Intron 1-Mediated Regulation of EGFR Expression In EGFR-Dependent Malignancies is Mediated by AP-1 and BET Proteins

Abstract

The epidermal growth factor receptor (EGFR) is overexpressed in numerous solid tumors and is the subject of extensive therapeutic efforts. Much of the research on EGFR is focused on protein dynamics and downstream signaling, however few studies have explored its transcriptional regulation. Here, we identified two enhancers (CE1 and CE2) present within the first intron of the EGFR gene in models of glioblastoma (GBM) and head and neck squamous cell carcinoma (HNSCC). CE1 and CE2 contain open chromatin and H3K27Ac histone marks, enhance transcription in reporter assays, and interact with the EGFR promoter. Enhancer genetic deletion by CRISPR/Cas9 significantly reduces EGFR transcript levels, with double deletion exercising an additive effect. Targeted repression of CE1 and CE2 by dCas9-KRAB demonstrates repression of transcription similar to that of genomic deletion. We identify AP-1 transcription factor family members in concert with BET bromodomain proteins as modulators of CE1 and CE2 activity in HNSCC and GBM through de novo motif identification and validate their presence. Genetic inhibition of AP-1 or pharmacologic disruption of BET/AP-1 binding results in downregulated EGFR protein and transcript levels, confirming a role for these factors in CE1 and CE2. Our results identify and characterize these novel enhancers, shedding light on the role that epigenetic mechanisms play in regulating EGFR transcription in EGFR-dependent cancers.

Implications:

We identify critical constituent enhancers present in the first intron of the EGFR gene, and provide rationale for therapeutic targeting of EGFR intron 1 enhancers through perturbation of AP-1 and BET in EGFR-positive malignancies.

Introduction

Mammalian cells contain thousands of transcriptional control elements known as enhancers responsible for the regulation of gene expression (1). Enhancers contain open chromatin (2) and are marked by specific chromatin modifications, including mono-methylation of histone H3 at lysine 4 (H3K4me1) and acetylation of histone 3 at lysine 27 (H3K27Ac) (3). Active enhancers are typically identified by a specific enrichment of H3K27Ac (4) and contain high levels of enhancer-associated transcription factors (TF’s) (5) that are often cancer-specific (6). The activator protein-1 (AP-1) family of oncogenic transcription factors activates transcription of different genes through homo- and hetero-dimers of Jun, Fos, and ATF family members (7) and has been shown to be critical for maintenance of GBM transcriptional heterogeneity (8). These factors bind to and modulate enhancer activity in combination with other chromatin associated proteins including BRD4 (9,10), the YAP/TAZ/TEAD complex (11,12), and the SWI/SNF (BAF) complex (13).

The epidermal growth factor receptor (EGFR) is a transmembrane tyrosine kinase whose downstream signaling pathways modulate a wide range of cellular activities, including growth, migration, and survival (14). EGFR is frequently overexpressed in a variety of cancer types, including cancers of the head and neck (HNSCC) and glioblastoma (GBM) (15). Over expression of EGFR is detectable in as much as 84% of HNSCC tumors, with mutation and/or amplification occurring in approximately 31% of these tumors (16), suggesting high EGFR protein levels are driven by transcriptional control mechanisms in HNSCC. GBM possesses a stronger correlation between EGFR copy number and expression, with mutation and/or amplification occurring in approximately 46% of GBM, over 90% of which overexpress the protein (17). Recent large-scale analysis of cancer epigenomes identified a significant relationship between somatic copy number alterations (SCNA’s) and enhancer expression, with the most significant increases in enhancer expression occurring in tumors which have high aneuploidy and high mutation-load (18). HNSCC and GBM have high SCNA frequency (19) and a high frequency of EGFR gene alterations (20), indicating epigenome hyperactivity may play a role in overexpression of EGFR.

In spite of the prevalence of EGFR dependency in solid tumors, few studies have attempted to elucidate the mechanisms of transcriptional control of the gene. Early studies identified cis-acting elements which may regulate EGFR including CA dinucleotide repeats (21), intron 1 DNase I hypersensitive sites (22), and cooperative promoter-upstream and intron 1 enhancers (23). Lack of utilization of next generation sequencing (NGS) techniques limit the scope of these studies and argued for a larger breadth of analysis. Recently, EGFR super enhancers were identified in various cancer types including cervical, glioma, and lung (8,10,24–26), however systematic mapping of these super enhancers was lacking. The increased interest in enhancer-mediated expression of EGFR strongly argues for a clearer understanding of the regions critical for enhancer function at EGFR and the transcription factors which mediate these effects.

In this study we interrogated the transcriptional regulation control of the EGFR locus. We utilized cell line models of solid tumors which commonly overexpress EGFR to identify the cis- and trans- acting factors involved in the transcriptional control of the EGFR gene and identified two critical constituent enhancers located within intron 1 of EGFR. We characterized these enhancers by mapping their domains with luciferase reporter assays, chromatin interaction assays, and CRISPR/Cas9-mediated genetic perturbation. Finally, genome-wide motif analysis implicated AP-1 TF and BET (Bromodomain and Extraterminal domain) protein family members whose presence and activity in EGFR intron 1 were further functionally validated. The results revealed that two constituent enhancers regulate EGFR transcriptional control, proposing an epigenetic regulation of the EGFR gene in cancer.

Materials and Methods

Cell Culture.

GBM cell lines U87 (RRID:CVCL_0022), T98G (RRID:CVCL_0556), LN229 (RRID:CVCL_0393) were purchased from ATCC. LNZ308 (RRID:CVCL_0394) was provided by Dr. Erwin Van Meir (Emory University, Atlanta, GA). SF767 (RRID:CVCL_6950) was provided by Dr. Mitch Berger (UCSF Brain Tumor Center, San Francisco, CA). Head and neck cell lines HN12 (RRID:CVCL_5518), Cal27 (RRID:CVCL_1107) and Detroit562 (RRID:CVCL_1171) (provided by Dr. Silvio Gutkind, UCSD Moores Cancer Center, San Diego, CA) were maintained in DMEM (Hyclone, #SH30022.01) supplemented with 10% fetal bovine serum (Atlanta Biologicals, #S12450) and 1% penicillin-streptomycin (Gibco, #15140-122) and grown as adherent cultures. GBM neurosphere cell lines GSC23 (RRID:CVCL_DR59, Dr. Fred Lang, University of Texas MD Anderson Cancer Center, Houston, TX) and TS576 (Dr. Cameron Brennan, Memorial Sloan Kettering Cancer Center, New York, NY) were maintained in DMEM/F12 (Gibco, #11320-033) supplemented with B27 supplement (Gibco, #12504-044) and 1% penicillin-streptomycin and grown in suspension. Mycoplasma testing was performed with the PlasmoTest kit (InvivoGen, #rep-pt1) and found to be negative. All experiments are performed within 10 passages of the original frozen stock or post-manipulation.

