Inactivation of the Euchromatic Histone-Lysine N-Methyltransferase 2 Pathway in Pancreatic Epithelial Cells Antagonizes Cancer Initiation and Pancreatitis-Associated Promotion by Altering Growth and Immune Gene Expression Networks

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive, painful disease with a 5-year survival rate of only 9%. Recent evidence indicates that distinct epigenomic landscapes underlie PDAC progression, identifying the H3K9me pathway as important to its pathobiology. Here, we delineate the role of Euchromatic Histone-lysine N-Methyltransferase 2 (EHMT2), the enzyme that generates H3K9me, as a downstream effector of oncogenic KRAS during PDAC initiation and pancreatitis-associated promotion. EHMT2 inactivation in pancreatic cells reduces H3K9me2 and antagonizes KrasG12D-mediated acinar-to-ductal metaplasia (ADM) and Pancreatic Intraepithelial Neoplasia (PanIN) formation in both the Pdx1-Cre and P48Cre/+ KrasG12D mouse models. Ex vivo acinar explants also show impaired EGFR-KRAS-MAPK pathway-mediated ADM upon EHMT2 deletion. Notably, KrasG12D increases EHMT2 protein levels and EHMT2-EHMT1-WIZ complex formation. Transcriptome analysis reveals that EHMT2 inactivation upregulates a cell cycle inhibitory gene expression network that converges on the Cdkn1a/p21-Chek2 pathway. Congruently, pancreas tissue from KrasG12D animals with EHMT2 inactivation have increased P21 protein levels and enhanced senescence. Furthermore, loss of EHMT2 reduces inflammatory cell infiltration typically induced during KrasG12D-mediated initiation. The inhibitory effect on KrasG12D-induced growth is maintained in the pancreatitis-accelerated model, while simultaneously modifying immunoregulatory gene networks that also contribute to carcinogenesis. This study outlines the existence of a novel KRAS-EHMT2 pathway that is critical for mediating the growth-promoting and immunoregulatory effects of this oncogene in vivo, extending human observations to support a pathophysiological role for the H3K9me pathway in PDAC.


INTRODUCTION
Pancreatic cancer remains a devastating disease, currently ranking 3rd for cancer-related deaths in the United States and predicted to rank 2nd by 2030 (Rahib et al., 2014). Pancreatic ductal adenocarcinoma (PDAC), the most common type, arises through a stepwise progression from low-grade to high-grade Pancreatic Intraepithelial Neoplasia (PanINs) and eventually leading to invasive adenocarcinoma (Andea et al., 2003). The transitions through increasingly aggressive lesions are accompanied by accumulation of genetic and epigenetic alterations (Macgregor-Das and Iacobuzio-Donahue, 2013;Lomberk et al., 2019). Activating mutations in the KRAS gene are almost consistently the initiator and present even in low-grade PanINs (Hezel et al., 2006). As a result, oncogenic KRAS, in particular Kras G12D , serves as the cornerstone of genetically engineered mouse models (GEMM) for PanIN lesions, as well as PDAC, when crossed to additional genetic models (Herreros-Villanueva et al., 2012). Activation of a Kras G12D allele in mice induces hyperplasia, acinar-to-ductal metaplasia (ADM), and PanIN formation (Hingorani et al., 2003). Given the lack of additional genetic events prior to higher-grade PanIN lesions, these transitions from hyperplasia and ADM through establishing low-grade PanIN are thought to occur at an epigenomic level (Shibata et al., 2018). In addition, evidence supports that the heterogeneity of PDAC results from the presence of distinct epigenomic landscapes, which also carries the potential to induce certain types of plasticity between PDAC subtypes (Lomberk et al., 2018). Therefore, dissecting the role of various epigenomic pathways should provide important insights into PDAC tumorigenesis.
Histone H3 lysine 9 (H3K9) methylation is emerging as an important transcriptional regulatory and epigenetic pathway in pancreatic cancer (McDonald et al., 2017;Lomberk et al., 2019). Histone lysine methylation plays a critical role, along with DNA methylation, for long-term epigenetic maintenance, as well as propagation of overall chromosome structural features and stability (Sims et al., 2003;Martin and Zhang, 2005). Euchromatic histone-lysine N-methyltransferase 2 (EHMT2/G9a) is the main SET domain-containing histone lysine methyltransferase (HMT) responsible for catalyzing H3K9 mono-and di-methylation (H3K9me1 and H3K9me2) (Casciello et al., 2015). The fact that EHMT2 functions in the regulation of various processes, including cellular differentiation, proliferation, epithelial-tomesenchymal transition (EMT), senescence, DNA replication and DNA repair among others, has suggested a key role for this protein in the epigenetics of human cancers (Shinkai and Tachibana, 2011;Dong et al., 2012;Casciello et al., 2015;Yang et al., 2017). Indeed, EHMT2 is upregulated in many cancers, including PDAC (Casciello et al., 2015), in which its expression correlates with shorter times to relapse and survival (Pan et al., 2016). Pharmacological inhibition of EHMT2 in the PANC-1 PDAC cell line has implicated potential roles in senescence, autophagy and overcoming chemotherapy resistance (Yuan et al., 2012(Yuan et al., , 2013Pan et al., 2016). However, the impact that its function has on the effect of activated oncogenes, such as KRAS, during PDAC development in vivo remained to be defined and constitutes the main goal of the current study. Initial studies in P48 Cre/+ Kras G12D mice showed that EHMT2 deficiency modifies PanIN progression and animal survival (Kato et al., 2020). The current study uses several in vivo along with in vitro models to extend mechanistic information on the impact of EHMT2 in Kras G12D -mediated initiation. In addition, we also study the role of this protein in the context of inflammation-associated pancreatic cancer using pancreatitis-induced neoplastic promotion. We provide new mechanistic information that supports the dysregulation of gene expression networks antagonistic to cell growth and induction of P21/β-galactosidase-positive senescence. We also report that oncogenic KRAS regulates EHMT2 levels and the formation of its complex with EHMT1 and WIZ, leading to increased levels of its enzymatic product, the H3K9me2 mark. We find reduced inflammatory responses in pancreas tissue from animals carrying EHMT2 inactivation compared to Kras G12D mice retaining the wildtype allele, which is also reflected by functionally coherent gene expression networks. Moreover, genetic inactivation of EHMT2 sustains the antagonistic effects on initiation of Kras G12D -driven neoplastic cell growth even in the pancreatitis-associated promotion model. This phenotypic response is accompanied by alterations in both cell growth and immunoregulatory gene expression networks, thereby affecting the tumor microenvironment through disruption of this pathway in epithelial cells. Combined, these data designate EHMT2 as part of the Kras G12D pathway, as well as reveal a role for this epigenetic regulator in the growth-promoting effects and inflammatory response necessary for Kras G12D -induced carcinogenesis.

