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

A dynamic co-expression approach reveals Gins2 as a potential upstream modulator of HNSCC metastasis

Head and neck squamous cell carcinoma (HNSCC) is an aggressive cancer that is notably associated with a high risk of lymph node metastasis, a major cause of cancer mortality. Current therapeutic options remain limited to surgery supplemented by radio- or chemotherapy; however, these interventions often result in high-grade toxicities. Distant metastasis significantly contributed to the poor prognosis and decreased survival rates. However, the underlying molecular mechanisms remain poorly understood. Disease-related "omics" data provide a comprehensive overview of gene relationships, helping to decode the complex molecular mechanisms involved. Interactions between biological molecules are complex and highly dynamic across various cellular conditions, making traditional co-expression methods inadequate for understanding these intricate relationships. In the present study, a novel three-way interaction approach was employed to uncover dynamic co-expression relationships underlying the metastatic nature of HNSCC. Subsequently, the biologically relevant triples from statistically significant ones were defined through gene set enrichment analysis and reconstruction of the gene regulatory network. Finally, the validity of biologically relevant triplets was assessed at the protein level. The results highlighted the "PI3K/AKT/mTOR (PAM) signaling pathway" as a disrupted pathway involved in the metastatic nature of HNSCC. Notably, Gins2, identified as a switch gene, along with the gene pair {Akt2, Anxa2}, formed a statistically significant and biologically relevant triplet. It suggests that Gins2 could serve as a potential upstream modulator in the PAM signaling pathway, playing a crucial role in the distant metastasis of HNSCC. In addition, survival analysis of significant switch genes indicated that two genes, C19orf33 and Usp13, may be especially important for prognostic purposes in HNSCC.

A novel immune-related model to predict prognosis and responsiveness to checkpoint and angiogenesis blockade therapy in advanced renal cancer

Background

Immune checkpoint blockade (ICB) and anti-angiogenic drug combination has prolonged the survival of patients with advanced renal cell carcinoma (RCC). However, not all patients receive clinical benefits from this intervention. In this study, we aimed to establish a promising immune-related prognostic model to stratify the patients responding to ICB and anti-angiogenic drug combination and facilitate the development of personalized therapies for patients with RCC.

Materials and methods

Based on clinical annotations and RNA-sequencing (RNA-seq) data of 407 patients with advanced RCC from the IMmotion151 cohort, nine immune-associated differentially expressed genes (DEGs) between responders and non-responders to atezolizumab (anti-programmed death-ligand 1 antibody) plus bevacizumab (anti-vascular endothelial growth factor antibody) treatment were identified via weighted gene co-expression network analysis. We also conducted single-sample gene set enrichment analysis to develop a novel immune-related risk score (IRS) model and further estimate the prognosis of patients with RCC by predicting their sensitivity to chemotherapy and responsiveness to immunotherapy. IRS model was further validated using the JAVELIN Renal 101 cohort, the E-MTAB-3218 cohort, the IMvigor210 and GSE78220 cohort. Predictive significance of the IRS model for advanced RCC was assessed using receiver operating characteristic curves.

Results

The IRS model was constructed using nine immune-associated DEGs: SPINK5, SEMA3E, ROBO2, BMP5, ORM1, CRP, CTSE, PMCH and CCL3L1. Advanced RCC patients with high IRS had a high risk of undesirable clinical outcomes (hazard ratio = 1.91; 95% confidence interval = 1.43–2.55; P < 0.0001). Transcriptome analysis revealed that the IRS-low group exhibited significantly high expression levels of CD8+ T effectors, antigen-processing machinery, and immune checkpoints, whereas the epithelial–mesenchymal transition pathway was enriched in the IRS-high group. IRS model effectively differentiated the responders from non-responders to ICB combined with angiogenesis blockade therapy or immunotherapy alone, with area under the curve values of 0.822 in the IMmotion151 cohort, 0.751 in the JAVELIN Renal 101 cohort, and 0.776 in the E-MTAB-3218 cohort.

Conclusion

IRS model is a reliable and robust immune signature that can be used for patient selection to optimize the efficacy of ICB plus anti-angiogenic drug therapies in patients with advanced RCC.

