ArticleCancer cell international2021
Identification of DNA repair-related genes predicting pathogenesis and prognosis for liver cancer.
Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed, 27 citations in OpenAlex.
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- Applications of artificial intelligence and machine learning models in the prognosis and diagnosis of ovarian cancer.Frontiers in oncology · 2026Review
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- Establishment of the Prognostic Signature with Genes Related to G2/M Checkpoint in Hepatocellular Carcinoma.Biochemical genetics · 2025Article
- Single-cell landscape of peripheral immune cells in MASLD/MASH.Hepatology communications · 2025Article
- Interaction of STIL with FOXM1 regulates SF3A3 transcription in the hepatocellular carcinoma development.Cell division · 2025Article
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- Unveiling the role of UPF3B in hepatocellular carcinoma: Potential therapeutic target.Cancer science · 2024Article
- Identification of RFC4 as a potential biomarker for pan-cancer involving prognosis, tumour immune microenvironment and drugs.Journal of cellular and molecular medicine · 2024Article
- Prognostic and immunological roles of heat shock protein A4 in lung adenocarcinoma.World journal of clinical oncology · 2024Article
- Fatty acid binding protein 5 is a novel therapeutic target for hepatocellular carcinoma.World journal of clinical oncology · 2024Article
- Vesicle-mediated transport-related genes predict the prognosis and immune microenvironment in hepatocellular carcinoma.Journal of Cancer · 2024Article
- Knockdown of RFC4 inhibits the cell proliferation of nasopharyngeal carcinoma in vitro and in vivo.Frontiers of medicine · 2023Article
- A pan-cancer analysis of pituitary tumor-transforming 3, pseudogene.American journal of translational research · 2023Article
- Article
- CircSCAP interacts with SF3A3 to inhibit the malignance of non-small cell lung cancer by activating p53 signaling.Journal of experimental & clinical cancer research : CR · 2022Article
- Identification of DNA Repair-Related Genes Predicting Clinical Outcome for Thyroid Cancer.Journal of oncology · 2022Article
- DNA Repair and Replication-Related Gene Signature Based on Tumor Mutation Burden Reveals Prognostic and Immunotherapy Response in Gastric Cancer.Journal of oncology · 2022Article
- A Panel of E2F Target Gene Signature Predicting the Prognosis of Hepatocellular Carcinoma.Frontiers in genetics · 2022Article
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6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundLiver cancer (LC) is one of the most fatal cancers throughout the world. More efficient and sensitive gene signatures that could accurately predict survival in LC patients are vitally needed to promote a better individualized and effective treatment. MATERIAL/
methods422 LC and adjacent normal tissues with both RNA-Seq and clinical data in TCGA were embedded in our study. Gene set enrichment analysis (GSEA) was applied to identify genes and hallmark gene sets that are more valuable for liver cancer therapy. Cox regression analysis was used to identify genes related to overall survival (OS) and build the prediction model. cBioPortal database was used to examine the alterations of the panel mRNA signature. ROC curves and Kaplan-Meier curves were used to validate the prediction model. Besides, the expression of the genes in the model were validated using quantitative real-time PCR in clinical tissue specimens.
resultsThe panel of DNA repair-related mRNA signature consisted of seven mRNAs: RFC4 (replication factor C subunit 4), ZWINT (ZW10 interacting kinetochore protein), UPF3B (UPF3B regulator of nonsense mediated mRNA decay), NCBP2 (nuclear cap binding protein subunit 2), ADA (adenosine deaminase), SF3A3 (splicing factor 3a subunit 3) and GTF2H1 (general transcription factor IIH subunit 1). On-line analysis of cBioPortal database found that the expression of the panel mRNA has a wide variation ranging from 7 to 10%. All the mRNAs were significantly upregulated in LC tissues compared to normal tissues (P < 0.05). The risk model is closely related to the OS of LC patients. The hazard ratio (HR) is 2.184 [95% CI (confidence interval) 1.523-3.132] and log-rank P-value < 0.0001. For clinical specimen validation, we found that all of the genes in the model upregulated in liver cancer tissues versus normal liver tissues, which was consistent with the results predicted.
conclusionsOur study demonstrated a mRNA signature including seven mRNA for prognosis prediction of LC. This panel gene signature provides a new criterion for accurate diagnosis and therapeutic target of LC.
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