Cell Lines and Reagents
Mouse iKras 4292 cell lines were obtained from Dr. Marina Pasca di Magliano [University of Michigan] (Collins et al., 2012). Cells were maintained in RPMI 1640 media supplemented with 10% (v/v) FBS and 10 µg/ml doxycycline hyclate (doxy, Sigma Aldrich, Cat# D9891) for regular culture. For Kras G12D induction experiments, cells were deprived of doxy at least 48 h for beginning experiments (0 h, baseline). Then, fresh media containing doxy 10 µg/ml was added, and cells maintained under culture during multiple time intervals (12, 24 and 48 h). Human hTERT-E6/E7-HPNE (ATCC Cat# CRL-4037, RRID: CVCL_C468) and hTERT-E6/E7-HPNE-KRAS G12D (ATCC Cat# CRL-4039, RRID: CVCL_C470) pancreatic cell lines were obtained from ATCC and maintained in appropriate media according to recommendations. All cells were cultured at 37 • C in a humidified incubator with 5% CO2 and were used to a maximum of 30 passages. All cell lines tested negative for Mycoplasma with last testing performed in July 2020.

Western Blot Analysis
Mouse pancreas (∼100 mg) was cut in small pieces and homogenized in protein extraction buffer [10 mM Tris-HCl, 1 mM EDTA, 1% (v/v) Triton-X100, 1% (w/v) Sodium Deoxycholate, 0.1% (w/v) SDS, 140 mM NaCl and 1 mM PMSF] with freshly added protease and phosphatase inhibitors (Thermo Fisher Scientific). Homogenized tissue was moved to a 2 mL microcentrifuge tube containing 1 stainless steel bead (7 mm diameter) and further dissociated using TissueLyser LT (2 min at 50 Hz). The lysate was then sonicated twice (amplitude 5 for 10 s) and supernatant was cleared by centrifugation (10,000 rpm, 10 min, 4 • C). HPNE and iKras proteins were collected from cells by lysis in protein extraction buffer supplemented with phosphatase and protease inhibitors. Equal amounts of protein from pancreas or cell lysates were electrophoresed on 12% SDS-PAGE gels and transferred to nitrocellulose membranes (GE Healthcare). Membranes were blocked in either 5% (w/v) milk or 3% (w/v) BSA for 1 h, and primary antibody incubations were performed overnight at 4 • C with rocking. Supplementary Table 1 contains primary antibodies used. Antimouse or anti-rabbit HRP-conjugated secondary antibodies (1:5000, Millipore) were incubated on the membranes for 1 h at room temperature with agitation, followed by detection with chemiluminescence (Thermo Fisher Scientific). Quantification of bands in n = 3 experiments was completed using ImageJ and statistical significance determined by Student's t-tests in GraphPad Prism 7.
Immunofluorescence, Proximity Ligation Assays (PLA) and Confocal Microscopy iKras 4292 cells were stimulated with doxy at the indicated intervals, fixed using 4% Formaldehyde and washed three times with 1× PBS. Cells were permeabilized using 0.2% Triton X-100 for 10 min, PBS washed and blocked with 1% (w/v) BSA in PBS-Tween 20 solution. Slides were then incubated with EHMT2, EHMT1 and WIZ primary antibodies at 4 • C overnight and labeled using Alexa Fluor-conjugated secondary antibodies. For proximity ligation assays (PLA) assays, the Duolink PLA Starter Kit (Sigma Aldrich, Cat# DUO92102) was used according to manufacturer's instructions. Coverslips were mounted using Prolong Gold antifade mounting media (with DAPI, Life technologies, Cat# P36930). Antibodies used are listed in Supplementary Table 1. Images were acquired using a Zeiss LSM510 confocal microscope with a 63× magnification objective.

Immunoprecipitation (IP) and Mass Spectrometry
Immunoprecipitation (IP) of EHMT2 was performed by conjugating the EHMT2 antibody (Thermo Fisher Scientific Cat# PA5-34971, RRID: AB_2552320) or control IgG antibody to Protein A/G Magnetic Beads (Thermo Fisher Scientific) through disuccinimidyl suberate crosslinking. iKras 4292 cells were grown and then stimulated with doxy for 24 h. Cells were lysed with IP Lysis/Wash Buffer (Thermo Fisher Scientific-Pierce), and lysates were incubated overnight with the antibody conjugates at 4 • C. Immunoprecipitated complexes were washed, eluted, and run on a 4-15% Criterion TM Tris-HCl Protein Gel (Bio-Rad). The gel was subsequently visualized with BioSafe TM Coomassie Stain (Bio-Rad). Each gel lane was de-stained, dehydrated, dried, and subjected to trypsin digestion. Subsequently, liquid chromatography (LC)-ESI-MS/MS analysis was performed on a Thermo Scientific LTQ Orbitrap mass spectrometer at the Mayo Clinic Proteomics Core.
To induce chronic pancreatitis, caerulein was administered via IP injection to 4-week-old mice once a day, five times a week, for a total of 4 weeks at a dose of 50 µg/kg. Animals were given 7 days with no treatment before sacrifice to allow recovery. Animal and pancreas weights were recorded at the time of sacrifice and tissue was taken for RNA, protein and histological analysis.

Immunohistochemistry
Immunohistochemistry was performed on mouse pancreas tissue as described previously (Mathison et al., 2013). Primary antibodies (Supplementary Table 1) were incubated overnight at 4 • C. Slides were developed with Nova Red (Vector Laboratories, Cat# SK-4800) and counterstained with Mayer hematoxylin. Five random fields (10× objective) per slide, containing at least 1,000 cells per field, were imaged, and counted.

3D Acinar Culture
CAGGCre-ER TM and CAGGCre-ER TM ;EHMT2 fl/fl mice were euthanized and pancreas immediately injected with 2 mL of chilled collagenase P (1.33 mg/ml), dissected and cut into small pieces for digestion (20 min at 37 • C with gentle shaking). Acinar cells were collected by centrifugation and resuspended in 3D culture base medium (RPMI 1640 medium supplemented with 1% FBS, 0.1 mg/ml soybean trypsin inhibitor, sodium pyruvate 1× and antibiotics). 96-well plates were pre-coated with Matrigel (Corning, Cat# 356231, 30 µL) for 1 h at 37 • C. Cell suspensions were mixed 1:1 with Matrigel and plated (100 µL/well). The cell/Matrigel mix was allowed to solidify for 1 h at 37 • C before addition of 175 µL 3D culture media. For the first 48 h, DMSO or 4-OHT (10 mmol/L) was added, followed by EGF (20 ng/mL) or TGFα (50 ng/mL) for an additional 5-6 days (Martinelli et al., 2016). Pictures from ductal structures were taken after 8 days in culture using a Canon EOS Rebel Xsi camera mounted on a Nikon Eclipse TS100 microscope at 10× magnification. Duct size was measured using ImageJ software, and plotted values represent fold-change of treated groups over respective controls.

