Hyung Seok Kim, Jung Hwan Yoon, Ji Yi Choi, Moon Gyeong Yoon, Geum Ok Baek, Minji Kang, Se Ha Jang, Won Park, Yunjin Go, Jestlin Tianthing Ng, Suk Woo Nam, Jee-Yeong Jeong, Ji Eun Han, Hyo Jung Cho, Su Bin Lim, Soon Sun Kim, Jae Youn Cheong, Jung Woo Eun
Clin Mol Hepatol 2025;31(3):914-934. Published online February 6, 2025
Background/Aims Hepatocellular carcinoma (HCC) is characterized by high recurrence and mortality, necessitating the identification of reliable biomarkers. In this study, we aimed to identify the predictive gene signatures for HCC recurrence and evaluate the efficiency of GULP PTB domain-containing engulfment adaptor 1 (GULP1) as a predictive and diagnostic marker and therapeutic target for HCC.
Methods We analyzed genomic datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases via least absolute shrinkage and selection operator Cox regression and 10-fold cross-validation, leading to the development of a 15-gene risk score model, which was validated using three independent datasets. Serum GULP1 and α-fetoprotein levels were assessed to determine the diagnostic accuracy of the model. Using clinical cohorts and patient sera, GULP1 roles were examined, and functional assays in vitro and in vivo were used to evaluate its effects on cell growth, epithelial–mesenchymal transition (EMT), ADP-ribosylation factor 6 (ARF6) activation, and β-catenin signaling.
Result s: Our newly developed risk-score model accurately predicted recurrent HCC in all datasets. Among the 15 genes in the risk score model, GULP1 was overexpressed in patients with HCC and independently predicted HCC recurrence. Its expression modulation influenced cell growth and EMT, with observed effects on ARF6 activation and β-catenin signaling pathways.
Conclusions GULP1 is a crucial biomarker for HCC, serving as a non-invasive diagnostic and predictive tool. It also plays key roles in HCC progression. Our findings highlight the potential use of GULP1 in treatment strategies targeting EMT and HCC recurrence to improve the personalized care and patient outcomes.
Citations
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