Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors

doi:10.21203/rs.3.rs-2909119/v1

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Research Article

Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors

https://doi.org/10.21203/rs.3.rs-2909119/v1

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Journal Publication

published 28 Nov, 2023

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Background

Triple-negative breast cancer (TNBC) is an aggressive subtype that exhibits a high incidence of distant metastases and lacks targeted therapeutic options. Here we explored how the epigenome may contribute to matrix metalloprotease (MMP) dysregulation given their key role in invasion, which is the first step of the metastatic process.

Methods

We combined RNA expression and chromatin interaction data to identify insulator elements potentially associated with invasion. We stably disrupted the CCCTC-Binding Factor (CTCF) binding site of a single insulator element in two TNBC cellular models. We characterized these models by combining Hi-C, ATAC-seq, and RNA-seq with functional experiments to determine invasive ability. Our findings were then also tested in a ductal carcinoma in situ (DCIS) cohort.

Results

We explored the clinical relevance of an insulator element located within the Chr11q22.2 locus, downstream of the MMP8 gene (IE8). This regulatory element resulted in a topologically associating domain (TAD) boundary that isolated nine MMP genes into two anti-correlated expression clusters. This expression pattern was strongly associated with worse relapse-free (HR = 1.57 [1.06 − 2.33]; p = 0.023) and overall (HR = 2.65 [1.31 − 5.37], p = 0.005) survival of TNBC patients. After CRISPR/Cas9-mediated disruption of IE8, cancer cells showed a switch in the MMP expression signature, specifically downregulating the pro-invasive MMP1 gene and upregulating the antitumorigenic MMP8 gene, resulting in reduced invasive ability. Finally, we observed that the imbalance in the MMP expression predicts DCIS that eventually progresses into invasive ductal carcinomas (AUC = 0.77, p < 0.01).

Conclusion

Our study demonstrates how the activation of an IE near the MMP8 gene determines the regional transcriptional regulation of MMP genes with opposing functional activity, ultimately influencing the invasive properties of aggressive forms of breast cancer.

MMP1

MMP8

CTCF

insulator

chromatin

gene regulatory element

cis-regulatory element

breast cancer

invasion

ATAC-seq

RNA-seq

Hi-C

Breast cancer is the leading cause of cancer death in women [1]. Between 20–30% of patients with early breast cancer relapse with distant metastases [2]. However, breast cancer subtypes vary in their aggressivity. For example, triple-negative breast cancer (TNBC) – defined by the lack of estrogen and progesterone receptors as well as the absence of HER2 overexpression or amplification [3] – is associated with worse survival and higher frequencies of lung, brain, and distant nodal relapse compared to other breast cancer subtypes [2]. The ability to invade adjacent tissues and colonize secondary sites through metastasis is associated with at least two-thirds of cancer deaths [4]. The clinical relevance of invasion in breast cancer is not limited to distant metastasis, as the progression from in situ ductal carcinomas (DCIS) [5] to invasive ductal carcinomas (IDC) constitutes an unsolved clinical challenge.

The lack of understanding regarding the molecular determinants involved in the invasion steps often results in overtreatment for patients with early breast cancer or hinders the ability to suppress metastatic progression [6]. Initial invasion, as well as distant metastasis, are tightly regulated by the coordinated activation of gene expression programs. Matrix metalloproteinases (MMPs) are key mediators of invasion [7]. Apart from extracellular matrix (ECM) remodeling, these enzymes promote the release of cytokines or growth factors involved in angiogenesis, epithelial-to-mesenchymal transition (EMT), and inflammation, among others [8]. The human MMP family comprises 23 matrix-degrading enzymes, which are either secreted into the extracellular space or displayed on the cell surface [9]. Control of MMP expression and spatiotemporal distribution is lost during tumorigenesis [10]. The upregulation of a set of MMPs, including MMP1, MMP2, and MMP9, has been associated with worse prognosis in different malignancies including breast cancer [11–13]. Despite the protumorigenic effects of certain MMPs, studies have revealed that other members of the MMP family exhibit different and even opposite roles depending on the context and tumor type. For instance, although MMP8 expression has been linked to poor prognosis in liver and gastric cancers, it surprisingly has a protective effect against metastatic progression in the head and neck, skin, and breast cancer [14–16]. These findings challenge the conventional notion that MMPs promote tumor progression and suggest a previously unrecognized protective role [17]. Therefore, gaining more comprehensive knowledge of MMP regulation is crucial to understanding how MMPs contribute to invasion.