Luciferase reporter assays.

DNA fragments tested in the luciferase reporter assay were cloned from human genomic DNA (Promega, #G3041). PCR products were cloned downstream of firefly luciferase in the pGL4.24 minimal promoter vector (Promega, #E8421) using the SalI (NEB, #R3138S) site. Constructs were sequence confirmed by Sanger sequencing using the pGL4.24-R primer. pMIEG3-JunDN (RRID: Addgene_40350) and 3xAP1pGL3 (RRID:Addgene_40342) were gifts from Alexander Dent. pMIEG3-Empty was created by removing the JunDN sequence by EcoRI digestion. For each transfection reaction, 100ng control plasmid expressing Renilla luciferase (Promega, #E2241) and 1μg Firefly luciferase construct were co-transfected with Lipofectamine 2000 (ThermoFisher, #11668030) into 2 x 10⁵ cells in a 12-well plate well. After 24 hours, cells were collected in 1X PLB. Luciferase activity was measured by the Dual-Luciferase Reporter Assay System (Promega, #E1910) on a Tecan Spark 10M with injection control. Transfection efficiency was controlled for by dividing Firefly luminescence by Renilla luminescence, and final activity was normalized to a negative control.

Quantitative real-time PCR.

RNA was extracted with the RNeasy Plus kit (Qiagen, #74134) according to the manufacturer’s instructions. Reverse transcription of mRNA was performed using 1μg RNA with the iScript Reverse Transcription Supermix (BioRad, #1708841). For real-time PCR analysis, 5μl of cDNA (50ng of starting RNA) was amplified per reaction using the iTaq Universal SYBR Green Supermix (Bio-Rad, #1725124) and the Bio-Rad CFX96 qPCR system.

Chromatin conformation capture (3C).

The experiment was performed as described (27) with the following modifications. Nuclei were treated with 1000U EcoRI (NEB, #R3101S) at 37°C overnight. 100U T4 enzyme (NEB, #M0202S) was added to digested nuclei and incubated at 16°C for 4 hours. Another 100U T4 enzyme was added and nuclei were incubated with rotation at 4°C overnight. 150ng of ligated DNA was quantified in triplicate by TaqMan real-time PCR using the PrimeTime Gene Expression Supermix (IDT, #1055772). Control 3C template was generated by using two bacterial artificial chromosomes (BACs) encompassing the entire EGFR gene, RP11-159M24 and RP11-148P17, were purchased from the Children’s Hospital Oakland Research Institute (CHORI). Equimolar of the two BACs were digested with EcoRI and ligated. The ligation product from BAC control was used for normalization. The relative interaction frequency was calculated as: 2^{Ct (BAC)-Ct (3C)}.

Guide RNA design.

Guide RNAs were designed using the MIT CRISPR Design website (http://crispr.mit.edu). To minimize potential off-target effects of guides, only high-score guide RNAs (score >80) were used. Guide RNA’s were annealed and diluted 1:200 in ddH2O and used for downstream applications.

CRISPR/Cas9-mediated genomic deletion.

Guide RNAs were cloned into pX330-BFP (from Dr. Tim Fenton) for upstream guides or pX458-GFP (Addgene, Plasmid #48138) for downstream guides. Products were sequence verified by Sanger sequencing with the hU6-F primer. Constructs were co-transfected with Lipofectamine 3000 (ThermoFisher, #L3000015) into 4.5 x 10⁵ cells in a 6-well plate. After 24 hours cells were collected and the top 1% of BFP+/GFP+ cells were sorted using the SH800S Cell Sorter (Sony Biotechnology). Single cells were plated in 96 well plates and grown for 2-3 weeks. Single clones were screened using PCR, and a minimum of 2 homozygous clones were mixed at equal ratios and used for downstream analysis.

Enhancer silencing by dCas9-KRAB.

SF767 and HN12 cells were transduced with Lenti-dCas9-KRAB-blast (from Dr. Paul Mischel) and selected with 10μg/ml blasticidin (Gibco, #A1113903) for 72 hours post transduction. Guide RNAs were cloned into the lentiGuide-Puro vector (Addgene, Plasmid #52963) and transformed into Stbl3 bacteria. Constructs were confirmed by Sanger sequencing using the hU6-F primer. Constructs were transduced individually into cells expressing dCas9-KRAB and selected with 1μg/ml puromycin. After assessing EGFR transcript levels by RT-qPCR, one highly effective CE1 guide-expressing cell line was selected for double gRNA expression and transduced with the complementary CE2 guide.

Cell growth analysis.

5x10² HN12, U87, or Cal27 cells or 1x10⁴ SF767 cells were seeded in 5 replicate black, clear bottom 96 well plate in 6 replicate wells in complete media. After 24 hours, complete media was removed and 100μl of 10μg/ml blasticidin and 1μg/ml puromycin in DMEM + 0.5% FBS was added to each well. Baseline luminescence was measured at day 1 with the ATPlite 1step Luminescence Assay System (PerkinElmer, #6016731) on a Tecan Spark 10M. Luminescence measurements were obtained at every other day for 9 days and plotted using GraphPad Prism.

Subcutaneous tumor growth.

1x10⁶ HN12 parental (n = 5) or CE1^−/−CE2^−/− (n = 4) cells were injected into the right flank of nude mice. Tumors were measured by caliper every 4 days until visible tumors formed and then measured every day until the appearance of necrosis or the volume reached 500mm³. The animal studies are approved by UCSD IACUC according to the NIH guidelines.

siRNA transfection.

