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. 2021 Nov 29;31(10):1599–1609. doi: 10.1093/hmg/ddab348

Disease-associated c-MYC downregulation in human disorders of transcriptional regulation

Maria M Pallotta 1,#, Maddalena Di Nardo 2,#, Patrizia Sarogni 3, Ian D Krantz 4, Antonio Musio 5,✉
PMCID: PMC9122636  PMID: 34849865

Abstract

Cornelia de Lange syndrome (CdLS) is a rare multiorgan developmental disorder caused by pathogenic variants in cohesin genes. It is a genetically and clinically heterogeneous dominant (both autosomal and X-linked) rare disease. Increasing experimental evidence indicates that CdLS is caused by a combination of factors, such as gene expression dysregulation, accumulation of cellular damage and cellular aging, which collectively contribute to the CdLS phenotype. The CdLS phenotype overlaps with a number of related diagnoses such as KBG syndrome and Rubinstein–Taybi syndrome both caused by variants in chromatin-associated factors other than cohesin. The molecular basis underlying these overlapping phenotypes is not clearly defined. Here, we found that cells from individuals with CdLS and CdLS-related diagnoses are characterized by global transcription disturbance and share common dysregulated pathways. Intriguingly, c-MYC (subsequently referred to as MYC) is downregulated in all cell lines and represents a convergent hub lying at the center of dysregulated pathways. Subsequent treatment with estradiol restores MYC expression by modulating cohesin occupancy at its promoter region. In addition, MYC activation leads to modification in expression in hundreds of genes, which in turn reduce the oxidative stress level and genome instability. Together, these results show that MYC plays a pivotal role in the etiopathogenesis of CdLS and CdLS-related diagnoses and represents a potential therapeutic target for these conditions.

Introduction

Cornelia de Lange syndrome [CdLS, Online Mendelian Inheritance in Man (OMIM) #122470, #300590, #610759, #614701, #300882] is a rare dominant condition with multiple structural and physiological anomalies affecting multiple organs including characteristic facial dysmorphism, pre- and postnatal growth retardation, congenital microcephaly, structural (upper) limb malformations, hypertrichosis and global neurodevelopmental delay (1). The estimated incidence is between 1:10 000 and 1:30 000 live births, with the majority of cases being sporadic and showing no difference between ethnic groups (2). CdLS is caused by pathogenic variants in cohesin structural and regulatory genes, namely NIPBL, SMC1A, SMC3, HDAC8, RAD21, BRD4 and ANKRD11 (3–9). Cohesin is an evolutionarily conserved protein complex involved in many biological processes fundamental for cell life. The canonical role of cohesin is in the cohesion of sister chromatids to ensure accurate chromosomal segregation to daughter cells during the cell cycle (10). Furthermore, experimental evidence indicates that cohesin also plays essential non-canonical roles in genome integrity because it promotes DNA repair by homologous recombination (11,12), acts as a scaffold for recruiting proteins involved in G2/M checkpoints (13,14), supervises fork replication speed (15,16) and preserves telomere stability (17,18). It is notable that pathogenetic variants in cohesin genes have been frequently detected in many human cancers (19–25). Finally, cohesin has been shown to be a key regulator of developmental gene expression, partially explained by its cooperation with the CCCTC-Binding Factor (CTCF), in conforming the mammalian genome into structures known as topologically associating domains (TADs) and bringing together distant enhancers with promoters (26–30). Cohesin depletion causes global disruption of appropriate TAD formation leading to gene expression dysregulation (31–35). Since CdLS is linked to cohesin dysfunction, it is not surprising that CdLS cells are characterized by both transcriptional dysregulation and genome instability (36–42).

