Dataset Information

Functional analysis of low-grade glioma genetic variants predicts key target genes and transcription factors.

ABSTRACT:

Background

Large-scale genome-wide association studies (GWAS) have implicated thousands of germline genetic variants in modulating individuals' risk to various diseases, including cancer. At least 25 risk loci have been identified for low-grade gliomas (LGGs), but their molecular functions remain largely unknown.

Methods

We hypothesized that GWAS loci contain causal single nucleotide polymorphisms (SNPs) that reside in accessible open chromatin regions and modulate the expression of target genes by perturbing the binding affinity of transcription factors (TFs). We performed an integrative analysis of genomic and epigenomic data from The Cancer Genome Atlas and other public repositories to identify candidate causal SNPs within linkage disequilibrium blocks of LGG GWAS loci. We assessed their potential regulatory role via in silico TF binding sequence perturbations, convolutional neural network trained on TF binding data, and simulated annealing-based interpretation methods.

Results

We built an interactive website (http://education.knoweng.org/alg3/) summarizing the functional footprinting of 280 variants in 25 LGG GWAS regions, providing rich information for further computational and experimental scrutiny. We identified as case studies PHLDB1 and SLC25A26 as candidate target genes of rs12803321 and rs11706832, respectively, and predicted the GWAS variant rs648044 to be the causal SNP modulating ZBTB16, a known tumor suppressor in multiple cancers. We showed that rs648044 likely perturbed the binding affinity of the TF MAFF, as supported by RNA interference and in vitro MAFF binding experiments.

Conclusions

The identified candidate (causal SNP, target gene, TF) triplets and the accompanying resource will help accelerate our understanding of the molecular mechanisms underlying genetic risk factors for gliomas.

SUBMITTER: Manjunath M

PROVIDER: S-EPMC8041333 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionPatients with high-grade glioma (HGG) suffered poor survival due to inherent or acquired therapeutic resistance and refractory recurrence. The outcome of HGG patients has improved little during the past decade. Therefore, molecular signatures are urgently needed for improving diagnosis, survival prediction and identification of therapeutic targets for HGG. E2F transcription factors (E2Fs), a family of transcription factors recognized as master regulators of cell proliferation, have been found to be involved in the pathogenesis of various tumor types.AimsTo investigate the expression of E2Fs and their prognosis value in high-grade glioma (HGG).ResultsExpression of E2Fs was analyzed in 394 HGG samples from TCGA dataset. E2Fs were generally expressed in HGG. Except for E2F3 and E2F5, expression of E2Fs was significantly upregulated and linked with grade progression. E2F1, E2F2, E2F7, and E2F8 were highly correlated with aggressive proliferation oncogenes, as well as potential therapeutic resistance oncogenes. Elevated E2Fs (not E2F3) were associated with adverse tumor features and poorer outcome. E2F7 and E2F8 exhibited superior outcome prediction performance compared with other E2Fs. Additionally, E2F7 and E2F8 independently predicted poorer survival in HGG patients. Gene set enrichment analysis identified a variety of critical oncogenic pathways that were tightly associated with E2F7 or E2F8, including epithelial-mesenchymal transition, NFκB, STAT3, angiogenesis pathways. Furthermore, elevated expression of E2F7 indicated worse therapeutic response of HGG to irradiation and silencing of E2F7 conferred higher cell-killing effect when combined with irradiation treatment. Mechanically, E2F7 directly regulates the transcriptional activity of EZH2 via binding at the corresponding promoter area.ConclusionsE2Fs (except for E2F3 and E2F5) are highly expressed in HGG and indicate adverse outcome. E2F7 and E2F8 were identified as novel potential prognostic markers in HGG. E2F7 was further validated to be closely associated with radioresistance of HGG and a critical transcriptional regulator of EZH2.