Identifying Prognostic Significance of RCL1 and Four-Gene Signature as Novel Potential Biomarkers in HCC Patients

Area of Science:

• Oncology
• Genomics
• Biomarker Discovery

Background:

• Hepatocellular carcinoma (HCC) is a highly aggressive cancer with poor survival rates.
• Current methods for monitoring HCC treatment and prognosis are limited.
• There is a critical need for reliable prognostic biomarkers in HCC management.

Purpose of the Study:

• To identify novel molecular biomarkers for predicting clinical outcome in HCC.
• To develop a robust prognostic model for hepatocellular carcinoma.
• To investigate the role of RNA terminal phosphate cyclase like 1 (RCL1) and long noncoding RNAs in HCC prognosis.

Main Methods:

• Utilized transcriptome and gene expression data from TCGA, ICGC, and GEO databases.
• Constructed a four-gene prognostic model using the random forest method based on RCL1 expression.
• Evaluated prognostic value using Kaplan-Meier analysis and assessed correlations with immune infiltration, TMB, and MSI.

Main Results:

• Aberrant RCL1 expression correlates with clinical outcome, immune infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI) in HCC.
• Identified significant co-expression of long noncoding RNAs (AC079061, AL354872, LINC01093) with RCL1 in HCC.
• Validated a four-gene signature (SPP1, MYBL2, TRNP1, FTCD) as an independent prognostic factor with high model robustness (AUC 0.7-0.8).

Conclusions:

• RCL1 and a novel four-gene signature serve as effective prognostic biomarkers for HCC.
• The developed model can assist in the individualized treatment monitoring of HCC patients.
• This research provides valuable tools for improving HCC patient management and clinical decision-making.