Epigenetically silenced GNG4 inhibits SDF1α/CXCR4 signaling in mesenchymal glioblastoma

Engagement of N6-methyladenisine methylation of Gng4 mRNA in astrocyte dysfunction regulated by CircHECW2

The N6-methyladenosine (m6A) modification is the most prevalent modification of eukaryotic mRNAs and plays a crucial role in various physiological processes by regulating the stability or function of target mRNAs. Accumulating evidence has suggested that m6A methylation may be involved in the pathological process of major depressive disorder (MDD), a common neuropsychiatric disorder with an unclear aetiology. Here, we found that the levels of the circular RNA HECW2 (circHECW2) were significantly increased in the plasma of both MDD patients and the chronic unpredictable stress (CUS) mouse model. Notably, the downregulation of circHECW2 attenuated astrocyte dysfunction and depression-like behaviors induced by CUS. Furthermore, we demonstrated that the downregulation of circHECW2 increased the expression of the methylase WTAP, leading to an increase in Gng4 expression via m6A modifications. Our findings provide functional insight into the correlation between circHECW2 and m6A methylation, suggesting that circHECW2 may represent a potential target for MDD treatment.

GNG4, as a potential predictor of prognosis, is correlated with immune infiltrates in colon adenocarcinoma

The tumour microenvironment (TME) and immunosuppression play an important role in colon cancer (CC) metastasis, which seriously affects the prognosis of CC. G protein subunit gamma 4 (GNG4) has been shown to participate in tumour progression and the tumour mutation burden (TMB) in colorectal cancer. However, the effect of GNG4 on the CC TME and immunology remains elusive. Weighted gene coexpression network analysis (WGCNA) was employed for screening aberrantly expressed genes associated with the immune score, and GNG4 was then selected through prognostic and immune correlation analysis. Based on RNA sequencing data obtained from the TCGA and GEO databases, the expression pattern and immune characteristics of GNG4 were comprehensively examined using a pan-cancer analysis. Upregulation of GNG4 was linked to an adverse prognosis and immune inhibitory phenotype in CC. Pan-cancer analysis demonstrated higher GNG4 expression in tumours than in paired normal tissue in human cancers. GNG4 expression was closely related to prognosis, TMB, immune checkpoints (ICPs), microsatellite instability (MSI) and neoantigens. GNG4 promoted CC cell proliferation, migration and invasion and participated in immune regulation in the TME. Significantly, GNG4 expression was found to negatively correlate with tumour-infiltrating immune cells, ICP, TMB and MSI in CC. GNG4 expression predicted the immunotherapy response in the IMvigor210 cohort, suggesting that GNG4 could be used as a potential biomarker in CC for prognostication and immunology. Moreover, the expression of GNG4 predicted the immunotherapy response of ICB in CC.

CXCR4 expression is associated with proneural-to-mesenchymal transition in glioblastoma

Glioblastoma (GBM) is the most common primary intracranial malignant tumor and consists of three molecular subtypes: proneural (PN), mesenchymal (MES) and classical (CL). Transition between PN to MES subtypes (PMT) is the glioma analog of the epithelial-mesenchymal transition (EMT) in carcinomas and is associated with resistance to therapy. CXCR4 signaling increases the expression of MES genes in glioma cell lines and promotes EMT in other cancers. RNA sequencing (RNAseq) data of PN GBMs in The Cancer Genome Atlas (TCGA) and secondary high-grade gliomas (HGGs) from an internal cohort were examined for correlation between CXCR4 expression and survival as well as expression of MES markers. Publicly available single-cell RNA sequencing (scRNAseq) data was analyzed for cell type specific CXCR4 expression. These results were validated in a genetic mouse model of PN GBM. Higher CXCR4 expression was associated with significantly reduced survival and increased expression of MES markers in TCGA and internal cohorts. CXCR4 was expressed in immune and tumor cells based on scRNAseq analysis. Higher CXCR4 expression within tumor cells on scRNAseq was associated with increased MES phenotype, suggesting a cell-autonomous effect. In a genetically engineered mouse model, tumors induced with CXCR4 exhibited a mesenchymal phenotype and shortened survival. These results suggest that CXCR4 signaling promotes PMT and shortens survival in GBM and highlights its inhibition as a potential therapeutic strategy.

High GNG4 predicts adverse prognosis for osteosarcoma: Bioinformatics prediction and experimental verification

Background

Guanine nucleotide binding (G) protein subunit γ 4 (GNG4) is closely related to the malignant progression and poor prognosis of various tumours. However, its role and mechanism in osteosarcoma remain unclear. This study aimed to elucidate the biological role and prognostic value of GNG4 in osteosarcoma.

Methods

Osteosarcoma samples in the GSE12865, GSE14359, GSE162454 and TARGET datasets were selected as the test cohorts. The expression level of GNG4 between normal and osteosarcoma was identified in GSE12865 and GSE14359. Based on the osteosarcoma single-cell RNA sequencing (scRNA-seq) dataset GSE162454, differential expression of GNG4 among cell subsets was identified at the single-cell level. As the external validation cohort, 58 osteosarcoma specimens from the First Affiliated Hospital of Guangxi Medical University were collected. Patients with osteosarcoma were divided into high- and low-GNG4 groups. The biological function of GNG4 was annotated using Gene Ontology, gene set enrichment analysis, gene expression correlation analysis and immune infiltration analysis. Kaplan-Meier survival analysis was conducted and receiver operating characteristic (ROC) curves were calculated to determine the reliability of GNG4 in predicting prognostic significance and diagnostic value. Functional in vitro experiments were performed to explore the function of GNG4 in osteosarcoma cells.

Results

GNG4 was generally highly expressed in osteosarcoma. As an independent risk factor, high GNG4 was negatively correlated with both overall survival and event-free survival. Furthermore, GNG4 was a good diagnostic marker for osteosarcoma, with an area under the receiver operating characteristic curve (AUC) of more than 0.9. Functional analysis suggested that GNG4 may promote the occurrence of osteosarcoma by regulating ossification, B-cell activation, the cell cycle and the proportion of memory B cells. In in vitro experiments, silencing of GNG4 inhibited the viability, proliferation and invasion of osteosarcoma cells.