MMP expression is altered through epigenetic mechanisms in cancer. At least 14 MMPs show a CpG island in their promoter region, where aberrant DNA methylation is associated with a loss of MMP expression in different cancers [18]. For instance, MMP2 and MMP9 expression levels are restored upon DNA methyltransferase inhibition with 5-aza-2′-deoxycytidine in pancreatic and breast cancer cell lines, respectively [19, 20]. Besides promoter silencing, chromatin conformation may influence transcriptional programs by modulating gene regulatory elements such as insulators and enhancers [21].

In this study, we have focused on the role of gene regulatory elements in the regulation of MMP expression on a genomic region (Chr11q22.2) that encodes nine MMPs. The combination of multi-omic assays and functional experiments revealed that disruption of an insulator element located near the MMP8 gene triggers changes in nearby promoter accessibility, gene expression, and chromatin conformation. Interestingly, the MMP8 insulator element impairment leads to a decrease in the pro-invasive enzyme MMP1 and increased MMP8 expression levels, two events that are associated with antitumor activity in breast cancer. Functionally, we determined that these changes decrease the invasiveness capability in cellular models. We found that tumors can be classified according to the ratio between the expression of pro-invasive and antitumoral MMP genes encoded in the surroundings of the MMP8 insulator element. This signature is significantly associated with disease-free and overall survival in patients with invasive TNBC, and most importantly, is associated with the progression of DCIS to IDC in clinical specimens. Thus, this study unraveled and characterized a regional regulatory role for an insulator element that defines MMP gene expression reprogramming, which may contribute to the invasive ability of aggressive breast cancer.

Detailed procedures regarding model generation, multi-omic experiments, and functional assays were provided in Supplemental Methods.

Data access, collection, and normalization. The Cancer Genome Atlas (TCGA) data, including mRNA expression and clinical data, were obtained using the TCGAbiolinks R package. Datasets were curated to define those patients with TNBC cancer, defined by the negativity of estrogen and progesterone receptors and HER2 [22, 23]. Moreover, only samples with a tumor purity higher than 66% were included. Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) data was obtained from Long-range chromatin interaction experiments in public tracks and WhasU Epigenome Browser [24]. Survival analysis was performed using the KM plotter web tool [25]. Overall survival and relapse-free survival were determined using gene chip breast cancer data. For survival analysis, TNBC patients were defined as those classified as ER and HER2 negative in array samples. The follow-up was restricted to 60 months. Kaplan Meier curves were performed on July 6^th, 2022. Expression quantitative trait loci (eQTLs) associated with each MMP located at the Chr11q22.2 were downloaded from Genotype-Tissue Expression (GTEx) Project [26]. Plotted arcs start at the SNP position and end at the TSS of the modulated gene. Association p-value is reflected in arc height, whereas arc sense depends on whether the eQTL is associated with an increase or a decrease in expression. mRNA expression levels of breast cancer cell lines were obtained from Cancer Cell Line Encyclopedia (CCLE) [27]. Data were downloaded from DepMap Public 22Q2 Primary Files. We used two non-coding mutation databases to interrogate mutations at the Chr11q22.2: the PCAWAG consensus call sets for SNV/Indel [28] (N = 2,658) and whole genome sequencing data of 237 TNBC samples [29]. CTCF binding sites were considered from the intersection between CTCF motifs and the Insulator elements from Figure S3a pipeline. Data processing and visualization were performed using corrplot, ggbio, ggpubr, patchwork, pheatmap, rstatix, RColorBrewer, tidyverse, and viridis R packages.

Cell lines. Cancer cell lines MDA-MB-231 and MDA-MB-436 were purchased from the American Type Culture Collection (ATCC). MDA-MB-231 and MDA-MB-436 were cultured in RPMI 1640 Glutamax™ supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin antibiotic at 37°C and 5% CO₂. Cell lines were validated with short tandem repeat analysis using the Genetics Core, The University of Arizona (Phoenix, USA). All cell lines and models were periodically verified as negative for mycoplasma contamination using MycoAlert Mycoplasma Detection Kit (Lonza).