1x10⁵ SF767 or 5x10⁵ HN12 cells were seeded in 12 well plates and grown overnight. siRNA’s were transfected into each well with Lipofectamine 2000 in serum free and antibiotic free DMEM. Media was changed to complete media 6 hours later. Samples were collected in SDS sample buffer 48-72 hours later. siRNA’s used for this study include BRD2 (Ambion, #s12070), BRD3 (Ambion, #s15544), BRD4 (Ambion, #s23902), and scramble control (Invitrogen, #12935-300).

JQ1 Treatment.

SF767 or HN12 cells were treated with 0.5μM JQ1 dissolved in DMSO (MedChemExpress, #HY-13030) for 24 hours. Vehicle control samples were treated with equal volume DMSO for 24 hours.

Western blotting.

Protein samples were collected in SDS sample buffer, separated using gel electrophoresis and transferred via wet transfer onto a PVDF membrane. The membrane was blocked with 5% milk in TBST and probed with primary antibodies at 1:1000 dilution overnight at 4°C and secondary HRP antibodies at 1:2000 for 1 hour at RT. Signal was assessed via chemiluminescence with the SuperSignal West Pico PLUS substrate (ThermoFisher, #34580) and visualized on a ChemiDoc MP system (Bio-Rad). Anti-Cas9 antibody (Cell Signaling, #14697), anti-β-actin (Sigma, #A3854), anti-c-Jun (Cell Signaling, #9165S), anti-c-Fos (Santa Cruz Biotechnology, #sc-52), anti-HA-HRP (Santa Cruz Biotechnology, #sc-805), anti-BRD4 (Active Motif, #39909), anti-BRD3 (Santa Cruz Biotechnology, #sc-515729), anti-BRD2 (Cell Signaling, #5848S), and c-Myc (Cell Signaling, #9402) and anti-EGFR (BD Biosciences, #610017) were used for analysis.

Chromatin immunoprecipitation.

Chromatin immunoprecipitation was performed as described previously (28) with the following modifications. Chromatin was sheared in diluted lysis buffer to 200-500bp using a Covaris M220 Focused-Ultrasonicator with the following parameters: 10 minutes, peak incident power 75, duty factor 10%, 200 cycles/burst. Antibodies for ChIP were obtained from commercially available sources: anti-H3K27Ac (Active Motif, #39133), anti-BRD4 (Active Motif, #39909), anti-c-Jun (Cell Signaling, #9165T), anti-c-Fos (Santa Cruz Biotechnology, #sc-166940), anti-BRD3 (Santa Cruz Biotechnology, #sc-515729), and anti-BRD2 (Cell Signaling, #5848S). 5% of the chromatin was not exposed to antibody and was used as control (input). For ChIP-qPCR analysis DNA quantity for each ChIP sample was normalized against input DNA. For ChIP-seq samples, after DNA purification ChIP-seq DNA libraries were prepared with either the TruSeq ChiP Library Prep Kit (Illumina, #IP-202-1012) or the Accel-NGS 2S Plus DNA Library kit (Swift Bioscience, #21024) and sequenced using 75 bp single-end sequencing on an Illumina Hi-seq 4000.

ATAC-seq.

Approximately 50,000 permeabilized nuclei were transposed using Tn5 transposase (Illumina, #FC-121-1030) as described previously (29). Libraries were amplified using NEBNext High-Fidelity 2X PCR Master Mix (NEB, #M0541) with primer extension at 72°C for 5 min, denaturation at 98°C for 30s, followed by 8 cycles of denaturation at 98°C for 10s, annealing at 63°C for 30s and extension at 72°C for 60s. Each library was size selected and sequenced on an Illumina NextSeq500 or HiSeq4000 to a depth of ≥ 20 million usable reads pairs. Sequencing runs that did not meet the read pair threshold were sequenced again, and all replicates were pooled for analysis. Tracks shown in figures 1A and supplemental figure 2 are pooled from two biological replicates.

Figure 1.

Chromatin landscape of wild-type EGFR. A: IGV snapshots showing H3K27Ac ChIP-seq (dark) and ATAC-seq (light) read densities at the EGFR locus in GBM and HNSCC cell lines. B: EGFR expression in 7 GBM and 3 HNSCC cell lines were analyzed by RT-qPCR. EGFR transcript level was first normalized to GAPDH and subsequently calculated as fold change relative to U87. C. Total aligned H3K27Ac ChIP-seq reads were calculated and plotted against the relative EGFR expression fold change. The relationship was analyzed using Spearman’s rank order correlation.

Statistical Analysis.

Correlative statistical analysis was performed on the relationship between ChIP-seq read count data and relative luciferase expression, EGFR expression, or relative interaction frequency using Spearman’s Rank-Order Correlation. Data from chromosomal interaction, CRISPR/Cas9 deletion, cell proliferation, and ChIP-qPCR enrichment were compared, and statistical analysis was performed using a Student’s t test.

Oligo Sequences.

All DNA oligo (primer, gRNA) sequences are listed in Supplementary Table S2.

Data Access.

All raw and processed sequencing data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE128275. Accession numbers for publicly available data accessed are listed in Supplementary Table S1.

Results

EGFR Intron 1 Contains Open Chromatin Regions Containing Histone Marks Indicative of Enhancers

To gain further insight into the mechanisms responsible for EGFR transcriptional control in HNSCC and GBM we performed ChIP-seq and ATAC-seq in 7 GBM and 3 HNSCC cell lines with non-amplified EGFR copy numbers and varying levels of EGFR activation. Overlay of IGV tracks of all 10 cell lines showed conservation of H3K27Ac intensity and open chromatin throughout intron 1, indicating the presence of enhancers in these regions (Fig. 1A). Since super enhancers (SE) are defined as large clusters of transcriptional enhancers that drive expression of genes that define cell identity, and are often found at oncogenes (30) we identified SE’s using the ROSE (Rank Ordering of Super-Enhancers) algorithm (6,31) (Supplementary Fig. 1A). Using this algorithm, we discovered cell-line specific SE’s in the first intron of EGFR, many of which rank highly in several of our cell lines (Supplementary Fig. 1B). Interestingly, the location and size of these SE’s varied and were dependent upon the local enrichment of H3K27Ac ChIP-seq signal.

