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. 2026 May 3;117(7):1894–1906. doi: 10.1111/cas.70408

Super‐Enhancer Formation in Scirrhous Gastric CAFs, and the Presence of a Stromal Field in Non‐Cancerous Tissues

Yoshimi Yasukawa 1, Naoko Hattori 1,2,✉, Yu‐Yu Liu 1, Masayuki Tobo 2, Genki Yamagishi 2, Takahiro Irie 1, Shigeki Sekine 3, Tohru Kiyono 4, Satoshi Yamashita 5, Yukinori Yamagata 6, Takaki Yoshikawa 6, Yasuyuki Seto 7, Toshikazu Ushijima 1,✉
PMCID: PMC13327015  PMID: 42070972

ABSTRACT

Scirrhous gastric cancer has aggressive clinical courses and is characterized by dominating cancer‐associated fibroblasts (CAFs). However, the origin of scirrhous CAFs remains unclear, and we here aimed to explore the epigenetic basis for scirrhous CAFs and their origin. Conditioned medium (CM) from scirrhous CAFs was shown to have a marked effect (2–4 folds) on the migration of gastric cancer cells compared to that from non‐scirrhous CAFs. The aggressive phenotype of scirrhous CAFs was associated with activation of TGFβ1 and NF‐κB, along with increased expression of their downstream genes. Scirrhous CAFs had heavily acetylated super‐enhancers, and therapeutic targeting of super‐enhancers by a BET bromodomain inhibitor, mivebresib and JQ‐1, markedly decreased their migration‐promoting activity. Notably, in scirrhous gastric cancer patients, normal fibroblasts in non‐cancerous tissues also had a strong migration‐promoting effect. It was suggested that fibroblasts in the non‐cancerous tissue of scirrhous gastric patients have already acquired tumor‐promoting capacity, forming a stromal field for scirrhous gastric cancer although its spatial extent remains to be solved.

Keywords: BET inhibitor, enhancer, epigenetics, epigenome, gastric cancer, histone acetylation

While CAFs are produced as a result of education by cancer cells in non‐scirrhous gastric cancer, normal fibroblasts of scirrhous gastric cancer patients are already pre‐conditioned, forming a stromal field for scirrhous gastric cancer.

graphic file with name CAS-117-1894-g004.jpg

Abbreviations

CAF

cancer‐associated fibroblast

ChIP

chromatin immunoprecipitation

CM

conditioned medium

NF

normal fibroblast

PBS

phosphate‐buffered saline

TSS

transcriptional start site

1. Introduction

The tissue ecosystem plays important roles in cancer development and progression [1], and cancer‐associated fibroblasts (CAFs) are a major component. Although many studies have shown that CAFs can support growth, infiltration, and migration of cancer cells [2, 3] via secretion of multiple factors into the stroma, fibroblasts have heterogeneity both in normal and cancer tissues [4], and some CAFs even show an anti‐tumoral effect [5]. Such factors, including IGF2, WNT, IL6, and other chemokines or growth factors, have recently attracted attention as therapeutic targets [6, 7, 8]. CAFs have been considered to be produced from local normal fibroblasts or mesenchymal stem cells by “education” from cancer cells [9, 10], and classified into three subtypes, myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), and antigen‐presenting CAFs (apCAFs) [11, 12, 13]. myCAFs are generated by activating the canonical TGFβ pathway, iCAFs are induced by inflammatory pathways including JAK–STAT and NF‐κB signaling, and apCAFs are characterized by high expression of MHC class II. CAFs maintain their phenotypes via DNA methylation changes [14, 15] and alterations in H3K27me3 histone modification, which stably suppress gene transcription [7, 16]. In addition to these changes, enhancer alterations, which result in stable changes in high‐order structures of the genome and transcriptional activities [17, 18], were also observed in CAFs, such as the enhancer activation of SAA1 in gastric CAFs [19].

CAFs have been reported to be especially important for scirrhous gastric cancer, which is characterized by the domination of CAFs [20] and rapid and aggressive progression, including peritoneal dissemination after surgery [21]. Scirrhous CAFs have been reported to exhibit strong tumor‐promoting activity by secreting growth factors (e. g. PDGFs, FGFs, TGFβ, and HGF), metalloproteases, and extracellular vesicles [20, 22, 23, 24]. Such phenotypes are believed to be educated by scirrhous cancer cells, and cell‐intrinsic mechanisms maintaining these phenotypes, such as epigenetic alterations, have been poorly studied. As an inducer or promoting factor of scirrhous gastric cancer, involvement of Helicobacter pylori infection is still controversial [25, 26], although its causal involvement in gastric cancer in general is well established [27].

Here, we focus on the distinct phenotypes of scirrhous CAFs and fibroblasts from non‐cancerous tissues of patients with scirrhous gastric cancer. The strong tumor‐promoting capacity and CAF‐like phenotypes in “normal” fibroblasts of scirrhous cancer patients indicates that fibroblasts primed for scirrhous CAFs may have been produced before the development of scirrhous cancer, providing a stromal field for scirrhous cancer.

2. Materials and Methods

2.1. Primary Fibroblasts and CAFs

Six scirrhous CAFs were established from cancer tissues of surgically resected stomach from six patients with scirrhous gastric cancer as previously described [7]. Scirrhous gastric cancer was diagnosed based upon final pathological diagnosis by a skilled pathologist (S.S.). All gastric cancer patients had gastric mucosal atrophy and were confirmed to have a history of H. pylori infection. Six non‐scirrhous CAFs were established previously [19]. At the same time, the fibroblasts from normal tissues located > 5 cm apart from the margin of cancer tissues were also established with each patient. As well as this, fibroblasts derived from intact tissue of three GIST patients without H. pylori infection were also established.

