Cancer-associated fibroblasts (CAF) are a major cell type in the stroma of solid tumors and can exert both tumor-promoting and tumor-restraining functions. CAF heterogeneity is frequently observed in pancreatic ductal adenocarcinoma (PDAC), a tumor characterized by a dense and hypoxic stroma that features myofibroblastic CAFs (myCAF) and inflammatory CAFs (iCAF) that are thought to have opposing roles in tumor progression. While CAF heterogeneity can be driven in part by tumor cell–produced cytokines, other determinants shaping CAF identity and function are largely unknown. In vivo, we found that iCAFs displayed a hypoxic gene expression and biochemical profile and were enriched in hypoxic regions of PDAC tumors, while myCAFs were excluded from these regions. Hypoxia led fibroblasts to acquire an inflammatory gene expression signature and synergized with cancer cell–derived cytokines to promote an iCAF phenotype in a HIF1α-dependent fashion. Furthermore, HIF1α stabilization was sufficient to induce an iCAF phenotype in stromal cells introduced into PDAC organoid cocultures and to promote PDAC tumor growth. These findings indicate hypoxia-induced HIF1α as a regulator of CAF heterogeneity and promoter of tumor progression in PDAC.

Significance:

Hypoxia in the tumor microenvironment of pancreatic cancer potentiates the cytokine-induced inflammatory CAF phenotype and promotes tumor growth.

See related commentary by Fuentes and Taniguchi, p. 1560

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive tumor and projected to become the second leading cause of cancer-related mortality by 2030 in the United States (1). A significant barrier to the delivery of effective therapy for PDAC is the desmoplastic stroma that can constitute up to 90% of the tumor volume (1). The prominent desmoplastic response observed in PDAC is characterized by a fibrotic and inflammatory stromal milieu, which is produced primarily by cancer-associated fibroblasts (CAF) and plays a role in both supporting tumor cell growth and promoting therapeutic resistance (2). The basal activity of CAFs to produce extracellular matrix is not sufficient to mediate these effects, as depletion of CAF-derived collagen promotes PDAC growth and reduces survival in mouse models (3). Thus, CAFs can have either tumor-promoting or tumor-suppressing properties within the pancreatic tumor microenvironment (TME).

Transcriptionally and functionally, heterogeneous subsets of CAFs have been identified in mouse and human PDAC (4–7). Myofibroblastic CAFs (myCAF) are marked by expression of alpha smooth muscle actin (αSMA), produce extracellular matrix and are thought to restrain tumor growth (8). Inflammatory CAFs (iCAF) express only low levels of αSMA, produce a variety of growth factors and inflammatory cytokines such as IL6 and can directly and indirectly promote tumor growth (9). Other, cancer-associated phenotypes of fibroblasts have also been reported, including antigen-presenting CAFs (apCAF) marked by MHC-II expression (5). Heterogeneity within the CAF population has been suggested to be established in part by growth factor and cytokine gradients within the TME including the local accumulation of tumor-derived TGFβ and IL1/TNFα (10), indicating that spatial differences in the accumulation of different CAF subpopulations exist. However, whether the metabolic conditions present in the pancreatic TME also contribute to regulating CAF heterogeneity is less well explored.

Understanding regulators of CAF heterogeneity has clinical implications: while patients with PDAC with high amounts of myCAFs in tumors had improved overall survival, they responded poorly to anti-PD-L1 therapy in retrospective studies (6, 8). In contrast, iCAFs are associated with poor response to chemotherapy in patients (11), and iCAF-derived factors including IL6 are directly involved in PDAC progression in mouse models (12–14). Thus, a better understanding of the determinants of CAF heterogeneity may facilitate the development of therapies selectively targeting tumor-promoting CAFs.

The TME of PDAC is characterized by nutrient depletion and hypoxia as a result of increased cancer cell demand and impaired vascularization (15, 16). Hypoxia results in stabilization of the transcription factor HIF1α, which mediates cellular adaptation to low oxygen tension (17). In cancer cells, this adaptive response promotes epithelial–mesenchymal transition and angiogenesis, and a hypoxia gene expression signature is associated with poor prognosis of patients with PDAC (18). In the stroma, hypoxia is known to promote lysyl oxidase expression to increase collagen cross-linking and tumor stiffness (19). Hypoxia is associated with an inflammatory fibroblast expression signature in genomic studies of human PDAC and has been shown to promote a secretory phenotype in CAFs while conversely, reducing αSMA expression (10, 20, 21). These data suggest that hypoxia could influence the CAF phenotype, but whether hypoxia and HIF1α are causatively involved in the generation of distinct CAF subsets in PDAC is not understood. Here, we report the ability of hypoxia to synergize with cancer cell–derived cytokines in activating HIF1α to promote the iCAF phenotype and tumor growth in PDAC.

