Overexpression of GINS4 Is Associated With Tumor Progression and Poor Survival in Hepatocellular Carcinoma

Abstract

PurposeOur research was aimed to identify the expression, clinical value and biological significance of GINS complex subunit 4 (GINS4) in hepatocellular carcinoma (HCC).Materials and MethodsGINS4 was initially screened through weighted gene co-expression network analysis (WGCNA). The TCGA, GEO, and TIMER databases were applied for analyzing the GINS4 mRNA expression in HCC. GINS4 protein levels were detected via immunohistochemistry (IHC). Receiver operating characteristic (ROC) curve was applied for estimating the diagnostic significance of GINS4 in HCC. Kaplan-Meier plots, Cox model, and nomogram were used to assess the prognostic performance of GINS4 in HCC. Nomogram validation was conducted through time-dependent ROC and decision curve analysis (DCA). The Wanderer, UALCAN, and DiseaseMeth databases were utilized to identify GINS4 methylation levels in HCC. Genes co-expressed with GINS4 in HCC were estimated through the TCGA, cBioPortal, and GEPIA. GO, KEGG, and GSEA unraveled the possible biological mechanisms of GINS4 in HCC.ResultsWGCNA confirmed that GINS4 was one of hub genes significantly associated with histological grade of HCC. Multiple databases confirmed the significant upregulation of GINS4 in HCC tissues compared with non-tumor controls. IHC analysis of 35 HCC patients demonstrated that overexpressed GINS4 positively correlated with advanced TNM stage and poor pathological differentiation. GINS4 could effectively differentiate HCC cases from healthy individuals, with an AUC of 0.865. Increased GINS4 expression predicted unsatisfactory prognosis in HCC patients, especially in age >60 years, histological grade 1, HBV infection-negative, and occurring relapse subgroup. Nomogram incorporating GINS4 level and TNM stage displayed satisfactory predictive accuracy and clinical utility in predicting HCC prognosis. Upregulated GINS4 exhibited hypomethylated levels in HCC. Functional analysis indicated that GINS4 potentially positively modulated cell cycle and PI3K/AKT/mTOR pathway.ConclusionGINS4 is overexpressed in HCC and is correlated with undesirable survival of HCC patients.

GINS4 might be a novel prognostic immune-related biomarker of not only esophageal squamous cell carcinoma and other cancers

“…Zhu et al found that GINS4 was highly expressed in gastric cancer and correlated closely with gastric cancer clinicopathological features such as OS and disease-free survival (DFS) [ 31 ]. Similar results were also found in colorectal cancer [ 32 ], pancreatic cancer [ 33 ] and hepatocellular carcinoma [ 34 ] and breast cancer [ 35 ].…”

Combined analysis of expression, prognosis and immune infiltration of GINS family genes in human sarcoma

“…Accordingly, we conducted our study using bioinformatics analysis. Previous study has reported the functional role of several GINS member in sarcoma [23][24][25]. This study used a bioinformatics approach to investigate the expression of the GINS family in sarcoma and its impact on the prognosis of sarcoma patients, and to further investigate the relationship with immune cell infiltration in the sarcoma microenvironment.…”

GINS Complex Subunit 2 Facilitates Gastric Adenocarcinoma Proliferation and Indicates Poor Prognosis

“…For example, high expression of GINS1 promotes drug resistance in leukemia cells (Hsieh et al 2020) and help predicts clinical outcomes of colorectal cancer patients (Bu et al 2020b). On the other hand, high GINS4 results in tumorigenesis of human bladder cancer, colorectal cancer, and hepatocellular carcinoma (Yamane et al 2016;Rong et al 2020;Zhang et al 2021). However, our knowledge regarding the role of GINS2 in gastric cancer is limited.…”

“…BALB/c nude mice at 4 weeks old were selected for in vivo xenograft assay. Briefly, 5 × 10 5 stable-transfected KATO-III or MKN45 cells were subcutaneously injected into the mice (Chen et al 2021). After five days, the tumor diameter was measured by a vernier caliper every 5-days for one month, and the tumor volume was calculated according to the following formula: Volume = (π × length × width 2 )/6.…”