The CAFs and fibroblasts were maintained in an MF medium (Toyobo, Tokyo, Japan) or D‐MEM medium (high glucose, FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan) supplemented with Insulin‐Transferrin‐Selenium (Thermo Fisher Scientific, Waltham, MA), and confirmed to be negative for mycoplasma infection using a MycoAlert Mycoplasma Detection Kit (Lonza, Basel, Switzerland). All the primary fibroblasts were used within 10 passages from the first culture. All the specimens were obtained with written informed consents, and the study was approved by the Institutional Review Boards at the National Cancer Center (2013‐073).

Total RNA was extracted using a ReliaPrep kit (Promega, Madison, WI). Genomic DNA was extracted using 10% SDS, EDTA, and proteinase K (Thermo Fisher Scientific), and was purified by phenol and chloroform extraction followed by ethanol precipitation.

2.2. Gastric Cancer Cell Lines

The N87 and the HSC58 cell lines were gifted by Dr. K Yanagihara at the National Cancer Center on August 11, 2014. STR profiling analysis was performed by Takara Bio Inc. (Shiga, Japan) using the GenePrint 10 System (Promega), and the cell authenticity was confirmed using CLASTR: the Cellosaurus STR similarity search tool (https://web.expasy.org/cellosaurus) [28]. Cells were tested for mycoplasma infection with a MycoAlert Mycoplasma Detection Kit (Lonza).

2.3. Preparation of Conditioned Medium (CM)

Each conditioned medium (CM) was prepared as previously described [19]. Briefly, 24 h after seeding fibroblasts, 4 mL serum‐free phenol red‐free RPMI1640 medium (FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan) was added and incubated for 24 h. The culture supernatant was filtered with 0.45 μm filter, and centrifugally concentrated using an Amicon Ultra‐15 Centrifugal Filter (Merck Millipore, Burlington, MA). Control CM without fibroblasts was prepared from serum‐free RPMI1640 medium incubated in empty dishes.

2.4. Treatment of Primary Fibroblasts and CAFs With a BET Inhibitor

The BET inhibitor mivebresib and JQ‐1 were purchased from Selleck Biotech (Tokyo, Japan) and AdooQ bioscience (Irvine, CA), respectively. Primary fibroblasts and CAFs were seeded in 10 cm dishes, and sub‐confluent cells (80%–90%) were treated with mivebresib or JQ‐1 dissolved in DMSO for 3 days at a specified concentration. For CM preparation, on Day 4, the dishes were elaborately washed with PBS (−) to remove the drug as much as possible, and the medium was changed to a MF medium or D‐MEM medium supplemented with Insulin‐Transferrin‐Selenium. On Day 5, the medium was replaced with 4 mL of serum‐free phenol red‐free RPMI1640 medium. After 24‐h incubation, CM was prepared as above.

2.5. Cell Migration and Growth Assay

Cell migration assay was performed using a Transwell Permeable Supports 6.5 mm 24 well (Corning Incorporated, Corning, NY) and N87 gastric cancer cells, as previously reported [19]. Condensed CM (the concentration rate: 10‐fold) was added to a serum‐free RPMI1640 medium at 20%. Cell growth assay was conducted using N87 cells, and cell numbers were estimated on Day 3, measuring the absorbance at 450 nm using the Cell Counting Reagent SF (Nacalai Tesque, Kyoto, Japan), as previously reported [19].

2.6. Western Blot Analysis

Nuclear and cytoplasmic proteins were extracted separately using NE‐PER Nuclear and Cytoplasmic Extraction Reagents (Thermo Fisher Scientific). Proteins were resolved by SDS‐PAGE and transferred to an Immobilon‐P nylon membrane (Merck Millipore). After blocking, each membrane was incubated with one of the following primary antibodies; anti‐phospho‐Smad2 (Ser465/467, #3101, Cell Signaling Technology, Danvers, MA), anti‐Smad2/3 (#3102, Cell Signaling Technology), anti‐phospho‐NF‐κB (Ser536, #3033, Cell Signaling Technology), anti‐NF‐κB (C22B4, #4764, Cell Signaling Technology), anti‐NUP98 (C39A3, #2598, Cell Signaling Technology), and anti‐α‐tubulin (#69–125, ICN Biomedicals, Santa Ana, CA). Using a secondary antibody [anti‐rabbit IgG, HRP‐linked antibody (#7074, Cell Signaling Technology) for phospho‐Smad2, Smad2/3, phospho‐NF‐κB, NF‐κB, and NUP98, anti‐mouse IgG antibody (#5220–0339, Kirkegaard & Perry Laboratories Inc., Gaithersburg, MD) for α‐tubulin], protein bands were visualized by chemiluminescence using an ECL kit (Cytiva, Marlborough, MA).

2.7. Quantitative Reverse Transcription PCR (RT‐qPCR)

From total RNA, complementary DNA (cDNA) was synthesized using oligo‐(dT)20 (Toyobo) and SuperScript IV Reverse Transcriptase (Thermo Fisher Scientific). cDNA molecules were quantified by RT‐qPCR using specific primers (Table S1), ThunderBird Next SYBR Green Mix (Toyobo), and the CFX Connect Real‐Time PCR Detection System (Bio‐Rad, Hercules, CA). The number of target gene cDNA molecules in a sample was determined by comparing its amplification curve with standard DNA samples of known copy numbers. The quantified number of target cDNA molecules was normalized to that of GAPDH cDNA molecules.