RNA Extraction
For RNA extraction from tissue, a section of pancreas was taken at time of euthanasia, minced in RNAlater and snap frozen with liquid nitrogen. RNA extraction was completed with ToTALLY RNA Kit (Ambion, Cat# AM1910) according to manufacturer's protocols. Briefly, frozen samples were lysed with tissue Denaturation Solution and disrupted in the TissueLyser LT (Qiagen, 2 min at 50 Hz) with a single, 7 mm stainless steel bead. RNA isolation continued with Phenol:Chloroform:IAA and Acid-Phenol:Chloroform extractions to the aqueous phase and a final isopropanol precipitation. Precipitated RNA was cleaned up according to Qiagen's protocol on the miRNeasy column (Qiagen, Cat# 217004), with an on-column DNA digestion and RNaseOUT (Invitrogen, Cat# 10777019) added to final elution to reduce degradation during storage at −80 • C. Isolation of RNA from cells was completed according to Qiagen's protocol for the RNeasy kit, including an on-column DNase digestion.

RNA-seq and Bioinformatic Analysis
RNA was quantified by Qubit (Invitrogen) and quality assessed with a Fragment Analyzer (Agilent), with the highest quality (typically RINs > 6, DV200 > 80%) utilized for library preparations. Pancreas RNA was prepared and sequenced in the Mayo Clinic Medical Genomics Core using the Illumina TruSeq RNA v2 library preparation kit and the Illumina High Seq-2000 with 101 bp paired end reads. Reads were aligned to the mouse reference transcriptome Gencode vM23 (GRCm38.p6) with at least 24 million mapped read pairs acquired per sample. Sequencing reads were processed through the GSPMC workflow including MapRseq3 (Kalari et al., 2014) and differential expression calculated by EdgeR (McCarthy et al., 2012). Differentially expressed genes (DEGs) were filtered based on a false discovery rate (FDR) < 0.1 and an absolute FC ≥ | 1.5| called between at least one condition and the reference control sample. For RNA-seq on caeruleintreated animals, DEGs were filtered with FC ≥ | 2| and FDR < 0.05. Pathway analysis of DEGs was completed with RITAN (R package-rapid integration of annotation, network, and molecular database) (Zimmermann et al., 2019), which queries different annotation resources to analyze enrichment for an input set of genes. RITAN performs a hypergeometric test and generates FDR adjusted p-values, called q-values, for assessing pathway significance, which queries different annotation resources to analyze enrichment for an input set of genes. The Molecular Signatures Database (MSigDB) hallmark gene set collection (Liberzon et al., 2015) was used as the annotation resource. Pathways with q-values < 0.05 were considered enriched. Gene network and upstream regulatory analyses were performed using Ingenuity R Pathway Analysis (IPA R ; Qiagen). To quantitatively determine the percentage of infiltrating immune cell types, we utilized a "digital cytometry" method called the quanTIseq deconvolution algorithm, which estimates the absolute proportions of relevant infiltrating immune cell types from bulk RNA-seq profiles . The cell type fraction scores provided by this method allow intra-sample and inter-sample comparisons of 10 immune cell type fractions. We applied the quanTIseq method through an R package called Immunedeconv (Sturm et al., 2019) on DEGs from the Pdx1-Cre;EHMT2 fl/fl , Pdx1-Cre;LSL-Kras G12D , and Pdx-Cre;LSL-Kras G12D ;EHMT2 fl/fl dataset (1039 DEGs), as well as the caerulein-treated animals dataset (4654 DEGs).

Reverse Transcriptase Quantitative PCR (RT-qPCR)
Reverse transcriptase was performed using RT 2 first strand kit (Qiagen) following manufacturer's protocol. Real-time PCR was performed in a volume of 20 ul using SYBR Green Master Mix and CFX96 Real Time System (Bio-Rad). Primer sequences are shown in Supplementary Table 2. RT 2 Profiler PCR Array (SA Biosciences, Qiagen) was used to examine the expression patterns of 84 genes involved in cell cycle. The array was performed Frontiers in Cell and Developmental Biology | www.frontiersin.org following manufacturer instructions. ddCT was obtained using Qiagen software and all groups were normalized to Pdx1-Cre mice, with an absolute FC ≥ | 1.5| for the generation of a heatmap using R-studio.

Senescence β-Galactosidase Staining
Senescence-associated β-galactosidase activity was assessed in fresh pancreas tissue using the Cell Signaling β-Galactosidase Staining kit, according to manufacturer's protocol (Cell Signaling Technologies, Cat# 9860S). Briefly, under terminal anesthesia, pancreas from LSL-Kras G12D ;EHMT2 +/+ and LSL-Kras G12D ;EHMT2 fl/fl with both Pdx1-Cre and P48 Cre/+ drivers were collected, washed in PBS (1×) and placed in a well of a 12-well dish containing 1 mL of fixative solution for 15 min. Pancreas were then rinsed twice with PBS (1×) and stained with β-galactosidase solution at 37 • C overnight in a dry incubator. Next morning, pancreata were washed with PBS (1×), and images acquired.

Ethics Statement
Animal care and all protocols were reviewed and approved by the Institutional Animal Care and Use Committees of Mayo Clinic Rochester (IACUC protocols A00002240-16 and A24815) and the Medical College of Wisconsin (AUA00005963).