In situ and invasive breast cancer clinical tissue gene expression profiling. The study cohort included invasive and in situ BC tissues that were processed as described [30]. Cases without data about tumor size (T), relapse and/or follow-up under three years, or missing relapse data were removed from the analysis. The relapse-free event was used as an endpoint. Read counts were normalized by applying Log2(Counts + 1). The expression of each MMP gene was standardized using the gene median expression in the entire cohort, and non-detectable levels of any of the MMPs were replaced by their minimal detected signal for each given gene. This cohort includes 85 DCIS, from which 14 progressed into IDC; T1 (N = 2,558), T2 (N = 1,006), and T3 (N = 56) invasive ductal carcinomas. Kaplan-Meier analyses were performed using the DCIS from the same cohort and the receiver operating curves (ROC) were obtained using the pROC v1.16.2 R package. Additionally, breast cancer tissues from patients with DCIS with (N = 55) or without (N = 95) invasive recurrence were processed as described [31]. Data from differentially expressed genes comparing DCIS with or without ipsilateral breast event recurrence were used to evaluate MMP expression between these tumor types.

MMP dysregulation in TNBC is associated with relapse-free and overall survival.

Given the relevance of MMPs in the first step of the metastatic process, we explored the differences in mRNA expression levels between non-metastatic TNBC and normal tissue samples in The Cancer Genome Atlas (TCGA) cohort. Seven MMPs were downregulated and ten MMPs were upregulated in TNBC tumors (n = 90) compared to normal tissues (n = 99, Figure S1a). Interestingly, six consecutive MMP genes with increased expression in TNBC tumors are encoded on the same genomic locus (Fig. 1a), in a region that harbors nine different MMP genes, located at Chr11q22.2 (Figure S1b). Furthermore, coexpression patterns were observed in TNBC tumors between genes located on each side of the MMP region, revealing two different expression clusters (Fig. 1b), which were defined as 5’MMP region (containing MMP7, MMP8, MMP20, and MMP27; in addition to neighbor non-MMP genes TMEM123 and BIRC3) and 3’MMP region (containing MMP1, MMP3, MMP10, MMP12, and MMP13). The ratio of the expression levels between MMP genes located at Chr11q22.2 (3’MMP/5’MMP) was significantly higher in TNBC (Figure S1c). Thus, we hypothesized that the alternative expression of these two clusters might be associated with survival in TNBC patients. Using the Kaplan-Meier analysis in patients with TNBC (n = 417), we observed that tumors with higher expression of MMPs located at the 3’MMP region have a significantly shorter relapse-free survival (RFS; Fig. 1c, [log rank P = 0.023; hazard ratio (HR) = 1.57, 95% CI = 1.06 − 2.33]) and overall survival (Fig. 1c, OS; [log rank P = 0.0048; HR = 2.65, 95% CI = 1.31 − 5.37]). We examined if the expression of these MMP genes was also linked to differential prognosis in non-TNBC cohorts. No differences were observed in RFS neither in hormone receptor-positive nor HER2-positive breast cancer subtypes. Regarding OS, the MMP signature was associated with a shorter survival in hormone receptor-positive, but a better prognosis was found in HER2-positive breast cancer. Interestingly, when considering non-breast solid tumors, this signature was associated with a worse prognosis in liver cancer, lung adenocarcinoma, and sarcoma, whereas it correlated with better survival in gastric cancer (Figure S2). Thus, the upregulation of 3’MMP genes appears to be associated with worse survival outcomes in patients beyond TNBC, so we will focus on this breast cancer subtype as a model for the study of this alteration.

An insulator element nearby the MMP8 gene promoter region is involved in regional MMP gene regulation.

Considering the expression pattern exhibited by the MMP genes at Chr11q22.2, we explored the distribution of gene regulatory elements in this region ( Figure S3a). We found 29 potential insulator elements (IEs) and 13 potential enhancer elements (EEs) at Chr11q22.2 (Fig. 2a). The IEs play a pivotal role in the topologically associating domain (TAD) formation, being DNA elements recognized by the CCCTC-binding factor (CTCF) and contributing to chromatin loop formation [32]. We explored potential TADs at Chr11q22.2 using data from CTCF ChIA-PET (Figure S3b). This data suggested that the IE located between the MMP8 promoter region and the MMP10 gene body (chr11:102,732,800 − 102,733,900; hg38), hereinafter IE8, demarcates a boundary for a TAD contributing to the expression signature observed by MMP genes at Chr11q22.2. This is supported by data from eQTLs. We observed that SNPs tend to modulate the expression of genes located on the same side TADs at Chr11q22.2 (Figure S3c). It is worth noting that the CTCF binding site of the IE8 was depleted in mutations according to data from the Pan-Cancer Analysis of Whole Genomes (PCAWAG) database (N = 2,658) and whole genome sequencing of TNBC samples (N = 237) (Figure S3d), indicating that its normal function is required in cancer.