2.8. CUT&RUN and Quantitative PCR (qPCR)

CUT&RUN was performed using the CUT&RUN Assay Kit (Cell Signaling Technology). Briefly, 1 × 105 cells of CAF36 and CAF66 treated with mivebresib (0 or 0.3 μM) were bound to Concanavalin A‐coated beads and incubated at 4°C overnight with 2 μL of anti‐BRD4 antibody (#14330, Cell Signaling Technology), 2 μL of anti‐H3K4me3 antibody (#9751, Cell Signaling Technology), or 5 μL of rabbit IgG antibody (#66362, Cell Signaling Technology)  in the presence of digitonin. [Correction added on 12 June 2026, after first online publication: The unit “µg” has been corrected to “µL” in the prior sentence.]. Protein A‐protein G‐micrococcal nuclease (1.5 μL, 25 ng/μL) was added and activated by calcium chloride to cleave out antibody‐bound DNA fragments. For normalization, 50 pg of spike‐in control DNA provided in the kit was added to chromatin in each sample. DNA was isolated using phenol‐chloroform extraction and ethanol precipitation. The number of DNA molecules was quantified by qPCR using specific primers (Table S1), ThunderBird Next SYBR Green Mix (Toyobo), and the CFX Connect Real‐Time PCR Detection System (Bio‐Rad, Hercules, CA). Region‐specific affinity with BRD4 and H3K27ac was analyzed by IP ratio in qPCR, which showed the ratio of immunoprecipitated DNA to input DNA.

2.9. RNA‐Seq and Data Analysis

RNA‐seq was conducted using an Illumina TruSeq Stranded Total RNA Library Prep Kit with Ribo‐Zero Human and NovaSeq 6000 (TruSeq stranded, paired 100 bases, read depth 60–80 M per sample). Reads were aligned to the human transcriptome using STAR software (version 2.7.3a) and each mRNA count number and TPM was calculated using RSEM (version 1.3.1). Fold‐change and p‐values comparing scirrhous CAFs (S‐CAF) and six non‐scirrhous CAFs (non‐S‐CAF) were calculated using edgeR. Genes with a p‐value < 0.05 and FDR < 0.01 were considered as differentially expressed genes.

2.10. DNA Methylation Analysis

Genome‐wide DNA methylation analysis was performed using an Infinium HumanMethylation450 BeadArray or Infinium Human MethylationEPIC BeadChip v1.0 (Illumina, Sam Diego, CA) as described previously [29]. The BeadArray assessed the degree of methylation as a β‐value that ranged from 0 (unmethylated) to 1 (fully methylated). Enhancer regions were defined according to the Illumina annotation for MethylationEPIC v1.0 (http://support.illumina.com/array/array_kits/infinium‐methylationepic‐beadchip‐kit/downloads.html), which originated from the ENCODE and FAMTOM5 projects [30].

2.11. Chromatin Immunoprecipitation (ChIP)‐seq Analysis

Chromatin was cross‐linked, and sonicated, as previously described [19]. 30 μg of sonicated chromatin was incubated at 4°C overnight with 2 μg of anti‐H3K27ac antibody (ab4729, Abcam, Cambridge, MA). 10 μg of sonicated chromatin was incubated overnight at 4°C with 10 μL of anti‐H3K4me1 antibody (#5326, Cell Signaling Technology, Danvers, MA) and 10 μL of anti‐H3K4me3 antibody. 20 ng of Spike‐in chromatin (#53083, Active Motif, Carlsbad, CA) and 2 μL of Spike‐in antibody (#61686, Active Motif) were added to the chromatin solution. Chromatin bound with the antibody was collected using Dynabeads Protein G (Thermo Fisher Scientific) and then eluted with TE buffer. Cross‐link in the eluate was reversed in the presence of 200 mM NaCl overnight at 65°C, digested with proteinase K (Thermo Fisher Scientific), and purified by phenol and chloroform extraction and ethanol precipitation. [Correction added on 12 June 2026, after first online publication: The unit “µg” has been corrected to “µL” in Section 2.11.]

For ChIP‐seq analysis, sequencing libraries were prepared with a GenNext NGS Library Prep Kit (Toyobo) and sequenced using Illumina HiSeq X (Illumina, San Diego, CA) for H3K27ac or Illumina NextSeq2000 (Illumina) for H3K4me1 and H3K4me3 for a final sequencing depth of 40 million reads per sample for H3K27ac, and 10–30 million reads per sample for H3K4me1 and H3K4me3. For sequencing QC and adapter trimming of all ChIP‐seq data, fastp (version 0.23.4 for H3K27ac; version 0.22.0 for H3K4me1 and H3K4me3) was used. All reads were aligned to the human genome GRCh38/hg38 and spike‐in Drosophila genome dm6 using the short‐read aligner Bowtie 2 (version 2.5.1) with default parameters. The resultant SAM file was converted into a BAM file, and duplicates were removed using SAMtools (version 1.18). The resultant SAM file was converted into a BAM file, and peaks for H3K27ac, H3K4me1, and H3K4me3 were called using Macs2 (version 2.2.9.1) with the input control with default parameters [31]. Uniquely aligned Drosophila sequence tags were counted and compared with the sample containing the least number of tags to generate a normalization factor for random downsampling.

