Pan-cancer analysis reveals presence of pronounced DNA methylation drift in CpG island methylator phenotype clusters

Deciphering the etiology and role in oncogenic transformation of the CpG island methylator phenotype: a pan-cancer analysis

Numerous cancer types have shown to present hypermethylation of CpG islands, also known as a CpG island methylator phenotype (CIMP), often associated with survival variation. Despite extensive research on CIMP, the etiology of this variability remains elusive, possibly due to lack of consistency in defining CIMP. In this work, we utilize a pan-cancer approach to further explore CIMP, focusing on 26 cancer types profiled in the Cancer Genome Atlas (TCGA). We defined CIMP systematically and agnostically, discarding any effects associated with age, gender or tumor purity. We then clustered samples based on their most variable DNA methylation values and analyzed resulting patient groups. Our results confirmed the existence of CIMP in 19 cancers, including gliomas and colorectal cancer. We further showed that CIMP was associated with survival differences in eight cancer types and, in five, represented a prognostic biomarker independent of clinical factors. By analyzing genetic and transcriptomic data, we further uncovered potential drivers of CIMP and classified them in four categories: mutations in genes directly involved in DNA demethylation; mutations in histone methyltransferases; mutations in genes not involved in methylation turnover, such as KRAS and BRAF; and microsatellite instability. Among the 19 CIMP-positive cancers, very few shared potential driver events, and those drivers were only IDH1 and SETD2 mutations. Finally, we found that CIMP was strongly correlated with tumor microenvironment characteristics, such as lymphocyte infiltration. Overall, our results indicate that CIMP does not exhibit a pan-cancer manifestation; rather, general dysregulation of CpG DNA methylation is caused by heterogeneous mechanisms.

CpG Island Methylator Phenotype-A Hope for the Future or a Road to Nowhere?

The CpG island methylator phenotype (CIMP) can be regarded as the most notable emanation of epigenetic instability in cancer. Since its discovery in the late 1990s, CIMP has been extensively studied, mainly in colorectal cancers (CRC) and gliomas. Consequently, knowledge on molecular and pathological characteristics of CIMP in CRC and other tumour types has rapidly expanded. Concordant and widespread hypermethylation of multiple CpG islands observed in CIMP in multiple cancers raised hopes for future epigenetically based diagnostics and treatments of solid tumours. However, studies on CIMP in solid tumours were hampered by a lack of generalisability and reproducibility of epigenetic markers. Moreover, CIMP was not a satisfactory marker in predicting clinical outcomes. The idea of targeting epigenetic abnormalities such as CIMP for cancer therapy has not been implemented for solid tumours, either. Twenty-one years after its discovery, we aim to cover both the fundamental and new aspects of CIMP and its future application as a diagnostic marker and target in anticancer therapies.

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas

Molecular mechanisms of lower-grade (II-III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.

Highly recurrent CBS epimutations in gastric cancer CpG island methylator phenotypes and inflammation

Background

CIMP (CpG island methylator phenotype) is an epigenetic molecular subtype, observed in multiple malignancies and associated with the epigenetic silencing of tumor suppressors. Currently, for most cancers including gastric cancer (GC), mechanisms underlying CIMP remain poorly understood. We sought to discover molecular contributors to CIMP in GC, by performing global DNA methylation, gene expression, and proteomics profiling across 14 gastric cell lines, followed by similar integrative analysis in 50 GC cell lines and 467 primary GCs.

Results

We identify the cystathionine beta-synthase enzyme (CBS) as a highly recurrent target of epigenetic silencing in CIMP GC. Likewise, we show that CBS epimutations are significantly associated with CIMP in various other cancers, occurring even in premalignant gastroesophageal conditions and longitudinally linked to clinical persistence. Of note, CRISPR deletion of CBS in normal gastric epithelial cells induces widespread DNA methylation changes that overlap with primary GC CIMP patterns. Reflecting its metabolic role as a gatekeeper interlinking the methionine and homocysteine cycles, CBS loss in vitro also causes reductions in the anti-inflammatory gasotransmitter hydrogen sulfide (H₂S), with concomitant increase in NF-κB activity. In a murine genetic model of CBS deficiency, preliminary data indicate upregulated immune-mediated transcriptional signatures in the stomach.

Conclusions

Our results implicate CBS as a bi-faceted modifier of aberrant DNA methylation and inflammation in GC and highlights H₂S donors as a potential new therapy for CBS-silenced lesions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02375-2.

MBD2 Correlates with a Poor Prognosis and Tumor Progression in Renal Cell Carcinoma

Purpose

DNA methylation plays an important role in regulating gene expression. Methyl-CpG-binding domain (MBD) proteins recognize and bind to methylated DNA, which mediate gene silencing by the interaction with deacetylases and histone methyltransferases. MBD2 has been reported in various human cancers; however, its clinical implication and potential regulatory role in renal cell carcinoma (RCC) have not been elaborated.