Conclusion

Through bioinformatics analysis and experimental verification, high expression of GNG4 in osteosarcoma was identified as an oncogene and reliable biomarker for poor prognosis. This study helps to elucidate the significant potential of GNG4 in carcinogenesis and molecular targeted therapy for osteosarcoma.

LINE-1 hypomethylation is associated with poor outcomes in locoregionally advanced oropharyngeal cancer

BACKGROUND AND PURPOSE

Currently, human papillomavirus (HPV) positivity represents a strong prognostic factor for both reduced risk of relapse and improved survival in patients with oropharyngeal squamous cell carcinoma (OPSCC). However, a subset of HPV-positive OPSCC patients still experience poor outcomes. Furthermore, HPV-negative OPSCC patients, who have an even higher risk of relapse, are still lacking suitable prognostic biomarkers for clinical outcome. Here, we evaluated the prognostic value of LINE-1 methylation level in OPSCC patients and further addressed the relationship between LINE-1 methylation status and p53 protein expression as well as genome-wide/gene-specific DNA methylation.

RESULTS

In this study, DNA was extracted from 163 formalin-fixed paraffin-embedded tissue samples retrospectively collected from stage III-IVB OPSCC patients managed with curative intent with up-front treatment. Quantitative methylation-specific PCR revealed that LINE-1 hypomethylation was directly associated with poor prognosis (5-year overall survival-OS: 28.1% for LINE-1 methylation < 35% vs. 69.1% for ≥ 55%; p < 0.0001). When LINE-1 methylation was dichotomized as < 55% versus ≥ 55%, interaction with HPV16 emerged: compared with hypermethylated HPV16-positive patients, subjects with hypomethylated HPV16-negative OPSCC reported an adjusted higher risk of death (HR 4.83, 95% CI 2.24-10.38) and progression (HR 4.54, 95% CI 2.18-9.48). Tumor protein p53 (TP53) gene is often mutated and overexpressed in HPV-negative OPSCC. Since p53 has been reported to repress LINE-1 promoter, we then analyzed the association between p53 protein expression and LINE-1 methylation levels. Following p53 immunohistochemistry, results indicated that among HPV16-negative patients with p53 ≥ 50%, LINE-1 methylation levels declined and remained stable at approximately 43%; any HPV16-positive patient reported p53 ≥ 50%. Finally, DNA methylation analysis demonstrated that genome-wide average methylation level at cytosine-phosphate-guanine sites was significantly lower in HPV16-negative OPSCC patients who relapsed within two years. The subsequent integrative analysis of gene expression and DNA methylation identified 20 up-regulated/hypomethylated genes in relapsed patients, and most of them contained LINE-1 elements in their promoter sequences.

CONCLUSIONS

Evaluation of the methylation level of LINE-1 may help in identifying the subset of OPSCC patients with bad prognosis regardless of their HPV status. Aberrant LINE-1 hypomethylation might occur along with TP53 mutations and lead to altered gene expression in OPSCC.

G protein gamma subunit, a hidden master regulator of GPCR signaling

Heterotrimeric G proteins (αβγ subunits) that are activated by G protein-coupled receptors (GPCRs) mediate the biological responses of eukaryotic cells to extracellular signals. The α subunits and the tightly bound βγ subunit complex of G proteins have been extensively studied and shown to control the activity of effector molecules. In contrast, the potential roles of the large family of γ subunits have been less studied. In this review, we focus on present knowledge about these proteins. Induced loss of individual γ subunit types in animal and plant models result in strikingly distinct phenotypes indicating that γ subtypes play important and specific roles. Consistent with these findings, downregulation or upregulation of particular γ subunit types result in various types of cancers. Clues about the mechanistic basis of γ subunit function have emerged from imaging the dynamic behavior of G protein subunits in living cells. This shows that in the basal state, G proteins are not constrained to the plasma membrane but shuttle between membranes and on receptor activation βγ complexes translocate reversibly to internal membranes. The translocation kinetics of βγ complexes varies widely and is determined by the membrane affinity of the associated γ subtype. On translocating, some βγ complexes act on effectors in internal membranes. The variation in translocation kinetics determines differential sensitivity and adaptation of cells to external signals. Membrane affinity of γ subunits is thus a parsimonious and elegant mechanism that controls information flow to internal cell membranes while modulating signaling responses.

Screening for aberrantly methylated and differentially expressed genes in nonalcoholic fatty liver disease of hepatocellular carcinoma patients with cirrhosis

Background

Nonalcoholic fatty liver disease (NAFLD) as the leading chronic liver disease worldwide causes hepatic fibrosis, cirrhosis and hepatocellular carcinoma (HCC). The aim of this study was to find potential aberrantly methylated and differentially expressed genes in NAFLD of HCC patients with cirrhosis.

Methods

DNA methylation data, mRNA expression data, and the corresponding clinical information of HCC were downloaded from the Cancer Genome Atlas (TCGA, tissue sample) database. HCC patients with cirrhosis were divided into two groups according to the presence of NAFLD. The differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were obtained.

Results

By overlapping 79 up-regulated genes and 1020 hypomethylated genes, we obtained 5 hypomethylated-highly expressed genes (Hypo­HGs). By overlapping 365 down-regulated genes and 481 hypermethylated genes, we identified 13 hypermethylated-lowly expressed genes (Hyper-LGs). Survival analysis of these 18 MDEGs indicated that the expression of DGKK and HOXD9 was significantly correlated with the overall survival time of NAFLD patients.

Conclusions

We identified several candidate genes whose expressions were regulated by DNA methylation of NAFLD of HCC with cirrhosis, which may provide a new field in understanding the clinical pathological mechanism of NAFLD of HCC with cirrhosis.

