Drug repositioning and biomarkers in low-grade glioma via bioinformatics approach

Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis

Glioblastoma (GBM) is the most devastating and frequent type of primary brain tumor with high morbidity and mortality. Despite the use of surgical resection followed by radio- and chemotherapy as standard therapy, the progression of GBM remains dismal with a median overall survival of <15 months. GBM embodies a populace of cancer stem cells (GSCs) that is associated with tumor initiation, invasion, therapeutic resistance, and post-treatment reoccurrence. However, understanding the potential mechanisms of stemness and their candidate biomarkers remains limited. Hence in this investigation, we aimed to illuminate potential candidate hub genes and key pathways associated with the pathogenesis of GSC in the development of GBM. The integrated analysis discovered differentially expressed genes (DEGs) between the brain cancer tissues (GBM and GSC) and normal brain tissues. Multiple approaches, including gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were employed to functionally annotate the DEGs and visualize them through the R program. The significant hub genes were identified through the protein-protein interaction network, Venn diagram analysis, and survival analysis. We observed that the upregulated DEGs were prominently involved in the ECM-receptor interaction pathway. The downregulated genes were mainly associated with the axon guidance pathway. Five significant hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) were screened out through multiple analyses. GO and KEGG analyses of hub genes uncovered that these genes were primarily enriched in disease-associated pathways such as the inhibition of apoptosis and the DNA damage repair mechanism, activation of the cell cycle, EMT (epithelial-mesenchymal transition), hormone AR (androgen receptor), hormone ER (estrogen receptor), PI3K/AKT (phosphatidylinositol 3-kinase and AKT), RTK (receptor tyrosine kinase), and TSC/mTOR (tuberous sclerosis complex and mammalian target of rapamycin). Consequently, the epigenetic regulatory network disclosed that hub genes played a vital role in the progression of GBM. Finally, candidate drugs were predicted that can be used as possible drugs to treat GBM patients. Overall, our investigation offered five hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) that could be used as precise diagnostic and prognostic candidate biomarkers of GBM and might be used as personalized therapeutic targets to obstruct gliomagenesis.

Role of FRG1 in predicting the overall survivability in cancers using multivariate based optimal model

FRG1 has a role in tumorigenesis and angiogenesis. Our preliminary analysis showed that FRG1 mRNA expression is associated with overall survival (OS) in certain cancers, but the effect varies. In cervix and gastric cancers, we found a clear difference in the OS between the low and high FRG1 mRNA expression groups, but the difference was not prominent in breast, lung, and liver cancers. We hypothesized that FRG1 expression level could affect the functionality of the correlated genes or vice versa, which might mask the effect of a single gene on the OS analysis in cancer patients. We used the multivariate Cox regression, risk score, and Kaplan Meier analyses to determine OS in a multigene model. STRING, Cytoscape, HIPPIE, Gene Ontology, and DAVID (KEGG) were used to deduce FRG1 associated pathways. In breast, lung, and liver cancers, we found a distinct difference in the OS between the low and high FRG1 mRNA expression groups in the multigene model, suggesting an independent role of FRG1 in survival. Risk scores were calculated based upon regression coefficients in the multigene model. Low and high-risk score groups showed a significant difference in the FRG1 mRNA expression level and OS. HPF1, RPL34, and EXOSC9 were the most common genes present in FRG1 associated pathways across the cancer types. Validation of the effect of FRG1 mRNA expression level on these genes by qRT-PCR supports that FRG1 might be an upstream regulator of their expression. These genes may have multiple regulators, which also affect their expression, leading to the masking effect in the survival analysis. In conclusion, our study highlights the role of FRG1 in the survivability of cancer patients in tissue-specific manner and the use of multigene models in prognosis.

Expression and Prognostic Value Identification of Methylenetetrahydrofolate Dehydrogenase 2 (MTHFD2) in Brain Low-Grade Glioma

Objective

This study aimed to reveal the potential function of methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) and emphasized its importance in brain low-grade glioma (LGG).

Methods

We firstly explored the differential expression of MTHFD2 mRNA in LGG and normal tissues, followed by correlation analysis of MTHFD2 mRNA expression with patient’s clinical characteristics. MTHFD2 protein expression in LGG and subcellular location were also evaluated. Then, survival analysis was performed to reveal the influence of MTHFD2 expression on the overall survival of patients, and Cox regression analysis was applied to predict the prognostic factor for overall survival of LGG. Finally, we performed functional analysis to reveal potential MTHFD2-associated pathways involved in LGG.

Results

We found that MTHFD2 was highly expressed in LGG patients (P<0.05), and MTHFD2 expression was related to patient’s age and IDH mutation status (all P<0.05). MTHFD2 protein was mainly localized to the mitochondria. Survival analysis showed that high expression of MTHFD2 desirably improved the prognosis of LGG patients (P<0.001), especially for those patients with age ≥45 years (P<0.05). But independent prognostic role of MTHFD2 in LGG was not observed. Pathway enrichment analysis indicated that MTHFD2 high expression significantly and positively participated in the pathway of one carbon pool by folate (all P<0.05).

Conclusion

High expression of MTHFD2 was observed in LGG, which was favorable for the overall survival of LGG patients. Our results assumed that MTHFD2 high expression might play a pivotal role in LGG through positively regulating pathway of one carbon pool by folate.

miR-944 Suppresses EGF-Induced EMT in Colorectal Cancer Cells by Directly Targeting GATA6

Background

miR-944 belongs to the MicroRNAs family, as shown in our previous study, and is essential in the colorectal cancer (CRC) progression. It is negatively associated with invasion depth and lymph node status. Epithelial-mesenchymal transition (EMT) is essential in tumor invasion and metastasis. However, the relationship between miR-944 and EMT in CRC is unknown and should be further investigated.

Methods

Epithelial–mesenchymal transition (EMT) progression in CRC cell lines was detected with Cell morphology and Western blotting. CRC cell migration and invasion were examined using Transwell assays. Transcriptome and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. The potential pathway of miR-944 and GATA6 were predicted using KEGG analysis. Colocalization was validated using immunofluorescence and Immunohistochemistry. Nuclear and Cytoplasmic Protein Extraction assays were conducted to determine the effects of miR-944 on Wnt/β-catenin signaling.

Results

We found that miR‑944 influences EGF-induced EMT malignant phenotype in vitro. KEGG analyses showed that miR-944 and GATA6 are associated with EMT related pathways, wnt signaling pathways. On the other hand, Western Blot analyses showed that miR-944 can regulate EMT and wnt-β-catenin pathway-related protein, including β-catenin, ZEB1, snail1 via GATA6 regulation. miR-944 also abrogates E-ca after EGF induction. Immunohistochemistry (IHC) and Immunofluorescence (IF) co-expression showed that GATA6 expression is positively associated with β-catenin and ZEB1. GATA6 silencing can reverse EMT malignant phenotype and alterations of related protein induced by miR-944. Quantitative polymerase chain reaction analysis results showed that miR-944 is negatively associated with the UICC stage (P= 0.02), lymph nodes (p=0.04), and liver metastasis (p=0.03). Moreover, patients with high miR-944 expression have better survival (p=0.045). We finally combined miR-944 and GATA6 and found that miR-944/GATA6 ratio could be a novel prognostic biomarker in the TCGA dataset and it is an independent risk prognosis factor (p=0.045).

Conclusion

Our results suggest that miR-944 suppresses the aggressive biological processes by directly repressing GATA6 expression and could be a potential candidate for therapeutic applications in CRC.