Differential regulation of CpG island methylation within divergent and unidirectional promoters in colorectal cancer

FHIP1A-DT is a potential novel diagnostic, prognostic, and therapeutic biomarker of colorectal cancer: A pan-cancer analysis

BACKGROUND

FHIP1A-DT is a long non-coding RNA (lncRNA) obtained by divergent transcription whose mechanism in pan-cancer and colorectal cancer (CRC) is unclear. We elucidated the molecular mechanism of FHIP1A-DT through bioinformatics analysis and in vitro experiments.

METHODS

Pan-cancer and CRC data were downloaded from the University of California, Santa Cruz (UCSC) Genome Browser and the Cancer Genome Atlas (TCGA). We analyzed FHIP1A-DT expression and its relationship with clinical stage, diagnosis, prognosis, and immunity characteristics in pan-cancer. We also analyzed FHIP1A-DT expression in CRC and explored the relationship between FHIP1A-DT and CRC diagnosis and prognosis. Then, we analyzed the correlation between FHIP1A-DT and drug sensitivity, immune cell infiltration, and the biological processes involved in FHIP1A-DT. The competing endogenous RNA (ceRNA) regulatory network associated with FHIP1A-DT was explored. External validation was conducted using external data sets GSE17538 and GSE39582 and in vitro experiments.

RESULTS

FHIP1A-DT expression was different in pan-cancer and had excellent diagnostic and prognostic capability for pan-cancer. FHIP1A-DT was also related to the pan-cancer tumor mutation burden (TMB), microsatellite instability (MSI), and immune cell content. FHIP1A-DT was downregulated in CRC, where patients with CRC with low FHIP1A-DT expression had a worse prognosis. A nomogram combined with FHIP1A-DT expression demonstrated excellent predictive ability for prognosis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that FHIP1A-DT was associated with epigenetic modification and regulated many cancer-related pathways. The ceRNA network demonstrated the potential gene regulation of FHIP1A-DT. FHIP1A-DT was related to many chemotherapeutic drug sensitivities and immune cell infiltration such as CD4 memory resting T cells, monocytes, plasma cells, neutrophils, and M2 macrophages. The FHIP1A-DT expression and prognostic analysis of GSE17538 and GSE39582, and qPCR yielded similar external verification results.

CONCLUSION

FHIP1A-DT was a novel CRC-related lncRNA related to CRC diagnosis, prognosis, and treatment sensitivity. It could be used as a significant CRC biomarker in the future.

MSIMEP: Predicting microsatellite instability from microarray DNA methylation tumor profiles

Deficiency in DNA MMR activity results in tumors with a hypermutator phenotype, termed microsatellite instability (MSI). Beyond its utility in Lynch syndrome screening algorithms, today MSI has gained importance as predictive biomarker for various anti-PD-1 therapies across many different tumor types. Over the past years, many computational methods have emerged to infer MSI using either DNA- or RNA-based approaches. Considering this together with the fact that MSI-high tumors frequently exhibit a hypermethylated phenotype, herein we developed and validated MSIMEP, a computational tool for predicting MSI status from microarray DNA methylation tumor profiles of colorectal cancer samples. We demonstrated that MSIMEP optimized and reduced models have high performance in predicting MSI in different colorectal cancer cohorts. Moreover, we tested its consistency in other tumor types with high prevalence of MSI such as gastric and endometrial cancers. Finally, we demonstrated better performance of both MSIMEP models vis-à-vis a MLH1 promoter methylation-based one in colorectal cancer.

The Progress of the Specific and Rapid Genetic Detection Methods for Ovarian Cancer Diagnosis and Treatment

Cancer is a public health problem that threatens human health. Due to the lack of specific and rapid diagnosis and treatment methods, the 5-year survival rate of patients has not been effectively improved in the past 10 years. Abnormal gene expression is closely related to the occurrence and development of cancer. Cancer diagnosis and treatment methods based on genetic testing have received extensive attention in recent years. It is essential to explore specific and rapid cancer genetic testing methods. Taking ovarian cancer as an example, we reviewed the progress of specific and rapid nucleic acid detection methods related to cancer risk assessment, low-abundance mutation detection, and methylation detection, to provide new strategies and ideas for related research.