2.12. Identification of Super‐Enhancers

Super‐enhancers were identified as previously described [32, 33]. Briefly, peaks within a window ±2000 bp around TSS were excluded, and then those within 12,500 bp were stitched into one region. Read density of each stitched region was calculated by adding up the pileup signals for each bp and was normalized to reads per million per bp (rpm/bp). To draw the threshold between enhancers and super‐enhancers, all stitched regions of H3K27ac were ranked along the x‐axis by the background‐subtracted ChIP‐seq density in increasing order. The threshold was defined as the intersection of the slope of 1 tangent to the curve produced by ranked stitched regions. Regions below this threshold were defined as typical enhancers, and those above as super‐enhancers. Annotation of identified super‐enhancers was performed using HOMER, and data for H3K27ac signals and super‐enhancers were visualized using the Integrated Genomics Viewer (IGV).

2.13. Ingenuity Pathways Analysis (IPA)

The biological functions of the super‐enhancers specific to scirrhous CAFs were analyzed using Ingenuity Pathway Analysis (IPA) software (Version 01‐19‐00, Qiagen, Ingenuity H Systems, Redwood City, CA; http://www.ingenuity.com). “Pathways associated with genes with super‐enhancers” were searched for by pathway analysis. “Upstream regulators” were defined based on knowledge of the relationships between upstream transcriptional regulators and their downstream targets obtained from published literature. p‐values were calculated using right‐tailed Fisher's exact test.

2.14. Gene Set Enrichment Analysis (GSEA)

Analysis of the differentially expressed gene sets in RNA‐seq was performed using the Gene Set Enrichment Analysis (GSEA) software (version 4.3.2, GSEA/MSigDB Team, UC San Diego, CA; http://www.gsea‐msigdb.org/gsea/index.jsp).

2.15. Statistical Analysis

Differences in gene expression levels, cell invasion, cell viability, IP ratios, and the data of biochemical tests were analyzed using an unpaired Student's t‐test. The results were considered significant when a p‐value < 0.05 was obtained by a two‐sided test. All calculations were performed using Microsoft Excel software (Microsoft Corp, Seattle, WA).

3. Results

3.1. Scirrhous Gastric CAFs Have Marked Migration‐Promoting Capacity

We established CAFs from six scirrhous gastric cancer patients and analyzed their influence on cancer cell migration and proliferation. First, migration‐promoting capacity of these six scirrhous CAFs, along with six non‐scirrhous CAFs previously established [19], was analyzed by cell migration assay using their conditioned medium (CM) and a gastric cancer cell line, N87. The CMs from scirrhous CAFs showed a marked effect on cancer cell migration, being 2‐ to 4‐fold as strong as those from non‐scirrhous CAFs (Figure 1A). Then, we performed cell growth assay using the same gastric cancer cell line and CMs and observed that cell growth was moderately increased when treated with CMs from scirrhous CAFs (Figure 1B), confirming the results of a previous report [10]. These results showed marked migration‐promoting capacity and confirmed cell proliferation‐promoting activity of scirrhous CAFs.

FIGURE 1.

FIGURE 1

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Higher tumor‐promoting capacity of scirrhous CAFs compared with non‐scirrhous CAFs. (A) Cancer cell migration assay using CM derived from six non‐scirrhous CAFs and six scirrhous CAFs. CMs obtained from the scirrhous CAFs markedly promoted migration of gastric cancer cells compared with those from non‐scirrhous CAFs. (B) Cancer cell growth‐promoting effect of the same CMs as in (A). The amount of living cells on Day 3 was measured by absorbance using Cell Counting Reagent. CMs derived from scirrhous CAFs increased the growth of gastric cancer cells compared with those from non‐scirrhous CAFs.

3.2. TGFβ1‐Mediated Pathways Are Activated in Scirrhous CAFs

Establishing CAFs with high tumor‐promoting capacity, we explored gene expression alterations in scirrhous CAFs by RNA‐seq using the six scirrhous CAFs and the six non‐scirrhous CAFs. Gene Set Enrichment Analysis (GSEA) identified target genes of TGFβ1 as upregulated in scirrhous CAFs (Figure 2A,B, Figure S1). In addition, to search upstream regulators of genes upregulated and downregulated in scirrhous CAFs, we performed Ingenuity Pathway Analysis (IPA). Resultantly, TGFβ1 and IL1β were identified as upstream regulators of genes highly expressed in scirrhous CAFs (Figure 2C).

FIGURE 2.

FIGURE 2

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Upregulation of TGFβ1‐mediated pathways in scirrhous CAFs. (A) Volcano plot to compare gene expression between the six scirrhous CAFs (S‐CAF) and six non‐scirrhous CAFs (non‐S‐CAF). (B) Enrichment of TGFβ1 target genes among the upregulated genes in scirrhous CAFs. GSEA was performed on genes upregulated in scirrhous CAFs [log2FC (scirrhous CAFs/non‐scirrhous CAFs) > 2 and p‐value < 0.01], and the TGFβ1 target gene set was among the top 5 gene sets. (C) Upstream regulators of genes up‐ or down‐regulated in scirrhous CAFs identified by IPA. IL1β and TGFβ1 were among the top five regulators of genes highly expressed in scirrhous CAFs (IL1β: Top 1, TGFβ1: Top 3). (D) Expressions of myCAF, iCAF, and apCAF markers. Scirrhous CAFs exhibited higher expression of some myCAF and iCAF markers than non‐scirrhous CAFs. Both scirrhous and non‐scirrhous CAFs showed very low expression (mean TPM < 1.3) of apCAF markers. (E) Western blot analysis of phospho‐SMAD2, SMAD2/3, phospho‐NF‐κB, and NF‐κB in two non‐scirrhous CAFs and three scirrhous CAFs. Phospho‐SMAD2 was strongly detected in the nucleus of two scirrhous CAFs and one non‐scirrhous CAF. On the other hand, phospho‐NF‐κB was strongly detected in the nucleus of all three scirrhous CAFs. (F) Visualization of signals of RNA‐seq (upper row), H3K27ac ChIP‐seq (lower row), H3K4me1 ChIP‐seq, and H3K4me3 ChIP‐seq by IGV in the CXCL3 genomic region for three scirrhous CAFs and three non‐scirrhous CAFs. H3K27ac and H3K4me1 in putative enhancer and super‐enhancer regions was higher in scirrhous CAFs than in non‐scirrhous CAFs. Upregulation of CXCL3 is noted in (A).

