DNA methylome profiling beyond promoters - taking an epigenetic snapshot of the breast tumor microenvironment

LuxHMM: DNA methylation analysis with genome segmentation via hidden Markov model

BACKGROUND

DNA methylation plays an important role in studying the epigenetics of various biological processes including many diseases. Although differential methylation of individual cytosines can be informative, given that methylation of neighboring CpGs are typically correlated, analysis of differentially methylated regions is often of more interest.

RESULTS

We have developed a probabilistic method and software, LuxHMM, that uses hidden Markov model (HMM) to segment the genome into regions and a Bayesian regression model, which allows handling of multiple covariates, to infer differential methylation of regions. Moreover, our model includes experimental parameters that describe the underlying biochemistry in bisulfite sequencing and model inference is done using either variational inference for efficient genome-scale analysis or Hamiltonian Monte Carlo (HMC).

CONCLUSIONS

Analyses of real and simulated bisulfite sequencing data demonstrate the competitive performance of LuxHMM compared with other published differential methylation analysis methods.

Genome-wide DNA methylation profile analysis identifies an individualized predictive signature for melanoma immune response

PURPOSE

The current evaluation methods for tumor infiltrating lymphocytes (TILs), particularly CD8 + TILs, mainly rely on semiquantitative immunohistochemistry with high variability. We aimed to construct an individualized DNA methylation-based signature for CD8 + TILs (CD8 + MeTIL) that may characterize melanoma immune microenvironment and guide therapeutic selection.

METHODS

The transcriptome profiles and DNA methylation data of 457 melanoma patients from The Cancer Genome Atlas (TCGA) database were analyzed. Differential methylation analysis between groups with high and low CD8 + TILs was performed to select differentially methylated positions (DMPs) and define CD8 + MeTIL. The prognostic value of CD8 + MeTIL and its predictive value for immunotherapy response were investigated using multiple melanoma cohorts.

RESULTS

We successfully constructed the CD8 + MeTIL signature based on four DMPs. The survival analyses showed that higher CD8 + MeTIL score was associated with worse survival outcomes in TCGA-SKCM and GSE144487 cohorts. The ROC curve for the predictive analysis revealed that the survival prediction of CD8 + MeTIL score was superior compared with CD8 + TILs (CIBERSORT) and CD8B mRNA expression. Furthermore, we founded that tumors with higher CD8 + MeTIL score were marked with immunosuppressive characteristics, including low immune score and downregulated immune-related pathways. More importantly, the CD8 + MeTIL score showed a potential predictive value for the benefit from immunotherapy in two published cohorts. When combined CD8 + MeTIL with PD-L1 expression, the patient classification showed significantly different immunotherapy response rates and long-term survival outcomes.

CONCLUSIONS

The CD8 + MeTIL signature might be as a novel method to evaluate CD8 + TILs and guide immunotherapy approaches.

A Novel Gene Prognostic Signature Based on Differential DNA Methylation in Breast Cancer

Background: DNA methylation played essential roles in regulating gene expression. The impact of DNA methylation status on the occurrence and development of cancers has been well demonstrated. However, little is known about its prognostic role in breast cancer (BC).

Materials: The Illumina Human Methylation450 array (450k array) data of BC was downloaded from the UCSC xena database. Transcriptomic data of BC was downloaded from the Cancer Genome Atlas (TCGA) database. Firstly, we used univariate and multivariate Cox regression analysis to screen out independent prognostic CpGs, and then we identified methylation-associated prognosis subgroups by consensus clustering. Next, a methylation prognostic model was developed using multivariate Cox analysis and was validated with the Illumina Human Methylation27 array (27k array) dataset of BC. We then screened out differentially expressed genes (DEGs) between methylation high-risk and low-risk groups and constructed a methylation-based gene prognostic signature. Further, we validated the gene signature with three subgroups of the TCGA-BRCA dataset and an external dataset GSE146558 from the Gene Expression Omnibus (GEO) database.