Mouse experiments

All animal experiments described adhered to policies and practices approved by Memorial Sloan Kettering Cancer Center's Institutional Animal Care and Use Committee (IACUC) and were conducted as per NIH guidelines for animal welfare (protocol number 11-03-007, Animal Welfare Assurance Number FW00004998). Mouse experiments were performed as described previously (22). The maximal tumor size/burden permitted by the IACUC (tumor burden may not exceed 10% of the weight of the mouse, which is equivalent to a tumor volume of 2.5 cm3 for a 25 g mouse) was not exceeded. Mice were maintained under specific pathogen-free conditions and housed at 4–5 mice per cage at a 12-hour light/dark cycle at a relative humidity of 30% to 70% and room temperature of 22.2°C ± 1.1°C, and were allowed access to food and water ad libitum. Mice were maintained in individually ventilated polysulfone cages with a stainless-steel wire bar lid and filter top on autoclaved aspen chip bedding. Mice were fed a closed-formula, natural-ingredient, γ-irradiated diet (5053 - PicoLab Rodent Diet 20, Purina LabDiet), which was surface decontaminated using “flash” sterilization (100°C for 1 minute). Mice were provided reverse-osmosis acidified (pH 2.5 to 2.8, with hydrochloric acid) water. Cage bottoms were changed weekly, whereas the wire bar lid, filter top and water bottle were changed biweekly.

Orthotopic organoid injection model

Orthotopic injections were performed as described previously (23). Organoids derived from pancreatic tumors of KrasLSL-G12D/+;Trp53LSL-R172H/+;Pdx1-Cre (KPC) mice in a C57BL/6 background were used. Syngeneic C57BL/6 mice were anesthetized with isoflurane and an incision was made in the left abdominal side. Organoids were dissociated from cultures with TrypLE (Thermo Fisher Scientific) and resuspended in 30 μL growth factor reduced (GFR) Matrigel (Corning). Approximately 1 × 105 cells were injected per recipient mouse into the tail region of the pancreas using a Hamilton Syringe. Successful injection was verified by the appearance of a fluid bubble without signs of intraperitoneal leakage. The abdominal wall was sutured with absorbable Vicryl sutures (Ethicon), and the skin was closed with wound clips (CellPoint Scientific Inc.). Mice were monitored for tumor development by ultrasound 5 weeks after injection and once per week afterward using a Vevo 2100 System with a MS250 13-24 MHz scan head (VisualSonics). When tumors were approximately 500 mm3 in size, 60 mg/kg body weight of pimonidazole (Hypoxyprobe) in 0.9% saline was injected intraperitoneally 1 hour before euthanasia. Tumors were collected, and half of the tumor was allocated for 10% formalin fixation for histologic analysis, and the other half was used to generate single-cell suspensions for flow cytometry analysis.

Subcutaneous coinjection model

Subcutaneous injections were performed as described previously (22). A total of 2 × 105 KPC cells alone or together with 1 × 106 pancreatic stellate cells (PSC) were resuspended in 100 μL PBS and injected subcutaneously into the flanks of 8–10 weeks old female syngeneic C57BL/6 mice (JAX, 000664). At the beginning of each experiment, and at the onset of treatment with mAbs, mice were randomly assigned to the different groups. No estimation of sample size was performed before the experiments. Treatment with mAbs was started 1 week after tumor inoculation and performed as described previously (23). Mice were injected intraperitoneally every 3 days over 2 weeks with anti-IL6 (200 μg; MP5-20F3, BioXCell), anti-VEGFR2 (800 μg; DC101, BioXCell), or IgG1 isotype control (800 μg; MOPC-21, BioXCell). Mice were monitored daily, and tumor volume was measured by calipers. Measurements were taken in two dimensions, and tumor volume was calculated as length × width2 × π/6. At the end of the experiment, mice were euthanized with CO2, and tumors were collected and aliquoted for 10% formalin fixation for IHC and digestion for flow cytometry analysis.