Expression of NMU, PPBP and GNG4 in colon cancer and their influences on prognosis

BACKGROUND

This study aims to identify the core genes that influence the prognosis of colon cancer (CC) and analyze their relationships with clinical characteristics.

METHODS

The gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were identified. The top ten core genes were selected by bioinformatics tools and screened through the Oncomine database. The expression of core genes in CC tissues and cells was validated by immunohistochemistry, immunoblotting and quantitative real-time polymerase chain reaction. Spearman correlation was used to analyze the relationship between different parameters. Overall survival was assessed by the Kaplan-Meier method. The area under the curve (AUC) and the receiver operating curve (ROC) were applied to assess the accuracy of genes for predicting prognosis.

RESULTS

There were 1,665 DEGs that were identified from TCGA database. Bioinformatics analysis found that GNGT1, NMU, PPBP, AGT, and GNG4 were differentially expressed in CC tissue. Overexpression of NMU, PPBP, AGT, and GNG4 in CC was associated with shortened survival time (P<0.05). In the validation studies, the high expression levels of NMU, PPBP and GNG4 in CC cells and tissues were confirmed compared to the control groups (P<0.05) and were adverse prognostic biomarkers (P<0.01). The combination prognostic model of the three core genes predicted the 1-, 3-, and 5-year survival of CC with AUCs of 0.868, 0.635 and 0.770, respectively.

CONCLUSIONS

High levels of NMU, PPBP, and GNG4 were associated with poor prognosis in CC. The combination prognostic model of these three genes could be a new option.

Association of a Novel DOCK2 Mutation-Related Gene Signature With Immune in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality worldwide. Many studies have shown that dedicator of cytokinesis 2 (DOCK2) has a crucial role as a prognostic factor in various cancers. However, the potentiality of DOCK2 in the diagnosis of HCC has not been fully elucidated. In this work, we aimed to investigate the prognostic role of DOCK2 mutation in HCC. The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) cohorts were utilized to identify the mutation frequency of DOCK2. Then, univariate Cox proportional hazard regression analysis, random forest (RF), and multivariate Cox regression analysis were performed to develop the risk score that was significantly related to DOCK2 mutation. Moreover, Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and immune correlation analysis were conducted for an in-depth study of the biological process of DOCK2 mutation involved in HCC. The results revealed that the mutation frequency of DOCK2 was relatively higher than that in non-cancer control subjects, and patients with DOCK2 mutations had a low survival rate and a poor prognosis compared with the DOCK2-wild group. In addition, the secretin receptor (SCTR), tetratricopeptide repeat, ankyrin repeat and coiled-coil domain-containing 1 (TANC1), Alkb homolog 7 (ALKBH7), FRAS1-related extracellular matrix 2 (FREM2), and G protein subunit gamma 4 (GNG4) were found to be the most relevant prognostic genes of DOCK2 mutation, and the risk score based on the five genes played an excellent role in predicting the status of survival, tumor mutation burden (TMB), and microsatellite instability (MSI) in DOCK2 mutant patients. In addition, DOCK2 mutation and the risk score were closely related to immune responses. In conclusion, the present study identifies a novel prognostic signature in light of DOCK2 mutation-related genes that shows great prognostic value in HCC patients; and this gene mutation might promote tumor progression by influencing immune responses. These data may provide valuable insights for future investigations into personalized forecasting methods and also shed light on stratified precision oncology treatment.

G-Protein Subunit Gamma 4 as a Potential Biomarker for Predicting the Response of Chemotherapy and Immunotherapy in Bladder Cancer

Background: GNG4, a member of the G-protein γ family, is a marker of poor overall survival (OS) rates in some malignancies. However, the potential role of GNG4 in bladder cancer (BLCA) is unknown. It is also unclear whether GNG4 may be utilized as a marker to guide chemotherapy or immunotherapy. Methods: Single-cell RNA sequencing data were used to explore the expression of GNG4 in tumor microenvironment of BLCA. Bulk RNA sequencing data from TCGA were used to evaluate the relationship between GNG4 expression and biological features, such as immune cell infiltrations and gene mutations. The associations between GNG4 expression and survival in BLCA patients under or not under immunotherapy were evaluated using seven BLCA cohorts. Results: GNG4 was specifically expressed in exhausted CD4⁺ T cells. And the high expression of the GNG4 was associated with high level of immune cell infiltration. The high-GNG4-expression group displayed a better response to immunotherapy, whereas patients in the low-GNG4-expression group often benefited from chemotherapy. Moreover, the high-GNG4 group was more similar to the basal group, whereas the low-GNG4 group was similar to the luminal group. Conclusions: GNG4 may be a potential biomarker for the prediction of the response to therapy in BLCA. Higher GNG4 expression can be used as a predictor of response to immunotherapy, and lower GNG4 expression can be used as a predictor of response to chemotherapy.

GNG4 Promotes Tumor Progression in Colorectal Cancer

Colorectal cancer is a common digestive system tumor, which lacks effective therapeutic targets and biomarkers to accurately determine the prognosis. Sequencing data, immunohistochemistry, and Kaplan–Meier analysis were used to explore GNG4 clinical significance in colorectal cancer. And, through in vitro experiments, the effects of GNG4 on cell behaviors were investigated. The results showed that the mRNA and protein expression levels of GNG4 in patients with colorectal cancer were significantly higher than in normal people. The patients with high GNG4 expression had a worse prognosis than patients with low GNG4 expression. The in vitro experiments presented that after downregulating the expression of GNG4, proliferation, migration, and invasion of SW-620 colon cancer cells were all significantly reduced, apoptosis was significantly increased, and the cell cycle was blocked in the S phase. In summary, GNG4 may be of importance in the therapy of the colorectal cancer; therefore, targeting GNG4 may have certain clinical value in the treatment of colorectal cancer.