To determine if presence of putative enhancers in EGFR intron 1 was predictive of EGFR expression we first measured EGFR transcript in each GBM and HNSCC cell line (Fig. 1B). Due to cell line-specific presence and location of predicted EGFR super enhancers, we used total number of intron-1 mapped H3K27ac ChIP-seq reads as a measure of enhancer presence and plotted these values against the fold change in EGFR expression. Analyzing the relationship by Spearman’s correlation showed a highly significant correlation (Fig. 1C). Together, these results identify regions containing characteristics of SE’s in the first intron of EGFR and suggests that presence of these putative enhancers is important for high levels of EGFR transcript.

Two Critical Constituent Enhancers Reside in the First Intron of EGFR

It has been reported previously that SE’s are congregations of active constituent enhancers (CE) (32). To determine which CE’s of the identified SE’s are active, we segmented regions which exhibited highly conserved H3K27Ac ChIP-seq and ATAC-seq signals into 2kb segments (Supplemental Fig. 2). Each segment was then measured for enhancer activity by in vitro bioluminescence (Fig. 2A). Regions which exhibited conserved luciferase expression included 1, 3, and 16-19. Interestingly, activity of segments 8 and 9 were HNSCC specific, while segments 1 and 3 were more glioma specific. Segments 16-19 consistently enhanced luciferase activity in both tumor models. Combining H3K27Ac presence by ChIP-seq, open chromatin accessible regions by ATAC-seq, and functional activity as defined by our luciferase system in both tumor types, we define two distinct CE’s. Specifically, we combined segments 1-3 into an approximately 6kb region which we have termed Constituent Enhancer 1 (CE1), and combined segments 16-19 into an approximately 8kb region which we have termed Constituent Enhancer 2 (CE2) (Fig. 2A). CE1 and CE2 reside in regions of conserved high levels of H3K27Ac, however other segments do not have associated H3K27Ac enrichment. We hypothesized that the specific enrichment of H3K27Ac at an enhancer segment would correlate to luciferase expression in the matched cell line. Indeed, plotting the normalized luciferase intensity against the average H3K27Ac read intensity (Fig. 2B and 2C) reveals a highly significant relationship (p < 0.001, Spearman’s correlation). These results define two conserved putative CE’s within EGFR intron 1 and establish a relationship between histone acetylation at these regions and enhancer activity as measured by in vitro bioluminescence.

Figure 2.

Identification of critical constituent enhancers in EGFR intron 1. A: (Top) Schematic of positioning of the enhancer segments in the pGL4.24 construct. (Bottom) Luciferase activity in GBM (cell lines left to right: U87, T98G, LN229, LNZ308, SF767, GSC23, TS576) and HNSCC (cell lines left to right: HN12, Cal27, Detroit562) cell lines after transfection with pGL4.24 constructs containing cloned fragments of EGFR intron 1. A negative control region 10kb downstream of the EGFR promoter was used for normalization. B-C: Relative luciferase expression for P1-20 was plotted against the average H3K27Ac read density for each individual segment in (left) GBM and (right) HNSCC. The relationship was analyzed using Spearman’s rank order correlation.

Significant Interactions Between CE1, CE2 and the EGFR Promoter

Enhancers typically make contact with one or more gene promoters through long-range interactions (30). To test if the predicted enhancer regions CE1 or CE2 interact with the EGFR promoter we performed a chromosome conformation capture (3C) assay. Primers were designed around the EcoRI sites in CE1 (F1 to F5) and CE2 (F6 to F10) and nearby the EGFR promoter (Fig. 3A). Since we hypothesized that an increased interaction frequency would correlate with increased transcript levels, we chose the cell lines with the highest EGFR expression levels in both tumor types (HN12/SF767) and compared them against a cell line with virtually no EGFR expression (TS576). Compared to TS576, in SF767 cells low levels of interaction with CE1 and CE2 were found; however, significantly stronger interactions were identified at F2 and F4 of CE1 and 4 out of 5 regions of CE2 in the HN12 cell line (Fig. 3B). These primers reside in highly acetylated regions in HN12 cells, thus we hypothesized there is a correlation between H3K27Ac intensity and interaction frequency. Correspondingly, we identified a significant correlation between H3K27Ac peak intensity and interaction frequency when comparing all three cell lines (Fig. 3C). Together, the data thus far indicates that CE1 and CE2 have characteristics ascribing them to active enhancers: surrounded by nucleosomes with high H3K27Ac, open chromatin, transcriptional enhancement, and interaction with a promoter.

Figure 3.

Enhancer-promoter interaction by chromatin conformation capture (3C). A: Schematic showing position of 3C primers relative to CE1 and CE2. 3C qPCR was done in combination with a forward primer in the EGFR promoter region. IGV tracks for H3K27Ac in HN12, SF767 and TS576 are shown for reference. B: Relative interaction frequency of each restriction fragment (F1-10) was calculated as described in the experimental procedures and was plotted against genomic location of the EcoRI restriction site. Significant differences in interaction are indicated for HN12 relative to control (TS576) (*p < 0.05, **p < 0.005, n = 3 independent experiments, Student’s t test). C: H3K27Ac read density at the primer site was plotted against the relative interaction frequency for all three measured cell lines. The relationship was analyzed using Spearman’s rank order correlation.

Deletion of CE1 and CE2 by CRISPR/Cas9 Results in Reduced EGFR Expression

To directly assess if CE1 and CE2 were essential for EGFR expression, we used the CRISPR/Cas9 system to delete CE1 (hg 38, chr7: 55,060,994-55,066,815) and CE2 (hg38, chr7: 55,127,646-55,135,347). To test how enhancer loss effects cells with different EGFR expression levels we made these deletions in two GBM cell lines and two HNSCC cell lines which had either high (SF767, HN12) or low (U87, Cal27) relative EGFR expression. Single enhancer deletions were generated with a dual-guide deletion strategy (Fig. 4A) and the deletion was confirmed by genotyping PCR (Fig. 4B). Compared to parental cell lines, EGFR transcript and protein was significantly decreased in each deletion (Fig. 4C). In those cell lines which express EGFR highly, CE1 deletion provided the strongest knockdown of EGFR transcript and protein, however U87 had the strongest effect in the CE2 knockout cell line. Cell-type specific differences in transcript levels between CE1 and CE2 indicate there may be differential utilization of either CE1 or CE2 in different cell lines, possibly due to cell line specific expression of transcription factors critical for EGFR enhancer activity.