To explore the role of IE8 activation on MMP expression, we stably disrupted the CTCF binding motif on IE8 using CRISPR/Cas9 technology in TNBC cell lines. We initially explored the expression levels of MMP genes in a panel of well-characterized TNBC cell lines (n = 17; Fig. 2b). We selected MDA-MB-231 and MDA-MB-436, two cell lines that showed an increased expression of the 3’MMP genes when compared to the 5’MMP genes, which recapitulates the expression pattern observed in TNBC-patient samples (Fig. 1a and S1c). We characterized chromatin interactions in these two cell lines using Hi-C. We observed that IE8 colocalizes with TAD boundaries in both models, in concordance with data from ChIA-PET (Fig. 2c).

Cancer cells were transiently transfected with a Cas9-containing plasmid and a sgRNA against the IE8. A single clone for each condition was selected to perform further experiments (Figure S4). To evaluate the disruption, CTCF binding ability to IE8 was tested in both cell lines through Cleavage Under Targets and Release Using Nuclease (CUT&RUN) followed by qPCR [33]. Basal levels of CTCF occupancy were higher in MDA-MB-231 than in MDA-MB-436. After IE8 disruption, a significant decrease in CTCF binding was observed in both MDA-MB-231 and MDA-MB-436 when compared to wild-type counterparts (Fig. 2d).

Hi-C was also performed on TNBC cell lines after IE8 disruption. We found that disruption of IE8 did not change TAD distribution at Chr11q22.2 (Figure S5a). However, we observed that IE8 tends to interact with 3’ distal regions in both models and conditions. Interestingly, some of these potential interactions contain other IEs disposed of in a convergent orientation to IE8. It has been reported that 90% of IE interactions are convergently oriented. Thus, we identified some potential partners of IE8 located at the 3’MMP region of Chr11q22.2 (Figure S5b).

Disruption of IE8 leads to local chromatin accessibility changes.

To address the implications of the IE8 disruption on chromatin accessibility we performed ATAC-seq on our TNBC cell line models. 34,047 common peaks between all replicates were identified in MDA-MB-231, whereas 35,347 common peaks were found in MDA-MB-436. Accessibility analysis was performed by assessing differential accessibility peaks, which were defined by either their presence in only one condition (WT or IE8 dis) or by the significant change in intensity of shared peaks between conditions (Figure S6a). Thus, we identified 3,083 and 2,232 regions that gained and lost accessibility upon IE8 disruption in MDA-MB-231, respectively. Regarding MDA-MB-436, 8,673 and 370 regions were more and less accessible after IE8 disruption, respectively (Fig. 3a). Importantly, a significant overlap between the differentially accessible regions (n = 1,033) of both cell lines was observed.

Despite changes in chromatin accessibility being detected across the genome, we examined whether they were also specifically enriched around IE8. We explored the differentially accessible regions located on chromosome 11- where our region of interest is located – as well as in different width windows around IE8 (± 10MB to ± 0.5MB). Significant enrichment in the number of differentially accessible regions was observed in the IE8 genome vicinity whereas no differences were observed across chromosome 11 (Fig S6b).

Moreover, we aimed to identify potential gene regulatory elements associated with differential chromatin accessibility reprogramming after IE8 disruption. The relative abundance of promoter, enhancer, and insulator elements that exhibited differential accessibility after IE8 disruption was similar between MDA-MB-231 and MDA-MB-436 (Figure S6c). We focused on changes in chromatin accessibility around (± 2 kb) the gene transcription start sites (TSS). As expected, the resulting heatmap displayed a similar accessibility profile on all conditions with increased peak density on the TSS (Fig. 3b). Similar profiles were also observed between all conditions when peaks were centered in insulators and enhancers (Figure S6d). However, we found interesting differences when we focused on the TSS of the genes located at the Chr11q22.2. Promoters in the 5’MMP region were more accessible upon IE8 disruption, but no changes were observed in promoter regions located toward the 3’MMP region (Fig. 3b and Fig. 3c). In this regard, we also found changes in the accessibility of enhancer elements in both 5’ and 3’ MMP regions (Figure S6e). We additionally identified a decrease in chromatin accessibility at the IE8 CTCF binding site disrupted by CRISPR/Cas9 (Fig. 3d). In agreement with a higher CTCF occupancy detected by CUT&RUN (Fig. 2d), the decrease in chromatin accessibility of this site was more evident in the MDA-MB-231 cells than in the MDA-MB-436 cells.

