Temporal dynamic reorganization of 3D chromatin architecture in hormone-induced breast cancer and endocrine resistance

Abstract

Recent studies have demonstrated that chromatin architecture is linked to the progression of cancers. However, the roles of 3D structure and its dynamics in hormone-dependent breast cancer and endocrine resistance are largely unknown. Here we report the dynamics of 3D chromatin structure across a time course of estradiol (E2) stimulation in human estrogen receptor α (ERα)-positive breast cancer cells. We identified subsets of temporally highly dynamic compartments predominantly associated with active open chromatin and found that these highly dynamic compartments showed higher alteration in tamoxifen-resistant breast cancer cells. Remarkably, these compartments are characterized by active chromatin states, and enhanced ERα binding but decreased transcription factor CCCTC-binding factor (CTCF) binding. We finally identified a set of ERα-bound promoter–enhancer looping genes enclosed within altered domains that are enriched with cancer invasion, aggressiveness or metabolism signaling pathways. This large-scale analysis expands our understanding of high-order temporal chromatin reorganization underlying hormone-dependent breast cancer.

FOXA1 upregulation promotes enhancer and transcriptional reprogramming in endocrine-resistant breast cancer

“…This raises the possibility that H-FOXA1 adopts a similar mechanism, as shown in embryonic development, to establish SEs engaged by multiple self-reinforcing TFs and to activate transcriptional reprogramming to promote endocrine resistance and metastasis. Future studies are needed to further advance our understanding of the involvement of 3D chromatin architecture (56) in enhancer reprogramming upon endocrine resistance driven by H-FOXA1 signaling, including by endogenous or exogenous FOXA1 OE and amplification.…”

Modeling and analysis of Hi-C data by HiSIF identifies characteristic promoter-distal loops

“…Four publicly available human Hi-C datasets representing different experimental protocols and sequencing depths were downloaded, including Hi-C data in MCF10A and MCF7 cells [36], hESC cells [35], and in situ Hi-C data in GM12878 cells and K562 cells [5]. Raw and processed Hi-C data for MCF7 and MCF7-TamR cells is deposited in GEO under accession number GSE108787 [37]. All Hi-C data were aligned to human genome hg19 and pre-processed using the hiclib pipeline [16], and formatted as an appropriate input to HiSIF.…”

“…3C-qPCR experiments were referred to chromosome conformation capture assay as previously described [37,43]. Briefly, ten million cells were collected and then fixed with 1% formaldehyde.…”

TADCompare: An R Package for Differential and Temporal Analysis of Topologically Associated Domains

“…The continuous nature of boundary score allows for adopting time course analysis methods developed for gene expression studies (Bar-Joseph et al, 2012). More flexible classification of temporal trends may be considered, such as 24 temporal patterns proposed by Zhou et al (2019), or fuzzy clustering techniques that do not require a pattern to belong to a specific cluster (Abu-Jamous and Kelly, 2018). In summary, our work enables further development of various aspects of 3D genome analysis.…”

“…As the costs of Hi-C data continue to drop, several studies started to investigate the dynamics of 3D changes over time. The most notable applications include cell differentiation studies (Bonev et al, 2017), embryonic development (Du et al, 2017;Hug et al, 2017;Ke et al, 2017), cancer progression (Zhou et al, 2019). Typically, TAD boundary changes over time are quantified by overlap (Du et al, 2017;Hug et al, 2017) and classified into distinct patterns (Zhou et al, 2019).…”