Results: We established a methylation prognostic signature and a methylation-based gene prognostic signature, and there was a close positive correlation between them. The gene prognostic signature involved six genes: IRF2, KCNJ11, ZDHHC9, LRP11, PCMT1, and TMEM70. We verified their expression in mRNA and protein levels in BC. Both methylation and methylation-based gene prognostic signatures showed good prognostic stratification ability. The AUC values of 3-years, 5-years overall survival (OS) were 0.737, 0.744 in the methylation signature and 0.725, 0.715 in the gene signature, respectively. In the validation groups, high-risk patients were confirmed to have poorer OS. The AUC values of 3 years were 0.757, 0.735, 0.733 in the three subgroups of TCGA dataset and 0.635 in GSE146558 dataset.

Conclusion: This study revealed the DNA methylation landscape and established promising methylation and methylation-based gene prognostic signatures that could serve as potential prognostic biomarkers and therapeutic targets.

A High Epigenetic Risk Score Shapes the Non-Inflamed Tumor Microenvironment in Breast Cancer

Background: Epigenetic dysregulation via aberrant DNA methylation has gradually become recognized as an efficacious signature for predicting tumor prognosis and response to therapeutic targets. However, reliable DNA methylation biomarkers describing tumorigenesis remain to be comprehensively explored regarding their prognostic and therapeutic potential in breast cancer (BC).

Methods: Whole-genome methylation datasets integrated from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were profiled (n = 1,268). A three-stage selection procedure (discovery, training, and external validation) was utilized to screen out the prominent biomarkers and establish a robust risk score from more than 300,000 CpG sites after quality control, rigorous filtering, and reducing dimension. Moreover, gene set enrichment analyses guided us to systematically correlate this epigenetic risk score with immunological characteristics, including immunomodulators, anti-cancer immunity cycle, immune checkpoints, tumor-infiltrating immune cells and a series of signatures upon modulating components within BC tumor microenvironment (TME). Multi-omics data analyses were performed to decipher specific genomic alterations in low- and high-risk patients. Additionally, we also analyzed the role of risk score in predicting response to several treatment options.

Results: A 10-CpG-based prognostic signature which could significantly and independently categorize BC patients into distinct prognoses was established and sufficiently validated. And we hypothesize that this signature designs a non-inflamed TME in BC based on the evidence that the derived risk score is negatively correlated with tumor-associated infiltrating immune cells, anti-cancer immunity cycle, immune checkpoints, immune cytolytic activity, T cell inflamed score, immunophenoscore, and the vast majority of immunomodulators. The identified high-risk patients were characterized by upregulation of immune inhibited oncogenic pathways, higher TP53 mutation and copy number burden, but lower response to cancer immunotherapy and chemotherapy.

Conclusion: Our work highlights the complementary roles of 10-CpG-based signature in estimating overall survival in BC patients, shedding new light on investigating failed events concerning immunotherapy at present.

Methylation-eQTL Analysis in Cancer Research

MOTIVATION

DNA methylation is a key epigenetic factor regulating gene expression. While promoter methylation has been well studied, recent publications have revealed that functionally important methylation also occurs in intergenic and distal regions, and varies across genes and tissue types. Given the growing importance of inter-platform integrative genomic analyses, there is an urgent need to develop methods to discover and characterize gene-level relationships between methylation and expression.

RESULTS

We introduce a novel sequential penalized regression approach to identify methylation-expression quantitative trait loci (methyl-eQTLs), a term that we have coined to represent, for each gene and tissue type, a sparse set of CpG loci best explaining gene expression and accompanying weights indicating direction and strength of association. Using TCGA and MD Anderson colorectal cohorts to build and validate our models, we demonstrate our strategy better explains expression variability than current commonly used gene-level methylation summaries. The methyl-eQTLs identified by our approach can be used to construct gene-level methylation summaries that are maximally correlated with gene expression for use in integrative models, and produce a tissue-specific summary of which genes appear to be strongly regulated by methylation. Our results introduce an important resource to the biomedical community for integrative genomics analyses involving DNA methylation.

AVAILABILITY AND IMPLEMENTATION

We produce an R Shiny app (https://rstudio-prd-c1.pmacs.upenn.edu/methyl-eQTL/) that interactively presents methyl-eQTL results for colorectal, breast, and pancreatic cancer. The source R code for this work is provided in the supplement.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Burden of Post-Translational Modification (PTM)-Disrupting Mutations in the Tumor Matrisome

BACKGROUND

To evaluate the occurrence of mutations affecting post-translational modification (PTM) sites in matrisome genes across different tumor types, in light of their genomic and functional contexts and in comparison with the rest of the genome.

