Transcription factor 7 functions as an unfavorable prognostic marker of glioblastoma multiforme by promoting proliferation by upregulating c-Myc

Integrative analysis of small non-coding RNAs predicts a piRNA/miRNA-CCND1/BRAF/HRH1/ATXN3 regulatory circuit that drives oncogenesis in glioblastoma

The high-grade astrocytoma, glioblastoma multiforme (GBM), is the most common primary tumour of the brain, known for being aggressive and developing drug resistance. The non-coding RNAs (ncRNAs), such as microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), have critical functions in tumorigenesis and cancer drug resistance. Hence, we profiled miRNAs, piRNAs, and genes in U-87 MG GBM cells by next-generation sequencing and performed target prediction, pathway enrichment, protein-protein interaction, co-expression studies, and qRT-PCR validations to predict their possible roles in the malignancy. The study identified 335 miRNAs, 665 piRNAs, and 4286 genes differentially expressed (DE) in GBM. Among them 128 DE genes (DEGs) were targeted by both miRNAs and piRNAs, while 1817 and 192 were targeted solely by miRNAs or piRNAs, respectively. Interestingly, all the DEG targets enriched in cancer processes were overexpressed in GBM. Among these, BRAF was solely targeted by two piRNAs and this was found to be co-expressed with 19 sole targets of 5 miRNAs, including CCND1, and both were found to regulate cell proliferation in cancer. We conjectured that upregulated HRH1 and ATXN3 were targeted by both piRNAs and miRNAs, and along with BRAF and CCND1 might induce cell proliferation in GBM through G-protein-coupled receptor or Akt signalling pathways due to downregulation of the respective targeting small RNAs. These targets were also linked to the progression and overall survival of GBM patients, suggesting that they could be used as biomarkers. Overall, this study has identified a few novel ncRNA targets, which might aid in a better understanding of GBM pathogenesis.

High DKK3 expression related to immunosuppression was associated with poor prognosis in glioblastoma: machine learning approach

Background

Glioblastoma multiforme (GBM) is an aggressive malignant primary brain tumor. Wnt/β-catenin is known to be related to GBM stemness. Cancer stem cells induce immunosuppressive and treatment resistance in GBM. We hypothesized that Wnt/β-catenin-related genes with immunosuppression could be related to the prognosis in patients with GBM.

Methods

We obtained the clinicopathological data of 525 patients with GBM from the brain cancer gene database. The fraction of tumor-infiltrating immune cells was evaluated using in silico flow cytometry. Among gene sets of Wnt/β-catenin pathway, Dickkopf-3 (DKK3) gene related to the immunosuppressive response was found using machine learning. We performed gene set enrichment analysis (GSEA), network-based analysis, survival analysis and in vitro drug screening assays based on Dickkopf-3 (DKK3) expression.

Results

In analyses of 31 genes related to Wnt/β-catenin signaling, high DKK3 expression was negatively correlated with increased antitumoral immunity, especially CD8 + and CD4 + T cells, in patients with GBM. High DKK3 expression was correlated with poor survival and disease progression in patients with GBM. In pathway-based network analysis, DKK3 was directly linked to the THY1 gene, a tumor suppressor gene. Through in vitro drug screening, we identified navitoclax as an agent with potent activity against GBM cell lines with high DKK3 expression.

Conclusions

These results suggest that high DKK3 expression could be a therapeutic target in GBM. The results of the present study could contribute to the design of future experimental research and drug development programs for GBM.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00262-022-03222-4.

