Smarcd3 is an epigenetic modulator of the metabolic landscape in pancreatic ductal adenocarcinoma

Pancreatic cancer is characterized by extensive resistance to conventional therapies, making clinical management a challenge. Here we map the epigenetic dependencies of cancer stem cells, cells that preferentially evade therapy and drive progression, and identify SWI/SNF complex member SMARCD3 as a regulator of pancreatic cancer cells. Although SWI/SNF subunits often act as tumor suppressors, we show that SMARCD3 is amplified in cancer, enriched in pancreatic cancer stem cells and upregulated in the human disease. Diverse genetic mouse models of pancreatic cancer and stage-specific Smarcd3 deletion reveal that Smarcd3 loss preferentially impacts established tumors, improving survival especially in context of chemotherapy. Mechanistically, SMARCD3 acts with FOXA1 to control lipid and fatty acid metabolism, programs associated with therapy resistance and poor prognosis in cancer. These data identify SMARCD3 as an epigenetic modulator responsible for establishing the metabolic landscape in aggressive pancreatic cancer cells and a potential target for new therapies.

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Dr. Tannishtha Reya 11/14/2022 FACS Diva v6.1.3 used to to acquire Flow cytometry data All software used for data analysis is is described in in the Methods section in in detail and in in Supplementary Table 3. 3. Briefly: ImageJ v1.50i was used for image analysis, FlowJo v10.5.3 was used to to analyze all FACS data, GraphPad Prism 8.2.0 was used for statistical analysis (T-cests, ANOVA, linear regression), tumor tissue area and tumor cell number analysis by by histology was done using QuPath 0.2.3, Scorenado was used to to analyze clinically annotated human PDAC tissue microarray, 10X Genomics Cell Ranger v3.0, Seurat v3.1, and UMAP 0.3.8 were used to to analyze and plot human PDAC scRNAseq data, STAR v2.5 was used to to align mouse pancreatic cancer RNA-seq and ChIP-seq data, HOMER v4.8 was used to to process ChIP-seq alignment files, binding enrichment, and differential RNA-seq expression using DESEQ2 3.15, Gene Set Enrichment Analysis desktop 4.0.3 was used for GSEA analysis of of RNA-seq data using Bioconductor GSVA C2, C6, and C7 C7 BroadSets gene set collections, Cytoscape v.3.8.2 desktop was and the GLay clustering algorithm (clusterMaker2 v2.2) were used to to construct the RNA-seq network using the mouse STRING interactome (1.5.1), STRING functional enrichment was used to to annotate network clusters within Cytoscape. Scorenado for TMA scoring is is available on on github: https://github.com/digitalpathologybern/scorenado.

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April 2020 Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection. In a few cases, data points were excluded from the analysis of KPf/fC tumors if these data points were identified as an outlier by statistical measures. In each case where an outlier has been excluded, this is specifically noted in each figure legend along with the specific statistical test that has been used.
The level of replication for each in vitro and in vivo study is noted in the figure legends for each figure and described in detail in the Methods section, but will be briefly summarized here. However, to summarize briefly, in vitro sphere or colony formation studies were conducted with n=3 independent wells per cell line across two independent shRNA of n=3 wells; the majority of these experiments were additionally completed in >2 independently derived cell line, n=3 wells per shRNA. Because material was limited, PDX organoids treated with shRNA were plated in n=3-4 wells per experiment, for one experiment each using two independent PDX organoid lines. Flank shRNA studies were conducted three times using independent cell lines, with n=3-4 tumors per group in each experiment. Analysis of midpoint (7-8 weeks old) KPf/fC tumors was conducted with n=5-16 mice per group. Secondary syngeneic transplants were conducted with n=3-4 independent tumors per group, transplanted into n=2-4 littermate recipients each. Survival studies in KPf/fC mice plus and minus gemcitabine treatment were conducted with n=6-10 mice per group. Flank KPF + adCre and KPF-R26-CreERT2 tamoxifen treated transplants were conducted in 3 biological replicates at n=3-5 tumors per group. Autochthonous tumor studies were completed in n=4-5. Tumor initiation studies in the autochthonous KC model were conducted with n=3-9 mice for all Cre systems used. 3 independent PDX tumors were used for shRNA studies in vivo, one PDX sample was used for one experiment while the other two were completed in duplicate for a total of n=4-5 per shRNA for 2 independent shRNA. RNA-seq in KPf/fC cells was run in triplicate, H3K27-acetyl ChIP-seq was run in duplicate, and one ChIP each was run for H3K4me, H3K4me3, SMARCA4, ARID1A, FOXA1, and KLF5 ChIP-seq.
Randomization for in vivo studies is described in detail in the Methods section. Briefly, for all in vivo studies using authochthonous mouse models, no sexual dimorphism was noted in all mouse models. Therefore, males and females of each strain were equally used for experimental purposes and both sexes are represented in all data sets; littermates of the same sex were randomized into experimental groups when applicable or possible based on available mice. Mice were chosen for transplants and analysis of primary tumors at random in the order in which mice of the correct genotype were born. All flank transplants were measured, binned by size, and enrolled into two treatment arms in order of size. For secondary syngeneic transplants of primary KPf/fC cells, male and female littermate recipients were used equivalently when possible given limited number of littermates of the appropriate genotype. The sex, age, and number of all mice for all experiments are detailed in Supplementary Table 3.
For sphere-forming and in vitro growth assays, specific wells were kept blinded during counting and analysis. For immunofluorescence analysis, tissue sections were de-identified when possible until after analysis. Tissue section genotype as well as disease model were blinded for pathological analysis of initiation models. For pathological analysis of tumor initiation models, pathologist was blinded to genotype of mice for analysis. The investigators were not blinded during outcome assessment for other experiments since data acquisition and analysis were done using indicated software.
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ChIP-seq Data deposition
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May remain private before publication. FG (COLO-357) human pancreatic cancer cells were provided by Dr. Andrew Lowy.Mouse primary pancreatic cancer cell lines were established from end-stage wild-type KPf/fC and Msi2-GFP-KPf/fC (9-12 weeks of age), KPC (16-20 weeks of age), Smarcd3f/f-KPF (10-15 weeks of age) mice by isolating primary tumors, dissociating to a single cell suspension and plating in 2D culture. At the first passage, cells were collected and EpCAM-APC+ tumor cells were sorted and re-plated for at least one additional passage. Patient-derived organoid lines were derived by isolating end-stage patient-derived xenograft tumors and dissociating to single cell and plating in a matrigel dome covered in human organoid growth media.
FG human pancreatic cancer cells were previously derived from a PDAC metastasis and validated by Morgan et al. 1980. To evaluate any cellular contamination and validate the epithelial nature of primary mouse pancreatic cancer cell lines, cells were analyzed by flow cytometry again at the second passage for markers of blood cells, endothelial cells, and fibroblasts (PDGFR-PacBlue, Biolegend). Patient-derived organoid lines were passaged to select for cancer cells as previously described (Baker et al. 2017) and checked for EpCAM expression to validate their epithelial nature. We have not authenticated any cell lines using STR fingerprinting.
All cell lines were regularly tested for the presence of mycoplasma and verified to be negative. This study did not involve wild animals.

None
The study involved no field-collected samples IAUCUC and the University of California San Diego approved our animal use protocol for all strains, experiments, and procedures outlined in these studies.
All sequencing data has been submitted at GEO, GSE168490. Reviewer token: anqruiogprufpkb