Immunostaining of mouse PDAC tumors

Automated multiplex immunofluorescence (IF) was conducted using the Leica Bond BX staining system. Paraffin-embedded tissues were sectioned at 5 μm and baked at 58°C for 1 hour. Slides were loaded in Leica Bond and IF staining was performed as follows. Samples were pretreated with ethylenediaminetetraacetic acid (EDTA)–based epitope retrieval ER2 solution (AR9640, Leica) for 20 minutes at 95°C. The quadruplex antibody staining and detection was conducted sequentially. The primary antibodies against PDPN (0.05 μg/mL, hamster, DSHB, 8.1.1, RRID:AB_531893), PIMO (0.12 μg/mL, mouse, Hydroxyprobe Inc. MAB1, RRID:AB_2801307), SMA (0.1 μg/mL, rabbit, Abcam, ab5694, RRID:AB_2223021), HIF1α (0.5 μg/mL, rabbit, Novus, NB100, RRID:AB_350071) were used. For the rabbit antibody, Leica Bond Polymer anti-rabbit horseradish peroxidase (HRP) was used, for the hamster antibody and the mouse antibody, rabbit anti-Hamster (Novex, A18891) and rabbit anti-mouse (Abcam, ab133469) secondary antibodies were used as linkers before the application of the Leica Bond Polymer anti-rabbit HRP. After that, Alexa Fluor tyramide signal amplification reagents (Life Technologies, B40953, B40958) or CF dye tyramide conjugates (Biotium, 92174, 96053) were used for detection. After each round of IF staining, Epitope retrieval was performed for denaturization of primary and secondary antibodies before another primary antibody was applied. After the run was finished, slides were washed in PBS and incubated in 5 μg/mL 4′,6-diamidino-2-phenylindole (DAPI; Sigma-Aldrich) in PBS for 5 minutes, rinsed in PBS, and mounted in Mowiol 4-88 (Calbiochem). Slides were kept overnight at −20°C before imaging. IHC was performed by Histowiz using the following antibodies: SMA (ab5694, RRID:AB_2223021), CD31 (ab28364, RRID:AB_726362).

Imaging and analysis

Images from tissue sections of PDAC tumors were acquired with a Mirax Slide Scanner at 40× magnification. Images were analyzed in ImageJ (RRID:SCR_003070). Pimonidazole+ regions were located in each tissue section. Within each region, the number of PDPN+ only pixels, SMA+ only pixels, and double-positive pixels were quantified. Thresholds were set manually for each channel and kept consistent for each image. Two sections per tumor were analyzed. Live images from PSC monocultures were acquired with a Leica SP5 Inverted confocal microscope with cells placed in an environmental chamber. IHC-stained slides were scanned by Histowiz, and images were analyzed in ImageJ. Thresholds were set manually and kept consistent for each image.

Cell culture

293T cells were obtained from ATCC (CRL-3216). PSCs were isolated from either wildtype C57BL/6 mice or αSMA-DsRed mice (24) by differential centrifugation as described previously (25) and immortalized by spontaneous outgrowth. KPC (KrasLSL-G12D/+;Trp53LSL-R172H/+;Pdx1-Cre) mouse PDAC cells and organoids were described before (23). All cells were cultured at 37°C in 5% CO2 and 20% O2 and were maintained in DMEM supplemented with 10% FBS (Gemini), 100 U/mL penicillin, and 100 μg/mL streptomycin (1% P/S). For hypoxia experiments, cells were cultured in a hypoxia glove box (Coy) set at 0.5% O2, 37°C and 5% CO2 for 48 hours. Cells were verified as Mycoplasma free by the MycoAlert Mycoplasma Detection Kit (Lonza). Cells were treated with 2 ng/mL murine IL1α (211-11A, Peprotech) and TNFα (315-01A, Peprotech) as indicated (“cytokines”). Cells were also treated with MLN120B (IKKβ inhibitor, 10 μmol/L), AZD1480 (JAK inhibitor, 2 μmol/L), anti-leukemia inhibitory factor (LIF; 4 μg/mL, AF449, R&D), cobalt chloride (CoCl2; 100 μmol/L, Sigma)

