance in hepatocellular carcinoma (HCC). Methods: We employed bioinformatics and statistical knowledge to examine the transcriptome data of HCC patients in the TCGA and GEO databases, with the goal of constructing a multigene predictive model. Then, we separated the patients into high- and low-risk groups based on the score. The model's dependability was determined using principal components analysis (PCA), survival analysis, independent prognostic analysis, and receiver operating characteristic (ROC) analysis. Following that, we examined the clinical correlations, pharmacological treatment sensitivity, immune checkpoint expression, and immunological correlations between patients in high and low risk groups. Finally, we evaluated the variations in gene expression between high- and low-risk groups and further analyzed the network core genes using protein-protein interaction network analysis. Results: Prognostic models were built using eight genes (OPTN, ATG12, CSNK2A2, MFN1, PGAM5, SQSTM1, TOMM22, TOMM5). During validation, the prognostic model demonstrated high reliability, indicating that it could accurately predict the prognosis of HCC patients. Additionally, we discovered that typical HCC treatment medicines had varying impacts on patients classified as high or low risk, and that individuals classified as high risk are more likely to fail immunotherapy. Additionally, the high-risk group expressed more immunological checkpoints. The immunological status of patients in different risk categories varies as well, and patients with a high-risk score have a diminished ability to fight cancer. Finally, PPI analysis identified ten related genes with potential for research. Conclusion: Our prognostic model had good and reliable predictive ability, as well as clinical diagnosis and treatment guiding significance. Eight prognostic MRGs and ten network core genes merited further investigation.

Dataset Information

Promising diagnostic and prognostic value of six genes in human hepatocellular carcinoma.

Publications

Promising diagnostic and prognostic value of six genes in human hepatocellular carcinoma.

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