The enhancement of TGFβ1 signaling has been reported as the phenotype of myCAF in several types of cancers [11, 34], and, in scirrhous GCs, as contributing to activation and maintenance of myofibroblasts [35]. Therefore, we analyzed the expression of myCAF markers (ACTA2, ANTXR1, LRRC15, MCAM, MYH11, MYLK, POSTN, and TAGLN), along with iCAF markers (CXCL12, IL1R1, IL6, ISRL, LIF, and PDPN) and apCAF makers (CD74, HLA‐DRA1, HLA‐DPB1, HLA‐DRA, and HLA‐DRB1) [34, 36, 37, 38, 39, 40, 41] (Figure 2D). Scirrhous CAFs exhibited higher expression of two myCAF markers, ACTA2 and ANTXR1, and three iCAF markers, IL1R1, ISLR, and PDPN, than non‐scirrhous CAFs. Both scirrhous and non‐scirrhous CAFs showed very low expression (mean TPM < 1.3) of apCAF markers. These results suggested that both scirrhous and non‐scirrhous CAFs consisted mostly of myCAFs and iCAFs with few apCAFs, although precise CAF composition could not be determined based on the bulk RNA‐seq data.

Since TGFβ1 is known to transmit its signal via SMAD2/3 [42] and IL1β is known to activate NF‐κB [43], we conducted their Western blot analysis using three scirrhous and two non‐scirrhous CAFs. Phospho‐SMAD2 in the nucleus was prominent in two of the three scirrhous CAFs and one of the two non‐scirrhous CAFs (Figure 2E), suggesting the activation of the TGFβ1 pathway in scirrhous CAFs. Phospho‐NF‐κB in the nucleus was prominent in the three scirrhous CAFs compared with the two non‐scirrhous CAFs (Figure 2E), showing that NF‐κB was also activated in scirrhous CAFs. These data indicated that SMAD2 and NF‐κB were involved in the regulation of genes highly expressed in scirrhous CAFs.

Among the genes upregulated in scirrhous CAFs, CXCL3, a secreted growth factor associated with inflammation targeted by TGFβ1 [44], was present (Figure 2A,F). ChIP‐seq showed that H3K27ac was increased 3.0 and 20 k bp upstream of the CXCL3 promoter in scirrhous CAFs (Figure 2F). To further characterize these regions, we performed ChIP‐seq for H3K4me1 and H3K4me3 (Figure S2). No enrichment of H3K4me3 was observed at these upstream regions in either non‐scirrhous CAF (CAF30) or scirrhous CAF (CAF66), showing the lack of promoter activity (Figure 2F). In contrast, H3K4me1 marks were detected at these regions, consistent with features of enhancers (Figure 2F). Moreover, the H3K4me1 peaks at the putative proximal enhancer were higher in scirrhous CAF (CAF66) than in non‐scirrhous CAF (CAF30), supporting enhancer activity at this locus. This result suggested that enhanced TGFβ1 signaling led to upregulation of inflammatory factors, some of which may involve enhancer activation.

3.3. Scirrhous CAFs Are Characterized by Highly Acetylated Super‐Enhancers

We then explored two epigenetic mechanisms underlying their phenotypes. First, we performed DNA methylation analysis with a DNA methylation BeadArray using the six scirrhous CAFs, 10 non‐scirrhous CAFs, including the above six non‐scirrhous CAFs, and three fibroblasts from gastrointestinal stromal tumor (GIST) patients without H. pylori infection. A cluster analysis using 3000 of the 65,464 probes from CpG islands that had the highest standard deviation (SD) or using 3000 probes with the highest SD of 20,135 probes from promoters (200 bp within TSS) did not produce a clear distinction between scirrhous CAFs and non‐scirrhous CAFs (Figure 3A,B). A cluster analysis using 3000 probes with the highest SD of 76,810 probes from enhancer regions clustered five of the six scirrhous CAFs together, but this cluster also included three GIST fibroblasts, which were considered to be near normal (Figure 3C). Therefore, the results did not support the involvement of DNA methylation in the formation of scirrhous CAFs.

FIGURE 3.

FIGURE 3

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Little involvement of DNA methylation in scirrhous CAFs (A) Cluster analysis of the six scirrhous CAFs, 10 non‐scirrhous CAFs, and three fibroblasts from GIST patients using DNA methylation profiles of the 3000 most variable CpG island probes. No clear difference was observed between scirrhous CAFs and non‐scirrhous CAFs. (B) Cluster analysis using DNA methylation profiles of 3000 probes from promoter regions (TSS < 200 bp) with the highest standard deviation (SD). No clear difference was observed between scirrhous CAFs and non‐scirrhous CAFs. (C) Cluster analysis using DNA methylation profiles of 3000 probes from enhancer regions with the highest standard deviation (SD). Enhancer regions were defined according to the Illumina annotation for MethylationEPIC v1.0 (http://support.illumina.com/array/array_kits/infinium‐methylationepic‐beadchip‐kit/downloads.html), which originated from the ENCODE and FAMTOM5 projects [30]. Even though some clusters were generated, no clear separation was observed.

