Figure S5 contains cycle cycle analysis of MCF7 DpVp300 cells following knockdown of METTL7A.

Figure S4 contains cytotoxicity assay and immunoblot data from the MCF7 and MCF7 DpVp300 cell lines showing that expression of METTL7A confers resistance.

Figure S1 contains chemical structures of select HDAC inhibitors

Supplemental Table S4 contains information about the cross-resistance profile of MCF7 DpVp300 cells with thiol-based HDACis

Supplemental Table S2 contains information about the cross-resistance profile of MCF7 DpVp300 cells for multiple drugs

Supplemental Table S3 contains information from high-throughput sequencing

Supplemental Table S7 contains information about the normal tissue expression of METTL7A and METTL7B

Supplemental Table S8 contains information about METTL7A and METTL7B in T-cell lymphoma tissue microarray samples

Figure S2 contains cell cycle analysis and cytotoxicity data for MCF7 DpVp300 cells showing they are resistant to romidepsin and do not overexpress P-gp

Figure S3 contains gene ontology analysis, motif analysis, and nucleosome density from the RNA-seq and ATAC-seq data.

Supplemental Table S6 contains information about the cross-resistance profile of the Vector, 7A 1-2, 7A 1-4, 7B 1-3 and 7B 2-2 cells

Figure S6 contains cell cycle analysis of cells overexpressing METTL7A.

Cell type-specific enhancers are critically important for lineage specification. The mechanisms that determine cell-type specificity of enhancer activity, however, are not fully understood. Most current models for how enhancers function invoke physical proximity between enhancer elements and their target genes. Here, we use an imaging-based approach to examine the spatial relationship of cell type-specific enhancers and their target genes with single-cell resolution. Using high-throughput microscopy, we measure the spatial distance from target promoters to their cell type-specific active and inactive enhancers in individual pancreatic cells derived from distinct lineages. We find increased proximity of all promoter-enhancer pairs relative to non-enhancer pairs separated by similar genomic distances. Strikingly, spatial proximity between enhancers and target genes was unrelated to tissue-specific enhancer activity. Furthermore, promoter-enhancer proximity did not correlate with the expression status of target genes. Our results suggest that promoter-enhancer pairs exist in a distinctive chromatin environment but that genome folding is not a universal driver of cell-type specificity in enhancer function.

Abstract Genetic or epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies, including pancreas cancer. Pinpointing genes affecting pancreas cancer risk holds promise for early detection, prevention, and effective therapies. Despite recent advances, linking enhancer elements to target genes and predicting the transcriptional outcome of enhancer dysfunction remain significant challenges. Using 3D chromatin assays, we generated an extensive enhancer interaction dataset for the human pancreas, spanning more than 20 donors and five major cell types, including both the exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating quantitative, genome-wide analysis of enhancer connectivity. Using the tree models, we developed a machine learning algorithm capable of estimating the impact of enhancer perturbations on cell-type specific gene expression in the human pancreas. Complementing this computational approach, we streamlined an experimental platform using CRISPR-interference and RNA-FISH coupled with high-throughput imaging to quantitatively measure the effect size of enhancer perturbations in primary human pancreas cells. Our enhancer tree models enabled functional annotation of genetic variants associated with pancreas diseases, revealing novel target genes in specific cell types. For pancreas cancer (PDAC), our data suggests a stronger association of disease susceptibility variants with acinar cells, even though ductal cells historically have been the focus of PDAC. This discovery linked three potentially functional variants associated with PDAC risk to acinar cell enhancers, revealing novel target genes to further investigation. By integrating genomics with mechanistic findings into enhancer function, our work offers a framework for understanding genetic basis of pancreas cancer disease risk. Citation Format: Li Wang, Songjoon Baek, Gauri Prasad, Thucnhi Truongvo, Jason Hoskins, Laufey Amundadottir, Efsun Arda. A novel approach to understanding pancreas cancer risk through enhancer- promoter interactions [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C058.

Abstract Histone deacetylase inhibitors (HDACi) are part of a growing class of epigenetic therapies used for the treatment of cancer. Although HDACis are effective in the treatment of T-cell lymphomas, treatment of solid tumors with this class of drugs has not been successful. Overexpression of the multidrug resistance protein P-glycoprotein (P-gp), encoded by ABCB1, is known to confer resistance to the HDACi romidepsin in vitro, yet increased ABCB1 expression has not been associated with resistance in patients, suggesting that other mechanisms of resistance arise in the clinic. To identify alternative mechanisms of resistance to romidepsin, we selected MCF-7 breast cancer cells with romidepsin in the presence of the P-gp inhibitor verapamil to reduce the likelihood of P-gp-mediated resistance. The resulting cell line, MCF-7 DpVp300, does not express P-gp and was found to be selectively resistant to romidepsin but not to other HDACis such as belinostat, panobinostat, or vorinostat. RNA-sequencing analysis revealed upregulation of the mRNA coding for the putative methyltransferase, METTL7A, whose paralog, METTL7B, was previously shown to methylate thiol groups on hydrogen sulfide and captopril. As romidepsin has a thiol as the zinc-binding moiety, we hypothesized that METTL7A could inactivate romidepsin and other thiol-based HDACis via methylation of the thiol group. We demonstrate that expression of METTL7A or METTL7B confers resistance to thiol-based HDACis and that both enzymes are capable of methylating thiol-containing HDACis. We thus propose that METTL7A and METTL7B confer resistance to thiol-based HDACis by methylating and inactivating the zinc-binding thiol.