Novel diagnostic and prognostic biomarkers of colorectal cancer: Capable to overcome the heterogeneity-specific barrier and valid for global applications

Introduction

The heterogeneity-specific nature of the available colorectal cancer (CRC) biomarkers is significantly contributing to the cancer-associated high mortality rate worldwide. Hence, this study was initiated to investigate a system of novel CRC biomarkers that could commonly be employed to the CRC patients and helpful to overcome the heterogenetic-specific barrier.

Methods

Initially, CRC-related hub genes were extracted through PubMed based literature mining. A protein-protein interaction (PPI) network of the extracted hub genes was constructed and analyzed to identify few more closely CRC-related hub genes (real hub genes). Later, a comprehensive bioinformatics approach was applied to uncover the diagnostic and prognostic role of the identified real hub genes in CRC patients of various clinicopathological features.

Results

Out of 210 collected hub genes, in total 6 genes (CXCL12, CXCL8, AGT, GNB1, GNG4, and CXCL1) were identified as the real hub genes. We further revealed that all the six real hub genes were significantly dysregulated in colon adenocarcinoma (COAD) patients of various clinicopathological features including different races, cancer stages, genders, age groups, and body weights. Additionally, the dysregulation of real hub genes has shown different abnormal correlations with many other parameters including promoter methylation, overall survival (OS), genetic alterations and copy number variations (CNVs), and CD8+T immune cells level. Finally, we identified a potential miRNA and various chemotherapeutic drugs via miRNA, and real hub genes drug interaction network that could be used in the treatment of CRC by regulating the expression of real hub genes.

Conclusion

In conclusion, we have identified six real hub genes as potential biomarkers of CRC patients that could help to overcome the heterogenetic-specific barrier across different clinicopathological features.

Ileal Derived Organoids From Crohn's Disease Patients Show Unique Transcriptomic and Secretomic Signatures

BACKGROUND & AIMS

We used patient-derived organoids (PDOs) to study the epithelial-specific transcriptional and secretome signatures of the ileum during Crohn's disease (CD) with varying phenotypes to screen for disease profiles and potential druggable targets.

METHODS

RNA sequencing was performed on isolated intestinal crypts and 3-week-old PDOs derived from ileal biopsies of CD patients (n = 8 B1, inflammatory; n = 8 B2, stricturing disease) and non-inflammatory bowel disease (IBD) controls (n = 13). Differentially expressed (DE) genes were identified by comparing CD vs control, B1 vs B2, and inflamed vs non-inflamed. DE genes were used for computational screening to find candidate small molecules that could potentially reverse B1and B2 gene signatures. The secretome of a second cohort (n = 6 non-IBD controls, n = 7 CD, 5 non-inflamed, 2 inflamed) was tested by Luminex using cultured organoid conditioned medium.

RESULTS

We found 90% similarity in both the identity and abundance of protein coding genes between PDOs and intestinal crypts (15,554 transcripts of 19,900 genes). DE analysis identified 814 genes among disease group (CD vs non-IBD control), 470 genes different between the CD phenotypes, and 5 false discovery rate correction significant genes between inflamed and non-inflamed CD. The PDOs showed both similarity and diversity in the levels and types of soluble cytokines and growth factors they released. Perturbagen analysis revealed potential candidate compounds to reverse B2 disease phenotype to B1 in PDOs.

CONCLUSIONS

PDOs are similar at the transcriptome level with the in vivo epithelium and retain disease-specific gene expression for which we have identified secretome products, druggable targets, and corresponding pharmacologic agents. Targeting the epithelium could reverse a stricturing phenotype and improve outcomes.

Identifying GNG4 might play an important role in colorectal cancer TMB

BACKGROUND

Colorectal carcinoma (CRC) is one of the most leading cause of cancer death all over the world. The tumor immune microenvironment is illustrated to be necessary for the progress of CRC. And the accumulating evidence indicated that tumor mutation burden (TMB) is effective in differentiating responding population of immune checkpoint inhibitor (ICI) therapies in various cancers. In this study, we aimed to evaluated the potential relationship between TMB and the recurrence risk of CRC.

METHODS

The transcriptomic and clinical data of CRC patients were collected from The Cancer Genome Atlas (TCGA) database (n= 382). Then the genomic analysis of tumor mutation burden and tumor purity were conducted by a computational method based on transcriptomic data.

RESULTS

Firstly, we accessed the distribution of TMB and preferences at the gene and mutation level using somatic mutation data from TCGA data about CRC. We identified that high TMB predicted better prognosis of CRC patients. Secondly, the differentially expressed genes (DEGs) between the low TMB and high TMB group was clarified. Then the protein-protein interaction (PPI) analysis was performed, and the results confirmed ten hub genes among the DEGs. Utilizing the GEPIA web-tool, we discovered that GNG4 was up-regulated in tumor tissues, and GNG4 was related to the overall survival (OS) and tumor free survival (TFS) of CRC patients. Therefore, we considered GNG4 was essential for the tumor immune microenvironment of CRC. Furthermore, we also accessed the protein level of GNG4 in CRC and liver metastases from CRC.

CONCLUSIONS

In this study, GNG4 was demonstrated to be the key element of the CRC TMB, which will be essential for the ICI therapy of CRC. Besides, GNG4 was up-regulated in CRC and liver metastases from CRC tissues. Thus, we thought that GNG4 might play an important role in colorectal cancer TMB and induce its metastasis in liver.

A Novel Classification of Glioma Subgroup, Which Is Highly Correlated With the Clinical Characteristics and Tumor Tissue Characteristics, Based on the Expression Levels of Gβ and Gγ Genes

Purpose

Glioma is a classical type of primary brain tumors that is most common seen in adults, and its high heterogeneity used to be a reference standard for subgroup classification. Glioma has been diagnosed based on histopathology, grade, and molecular markers including IDH mutation, chromosome 1p/19q loss, and H3K27M mutation. This subgroup classification cannot fully meet the current needs of clinicians and researchers. We, therefore, present a new subgroup classification for glioma based on the expression levels of Gβ and Gγ genes to complement studies on glioma and Gβγ subunits, and to support clinicians to assess a patient’s tumor status.