Recently, individuals with phenotypes resembling CdLS, such as KBG (OMIM #148050), and Rubinstein–Taybi (RSTS, OMIM #180849, #613684), have been described. These individuals share some phenotypic features suggestive of CdLS, such as neurodevelopmental delays, microcephaly, short stature, thin upper lip and synophrys. Notably, they carried pathogenic variants in chromatin-associated factors other than cohesin genes, specifically in the EP300 and ANKRD11 genes (3,43–47). EP300 codes a histone acetyltransferase that regulates transcription via chromatin remodeling (48,49), whereas ANKRD11is a chromatin-associated protein involved in gene expression regulation via the recruitment of histone deacetylase proteins (50,51). Collectively, CdLS and disorders with CdLS-like features belong to a class of human diseases called ‘transcriptomopathies’ (45) or ‘disorders of transcriptional regulation (DTRs)’ (52). These observations suggest that alterations in chromatin remodeling lead to gene expression dysregulation that results in human disorders that can phenocopy or overlap with CdLS. However, the molecular basis underlying these overlapping phenotypes is still elusive. To gain insight into this matter, we investigated gene expression profiles of CdLS individuals, probands with clinical diagnosis of CdLS (but without variants in known genes) and CdLS-like subjects. We found a conserved pattern of gene dysregulation in these different cell lines. Interestingly, the c-MYC gene (hereafter MYC) was downregulated in all cell lines and was at the hub of many of the identified dysregulated pathways. Subsequent treatment with estradiol rescued MYC expression by modulating cohesin binding at the promoter region. Finally, MYC activity changed the expression of hundreds of genes leading to a reduction of oxidative stress and genome instability. Our data led to the identification of specific MYC-dependent dysregulated pathways in CdLS and CdLS-like cells. Restoring MYC expression could offer a possible therapeutic strategy for CdLS and related disorders.

Results

Gene expression is dysregulated in CdLS, CdLS with unknown mutation and CdLS-related disorders

Six CdLS lymphoblastoid cell lines carrying pathogenic variants in NIPBL, or SMC1A or SMC3 genes (Pt1–Pt6), five lymphoblastoid cell lines derived from subjects with a clinical diagnosis of CdLS (Pt10–Pt14) but without pathogenic variants (CdLS-unknown) in causative genes, three CdLS-like lymphoblastoid cell lines harboring variants in ANKRD11 or EP300 genes (Pt7–Pt9) and three control cell lines (Ctrl1–Ctrl3) were used for genome-wide assessment of transcription (Supplementary Material, Table S1). We have identified 1140 (755 up- and 385 downregulated), 1127 (582 up- and 545 downregulated) and 2517 (1363 up- and 1154 downregulated) differentially expressed genes (DEGs) in CdLS, CdLS-unknown and CdLS-like cell lines, respectively (Fig. 1A, Table 1, Supplementary Material, Tables S2–4). Transcriptome changes can be appreciated in volcano plots reported in Supplementary Material, Figure S1. Unsupervised sample clustering by principal component analysis (PCA) of all the expressed probe sets was able to separate most (82%, 9 out of 11) of the CdLS and CdLS-unknown probands from controls indicating these three groups have different gene expression patterns. CdLS-like subjects, instead, were spread out suggesting that their transcription profiles are divergent among them (Fig. 1B). Comparison of DEGs demonstrated that CdLS and CdLS-unknown cells shared 158 genes, CdLS and CdLS-like cells shared 242 genes and CdLS-like and CdLS-unknown cells shared 290 genes (Fig. 1A, Supplementary Material, Tables S5–7), whereas all three groups shared 241 genes (Fig. 1A, Supplementary Material, Table S8). All of them displayed only minor fold changing ranging from −2 to +2 when compared with control cell lines. In addition, it is worth noting that 239 out of 241 (99%) DEGs showed the same trend though to a different extent being 191 up- and 48 downregulated (Supplementary Material, Fig. S2).

Figure 1.

Figure 1

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Gene expression dysregulation in DTRs cell lines. (A) Venn diagram of DEGs. CdLS, CdLS-unknown and CdLS-like cells share 241 dysregulated genes. (B) Classification of probands by gene expression. Unsupervised sample clustering by PCA of dysregulated genes was able to distinguish most CdLS and CdLS-unknown probands from healthy subjects. (C) GO term enrichment analysis of biological processes that were significantly over represented when considering the 241 DEGs that were shared between CdLS, CdLS-unknown and CdLS-like groups.

Table 1.

