Expression and prognosis analysis of GINS subunits in human breast cancer

Plasma Circular RNAs as Biomarkers for Breast Cancer

Breast cancer (BC) is currently the most common neoplasm, the second leading cause of cancer death in women worldwide, and is a major health problem. The discovery of new biomarkers is crucial to improve our knowledge of breast cancer and strengthen our clinical approaches to diagnosis, prognosis, and follow-up. In recent decades, there has been increasing interest in circulating RNA (circRNA) as modulators of gene expression involved in tumor development and progression. The study of circulating circRNAs (ccircRNAs) in plasma may provide new non-invasive diagnostic, prognostic, and predictive biomarkers for BC. This review describes the latest findings on BC-associated ccircRNAs in plasma and their clinical utility. Several ccircRNAs in plasma have shown great potential as BC biomarkers, especially from a diagnostic point of view. Mechanistically, most of the reported BC-associated ccircRNAs are involved in the regulation of cell survival, proliferation, and invasion, mainly via MAPK/AKT signaling pathways. However, the study of circRNAs is a relatively new area of research, and a larger number of studies will be crucial to confirm their potential as plasma biomarkers and to understand their involvement in BC.

The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci

Backgrounds

Glioma is a highly malignant brain tumor with a grim prognosis. Genetic factors play a role in glioma development. While some susceptibility loci associated with glioma have been identified, the risk loci associated with prognosis have received less attention. This study aims to identify risk loci associated with glioma prognosis and establish a prognostic prediction model for glioma patients in the Chinese Han population.

Methods

A genome-wide association study (GWAS) was conducted to identify risk loci in 484 adult patients with glioma. Cox regression analysis was performed to assess the association between GWAS-risk loci and overall survival as well as progression-free survival in glioma. The prognostic model was constructed using LASSO Cox regression analysis and multivariate Cox regression analysis. The nomogram model was constructed based on the single nucleotide polymorphism (SNP) classifier and clinical indicators, enabling the prediction of survival rates at 1-year, 2-year, and 3-year intervals. Additionally, the receiver operator characteristic (ROC) curve was employed to evaluate the prediction value of the nomogram. Finally, functional enrichment and tumor-infiltrating immune analyses were conducted to examine the biological functions of the associated genes.

Results

Our study found suggestive evidence that a total of 57 SNPs were correlated with glioma prognosis (p < 5 × 10-5). Subsequently, we identified 25 SNPs with the most significant impact on glioma prognosis and developed a prognostic model based on these SNPs. The 25 SNP-based classifier and clinical factors (including age, gender, surgery, and chemotherapy) were identified as independent prognostic risk factors. Subsequently, we constructed a prognostic nomogram based on independent prognostic factors to predict individualized survival. ROC analyses further showed that the prediction accuracy of the nomogram (AUC = 0.956) comprising the 25 SNP-based classifier and clinical factors was significantly superior to that of each individual variable.

Conclusion

We identified a SNP classifier and clinical indicators that can predict the prognosis of glioma patients and established a prognostic prediction model in the Chinese Han population. This study offers valuable insights for clinical practice, enabling improved evaluation of patients' prognosis and informing treatment options.