Identification of Hub Genes and Key Pathways Associated with Anti-VEGF Resistant Glioblastoma Using Gene Expression Data Analysis

Anti-VEGF therapy is considered to be a useful therapeutic approach in many tumors, but the low efficacy and drug resistance limit its therapeutic potential and promote tumor growth through alternative mechanisms. We reanalyzed the gene expression data of xenografts of tumors of bevacizumab-resistant glioblastoma multiforme (GBM) patients, using bioinformatics tools, to understand the molecular mechanisms of this resistance. An analysis of the gene set data from three generations of xenografts, identified as 646, 873 and 1220, differentially expressed genes (DEGs) in the first, fourth and ninth generations, respectively, of the anti-VEGF-resistant GBM cells. Gene Ontology (GO) and pathway enrichment analyses demonstrated that the DEGs were significantly enriched in biological processes such as angiogenesis, cell proliferation, cell migration, and apoptosis. The protein–protein interaction network and module analysis revealed 21 hub genes, which were enriched in cancer pathways, the cell cycle, the HIF1 signaling pathway, and microRNAs in cancer. The VEGF pathway analysis revealed nine upregulated (IL6, EGFR, VEGFA, SRC, CXCL8, PTGS2, IDH1, APP, and SQSTM1) and five downregulated hub genes (POLR2H, RPS3, UBA52, CCNB1, and UBE2C) linked with several of the VEGF signaling pathway components. The survival analysis showed that three upregulated hub genes (CXCL8, VEGFA, and IDH1) were associated with poor survival. The results predict that these hub genes associated with the GBM resistance to bevacizumab may be potential therapeutic targets or can be biomarkers of the anti-VEGF resistance of GBM.

C-Myc Signaling Pathway in Treatment and Prevention of Brain Tumors

Brain tumors are responsible for high morbidity and mortality worldwide. Several factors such as the presence of blood-brain barrier (BBB), sensitive location in the brain, and unique biological features challenge the treatment of brain tumors. The conventional drugs are no longer effective in the treatment of brain tumors, and scientists are trying to find novel therapeutics for brain tumors. In this way, identification of molecular pathways can facilitate finding an effective treatment. c-Myc is an oncogene signaling pathway capable of regulation of biological processes such as apoptotic cell death, proliferation, survival, differentiation, and so on. These pleiotropic effects of c-Myc have resulted in much fascination with its role in different cancers, particularly brain tumors. In the present review, we aim to demonstrate the upstream and down-stream mediators of c-Myc in brain tumors such as glioma, glioblastoma, astrocytoma, and medulloblastoma. The capacity of c-Myc as a prognostic factor in brain tumors will be investigated. Our goal is to define an axis in which the c-Myc signaling pathway plays a crucial role and to provide direction for therapeutic targeting in these signaling networks in brain tumors.

Clinical Significance of Transcription Factor 7 (TCF7) as a Prognostic Factor in Gastric Cancer

Background

Transcription factor 7 (TCF7) plays an essential role in Wnt signaling by interacting with β-catenin. Emerging evidence demonstrates that overexpression of TCF7 promotes progression or correlates with poor progression in several types of cancers, but the functions of TCF7 in gastric cancer (GC) have not been revealed.

Material/Methods

A total of 168 patients with GC who underwent radical surgeries were collected and regarded as the test cohort. The expression of TCF7 in the 168 patients was detected with immunohistochemistry. Moreover, the mRNA levels of TCF7 in 11 pairs of GC and adjacent tissues were detected with quantitative real-time PCR (qRT-PCR). The correlations between TCF7 and the clinicopathological factors were evaluated with the chi-square test, and the prognostic value of TCF7 in GC was investigated with univariate analysis and multivariate analysis.

Results

The mRNA levels of TCF7 in GC tissues were significantly higher than in corresponding tumor adjacent tissues. The patients of low TCF7 expression and high TCF7 expression accounted for 76.79% (129/168) and 23.21% (39/168), respectively. In our experiments, TCF7 was significantly associated with positive lymphatic invasion (P=0.022) and metastasis (P<0.001). The high expression of TCF7 was correlated with low survival rates (P=0.012) and was confirmed as an independent prognostic factor (HR=1.92, 95%CI =1.06–3.47, P=0.031) of GC in multivariate analysis.

Conclusions

TCF7 expression is correlated with metastasis and is an independent prognostic factor of GC. TCF7 detection of GC could help stratify the patients with high risk and guide precise treatment.