Organoid culture

Organoids were derived from pancreatic tumors of KPC (KrasLSL-G12D/+;Trp53LSL-R172H/+;Pdx1-Cre) mice in a C57BL/6 background and described before (23). Organoids were cultured in 24-well plates in GFR Matrigel (Corning) in Advanced DMEM/F12 supplemented with the following: 1% P/S, 2 mmol/L glutamine, 1X B27 supplement (12634-028, Invitrogen), 50 ng/mL murine EGF (PMG8043, Peprotech), 100 ng/mL murine Noggin (250–38; Peprotech), 100 ng/mL human FGF10 (100-26, Peprotech), 10 nmol/L human Leu-Gastrin I (G9145, Sigma), 1.25 mmol/L N-acetylcysteine (A9165, Sigma), 10 mmol/L nicotinamide (N0636, Sigma), and R-spondin1 conditioned media (10% final). Organoids were dissociated with 1× TrypLE (12604013, Thermo Fisher Scientific) and passaged every 3 to 4 days. For PSC coculture, confluent wells of organoids were dissociated with 1× TrypLE and plated at a splitting ratio of 1:5 (∼1 × 104 cells) together with 8 × 104αSMA-DsRed expressing PSCs in GFR Matrigel. Cocultures were cultured with DMEM supplemented with 10% FBS (Gemini) and 1% P/S in 20% O2 and 5% CO2. For experiments in hypoxia, cocultures were placed in a hypoxia glove box (Coy) set at 0.5% O2 for the last 48 hours of the experiment. For measurement of organoid growth in cocultures, organoids expressing Luciferase were used. Cultures were treated with luciferin, lysed, and luminescence was measured.

Metabolic microenvironment chamber experiments

Metabolic microenvironment chambers (MEMIC) were fabricated and used as described in detail previously (26). In brief, MEMICs were three-dimensional printed in a 12-well format, and coverslips were glued at the bottom and the top to create inner and outer chambers. For each condition tested, one well was prepared without the coverslip on the top to create a control well without gradients. MEMICs were washed with water, UV-sterilized, washed twice with PBS and once with complete media before cell seeding. A total of 85 μL cell suspension containing 2 × 104 PSCs was filled in the inner chamber. For the open wells, 1.5 mL of a 1 × 105/mL cell suspension was added to the entire well. Cells were allowed to settle for 1 hour, and 1.5 mL media was added in the outer chamber in wells plated with cells in the inner chamber. The next day, cells were mock-treated or treated with cytokines. The gradient was allowed to form for 48 hours, and cells were either imaged live or fixed with 4% paraformaldehyde for 10 minutes, permeabilized with 0.1% Triton X-100, blocked with 2.5% BSA in PBS, and stained for 1 hour with an anti-GFP antibody (A10262, Invitrogen, RRID:AB_2534023). Wells were washed three times with PBS and incubated with an anti-chicken Alexa Fluor 488 coupled secondary antibody (A11039, Invitrogen) and Hoechst for nuclear staining for 30 minutes before being washed three times with PBS. Wells were imaged using BZ-X800 microscope from Keyence (×20 magnification) and stitched using the BZ-X800 analysis software. Images were processed using custom MATLAB (RRID:SCR_001622) scripts. GFP/UnaG and DsRed fluorescence intensities were quantified and plotted according to their distance to the opening of the well. For per cell fluorescence quantification, images were segmented using nuclear staining and dilated to include adjacent cytoplasmic areas creating a mask for each cell. Then total fluorescence was integrated for each cell using these masks. Image analysis code is available upon request.

Ectopic gene expression and CRISPR/Cas9-mediated gene deletion

Guide RNAs targeting murine Hif1a and Vhl were designed using GuideScan (http://www.guidescan.com/) and cloned into pLentiCRISPRv2 (RRID:Addgene_127644). The following guide sequences were used: TCGTTAGGCCCAGTGAGAAA (Hif1a sg1), CAAGATGTGAGCTCACATTG (Hif1a sg2), CCGATCTTACCACCGGGCAC (Vhl sg1), GGCTCGTACCTCGGTAGCTG (Vhl sg2). Rosa26 targeting guides (Ctrl sg) were described before (27). To create IL6 and hypoxia reporters, a Gibson assembly-based modular assembly platform (GMAP) was used (28). HRE-dUnaG from pLenti-HRE-dUnaG (RRID:Addgene_124372), and a phosphoglycerate kinase (PGK)-driven hygromycin selection cassette from MSCV Luciferase PGK-hygro (RRID:Addgene_18782) were amplified using primers containing overhangs with the homology sites for GMAP cloning and inserted into a lentiviral vector (LV 1-5; Addgene, 68411). IL6-EGFP from pmIL-6promoterEGFP (RRID:Addgene_112896), and a PGK-driven blasticidin selection cassette from pMSCV-Blasticidin (RRID:Addgene_75085) were amplified for GMAP similarly and inserted into LV 1-5. Lentiviral particles were produced in 293T cells by using psPAX2 (RRID:Addgene_12260) and pCMV-VSV-G (RRID:Addgene_8454) packaging plasmids. Viral supernatant was collected after 48 hours, passed through a 0.45 μm nylon filter and used to transduce PSCs in the presence of 8 μg/mL polybrene (Sigma) overnight. Cells were subjected to puromycin (2 μg/mL, Sigma), hygromycin (250 μg/mL), or blasticidin (10 μg/mL, Invivogen) antibiotic selection the following day. Polyclonal cell populations were used for the experiments.

