Affiliation:
1. Hunan University of Chinese Medicine
2. Second Xiangya Hospital of Central South University
3. Hunan Cancer Hospital
4. Xiangya Hospital Central South University
Abstract
Abstract
Background
Stress granules formation is closely associated with the progression of hepatocellular carcinoma (HCC). Factors determination this process remain to be elucidated. In this study, stress granule-related genes were validated as a predictor of HCC.
Methods
The stress granules-related associated genes were collected from the MSGP database and the MsigDB database. A novel prognostic risk scoring model were constructed by paired gene signature method. We identified eukaryotic translation initiation factor 4A3 (EIF4A3) and karyopherin subunit alpha 2 (KPNA2) as candidate prognostic biomarkers, and their correlation with both prognosis and immune infiltration in HCC were evaluated. The expression of EIF4A3 and KPNA2 in HCC tissues was detected through immunohistochemistry (IHC).
Results
Through pairing of all DESG gene, we obtained a total of 16251 significance pairs. Subsequently, 93 pairs of all pairs containing EIF4A3 were extracted in this research. As a stress granule formation regulator, KPNA2 displayed the greatest correlations with EIF4A3 in HCC. Hyperactivated EIF4A3 and KPNA2 is associated with the poor clinical outcome of HCCs after hepatic resection. Involvement of EIF4A3 and KPNA2 in immune infiltration have been showed.
Conclusion
Our study identified coexistence of EIF4A3 and KPNA2 dysregulation inform poor clinical outcomes in HCC.
Publisher
Research Square Platform LLC
Reference35 articles.
1. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA: a cancer journal for clinicians. 2023;73(1):17–48.
2. Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma;Sun Y;Cell,2021
3. Dynamic risk profiling of HCC recurrence after curative intent liver resection;Ivanics T;Hepatology,2022
4. Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning;Shi JY;Gut,2021
5. Song MS, Grabocka E. Stress Granules in Cancer. Reviews of physiology, biochemistry and pharmacology. 2023;185:25–52.