Methods

Glioma samples retrieved from the CGGA database and the TCGA database. We clustered the gliomas into different groups by using expression values of Gβ and Gγ genes extracted from RNA sequencing data. The Kaplan–Meier method with a two-sided log-rank test was adopted to compare the OS of the patients between GNB2 group and non-GNB2 group. Univariate Cox regression analysis was referred to in order to investigate the prognostic role of each Gβ and Gγ genes. KEGG and ssGSEA analysis were applied to identify highly activated pathways. The “estimate” package, “GSVA” package, and the online analytical tools CIBERSORTx were employed to evaluate immune cell infiltration in glioma samples.

Results

Three subgroups were identified. Each subgroup had its own specific pathway activation pattern and other biological characteristics. High M2 cell infiltration was observed in the GNB2 subgroup. Different subgroups displayed different sensitivities to chemotherapeutics. GNB2 subgroup predicted poor survival in patients with gliomas, especially in patients with LGG with mutation IDH and non-codeleted 1p19q.

Conclusion

The subgroup classification we proposed has great application value. It can be used to select chemotherapeutic drugs and the prognosis of patients with target gliomas. The unique relationships between subgroups and tumor-related pathways are worthy of further investigation to identify therapeutic Gβγ heterodimer targets.

High expression of PSMC2 promotes gallbladder cancer through regulation of GNG4 and predicts poor prognosis

Gallbladder cancer (GBC) is a common malignant tumor of the biliary tract, which accounts for 80-95% of biliary tumors worldwide, and is the leading cause of biliary malignant tumor-related death. This study identified PSMC2 as a potential regulator in the development of GBC. We showed that PSMC2 expression in GBC tissues is significantly higher than that in normal tissues, while high PSMC2 expression was correlated with more advanced tumor grade and poorer prognosis. The knockdown of PSMC2 in GBC cells induced significant inhibition of cell proliferation, colony formation and cell motility, while the promotion of cell apoptosis. The construction and observation of the mice xenograft model also confirmed the inhibitory effects of PSMC2 knockdown on GBC development. Moreover, our mechanistic study recognized GNG4 as a potential downstream target of PSMC2, knockdown of which could aggravate the tumor suppression induced by PSMC2 knockdown in vitro and in vivo. In conclusion, for the first time, PSMC2 was revealed as a tumor promotor in the development of GBC, which could regulate cell phenotypes of GBC cells through the interaction with GNG4, and maybe a promising therapeutic target in GBC treatment.

G-protein subunit gamma-4 expression has potential for detection, prediction and therapeutic targeting in liver metastasis of gastric cancer

BACKGROUND

The liver is the most common site for haematogenous metastasis of gastric cancer, and liver metastasis is fatal.

METHODS

We conducted a transcriptomic analysis between metastatic foci in the liver, primary tumour and adjacent tissues from gastric cancer patients with metastasis limited to the liver. We determined mRNA expression levels in tumour tissues of 300 patients with gastric cancer via quantitative RT-PCR. The oncogenic phenotypes of GNG4 were determined with knockdown, knockout and forced expression experiments. We established and compared subcutaneous and liver metastatic mouse xenograft models of gastric cancer to reveal the roles of GNG4 in tumorigenesis in the liver.

RESULTS

GNG4 was upregulated substantially in primary gastric cancer tissues as well as liver metastatic lesions. High levels of GNG4 in primary cancer tissues were associated with short overall survival and the likelihood of liver recurrence. Functional assays revealed that GNG4 promoted cancer cell proliferation, the cell cycle and adhesiveness. Tumour formation by GNG4-knockout cells was moderately reduced in the subcutaneous mouse model and strikingly attenuated in the liver metastasis mouse model.

CONCLUSIONS

GNG4 expression may provide better disease monitoring for liver metastasis, and GNG4 may be a novel candidate therapeutic target for liver metastasis.

Genome-wide DNA methylation analysis using MethylCap-seq in canine high-grade B-cell lymphoma

DNA methylation is a comprehensively studied epigenetic modification and plays crucial roles in cancer development. In the present study, MethylCap-seq was used to characterize the genome-wide DNA methylation patterns in canine high-grade B-cell lymphoma (cHGBL). Canine methylated DNA fragments were captured and the MEDIUM-HIGH and LOW fraction of methylated DNA was obtained based on variation in CpG methylation density. In the MEDIUM-HIGH and LOW fraction, 2144 and 1987 cHGBL-specific hypermethylated genes, respectively, were identified. Functional analysis highlighted pathways strongly related to oncogenesis. The relevant signaling pathways associated with neuronal system were also revealed, echoing recent novel findings that neurogenesis plays key roles in tumor establishment. In addition, 14 genes were hypermethylated in all the cHGBL cases but not in the healthy dogs. These genes might be potential signatures for tracing cHGBL, and some of them have been reported to play roles in various types of cancers. Further, the distinct methylation pattern of cHGBL showed a concordance with the clinical outcome, suggesting that aberrant epigenetic changes may influence tumor behavior. In summary, our study characterized genome-wide DNA methylation patterns using MethylCap-seq in cHGBL; the findings suggest that specific DNA hypermethylation holds promise for dissecting tumorigenesis and uncovering biomarkers for monitoring the progression of cHGBL.

