Mining database for the therapeutic targets and prognostic biomarkers among STAT family in glioblastoma

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.

High Expression of Interferon Pathway Genes CXCL10 and STAT2 Is Associated with Activated T-Cell Signature and Better Outcome of Oral Cancer Patients

To improve the survival rate of cancer patients, biomarkers for both early diagnosis and patient stratification for appropriate therapeutics play crucial roles in precision oncology. Investigation of altered gene expression and the relevant molecular pathways in cancer cells are helpful for discovering such biomarkers. In this study, we explore the potential prognostic biomarkers for oral cancer patients through systematically analyzing five oral cancer transcriptomic data sets (TCGA, GSE23558, GSE30784, GSE37991, and GSE138206). Gene Set Enrichment Analysis (GSEA) was individually applied to each data set and the upregulated Hallmark molecular pathways of each data set were intersected to generate 13 common pathways including interferon-α/γ pathways. Among the 5 oral cancer data sets, 43 interferon pathway genes were commonly upregulated and 17 genes exhibited prognostic values in TCGA cohort. After validating in another oral cancer cohort (GSE65858), high expressions of C-X-C motif chemokine ligand 10 (CXCL10) and Signal transducer and activator of transcription 2 (STAT2) were confirmed to be good prognostic biomarkers. GSEA of oral cancers stratified by CXCL10/STAT2 expression showed that activation of T-cell pathways and increased tumor infiltration scores of Type 1 T helper (Th1) and CD8+ T cells were associated with high CXCL10/STAT2 expression. These results suggest that high CXCL10/STAT2 expression can predict a favorable outcome in oral cancer patients.

Comprehensive Analysis of CD163 as a Prognostic Biomarker and Associated with Immune Infiltration in Glioblastoma Multiforme

Background

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignancy in adults with high aggression. The prognosis of GBM patients is poor. There is a critical need for novel biomarkers for the prognosis and therapy of GBM.

Methods

Differentially expressed genes (DEGs) in GBM were screened using TCGA cohort. Univariate and multivariate Cox regression analyses were performed on DEGs to identify the optimal prognosis-related genes. qRT-PCR was performed to verify the result.

Results

A total of 5216 DEGs, including 2785 upregulated and 2458 downregulated genes, were obtained. Enrichment analysis revealed that these DEGs were mainly involved in the p53 signaling pathway and cell cycle, immune response, and MAPK signaling pathways. Moreover, the top 50 DEGs were associated with drug resistance or drug sensitivity. Prognosis analysis revealed that GBM patients with a high expression of CD163 and CHI3L2 had a poor overall survival, prognosis-free survival, and disease-specific survival. The univariate and multivariate analyses revealed that CD163 and age were independent factors affecting the prognosis of GBM patients. A validation study revealed that CD163 was upregulated in GBM tissues and associated with poor overall survival. Moreover, further analysis revealed that CD163 showed significant correlation with immune cells, immune biomarkers, chemokines, and chemokine receptors. We also identified several CD163-associated kinase, miRNA, and transcription factor targets in GBM, including LCK, miR-483, and ELF1.

Conclusions

In conclusion, our study suggested CD163 as a prognostic biomarker and associated it with immune infiltration in GBM.