Materials and Methods

In the study, we estimated the expression and prognostic value of MBD2 in RCC cell lines and tissues by Western blotting and immunohistochemistry. The associations of MBD2 expression and pathological characters and survival in RCC patients were performed using χ2 and Kaplan-Meier survival analysis, respectively. Univariate and multivariable Cox regression analyses suggested the independent predictors in RCC prognosis. The functional role of MBD2 in RCC progression was assessed by in vitro cell experiments. In addition, we identified the MBD2-mediated alterations of protein-related proliferation and EMT markers in RCC cells after MBD2 overexpression and knockdown.

Results

We found that the protein levels of MBD2 were upregulated in RCC cells and tissues. High MBD2 expression was related to TNM stage and predicted poorer survival in RCC. Enforced expression of MBD2 significantly promoted the proliferation, cycle progress, invasion and migration of RCC cells in vitro. However, downregulating MBD2 remarkably weakened the above cell functions. Mechanistically, the promotive effect of MBD2 overexpression may be regulated by its effects onp21, p53 and Cyclin D1 expression and EMT process.

Conclusion

These results indicated that MBD2confers an oncogenic function in the malignant progression of RCC. MBD2 could be served as a meaningful prognostic biomarker and a latent therapeutic target in RCC patients.

Computational assessment of MCM2 transcriptional expression and identification of the prognostic biomarker for human breast cancer

Minichromosome maintenance protein 2 (MCM2) is a highly conserved protein from the MCM protein family that plays an important role in eukaryotic DNA replication as well as in cell cycle progression. In addition, it maintains the ploidy level consistency in eukaryotic cells, hence, mutations or alteration of this protein could result in the disintegration of the fine-tuned molecular machinery that can lead to uncontrolled cell proliferation. Moreover, MCM2 has been found to be an important marker for progression and prognosis in different cancers. Therefore, we aimed to analyze the MCM2 expression and the associated outcome in breast cancer (BC) patients based on the publicly available online databases. In this study, server-based gene expression analyses indicate the upregulation of MCM2 (p < 10^-6; fold change>2.0) in various BC subtypes as compared to the respective normal tissues. Besides, the evaluation of histological sections from healthy and cancer tissues showed strong staining signals indicating higher expression of MCM2 protein. The overexpression of MCM2 was significantly correlated to promoter methylation and was related to patients' clinical features. Further, mutation analysis suggested missense as the predominant type of mutation (71.4%) with 18 copy-number alterations and 0.2% mutation frequency in the MCM2 gene. This study revealed a significant correlation (Cox p ≤ 0.05) between the higher MCM2 expression and lower patient survival. Finally, we identified the co-expressed genes with gene ontological features and signaling pathways associated in BC development. We believe that this study will provide a basis for MCM2 to be a significant biomarker for human BC prognosis.

Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz

DNA methylation profiling offers unique insights into human development and diseases. Often the analysis of complex tissues and cell mixtures is the only feasible option to study methylation changes across large patient cohorts. Since DNA methylomes are highly cell type specific, deconvolution methods can be used to recover cell type-specific information in the form of latent methylation components (LMCs) from such 'bulk' samples. Reference-free deconvolution methods retrieve these components without the need for DNA methylation profiles of purified cell types. Currently no integrated and guided procedure is available for data preparation and subsequent interpretation of deconvolution results. Here, we describe a three-stage protocol for reference-free deconvolution of DNA methylation data comprising: (i) data preprocessing, confounder adjustment using independent component analysis (ICA) and feature selection using DecompPipeline, (ii) deconvolution with multiple parameters using MeDeCom, RefFreeCellMix or EDec and (iii) guided biological inference and validation of deconvolution results with the R/Shiny graphical user interface FactorViz. Our protocol simplifies the analysis and guides the initial interpretation of DNA methylation data derived from complex samples. The harmonized approach is particularly useful to dissect and evaluate cell heterogeneity in complex systems such as tumors. We apply the protocol to lung cancer methylomes from The Cancer Genome Atlas (TCGA) and show that our approach identifies the proportions of stromal cells and tumor-infiltrating immune cells, as well as associations of the detected components with clinical parameters. The protocol takes slightly >3 d to complete and requires basic R skills.

HDNA methylation data-based molecular subtype classification related to the prognosis of patients with hepatocellular carcinoma

Background

DNA methylation is a common chemical modification of DNA in the carcinogenesis of hepatocellular carcinoma (HCC).

Methods

In this bioinformatics analysis, 348 liver cancer samples were collected from the Cancer Genome Atlas (TCGA) database to analyse specific DNA methylation sites that affect the prognosis of HCC patients.

