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Regional methylome profiling reveals dynamic epigenetic heterogeneity and convergent hypomethylation of stem cell quiescence-associated genes in breast cancer following neoadjuvant chemotherapy.

ABSTRACT: Background:Neoadjuvant chemotherapy (NAC) induces a pathological complete response (pCR) in ~?30% of patients with breast cancer. However, aberrant DNA methylation alterations are frequent events during breast cancer progression and acquisition of chemoresistance. We aimed to characterize the inter- and intra-tumor methylation heterogeneity (MH) in breast cancer following NAC. Methods:DNA methylation profiles of spatially separated regions of breast tumors before and after NAC treatment were investigated using high-density methylation microarray. Methylation levels of genes of interest were further examined using multiplexed MethyLight droplet digital PCR (ddPCR). Results:We have discovered different levels of intra-tumor MH in breast cancer patients. Moreover, NAC dramatically altered the methylation profiles and such changes were highly heterogeneous between the patients. Despite the high inter-patient heterogeneity, we identified that stem cell quiescence-associated genes ALDH1L1, HOPX, WNT5A and SOX9 were convergently hypomethylated across all the samples after NAC treatment. Furthermore, by using MethyLight ddPCR, we verified that the methylation levels of these 4 genes were significantly lower in breast tumor samples after NAC than those before NAC. Conclusions:Our study has revealed that NAC dramatically alters epigenetic heterogeneity in breast cancer and induces convergent hypomethylation of stem cell quiescence-associated genes, ALDH1L1, HOPX, WNT5A and SOX9, which can potentially be developed as therapeutic targets or biomarkers for chemoresistance.

SUBMITTER: Luo Y

PROVIDER: S-EPMC6367786 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Regional methylome profiling reveals dynamic epigenetic heterogeneity and convergent hypomethylation of stem cell quiescence-associated genes in breast cancer following neoadjuvant chemotherapy.

Luo Yumei Y Huang Juan J Tang Yi Y Luo Xitu X Ge Lingxia L Sheng Xiujie X Sun Xiaofang X Chen Yaoyong Y Zhu Detu D

Cell & bioscience 20190207

<h4>Background</h4>Neoadjuvant chemotherapy (NAC) induces a pathological complete response (pCR) in ~ 30% of patients with breast cancer. However, aberrant DNA methylation alterations are frequent events during breast cancer progression and acquisition of chemoresistance. We aimed to characterize the inter- and intra-tumor methylation heterogeneity (MH) in breast cancer following NAC.<h4>Methods</h4>DNA methylation profiles of spatially separated regions of breast tumors before and after NAC tre ...[more]

PMID: 30774927

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Project description:Microglia, the innate immune cells in the central nervous system, exhibit distinct transcriptional profiles across brain regions that are important for facilitating their specialized function. There has been recent interest in identifying the epigenetic modifications associated with these distinct transcriptional profiles, as these may improve our understanding of the underlying mechanisms governing the functional specialization of microglia. One obstacle to achieving this goal is the large number of microglia required to obtain a genome-wide profile for a single histone modification. Given the cellular and regional heterogeneity of the brain, this would require pooling many samples which would impede biological applications that are limited by numbers of available animals. To overcome this obstacle, we have adapted a method of chromatin profiling known as Cleavage Under Targets and Tagmentation (CUT&Tag-Direct) to profile histone modifications associated with regional differences in gene expression throughout the brain reward system. Consistent with previous studies, we find that transcriptional profiles of microglia vary by brain region. However, here we report that these regional differences also exhibit transcriptional network signatures specific to each region. Additionally, we find that these region-dependent network signatures are associated with differential deposition of H3K27ac and H3K7me3, and while the H3K27me3 landscape is remarkably stable across brain regions, the H3K27ac landscape is most consistent with the anatomical location of microglia which explain their distinct transcriptional profiles. Altogether, these findings underscore the established role of H3K27me3 in cell fate determination and support the active role of H3K27ac in the dynamic regulation of microglial gene expression. In this study, we report a molecular and computational framework that can be applied to improve our understanding of the role of epigenetic regulation in microglia in both health and disease, using as few as 2,500 cells per histone mark.

Project description:Breast tumor morphological and vascular characteristics can be changed during neoadjuvant chemotherapy (NACT). The early changes in tumor heterogeneity can be quantitatively modeled by longitudinal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is useful in predicting responses to NACT in breast cancer. In this retrospective analysis, 114 female patients with unilateral unifocal primary breast cancer who received NACT were included in a development (n = 61) dataset and a testing dataset (n = 53). DCE-MRI was performed for each patient before and after treatment (two cycles of NACT) to generate baseline and early follow-up images, respectively. Feature-level changes (delta) of the entire tumor were evaluated by calculating the relative net feature change (deltaRAD) between baseline and follow-up images. The voxel-level change inside the tumor was evaluated, which yielded a Jacobian map by registering the follow-up image to the baseline image. Clinical information and the radiomic features were fused to enhance the predictive performance. The area under the curve (AUC) values were assessed to evaluate the prediction performance. Predictive models using radiomics based on pre- and post-treatment images, Jacobian maps and deltaRAD showed AUC values of 0.568, 0.767, 0.630 and 0.726, respectively. When features from these images were fused, the predictive model generated an AUC value of 0.771. After adding the molecular subtype information in the fused model, the performance was increased to an AUC of 0.809 (sensitivity of 0.826 and specificity of 0.800), which is significantly higher than that of the baseline imaging- and Jacobian map-based predictive models (p = 0.028 and 0.019, respectively). The level of tumor heterogeneity reduction (evaluated by texture feature) is higher in the NACT responders than in the nonresponders. The results suggested that changes in DCE-MRI features that reflect a reduction in tumor heterogeneity following NACT could provide early prediction of breast tumor response. The prediction was improved when the molecular subtype information was combined into the model.

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Dataset Information

Regional methylome profiling reveals dynamic epigenetic heterogeneity and convergent hypomethylation of stem cell quiescence-associated genes in breast cancer following neoadjuvant chemotherapy.

Publications

Regional methylome profiling reveals dynamic epigenetic heterogeneity and convergent hypomethylation of stem cell quiescence-associated genes in breast cancer following neoadjuvant chemotherapy.

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