Comprehensive analysis of a novel RNA modifications-related model in the prognostic characterization, immune landscape and drug therapy of bladder cancer

Background: Bladder cancer (BCa) is the leading reason for death among genitourinary malignancies. RNA modifications in tumors closely link to the immune microenvironment. Our study aimed to propose a promising model associated with the "writer" enzymes of five primary RNA adenosine modifications (including m⁶A, m⁶A_m, m¹A, APA, and A-to-I editing), thus characterizing the clinical outcome, immune landscape and therapeutic efficacy of BCa. Methods: Unsupervised clustering was employed to categorize BCa into different RNA modification patterns based on gene expression profiles of 34 RNA modification "writers". The RNA modification "writers" score (RMS) signature composed of RNA phenotype-associated differentially expressed genes (DEGs) was established using the least absolute shrinkage and selection operator (LASSO), which was evaluated in meta-GEO (including eight independent GEO datasets) training cohort and the TCGA-BLCA validation cohort. The hub genes in the RMS model were determined via weighted gene co-expression network analysis (WGCNA) and were further validated using human specimen. The potential applicability of the RMS model in predicting the therapeutic responsiveness was assessed through the Genomics of Drug Sensitivity in Cancer database and multiple immunotherapy datasets. Results: Two distinct RNA modification patterns were determined among 1,410 BCa samples from a meta-GEO cohort, showing radically varying clinical outcomes and biological characteristics. The RMS model comprising 14 RNA modification phenotype-associated prognostic DEGs positively correlated with the unsatisfactory outcome of BCa patients in meta-GEO training cohort (HR = 3.00, 95% CI = 2.19-4.12) and TCGA-BLCA validation cohort (HR = 1.53, 95% CI = 1.13-2.09). The infiltration of immunosuppressive cells and the activation of EMT, angiogenesis, IL-6/JAK/STAT3 signaling were markedly enriched in RMS-high group. A nomogram exhibited high prognostic prediction accuracy, with a concordance index of 0.785. The therapeutic effect of chemotherapeutic agents and antibody-drug conjugates was significantly different between RMS-low and -high groups. The combination of the RMS model and conventional characteristics (TMB, TNB and PD-L1) achieved an optimal AUC value of 0.828 in differentiating responders from non-responders to immunotherapy. Conclusion: We conferred the first landscape of five forms of RNA modifications in BCa and emphasized the excellent power of an RNA modifications-related model in evaluating BCa prognosis and immune landscape.

Comprehensive analysis of GINS subunits prognostic value and ceRNA network in sarcoma

Background: The GINS complex, composed of GINS1/2/3/4 subunits, is an essential structure of Cdc45-MCM-GINS (CMG) helicase and plays a vital role in establishing the DNA replication fork and chromosome replication. Meanwhile, GINS genes have been associated with the poor prognosis of various malignancies. However, the abnormal expression of GINS genes and their diagnostic and prognostic value in sarcomas (SARC) remain unclear.

Methods: Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, Cancer cell line encyclopedia (CCLE), The University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), R studio, and Tumor Immune Estimation Resource (TIMER) were used to analyze the expression profiles, prognostic value, biological function, ceRNA, and immune infiltration associated with GINS genes in sarcomas.

Results: We found that GINS1/2/3/4 genes exhibited significantly upregulated transcription levels in SARC samples compared to non-tumor tissues and exhibited high expression levels in sarcoma cell lines. In addition, SARC patients with increased expression levels of GINS1/2/3/4 showed poorer survival rates. Immune infiltration analysis showed that GINS subunits were closely associated with the infiltration of immune cells in sarcomas.

Conclusion: Our research identified GINS subunits as potential diagnostic and prognostic biological targets in SARC and elucidated their underlying effects in the genesis and progression of SARC. These results may provide new opportunities and research directions for targeted sarcoma therapy.

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

OBJECTIVE

This study was undertaken to explore the expression and prognostic value of GINS family in human sarcoma, as well as the association between the expression levels of the GINS family and sarcoma immune infiltration.

RESULTS

We discovered that the mRNA expression levels of GINS1, GINS2, GINS3, and GINS4 were all higher in the majority of tumor tissues than in normal samples, of course, including sarcoma. Through the CCLE, all the four members expression were observed in high levels in sarcoma cell lines. In Gene Expression Profiling Analysis (GEPIA) and Kaplan-Meier Plotter, our results indicated that the poor overall survival (OS), disease-free survival (DFS) and relapse free survival (RFS) were tightly associated with the increased expression of GINS genes. In TIMER database, we found that highly expressed GINS was significantly correlated with the low infiltration level of CD4+ T cell and macrophage.