Results

10,699 CpG sites (CpGs) that were significantly related to the prognosis of patients were clustered into 7 subgroups, and the samples of each subgroup were significantly different in various clinical pathological data. In addition, by calculating the level of methylation sites in each subgroup, 119 methylation sites (corresponding to 105 genes) were selected as specific methylation sites within the subgroups. Moreover, genes in the corresponding promoter regions in which the above specific methylation sites were located were subjected to signalling pathway enrichment analysis, and it was discovered that these genes were enriched in the biological pathways that were reported to be closely correlated with HCC. Additionally, the transcription factor enrichment analysis revealed that these genes were mainly enriched in the transcription factor KROX. A naive Bayesian classification model was used to construct a prognostic model for HCC, and the training and test data sets were used for independent verification and testing.

Conclusion

This classification method can well reflect the heterogeneity of HCC samples and help to develop personalized treatment and accurately predict the prognosis of patients.

Pan-cancer analysis of clinical relevance of alternative splicing events in 31 human cancers

Alternative splicing represents a critical posttranscriptional regulation of gene expression, which contributes to the protein complexity and mRNA processing. Defects of alternative splicing including genetic alteration and/or altered expression of both pre-mRNA and trans-acting factors give rise to many cancers. By integrally analyzing clinical data and splicing data from TCGA and SpliceSeq databases, a number of splicing events were found clinically relevant in tumor samples. Alternative splicing of KLK2 (KLK2_51239) was found as a potential inducement of nonsense-mediated mRNA decay and associated with poor survival in prostate cancer. Consensus K-means clustering analysis indicated that alternative splicing events could be potentially used for molecular subtype classification of cancers. By random forest survival algorithm, prognostic prediction signatures with well performances were constructed for 31 cancers by using survival-associated alternative splicing events. Furthermore, an online tool for visualization of Kaplan-Meier plots of splicing events in 31 cancers was explored. Briefly, alternative splicing was found of significant clinical relevance with cancers.

Perinatal polychlorinated biphenyls and polychlorinated dibenzofurans exposure are associated with DNA methylation changes lasting to early adulthood: Findings from Yucheng second generation

Epigenome-wide DNA methylation has not been studied in men perinatally exposed to PCBs and dioxins. Therefore, we examined whether perinatal exposure to polychlorinated biphenyls (PCBs) and polychlorinated dibenzofurans (PCDFs) induces sustained methylation changes lasting to early adulthood. We used the Illumina HumanMethylation450 BeadChip to assess DNA methylation in whole blood among Yucheng second generation (people perinatal exposed to high PCBs and PCDFs) compared with referents. Thirty male offspring from the Yucheng cohort were randomly selected and matched with 30 male offspring from the Yucheng' neighborhood referents with similar backgrounds. Methylation differences between the Yucheng second generation and non-exposed referents were identified using a P value < 1.06 × 10^-7. Differential DNA methylation with epigenome-wide statistical significance was observed for 20 CpGs mapped to 11 genes, and 19 CpGs were correlated with gestational levels of PCBs or PCDF toxic equivalency (PCDF-TEQ) with the same direction of effect. Among the 11 genes, AHRR and CYP1A1 are involved in the aryl hydrocarbon receptor signaling pathway known to mediate dioxin toxicity. MYO1G, FRMD4A, ARL4C, OLFM1, and WWC3 were previously reported to be related to carcinogenesis. This is the first study examining genome-wide DNA methylation among people perinatally exposed to high concentrations of PCBs and PCDFs. We observed novel differential methylation of several genes, indicating that modifications of DNA methylation associated with perinatal PCB and PCDF exposure may persist in exposed offspring for more than 20 years. Furthermore, involvement of several carcinogesis-related genes suggested a potential in utero epigenetic mechanisms.

Multilevel omic data clustering reveals variable contribution of methylator phenotype to integrative cancer subtypes

AIM

We aimed to assess to what extent CpG island methylator phenotype (CIMP) contributes to cancer subtypes obtained by multilevel omic data analysis.

MATERIALS & METHODS

16 The Cancer Genome Atlas datasets encompassing three data layers in 4688 tumor samples were analyzed. We identified cancer integrative subtypes (ISs) by the use of similarity network fusion and consensus clustering. CIMP high (CIMP-H) associated ISs were profiled by gene sets and transcriptional regulators enrichment analysis.

RESULTS & CONCLUSION

In nine out of 16 cancer datasets CIMP-H clusters significantly overlaped with unique ISs. The contribution of CIMP-H on integrative molecular profiling is variable; therefore, only in a subset of cancer types does CIMP-H contribute to homogenous integrative subtype. CIMP-H associated ISs are heterogenous groups with regard to deregulated pathways and transcriptional regulators.