Blood DNA methylation profiles improve breast cancer prediction.
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ABSTRACT:
SUBMITTER: Kresovich JK
PROVIDER: S-EPMC8732352 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:As one of the most described epigenetic marks in human cancers, DNA methylation plays essential roles in gene expression regulation and has been implicated in the prognosis and therapeutics of many cancers. We are motivated in this study to explore DNA methylation profiles capturing breast cancer heterogeneity to improve breast cancer prognosis at the epigenetic level. RESULTS:Through comparisons on differentially methylated CpG sites among breast cancer subtypes followed by a sequential validation and functional studies using computational approaches, we propose 313 CpG, corresponding to 191 genes, whose methylation pattern identifies the triple negative breast cancer subtype, and report cell migration as represented by extracellular matrix organization and cell proliferation as mediated via MAPK and Wnt signalings are the primary factors driving breast cancer subtyping. CONCLUSIONS:Our study offers novel CpGs and gene methylation patterns with translational potential on triple negative breast cancer prognosis, as well as fresh insights from the epigenetic level on breast cancer heterogeneity.
| S-EPMC6839140 | biostudies-literature
Project description:Epigenetic alterations in tissues targeted for cancer play a causal role in carcinogenesis. Changes in DNA methylation in nontarget tissues, specifically peripheral blood, can also affect risk of malignant disease. We sought to identify specific profiles of DNA methylation in peripheral blood that are associated with bladder cancer risk and therefore serve as an epigenetic marker of disease susceptibility.We performed genome-wide DNA methylation profiling on participants involved in a population-based incident case-control study of bladder cancer.In a training set of 112 cases and 118 controls, we identified a panel of 9 CpG loci whose profile of DNA methylation was significantly associated with bladder cancer in a masked, independent testing series of 111 cases and 119 controls (P < .0001). Membership in three of the most methylated classes was associated with a 5.2-fold increased risk of bladder cancer (95% CI, 2.8 to 9.7), and a model that included the methylation classification, participant age, sex, smoking status, and family history of bladder cancer was a significant predictor of bladder cancer (area under the curve, 0.76; 95% CI, 0.70 to 0.82). CpG loci associated with bladder cancer and aging had neighboring sequences enriched for transcription-factor binding sites related to immune modulation and forkhead family members.These results indicate that profiles of epigenetic states in blood are associated with risk of bladder cancer and signal the potential utility of epigenetic profiles in peripheral blood as novel markers of susceptibility to this and other malignancies.
| S-EPMC3083868 | biostudies-other
Project description:Despite the advantages of neoadjuvant chemotherapy (NACT), associated toxicity is a serious complication that renders monitoring of the patients' response to NACT highly important. Thus, prediction of tumor response to treatment is imperative to avoid exposure of potential non-responders to deleterious complications. We have performed genome-wide analysis of DNA methylation by XmaI-RRBS and selected CpG dinucleotides differential methylation of which discriminates luminal B breast cancer samples with different sensitivity to NACT. With this data, we have developed multiplex methylation sensitive restriction enzyme PCR (MSRE-PCR) protocol for determining the methylation status of 10 genes (SLC9A3, C1QL2, DPYS, IRF4, ADCY8, KCNQ2, TERT, SYNDIG1, SKOR2 and GRIK1) that distinguish BC samples with different NACT response. Analysis of these 10 markers by MSRE-PCR in biopsy samples allowed us to reveal three top informative combinations of markers, (1) IRF4 and C1QL2; (2) IRF4, C1QL2, and ADCY8; (3) IRF4, C1QL2, and DPYS, with the areas under ROC curves (AUCs) of 0.75, 0.78 and 0.74, respectively. A classifier based on IRF4 and C1QL2 better meets the diagnostic panel simplicity requirements, as it consists of only two markers. Diagnostic accuracy of the panel of these two markers is 0.75, with the sensitivity of 75% and specificity of 75%.