A systems-based framework to computationally describe putative transcription factors and signaling pathways regulating glycan biosynthesis

Glycosylation is a common posttranslational modification, and glycan biosynthesis is regulated by a set of glycogenes. The role of transcription factors (TFs) in regulating the glycogenes and related glycosylation pathways is largely unknown. In this work, we performed data mining of TF–glycogene relationships from the Cistrome Cancer database (DB), which integrates chromatin immunoprecipitation sequencing (ChIP-Seq) and RNA-Seq data to constitute regulatory relationships. In total, we observed 22,654 potentially significant TF–glycogene relationships, which include interactions involving 526 unique TFs and 341 glycogenes that span 29 the Cancer Genome Atlas (TCGA) cancer types. Here, TF–glycogene interactions appeared in clusters or so-called communities, suggesting that changes in single TF expression during both health and disease may affect multiple carbohydrate structures. Upon applying the Fisher’s exact test along with glycogene pathway classification, we identified TFs that may specifically regulate the biosynthesis of individual glycan types. Integration with Reactome DB knowledge provided an avenue to relate cell-signaling pathways to TFs and cellular glycosylation state. Whereas analysis results are presented for all 29 cancer types, specific focus is placed on human luminal and basal breast cancer disease progression. Overall, the article presents a computational approach to describe TF–glycogene relationships, the starting point for experimental system-wide validation.

Genome-Wide Analysis of Cell-Free DNA Methylation Profiling for the Early Diagnosis of Pancreatic Cancer

As one of the most malicious cancers, pancreatic cancer is difficult to treat due to the lack of effective early diagnosis. Therefore, it is urgent to find reliable diagnostic and predictive markers for the early detection of pancreatic cancer. In recent years, the detection of circulating cell-free DNA (cfDNA) methylation in plasma has attracted global attention for non-invasive and early cancer diagnosis. Here, we carried out a genome-wide cfDNA methylation profiling study of pancreatic ductal adenocarcinoma (PDAC) patients by methylated DNA immunoprecipitation coupled with high-throughput sequencing (MeDIP-seq). Compared with healthy individuals, 775 differentially methylated regions (DMRs) located in promoter regions were identified in PDAC patients with 761 hypermethylated and 14 hypomethylated regions; meanwhile, 761 DMRs in CpG islands (CGIs) were identified in PDAC patients with 734 hypermethylated and 27 hypomethylated regions (p-value < 0.0001). Then, 143 hypermethylated DMRs were further selected which were located in promoter regions and completely overlapped with CGIs. After performing the least absolute shrinkage and selection operator (LASSO) method, a total of eight markers were found to fairly distinguish PDAC patients from healthy individuals, including TRIM73, FAM150A, EPB41L3, SIX3, MIR663, MAPT, LOC100128977, and LOC100130148. In conclusion, this work identified a set of eight differentially methylated markers that may be potentially applied in non-invasive diagnosis of pancreatic cancer.

Genome-wide methylation and expression profiling identify a novel epigenetic signature in gastrointestinal pan-adenocarcinomas

Aim: To identify methylation-driven genes and establish a novel epigenetic signature for gastrointestinal (GI) pan-adenocarcinomas. Materials & methods: Methylation and RNA-seq data for GI adenocarcinomas were downloaded from the Cancer Genome Atlas database. A methylation-driven gene signature was established by multivariate Cox regression analysis. We developed a prognostic nomogram using a combination of methylation-driven gene risk score and clinicopathological variables. A joint survival analysis based on gene expression and methylation was conducted to further investigate the prognostic role of methylation-driven genes. Results: An epigenetic signature was established based on five methylation-driven genes. We also established a prognostic nomogram based on methylation-driven gene risk score and clinicopathologic factors, with a favorable predictive ability. Joint survival analysis revealed that 28 methylation-driven genes could be independent prognostic factors for overall survival for GI adenocarcinomas. Conclusion: An epigenetic signature was established that effectively predicts the overall survival for GI adenocarcinomas across anatomic boundaries.

Differential regulation of CpG island methylation within divergent and unidirectional promoters in colorectal cancer

The silencing of tumor suppressor genes by promoter CpG island (CGI) methylation is an important cause of oncogenesis. Silencing of MLH1 and BRCA1, two examples of oncogenic events, results from promoter CGI methylation. Interestingly, both MLH1 and BRCA1 have a divergent promoter, from which another gene on the opposite strand is also transcribed. Although studies have shown that divergent transcription is an important factor in transcriptional regulation, little is known about its implication in aberrant promoter methylation in cancer. In this study, we analyzed the methylation status of CGI in divergent promoters using a recently enriched transcriptome database. We measured the extent of CGI methylation in 119 colorectal cancer (CRC) clinical samples (65 microsatellite instability high [MSI‐H] CRC with CGI methylator phenotype, 28 MSI‐H CRC without CGI methylator phenotype and 26 microsatellite stable CRC) and 21 normal colorectal tissues using Infinium MethylationEPIC BeadChip. We found that CGI within divergent promoters are less frequently methylated than CGI within unidirectional promoters in normal cells. In the genome of CRC cells, CGI within unidirectional promoters are more vulnerable to aberrant methylation than CGI within divergent promoters. In addition, we identified three DNA sequence motifs that correlate with methylated CGI. We also showed that methylated CGI are associated with genes whose expression is low in normal cells. Thus, we here provide fundamental observations regarding the methylation of divergent promoters that are essential for the understanding of carcinogenesis and development of cancer prevention strategies.