We then analyzed acetylation alterations by ChIP‐seq of H3K27ac using three of the six scirrhous and three of the ten non‐scirrhous CAFs. H3K27ac peaks in all CAFs were enriched around the majority of the TSSs and a minority of enhancer regions (Figure S3). Regarding super‐enhancers, their total number ranged from 553 to 616 in non‐scirrhous CAFs, and 214 to 683 in scirrhous CAFs, with no significant difference (Figure 4A). We selected the genes that were not associated with a super‐enhancer in normal fibroblasts, and then conducted IPA using the genes that had super‐enhancers in at least one scirrhous CAFs but in fewer non‐scirrhous CAFs (Tables S2 and S3) to search for (i) pathways associated with the genes with the super‐enhancers and (ii) their upstream regulators. The pathways included osteoarthritis, fibrosis, and IL‐10 signaling, all of which are strongly regulated by TGFβ1 (Figure 4B). The upstream regulators included TGFβ1, involved in fibroblast activation, and TNF, which mediates fibroblast growth factor‐inducible inflammatory and immunologic pathways [45] (Figure 4C). On the other hand, IPA using the genes that were associated with super‐enhancers in at least one non‐scirrhous CAFs but in fewer scirrhous CAFs identified TNF as the most relevant upstream regulator (Figure S4C).

FIGURE 4.

FIGURE 4

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Strong involvement of super‐enhancers in scirrhous CAFs. (A) Super‐enhancer analysis of three non‐scirrhous CAFs and three scirrhous CAFs. All the enhancers were ranked by the intensity of H3K27ac signal, and those with sufficiently strong signals were considered as super‐enhancers. The total number of super‐enhancers ranged from 553 to 616 in non‐scirrhous CAFs, and 214 to 693 in scirrhous CAFs, showing no significant difference. (B) Canonical pathways identified by IPA. The genes that were not associated with a super‐enhancer in normal fibroblasts were selected, and then IPA was performed on genes that were associated with super‐enhancers at least in scirrhous CAFs but in fewer non‐scirrhous CAFs. Three of the top five pathways were associated with inflammation or fibrosis, both of which are strongly regulated by TGFβ1. Details for each pathway are also shown in Table S2. (C) Upstream regulators of the same super‐enhancers as (B). IPA identified TGFβ as the most significant upstream regulator. Downstream target genes of each regulator are shown in Table S3. Representative canonical pathways and upstream regulators in non‐scirrhous CAFs are shown in Figure S4. (D) H3K27ac intensity at the super‐enhancers associated with target genes of TGFβ1 and NF‐κB. Quantification of the intensity revealed that scirrhous CAFs had higher H3K27ac intensity than non‐scirrhous CAFs.

TGFβ1 and NF‐κB signaling were upregulated in scirrhous CAFs (Figure 2B,C,E), suggesting their involvement in super‐enhancer formation in scirrhous CAFs. Indeed, NF‐kB is reported to be involved in the formation and activation of super‐enhancers [46, 47, 48]. Therefore, we analyzed super‐enhancer formation in TGFβ1 and NF‐κB target genes (Figure 4D). Super‐enhancers were associated with 10 genes among the 53 TGFβ1 target genes and three genes among the 21 NF‐κB target genes in at least one CAFs. Quantification of the intensity of H3K27ac at each super‐enhancer revealed that scirrhous CAFs exhibited higher H3K27ac intensity than non‐scirrhous CAFs. The link between super‐enhancer and TGFβ1 target genes was explored using H3K27ac HiChIP and Hi‐C data of IMR‐90 from the Loop Catalog (https://loopcatalog.lji.org/loops/?genome=hg38). Comparison with H3K27ac profiles of scirrhous CAFs (our data) and IMR‐90 (SRX6614778) showed that, at the SMAD3 and WWTR1 loci, H3K27ac marks were present in IMR‐90, similar to those in scirrhous CAFs, and promoter‐super‐enhancer looping was detected in IMR‐90. These data provided support for the association between super‐enhancers and target genes in scirrhous CAFs (Figure S4D). Taken together, highly acetylated super‐enhancers in the TGFβ1 and NF‐κB target genes were characteristic of scirrhous CAFs.

3.4. Super‐Enhancer Activation in Scirrhous CAFs Can Be a Target of Tumor Stroma‐Directed Therapy

Finding the highly acetylated enhancers and super‐enhancers in scirrhous CAFs, we hypothesized that targeting enhancers and super‐enhancer acetylation may have a therapeutic effect. To suppress the enhancer and super‐enhancer, we treated scirrhous CAF (CAF63) with mivebresib, which represses the binding of BRD4 to its target [49], and obtained CM (Figure 5A). The treatment of scirrhous CAF (CAF63) with mivebresib markedly decreased the migration‐promoting activity of its CM while the treatment of non‐scirrhous CAF (CAF30) did not (Figure 5B).

FIGURE 5.