| S-EPMC7280523 | biostudies-literature
Project description:BackgroundThe current Union International Committee on Cancer or the American Joint Committee on Cancer TNM stage system has shown valuable but insufficient estimation for subsets of gastric cancer and prediction for prognosis patients. Thus, there is an urgent need to identify diagnostic, prognostic, and predictive biomarkers to improve patients' outcomes. Our aim was to perform an integrative analysis on publicly available datasets to identify epigenetic changes that may play key role in the initiation and progression of gastric cancer, based on which we set to develop a DNA methylation signature to improve survival prediction of gastric cancer.ResultsA total of 340 methylation-related differentially expression genes (mrDEGs) were screened in gastric cancer patients from The Cancer Genome Atlas (TCGA) project. Pathway enrichment analysis revealed that they were involved in the biological process related to initiation and progression of gastric cancer. Based on the mrDEGs identified, we developed a DNA methylation signature consisting of ten gene members (SCNN1B, NFE2L3, CLDN2, RBPMS2, JPH2, GBP6, COL4A5, SMKR1, PPP1R14A, and ARL4D) according to their methylation β value. This innovative DNA methylation signature was associated with cancer recurrence, while it showed independence of cancer recurrence and TNM stage for survival prediction. Combination of this DNA methylation signature and TNM stage improved overall survival prediction in the receiver operating characteristic analysis. We also verified that two individual genes (PPP1R14A and SCNN1B) of the identified prognostic signature were regulated by promoter region methylation in a panel of gastric cell lines.ConclusionsThis study presents a powerful DNA methylation signature by performing analyses integrating multi-source data including transcriptome, methylome, and clinical outcome of gastric cancer patients from TCGA. The identified DNA methylation signature may be used to refine the current prognostic model and facilitate further stratification of patients in the future clinical trials. Further experimental studies are warranted to unveil the regulatory mechanism and functional role of all the individual genes of the DNA methylation signature. Also, clinical investigations in large GC patient cohorts are greatly needed to validate our findings.
| S-EPMC6972030 | biostudies-literature
Project description:Despite the advantages of neoadjuvant chemotherapy (NACT), associated toxicity is a serious complication that renders monitoring of the patients response to NACT highly important. Thus, prediction of tumor response to treatment is imperative to avoid exposure of potential non-responders to deleterious complications. We have performed genome-wide analysis of DNA methylation by XmaI-RRBS and selected CpG dinucleotides differential methylation of which discriminates luminal B breast cancer samples with different sensitivity to NACT. With this data, we have developed multiplex methylation sensitive restriction enzyme PCR (MSRE-PCR) protocol for determining the methylation status of 10 genes (SLC9A3, C1QL2, DPYS, IRF4, ADCY8, KCNQ2, TERT, SYNDIG1, SKOR2 and GRIK1) that distinguish BC samples with different NACT response. Analysis of these 10 markers by MSRE-PCR in biopsy samples allowed us to reveal three top informative combinations of markers, (1) IRF4 and C1QL2; (2) IRF4, C1QL2, and ADCY8; (3) IRF4, C1QL2, and DPYS, with the areas under ROC curves (AUCs) of 0.75, 0.78 and 0.74, respectively. A classifier based on IRF4 and C1QL2 better meets the diagnostic panel simplicity requirements, as it consists of only two markers. Diagnostic accuracy of the panel of these two markers is 0.75, with the sensitivity of 75% and specificity of 75%.