Data Availability
RNA-seq datasets that support the findings of this study have been deposited to the public database repository Gene Expression Omnibus (GEO) under accession code GSE169525.
To mechanistically complement our in vivo data, we next investigated whether EHMT2 is involved in the ADM process, using a genetically engineered ex vivo approach with acinar explants from a tamoxifen-inducible model of EHMT2 knockout. This model carries a CAGGCre-ER TM transgene, which has the chicken β-actin promoter/enhancer coupled with the cytomegalovirus immediate-early enhancer to drive high levels of Cre expression, allowing this enzyme to translocate into the nucleus (Hayashi and McMahon, 2002) upon tamoxifen treatment. Acinar cells from CAGGCre-ER TM and CAGGCre-ER TM ;EHMT2 fl/fl animals were isolated and grown in 3D matrigel in the absence (−) or presence (+) of 4-Hydroxytamoxifen (4-OHT) to inactivate EHMT2. Western blot showed that EHMT2 protein levels were reduced after 4-OHT treatment ( Figure 3A). Subsequently, acinar cell explants were cultured in presence of EGF or TGFα for 5-6 days to activate the KRAS-MAPK pathway, which induces ex vivo ADM formation. Phase microscopy of 3D cultures showed that EGF and TGF-α induced duct-like structures from acini isolated from CAGGCre-ER TM (−/+4-OHT) controls, demonstrating ADM formation ( Figure 3B). No significant difference was observed in the size of duct-like structures formed from acini of CAGGCre-ER TM alone animals either in the absence or presence of 4-OHT upon EGF treatment (17.51 ± 0.6 FC with DMSO vs. 19.07 ± 0.6 FC with 4-OHT) or after TGFα treatment (14.3 ± 0.7 FC with DMSO vs. 15.05 ± 1.4 FC with 4-OHT; Figure 3B). CAGGCre-ER TM ;EHMT2 fl/fl without 4-OHT treatment also demonstrated ADM formation after EGF and TGFα treatment ( Figure 3C). However, upon EHMT2 inactivation (+4-OHT), the quantification of duct-like structures revealed significantly reduced ADM formation with EGF (19.08 ± 0.7 FC with DMSO vs. 8.36 ± 0.6 FC with 4-OHT; p < 0.001) or TGFα (17.58 ± 0.5 FC with DMSO vs. 8.19 ± 0.75 FC with 4-OHT; p < 0.001; Figure 3C). Thus, congruent with the antagonism to Kras G12D -mediated ADM and PanIN initiation found in LSL-Kras G12D ;EHMT2 fl/fl mice, loss of EHMT2 impairs the phenotypic conversion of acinar cells to more duct-like structures in 3D ex vivo cultures stimulated with growth factors that activate the EGF-KRAS pathway, further supporting the rigor of our in vivo observations. Kras G12D Induces Heterotrimerization of the EHMT2-EHMT1-WIZ Complex, Increasing H3K9me2 Levels We also investigated whether Kras G12D behaves as an upstream regulator of EHMT2 activity. For this purpose, we utilized a GEMM-derived PDAC cell model in which oncogenic Kras G12D expression is induced by doxycycline (Collins et al., 2012) (iKras 4292) to evaluate downstream effects on the EHMT2-H3K9me2 epigenetic pathway. We induced Kras G12D expression and collected lysates at various timepoints to examine levels of proteins from this pathway ( Figure 4A). Kras G12D protein levels were detected at 12 h, reaching maximum after 48 h (10.57 ± 1.6-fold change (FC) vs. 0 h; p < 0.01; Supplementary Figure 3A). We found that Kras G12D increased protein levels for both, H3K9 methyltransferases EHMT2 and EHMT1, peaking at 48 h (4.6 ± 1.2 FC for EHMT2 at 48 h vs. 0 h, p < 0.05, and 4.18 ± 1.7 FC for EHMT1 at 48 h compared to 0 h, p < 0.01; Supplementary Figure 3A). EHMT2 and EHMT1 form an enzymatically active heterotrimer with WIZ, which stabilizes the complex on chromatin (Simon et al., 2015). We also observed increased levels of WIZ (3.2 ± 1.3 FC at 48 h vs. 0 h; p < 0.05; Supplementary Figure 3A). Levels of the H3K9me2 mark increased upon Kras G12D induction as well (2.50 ± 0.4 FC at 48 h vs. 0 h; p < 0.001; Supplementary Figure 3A). In addition, using immunofluorescence-based FIGURE 3 | EHMT2 inactivation impairs EGFR-KRAS-MAPK pathway-driven ADM in primary acinar cell explant cultures. (A) Acinar cell explant cultures derived from CAGGCre-ER TM ;EHMT2 +/+ and CAGGCre-ER TM ;EHMT2 fl/fl animals were grown in the absence (-) or presence (+) of 4-Hydroxytamoxifen (4-OHT) to achieve EHMT2 knockout. Left: Western blot evaluation of protein lysates from acinar explant cultures was performed to confirm that 4-OHT treatment reduced EHMT2 levels in cells derived from CAGGCre-ER TM ;EHMT2 fl/fl mice. Alpha-tubulin was used as a loading control. Right: Graph depicts relative densitometry values for EHMT2 normalized to tubulin. Representative phase contrast images of CAGGCre-ER TM ;EHMT2 +/+ (B) and CAGGCre-ER TM ;EHMT2 fl/fl (C) explant cultures after 5-6 days of EGF (20 ng/mL) or TGFα (50 ng/mL) exposure to induce ADM. Cells were also treated with vehicle (DMSO) or 4-OHT to inactivate EHMT2. Right: Quantification of duct-like structures is shown as fold-change in size relative to control. * indicates p-value ≤ 0.05, and *** indicates p-value ≤ 0.001. All data is expressed as mean ± SEM (experiment performed in triplicate).
Next, since stability and methyltransferase activity depends on formation of the complex (Ueda et al., 2006), we immunopurified EHMT2 from iKras 4292 cells and performed mass spectrometry, which revealed increased hetero-trimerization of EHMT2, EHMT1, and WIZ after 24 h of Kras G12D expression (Supplementary Figure 3G). We also used PLA to detect, in situ, the interaction between endogenous EHMT2 and EHMT1 or WIZ (Figures 4C,D and Supplementary Figures 4A,B). PLA signals from EHMT2 + EHMT1 complexes increased after Kras G12D induction, with MFI of 6.29e3 ± 3.98e2 at baseline and 1.75e4 ± 1.12e3 after 24 h (p < 0.001, Figure 4C). This effect was also accompanied by increased PLA signals for EHMT2 + WIZ complexes upon Kras G12D expression (MFI of 7.89e3 ± 6.47e2 at baseline vs. 1.33e4 ± 1.16e3 at 24 h, p < 0.001, Figure 4D). The induction of EHMT2, EHMT1, and WIZ protein levels, as well as the formation of their complex detected by mass spectrometry and PLA are important since we did not detect changes in their mRNA levels either in the absence or presence of Kras G12D (Supplementary Figure 4C). This result was recapitulated in the human KRAS G12D cell models, as we found no statistical difference in EHMT2, EHMT1 and WIZ transcript levels from HPNE cells compared to HPNE-KRAS G12D cells (Supplementary Figure 4D). These comparable transcript levels in the absence and presence of oncogene activation suggest that KRAS G12D -effects on the EHMT2 complex are possibly not via transcriptional regulation of these genes but rather potentially due to protein stability. Given this result, we also performed staining for the H3K9me2 mark, by immunohistochemistry (IHC) in wild-type and Kras G12D expressing mice to translate these effects to the in vivo situation. Pancreata were harvested from both, Pdx1-Cre;LSL-Kras G12D and P48 Cre/+ ;LSL-Kras G12D mouse models. Upon quantification of positively stained nuclei compared to total nuclei, we found that Pdx1-Cre;LSL-Kras G12D animals had higher levels of H3K9me2 compared to control Pdx1-Cre mice (17.1 ± 2.7% vs. 8.0 ± 1.4%, p < 0.05; Figure 4E). Similar results were obtained when Kras G12D activation was driven by Cre expression from the Ptf1a-P48 promoter via knock-in (17.5 ± 1.3% in P48 Cre/+ ;LSL-Kras G12D mice compared to 9.0 ± 2.1% in P48 Cre/+ controls, p < 0.01; Figure 4E). Thus, based on these collective data, we conclude that EHMT2, EHMT1 and WIZ proteins form a stable complex upon Kras G12D activation, which leads to enhanced deposition of the H3K9me2 mark, supporting a role for this epigenetic pathway downstream of the most commonly mutated oncogene in PDAC.