FIGURE 5

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Therapeutic effect of targeting heavily acetylated enhancers and super‐enhancers in scirrhous CAFs. (A) Preparation protocol of CM from normal fibroblasts (NFs) or CAFs with mivebresib treatment. Mivebresib was added to NF or CAF in a 10‐cm dish at a designated dose. The medium was changed to an MF medium after 72‐h incubation, and CM was prepared from the culture supernatant. (B) Increase of cancer cell migration by the CM from scirrhous CAFs, and its cancelation by incubation of the scirrhous CAFs with mivebresib. (C) Reduced expression of super‐enhancer‐associated TGFβ1‐target genes. Expression of CXCL3, HIPK2, and SMAD3 was significantly decreased by mivebresib treatment. (D) BRD4 binding and H3K27ac enrichment in mivebresib‐treated scirrhous CAFs. BRD4 binding was not detected at the CXCL3 enhancers in CAF36 and CAF66 or at the HIPK2 enhancer in CAF66, while it was significantly reduced at the HIPK2 enhancer in CAF36 and the SMAD3 enhancers in both CAF36 and CAF66. H3K27ac levels at the enhancer regions of these genes were decreased in both CAF36 and CAF66. (E) Reduction of cancer cell migration by treatment of the scirrhous CAFs with JQ‐1. JQ‐1 abolished the migration‐promoting activity of CMs from scirrhous CAFs, whereas no significant change was observed in non‐scirrhous CAFs.

To confirm the direct effect of mivebresib on enhancer suppression, we analyzed gene expression and BRD4 and H3K27ac enrichment at the super‐enhancer‐associated TGFβ1 target genes (CXCL3, HIPK2, and SMAD3). Mivebresib treatment reduced the expression of these genes (Figure 5C). BRD4 binding was not detected at the CXCL3 enhancers in CAF36 and CAF66 or at the HIPK2 enhancer in CAF66. In contrast, BRD4 binding was significantly reduced at the HIPK2 enhancer in CAF36 and the SMAD3 enhancers in both CAF36 and CAF66 (Figure 5D). Consistently, H3K27ac levels at the enhancer regions of these genes were also decreased (Figure 5D). Taken together, it was suggested that decreased enhancer activity in scirrhous CAFs, at least in part, may contribute to the reduction of the migration‐promoting activity by mivebresib treatment.

To validate the effects of BET inhibition on migration‐promoting activity, JQ‐1 was applied to CAF culture, and CMs were collected. Treatment of scirrhous CAFs (CAF36 and CAF66) with JQ‐1 also reduced the migration‐promoting activity of their CM, whereas treatment of non‐scirrhous CAFs (CAF19) did not (Figure 5E). Only marginal decreases in cancer cell viability and no clear alterations in cell cycle distribution were observed (Supporting Information and Methods S1; Figure S5). These data showed that super‐enhancer activation can be a target for tumor‐stromal therapy in scirrhous gastric cancer.

3.5. “Normal” Fibroblasts From Scirrhous Patients Have CAF‐Like Tumor‐Promoting Capacity

Previous studies showed that fibroblasts derived from the area surrounding a scirrhous cancer exhibited a moderate ability to promote migration [50, 51]. In this study, we first also analyzed tumor‐promoting capacity of CAFs and fibroblasts in non‐cancerous tissues of scirrhous and non‐scirrhous gastric cancer patients. Two fibroblasts in non‐cancerous tissue (“normal” fibroblasts) of scirrhous cancer patients showed almost as high a migration‐promoting effect as scirrhous CAFs, which was much stronger than non‐scirrhous CAFs (Figure 6A).

FIGURE 6.

FIGURE 6

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CAF‐like tumor‐promoting capacity of fibroblasts in non‐cancerous tissue of scirrhous cancer patients. (A) Cancer cell migration assay using CMs from normal fibroblasts (NFs) and CAFs from two non‐scirrhous and two scirrhous gastric cancer patients. CMs from NFs of scirrhous gastric cancer patients, as CMs from scirrhous CAFs, promoted migration of gastric cancer cells much more than CMs from NFs or CAFs of non‐scirrhous gastric cancer patients. (B) Schematic model of stromal field production for scirrhous gastric cancer. While CAFs are produced as a result of education by cancer cells in non‐scirrhous gastric cancer, normal fibroblasts of scirrhous gastric cancer patients are already pre‐conditioned, forming a stromal field for scirrhous gastric cancer.

4. Discussion

Epigenetic reprogramming with heavily acetylated enhancers and super‐enhancers was shown to be present in scirrhous CAFs. Inhibition of enhancer activity by a BET inhibitor clearly suppressed the tumor‐promoting activity of scirrhous CAFs, raising a possibility of therapeutic targeting super‐enhancers. TGFβ1 was shown to be the upstream regulator of scirrhous CAF‐specific super‐enhancers and thus highly expressed genes. Such important roles of epigenetic reprogramming have recently been reported in CAFs of prostate and gastric cancers [52, 53] but not in scirrhous gastric cancer.

Importantly, “normal” fibroblasts from scirrhous gastric cancer patients were equipped with similar migration‐promoting effects as scirrhous CAFs, unlike normal fibroblasts from non‐scirrhous gastric cancer patients. This pre‐conditioning was in line with previous reports [50, 51], and this study illuminated underlying molecular alterations, namely high expression of target genes of TGFβ1. The upregulation was likely to be due to formation of heavily acetylated enhancers and super‐enhancers as observed in scirrhous CAFs. This raised a possibility that some forms of environmental insult, such as inflammation and hypoxia, may induce enhancer and super‐enhancer activation in “normal” fibroblasts. The presence of such pre‐conditioned “normal” fibroblasts may provide a stromal field for scirrhous cancer by conferring migration‐ and proliferation‐promoting factors. Although the spatial extent of this stromal field remains to be determined, we unfortunately were unable to assess this in the present study, as only fibroblasts derived from a single normal tissue were analyzed. Further studies using multiple spatially defined samples will help clarify the relationships between distance from tumor tissues and the degree of CAF‐like phenotype.