IE8 disruption modulates regional MMP expression patterns

We determined whether the observed alterations in chromatin accessibility resulted in differential expression of the MMP genes nearby IE8. We assessed the mRNA expression levels of MMP genes in the wild-type and IE8-disrupted cells through RNA-seq. We observed 237 mRNAs with a significant differential expression upon IE8 impairment (Fig. 4a). We performed a gene ontology (GO) analysis to classify the 166 significantly upregulated and 71 downregulated genes by biological process. Significant pathways, such as extracellular matrix organization or Ca²⁺-dependent cell-cell adhesion were found significantly modulated (Figure S7a). Since the CRISPR/Cas9-mediated IE8 disruption occurred in chromosome 11, we assessed whether significant changes were enriched on this chromosome. We did not observe significant variation in gene expression when considering all the genes, but the genes located 1Mb around IE8 were significantly modulated after IE8 disruption in MDA-MB-231 (Fig. 4b).

Regarding the Chr11q22.2 encoded genes, the modification of regional gene expression patterns supports the promoter accessibility changes (Fig. 3c, Figure S6d). RNA-seq revealed two interesting changes at the mRNA level, an increase in MMP8 and a decrease in MMP1 (Fig. 4c) after IE8 disruption. These alterations were confirmed by qPCR (Fig. 4d). MDA-MB-231 showed a shift between MMP1 and MMP8 after the IE8 disruption, exhibiting a decrease in the pro-invasive enzyme MMP1 and an increase in MMP8, associated with antitumor activity. Although variations were not statistically significant, RNA expression levels displayed a similar tendency in MDA-MB-436 (Fig. 4d). Thus, the ratio between MMP1 and MMP8 is decreased after IE8 disruption, resembling the profile observed in healthy breast samples as opposed to tumor samples (Figure S7b).

We explored whether dysregulation of the MMPs located in the genomic vicinity of IE8 triggered any compensatory mechanism either modulating the expression of tissue inhibitor of metalloproteinases (TIMP) genes, a four-member family that balances the MMP activity or altering the RNA levels of two other relevant metalloproteinases, MMP2 and MMP9. TIMP1, TIMP2, TIMP3, and TIMP4 did not show significant changes at the mRNA level upon IE8 disruption (Figure S7c). IE8 depletion was not associated with changes in chromatin accessibility at MMP2 or MMP9 promoter regions. However, an important increase in accessibility was reported on enhancer elements located 8kb and 15kb upstream of TSS of the MMP2 and MMP9 genes, respectively (Fig. 4e). These changes were translated into a cell line-dependent increase in MMP mRNA levels. MMP2 was upregulated only in MDA-MB-231 whereas MMP9 was increased in MDA-MB-436 after IE8-disruption (Fig. 4f).

We considered whether changes in chromatin accessibility and the concomitant modulation of gene expression may also be observed in TNBC patient samples. We explored the six TCGA TNBC samples with ATAC-seq and mRNA-expression data. We found different levels of chromatin accessibility at IE8 (Figure S8a). Interestingly, we could associate these changes to variations in 3’MMP/5’MMP expression. We observed that those patient-derived samples with higher levels of accessibility at IE8 showed a higher ratio of 3’MMP vs 5’ MMP genes (Figure S8b)

IE8 disruption interferes with MMP1 release and decreases invasive potential in breast cancer.

We observed that IE8 disruption triggered a significant decrease in MMP1 protein levels both in MDA-MB-231 and MDA-MB-436 (Fig. 5a). We checked the functional consequences of IE8 disruption on relevant features of cancer cells. We did not observe differences either in cell proliferation (Fig. 5b) or in clonogenic ability (Figure S9a). Migration capacity assessed by wound healing assay showed no changes between wild-type and IE8 disruption conditions (Fig. 5c, Figure S9b). However, the invasion competence interrogated through 3D spheroid invasion assay was significantly reduced in IE8-disrupted MDA-MB-231 cells, but no differences were observed in the IE8-disrupted MDA-MB-436 cells (Fig. 5d). However, when we employed collagen I – which is a major component of ECM and the breast basement membrane [34]- we observed a significant decrease in the number of invasive cells after IE8 disruption in both the MDA-MB-231 and MDA-MB-436 cells (Fig. 5e).