Molecular heterogeneity of guanine nucleotide binding-protein γ subunit 4 in left- and right-sided colon cancer

Molecular heterogeneity determines the differences in the pathological features, prognosis and survival after relapse when comparing left-sided colon cancer (LCC) and right-sided colon cancer (RCC). At present, the discrepancy in the underlying molecular events between the two types of colon cancer has not been thoroughly investigated. The present study aimed to explore novel targets to predict the disease stage and prognosis of LCC and RCC. Expression analysis of guanine nucleotide binding-protein γ subunit 4 (GNG4) was performed using the Gene Expression Profiling Interactive Analysis (GEPIA) and Oncomine databases. Survival and association analyses were performed using GEPIA and the colon adenocarcinoma dataset from The Cancer Genome Atlas database. GNG4-positive cells in a tissue microarray were examined using immunohistochemistry. According to the GNG4 expression data from Caucasian patients included in the TCGA dataset, GNG4 was highly expressed and positively associated with pathological stage and overall survival (OS) rates in colon cancer. GNG4 expression was higher in LCC than in RCC. Patients with LCC with high GNG4 expression exhibited higher pathological stage and lower survival rates, whereas this was not observed in patients with RCC. In addition, the clinical tissues used in the microarray showed that GNG4 expression was increased in Chinese patients with LCC compared with that in patients with RCC. Consistently, GNG4 expression was negatively associated with OS in patients with LCC, but not in patients with RCC. However, no association was observed between GNG4 expression and the disease stage of colon cancer in both patients with LCC and RCC. Overall, the molecular heterogeneity of GNG4 in LCC and RCC suggests that GNG4 may be used as a diagnostic and prognostic biomarker in patients with LCC.

DNA methylation of GHSR, GNG4, HOXD9 and SALL3 is a common epigenetic alteration in thymic carcinoma

Thymic epithelial tumors comprise thymoma, thymic carcinoma and neuroendocrine tumors of the thymus. Recent studies have revealed that the incidence of somatic non‑synonymous mutations is significantly higher in thymic carcinoma than in thymoma. However, limited information is currently available on epigenetic alterations in these types of cancer. In this study, we thus performed genome‑wide screening of aberrantly methylated CpG islands in thymoma and thymic carcinoma using Illumina HumanMethylation450 K BeadChip. We identified 92 CpG islands significantly hypermethylated in thymic carcinoma in relation to thymoma and selected G protein subunit gamma 4 (GNG4), growth hormone secretagogue receptor (GHSR), homeobox D9 (HOXD9) and spalt like transcription factor 3 (SALL3), which are related to cancer. We examined the promoter methylation of 4 genes in 46 thymic epithelial tumors and 20 paired thymus tissues using bisulfite pyrosequencing. Promoter methylation was significantly higher in thymic carcinoma than in thymoma and revealed a high discrimination between thymic carcinoma and thymoma in all 4 genes. Promoter methylation was higher in thymic carcinoma than in the thymus. No significant differences were observed in the promoter methylation of GNG4, HOXD9, or SALL3 between thymoma and the thymus. The promoter methylation of the 4 genes was not significantly higher in advanced‑stage tumors than in early‑stage tumors in all thymic epithelial tumors. Among the 4 genes, relapse‑free survival was significantly worse in tumors with a higher DNA methylation than in those with a lower DNA methylation in all thymic epithelial tumors. Moreover, relapse‑free survival was significantly worse in thymomas with a higher DNA methylation of HOXD9 and SALL3 than in those with a lower DNA methylation. On the whole, the findings of this study indicated that the promoter methylation of cancer‑related genes was significantly higher in thymic carcinoma than in thymoma and the thymus. This is a common epigenetic alteration of high diagnostic value in thymic carcinoma and may be involved in the carcinogenesis of thymic carcinoma. However, epigenetic alterations in the 3 genes, apart from GHSR, are not involved in the tumorigenesis of thymoma.

Identification of modules and functional analysis in CRC subtypes by integrated bioinformatics analysis

Colorectal cancer is one of the top three causes of cancer-related mortality globally, but no predictive molecular biomarkers are currently available for identifying the disease stage of colorectal cancer patients. Common molecular patterns in the disease, beyond superficial manifestations, can be significant in determining treatment choices. In this study, we used microarray data from colorectal cancer and adjacent normal tissue from the GEO database. These data were categorized into four consensus molecular subtypes based on distinct gene expression signatures. Weighted gene-based protein-protein interaction network analysis was performed for each subtype. NUSAP1, CD44, and COL4A1 modules were found to be statistically significant and present among all the subtypes and displayed though similar but not identical functional enrichment results. Reference of the characteristics of the subtypes to functional modules is necessary since the latter can stay resistant to platform changes and technique noise when compared with other analyses. The CMS4-mesenchymal group, which currently has a poor prognosis, was examined in the study. It is composed mainly of genes involved in immune and stromal expression, with modules focused on ECM dysregulation and chemokine biological processes. Hub genes detection and its' mapping into the protein-protein interaction network can be indicative of possible targets against specific modules. This approach identified subtypes using enrichment-oriented analysis in functional modules. Proper annotation of functional analysis of modules from different subtypes of CRC might be directive for finding extra options for treatment targets and guiding clinical routines.

Genome-wide analysis of long noncoding RNAs, microRNAs, and mRNAs forming a competing endogenous RNA network in repeated implantation failure

Repeated implantation failure (RIF) was mainly due to poor endometrium receptivity. Long noncoding RNAs (lncRNAs) could regulate endometrium receptivity and act in competing endogenous RNA (ceRNA) theory. However, the regulatory mechanism of the lncRNA-miRNA-mRNA network in repeated implantation failure (RIF) is unclear. We obtained RIF-related expression profiles of lncRNAs, mRNAs, and miRNAs using mid-secretory endometrial tissue samples from 5 women with RIF and 5 controls by RNA-sequencing. Co-expression analysis revealed that three functional modules were enriched in immune response/inflammation process; two functional modules were enriched in metabolic/ biosynthetic process, and one functional module were enriched in cell cycle pathway. By adding the miRNA data, ceRNA regulatory relationship of each module was reconstructed. The ceRNA network of the whole differentially expressed RNAs revealed 10 hub lncRNAs. Among them, TRG-AS1, SIMM25, and NEAT1 were involved in the module1, module2, and module3, respectively; LNC00511 and SLC26A4-AS1 in the module4; H19 in the module5. The real-time polymerase chain reaction (RT-PCR) results of 15 randomly selected RNAs were consistent with our sequencing data. These can be used as novel potential biomarkers for RIF. Furthermore, they might be involved in endometrium receptivity by acting as ceRNA.

