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Dysfunction of Sister Chromatids Separation Promotes Progression of Hepatocellular Carcinoma According to Analysis of
Baozhen Sun1, Guibo Lin2, Degang Ji1
1Department of Hepatopancreatobiliary, China-Japan Union Hospital of Jilin University, Changchun, China.
Abstract:
Despite studying the various molecular mechanisms of hepatocellular carcinoma (HCC), effective drugs and biomarkers in HCC therapy are still scarce. The present study was designed to investigate dysregulated pathways, novel biomarkers and therapeutic targets for HCC. The gene expression dataset of GSE14520, which included 362 tumor and their paired non-tumor tissues of HCC, was extracted for processing by the Robust multi-array average (RMA) algorithm in the R environment. SAM methods were leveraged to identify differentially expressed genes (DEGs). Functional analysis of DEGs was performed using DAVID. The GeneMania and Cytohubba were used to construct the PPI network. To avoid individual bias, GSEA and survival analysis were employed to verify the results. The results of these analyses indicated that separation of sister chromatids was the most aberrant phase in the progression of HCC, and the most frequently involved genes, EZH2, GINS1, TPX2, CENPF, and BUB1B, require further study to be used as drug targets or biomarkers in diagnosis and treatment of HCC.
Insights
This study identifies the separation of sister chromatids as a key aberrant phase in hepatocellular carcinoma (HCC) progression. Genes like EZH2 and GINS1 show potential as novel biomarkers and therapeutic targets for HCC.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Hepatocellular carcinoma (HCC) remains a significant health challenge with limited effective therapeutic drugs and biomarkers.
- Understanding the molecular underpinnings of HCC is crucial for developing targeted treatments.
Purpose of the Study:
- To investigate dysregulated molecular pathways in HCC.
- To identify novel biomarkers for HCC diagnosis and prognosis.
- To discover potential therapeutic targets for HCC treatment.
Main Methods:
- Utilized the Robust multi-array average (RMA) algorithm on the GSE14520 gene expression dataset (362 tumor and paired non-tumor HCC tissues).
- Employed Significance Analysis of Microarrays (SAM) to identify differentially expressed genes (DEGs).
- Performed functional enrichment analysis (DAVID), protein-protein interaction (PPI) network construction (GeneMANIA, Cytohubba), Gene Set Enrichment Analysis (GSEA), and survival analysis.
Main Results:
- Identified the separation of sister chromatids as the most significantly aberrant phase during HCC progression.
- Highlighted frequently involved genes in this aberrant phase, including EZH2, GINS1, TPX2, CENPF, and BUB1B.
- Confirmed findings through GSEA and survival analyses to mitigate individual bias.
Conclusions:
- The identified genes (EZH2, GINS1, TPX2, CENPF, BUB1B) are strongly implicated in HCC pathogenesis.
- These genes represent promising candidates for further investigation as diagnostic biomarkers and therapeutic targets in hepatocellular carcinoma.
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