Therefore, we explored whether the ratios between pro-invasive and antitumorigenic MMPs are linked to the progression of ductal carcinomas in situ (DCIS) to invasive ductal carcinoma (IDC) regardless of the breast cancer subtype. We compared clinical specimens of normal breast tissue, pure DCIS, and IDC from different TNM stages. The MMP (3’MMP/5’MMP) ratio was significantly higher in DCIS and IDC when compared to normal breast tissue (P_DCIS<0.001, P_IDC<0.001), (Figure S9c). Importantly, DCIS that eventually progressed to invasive disease displayed a significantly higher MMP ratio than those that did not progress (Figure S9d). Remarkably when considering the ratio between the pro-invasive MMP1 and the antimetastatic MMP8, the differences in DCIS that progressed to invasive disease were even more pronounced (P = 0.002, Fig. 5e). There were no changes between IDC stratified by tumor size. High MMP ratios were also associated with shorter relapse-free survival in patients with DCIS (p-value < 0.001, Fig. 5f and Figure S9e). Importantly, MMP ratios significantly predicted which DCIS patients will progress to invasive disease (AUC = 0.67–0.77, Fig. 5g, Figure S9f). Importantly, in an independent cohort of DCIS patients [31] we found that MMP1 is significantly upregulated in DCIS that progressed ipsilateral breast event (Figure S9g). Altogether, our results suggest that IE8 disruption diminishes invasiveness in the presence of collagen I and that MMP gene expression reprogramming significantly predicts the progression of DCIS to invasive disease.

Metastasis is an orchestrated process that starts with the escape of cancer cells from their primary niche and ends with the colonization of secondary sites. During the first stage, cancer cells degrade the basement membrane through the release and activation of MMP enzymes and undergo an EMT, establishing crosstalk with stromal cells [35]. In this study, we showed that the balanced expression profile of nine MMP genes located at chromosome 11 (Chr11q22.2) is influenced by an insulator element near the MMP8 gene (IE8). CRISPR/Cas9-mediated disruption of IE8 triggered changes in chromatin accessibility and mRNA expression on the genomic region around IE8. Among these changes, we observed an upregulation of MMP8 and a downregulation of MMP1. These changes in mRNA expression were accompanied by differences in the invasive properties of TNBC.

MMP1 upregulation displays a pivotal role in metastasis in several malignancies including TNBC. MMP1 is overexpressed during lymph node metastasis in xenografted mice in a TNBC model [36] and exosomes extracted from the serum of metastatic TNBC patients displayed higher levels of MMP1 than in patients with no metastatic disease [37]. In addition, RUNX2-mediated increment of MMP1 levels has been associated with chemoresistance [38]. Regarding drug resistance, MMP1 promoter hypomethylation increases tamoxifen resistance in hormone receptor-positive breast cancer [39]. Therefore, several publications support the role of MMP1 in aggressiveness in different malignancies. Specifically, on TNBC, Wang et al. observed a decrease in cell proliferation, migration, and colony formation after MMP1 knockdown through shRNAs in MDA-MB-231, one of the TNBC cell lines used in our study [12]. However, we did not observe these consequences after the IE8 disruption. This disparity could be explained by the fact that the decrease in MMP1 after IE8 disruption is not as pronounced as that seen with MMP1 mRNA-directed shRNAs. In addition, the cell line-dependent upregulation of MMP2 and MMP9 that we observe in our models may mitigate the impact of the reduction of MMP1 levels, an observation not reported by Wang et al. The effects on cell invasion after IE8 disruption detected in our study are consistent with the findings by Lim et al, who observed a decrease in invasiveness after the knockdown of the MMP1 upstream activating factor YBX1 [40].

The role of MMP8 in cancer is more controversial since its expression has been associated with both better and worse prognoses depending on the tissue of origin [15]. Most studies performed in breast cancer associate MMP8 with a protective role. MMP8-expressing cells are less invasive in vitro [41], systemic MMP8 expression decreases tumor size in mice [42] and MMP8 blood levels are associated with lower lymph node metastasis rates [14]. Various complementary studies delved into the underlying mechanisms that link MMP8 upregulation and the reported tumor-protective effects. MMP8 overexpression enhanced the cleavage of decorin, which diminished the transforming growth factor β (TGF-β) signaling. The decrease in this pathway promoted miR-21 downregulation and the subsequent induction of tumor suppressors such as programmed cell death 4 (PDCD4) [43]. MMP8 also alters the adhesive and proteolytic properties of the ECM, increasing cell-cell adhesion [44] and cleaving other MMPs, such as MMP3 [42]. We believe that the differential CTCF occupancy at IE8 may also contribute to the protective role that has been associated with MMP8 upregulation since its activation – as well as the other 5’MMP genes – implies a compensatory decrease in MMP1 and other 3’MMP genes. Thus, an integrative vision of MMPs encoded at the Chr11q22.2 rather than focusing on a single MMP may be more useful for determining the progression risk of breast cancer patients and evaluating potential therapeutic strategies.