Western blot analysis

Lysates were generated by incubating cells in RIPA buffer (Millipore). Cytoplasmic and nuclear fractions were generated as described previously (29). A total of 20–30 μg of cleared lysate were analyzed by SDS-PAGE as described previously (27). The following primary antibodies were used: vinculin (1:5,000 dilution, Sigma, V9131, RRID:AB_477629), β-actin (1:5,000; Sigma, A5441, RRID:AB_476744), HIF1α (1:1,000, 10006421, Cayman, RRID:AB_409037), VHL (1:200, sc-5575, Santa Cruz Biotechnology, RRID:AB_2241850), LDHA (1:1,000, 2012S, Cell Signaling Technology, RRID:AB_2137173), GFP (1:1,000, 11814460001, Sigma, RRID:AB_390913), phospho-Stat3 Tyr709 (1:1,000, 9145S, Cell Signaling Technology, RRID:AB_2491009) or Stat3 (1:1,000, 9139S, Cell Signaling Technology), p65 (1:1,000, 8242S, Cell Signaling Technology, RRID:AB_331757), lamin A/C (1:1,000, 4777, Cell Signaling Technology, RRID:AB_10545756). The following secondary antibodies were used: anti-rabbit HRP (1:5,000, NA934V, GE, RRID:AB_11112914) and anti-mouse HRP (1:5,000, NA931, GE, RRID:AB_772210).

ELISA

Quantification of IL6 in PSC conditioned media was performed with the Mouse IL6 ELISA Kit (ab100712, Abcam). VEGF was quantified with the Mouse VEGF Quantikine ELISA Kit (MMV00, R&D).

Flow cytometry

For analysis of PSC monocultures, cells were trypsinized, washed, stained with DAPI and analyzed on an LSRFortessa II (BD). Live cells (DAPI) were analyzed for EGFP fluorescence. For organoid/PSC cocultures, Matrigel was digested with Dispase (Corning), and cells and organoids were dissociated mechanically by pipetting up and down at least 30 times. PSCs were analyzed by gating for DAPI and DsRed+ cells followed by analysis of EGFP fluorescence intensity. For analysis of CAFs from PDAC tumors arising from orthotopic injection of KPC organoids, tumors were minced and resuspended in 5 mL DMEM with 800 μg/mL Dispase (Sigma), 500 μg/mL Collagenase P (Sigma), 100 μg/mL Liberase TL (Roche), 100 μg/mL DNaseI (Sigma), 100 μg/mL Hyaluronidase (Sigma). Samples were then transferred to C-tubes and processed using program 37C_m_TDK1_2 on a gentleMACS Octo dissociator with heaters (Miltenyi Biotec). Dissociated tissue was passaged through a 40 μm cell strainer and centrifuged at 1,500 rpm × 5 minutes. Red blood cells were lysed with ACK (Ammonium-Chloride-Potassium) lysis buffer (A1049201, Thermo Fisher Scientific) for 1 minute, and tubes were filled up with PBS. Samples were centrifuged and resuspended in FACS buffer (PBS supplemented with 2% FBS) and stained with Ghost Dye Violet 510 (1:1,000, Tonbo Biosciences) on ice for 10 minutes for discrimination of viable and nonviable cells. Samples were blocked with anti-CD16/32 (FC block, 1:100, BioLegend, RRID:AB_2612550) for 15 minutes on ice and then incubated with the following antibodies (all from BioLegend) in Brilliant stain buffer (Thermo Fisher Scientific) for 30 minutes on ice: CD326-FITC (G8.8, 1:50), CD45-BV711 (30-F11, 1:200, RRID:AB_2564590), CD31-PE/Cy7 (390, 1:200, RRID:AB_2795050), PDPN-APC/Cy7 (8.1.1, 1:100, RRID:AB_2629804), Ly6C-BV421 (HK1.4, 1:200, RRID:AB_2562178), MHCII-BV785 (M5/114.15.2, 1:200, RRID:AB_2565977). Samples were washed in FACS buffer and fixed and permeabilized with the Foxp3/Transcription Factor Staining Buffer Set (00-5523-00, Thermo Fisher Scientific) according to the manufacturer's instructions. Samples were stained with anti-pimonidazole antibody (4.3.11.3, 1:50, Hypoxyprobe, RRID:AB_2801307) in permeabilization buffer at 4°C overnight. Samples were incubated with anti-mouse Alexa Fluor 647 (1:400, Thermo Fisher Scientific, RRID:AB_2535804) in permeabilization buffer for 15 minutes at room temperature. Samples were resuspended in FACS buffer and analyzed on an LSRFortessa II by gating for Ghost Dye-, CD45, CD31, CD326, PDPN+ cells comparing Ly6C with Ly6C+ cells or iCAFs (Ly6C+, MHCII), apCAFs (Ly6C, MHCII+) and myCAFs (Ly6C, MHCII). Compensation was performed with UltraComp eBeads (01-2222-42, Thermo Fisher Scientific). Data were analyzed with FlowJo software (RRID:SCR_008520). For analysis of αSMA expression, fixed and permeabilized samples were stained with Alexa Fluor 488 coupled anti-SMA antibody (1A4, 1:200, Thermo Fisher Scientific, RRID:AB_2574461).