METHODS

This study spans 9075 tumor samples and 32 tumor types from The Cancer Genome Atlas (TCGA) Pan-Cancer cohort and identifies 151,088 non-silent mutations in the coding regions of the matrisome, of which 1811 affecting known sites of hydroxylation, phosphorylation, N- and O-glycosylation, acetylation, ubiquitylation, sumoylation and methylation PTM.

RESULTS

PTM-disruptive mutations (PTMmut) in the matrisome are less frequent than in the rest of the genome, seem independent of cell-of-origin patterns but show dependence on the nature of the matrisome protein affected and the background PTM types it generally harbors. Also, matrisome PTMmut are often found among structural and functional protein regions and in proteins involved in homo- and heterotypic interactions, suggesting potential disruption of matrisome functions.

CONCLUSIONS

Though quantitatively minoritarian in the spectrum of matrisome mutations, PTMmut show distinctive features and damaging potential which might concur to deregulated structural, functional, and signaling networks in the tumor microenvironment.

High-fat diet-induced and genetically inherited obesity differentially alters DNA methylation profile in the germline of adult male rats

BACKGROUND

Paternal obesity has been associated with reduced live birth rates. It could lead to inheritance of metabolic disturbances to the offspring through epigenetic mechanisms. However, obesity is a multifactorial disorder with genetic or environmental causes. Earlier we had demonstrated differential effects of high-fat diet-induced obesity (DIO) and genetically inherited obesity (GIO) on metabolic, hormonal profile, male fertility, and spermatogenesis using two rat models. The present study aimed to understand the effect of DIO and GIO on DNA methylation in male germline, and its subsequent effects on the resorbed (post-implantation embryo loss) and normal embryos. First, we assessed the DNA methylation enzymatic machinery in the testis by Real-Time PCR, followed global DNA methylation levels in spermatozoa and testicular cells by ELISA and flow cytometry, respectively. Further, we performed Methylation Sequencing in spermatozoa for both the groups. Sequencing data in spermatozoa from both the groups were validated using Pyrosequencing. Expression of the differentially methylated genes was assessed in the resorbed and normal embryos sired by the DIO group using Real-Time PCR for functional validation.

RESULTS

We noted a significant decrease in Dnmt transcript and global DNA methylation levels in the DIO group and an increase in the GIO group. Sequencing analysis showed 16,966 and 9113 differentially methylated regions in the spermatozoa of the DIO and GIO groups, respectively. Upon pathway analysis, we observed genes enriched in pathways involved in embryo growth and development namely Wnt, Hedgehog, TGF-beta, and Notch in spermatozoa for both the groups, the methylation status of which partially correlated with the gene expression pattern in resorbed and normal embryos sired by the DIO group.

CONCLUSION

Our study reports the mechanism by which diet-induced and genetically inherited obesity causes differential effects on the DNA methylation in the male germline that could be due to a difference in the white adipose tissue accumulation. These differences could either lead to embryo loss or transmit obesity-related traits to the offspring in adult life.

HOPX Is an Epigenetically Inactivated Tumor Suppressor and Overexpression of HOPX Induce Apoptosis and Cell Cycle Arrest in Breast Cancer

Background

Evidence has been shown that abnormal DNA methylation plays a vital role in the progression of breast cancer via silencing of gene expression. The results of bisulfite sequencing showed that the methylation status of HOPX in breast cancer tissues was higher than that in normal breast cancer tissues, but little known about the biological functions of HOPX in breast cancer.

Methods

A total of 13 paired breast cancer and adjacent noncancerous tissues were subjected to bisulfite sequencing. Meanwhile, the methylation levels of cg218995965 and cg24862548 in breast cancer cells were detected by methylation-specific PCR (MSP). Flow cytometry, wound healing and transwell invasion assays were used to detect the apoptosis, migration and invasion in breast cancer cells. In addition, the expressions of HOPX, p21, cyclin D1 and CDK4 in cells were detected with Western blot assay.