Comprehensive Analysis of Core Genes and Potential Mechanisms in Rectal Cancer

Rectal cancer is a common type of colorectal cancer with high mortality and morbidity. The objective of this study was to identify gene signatures and uncover the potential mechanisms during rectal cancer samples. The gene expression profiles of GSE87211 data set were downloaded from GEO (Gene Expression Omnibus) database. The GSE87211 data set contained 2363 samples, including 203 rectal cancer samples and 160 matched mucosa control samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted, and protein-protein interaction network of differentially expressed genes (DEGs) was performed by Cytoscape. Then, Gene Expression Profiling Interactive Analysis (GEPIA) was applied to get the hub genes expression level and survival analysis between rectum adenocarcinoma (READ) tissues and normal tissues. In total, 846 DEGs were identified, including 402 upregulated genes and 444 downregulated genes. GO analysis showed that upregulated DEGs were enriched in inflammatory response, signal transduction, cell adhesion, immune response, and positive regulation of cell proliferation. KEGG pathway analysis showed that upregulated DEGs were enriched in cytokine-cytokine receptor interaction, Pi3K-Akt signaling pathway, and chemokine signaling pathway. The top 20 hub genes contained IL8, CXCR1, SSTR2, SST, CXCR2, GALR1, GAL, CXCL1, SSTR1, NPY1R, NPY, AGT, PPY, PPBP, CXCL2, CXCL6, CXCL11, CXCL3, GNG4, and GNGT1, and only four genes significantly increased expression levels with obvious changes of survival analysis in READ tissues based on GEPIA. Our study indicated that identified DEGs might promote our understanding of molecular mechanisms, which might be used as molecular targets or diagnostic biomarkers for the treatment of rectal cancer.

Identification of crucial miRNAs and lncRNAs for ossification of ligamentum flavum

The present study aimed to screen crucial micro (mi)RNAs and long non-coding (lnc)RNAs involved in the development of ossification of ligamentum flavum (OLF) based on the miRNA-mRNA and lncRNA-miRNA-mRNA competing endogenous (ce)RNA regulatory network analyses, which are rarely reported. The differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs) and differentially expressed miRNAs (DEMs) between 4 OLF and 4 healthy controls were identified using two microarray datasets GSE106253 and GSE106256 collected from the Gene Expression Omnibus database. A protein-protein interaction (PPI) network was constructed, followed by calculation of topological characteristics and sub-module analysis in order to obtain hub DEGs. The miRNA-mRNA and lncRNA-miRNA networks that were established based on their interaction pairs, obtained from miRwalk and starBase databases, respectively, were integrated to form the ceRNA network. The underlying functions of mRNAs were predicted using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The present study screened 828 DEGs, 119 DELs and 81 DEMs between OLF and controls. PPI network and module analyses identified interleukin (IL)10, adenylate cyclase (ADCY)5, suppressor of cytokine signaling (SOCS)3, G protein subunit gamma (GNG) 4, collagen type II α 1 chain (COL2A1) and collagen type XIII α 1 chain (COL13A1) as hub genes. The miRNA-mRNA network analysis demonstrated IL10 could be regulated by miR-210-3p, while COL13A1 and COL2A1 could be modulated by miR-329-3p and miR-222-5p, respectively. lncRNA-miRNA-mRNA ceRNA network analysis identified that small nucleolar RNA host gene 16-hsa-miR-196a-5p-SOCS3, ankyrin repeat and SOCS box containing 16-AS1-hsa-miR-379-5p-GNG4, nuclear enriched abundant transcript 1-has-miR-181b-5p-ADCY5, rhophilin 1-AS1-hsa-miR-299-3p-WNT7B interaction axes may be crucial. DAVID analysis predicted IL10, ADCY5, GNG4 and SOCS3 were involved in ‘adaptive immune response’, ‘Chemokine signaling pathway’ and ‘regulation of apoptosis’ processes, while COL2A1, COL13A1 and WNT7B may be ossification related. In conclusion, the identification of these crucial miRNAs and lncRNAs may be conducive for explaining the pathogenesis of OLF and provide certain natural, endogenous and nontoxic drug targets for the treatment of OLF.

Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis

BACKGROUND

The current study aimed to identify potential diagnostic and prognostic gene biomarkers for colorectal cancer (CRC) based on the Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) dataset.

METHODS

Microarray data of gene expression profiles of CRC from GEO and RNA-sequencing dataset of CRC from TCGA were downloaded. After screening overlapping differentially expressed genes (DEGs) by R software, functional enrichment analyses of the DEGs were performed using the DAVID database. Then, the STRING database and Cytoscape were used to construct a protein-protein interaction (PPI) network and identify hub genes. The receiver operating characteristic (ROC) curves were conducted to assess the diagnostic values of the hub genes. Cox proportional hazards regression was performed to screen the potential prognostic genes. Kaplan-Meier curve and the time-dependent ROC curve were used to assess the prognostic values of the potential prognostic genes for CRC patients.

RESULTS

Integrated analysis of GEO and TCGA databases revealed 207 common DEGs in CRC. A PPI network consisted of 70 nodes and 170 edges were constructed and top 10 hub genes were identified. The area under curve (AUC) of the ROC curves of the hub genes were 0.900, 0.927, 0.869, 0.863, 0.980, 0.682, 0.903, 0.790, 0.995, and 0.989 for CCL19, CXCL1, CXCL5, CXCL11, CXCL12, GNG4, INSL5, NMU, PYY, and SST, respectively. A prognostic gene signature consisted of 9 genes including SLC4A4, NFE2L3, GLDN, PCOLCE2, TIMP1, CCL28, SCGB2A1, AXIN2, and MMP1 was constructed with a good performance in predicting overall survivals of CRC patients. The AUC of the time-dependent ROC curve was 0.741 for 5-year survival.

CONCLUSION

The results in this study might provide some directive significance for further exploring the potential biomarkers for diagnosis and prognosis prediction of CRC patients.