EHMT2 Inactivation Establishes a Transcriptional Landscape Antagonistic to PDAC Initiation
Oncogenic KRAS mounts transcriptional responses that program the growth-promoting phenotype that characterizes pancreatic cancer initiation (Waters and Der, 2018). This observation, along with the fact that EHMT2 is a well-known regulator of transcriptional responses (Shankar et al., 2013), led us to carry out RNA-seq from whole pancreas to evaluate gene expression networks affected by EHMT2 inactivation. We  Figure 5B). Next, we performed calculations of distances among cluster centroids for experimental samples and controls (marked by empty circles in Figure 5B), as a similarity measure among genetic conditions. The distance between the EHMT2 inactivated groups was 21.7 while the distance between Pdx1-Cre;EHMT2 fl/fl and Pdx1-Cre;LSL-Kras G12D was 46.8 and between the two Kras G12D activated groups was 48.7. Thus, EHMT2 inactivation in the Pdx1-Cre;LSL-Kras G12D EHMT2 fl/fl animals clustered much closer to Pdx1-Cre;EHMT2 fl/fl and significantly separated from Kras G12D mice with EHMT2 intact, indicating that EHMT2 inactivation is characterized by a transcriptional profile that is functionally antagonistic to oncogenic KRAS. Hierarchical clustering of normalized DEG across all three conditions (1039 genes) revealed four major expression patterns ( Figure 5C). When compared to Pdx1-Cre controls and Kras G12D animals, the 245 genes defining cluster 1 (green) were upregulated in EHMT2 fl/fl and Kras G12D ;EHMT2 fl/fl mice, while 647 genes characterized cluster 2 (yellow) with genes downregulated upon EHMT2 inactivation, either alone or with Kras G12D . Cluster 3 (pink) displayed 65 genes upregulated in Kras G12D animals, and Cluster 4 (purple) was defined by 82 genes downregulated in Kras G12D animals, independent of EHMT2 status. Notably, ADM and PanIN-related mRNA markers, such as Gkn1, Gkn2, and Muc5a, were downregulated in Pdx1-Cre;LSL-Kras G12D ;EHMT2 fl/fl animals (Supplementary Figure 5A), supporting our histological observations. Together, these studies revealed that mice with EHMT2 inactivated in their pancreas epithelial cells displayed a gene expression pattern antagonistic to the Kras G12D -regulated gene expression program.

Growth-Inhibitory Gene Networks Are a Hallmark of EHMT2 Inactivation During KRAS-Mediated Initiation
We used different tools for data mining the biological and mechanistic significance of the gene expression networks identified by RNA-seq. Hierarchical clustering identified four main patterns of gene expression. Cluster 1 genes represented those upregulated upon EHMT2 inactivation that remained elevated in EHMT2 fl/fl crossed to Kras G12D mice. Notably, cluster 1 included a gene network corresponding to the P21 pathway (q-value = 1.81 × 10 −5 ; Figure 5D and Supplementary Table 4), which causes growth arrest. Cluster 2 genes, downregulated by EHMT2 inactivation, involved gene networks that participate in KRAS signaling (q-value = 1.5 × 10 −10 ) and immunoregulatory/inflammationrelated pathways (q-value = 2.3 × 10 −14 ), (e.g., type I interferon response, IL6-Jak-Stat3 signaling, and IL2-Stat5 signaling; Supplementary Table 4). This is important since inflammatory responses are required for Kras G12D -mediated initiation (di Magliano and Logsdon, 2013). No biological pathway was found to be significant in cluster 3, while cluster 4 contained genes downregulated in Kras G12D animals, which participate in EMT (q-value = 2.3 × 10 −2 ). Additional gene network enrichment and visualization analyses using semantic-based algorithms (Krämer et al., 2014) showed that EHMT2 inactivation results in antagonism of transcriptional networks corresponding to inflammatory responses as part of gene networks that participate in KRAS signaling ( Figure 5E). Upstream Regulatory Analysis linked the upregulation of Cdkn1a/p21, Chek2, Bax, Jun, and Ccng1, among other genes, to a P53-like transcriptional network activated in EHMT2 fl/fl mice, and this molecular phenotype was transferred to the Kras G12D ;EHMT2 fl/fl mice ( Figure 5F). Therefore, EHMT2 inactivation antagonizes oncogenic Kras G12D at the molecular level, at least in part, by upregulating wellknown pathways for cell cycle inhibitory checkpoints, though also unexpectedly, downregulating inflammatory responses.
RNA-seq counts from pancreas are dominated by the high expression of multiple key digestive enzyme genes (Hoang et al., 2016), occasionally masking genes expressed at lower levels that can be causal of phenotypes. For this reason, we also utilized more sensitive, pathway-specific RT-qPCRbased gene expression profiling focused on cell cycle-related transcripts to monitor the status of the entire gene expression network that regulates cell cycle. Results from EHMT2 fl/fl , Kras G12D , or Kras G12D ;EHMT2 fl/fl mice were normalized to those from Pdx1-Cre mice. Indeed, this approach revealed that Kras G12D ;EHMT2 fl/fl and EHMT2 fl/fl animals clustered closer to each other than with Kras G12D , sharing a similar expression profile for cell cycle-related genes (Supplementary Figure 5B). Genes forming Cluster 1 were involved in cell cycle arrest and senescence after replication stress (Cdkn1a/p21 and  Color scale denotes -log 10 (q-value) for significance of each represented pathway. (E) The inflammatory gene network enriched in Cluster 2, which represents genes upregulated by Kras G12D activation but downregulated in animals carrying the EHMT2 fl/fl allele. Gene fold changes with respect to controls are represented with red (up) and blue (down) nodes. (F) Upstream regulatory analysis of genes in Cluster 1, which represent the P21 pathway upregulated in EHMT2 fl/fl mice. Color scheme of nodes is same as in panel (E). Outlined central node represents the predicted link with the upstream regulator, TP53, while orange lines and blue lines indicate predicted relationships that lead to activation or inhibition, respectively. Yellow lines designate that the predicted relationship is inconsistent with gene expression, and gray lines denote no predicted effect. upregulated in both EHMT2 fl/fl and Kras G12D ;EHMT2 fl/fl mice (orange, Supplementary Figure 5B). Genes within cluster 2 contained networks that also function in replication stress responses (Atr, Wee1, Brca1, and Rad9a), which often also result in senescence induction (Gralewska et al., 2020), as well as genes, including Skp2 and Cdc6, involved in origin licensing during DNA replication (Cook, 2009). These genes ranged in levels from unchanged to slightly increased by Kras G12D but underwent further upregulation upon EHMT2 inactivation, whether in the absence or presence of Kras G12D (purple, Supplementary Figure 5B). Cluster 3 genes were characterized by the presence of the replication stress kinase Chek1 and several cyclins (Ccna2, Ccnb1, Ccnd1, and Ccnd2). These genes were downregulated by Kras G12D alone but markedly upregulated in both EHMT2 fl/fl and Kras G12D ;EHMT2 fl/fl mice (green, Supplementary Figure 5B). Thus, combined these data suggest that EHMT2 inactivation alone increases the levels of cell cycle regulatory molecules known to function as checkpoints to arrest cell growth in response to replication stress, congruent with emerging data suggesting that this protein localizes and works at the replication fork (Estève et al., 2006;Dungrawala et al., 2015;Ferry et al., 2017) and pharmacological data that has implicated a role of this protein in senescence without much mechanistic insight (Yuan et al., 2012). Notably, these expression networks were inherited when EHMT2 fl/fl mice were crossed to the Kras G12D background. While cluster 4 was primarily formed by Kras G12D -downregulated transcripts, its pattern displayed a mixed profile of downregulated, unchanged, and minimally upregulated transcripts in the EHMT2 fl/fl and Kras G12D ;EHMT2 fl/fl mice (red, Supplementary Figure 5B). EHMT2 fl/fl and Kras G12D ;EHMT2 fl/fl mice blunted the Kras G12Dmediated downregulation of transcripts in this cluster, which encompassed DNA damage and apoptosis-related genes. Thus, these data further support the significant role that EHMT2 inactivation plays in the regulation of gene expression networks that are primarily involved in signaling for replication stress, cell cycle arrest and senescence.