Results

Bisulfite sequencing indicated that the CpG sites (cg218995965 and cg24862548) in the HOPX promoter region showed significantly higher methylation in breast cancer tissues. In addition, methylation-specific PCR revealed that HOPX was significantly hypermethylated in breast cancer cell lines MDA-MB-468 and MCF-7. Furthermore, overexpression of HOPX significantly inhibited the proliferation of MDA-MB-468 and MCF-7 cells via inducing the apoptosis. Moreover, upregulation of HOPX markedly inhibited the migration and invasion abilities of MDA-MB-468 cells. Meanwhile, overexpression of HOPX obviously induced cell cycle arrest in MDA-MB-468 cells via upregulation of p21, and downregulation of cyclin D1 and CDK4. Additionally, overexpression of HOPX suppressed tumor growth of breast cancer in vivo.

Conclusion

Our data showed that HOPX, a tumor suppressor, is epigenetically silenced in breast cancer. Overexpression of HOPX could suppress the progression of breast cancer, and thus indicating that it might serve as a potential target for the treatment of patients with breast cancer.

Prognostic DNA methylation markers for hormone receptor breast cancer: a systematic review

BACKGROUND

In patients with hormone receptor-positive breast cancer, differentiating between patients with a low and a high risk of recurrence is an ongoing challenge. In current practice, prognostic clinical parameters are used for risk prediction. DNA methylation markers have been proven to be of additional prognostic value in several cancer types. Numerous prognostic DNA methylation markers for breast cancer have been published in the literature. However, to date, none of these markers are used in clinical practice.

METHODS

We conducted a systematic review of PubMed and EMBASE to assess the number and level of evidence of published DNA methylation markers for hormone receptor-positive breast cancer. To obtain an overview of the reporting quality of the included studies, all were scored according to the REMARK criteria that were established as reporting guidelines for prognostic biomarker studies.

RESULTS

A total of 74 studies were identified reporting on 87 different DNA methylation markers. Assessment of the REMARK criteria showed variation in reporting quality of the studies. Eighteen single markers and one marker panel were studied in multiple independent populations. Hypermethylation of the markers RASSF1, BRCA, PITX2, CDH1, RARB, PCDH10 and PGR, and the marker panel GSTP1, RASSF1 and RARB showed a statistically significant correlation with poor disease outcome that was confirmed in at least one other, independent study.

CONCLUSION

This systematic review provides an overview on published prognostic DNA methylation markers for hormone receptor-positive breast cancer and identifies eight markers that have been independently validated. Analysis of the reporting quality of included studies suggests that future research on this topic would benefit from standardised reporting guidelines.

Incorporating DNA Methyltransferase Inhibitors (DNMTis) in the Treatment of Genitourinary Malignancies: A Systematic Review

Inhibition of DNA methyltransferases (DNMTs) has emerged as a novel treatment strategy in solid tumors. Aberrant hypermethylation in promoters of critical tumor suppressor genes is the basis for the idea that treatment with hypomethylating agents may lead to the restoration of a "normal" epigenome and produce clinically meaningful therapeutic outcomes. The aim of this review article is to summarize the current state of knowledge of DNMT inhibitors in the treatment of genitourinary malignancies. The efficacy of these agents in genitourinary malignancies was reported in a number of studies and suggests a role of induced DNA hypomethylation in overcoming resistance to conventional cytotoxic treatments. The clinical significance of these findings should be further investigated.