Quantification of gene expression

RNA isolation and analysis was done as described previously (22). Total RNA was isolated from fibroblasts with TRIzol (Life Technologies) according to the manufacturer's instructions, and 1 μg RNA was used for cDNA synthesis using iScript (Bio-Rad). qPCR analysis was performed in technical triplicates using 1:20 diluted cDNAs and 0.1 μmol/L forward and reverse primers together with Power SYBR Green (Life Technologies) in a QuantStudio 7 Flex (Applied Biosystems). Gene expression was quantified in Microsoft Excel 365 (RRID:SCR_016137) as relative expression ratio using primer efficiencies calculated by a relative standard curve. The geometric mean of the endogenous control genes Actb and Rplp0 was used as reference sample. Primer pairs are as follows: TACCACCATGTACCCAGGCA (Actb FW), CTCAGGAGGAGCAATGATCTTGAT (Actb RV), AGATTCGGGATATGCTGTTGGC (Rplp0 FW), TCGGGTCCTAGACCAGTGTTC (Rplp0 RV), CCATCATGCGTCTGGACTT (αSMA FW), GGCAGTAGTCACGAAGGAATAG (αSMA RV), CTTCCATCCAGTTGCCTTCT (IL6 FW), CTCCGACTTGTGAAGTGGTATAG (IL6 RV), CATTGTCAAGTACAGTCCACACT (Ldha FW), TTCCAATTACTCGGTTTTTGGGA (Ldha RV). ATTTCGCTTCGGGACTAGC (Socs3 FW), AACTTGCTGTGGGTGACCAT (Socs3 RV), CTGCTCTCCCTCTTTCCTTTC (Lif FW), ACATTCCCACAGGGTACATTC (Lif RV).

RNA sequencing

Total RNA was isolated with TRIzol as above, and libraries were prepared from polyA-selected mRNA using the TruSeq RNA Sample Preparation Kit v2 (Illumina) according to the manufacturer's instructions. Libraries were sequenced using an Illumina HiSeq 4000 generating 150 bp paired-end reads. An average of 58 million reads per sample was retrieved. Adaptor sequences were removed from fastq files with Trimmomatic v.0.36 (RRID:SCR_011848), and trimmed reads were mapped to the mus musculus GRCm38 reference genome using the STAR aligner v.2.5.2b (RRID:SCR_004463). Aligned features were counted with featureCounts from the Subread package v.1.5.2 and differential expression was determined using DESeq2 v3.10 (RRID:SCR_000154) from Bioconductor in R v4.1.0.