Number of DEGs in CdLS, CdLS-unknown and CdLS-like cell lines

Cell lines Dysregulated genes Upregulated genes Downregulated genes
CdLS 1140 755 385
CdLS-like 2517 1363 1154
CdLS-unknown 1127 582 545
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Next, we used the Enrichr tool for classification by molecular function and biological process of the 241 dysregulated genes in common among the three groups. Most of the identified pathways are related to gene transcription regulation (Gene Ontology (GO):0010628, GO:1903508, GO:1903507, GO:0006355, GO:0010629 and GO:0045892) and protein synthesis and post-translational modification (GO:0016567, GO:0045727, GO:0032446, GO:32270, GO:0043687 and GO:31396) (Fig. 1C). RNA-sequencing (RNA-seq) data were validated in eight genes, ATF4, BCLAF1, CREBL2, FOXK2, MED21, NFATC1, SMARCAD1 and TRIM33 by quantitative RT-PCR experiments (Supplementary Material, Fig. S3). These genes were chosen because they were DEGs and are involved in gene transcription, a biological process that is affected in all cell lines irrespective of mutation status.

This finding indicates that gene expression dysregulation is not limited to CdLS but is also a feature of CdLS-related diseases, and all of them share specific dysregulated biological pathways.

MYC is downregulated by cohesin recruitment alteration in CdLS, CdLS-unknown and CdLS-like cells

The whole set of 241 DEGs was submitted to network analysis using MetaCore software. To establish a global functional pathway, the shortest path algorithm set to high trust interactions was selected. A short connectivity map was built between the genes (nodes) according to a precise scoring method involving a prioritized network database. This analysis predicted that about 55% of DEGs (132 out of 241) are related to MYC which is the most convergent hub directly or indirectly regulating most of the identified genes (Fig. 2, Supplementary Material, Fig. S4). Furthermore, RNA-seq data showed that MYC is significantly downregulated in all three groups, CdLS, CdLS-unknown and CdLS-like cells (Supplementary Material, Table S9). To evaluate the effectiveness of the RNA-seq data, we performed quantitative real-time polymerase chain reaction (qPCR). Results showed a general decrease in MYC expression in CdLS, CdLS-unknown and CdLS-like patients compared with control subjects (Fig. 3A). Since MYC plays a key role in cell cycle control, growth and proliferation, its expression is tightly regulated and the complexity of the MYC promoter reflects this role (53). It contains three exons, the first being a large non-coding exon and four distinct promoters, P0, P1, P2 and P3 (Fig. 3B). P0 transcripts start at multiple initiation sites; P1 and P2 are located at the 5′ end of exon 1, P3 maps between the exon 1 and 2. Exon 1 contains regulatory components as well as an enhancer element and a region that controls the elongation of nascent RNA transcripts (54–56). Previous work has shown that MYC transcription is positively regulated by cohesin in Drosophila, zebrafish and mouse (57–59). These observations prompted us to investigate whether a similar regulation exists in cell lines derived from our study cohort. To this aim, we used chromatin immunoprecipitation (ChIP) coupled with qPCR to examine cohesin binding in CdLS, CdLS-unknown and CdLS-like cells. We found no difference in RAD21 binding to the MYC insulator element (MINE) region of MYC locus, whereas the recruitment of cohesin at the first exon showed a significant decrease (P < 0.05) in all cell lines (Fig. 3C, Supplementary Material, Fig. S5).

Figure 2.

Figure 2

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MYC as the principal ‘hub’ of dysregulated genes. MetaCore network analysis of the 241 dysregulated gene results by using the shortest paths algorithm. MYC seems to be the most convergent hub directly or indirectly regulating most of the identified genes.

Figure 3.

Figure 3

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MYC dysregulation in DTRs. (A) MYC is downregulated in CdLS, CdLS-unknown and CdLS-like cell lines. (B) Schematic representation of human MYC locus. Solid boxes indicate translated regions. Primers were designed to regions A–C. ChIP experiments with an antibody against RAD21 were analyzed by qPCR with primer pairs B and C specific for the promoter region of MYC locus. Binding at each site was determined relative to primer A, where no RAD21 binding was predicted. The MYC locus length is not in scale. (C) ChIP-qPCR results showed that RAD21 co-localized to the promoter region of MYC gene, whereas bound cohesin was significantly reduced in exon 1 in all cell lines. Since no difference was found in control cell lines, data were pooled. Results shown are the averages of three independent experiments. Error bars represent standard error. *P < 0.05.