Scirrhous gastric cancer is known to be resistant to conventional therapy targeted to tumor epithelial cells for its high invasiveness and migratory activity [54, 55]. Here we showed that CAFs' tumor‐promoting activity can be targeted by inhibiting super‐enhancers using agents such as BET inhibitors, and its addition to traditional therapy targeting cancer cells can become an efficient therapeutic strategy against scirrhous gastric cancer. Further investigations, including in vivo experiments, are needed. Although BET inhibitors did not achieve high efficacy due to their toxicity in initial clinical trials [56], selection of cancer types in which super‐enhancers are involved both in cancer and stromal cells may help stratify patients suitable for the use of BET inhibitors.

A limitation of this study is the use of primary CAFs rather than tumor tissues, which raises a concern that primary CAFs may not fully reflect the in vivo tumor context. However, in line with our study, it is reported that α‐SMA (encoded by ACTA2, a myCAF marker) is highly expressed in fibroblasts of scirrhous gastric cancers than in those of non‐scirrhous gastric cancers by immunohistochemical analysis of clinical specimens [57]. Although validation using single‐cell RNA sequencing would be ideal, our findings are considered to at least partly reflect the in vivo tumor tissue context. Second, we were unable to pinpoint soluble mediators responsible for the migration‐promoting activity of scirrhous CAFs. Since podoplanin was the most upregulated gene in scirrhous CAFs by RNA‐seq (Figure 2D) and is a membrane protein with a secreted form [58], we examined its concentration in conditioned media but were unable to detect its expression (data not shown). A highly sensitive secretome analysis may be required to address this issue.

In conclusion, we found that scirrhous CAFs were characterized by highly acetylated enhancers and super‐enhancers, in TGFβ1 and NF‐κB target genes, that they can be therapeutically targeted, and that even "normal" fibroblasts in scirrhous cancer patients had tumor‐promoting activity.

Author Contributions

Yoshimi Yasukawa: conceptualization, data curation, funding acquisition, investigation, writing – original draft. Naoko Hattori: conceptualization, data curation, formal analysis, funding acquisition, investigation, supervision, writing – original draft. Yu‐Yu Liu: data curation, formal analysis, funding acquisition, investigation, software, writing – original draft. Masayuki Tobo: data curation, formal analysis. Genki Yamagishi: investigation. Takahiro Irie: investigation. Shigeki Sekine: investigation, resources. Tohru Kiyono: funding acquisition, investigation. Satoshi Yamashita: data curation, investigation, methodology. Yukinori Yamagata: resources. Takaki Yoshikawa: resources. Yasuyuki Seto: resources. Toshikazu Ushijima: supervision, writing – original draft.

Funding

This research was supported by AMED under Grant Number 20jk0210009 to T.K., AMED under Grant Number JP22gm1310006 to T.U., JSPS KAKENHI Grant Number JP21K20944 to Y. Yasukawa, JSPS KAKENHI Grant Number JP20K07628 to N.H., and JSPS KAKENHI Grant Number JP20K16347 to Y.‐Y.L.

Ethics Statement

This study (protocol number 2013‐073) was approved by the Institutional Review Boards at the National Cancer Center and was conducted according to the institutional guidelines.

Consent

In this study, written informed consent was obtained from all participants.

Conflicts of Interest

Tohru Kiyono and Toshikazu Ushijima are Editorial board members of Cancer Science. Yu‐Yu Liu and Toshikazu Ushijima had a research contract with Dazzeon Biotech Private Limited. Toshikazu Ushijima has received research funding from Sysmex Corporation. The other authors declare no conflicts of interest.

Supporting information

Data S1: cas70408‐sup‐0001‐Supinfo.pdf.

CAS-117-1894-s001.pdf (5.7MB, pdf)

Acknowledgments

We thank Ms. Mika Wakabayashi for assistance with the ChIP assay and Mr. Hari Tahli for professional English editing. ChIP‐seq for H3K4me1 and H3K4me3 was performed using NextSeq2000 system (Illumina) with support from the Early Life Stage of AMED‐CREST/PRIME, and we thank Dr. Hiroshi Sugishita for his assistance. This work was supported by research equipment shared in the Institute for Molecular and Cellular Regulation Joint Usage/Research Support Center (IMCR‐JURSC), Gunma University.

Contributor Information

Naoko Hattori, Email: naoko.hattori@gunma-u.ac.jp.

Toshikazu Ushijima, Email: tushijima142@hoshi.ac.jp.

Data Availability Statement

The datasets used in this study are available at the Gene Expression Omnibus (GEO) database (accession nos. GSE194259, GSE194261, GSE307738, GSE308330, and GSE322674; https://www.ncbi.nlm.nih.gov/geo/).

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Associated Data

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

Supplementary Materials

Data S1: cas70408‐sup‐0001‐Supinfo.pdf.

CAS-117-1894-s001.pdf (5.7MB, pdf)

Data Availability Statement

The datasets used in this study are available at the Gene Expression Omnibus (GEO) database (accession nos. GSE194259, GSE194261, GSE307738, GSE308330, and GSE322674; https://www.ncbi.nlm.nih.gov/geo/).

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