Gene set enrichment analysis

Gene set enrichment analysis (GSEA) was performed using a preranked gene list based on the log2-fold change comparing three Ctrl sg samples cultured in normoxia against three Ctrl sg samples cultured in hypoxia for 48 hours, or comparing three Ctrl sg samples cultured in hypoxia against three Hif1a sg7 samples cultured in hypoxia. GSEA 4.3.0 (RRID:SCR_003199) was used with 1,000 permutations and mouse gene symbols remapped to human orthologs v7.5 (MSigDB). Enrichment of the iCAF signature (4) or Hallmark signatures (MSigDB) was analyzed.

Statistical analysis

A Student t test was applied to compare one variable between two groups. One-way ANOVA was applied to compare one variable between three or more groups. Two-way ANOVA was applied to compare two independent variables between two groups. Correction for multiple comparisons was done using the Holm–Sidak method. Statistical analysis was done in GraphPad Prism 9 (RRID:SCR_002798). Most graphs show the mean + SD with individual datapoints, unless indicated otherwise in the figure legends. One tumor in the anti-VEGFR2 group was identified as an outlier (ROUT test) and was excluded from the analysis.

Data availability

RNA-sequencing data have been deposited in Gene Expression Omnibus (GSE221761). Other expression data analyzed in this study were obtained from NCBI dbGaP (phs001840.v1.p1). All other data are available from the corresponding authors upon reasonable request.

To investigate factors regulating CAF heterogeneity in PDAC, we analyzed publicly available single-cell RNA-sequencing (scRNA-seq) data from human patients with PDAC (5). Single-sample GSEA revealed enrichment of an inflammatory response signature in iCAFs and a collagen formation signature in myCAFs (Fig. 1A), as reported previously (5). Using these data, we found that an oxidative phosphorylation signature was enriched in myCAFs (Fig. 1A), consistent with our previous work showing that mitochondrial oxidative metabolism is required for proline biosynthesis and for collagen production (27). Conversely, a hypoxic gene expression signature was enriched in iCAFs (Fig. 1A). To confirm this finding, we used a murine orthotopic PDAC organoid transplantation model, which closely recapitulates key features of human PDAC (30). PDAC organoids derived from the KPC (KrasLSL-G12D/+;Trp53LSL-R172H/+;Pdx1-Cre) mouse model (31) were injected orthotopically into the pancreas of syngeneic C57BL/6 mice. Once tumors reached approximately 500 mm3, pimonidazole, a hypoxia indicator (32), was injected intraperitoneally one hour before euthanasia (Fig. 1B). Half of each tumor was digested, and CAFs (gated for CD31CD45EpCAMPDPN+ cells) were counterstained for Ly6C as an iCAF surface marker (10) and analyzed for pimonidazole accumulation by flow cytometry (Fig. 1CE). Consistent with the gene expression data, this analysis revealed that Ly6C+ CAFs had accumulated higher amounts of pimonidazole than Ly6C CAFs (Fig 1D and E). In a separate experiment, we also stained for MHC-II (Supplementary Fig. S1A), an apCAF surface marker (10). Consistent with the previous experiment, iCAFs (MHC-IILy6C+) accumulated significantly more pimonidazole compared with apCAFs (MHC-II+Ly6C) and myCAFs (MHC-IILy6C; Supplementary Fig. S1B and S1C). In addition, a hypoxia gene expression signature was enriched in iCAFs compared with apCAFs in scRNA-seq data from murine PDAC tumors (Supplementary Fig. S1D; ref. 5). Next, we analyzed the other halves of the PDAC tumors for the presence of pimonidazole, the general CAF marker PDPN and the myCAF marker αSMA by IF (Fig. 1F). Strikingly, the vast majority of αSMA+ cells was located outside pimonidazole+ areas (Fig. 1F). In turn, 80% of the PDPN+ areas within pimonidazole+ regions stained negative for αSMA (Fig. 1F and G).

Figure 1.