Altogether these results indicate that MYC is downregulated and represents a convergent hub lying at the center of dysregulated pathways.

MYC expression rescued by β-estradiol treatment

Because we found that MYC was downregulated in our patients and MYC is an estrogen-responsive gene, we next sought to determine if the treatment with estradiol was able to rescue its expression level. Since CdLS is characterized by genome instability and high level of oxidative stress (39,60), we performed this treatment on CdLS cells to investigate the effect of MYC rescue on those markers of CdLS. Results showed that MYC expression significantly increased following 1 μm estradiol treatment in CdLS cells (Fig. 4A). In addition, ChIP experiments using chromatin from estradiol-treated cells revealed that RAD21 binding showed a significant increase at the first exon of MYC locus (Fig. 4B). Next, we investigated the effect of estradiol treatment on gene expression by RNA-seq. We found 603 DEGs, 380 up- and 223 downregulated (Supplementary Material, Tables S10–11). Their fold change ranged from −3.8 to 4.3. Of note, 8 out of 10 top 10 representative pathways were related to transcription regulation, GO:1903508, GO:0006366, GO:0045892, GO:0010628, GO:0045944, GO:0006355, GO:0045893, GO:0006357 (Fig. 4C). RNA-seq data were validated by qPCR (Supplementary Material, Fig. S6). CdLS and estradiol-treated CdLS cells shared 31 genes (Supplementary Material, Fig. S7A); 33% of them (11 out of 31) reversed their expression level, whereas the remaining genes maintained the same trend though to a different extent (Supplementary Material, Fig. S7B). Then, we analyzed the effect of estradiol on the synthesis of cohesin subunits. We found that SMC1A, RAD21, STAG1 and STAG2 increased their synthesis level, though not significantly (Supplementary Material, Table S12).

Figure 4.

Figure 4

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Effects of estradiol treatment. (A) Hormonal treatments result in a significant increase of MYC expression in CdLS cell lines. (B) ChIP experiments with an antibody against RAD21 show increased cohesin binding at exon 1 of MYC gene following estradiol treatment. Binding at both B and C regions (Fig. 3B) was determined relative to primer A, where no RAD21 binding was predicted. (C) GO term enrichment analysis of biological processes that were significantly over represented shows that most dysregulated pathways are related to gene transcription control. (D) Protein carbonyl content, as marker of oxidative stress, was measured in both CdLS and control cells 24 h after the estradiol treatment. (E) The level of H2AX foci, as indicator of genome instability, decreases in CdLS cells following 24 h of hormonal treatment. Results shown are the averages of three independent experiments. Error bars represent standard error. *P < 0.05.

Previously we showed that CdLS cells display high level of both oxidative stress and genome instability (38–40). Therefore, we investigated the effects of estradiol on those cellular markers. The measurements of the levels of protein carbonyls (Fig. 4D) and H2AX foci (Fig. 4E), markers of oxidative stress and genome instability respectively, showed a significant decrease in all CdLS cell lines.

These observations indicate that MYC expression is rescued by estradiol treatment possibly through an increase in cohesin binding at the first promoter of the MYC locus. As a consequence, this leads to changes in gene expression, which in turn results in low levels of oxidative stress and genome instability.

Discussion

CdLS is the most common disease of a group of multiorgan system developmental syndromes collectively called DTRs. CdLS is genetically heterogeneous with pathogenic variants in seven genes, NIPBL, SMC1A, SMC3, HDAC8, RAD21, BRD4 and ANKRD11 resulting in a CdLS phenotype (61). Moreover, probands with CdLS-like phenotypes have been found to harbor variants in chromatin-associated factors other than cohesin genes including KBG and RSTS (3,43–47). These observations indicate that distinct disorders may share a common etiopathogenetic molecular mechanism. To gain insight into this issue, we performed RNA-seq analysis of CdLS, CdLS-like and CdLS-unknown probands. We found all cell lines showed gene expression dysregulation. The three groups shared 241 genes, 191 were up- and 48 were downregulated and 2 genes displayed different expression among the groups. Their fold change ranged from −2 to +2. These results suggest that chromatin remodeling genes may play the dual role of activator and repressor in gene transcription consistent with previous observations that cohesin activates the expression of some genes and inhibits the transcription of others (36,37,62). Furthermore, their small fold change indicates that CdLS and CdLS-like phenotypes are likely due to modest cumulative alterations in gene expression.