EHMT2 Knockout in the Epithelium Alters the Tumor Microenvironment During Pancreatitis in Kras Mice
Prolonged or chronic inflammatory conditions promote the initiation and development of neoplastic and fibrotic events, serving as a major risk factor leading to PDAC (Momi et al., 2012). Pancreatitis induced by caerulein, a decapeptide that stimulate Gq-coupled growth regulatory receptors (e.g., CCK), accelerates the effects of oncogenic Kras (Murtaugh and Keefe, 2015). Pancreatitis-accelerated Kras-induced neoplastic growth in mice experimentally models the inflammationassociated progression, in which the microenvironment aids the growth-promoting process (Perez-Mancera et al., 2012). We injected 4-week-old Pdx1-Cre;LSL-Kras G12D and Pdx1-Cre;LSL-Kras G12D ;EHMT2 fl/fl mice with caerulein for 4 weeks to induce repeated chronic pancreatitis. Macroscopic examination of the pancreas in animals sacrificed after 4 weeks of caerulein treatment demonstrated that EHMT2 deletion antagonizes the known effect of Kras G12D to increase pancreas-to-body weight ratios (Figure 8A; 3.27 ± 0.09% for Pdx1-Cre;LSL-Kras G12D vs. 1.43 ± 0.06% for Pdx1-Cre;LSL-Kras G12D ;EHMT2 fl/fl ; p < 0.001; n = 5 and 13, respectively). Histopathology showed extensive and dysplastic PanIN lesions with caerulein treatment in Kras G12D animals, while pancreatic tissues from Kras G12D mice with EHMT2 inactivation displayed more limited dysplasia ( Figure 8B). Measurements of pancreas area with mucin-rich PanIN lesions detected by Alcian Blue staining substantiated that Kras G12D ;EHMT2 fl/fl mice had reduced area occupied by PanIN lesions, even when challenged by the inflammation-stimulating conditions (Figure 8C; 1.28 ± 0.13% Kras G12D ;EHMT2 fl/fl + caerulein vs. 2.64 ± 0.23% Kras G12D + caerulein; p < 0.001). We conclude that EHMT2 deletion antagonizes Kras G12D -mediated cell growth even after enhanced stimulation by pancreatitis. FIGURE 7 | Genetic inactivation of EHMT2 in the mouse pancreas modifies the inflammatory phenotype that characterizes Kras G12D -mediated initiation. (A) Graph depicts the presence of polymorphonuclear (PMN) leukocytes or histiocytes in tubular complexes from Kras G12D ;EHMT2 +/+ and Kras G12D ;EHMT2 fl/fl animals driven by Pdx1-Cre (n = 5 or 6, respectively) or P48 Cre/+ (n = 5 or 11, respectively). (B) The extent of PMN or histiocyte luminal infiltration was scored as absent, rare, focal or substantial. Kras G12D animals with EHMT2 inactivation showed reduced infiltration of these cells for both backgrounds (Pdx1-Cre and P48 Cre/+ ). (C) The degree of inflammation in tubular complexes was classified as absent, mild, moderate or severe. While Kras G12D mice predominantly presented with moderate to severe inflammation, the majority of Kras G12D ;EHMT2 fl/fl animals only showed mild inflammation. (D) The type of inflammatory cells infiltrating these precursor lesions was evaluated and classified as absent, lymphoplasmacytic (Lympho), neutrophilic or mixed. While Kras G12D animals mostly presented with a mixed inflammatory infiltrate, Kras G12D ;EHMT2 fl/fl mice predominantly demonstrated lymphoplasmacytic infiltrate. (E) Immune cell type profiling demonstrates the percentage of infiltrating immune cell types obtained by quanTIseq analysis of DEG from Pdx1-Cre;EHMT2 fl/fl , Pdx1-Cre;LSL-Kras G12D ;EHMT2 +/+ , and Pdx1-Cre;LSL-Kras G12D ;EHMT2 fl/fl mice. Scores representing the absolute fractions of immune cells reveal that there is enrichment of T cells, neutrophils, M1-type macrophages and B cells in Kras G12D animals, which is not present in mice with EHMT2 inactivation. We performed RNA-seq in both caerulein-treated Kras G12D , and Kras G12D ;EHMT2 fl/fl animals and compared them with untreated Kras G12D mice as controls ( Figure 8D; fold change ≥ |2| and FDR < 0.05). We identified 3881 caeruleininduced DEGs in Kras G12D animals (2024 upregulated and 1857 downregulated). The upregulated subset included not only 6 distinct AP-1 transcription factors, which participate in growth, but also 19 different collagen genes and 11 chemokine ligands (Supplementary Table 5), reflecting the functional expansion of the tumor microenvironment. Among downregulated networks, we found 10 different subunits of mitochondrial respiratory chain complexes (Supplementary Table 5). Caerulein-treated Kras G12D ;EHMT2 fl/fl mice displayed 3612 DEGs (1949 upregulated and 1663 downregulated). Of these, 2839 DEGs were shared with caerulein-treated Kras G12D mice, but 773 DEGs were unique to EHMT2 inactivation ( Figure 8D). Thus, overall, chronic caerulein treatment of Kras G12D ;EHMT2 fl/fl mice induces significant changes of gene expression. Consequently, we used PCA to measure genome-wide level differences in the transcriptional landscape of these animals by comparing the position of centroids in 3D (Supplementary Figure 7A). The centroid separation in 3D of the Kras G12D and caerulein-treated Kras G12D mice was 114, while for Kras G12D and caerulein-treated Kras G12D ;EHMT2 fl/fl , it was 105. The distance between the two caerulein treated conditions was 60, indicative of a dominant effect of caerulein administration on gene expression. Hierarchical clustering