The ratios of 3’MMPs/5’MMPs and MMP1/MMP8 were found to be higher in DCIS which eventually progressed to invasive disease (Fig. 5). In fact, MMP1 has been previously associated with DCIS with micro-invasive foci [45], whereas MMP8 loss has been linked to DCIS progression [44]. Interestingly, the MMP1/MMP8 ratio alone exhibited similar performance to the 812-gene classifier generated by Strand et al [31] for the RAHBT cohort (AUC = 0.72). Therefore, this alteration appears to be relevant during the invasive transition of this disease. While further studies are needed to characterize the role of IE8 activation in breast cancer invasion, these results point towards a potential dynamic regulation of the gene expression program at Chr11q22.2.

Genome-wide analyses have revealed a strong overlap between chromatin loops and CTCF binding sites [46]. Furthermore, different studies have proven that the alteration of the CTCF binding site – either through its disruption or its inversion – has an impact on chromatin architecture, which disturbs promoter-enhancer interactions [47, 48]. Moreover, the gain or loss of cancer-specific CTCF binding events contributes to oncogenic transcriptional programs [49]. CTCF binding ability can be impaired through somatic mutations [21], but also DNA methylation [50]. We characterized that CTCF is effectively bound to the CTCF binding site located at IE8 in our TNBC models. After IE8-disruption and consequent CTCF decoupling, gene regulatory elements on both 5’ and 3’MMP regions can physically interact again. Consequently, IE8-disruption is followed by an increase in chromatin accessibility on promoter regions of the 5’MMP region as well as higher exposure of enhancer elements of both the 5’ and 3’MMP regions. The interplay between IE8 and the expression of local MMPs is not restricted to our cell models. We observed a strong positive correlation between chromatin accessibility at IE8 and the expression ratio between 3’MMPs (MMP1, MMP3, MMP10, MMP12, MMP13) and 5’MMPs (MMP7, MMP8, MMP20, MMP27) in TNBC patients, supporting the idea that IE8 effectively contributes to the modulation of gene expression at the Chr11q22.2 in this malignant neoplasm (Figure S8).

In summary, we combined multi-omics profiling with functional experiments to characterize the regulation of MMPs encoded at Chr11q22.2. This study provides evidence that a single chromatin insulator located between MMP8 and MMP10 orchestrates the expression of two different clusters of MMP genes in TNBC, which are associated with in vitro invasiveness and whose expression profile appears to impact DCIS progression and survival outcomes in patients with triple-negative breast cancer.

Abbreviation	Meaning
ATAC-seq	Assay for Transposase-Accessible Chromatin using sequencing
ATCC	American Type Culture Collection
AUC	Area under the curve
CCLE	Cancer Cell Line Encyclopedia
ChiA-PET	Chromatin Interaction Analysis with Paired-End Tag
CTCF	CCCTC-Binding Factor
CUT&RUN	Cleavage Under Targets and Release Using Nuclease
DCIS	Ductal carcinoma In situ
DEGs	Differentially Expressed Genes
ECM	Extra-Cellular Matrix
EE	Enhancer element
EMT	Epithelial-to-Mesenchymal Transition
eQTLs	Expression of quantitative trait loci
EV	Empty vector
FBS	fetal bovine serum
GO	Gene ontology
GTEX	Genotype-Tissue Expression
Hi-C	High‐throughput chromosome conformation capture
HR	Hazard ratio
IDC	Invasive Ductal Carcinoma
IE	Insulator element
IE8	Insulator element close to MMP8
Indel	Insertion or deletion
MMP	Matrix metalloproteinase
OS	Overall survival
PCAWAG	Pan-Cancer Analysis of Whole Genomes
qPCR	quantitative PCR
RFS	Relapse-Free survival
RIN	RNA Integrity Number
RNA-seq	RNA sequencing
sgRNA	Single guide RNA
SNP	Single Nucleotide Polymorphism
SNV	Single Nucleotide Variant
T	Tumor size
TAD	Topologically Associating Domain
TCGA	The Cancer Genome Atlas
TIMP	Tissue Inhibitor of Metalloproteinases
TNBC	Triple-negative breast cancer
TSS	Transcription start site
WT	Wildtype