Roles of DSCC1 and GINS1 in gastric cancer

Gastric carcinoma is a common malignant tumor originating from gastric mucosal epithelium. However, role of DS-cell cycle-dependent protein 1 (DSCC1) and GINS1 in gastric carcinoma remains unclear. The gastric carcinoma datasets GSE79973 and GSE118916 were downloaded from gene expression omnibus. Multiple datasets were merged and batched. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis was performed. Functional enrichment analysis, gene set enrichment analysis and immune infiltration analysis were performed. Construction and analysis of protein-protein interaction Network. Survival analysis and comparative toxicogenomics database were performed. A heat map of gene expression was drawn. Target Scan screen miRNAs regulating DEGs. Two thousand forty-four DEGs were identified. According to gene ontology analysis, in biological process, they were mainly enriched in cell migration, transforming growth factor β receptor signaling pathway, angiogenesis, and steroid metabolism process. In cellular component, they were mainly enriched in extracellular vesicles, basement membrane, endoplasmic reticulum lumen, and extracellular space. In molecular function, they focused on extracellular matrix structural components, protein binding, platelet-derived growth factor binding, and catalytic activity. In Kyoto encyclopedia of genes and genomes, they were mainly enriched in protein digestion and absorption, metabolic pathways, fatty acid degradation, Glycerophospholipid metabolism, ether lipid metabolism. Gene set enrichment analysis showed that DEGs were mainly enriched in transforming growth factor β receptor signaling pathway, steroid metabolism process, basement membrane, endoplasmic reticulum lumen, structural components of extracellular matrix, platelet-derived growth factor binding, Glycerophospholipid metabolism, ether lipid metabolism. The results of immune infiltration analysis showed that expression of T cell CD4 memory resting was lower in the samples of gastric cancer. The core genes (TRIP13, CHEK1, DSCC1, GINS1) are protective factors, their expression shows a downward trend with increase of risk score. Comparative toxicogenomics database analysis showed that TRIP13, CHEK1, DSCC1, GINS1 were related to gastric tumors, gastric diseases, tumors, inflammation, and necrosis. DSCC1 and GINS1 are highly expressed in gastric cancer. Higher expression levels of DSCC1 and GINS1, worse the prognosis.

The Molecular Pathogenesis of Tumor-Suppressive miR-486-5p and miR-486-3p Target Genes: GINS4 Facilitates Aggressiveness in Lung Adenocarcinoma

The involvement of passenger strands of miRNAs in the molecular pathogenesis of human cancers is a recent concept in miRNA research, and it will broaden our understanding of the molecular mechanisms of miRNA-mediated cancer. The analysis of our miRNA signature of LUAD revealed that both strands of pre-miR-486 (miR-486-5p and miR-486-3p) were downregulated in LUAD tissues. Ectopic expression of both miRNAs induced cell cycle arrest in LUAD cells, suggesting both strands of miRNAs derived from pre-miR-486 were tumor suppressive. Our in silico analysis showed a total of 99 genes may be under the control of both miRNAs in LUAD cells. Importantly, among these targets, the high expression of seven genes (MKI67, GINS4, RRM2, HELLS, MELK, TIMELESS, and SAPCD2) predicted a poorer prognosis of LUAD patients (p < 0.05). We focused on GINS4, a DNA replication complex GINS protein that plays an essential role in the initiation of DNA replication. Our functional assays showed that GINS4 was directly controlled by both strands of pre-miR-486, and its aberrant expression facilitated the aggressive behavior of LUAD cells. GINS4 is attractive as a therapeutic target for this disease. MiRNA analysis, including passenger strands, will further improve our understanding of the molecular pathogenesis of LUAD.

Hsa_circ_0008673 Promotes Breast Cancer Progression by MiR-578/GINS4 Axis

BACKGROUND

Circular RNAs (circRNAs) play a crucial role in breast cancer (BC) development. This study aimed to explore the new potential mechanism of hsa_circ_0008673 in BC.

MATERIALS AND METHODS

Hsa_circ_0008673, microRNA-578 (miR-578) and recombinant human GINS complex subunit 4 (GINS4) abundances were measured via quantitative real-time PCR or western blot. Cell proliferation, metastasis, angiogenesis and apoptosis were assessed via EdU assay, transwell assay, tube formation assay, and flow cytometry. The interactions among hsa_circ_0008673, miR-578 and GINS4 were tested via dual-luciferase reporter analysis and RNA pull-down assay. Animal studies were performed to assess the effect of hsa_circ_0008673 on BC tumor growth.

RESULTS

Hsa_circ_0008673 level was increased in BC tissues and cells. Hsa_circ_0008673 silencing repressed BC cell growth, metastasis and angiogenesis, as well as hampered BC tumor growth. Hsa_circ_0008673 acted as miR-578 sponge, and miR-578 targeted GINS4. Furthermore, hsa_circ_0008673 modulated GINS4 expression through sponging miR-578. Additionally, miR-578 inhibitor or GINS4 overexpression could reverse the inhibitory effect of hsa_circ_0008673 silencing on BC cell progression.