2020-01-25 | GSE144221 | GEO
Project description:DNA methylation is recognized as one of several epigenetic regulators of gene expression and as potential driver of carcinogenesis through gene-silencing of tumor suppressors and activation of oncogenes. However, abnormal methylation, even of promoter regions, does not necessarily alter gene expression levels, especially if the gene is already silenced, leaving the exact mechanisms of methylation unanswered. Using a large cohort of matching DNA methylation and gene expression samples of colorectal cancer (CRC; n = 77) and normal adjacent mucosa tissues (n = 108), we investigated the regulatory role of methylation on gene expression. We show that on a subset of genes enriched in common cancer pathways, methylation is significantly associated with gene regulation through gene-specific mechanisms. We built two classification models to infer gene regulation in CRC from methylation differences of tumor and normal tissues, taking into account both gene-silencing and gene-activation effects through hyper- and hypo-methylation of CpGs. The classification models result in high prediction performances in both training and independent CRC testing cohorts (0.92<AUC<0.97) as well as in individual patient data (average AUC = 0.82), suggesting a robust interplay between methylation and gene regulation. Validation analysis in other cancerous tissues resulted in lower prediction performances (0.69<AUC<0.90); however, it identified genes that share robust dependencies across cancerous tissues. In conclusion, we present a robust classification approach that predicts the gene-specific regulation through DNA methylation in CRC tissues with possible transition to different cancer entities. Furthermore, we present HMGA1 as consistently associated with methylation across cancers, suggesting a potential candidate for DNA methylation targeting cancer therapy.
| S-EPMC6140810 | biostudies-literature
Project description:BackgroundDNA-methylation-based machine learning algorithms have demonstrated powerful diagnostic capabilities, and these tools are currently emerging in many fields of tumor diagnosis and patient prognosis prediction. This work aimed to identify novel DNA methylation diagnostic biomarkers for differentiating cervical cancer (CC) from normal tissues, as well as a prognostic prediction model to predict survival of CC patients.MethodsThe methylation profiles with the available clinical characteristics were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) program. We first screened out the differential methylation sites in CC and normal tissues and performed multiple statistical analyses to discover DNA methylation diagnostic markers that are used to distinguish CC and normal control. Then, we developed a methylation-based survival model to improve risk stratification.ResultsA diagnostic prediction panel consists of five CpG markers that could predict cervical cancer versus normal tissue with highly correct rate of 100%, and cg16428251, cg22341310, and cg23316360 which in diagnostic prediction panel all could yield high sensitivity and specificity for detection of CC and normal in six cohorts (area under curve [AUC] > 0.8), in addition to excellent performance in discriminating between CC and normal sample. The diagnostic marker panel also effectively predicted the CIN3 versus normal tissue with high accuracy in two datasets (AUC = 0.80, 0.789, respectively). Furthermore, a prognostic prediction model aggregated two CpG markers that effectively stratified the prognosis of high-risk and low-risk groups (training cohort: hazard ratio [HR] 4, 95% CI: 1.7-9.6, P = 0.0021; testing cohort: hazard ratio [HR] 1.9, 95% CI: 1.2-3.1, P = 0.0072).ConclusionThe findings of our study showed that DNA methylation markers are of great value in the diagnosis and prognosis of CC.
| S-EPMC9249661 | biostudies-literature
Project description:Multiple studies have investigated global DNA methylation profiles and gene-specific DNA methylation in blood-based DNA to develop powerful screening markers for cancer. This systematic review summarizes the current evidence on methylation studies that investigated methylation level of blood-derived DNA of breast cancer (BC) patients in comparison to healthy controls by conducting a systematic literature review in PubMed and Web of Science. Essential results, such as methylation levels of BC cases and healthy controls, p values, and odds ratios, were extracted from these studies by two investigators independently. Overall, 45 publications met the inclusion criteria for this review. DNA from whole blood, as well as cell-free DNA (cfDNA) from serum or plasma, was used in these studies. The most common method used for measuring global DNA methylation was the investigation of repetitive elements as surrogates and the application of array-based genome-wide methylation analysis. For measuring gene-specific methylation level, methylation-specific PCR and pyrosequencing were the most frequently used methods. Epigenome-wide blood DNA hypomethylation in BC patients were reported in several studies; however, the evidence is still not conclusive. The most frequently investigated gene in whole blood was BRCA1, which was found more frequently methylated in patients compared to controls. RASSF1A was the most widely investigated gene in cfDNA of serum or plasma, which was also found more frequently methylated in patients compared to controls. Several of the eligible studies reported the associations of global hypomethylation and increased BC risk. Studies investigated associations between gene-specific methylation and BC risk, while got heterogeneous results. But two studies reported that hypermethylation of ATM gene was associated with increased BC risk, which suggest the potential use of this gene for BC risk stratification. Overall, our review suggests the possibility of using blood-based DNA methylation marker as promising marker for BC risk stratification, as several studies found associations between certain methylation level in blood and BC risk. However, so far, the evidence is still quite limited. Optimal markers are yet to be developed and promising results needed to be validated in prospective study cohorts and tested in large screening populations.