The transcriptome profiles allowed us to identify specific pathways that were dysregulated in our cohort most significantly involving gene transcription regulation, protein synthesis and post-translational modification.

Network interaction analysis permitted us to highlight the key role of MYC as a convergent hub that directly or indirectly regulates most of the dysregulated genes. MYC is a transcription factor that contributes to the swift up- and downregulation of about 15% of human genes and in turn is thought to orchestrate the plethora of transcriptional changes that foster cell growth and proliferation (63–66). We found that MYC is downregulated in all cell lines, CdLS, CdLS-like and CdLS-unknown. In addition, the occupancy of cohesin diminished at the first exon of the MYC locus. This observation is particularly interesting because cohesin is required for the activation of MYC and the first exon contains domains and regulatory elements that are important in the control of its expression (56,67–69). Our finding supports the notion that MYC is positively regulated by cohesin (40,57,69) and indicates that alterations in the promoter region cause MYC dysregulation, which in turn affects the expression of downstream genes leading to the gene expression dysregulation observed in CdLS and CdLS-like cells. It is likely that changes in MYC expression could have a large impact on transcription, raising the interesting possibility that a large number of dysregulated genes in DTRs are targets of MYC (Fig. 5A). This is supported by the findings that 99% of dysregulated genes showed the same trend in all cell lines.

Figure 5.

Figure 5

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MYC expression and CdLS cells. (A) MYC is downregulated in CdLS cells. In addition, the recruitment of cohesin decreases at the P1 promotor region in CdLS cells. As a consequence, hundreds of genes targeted by MYC are dysregulated. This phenomenon may contribute to the CdLS phenotype characterized by genome instability, premature aging and oxidative stress. (B) Estradiol treatment restores MYC expression through increased cohesin binding at the P1 region. This causes a change in gene expression, leading to decreased genome instability and oxidative stress.

Consistent with previous results (69,70), we found that estradiol treatment increased MYC expression. Furthermore, cohesin occupancy showed a significant increase at the first exon of MYC locus, whereas no difference was found at the MINE region. These data would suggest that cohesin regulates MYC transcription through the P1 promoter binding site, whereas MINE appears to be dispensable for the regulation of MYC expression following estradiol treatment. As a consequence of MYC rescue, we found changes in hundreds of genes. Thirty-one genes were in common between CdLS and estradiol-treated CdLS cells. Interestingly, 33% of them reversed their expression level. This subset of genes is involved in many biological processes affected in CdLS such as gene transcription (MED13 and ZNF395), energy production and oxidation/reduction (DHRS3 and ESRRA), cell growth and proliferation (FABP3, MAD2L1BP and RASA1) trafficking of proteins to either the cell membrane, or subcellular compartments (ABCA5, ATP8B4 and SORT1) and cytoskeletal remodeling (EPS8L2 and SYNPO). Interestingly, cohesin subunits showed an increase in their level of expression. Recent studies have revealed that specific structures play important roles in gene control. During gene activation, transcription factors bind enhancer elements and regulate transcription from the promoters of nearby genes through physical contacts that involve looping of DNA between enhancers and promoters (71,72). It is thought that this process is mediated by the cohesin (73). We propose that estradiol treatment results in new cohesin synthesis and its binding to the P1 promoter allows DNA looping and transcription of the MYC gene. In addition, estradiol treatment was able to protect cells from DNA damage and reduce the level of oxidative stress (Fig. 5B). This observation is interesting because it is well-known that oxidative stress and genome instability play a part in senescence and neurodegeneration (74–76).

The growing knowledge about the cellular and molecular basis of DTRs have laid the foundation for potential therapeutic options. In vitro treatments with antioxidant drugs, L-leucine or lithium chloride improve specific features of CdLS cell lines (61). Our data have potential clinical implications for the treatment of DTRs. Targeting MYC by estradiol treatment could reduce global transcription disturbance in those syndromes, mitigating the effect on genome instability, oxidative stress and premature aging which collectively contribute to phenotypes. Obviously, we are aware that it would have to be a very fine balance since overexpression of MYC may be oncogenic.