CONCLUSION

Hsa_circ_0008673 might promote BC progression via modulating miR-578/GINS4 pathway.

The role of FOXP3 in non-small cell lung cancer and its therapeutic potentials

Although in the last few decades we have witnessed the rapid development of treatments for non-small cell lung cancer (NSCLC), it still remains the leading cause of cancer-related death. Increasing efforts have been devoted to exploring potential biomarkers and molecular targets for NSCLC. Foxp3, a transcription factor that was discovered as a master regulator of regulatory T cells (Tregs), has been found to express abnormally in tumoral cells including lung cancer cells. In recent years, increasing evidence have surfaced, revealing the carcinogenic effect of FOXP3 in lung cancer. In this review, we analyzed and summarized the function of FOXP3, its regulation and therapeutic potentials in NSCLC, with a hope to facilitate the development of novel treatments for NSCLC.

Increased replication origin firing links replication stress to whole chromosomal instability in human cancer

Chromosomal instability (CIN) is a hallmark of cancer and comprises structural CIN (S-CIN) and numerical or whole chromosomal CIN (W-CIN). Recent work indicated that replication stress (RS), known to contribute to S-CIN, also affects mitotic chromosome segregation, possibly explaining the common co-existence of S-CIN and W-CIN in human cancer. Here, we show that RS-induced increased origin firing is sufficient to trigger W-CIN in human cancer cells. We discovered that overexpression of origin firing genes, including GINS1 and CDC45, correlates with W-CIN in human cancer specimens and causes W-CIN in otherwise chromosomally stable human cells. Furthermore, modulation of the ATR-CDK1-RIF1 axis increases the number of firing origins and leads to W-CIN. Importantly, chromosome missegregation upon additional origin firing is mediated by increased mitotic microtubule growth rates, a mitotic defect prevalent in chromosomally unstable cancer cells. Thus, our study identifies increased replication origin firing as a cancer-relevant trigger for chromosomal instability.

MicroRNA-133a-3p Inhibits Lung Adenocarcinoma Development and Cisplatin Resistance through Targeting GINS4

GINS subunit complex 4 (GINS4) is fundamental to DNA replication and G1/S phase transition of the cell cycle in eukaryotes. Further, recent studies implied that GINS4 can mediate the progression of several tumors, but its mechanism in lung adenocarcinoma (LUAD) is not clarified. Therefore, the role of GINS4 in LUAD was explored. miR-133a-3p and GINS4 mRNA expression were tested through qRT-PCR. Protein levels of the two genes were assayed by Western blot. Their targeting relationship was predicted and verified by bioinformatics prediction and dual-luciferase analysis. The functions of miR-133a-3p and GINS4 in LUAD were evaluated by Transwell, wound healing, CCK-8, and flow cytometry assays. MTT assay and caspase-3 activity detection were utilized to measure the regulation of miR-133a-3p/GINS4 in the cisplatin sensitivity of LUAD cells. The results showed that GINS4 was highly expressed in LUAD cells (p < 0.05). miR-133a-3p, the upstream gene of GINS4 in LUAD, negatively mediated GINS4 expression. Moreover, overexpressing GINS4 enhanced the proliferative, migratory, and invasive abilities of LUAD cells and inhibited cell apoptosis and the sensitivity to cisplatin, while overexpressing miR-133a-3p caused the contrary results. However, the promoting effects of GINS4 overexpression on LUAD could be offset by miR-133a-3p overexpression. miR-133a-3p could regulate malignant behaviors and cisplatin sensitivity of LUAD cells through negatively regulating GINS4. In conclusion, our findings demonstrated that GINS4 was overexpressed in LUAD and promoted the malignant behavior of LUAD cells. Moreover, miR-133a-3p could negatively regulate GINS4, thereby suppressing the malignant progression and increasing the cisplatin sensitivity of LUAD.