| S-EPMC5109688 | biostudies-literature
Project description:Alcohol intake is thought to be a risk factor for breast cancer, but the causal relationship and carcinogenic mechanisms are not clear. We performed an up-to-date meta-analysis of prospective studies to assess observational association, and then conducted MR analysis to make causal inference based on the genetic predisposition to alcohol consumption ("drinks per week") and pathological drinking behaviours ("alcohol use disorder" and "problematic alcohol use"), as well as genetically predicted DNA methylation at by alcohol-related CpG sites in blood. We found an observational dose-response association between alcohol intake and breast cancer incidence with an additional risk of 4% for per 10 g/day increase in alcohol consumption. Genetic predisposition to alcohol consumption ("drinks per week") was not causally associated with breast cancer incidence at the OR of 1.01 (95% CI 0.84, 1.23), but problematic alcohol use (PAU) was linked to a higher breast cancer risk at the OR of 1.76 (95% CI 1.04, 2.99) when conditioning on alcohol consumption. Epigenetic MR analysis identified four CpG sites, cg03260624 near CDC7 gene, cg10816169 near ZNF318 gene, cg03345232 near RIN3 gene, and cg26312998 near RP11-867G23.13 gene, where genetically predicted epigenetic modifications were associated with an increased breast cancer incidence risk. Our findings re-affirmed that alcohol consumption is of high risk for breast cancer incidence even at a very low dose, and the pathogenic effect of alcohol on breast cancer could be due to pathological drinking behaviour and epigenetic modification at several CpG sites, which could be potential intervention targets for breast cancer prevention.
| S-EPMC9329409 | biostudies-literature
Project description:Epigenetic mechanisms, especially DNA methylation, are suggested to play a role in the age-of-onset in Huntington's disease (HD) based on studies on patient brains, and cellular and animal models. Methylation is tissue-specific and it is not clear how HD specific methylation in the brain correlates with the blood compartment, which represents a much more clinically accessible sample. Therefore, we explored the presence of HD specific DNA methylation patterns in whole blood on a cohort of HDM and healthy controls from Slovenia. We compared CpG site-specific DNA methylation in whole blood of 11 symptomatic and 9 pre-symptomatic HDM (HDM), and 15 healthy controls, by using bisulfite converted DNA on the Infinium® Human Methylation27 BeadChip microarray (Illumina) covering 27,578 CpG sites and 14,495 genes. Of the examined 14,495 genes, 437 were differentially methylated (p < 0.01) in pre-symptomatic HDM compared to controls, with three genes (CLDN16, DDC, NXT2) retaining statistical significance after the correction for multiple testing (false discovery rate, FDR < 0.05). Comparisons between symptomatic HDM and controls, and the comparison of symptomatic and pre-symptomatic HDM further identified 260 and 198 differentially methylated genes (p < 0.01), respectively, whereas the comparison of all HDM (symptomatic and pre-symptomatic) and healthy controls identified 326 differentially methylated genes (p < 0.01), however, none of these changes retained significance (FDR < 0.05) after the correction for multiple testing. The results of our study suggest that methylation signatures in the blood compartment are not robust enough to prove as valuable biomarkers for predicting HD progression, but recognizable changes in methylation deserve further research.
| S-EPMC6104454 | biostudies-literature