CONCLUSIONS

The four GINS family members were all the prognostic biomarkers for the prognosis of human sarcoma and can reduce the level of immune cell infiltration in the sarcoma microenvironment.

METHODS

In terms of the expression levels of mRNA for GINS family members, a particular contrast in various cancers, especially human sarcoma, was conducted through ONCOMINE and GEPIA and CCLE databases. Kaplan-Meier Plotter was used to identify the prognostic value of GINS family in sarcoma. The relationship between the expression level of GINS and the infiltration of immune cells was analyzed in TIMER database.

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

Background

Immunotherapy using immune checkpoint inhibitors (ICIs), such as antibody of programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) has showed as a promising treatment for esophageal squamous cell carcinoma (ESCC), but resistance is unavoidable. This study aimed to find more immune-related genes to promote the efficiency of immunotherapy.

Materials and methods

Three datasets were downloaded from Gene Expression Omnibus (GEO) database. Gene differential analysis was performed to identify differentially expressed genes (DEGs), then ceRNA network was constructed based on differentially expressed lncRNAs and mRNAs. Next, Functional enrichment analysis and protein–protein interaction (PPI) network were built to reveal the potential function of mRNAs in ceRNA network. Survival analysis and immune cell infiltration level analysis were utilized to identify prognostic immune-related genes. Finally, pan-cancer analysis was performed to show the role of immune-related genes in other cancers.

Results

The data of 215 samples in total were obtained from GEO database (98 normal tissues and 117 tumor tissues), and 1685 differentially expressed mRNAs (176 downregulated and 1509 upregulated) and 3 upregulated lncRNAs (MCM3AP-AS1, HCP5 and GUSBP11, all upregulated) were found. ceRNA network was constructed to reveal some special correlation. Function enrichment showed some potential functions of mRNAs in ceRNA network such as mitotic cell cycle process, negative regulation of DNA-binding transcription factor activity, ossification, VEGFA-VEGFR2 signaling pathway, epithelial to mesenchymal transition, embryonic morphogenesis and so on. PPI network showed the physical interactions between each mRNA in ceRNA network. Through survival analysis and immune cell infiltration level analysis, GINS4 was confirmed as an immune-related prognostic gene in ESCC. GSEA showed some potential functions such as negative regulation of monocyte chemotaxis, antigen processing and presentation of endogenous peptide antigen via MHC class I via ER pathway, positive regulation of antigen processing and presentation, dendritic cell antigen processing and presentation and so on. Finally, pan-cancer analysis revealed that GINS4 might be a novel immune-related prognostic gene in ESCC and other cancers.

Conclusion

Our study suggested that GINS4 was correlated with prognosis and immune cell infiltration level of ESCC and other cancers. It may deserve further investigation as a potential immune-related prognostic biomarker of ESCC and other cancers.

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

Gastric cancer is the one of the most lethal malignancies of digestive system. Identifying molecular biomarkers is invaluable in help predicting clinical outcomes and developing targeted chemotherapies. GINS complex subunit 2 (GINS2) plays an essential role in the initiation and elongation of DNA replication. Although there have been studies revealing the prognostic significance of GINS2 in breast cancer and lung cancer, its involvement and function in gastric cancer need to be elucidated. We retrospectively enrolled a cohort of gastric adenocarcinoma patients after surgical resection (n = 123). By analyzing the mRNA and protein levels of GINS2 in tissue samples, we found that GINS2 presented a higher expression in tumor tissues than in adjacent normal stomach tissues. Besides, GINS2 level was positively correlated with tumor size and gastric adenocarcinoma tumor stage, implying its potential role as a tumor promoter. Univariate and multivariate analyses identified that patients with lower GINS2 showed a better overall survival compared to those with higher GINS2 expression. In addition, cellular and xenograft experiments confirmed the role of GINS2 in facilitating tumor proliferation both in vitro and in vivo. To our knowledge, this is the initial finding on GINS2 in promoting gastric adenocarcinoma progression. In conclusion, our study revealed a pro-oncogenic role of GINS2 in gastric cancer.