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.

MetastaSite: Predicting metastasis to different sites using deep learning with gene expression data

Deep learning has massive potential in predicting phenotype from different omics profiles. However, deep neural networks are viewed as black boxes, providing predictions without explanation. Therefore, the requirements for these models to become interpretable are increasing, especially in the medical field. Here we propose a computational framework that takes the gene expression profile of any primary cancer sample and predicts whether patients' samples are primary (localized) or metastasized to the brain, bone, lung, or liver based on deep learning architecture. Specifically, we first constructed an AutoEncoder framework to learn the non-linear relationship between genes, and then DeepLIFT was applied to calculate genes' importance scores. Next, to mine the top essential genes that can distinguish the primary and metastasized tumors, we iteratively added ten top-ranked genes based upon their importance score to train a DNN model. Then we trained a final multi-class DNN that uses the output from the previous part as an input and predicts whether samples are primary or metastasized to the brain, bone, lung, or liver. The prediction performances ranged from AUC of 0.93-0.82. We further designed the model's workflow to provide a second functionality beyond metastasis site prediction, i.e., to identify the biological functions that the DL model uses to perform the prediction. To our knowledge, this is the first multi-class DNN model developed for the generic prediction of metastasis to various sites.

Identification of lncRNA/circRNA-miRNA-mRNA ceRNA Network as Biomarkers for Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) accounts for the majority of liver cancer, with the incidence and mortality rates increasing every year. Despite the improvement of clinical management, substantial challenges remain due to its high recurrence rates and short survival period. This study aimed to identify potential diagnostic and prognostic biomarkers in HCC through bioinformatic analysis.

Methods: Datasets from GEO and TCGA databases were used for the bioinformatic analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out by WebGestalt website and clusterProfiler package of R. The STRING database and Cytoscape software were used to establish the protein-protein interaction (PPI) network. The GEPIA website was used to perform expression analyses of the genes. The miRDB, miRWalk, and TargetScan were employed to predict miRNAs and the expression levels of the predicted miRNAs were explored via OncomiR database. LncRNAs were predicted in the StarBase and LncBase while circRNA prediction was performed by the circBank. ROC curve analysis and Kaplan-Meier (KM) survival analysis were performed to evaluate the diagnostic and prognostic value of the gene expression, respectively.

Results: A total of 327 upregulated and 422 downregulated overlapping DEGs were identified between HCC tissues and noncancerous liver tissues. The PPI network was constructed with 89 nodes and 178 edges and eight hub genes were selected to predict upstream miRNAs and ceRNAs. A lncRNA/circRNA-miRNA-mRNA network was successfully constructed based on the ceRNA hypothesis, including five lncRNAs (DLGAP1-AS1, GAS5, LINC00665, TYMSOS, and ZFAS1), six circRNAs (hsa_circ_0003209, hsa_circ_0008128, hsa_circ_0020396, hsa_circ_0030051, hsa_circ_0034049, and hsa_circ_0082333), eight miRNAs (hsa-miR-150-5p, hsa-miR-19b-3p, hsa-miR-23b-3p, hsa-miR-26a-5p, hsa-miR-651-5p, hsa-miR-10a-5p, hsa-miR-214-5p and hsa-miR-486-5p), and five mRNAs (CDC6, GINS1, MCM4, MCM6, and MCM7). The ceRNA network can promote HCC progression via cell cycle, DNA replication, and other pathways. Clinical diagnostic and survival analyses demonstrated that the ZFAS1/hsa-miR-150-5p/GINS1 ceRNA regulatory axis had a high diagnostic and prognostic value.

Conclusion: These results revealed that cell cycle and DNA replication pathway could be potential pathways to participate in HCC development. The ceRNA network is expected to provide potential biomarkers and therapeutic targets for HCC management, especially the ZFAS1/hsa-miR-150-5p/GINS1 regulatory axis.

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.