The Hippo pathway plays a central role in tissue development and homeostasis. However, the function of Hippo in pancreatic endocrine development remains obscure. Here, we generated novel conditional genetically engineered mouse models to examine the roles of Hippo pathway-mediated YAP1/TAZ inhibition in the development stages of endocrine specification and differentiation. While YAP1 protein was localized to the nuclei in bipotent progenitor cells, Neurogenin 3 expressing endocrine progenitors completely lost YAP1 expression. Using genetically engineered mouse models, we found that inactivation of YAP1 requires both an intact Hippo pathway and Neurogenin 3 protein. Gene deletion of Lats1 and 2 kinases (Lats1&2) in endocrine progenitor cells of developing mouse pancreas using Neurog3Cre blocked endocrine progenitor cell differentiation and specification, resulting in reduced islets size and a disorganized pancreas at birth. Loss of Lats1&2 in Neurogenin 3 expressing cells activated YAP1/TAZ transcriptional activity and recruited macrophages to the developing pancreas. These defects were rescued by deletion of Yap1/Wwtr1 genes, suggesting that tight regulation of YAP1/TAZ by Hippo signaling is crucial for pancreatic endocrine specification. In contrast, deletion of Lats1&2 using β-cell-specific Ins1CreER resulted in a phenotypically normal pancreas, indicating that Lats1&2 are indispensable for differentiation of endocrine progenitors but not for that of β-cells. Our results demonstrate that loss of YAP1/TAZ expression in the pancreatic endocrine compartment is not a passive consequence of endocrine specification. Rather, Hippo pathway-mediated inhibition of YAP1/TAZ in endocrine progenitors is a prerequisite for endocrine specification and differentiation.

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach-combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays-produced a robust resource for studying the genetic basis of pancreas disorders.

Abstract Background: Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) to pancreatic ductal adenocarcinoma (PDAC) risk at over 20 genomic loci. The Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium are currently expanding on previous GWAS studies for PDAC from ∼9,000 cases and ∼12,000 controls to ∼36,000 cases and ∼800,000 controls in individuals of European and Asian ancestry. This ongoing GWAS phase is estimated to detect up to 50 new risk signals. Post-GWAS studies aim to fine-map and functionally assess risk variants in disease-relevant cell types and contexts to identify target genes and underlying mechanisms of risk. Massively parallel reporter assays (MPRAs) are a powerful method of assessing allele-specific gene regulatory effects. Integrating sequences into the genome using lentiviruses (Lenti-MPRA) enables the capture of variant function in the context of the native cellular chromatin. An added benefit is that Lenti-MPRAs can be used for difficult to transfect cells such as primary cells, that often reflect the disease relevant cell types. Methods: We have used a lentiviral MPRA to test 228 fine-mapped SNPs at the chr5p15.33 multi-cancer risk locus in PDAC cell lines (MIA PaCa-2, PANC-1) and the normal-derived ductal pancreas (HPDE) cell line. Additionally, we have optimized the transduction of large MPRA libraries into primary pancreas cells. Tunicamycin was used to induce ER stress in cell lines and primary cells, assessing downstream gene expression using RT-qPCR. Results: Our pilot MPRA demonstrated high reproducibility in PDAC cell lines (r2=0.93-0.97, MIA PaCa-2, PANC-1 cells) and normal-derived pancreatic ductal cells (r2=0.68-0.86, HPDE cells). We identified 33 SNPs out of 228 with significant allele-specific transcriptional activity in PDAC cell lines and 5 in HPDE cells (FDR ≤0.05). An additional 6-15% of variants exhibited significant allele-specific transcriptional activity when in the frames of the SNP-centered tested oligos were shifted left or right. We demonstrate the inducibility of ER-stress with tunicamycin treatment over 24 hours in cells lines and primary pancreatic cells. Additionally, we observed increased expression of CLPTM1IL at the chr5p15.33 locus after tunicamycin treatment over 24 hours in cell lines and primary pancreatic cells, suggesting ER-stress and inflammation may influence gene expression at this locus. Conclusions: Lentiviral MPRA assays in commonly used PDAC cell lines have demonstrated good reproducibility. The optimization studies and preliminary work in primary pancreatic cells provide a solid foundation for the next steps of assessing all GWAS loci in ER stress, an important disease relevant condition. Citation Format: Minal B Patel, Aidan O'Brien, Jun Zhong, Irene Collins, Jason W Hoskins, Stephen J Chanock, Samuel O Antwi, Rachel Z Stolzenberg-Solomon, Alison P Klein, Brian M Wolpin, Sara Lindström, H. Efsun Arda, Kevin M Brown, Katelyn E Connelly, Laufey T Amundadottir, Meagan Jezek. The functional characterization of pancreatic ductal adenocarcinoma GWAS risk variants in primary pancreatic cells – A pilot study [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A018.

Identification of somatic driver mutations in the noncoding genome remains challenging. To comprehensively characterize noncoding driver mutations for pancreatic ductal adenocarcinoma (PDAC), we first created genome-scale maps of accessible chromatin regions (ACRs) and histone modification marks (HMMs) in pancreatic cell lines and purified pancreatic acinar and duct cells. Integration with whole-genome mutation calls from 506 PDACs revealed 314 ACRs/HMMs significantly enriched with 3,614 noncoding somatic mutations (NCSMs). Functional assessment using massively parallel reporter assays (MPRA) identified 178 NCSMs impacting reporter activity (19.45% of those tested). Focused luciferase validation confirmed negative effects on gene regulatory activity for NCSMs near CDKN2A and ZFP36L2. For the latter, CRISPR interference (CRISPRi) further identified ZFP36L2 as a target gene (16.0 - 24.0% reduced expression, P = 0.023-0.0047) with disrupted KLF9 binding likely mediating the effect. Our integrative approach provides a catalog of potentially functional noncoding driver mutations and nominates ZFP36L2 as a PDAC driver gene.

Transcription factor regulon activities in the non-edge acinar to edge acinar transition.