TdIF1: a putative oncogene in NSCLC tumor progression

TdT-interacting factor 1 (TdIF1) is a ubiquitously expressed DNA- and protein-binding protein that directly binds to terminal deoxynucleotidyl transferase (TdT) polymerase. Little is known about the functional role of TdIF1 in cancer cellular signaling, nor has it previously been identified as aberrant in any type of cancer. We report here for the first time that TdIF1 is abundantly expressed in clinical lung cancer patients and that high expression of TdIF1 is associated with poor patient prognosis. We further established that TdIF1 is highly expressed in human non-small cell lung cancer (NSCLC) cell lines compared to a normal lung cell line. shRNA-mediated gene silencing of TdIF1 resulted in the suppression of proliferation and anchorage-independent colony formation of the A549 adenocarcinoma cell line. Moreover, when these TdIF1-silenced cells were used to establish a mouse xenograft model of human NSCLC, tumor size was greatly reduced. These data suggest that TdIF1 is a potent regulator of lung tumor development. Several cell cycle-related and tumor growth signaling pathways, including the p53 and HDAC1/2 pathways, were identified as participating in the TdIF1 signaling network by in silico analysis. Microarray, transcriptome and protein-level analyses validated p53 and HDAC1/2 modulation upon TdIF1 downregulation in an NSCLC cellular model. Moreover, several other cell cycle regulators were affected at the transcript level by TdIF1 silencing, including an increase in CDKN1A/p21 transcripts. Taken together, these results indicate that TdIF1 is a bona fide tumor-promoting factor in NSCLC and a potential target for therapy.

A protein involved in the immune system also plays a role in the most common type of lung cancer. Weiping Min, of the University of Western Ontario in Canada, and international colleagues found, for the first time, that the protein TdIF1 is significantly upregulated in non-small cell lung cancer (NSCLC) tissues in patients. High expression levels of this protein were correlated with poor prognosis. NSCLC tumor tissues grown in mice where TdIF1 expression was ‘knocked down’ were significantly smaller than in those without TdIF1 knockdown. Further analyses showed the protein was involved in known cell signaling pathways with roles in NSCLC progression. The findings indicate TdIF1 should be further investigated as a biomarker of NSCLC or as a molecular target for its treatment.

Specific breast cancer prognosis-subtype distinctions based on DNA methylation patterns

Tumour heterogeneity is an obstacle to effective breast cancer diagnosis and therapy. DNA methylation is an important regulator of gene expression, thus characterizing tumour heterogeneity by epigenetic features can be clinically informative. In this study, we explored specific prognosis-subtypes based on DNA methylation status using 669 breast cancers from the TCGA database. Nine subgroups were distinguished by consensus clustering using 3869 CpGs that significantly influenced survival. The specific DNA methylation patterns were reflected by different races, ages, tumour stages, receptor status, histological types, metastasis status and prognosis. Compared with the PAM50 subtypes, which use gene expression clustering, DNA methylation subtypes were more elaborate and classified the Basal-like subtype into two different prognosis-subgroups. Additionally, 1252 CpGs (corresponding to 888 genes) were identified as specific hyper/hypomethylation sites for each specific subgroup. Finally, a prognosis model based on Bayesian network classification was constructed and used to classify the test set into DNA methylation subgroups, which corresponded to the classification results of the train set. These specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes.

The signature of liver cancer in immune cells DNA methylation

Background

The idea that changes to the host immune system are critical for cancer progression was proposed a century ago and recently regained experimental support.

Results

Herein, the hypothesis that hepatocellular carcinoma (HCC) leaves a molecular signature in the host peripheral immune system was tested by profiling DNA methylation in peripheral blood mononuclear cells (PBMC) and T cells from a discovery cohort (n = 69) of healthy controls, chronic hepatitis, and HCC using Illumina 450K platform and was validated in two validation sets (n = 80 and n = 48) using pyrosequencing.

Conclusions

The study reveals a broad signature of hepatocellular carcinoma in PBMC and T cells DNA methylation which discriminates early HCC stage from chronic hepatitis B and C and healthy controls, intensifies with progression of HCC, and is highly enriched in immune function-related genes such as PD-1, a current cancer immunotherapy target. These data also support the feasibility of using these profiles for early detection of HCC.

DNA methylation-based immune response signature improves patient diagnosis in multiple cancers

BACKGROUND

The tumor immune response is increasingly associated with better clinical outcomes in breast and other cancers. However, the evaluation of tumor-infiltrating lymphocytes (TILs) relies on histopathological measurements with limited accuracy and reproducibility. Here, we profiled DNA methylation markers to identify a methylation of TIL (MeTIL) signature that recapitulates TIL evaluations and their prognostic value for long-term outcomes in breast cancer (BC).

