MGMT Epigenetics: The Influence of Gene Body Methylation and Other Insights Derived from Integrated Methylomic, Transcriptomic, and Chromatin Analyses in Various Cancer Types

Sarcoma_CellminerCDB: A tool to interrogate the genomic and functional characteristics of a comprehensive collection of sarcoma cell lines

Sarcomas are a diverse group of rare malignancies composed of multiple different clinical and molecular subtypes. Due to their rarity and heterogeneity, basic, translational, and clinical research in sarcoma has trailed behind that of other cancers. Outcomes for patients remain generally poor due to an incomplete understanding of disease biology and a lack of novel therapies. To address some of the limitations impeding preclinical sarcoma research, we have developed Sarcoma_CellMinerCDB, a publicly available interactive tool that merges publicly available sarcoma cell line data and newly generated omics data to create a comprehensive database of genomic, transcriptomic, methylomic, proteomic, metabolic, and pharmacologic data on 133 annotated sarcoma cell lines. The reproducibility, functionality, biological relevance, and therapeutic applications of Sarcoma_CellMinerCDB described herein are powerful tools to address and generate biological questions and test hypotheses for translational research. Sarcoma_CellMinerCDB (https://discover.nci.nih.gov/SarcomaCellMinerCDB) aims to contribute to advancing the preclinical study of sarcoma.

The prediction of tumor and normal tissues based on the DNA methylation values of ten key sites

Abnormal DNA methylation can alter the gene expression to promote or inhibit tumorigenesis in colon adenocarcinoma (COAD). However, the finding important genes and key sites of abnormal DNA methylation which result in the occurrence of COAD is still an eventful task. Here, we studied the effects of DNA methylation in the 12 types of genomic features on the changes of gene expression in COAD, the 10 important COAD-related genes and the key abnormal DNA methylation sites were identified. The effects of important genes on the prognosis were verified by survival analysis. Moreover, it was shown that the important genes were participated in cancer pathways and were hub genes in a co-expression network. Based on the DNA methylation levels in the ten sites, the least diversity increment algorithm for predicting tumor tissues and normal tissues in seventeen cancer types are proposed. The better results are obtained in jackknife test. For example, the predictive accuracies are 94.17 %, 91.28 %, 89.04 % and 88.89 %, respectively, for COAD, rectum adenocarcinoma, pancreatic adenocarcinoma and cholangiocarcinoma. Finally, by computing enrichment score of infiltrating immunocytes and the activity of immune pathways, we found that the genes are highly correlated with immune microenvironment.

Transcriptional Pausing and Activation at Exons-1 and -2, Respectively, Mediate the MGMT Gene Expression in Human Glioblastoma Cells

Background: The therapeutically important DNA repair gene O⁶-methylguanine DNA methyltransferase (MGMT) is silenced by promoter methylation in human brain cancers. The co-players/regulators associated with this process and the subsequent progression of MGMT gene transcription beyond the non-coding exon 1 are unknown. As a follow-up to our recent finding of a predicted second promoter mapped proximal to the exon 2 [Int. J. Mol. Sci.2021, 22(5), 2492], we addressed its significance in MGMT transcription. Methods: RT-PCR, RT q-PCR, and nuclear run-on transcription assays were performed to compare and contrast the transcription rates of exon 1 and exon 2 of the MGMT gene in glioblastoma cells. Results: Bioinformatic characterization of the predicted MGMT exon 2 promoter showed several consensus TATA box and INR motifs and the absence of CpG islands in contrast to the established TATA-less, CpG-rich, and GAF-bindable exon 1 promoter. RT-PCR showed very weak MGMT-E1 expression in MGMT-proficient SF188 and T98G GBM cells, compared to active transcription of MGMT-E2. In the MGMT-deficient SNB-19 cells, the expression of both exons remained weak. The RT q-PCR revealed that MGMT-E2 and MGMT-E5 expression was about 80- to 175-fold higher than that of E1 in SF188 and T98G cells. Nuclear run-on transcription assays using bromo-uridine immunocapture followed by RT q-PCR confirmed the exceptionally lower and higher transcription rates for MGMT-E1 and MGMT-E2, respectively. Conclusions: The results provide the first evidence for transcriptional pausing at the promoter 1- and non-coding exon 1 junction of the human MGMT gene and its activation/elongation through the protein-coding exons 2 through 5, possibly mediated by a second promoter. The findings offer novel insight into the regulation of MGMT transcription in glioma and other cancer types.

Genomic Space of MGMT in Human Glioma Revisited: Novel Motifs, Regulatory RNAs, NRF1, 2, and CTCF Involvement in Gene Expression

Background: The molecular regulation of increased MGMT expression in human brain tumors, the associated regulatory elements, and linkages of these to its epigenetic silencing are not understood. Because the heightened expression or non-expression of MGMT plays a pivotal role in glioma therapeutics, we applied bioinformatics and experimental tools to identify the regulatory elements in the MGMT and neighboring EBF3 gene loci. Results: Extensive genome database analyses showed that the MGMT genomic space was rich in and harbored many undescribed RNA regulatory sequences and recognition motifs. We extended the MGMT’s exon-1 promoter to 2019 bp to include five overlapping alternate promoters. Consensus sequences in the revised promoter for (a) the transcriptional factors CTCF, NRF1/NRF2, GAF, (b) the genetic switch MYC/MAX/MAD, and (c) two well-defined p53 response elements in MGMT intron-1, were identified. A putative protein-coding or non-coding RNA sequence was located in the extended 3′ UTR of the MGMT transcript. Eleven non-coding RNA loci coding for miRNAs, antisense RNA, and lncRNAs were identified in the MGMT-EBF3 region and six of these showed validated potential for curtailing the expression of both MGMT and EBF3 genes. ChIP analysis verified the binding site in MGMT promoter for CTCF which regulates the genomic methylation and chromatin looping. CTCF depletion by a pool of specific siRNA and shRNAs led to a significant attenuation of MGMT expression in human GBM cell lines. Computational analysis of the ChIP sequence data in ENCODE showed the presence of NRF1 in the MGMT promoter and this occurred only in MGMT-proficient cell lines. Further, an enforced NRF2 expression markedly augmented the MGMT mRNA and protein levels in glioma cells. Conclusions: We provide the first evidence for several new regulatory components in the MGMT gene locus which predict complex transcriptional and posttranscriptional controls with potential for new therapeutic avenues.