Figure 4.

CRISPR/Cas9-mediated deletion of CE1 and CE2 in GBM and HNSCC cell lines reduces EGFR expression and suppresses proliferation. A: Schematic outlining the CRISPR/Cas9 deletion strategy. B: Genotyping PCR for (left) CE1 and (right) CE2. Homozygous parental (lanes 1, 2) and heterozygous deleted (lanes 3, 4) are shown as PCR controls. Homozygous enhancer deletion (lanes 5-12) is shown for clone mixtures. A minimum of 2 homozygous clones were combined for downstream analysis. C: (Top) EGFR expression in deleted cell lines were analyzed by RT-qPCR. EGFR transcript level was first normalized to GAPDH and subsequently calculated as fold change relative to parental. D: Genotyping PCR confirms presence of both deletions in clone mixtures. A minimum of 2 double-deleted homozygous clones were combined for downstream analysis. E: EGFR expression in double-deleted cell lines was analyzed by RT-qPCR. EGFR transcript level was first normalized to GAPDH and subsequently calculated as fold change relative to parental (Ctrl). F: Cell proliferation curves were generated by measuring ATP levels every two days over 9 days. Significance is measured relative to parental (Ctrl). G: Subcutaneous tumors were generated and tumor volume was measured over 21 days. n = 5 (Ctrl) 4 (CE1^−/−CE2^−/−) *p < 0.05. Volume was measured with the formula V = (W² × L)/2. H: Wild-type EGFR expression was rescued in double knockout cells by lentiviral transduction. Proliferation was measured by ATP levels every 2 days over 9 days. Significance is measured relative to parental (Ctrl) for knockout cells and relative to double knockout (CE1^−/−CE2^−/−) for wtEGFR rescued cells. C,E,H: Western blot for EGFR expression. β-Actin was used as a loading control. C,E-F,H: (*p < 0.05, **p < 0.005, ***p < 0.0005, n = 3 independent experiments, Student’s t test).

Previous studies have indicated partial redundant control of a gene by multiple CE’s within a single SE (32). To evaluate if there was a compensatory effect on EGFR transcription by either CE1 or CE2, we performed a second round of CRISPR/Cas9 editing on the homozygous edited populations (Fig. 4D). Compared to parental cell lines, EGFR transcript levels were significantly decreased with loss of both enhancers (Fig. 4E). Notably, the amplitude of EGFR transcript loss was greater in CE1^−/−+CE2^−/− when compared against CE1^−/− or CE2^−/− alone. EGFR transcript and protein loss corresponded to significant proliferation deficiencies in each cell line measured, notably most significantly in double deleted cell lines (Fig. 4F). In HN12 cells, this proliferation difference between parental and double knockout cells translates to a significant repression of tumor growth in a subcutaneous tumor model (Fig. 4G). Restoring EGFR protein by lentiviral transduction of wild-type EGFR in CE1^−/−+CE2^−/− cells results in significant rescue of proliferation in HN12 cells (Fig. 4H). Incomplete rescue of growth in these cells indicates CE1 or CE2 may be enhancing other genes important for cell growth. Together, these results demonstrate both cell type-specific CE utilization as well as a cooperative relationship between the CE1 and CE2 whereby double enhancer deletion results in more significant deleterious effects than single deletions alone.

Repression of H3K27Ac by dCas9-KRAB Decreases EGFR Expression

To eliminate the possibility of structural variation being the root cause of EGFR expression-loss in CRISPR/Cas9 deleted clones, we hypothesized that histone de-acetylation would be sufficient for EGFR transcriptional repression. dCas9-KRAB is known to recruit endogenous chromatin modifying complexes to de-acetylate histones (33), therefore to test our hypothesis we targeted a nuclease deactivated Cas9 (dCas9) protein fused to the Krüppel-associated box (KRAB) domain of Kox1 (34) with four CE1 and five CE2 gRNAs in HN12 (Fig. 5A) and SF767 (Supplementary Fig. 3A) cell lines.

Figure 5.

Targeting dCas9-KRAB to the CE’s decreases EGFR gene transcription and suppresses proliferation. A: (Left) H3K27Ac IGV track of HN12 cells showing the position of gRNA’s targeting the EGFR intron 1 enhancers and off-target (O-T) control. (Right) Western blot for dCas9-KRAB expression after transduction with lenti-dCas9-KRAB-blast. B: H3K27Ac enrichment at the targeted enhancer regions before and after dCas9-KRAB targeting was analyzed by ChIP-qPCR. Primers were designed around the targeted regions as well as a PCR negative control (Ctrl) from a H3K27Ac-negative region within EGFR intron 1. C: EGFR expression in dCas9-KRAB expressing cell lines was analyzed by RT-qPCR. EGFR transcript level was first normalized to GAPDH and subsequently calculated as fold change relative to off-target control. D: Cell proliferation curves were generated by measuring ATP levels every two days over 9 days. Significance is measured relative to O-T for knockdown cells and relative to double knockdown (CE1.4+2.4) for wtEGFR rescued cells. C-D: Western blot for EGFR expression. β-Actin was used as a loading control. B-D: (*p < 0.05, **p < 0.005, ***p < 0.0005, n = 3 independent experiments, Student’s t test)

To ensure successful targeting of dCas9-KRAB we confirmed de-acetylation at the targeted regions. Compared to an enhancer off-target (O-T) gRNA, the targeting of dCas9-KRAB resulted in significant decreases in H3K27Ac in HN12 cells (Fig. 5B). Additionally, we measured EGFR transcript and protein levels and observed significant decreases in transcript in 80% (8/10) of enhancer-specific targeted regions (Fig. 5C). Interestingly, targeting CE2 had an overall stronger repressive effect on EGFR transcript levels, with repression by gRNA targeting CE2.4 achieving a greater than 3-fold decrease in expression. We performed double dCas9-KRAB repression by adding a second gRNA (CE1.4 + CE2.4) and observed the most significant decrease in EGFR transcript and protein levels, achieving an 8-fold decrease in RNA expression compared to the off-target gRNA (Fig. 5C). In SF767 cells, dCas9-KRAB was expressed to lower levels than that of HN12 (Supplementary Fig. 3A) and correspondingly we saw less significant reductions in H3K27Ac (Supplementary Fig. 3B). Importantly, we still saw significant repression of EGFR transcript levels in 50% (5/10) of enhancer-specific targeted regions in SF767 (Supplementary Fig. 3C). In these cells there was no observable preference for CE2, however the strongest repression was again observed by combining CE1.4 and CE2.4.