METHODS

MeTIL signature scores were correlated with clinical endpoints reflecting overall or disease-free survival and a pathologic complete response to preoperative anthracycline therapy in 3 BC cohorts from the Jules Bordet Institute in Brussels and in other cancer types from The Cancer Genome Atlas.

RESULTS

The MeTIL signature measured TIL distributions in a sensitive manner and predicted survival and response to chemotherapy in BC better than did histopathological assessment of TILs or gene expression-based immune markers, respectively. The MeTIL signature also improved the prediction of survival in other malignancies, including melanoma and lung cancer. Furthermore, the MeTIL signature predicted differences in survival for malignancies in which TILs were not known to have a prognostic value. Finally, we showed that MeTIL markers can be determined by bisulfite pyrosequencing of small amounts of DNA from formalin-fixed, paraffin-embedded tumor tissue, supporting clinical applications for this methodology.

CONCLUSIONS

This study highlights the power of DNA methylation to evaluate tumor immune responses and the potential of this approach to improve the diagnosis and treatment of breast and other cancers.

FUNDING

This work was funded by the Fonds National de la Recherche Scientifique (FNRS) and Télévie, the INNOVIRIS Brussels Region BRUBREAST Project, the IUAP P7/03 program, the Belgian "Foundation against Cancer," the Breast Cancer Research Foundation (BCRF), and the Fonds Gaston Ithier.

Molecular machineries of pH dysregulation in tumor microenvironment: potential targets for cancer therapy

Introduction: Cancer is an intricate disorder/dysfunction of cells that can be defined as a genetic heterogeneity in human disease. Therefore, it is characterized by several adaptive complex hallmarks. Among them, the pH dysregulation appears as a symbol of aberrant functions within the tumor microenvironment (TME). In comparison with normal tissues, in the solid tumors, we face with an irregular acidification and alkalinization of the extracellular and intracellular fluids. Methods: In this study, we comprehensively discussed the most recent reports on the hallmarks of solid tumors to provide deep insights upon the molecular machineries involved in the pH dysregulation of solid tumors and their impacts on the initiation and progression of cancer. Results: The dysregulation of pH in solid tumors is fundamentally related to the Warburg effect and hypoxia, leading to expression of a number of molecular machineries, including: NHE1, H+ pump V-ATPase, CA-9, CA-12, MCT-1, GLUT-1. Activation of proton exchangers and transporters (PETs) gives rise to formation of TME. This condition favors the cancer cells to evade from the anoikis and apoptosis, granting them aggressive and metastasis phenotype, as well as resistance to chemotherapy and radiation therapy. This review aimed to discuss the key molecular changes of tumor cells in terms of bio-energetics and cancer metabolism in relation with pH dysregulation. During this phenomenon, the intra- and extracellular metabolites are altered and/or disrupted. Such molecular alterations provide molecular hallmarks for direct targeting of the PETs by potent relevant inhibitors in combination with conventional cancer therapies as ultimate therapy against solid tumors. Conclusion: Taken all, along with other treatment strategies, targeting the key molecular machineries related to intra- and extracellular metabolisms within the TME is proposed as a novel strategy to inhibit or block PETs that are involved in the pH dysregulation of solid tumors.

Epigenetic control of the tumor microenvironment

Stromal cells of the tumor microenvironment have been shown to play important roles in both supporting and limiting cancer growth. The altered phenotype of tumor-associated stromal cells (fibroblasts, immune cells, endothelial cells etc.) is proposed to be mainly due to epigenetic dysregulation of gene expression; however, only limited studies have probed the roles of epigenetic mechanisms in the regulation of stromal cell function. We review recent studies demonstrating how specific epigenetic mechanisms (DNA methylation and histone post-translational modification-based gene expression regulation, and miRNA-mediated translational regulation) drive aspects of stromal cell phenotype, and discuss the implications of these findings for treatment of malignancies. We also summarize the effects of epigenetic mechanism-targeted drugs on stromal cells and discuss the consideration of the microenvironment response in attempts to use these drugs for cancer treatment.