In summary, we propose that MYC downregulation is responsible for the gene expression dysregulation observed in CdLS and CdLS-like syndromes. Probably shared phenotypes such as cognitive impairment, growth impairment, microcephaly, thin upper lip and synophrys depend on MYC activity that appears to be a central regulator of growth and development by transcriptional control of multiple pathways.

Finally, restoring MYC expression by estradiol treatment offers a therapeutic option for future treatment of patients with CdLS and CdLS-like phenotype. This notion is further supported by the observation that a girl carrying a pathogenic variant in NIPBL gene was treated with recombinant human growth hormone. This treatment led to a height gain of 1.6 SD score over 8 years (77). Altogether, these observations suggest that hormonal therapy has the potential to ameliorate the developmental phenotype ofCdLS.

Materials and Methods

Cell culture

Lymphoblastoid cell lines were grown in RPMI containing 10% fetal calf serum, penicillin (100 U/ml), streptomycin (0.1 mg/ml) and 1% L-glutamine. We analyzed six CdLS lymphoblastoid cell lines derived from six unrelated probands carrying pathogenic variants in either the NIPBL or the SMC1A or SMC3 gene (Pt1–Pt6) and three CdLS-like lymphoblastoid cells harboring variants in ANKRD11 or EP300 gene (Pt7–Pt9). All CdLS and CdLS-like cases have been previously described (40,47,78–80). In addition, we analyzed five lymphoblastoid cell lines derived from probands with clinical diagnosis of CdLS (Pt10–Pt14) but without variants in known genes, whereas three cell lines, gender and ethnicity-matched, were used as control (Ctrl1–Ctrl3). Samples are listed in Supplementary Material, Table S1 with a detailed description.

Ethics approval

Approval was granted by the Ethics Committee (Protocol Number 130) and IRB-approved protocol of informed consent at the Children’s Hospital of Philadelphia. Research was conducted in accordance with the principles of the Declaration of Helsinki.

RNA-sequencing

All 17 cell lines were processed for RNA-seq analyses as previously described (37,39). Briefly, library preparation was obtained using the TruSeq Stranded mRNA Sample Prep kit (Illumina). Libraries and RNA samples were quantified using the Qubit 2.0 Fluorometer (Invitrogen) and the quality was tested using the Agilent 2100 Bioanalyzer RNA Nano assay (Agilent). Libraries were sequenced on single-end mode on HiSeq 2500 (Illumina). The CASAVA 1.8.2 version of the Illumina pipeline was used to process raw data for format conversion and de-multiplexing. To avoid low-quality data, adapters were removed by Cutadapt 1 and lower quality bases were trimmed by ERNE. For the analysis of DEGs, the quality-checked reads were processed using the TopHat version 2.0.0 package (Bowtie 2 version 2.2.0) as FASTQ files. The human reference genome GRCh37/hg19 was used to map reads. Only protein-coding genes were considered, and gene level expression values were determined by fragments per kilobase million (FPKM) mapped. All genes with FPKM > 1 were designated as expressed and analyzed with an established P-value < 0.05.

Pathway analysis and function

DEGs were analyzed for biological processes using the Enrichr tool (https://maayanlab.cloud/Enrichr/). Network interactions was investigated by MetaCore software version 21.1 (http://www.genego.com).