DATA AVAILABILITY

All raw and processed data are freely available from the ENA repository and have been deposited under the following accession codes: E-MTAB-12825 (Hi-C), E-MTAB-12821(ATAC-seq), E-MTAB-12823 (RNA-seq). An exhaustive explanation of these datasets is available in our related data descriptor [Currently sent BMC Genomics].

CODE AVAILABILITY

All analyses were performed using open-source R and Python packages. ATAC-seq read processing was performed using the following software versions: nf-core/atacseq (v1.2.1), Nextflow (v21.04.3), FastQC (v0.11.9), Trim Galore!(v0.6.4_dev), BWA (v0.7.17-r1188), Samtools (v1.10), BEDTools (v2.29.2), BamTools (v2.5.1), deepTools (v3.4.3), Picard (v2.23.1), R (v3.6.2), Pysam (v0.15.3), MACS2 (v2.2.7.1), ataqv (v1.1.1), featureCounts (v2.0.1), Preseq (v2.0.3), MultiQC (v1.9). HiC read processing was performed using the following software versions: nf-core/hic (v1.3.0), Nextflow (v21.10.6), Bowtie2 (v2.3.5.1), Python (v3.7.6), Samtools (v1.9), MultiQC (v1.8). RNA-seq reads processing was performed using the following software versions: bcl2fastq (v2.20.0.422), FastQC (v0.11.9), MultiQC (v1.13.dev0), Fastp (v0.21.0), HISAT2 (v2.2.0), Samtools (v1.10), StringTie (v2.1.4). DESeq2 (1.3.1) was used to calculate differentially expressed genes from RNA-seq and perform PCA analysis. Further data processing was performed using R packages from tydiverse, such as dplyr, tidyr, and ggplot2; pheatmap, rstatix, and viridis. Galaxy servers were also used for ATAC-seq analysis.

ACKNOWLEDGMENTS

This project was supported by the National Genomics Infrastructure in Stockholm funded by Science for Life Laboratory, the Knut and Alice Wallenberg Foundation and the Swedish Research Council, and SNIC/Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We also want to acknowledge Llabata. P and Pellicer. B for their technical support in RNA-seq and CUT&RUN experiments, respectively.

FUNDING

This work was supported by the Instituto de la Salud Carlos III (ISCIII) Sara Borrell project (#CD22/00026), Miguel Servet Project (#CPII22/00004), and AES 2022 (#PI22/01496) co-funded by European Union, the Institut d’Investigació Sanitària Illes Balears (FOLIUM program and IMPETUS Call IMP21/10), the Govern de les Illes Balears (Margalida Comas program), the Fundación Francisco Cobos, the Asociación Española Contra el Cancer (AECC), the department of European Funds, University, and Culture of the Government of the Balearic Islands and the “CONTIGO Contra el Cancer de Mujer” foundation (#MERIT project). The Fashion Footwear Association of New York (FFANY) Foundation. The group acknowledges support from the EASI-Genomics project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 824110.

Contributions

P.L.-A., J.I.J.O., and D.M. designed the core of the study. M.L., A.B., and M.E. provided scientific input and experimental support to complete the experimental approach. J.C., E.S.H., and M.L.D. provided inputs and guidance about the interpretation of the clinical impact of the study. P.L.-A., M.E.-M., C.M, and M.S. were responsible for computational biology experiments. P.L.-A., J.I.J.O., S.I.-M., B.S., and B.V. performed cell culture and in vitro experiments. M.O. and A.M. supervised the ATAC-seq and Hi-C sequencing and data processing. P.L.-A. and D.M. wrote the manuscript with substantial contributions from E.S.H, J.I.J.O., J.C, M.D., M.E., A.B., and M.L.

ETHICS DECLARATIONS

Ethics approval and consent to participate

This study was approved by the Institutional Research Board of Hospital Universitario Son Espases (Code CI-542-21). It was performed following the Declaration of Helsinki. Written informed consent was obtained from each patient included by the original institutions.

Consent for publication

All authors revised and approved the manuscript.

Competing interests

The authors declare no competing interests.

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No competing interests reported.

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Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors

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