Finally, the effect of dCas9-KRAB-mediated EGFR repression on cell proliferation was assessed by ATPlite assay. At low (0.5%) serum, the relative proliferation of the indicated EGFR-repressed cells was significantly inhibited (Fig. 5D, Supplemental Fig. 3D). Importantly, cell lines with stronger EGFR-repression exhibited reduced proliferation over time. Reintroducing high levels of wild-type EGFR by lentiviral transduction resulted in a rescue of the proliferation ability of double knockdown cells. These results indicate that EGFR transcriptional changes in enhancer deleted regions (Fig. 4) are not due solely to structural alteration within the first intron. Moreover, these results demonstrate that loss of H3K27Ac at the identified EGFR enhancers is sufficient for significant decreases in EGFR protein and transcript levels and this reduction in EGFR is sufficient to reduce cell growth.

AP-1 Family Transcription Factors Bind to and Influence EGFR Intron 1 Enhancers

To identify transcription factors important for enhancer activity we further analyzed our H3K27Ac ChIP-seq and ATAC-seq data. To eliminate non-enhancer regulatory regions, we intersected ATAC-seq peaks with enhancer peaks from H3K27Ac and kept the TSS-distal (+/− 2.5kb) ATAC-seq peaks which mapped within an enhancer. Performing de novo motif analysis on these peaks in EGFR expressing cells (SF767 and HN12) identified an AP-1 transcription factor motif as the most significantly enriched motif (Supplemental Fig. 4A).

To validate the TF motifs identified in silico, we examined AP-1 family transcription factor ChIP-seq data deposited by the Encyclopedia of DNA Elements (ENCODE) consortium (Supplemental Table 1). Using this approach multiple c-Jun and c-Fos peaks were identified within the CE1 and CE2 of EGFR in HN12 and SF767 cells (Fig. 6A). Importantly, H3K27Ac ChIP-seq in HeLa-S3 and HUVEC also shows high levels of enhancer marks in the AP-1 marked regions (Supplemental Fig. 4B). For further analysis we chose c-Jun and c-Fos as the prototype AP-1 factors which form heterodimers that bind to the consensus 5’-TGA(C/G)TCA motif-3’ (35). We validated and quantified c-Fos and c-Jun enrichment at the CE1 and CE2 regions in EGFR expressing (SF767 and HN12) and non-expressing (TS576) cells and identified significant fold enrichment of both factors in EGFR expressing cells (Fig. 6B). Additionally, we identified significantly increased binding of c-Fos at the CE1-AP1-3 and c-Jun in CE1-AP1.3 and CE2-AP1.4 sub-regions in HN12 cells indicating these regions may be important for the increased EGFR expression levels in these cells.

Figure 6.

AP-1 family members bind to and modulate EGFR expression. A: Schematic of positions of AP-1 binding positions based on ENCODE ChIP-seq data, shown relative to ChIP-seq and ATAC-seq peak density. CE1 and CE2 are highlighted. B: Analysis of (left) c-Jun and (right) c-Fos occupancy at the indicated sites. Transcription factor binding is represented as fold change over a negative control region located in chr12. C: Analysis of EGFR, JunDN-HA, c-Jun, and c-Fos protein expression in HN12 cells by western blot after transduction with pMIEG3-JunDN-HA. β-Actin was used as a loading control. D: Analysis of JunDN efficacy on a luciferase reporter containing a trimerized AP-1 binding site. B,D: (*p < 0.05, **p < 0.005, ***p < 0.0005, n = 3 independent experiments, Student’s t test)

To validate the role of AP-1 transcription factors in EGFR transcription, we utilized a dominant-negative version of c-Jun (JunDN) (36). JunDN can dimerize with other AP-1 family members and bind DNA, however the transcriptional activation capability is eliminated. HN12 and U87 cells transduced with JunDN showed decreased EGFR protein levels, thus supporting a role for c-Jun heterodimers in the regulation of EGFR transcription (Fig. 6C, Supplemental Fig. 4C). Additionally, we detected a decrease in c-Jun levels when JunDN was present, likely due to autoregulation of the Jun promoter by c-Jun heterodimers (37). To confirm the effect of JunDN was due to reduced c-Jun heterodimer activity, we utilized a luciferase reporter containing a trimerized AP-1 binding motif. Luciferase reporter assays showed significant decreases in activity when JunDN is present compared to the empty vector control, confirming the reduced transcriptional activation potential of JunDN (Fig. 6D, Supplemental Fig. 4D). Taken together, these data suggest that AP-1 family members are critical for fine-tuned regulation of EGFR expression and specifically bind to EGFR enhancer regions. Perturbation of this AP-1 transactivation effect by expression of a dominant negative results in a significant repression of c-Jun heterodimer targets including EGFR and c-Jun, confirming the role of this family of transcription factors in intron 1-mediated EGFR expression.

Treatment with JQ1 Reduces EGFR Expression by Modulation of TF Activity

Previous research from our lab has shown treatment of mice harboring GBM neurosphere PDX models with the BET protein inhibitor JQ1 significantly prolongs survival, and combination of JQ1 with anti-EGFR therapy further increases this effect (38). To determine if this effect of JQ1 is partially attributable to downregulation of EGFR transcription through BET proteins we treated HN12 and SF767 cells with JQ1 and measured the effects on EGFR expression. Interestingly, after 24 hours of 0.5μM JQ1 EGFR protein and transcript levels were decreased in both HN12 (Fig. 7A, 7B) and SF767 (Supplementary Fig. 5A, 5B) cell lines. Protein expression of BET proteins BRD2, BRD3 and BRD4 increased in response to JQ1, however protein level of the known BRD4 target c-Myc was downregulated (Fig. 7A).