Cells Comprising the Prostate Cancer Microenvironment Lack Recurrent Clonal Somatic Genomic Aberrations

Prostate cancer-associated stroma (CAS) plays an active role in malignant transformation, tumor progression, and metastasis. Molecular analyses of CAS have demonstrated significant changes in gene expression; however, conflicting evidence exists on whether genomic alterations in benign cells comprising the tumor microenvironment (TME) underlie gene expression changes and oncogenic phenotypes. This study evaluates the nuclear and mitochondrial DNA integrity of prostate carcinoma cells, CAS, matched benign epithelium and benign epithelium-associated stroma by whole-genome copy-number analyses, targeted sequencing of TP53, and FISH. Array comparative genomic hybridization (aCGH) of CAS revealed a copy-neutral diploid genome with only rare and small somatic copy-number aberrations (SCNA). In contrast, several expected recurrent SCNAs were evident in the adjacent prostate carcinoma cells, including gains at 3q, 7p, and 8q, and losses at 8p and 10q. No somatic TP53 mutations were observed in CAS. Mitochondrial DNA (mtDNA) extracted from carcinoma cells and stroma identified 23 somatic mtDNA mutations in neoplastic epithelial cells, but only one mutation in stroma. Finally, genomic analyses identified no SCNAs, LOH, or copy-neutral LOH in cultured cancer-associated fibroblasts, which are known to promote prostate cancer progression in vivo

IMPLICATIONS

The gene expression changes observed in prostate cancer-adjacent stroma and the attendant contribution of the stroma to the development and progression of prostate cancer are not due to frequent or recurrent genomic alterations in the TME.

Epigenome-based personalized medicine in human cancer

Cancer genome sequencing has created an opportunity for precision medicine. Thus far, genetic alterations can only be used to guide treatment for small subsets of certain cancer types with these key alterations. Similar to mutations, epigenetic events are equally suitable for personalized medicine. DNA methylation alterations have been used to identify tumor-specific drug responsive markers. Methylation of MGMT sensitizes gliomas to alkylating agents is an example of epigenetic personalized medicine. Recent studies have revealed that 5-azacytidine and decitabine show activity in myelodysplasia, lung and other cancers. There are currently at least 20 kinds of histone deacetylase inhibitors in clinical testing. Inhibitors targeting other epigenetic regulators are being clinically tested, such as EZH2 inhibitor EPZ-6438.

Aberrant DNA methylation impacts gene expression and prognosis in breast cancer subtypes

DNA methylation has a substantial impact on gene expression, affecting the prognosis of breast cancer (BC) patients dependent on molecular subtypes. In this study, we investigated the prognostic relevance of the expression of genes reported as aberrantly methylated, and the link between gene expression and DNA methylation in BC subtypes. The prognostic value of the expression of 144 aberrantly methylated genes was evaluated in ER+/HER2-, HER2+, and ER-/HER2- molecular BC subtypes, in a meta-analysis of two large transcriptomic cohorts of BC patients (n = 1,938 and n = 1,640). The correlation between gene expression and DNA methylation in distinct gene regions was also investigated in an independent dataset of 104 BCs. Survival and Pearson correlation analyses were computed for each gene separately. The expression of 48 genes was significantly associated with BC prognosis (p < 0.05), and 32 of these prognostic genes exhibited a direct expression-methylation correlation. The expression of several immune-related genes, including CD3D and HLA-A, was associated with both relapse-free survival (HR = 0.42, p = 3.5E-06; HR = 0.35, p = 1.7E-08) and overall survival (HR = 0.50, p = 5.5E-04; HR = 0.68, p = 4.5E-02) in ER-/HER2- BCs. On the overall, the distribution of both positive and negative expression-methylation correlation in distinct gene regions have different effects on gene expression and prognosis in BC subtypes. This large-scale meta-analysis allowed the identification of several genes consistently associated with prognosis, whose DNA methylation could represent a promising biomarker for prognostication and clinical stratification of patients with distinct BC subtypes.

Special issue: epigenetics: introduction

Epigenetic studies focus on changes in genetic information that rely on histone modification, which complements information encoded by the DNA sequence. Research in this rapidly expanding field has greatly contributed to a better understanding of processes such as gene regulation, chromatin structure, and cell differentiation and disease. The most recent advances in this area are reviewed in the collection of papers included in this Special Issue.