of RPKM for these DEGs (4654 genes), depicted as a heatmap in Figure 8E, identified four main expression patterns or clusters, which were annotated for pathway enrichment analyses ( Figure 8F). Cluster 1 included metabolic gene networks that were downregulated by caerulein in Kras G12D mice regardless of EHMT2 status ( Figure 8F and Supplementary Table 6). This observation is relevant in light of the emergent relationship between metabolism and cell growth regulation by oncogenic KRAS (Kimmelman, 2015). Another important downregulated gene network, ontologically known as KRAS signaling "down, " contained genes typically downregulated by KRAS signaling (qvalue = 6.1 × 10 −10 ), which is congruent with caerulein signaling via the Gq pathway (Goldsmith and Dhanasekaran, 2007). EMT gene networks were upregulated by caerulein independent of the EHMT2 status, forming cluster 4 (q-value = 1.6 × 10 −22 ; Figures 7E,F and Supplementary Table 6). Cluster 2 was comprised of genes with expression upregulated by caerulein in Kras G12D ;EHMT2 fl/fl mice in comparison with caerulein-treated Kras G12D mice with EHMT2 intact (Figure 8E). Networks in cluster 2 were prominently represented by immunoregulatory genes (Figure 8F and Supplementary Table 6), such as H2-Oa (human gene HLA-DOA), H2-Ob (human gene HLA-DOB), H2-DMb2 (human gene HLA-DMB), Cd2, Cd96, Cd28, Cd8a, Ccl5, Lck, and Zap70 (q-value = 1.5 × 10 −14 ), congruent with lymphocyte infiltration of T-cell origin. Finally, cluster 3 contained genes downregulated in Kras G12D animals carrying EHMT2 inactivation (Figure 8E), primarily representing EMT processes (q-value = 7.7 × 10 −12 ), TNF-α signaling via NFκB (q-value = 2.3 × 10 −12 ), as well as genes upregulated in response to KRAS signaling (q-value = 1.4 × 10 −08 ) among others ( Figure 8F and Supplementary Table 6). Overall, these data suggest that during the process of pancreatitisenhanced carcinogenesis by Kras G12D , EHMT2 influences immunomodulatory processes, while reducing EMT, TNF-α signaling via NFκB, and KRAS signaling, which have welldocumented effects on growth promotion (Thiery et al., 2009;Taniguchi and Karin, 2018;Waters and Der, 2018). Functional inferences were further gathered by building gene expression networks represented with color-coded nodes, corresponding to fold changes in gene expression (Supplementary Figure 7B). These networks better illustrate that both, Kras and TNFα-NFκB pathways were upregulated by pancreatitis to a significantly lesser extent in mice carrying EHMT2 inactivation. This effect is particularly evident for a portion of the KRASassociated gene network, composed of Itga2, Etv4, and Wnt7a, and the TNF-α-NFκB pathway, containing Areg, Fos, and Cxcl5 (human gene CXCL6) (Supplementary Figure 7B). Notably, the growth inhibitory networks that included Cdkn1a/p21 and Chek2, which were upregulated in animals with EHMT2 inactivation under basal conditions ( Figure 5F and Supplementary Figure 5), were no longer a hallmark of the caerulein-treated Kras G12D ;EHMT2 fl/fl transcriptome. Using the same RNA-seq deconvolution approach shown in Figure 7E from pancreas tissue, we found that the treatment of Kras G12D mice with caerulein increased regulatory T cells (Tregs), NK cells, myeloid dendritic cells, monocytes and M2 macrophages ( Figure 8G). Surprisingly, caerulein-treated Kras G12D animals with inactivation of EHMT2 not only had the presence of the immune cell types found in the caerulein-treated Kras G12D mice, but in addition, increased the infiltration of CD8+ and non-regulatory CD4+ T cells, B cells and neutrophils ( Figure 8G). This result demonstrated that inactivation of this histone methyl transferase, in epithelial cells, leads to a change in the Kras G12D immune landscape in response to pancreatitis by significantly enriching the infiltrate with both cytotoxic and non-regulatory T cells and B cells, which are known to work in concert to mount more efficient antitumor responses (Wörmann et al., 2014). Immunohistochemical analyses, using CD3 as a pan-T cell marker, supported the increased immune infiltration in the pancreas of caerulein-treated Kras G12D ;EHMT2 fl/fl mice (18.76 ± 2.88% for caeruleintreated Pdx1-Cre;LSL-Kras G12D ;EHMT2 fl/fl vs. 8.96 ± 1.66% for caerulein-treated Pdx1-Cre;LSL-Kras G12D ; p < 0.05; n = 4) that was not detected in their corresponding untreated cohort (0.57 ± 0.14% for Pdx1-Cre;LSL-Kras G12D ;EHMT2 fl/fl vs. 1.08 ± 0.28% for Pdx1-Cre;LSL-Kras G12D ; n = 4; Supplementary Figure 7C). In summary, our data demonstrate that genetic inactivation of EHMT2 interferes with caerulein-induced promotion of Kras G12D -induced effects at the gross and histopathological levels. At a molecular level, EHMT2 inactivation affects gene expression networks involved in growth and immunoregulatory processes. This genotypephenotype integration of transcriptomic data suggests that targeting EHMT2 for inactivation ameliorates cell growth-and inflammation-associated Kras G12D functions, most likely by a combined effect not only on the targeted pancreatic epithelial cells but also in its contributions to cell populations in the microenvironment, such as those from the immune system.