Determination of genetic aberrations and novel transcripts involved in the pathogenesis of oligodendroglioma using array comparative genomic hybridization and next generation sequencing

The aim of the present study was to determine the genetic aberrations and novel transcripts, particularly the fusion transcripts, involved in the pathogenesis of low-grade and anaplastic oligodendroglioma. In the present study, tissue samples were obtained from patients with oligodendroglioma and additionally from archived tissue samples from the Brain Tumor Tissue Bank of the Brain Tumor Foundation of Canada. Six samples were obtained, three of which were low-grade oligodendroglioma and the other three anaplastic oligodendroglioma. DNA and RNA were extracted from each tissue sample. The resulting genomic DNA was then hybridized using the Agilent CytoSure 4×180K oligonucleotide array. Human reference DNA and samples were labeled using Cy3 cytidine 5′-triphosphate (CTP) and Cy5 CTP, respectively, while human Cot-1 DNA was used to reduce non-specific binding. Microarray-based comparative genomic hybridization data was then analyzed for genetic aberrations using the Agilent Cytosure Interpret software v3.4.2. The total RNA isolated from each sample was mixed with oligo dT magnetic beads to enrich for poly(A) mRNA. cDNAs were then synthesized and subjected to end-repair, poly(A) addition and connected using sequencing adapters using the Illumina TruSeq RNA Sample Preparation kit. The fragments were then purified and selected as templates for polymerase chain reaction amplification. The final library was constructed with fragments between 350–450 base pairs and sequenced using deep transcriptome sequencing on an Illumina HiSeq 2500 sequencer. The array comparative genomic hybridization revealed numerous amplifications and deletions on several chromosomes in all samples. However, the most interesting result was from the next generation sequencing, where one anaplastic oligodendroglioma sample was demonstrated to have five novel fusion genes that may potentially serve a critical role in tumor pathogenesis and progression.

Genetic regulation of antibody responsiveness to immunization in substrains of BALB/c mice

Antibody‐mediated immunity is highly protective against disease. The majority of current vaccines confer protection through humoral immunity, but there is high variability in responsiveness across populations. Identifying immune mechanisms that mediate low antibody responsiveness may provide potential strategies to boost vaccine efficacy. Here, we report diverse antibody responsiveness to unadjuvanted as well as adjuvanted immunization in substrains of BALB/c mice, resulting in high and low antibody response phenotypes. Furthermore, these antibody phenotypes were not affected by changes in environmental factors such as the gut microbiota composition. Antigen‐specific B cells following immunization had a marked difference in capability to class switch, resulting in perturbed IgG isotype antibody production. In vitro, a B‐cell intrinsic defect in the regulation of class‐switch recombination was identified in mice with low IgG antibody production. Whole genome sequencing identified polymorphisms associated with the magnitude of antibody produced, and we propose candidate genes that may regulate isotype class‐switching capability. This study highlights that mice sourced from different vendors can have significantly altered humoral immune response profiles, and provides a resource to interrogate genetic regulators of antibody responsiveness. Together these results further our understanding of immune heterogeneity and suggest additional research on the genetic influences of adjuvanted vaccine strategies is warranted for enhancing vaccine efficacy.

Identification of Core Genes and Key Pathways via Integrated Analysis of Gene Expression and DNA Methylation Profiles in Bladder Cancer

Background

Bladder cancer (BC) is the most common urological malignant tumor. In BC, aberrant DNA methylation is believed to be associated with carcinogenesis. Therefore, the identification of key genes and pathways could help determine the potential molecular mechanisms of BC development.

Material/Methods

Microarray data on gene expression and gene methylation were downloaded from the Gene Expression Omnibus (GEO) database. Abnormal methylated/expressed genes were analyzed by GEO2R and statistical software R. Gene Ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID database and KOBAS 3.0. STRING and Cytoscape software were used to construct protein–protein interaction (PPI) networks and analyze modules of the PPI network.

Results

A total of 71 hypomethylated/upregulated genes were significantly enriched in cell–cell adhesion and blood vessel development. KEGG pathway analysis highlighted p53 signaling and metabolic pathways. Five core genes in the PPI network were determined: CDH1, DDOST, CASP8, DHX15, and PTPRF. Additionally, 89 hypermethylated/downregulated genes were found. These genes were enriched mostly in cell adhesion and signal transduction. KEGG pathway analysis revealed enrichment in focal adhesion. The top 5 core genes in the PPI network were GNG4, ADCY9, NPY, ADRA2B, and PENK. We found most of the core genes were also significantly altered in the Cancer Genome Atlas database.

Conclusions

Abnormal methylated/expressed genes and key signaling pathways involved in BC were identified through integrated bioinformatics analysis. In the future, these genes may serve as biomarkers for diagnosis and therapeutic targets in BC.

Cancer-Associated IDH1 Promotes Growth and Resistance to Targeted Therapies in the Absence of Mutation

Oncogenic mutations in two isocitrate dehydrogenase (IDH)-encoding genes (IDH1 and IDH2) have been identified in acute myelogenous leukemia, low-grade glioma, and secondary glioblastoma (GBM). Our in silico and wet-bench analyses indicate that non-mutated IDH1 mRNA and protein are commonly overexpressed in primary GBMs. We show that genetic and pharmacologic inactivation of IDH1 decreases GBM cell growth, promotes a more differentiated tumor cell state, increases apoptosis in response to targeted therapies, and prolongs the survival of animal subjects bearing patient-derived xenografts (PDXs). On a molecular level, diminished IDH1 activity results in reduced α-ketoglutarate (αKG) and NADPH production, paralleled by deficient carbon flux from glucose or acetate into lipids, exhaustion of reduced glutathione, increased levels of reactive oxygen species (ROS), and enhanced histone methylation and differentiation marker expression. These findings suggest that IDH1 upregulation represents a common metabolic adaptation by GBMs to support macromolecular synthesis, aggressive growth, and therapy resistance.