STAT1 mediated downregulation of the tumor suppressor gene PDCD4, is driven by the atypical cadherin FAT1, in glioblastoma.

STAT1 (Signal Transducer and Activator of Transcription 1), belongs to the STAT protein family, essential for cytokine signaling. It has been reported to have either context dependent oncogenic or tumor suppressor roles in different tumors. Earlier, we demonstrated that Glioblastoma multiforme (GBMs) overexpressing FAT1, an atypical cadherin, had poorer outcomes. Overexpressed FAT1 promotes pro-tumorigenic inflammation, migration/invasion by downregulating tumor suppressor gene, PDCD4. Here, we demonstrate that STAT1 is a novel mediator downstream to FAT1, in downregulating PDCD4 in GBMs. In-silico analysis of GBM databases as well as q-PCR analysis in resected GBM tumors showed positive correlation between STAT1 and FAT1 mRNA levels. Kaplan-Meier analysis showed poorer survival of GBM patients having high FAT1 and STAT1 expression. SiRNA-mediated knockdown of FAT1 decreased STAT1 and increased PDCD4 expression in glioblastoma cells (LN229 and U87MG). Knockdown of STAT1 alone resulted in increased PDCD4 expression. In silico analysis of the PDCD4 promoter revealed four putative STAT1 binding sites (Site1-Site4). ChIP assay confirmed the binding of STAT1 to site1. ChIP-PCR revealed decrease in the binding of STAT1 on the PDCD4 promoter after FAT1 knockdown. Site directed mutagenesis of Site1 resulted in increased PDCD4 luciferase activity, substantiating STAT1 mediated PDCD4 inhibition. EMSA confirmed STAT1 binding to the Site 1 sequence. STAT1 knockdown led to decreased expression of pro-inflammatory cytokines and EMT markers, and reduced migration/invasion of GBM cells. This study therefore identifies STAT1 as a novel downstream mediator of FAT1, promoting pro-tumorigenic activity in GBM, by suppressing PDCD4 expression.

Identification of Gender-Specific Molecular Differences in Glioblastoma (GBM) and Low-Grade Glioma (LGG) by the Analysis of Large Transcriptomic and Epigenomic Datasets.

Differences in the incidence and outcome of glioma between males and females are well known, being more striking for glioblastoma (GB) than low-grade glioma (LGG). The extensive and well-annotated data in publicly available databases enable us to analyze the molecular basis of these differences at a global level. Here, we have analyzed The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases to identify molecular indicators for these gender-based differences by different methods. Based on the nature of data available/accessible, the transcriptomic profile was studied in TCGA by using DeSeq2 and in CGGA by T-test, after correction based. Only IDH1 wild-type tumors were studied in CGGA. Using weighted gene co-expression network analysis (WGCNA), network analysis was done, followed by the assessment of modular differential connectivity. Differentially affected signaling pathways were identified. The gender-based effects of differentially expressed genes on survival were determined. DNA methylation was studied as an indicator of gender-based epigenetic differences. The results clearly showed gender-based differences in both GB and LGG, whatever method or database was used. While there were differences in the results obtained between databases and methods used, some major signaling pathways such as Wnt signaling and pathways involved in immune processes and the adaptive immune response were common to different assessments. There was also a differential gender-based influence of several genes on survival. Also, the autosomal genes NOX, FRG1BP, and AL354714.2 and X-linked genes such as PUDP, KDM6A, DDX3X, and SYAP1 had differential DNA methylation and expression profile in male and female GB, while for LGG, these included autosomal genes such as CNIH3 and ANKRD11 and X-linked genes such as KDM6A, MAOB, and EIF2S3. Some, such as FGF13 and DDX3X, have earlier been shown to have a role in tumor behavior, though their dimorphic effects in males and females have not been identified. Our study thus identifies several crucial differences between male and female glioma, which could be validated further. It also highlights that molecular studies without consideration of gender can obscure critical elements of biology and emphasizes the importance of parallel but separate analyses of male and female glioma.

Identification of lncRNAs Associated With Neuroblastoma in Cross-Sectional Databases: Potential Biomarkers.

Long non-coding RNAs (lncRNAs) have emerged as an important regulatory control in biological systems. Though the field of lncRNA has been progressing rapidly, a complete understanding of the role of lncRNAs in neuroblastoma pathogenesis is still lacking. To identify the abrogated lncRNAs in primary neuroblastoma and in the metastasized as well as the relapsed form of neuroblastoma, we analyzed an RNA-seq dataset on neuroblastoma that is available online to identify the lncRNAs that could potentially be contributing to the biology of neuroblastoma. The identified lncRNAs were further scrutinized using a publicly available epigenetic dataset of neuroblastoma and a cancer database. After this cross-sectional study, we were able to identify three significant lncRNAs, CASC15, PPP1R26-AS1, and USP3-AS1, which could serve as potential biomarkers in clinical studies of neuroblastoma pathogenesis.