Figure 7.

JQ1 treatment reduces EGFR transcription through inhibition of transcription factor activity. A: Analysis of EGFR, BRD4, BRD3, BRD2, c-Fos, c-Myc, and c-Jun protein expression in HN12 cells by western blot after treatment with 0.5μM JQ1 for 24 hours. β-Actin was used as a loading control. B: EGFR expression was analyzed by RT-qPCR in HN12 cells treated with 0.5μM JQ1 for 24 hours. EGFR transcript level was first normalized to GAPDH and subsequently calculated as fold change relative to DMSO control. C: Fold changes in enrichment of the indicated factors after 24 hours of 0.5μM JQ1 was measured at the indicated regions by ChIP-qPCR. ChIP enrichment is normalized to a negative control region in chr12. D: Relative interaction frequency by 3C of each restriction fragment (F1-10) was calculated as described in the experimental procedures and was plotted against genomic location of the EcoRI restriction site. Significant differences in interaction are indicated for HN12 +JQ1 relative to control (HN12 +DMSO). E: (Bottom) Analysis of EGFR, BRD4, BRD3, BRD2 and β-Actin protein expression in HN12 cells by western blot after treatment with indicated siRNA. A scrambled siRNA was used as treatment control and β-Actin was used as a loading control. (Top) Quantification of relative protein expression. Significance is measured relative to scramble control. B-E: (*p < 0.05, **p < 0.005, ***p < 0.0005, n = 3 independent experiments, Student’s t test)

BRD4 is known to co-occupy enhancers with AP-1 family members (9,10) and is enriched at enhancers (6), and BRD2/3 have been shown to bind to hyperacetylated regions and allow for the activity of RNA polymerase II (39). JQ1 is a pan-BET inhibitor (40) thus to determine if JQ1 treatment was affecting EGFR levels through reduced activity of select BET family members, we first looked at expression levels of BET proteins in our cell line panel and found their expression to be highly variable but present in most cell lines (Supplemental Fig. 5C). We then looked for evidence of binding of these factors to CE1 and CE2. Recent data in the liposarcoma cell line LPS141 (41) shows presence of H3K27Ac in CE1 and CE2, and has binding of BET family members BRD2, BRD3 and BRD4 in those regions (Supplemental Fig. 5D). To confirm binding of these factors in GBM and HNSCC and to interrogate their relationship with AP-1, we performed ChIP-qPCR for c-Fos, c-Jun, BRD2, BRD3, BRD4 and H3K27Ac at regions of open chromatin in CE1 and CE2. In HN12 cells, treatment with JQ1 significantly reduces occupancy of H3K27Ac at all measured regions, and significantly reduces binding of BET and AP-1 family transcription factors to CE1 and CE2 (Fig. 7C). Interestingly, in contrast to steady state (Fig. 6C) which suggests CE2-AP1.4 is a critical c-Fos and c-Jun binding site, treatment with JQ1 only affects binding of BRD4 at that region (Fig. 7C). In SF767 cells, significant reductions in TF occupancy were observed primarily in CE2, with only BRD4 showing a significant reduction in binding to CE1 (Supplemental Fig. 5E). Importantly, JQ1 treatment also impedes EGFR transcription by inhibiting the interaction between CE1/CE2 and the EGFR promoter as measured by 3C (Fig. 7D, Supplemental Fig. 5F).

To determine the specific BET protein critical for maintenance of EGFR expression we performed siRNA knockdowns of BRD2/¾ individually as well as in combination. In HN12 cells single knockdown of BRD2 or BRD4, but not BRD3, resulted in downregulation of EGFR protein. Complete loss of BRD2/¾ protein by combination siRNA treatment resulted in the strongest downregulation of EGFR protein (Fig. 7D). In SF767 cells single knockdown of BRD2 produced the strongest downregulation of EGFR protein (Supplementary Fig. 5F), indicating BRD2 and BRD4 activity on EGFR expression may be cell type specific.

To further interrogate the relationship between EGFR, AP-1, and BET clinically we utilized H3K27Ac ChIP-seq and matched RNA-seq in 44 patient derived glioblastoma stem cells (GSCs) and 50 primary tumors (24). We organized these samples by their EGFR expression by RNA-seq and found that those tumors which have high EGFR also have high levels of H3K27Ac in intron 1 (Supplemental Fig. 6A). We then plotted EGFR RNA expression versus expression of JUN, FOS, BRD2, and BRD4 and found significant correlations between expression of these transcription factors and EGFR levels (Supplemental Fig. 6B). Finally, to determine if the activity of the EGFR enhancers are tumor specific we compared expression of these genes between tumor and normal samples in the TCGA database (42) (Supplemental Fig. 6C). We found in GBM tumor samples transcript levels for EGFR, FOS, JUN, BRD2, and BRD4 are significantly upregulated versus normal samples. In HNSCC tumor samples, transcript levels for EGFR, BRD2, and BRD4 are significantly upregulated versus normal samples. Taken together these results implicate a role for BRD2 and BRD4 cooperating with AP-1, in the maintenance of EGFR expression in GBM and HNSCC.

Discussion

In this study we identify regions of epigenetic regulation within the first intron of the EGFR gene in GBM and HNSCC, characterizing DNA regions which are cell type specific in their H3K27Ac deposition, but contain conserved regions of open chromatin and histone acetylation within EGFR-expressing cells. These regions pass the threshold to be considered super enhancers and contain individual constituents which demonstrate functional attributes of active enhancers, including transcriptional enhancement in reporter assays, 3D interactions with the EGFR promoter, and negative regulation of their target gene when removed or repressed. We identify the presence and activity of AP-1 transcription factors in the CE1 and CE2, and when the activity of these transcription factors is eliminated significant effects are seen in expression of target genes including EGFR and JUN, indicating direct AP-1 dependency of these genes. Pharmacologic disruption of the transcription factor complexes at these enhancers has significant effects on EGFR expression, providing a mechanism by which this transcriptional control mechanism may be targeted. While identification of EGFR super enhancers in other tumor types has been published previously (8,10,24–26), this study provides significant advances in our understanding of the most critical EGFR enhancer regions by undertaking functional genomic and pharmacologic approaches to directly perturb their activity and demonstrating functional consequences on tumor cell proliferation both in vitro and in vivo.