Cohesin binding at MYC locus by ChIP-qPCR

ChIP assays were performed as previously described (40) with minor modifications. Briefly, 107–108 cells were crosslinked with 1% formaldehyde for 15 min and quenched with 125 mM glycine. Pellets of cells were incubated with lysis buffer 1 (50 mM HEPES-KOH, pH 7.5, 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% NP-40 and 0.25% Triton X-100), then lysis buffer 2 (10 mM Tris–HCl, 100 mM NaCl and 1 mM EDTA) and sonicated in lysis buffer 3 (10 mM Tris–HCl, 100 mM NaCl, 1 mM EDTA, 0.1% sodium deoxycolate and 0.5 sarkosyl) to obtain a sheared chromatin of lengths of between 500 and 200 base pairs. Each sample was incubated with Dynabeads protein A (Invitrogen) previously bound with 10 μg of RAD21 (Bethyl Laboratories, A300-080A) antibody. Mouse IgG (Sigma) was used as negative control. Next, the beads were washed with low salt buffer (20 mM Tris–HCl, pH 8, 150 mM NaCl, 0.5 mM EDTA, 0.1% SDS, 1% Triton X-100), high salt buffer (20 mM Tris–HCl, pH 8, 500 mM NaCl, 0.5 mM EDTA, 0.1% SDS, 1% Triton X-100) and RIPA buffer (50 mM HEPES-KOH, pH 7.5, 0.5 mM EDTA, 10% NP-40, 0.7% sodium deoxycolate and 0.5 M LiCl) and eluted overnight at 65°C. The elutes were incubated with proteinase K and DNA was extracted with phenol–chloroform, followed by purification with QIAquick Purification Kit (Qiagen). For each cell line, three independent ChIP assays were carried out and analyzed by qPCR. Each sample was run in duplicate and repeated three times. Specific primers (listed in Supplementary Material, Table S13) were used to assay the relative enrichment for either the promoter or the first exon of MYC gene. The results are expressed as a fold enrichment relative to A region of MYC locus where no RAD21 binding was predicted.

cDNA synthesis and qPCR

Total RNA was extracted via the RNAeasy Mini-kit (Qiagen) and cDNA was synthesized with SuperScript™ II reverse transcriptase using oligo-dT (Invitrogen). qPCR was performed using Rotor Gene 3000 (Corbett). qPCR reactions were run in triplicate and normalized with respect to HPRT. Primers were designed using the national center for biotechnology information tool (https://www.ncbi.nlm.nih.gov/tools/primer-blast). Primers used in qPCR experiments are listed in Supplementary Material, Table S14.

Estradiol treatment

For hormonal deprivation, cells were cultured in phenol red-free media supplemented with 10% fetal bovine serum stripped with dextran-treated charcoal (Life Technologies). Cells were treated with 1 μm estradiol (Sigma) for 30 min.

Oxidative stress measurement

Protein carbonyl content was assayed with enzyme-linked immunosorbent assay (ELISA) after derivatization with 2,4-dinitrophenylhydrazine using Protein Carbonyl ELISA kit (Cell Biolabs) following the manufacturer’s instructions.

γ-H2AX foci

Cells were fixed in 2% paraformaldehyde, permeabilized in 0.2% Triton X-100 and blocked in PBS with 1% BSA. Then, cells were incubated with primary antibody-H2AX (Trevigen), and thereafter incubated with Alexa Fluor 488-conjugated goat anti-rabbit secondary antibody (Molecular Probes). γ-H2AX foci were scored manually from at least 200 cells by Leica DM2500 microscope.

Statistics

Data were analyzed by Student’s t-test. P-values of < 0.05 were considered statistically significant.

Supplementary Material

Supplementary_Material_ddab348
Click here for additional data file. (10.6MB, pdf)

Acknowledgements

We thank the Telethon Network of Genetic Biobanks that provided us with specimen.

Conflict of Interest statement. None declared.

Contributor Information

Maria M Pallotta, Institute for Genetic and Biomedical Research (IRGB), National Research Council (CNR), 56124 Pisa, Italy.

Maddalena Di Nardo, Institute for Genetic and Biomedical Research (IRGB), National Research Council (CNR), 56124 Pisa, Italy.

Patrizia Sarogni, Institute for Genetic and Biomedical Research (IRGB), National Research Council (CNR), 56124 Pisa, Italy.

Ian D Krantz, Roberts Individualized Medical Genetics Center, Division of Human Genetics, The Department of Pediatrics, The Children's Hospital of Philadelphia, and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA.

Antonio Musio, Institute for Genetic and Biomedical Research (IRGB), National Research Council (CNR), 56124 Pisa, Italy.

Data availability

Short reads have been deposited into NCBI Sequence Read Archive under BioProject accession PRJNA726869.

Funding

Fondazione Pisa (120/16) to A.M, X01 HL145697, R03 HD099530 (NIH/NICHD) and funding from Cool Cars for Kids, Inc. to I.D.K.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary_Material_ddab348
Click here for additional data file. (10.6MB, pdf)

Data Availability Statement

Short reads have been deposited into NCBI Sequence Read Archive under BioProject accession PRJNA726869.

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