DISCUSSION
The current study provides better insight on how the H3K9 methylation pathway, found to be altered on promoters in a specific subtype of human pancreatic cancer (Lomberk et al., 2018), influences the responses downstream of genetic alterations. This provides data to advance our understanding of the repertoire of epigenomic regulators that support the function of oncogenes (e.g., KRAS) so as to give rise to the pancreatic cancer phenotype. For PDAC, this observation extends the pathway of "initiation" from the membrane (EGFR) through the cytoplasm (KRAS) into the nucleus (EHMT2), as the functional communication between receptor and the oncogene is necessary for this process (Navas et al., 2012;Baumgart et al., 2014). Growing evidence has revealed the intricate involvement of epigenetic regulators in KRAS-mediated PDAC development, which includes those that support neoplastic progression [e.g., Bmi1 (Bednar et al., 2015) and Setdb1 (Ogawa et al., 2020)] and others serving as barriers to this process [e.g., Ezh2 (Mallen-St Clair et al., 2012), Brg1 (von Figura et al., 2014, Kdm6a (Mann et al., 2012;Andricovich et al., 2018), Arid1a (Kimura et al., 2018;Wang W et al., 2019), Setd2 (Niu et al., 2020), and Bap1 (Perkail et al., 2020)]. Concurrent with the conclusion of our study, another report also found that EHMT2 deficiency impairs the progression of PanIN lesions and prolongs survival of P48 Cre/+ Kras G12D mice (Kato et al., 2020). Our investigations corroborate and extend those findings, utilizing the Pdx1-Cre Kras G12D mouse model in addition to the P48-driven Cre, to demonstrate that EHMT2 inactivation in mice with activated Kras G12D inhibits ADM and PanIN formation. By inactivating EHMT2 in the pancreas with either Pdx1-Cre or P48 Cre/+ , we provide robust evidence that this pathway is not required for pancreas exocrine development and is tolerated in this organ under basal contexts. While EHMT2 is critical to support mouse embryonic life at the level of the whole organism (Tachibana et al., 2002), we add the pancreas to the list of cell lineages, such as skeletal muscle (Zhang et al., 2016), that do not require this epigenetic regulator for proper development. Setdb1, a methyltransferase for the H3K9me3 mark, was also recently shown to also be dispensable for proper pancreas development in mice (Ogawa et al., 2020). Thus, H3K9 methylation pathways, at least after embryonic day 8.5 or 9.5, do not appear to be necessary during pancreatic development, although it remains unknown whether confounding effects would occur with more than one H3K9 methyltransferase inactivated simultaneously. Genetic inactivation of EHMT2 with the same two Cre-drivers crossed to the LSL-Kras G12D model and the tamoxifen-inducible CAGGCre-ER TM demonstrated how loss of this epigenetic complex antagonizes EGF-KRAS-mediated PDAC initiation via ADM, in vitro and in vivo, as well as PanIN formation in vivo. Furthermore, we show that levels of the EHMT2-EHMT1-WIZ complex in exocrine pancreatic cells are normally low but are induced by the KRAS growth regulatory pathway. This increase in formation of the enzymatic EHMT2-EHMT1-WIZ complex in response to KRAS leads to enhanced deposition of its product, the H3K9me2 mark, supporting a novel role of this epigenetic regulator downstream of this mitogenic signaling pathway.
To examine molecular mechanisms that may account for how EHMT2 inactivation antagonizes the functions of oncogenic Kras G12D , we considered the properties of this epigenomic protein on transcriptional regulation. Indeed, RNA-seq and targeted pathway-specific RT-qPCR analyses indicated that mice carrying conditional EHMT2 inactivation in their pancreas had transcriptional profiles that were dominant over the Kras G12D -regulated gene expression program, highlighting the contribution that this histone methyltransferase has in promoting the Kras G12D -regulated gene expression program. EHMT2 inactivation resulted in the upregulation of key cell cycle inhibitory checkpoints, including Chk2 and Cdkn1a/p21, which function in cell cycle arrest in a manner that if persistent can induce senescence (Aliouat-Denis et al., 2005;d'Adda di Fagagna, 2008). Congruently, investigations of cellular mechanisms that could be responsible for the antagonism of Kras G12D -mediated growth determined that EHMT2 deletion in the Kras G12Dexpressing exocrine pancreas leads to senescence. Senescence is mechanistically important since it occurs in the context of Kras G12D oncogene-induced stress, a phenomenon that is operational in pancreatic cells and drives the accelerated firing of replication forks with uninterrupted cycles of cell proliferation caused by the oncogenic stimulus (Kotsantis et al., 2018). Under normal conditions, this stress is compensated so that this oncogene can proceed with accelerated growth unless cell cycle regulators and checkpoint proteins become activated leading to OIS (Liu et al., 2018). OIS is often a dominant mechanism that antagonizes the transformation process (Lowe et al., 2004). However, studies have shown that physiological levels of oncogenic Kras have the capacity to suppress premature senescence of pancreatic ductal epithelium in vivo, bypassing this process (Lee and Bar-Sagi, 2010). In this regard, our data is, at least in large part, consistent with the escape from senescence being operational under Kras G12D activation in vivo, which is thwarted when combined with EHMT2 deletion. Indeed, combined data from histology, IHC, β-galactosidase staining, RT-qPCR and RNA-seq identifies the previously unknown cooperation between EHMT2 and Kras G12D , which must be actively maintained to eventually bypass OIS and support PDAC initiation. Inactivation of EHMT2 in other organs can trigger different mechanisms, depending upon the cell type and the physiological or pathological context (Shankar et al., 2013;Casciello et al., 2015;Kramer, 2015). In these studies, EHMT2 has been found to participate in a large number of phenomena, and in some cells, loss of this epigenetic regulator induces senescence even in the absence of oncogenic stimulation (Takahashi et al., 2012;Wang et al., 2013). Interestingly, ectopic oncogenic Ras-induced senescence in human diploid fibroblasts results in proteosomal degradation of the EHMT2 complex by APC/C(cdh1) (Takahashi et al., 2012).
In addition, pharmacological inhibitors of EHMT2, which have similar pleomorphic effects in distinct cells and tissues (Casciello et al., 2015;Charles et al., 2019;Griñán-Ferré et al., 2019;Kim et al., 2019;Rybak et al., 2019), in certain cases, also induce senescence (Yuan et al., 2012). Altogether, our results support the conclusion that enhanced senescence is one important cellular mechanism by which EHMT2 inactivation appears to antagonize Kras G12D in exocrine pancreatic cells in vivo. Notably, the effects of EHMT2 inactivation on Kras G12D -induced growth remained under pancreatitis-stimulated conditions, providing further evidence that targeting this epigenomic regulator exerts a dominant effect over the functions of this oncogene. However, we also found that EHMT2 inactivation in caeruleintreated Kras G12D mice had additional impact on expression of immunoregulatory gene networks, which were not activated by the genetic manipulation of either EHMT2 or Kras G12D alone, and altered the composition of immune cell infiltration, enriching the proportion of cytotoxic and non-regulatory T cells and B cells, which is suggestive of an antitumor response (Wörmann et al., 2014). Thus, EHMT2 inactivation appears play a role in regulating pancreatitis-enhanced Kras G12D effects, not only through cell growth regulatory pathways, but also in part via immunomodulatory effects, thereby affecting the tumor microenvironment.
In summary, this work identifies EHMT2 as a KRASinducible epigenetic regulator which enables this oncogene to exert its effects on growth and inflammation, even when challenged in the pancreatitis-associated promotion model. Indeed, at the molecular level Kras G12D induces the levels of EHMT2, its heterotrimeric complex with EHMT1 and WIZ, as well as its enzymatic product, H3K9me2. Consequently, EHMT2 inactivation significantly reduces the levels of H3K9me2. The role of EHMT2 as a regulator of gene expression is clearly demonstrated by the fact that its inactivation changes the transcriptional profile of Kras G12D in a dominant manner. Noteworthy, while we manipulated the KRAS-EHMT2 pathway in epithelial cells, the results extend beyond this compartment to affect the tissue microenvironment, namely immune cell populations.
Besides the mechanistic importance of these results, this new information reinforces the role of EHMT2 as a potential therapeutic or chemopreventive target for pancreatic cancer and highlights the possibilities of this therapeutic strategy in combination with current inhibitors of the EGFR-KRAS pathway, which are widely available for clinical trials. In addition, the discovery that inhibition of EHMT2 in epithelial cells leads to reorganization of the immune landscape in the tumor microenvironment serves as the foundation for future studies focused on designing combinations with immunomodulatory agents. Lastly, the existence of this novel KRAS-EHMT2 pathway that is critical for mediating the growth-promoting and immunoregulatory effects of this oncogene in vivo predicts that these therapies will likely impact both the tumor-initiating epithelial cells and the tumor microenvironment.

DATA AVAILABILITY STATEMENT
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: GEO with dataset number GSE169525.

ETHICS STATEMENT
Animal care and all protocols were reviewed and approved by the Institutional Animal Care and Use Committees of Mayo Clinic Rochester (IACUC protocols A00002240-16 and A24815) and the Medical College of Wisconsin (AUA00005963).

AUTHOR CONTRIBUTIONS
RU and GL conceived and designed the study. GU, TA, AM, and AS conducted the experiments, acquired and analyzed the data. GU, RK, AZ, TS, VA, and BP participated in formal analysis. TA assembled figures. GU, TA, AM, MBD, MZ, JI, RU, and GL contributed to data interpretation. TA, JI, RU, and GL wrote the original draft. GL supervised the study. All authors provided valuable intellectual input on experiments, as well as read, offered feedback and approved the manuscript.