Elevated EGFR is a well-established therapeutic target, however responses to EGFR tyrosine kinase inhibitors (TKI) are sporadic. The mechanisms behind resistance to EGFR TKI are unique to each tumor type, and secondary resistance mutations are common. In HNSCC, high EGFR copy numbers are statistically associated with cetuximab and gefitinib resistance (43), and although rare, kinase domain mutations may be associated with altered responses to EGFR inhibitors (44). In GBM, resistance mechanisms are less well understood with prevailing theories including intratumoral heterogeneity (45), EGFR amplified extrachromosomal DNA (ecDNA) (46), and loss of PTEN (47). Another tumor type which has a high prevalence of EGFR overexpression is non-small cell lung cancer (NSCLC), the resistance mechanisms for which are largely kinase-domain mutations (48,49). With these challenges in mind, this study presents a kinase domain independent mechanism by which EGFR expression and activity can be prevented. Recent studies have shown targeted transcription factor blockade can overcome EGFR TKI resistance (50), thus this study presents an additional pathway which can be targeted alone or in combination with EGFR TKI’s to treat EGFR-positive tumors. Further studies should interrogate the CE1 and CE2 in EGFR-mutated models, specifically in NSCLC where TKI-resistant EGFR mutations are present in as much as 63% of tumors (48).

This study focuses exclusively on non-amplified EGFR, however significant fractions of both HNSCC and GBM tumors have high copy numbers of the gene (16,51). In GBM, EGFR can be amplified both as a homogeneously staining region (HSR) or on ecDNA (46), both of which include the entire EGFR gene and surrounding regions. Amplified enhancer regions maintain their enhancer signatures (52) and focal amplifications of super enhancers have been shown to drive transcription (53). Because amplified enhancers have standard enhancer features, we hypothesize that targeting amplified EGFR directly (Fig. 5) or pharmacologically (Fig. 7) will have similar inhibitory effects. Future studies should explore this hypothesis to further broaden the clinical implications of targeting EGFR intron 1 enhancers.

In tumor types which frequently alter EGFR, structural variations (SV’s) are common. One such SV, EGFR variant III (EGFRvIII), is an extracellular domain mutation which shows constitutive tyrosine kinase activity (54). The mutant receptor is highly tumor specific (55) and relatively common in GBM (51). EGFRvIII protein has been identified in other tumor types including HNSCC (56), although genomic deletion of exons 2-7 have not been detected. In GBM every incidence of EGFRvIII has unique genomic breakpoints within intron 1 and intron 8, removing exons 2-7 and large portions of intron 1 depending on breakpoint location, often including regions which we have identified as enhancers (57) (Fig. 1A). It is important to note the majority of identified EGFRvIII breakpoints occur nearer the 3’ end of EGFR intron 1, often removing the region which we have identified as CE2 (57). Interestingly, in some of our cell line models the data indicates a more significant role for CE2 in interaction with the EGFR promoter by 3C (Fig. 3) and influence on the expression of EGFR by dCas9-KRAB (Fig. 5). In other models the utilization of each CE is either equal (Supplemental Fig. 3) or demonstrates a CE1 bias (Fig. 4C, HN12/SF767/Cal27). But, targeting both CE’s always produces a combinatorial effect (Fig. 4, 5). These data demonstrate an intricate regulatory system that is cell type-specific and makes predicting the functional consequences of intron 1-loss on EGFRvIII expression difficult. Further research should interrogate directly how extent of intron 1-loss affects EGFRvIII through analysis of patient derived and/or CRISPR/Cas9-generated EGFRvIII+ models.

Many potent oncogenes are associated with super enhancers, including MYC and HER2 (30,58). These genes and others have been successfully targeted in cancers which express them by inhibiting the BET protein BRD4, a hallmark factor involved in super enhancer identity (6). The BET-bromodomain inhibitor JQ1 has been shown to inhibit BRD4 at super enhancers (6) and additionally sensitizes EGFR amplified GBM (38) and HNSCC (59) cells to EGFR TKI. Our data suggests that this sensitization may also be due in part to JQ1-mediated inhibition of AP-1 and other BET proteins at EGFR intron 1 enhancers (Fig. 7). Although site-specific inhibition of TF binding is cell type dependent, whether targeting TF binding pharmacologically (Fig. 7A–D, Supplemental Fig. 5A–G) or through RNAi (Fig. 7E, Supplemental Fig. 5F), the effects on EGFR are consistently deleterious. These results support the global targeting of AP-1 and BET rather than site-specific repression (e.g. dCas9-KRAB). Additionally, our study shows significant reduction of EGFR protein and transcript after JQ1 treatment independent of gene expression (Fig. 7A–B, Supplemental Fig. 5A–B), indicating a broader effect of JQ1 on tumor models which express EGFR at varying levels. Indeed, EGFR transcript levels are reduced to similar levels in SF767 cells which express less EGFR and exhibit less significant TF occupancy differences in response to JQ1 treatment (Supplementary Fig. 5E). Further, clinical benefit for patients with EGFR-expressing GBMs is supported by the presence of super enhancers in EGFR-positive GSC and primary tumor samples (Supplemental Fig. 6A). These tumors exhibit positive correlations between critical TF expression and EGFR mRNA, and suggest limited off-target effects in the brain due to significant differences in TF expression between normal and tumor tissues (Supplemental Fig. 6B–C). These data combined further support the combination of EGFR TKI and JQ1 as treatment for EGFR-positive malignancies.

In conclusion we found that EGFR expression is maintained in part through presence and activity of critical enhancers present in intron 1 of the gene. Characterization of CE1 and CE2 in multiple cell line systems identified a novel role for BET transcriptional co-activators and AP-1 transcription factors in these enhancers, and provided the rationale for therapeutic targeting of EGFR through perturbation of BET and AP-1 in EGFR-positive malignancies.