A hypoxic signature is enriched in inflammatory fibroblasts in PDAC. A, Single-sample GSEA of selected hallmark signatures in myCAFs and iCAFs based on scRNA-seq data from human PDAC. Data from ref. 5. B, Schematic of experimental workflow to analyze pimonidazole enrichment and localization in mouse PDAC tumors arising from orthotopic transplantation of KPC organoids. C–E, Analysis of pimonidazole in Ly6C+ and Ly6C cells among live, CD31CD45EpCAMPDPN+ cells in PDAC tumors. C, Gating for Ly6C in PDPN+ cells. D and E, Histogram of fluorescence intensity (D) and quantification of pimonidazole median fluorescence intensity (MFI; E) comparing Ly6C+ and Ly6C cells. A.U., arbitrary units. N = 3 mice. P value was calculated by ratio paired t test. F and G, IF staining of pimonidazole, PDPN, and αSMA in mouse PDAC tumors. F, Representative image. Nuclei were labeled with DAPI. Scale bar, 500 μm. G, Quantification of αSMA and αSMA+ pixel among PDPN+ pixel within pimonidazole-stained regions. N = 8 sections from four mice. Data represent mean + SD. P value was calculated by ratio paired t test. H, GSEA comparing PSCs cultured in normoxia (20% O2) or hypoxia (0.5% O2) for 48 hours. iCAF signature derived from ref. 4. Other signatures represent Hallmark signatures from MSigDB. N = 3 biological replicates.

Figure 1.

A hypoxic signature is enriched in inflammatory fibroblasts in PDAC. A, Single-sample GSEA of selected hallmark signatures in myCAFs and iCAFs based on scRNA-seq data from human PDAC. Data from ref. 5. B, Schematic of experimental workflow to analyze pimonidazole enrichment and localization in mouse PDAC tumors arising from orthotopic transplantation of KPC organoids. C–E, Analysis of pimonidazole in Ly6C+ and Ly6C cells among live, CD31CD45EpCAMPDPN+ cells in PDAC tumors. C, Gating for Ly6C in PDPN+ cells. D and E, Histogram of fluorescence intensity (D) and quantification of pimonidazole median fluorescence intensity (MFI; E) comparing Ly6C+ and Ly6C cells. A.U., arbitrary units. N = 3 mice. P value was calculated by ratio paired t test. F and G, IF staining of pimonidazole, PDPN, and αSMA in mouse PDAC tumors. F, Representative image. Nuclei were labeled with DAPI. Scale bar, 500 μm. G, Quantification of αSMA and αSMA+ pixel among PDPN+ pixel within pimonidazole-stained regions. N = 8 sections from four mice. Data represent mean + SD. P value was calculated by ratio paired t test. H, GSEA comparing PSCs cultured in normoxia (20% O2) or hypoxia (0.5% O2) for 48 hours. iCAF signature derived from ref. 4. Other signatures represent Hallmark signatures from MSigDB. N = 3 biological replicates.

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The above data indicate a significant positive correlation between hypoxia and the iCAF phenotype in PDAC. To test the hypothesis that hypoxia causally promotes acquisition of an iCAF state in fibroblasts, we used immortalized PSCs, which contribute to CAFs in PDAC (33). After confirming their fibroblast nature (Supplementary Fig. S1E), PSCs were cultured for 48 hours in normoxic (20% O2) or hypoxic (0.5% O2) conditions and their transcriptome was interrogated by RNA sequencing. While there was no significant change in the myCAF signature (Supplementary Fig. S1F), hypoxic culture conditions resulted in enrichment of an iCAF signature in PSCs, as well as an inflammatory response signature and IL6/JAK/STAT signaling (Fig. 1H).

The above data suggest a role of hypoxia in promoting an iCAF-like state. IL1 and TNFα have been identified as major cytokines secreted by pancreatic cancer cells that are capable of inducing an iCAF phenotype in PDAC (10). To assess the role of hypoxia in regulating CAF heterogeneity in relation to known inducers of the iCAF state, we treated PSCs with a combination of IL1 and TNFα (hereafter “cytokines”) to maximize cytokine signaling known to promote an iCAF phenotype. Hypoxia resulted in induction of the iCAF marker IL6 and repression of the myCAF marker αSMA (encoded by Acta2, hereafter αSMA; Supplementary Fig. S2A). When we cultured cytokine-treated PSCs in hypoxia there was a significant increase in IL6 expression and a further decrease in αSMA mRNA levels (Supplementary Fig. S2A). To monitor acquisition of an iCAF state in PSCs by orthogonal methods, we developed a reporter system in which EGFP expression is driven by the murine IL6 promoter region (Fig. 2A). Responsiveness of the reporter to cytokine treatment was confirmed (Fig. 2A and B). Hypoxia was sufficient to increase the IL6-EGFP reporter signal to a similar level as did cytokine treatment, and culture of cytokine-treated cells in hypoxia further increased the reporter signal to more than 15-fold above mock-treated cells cultured in normoxia (Fig. 2A and B). Similarly, hypoxia increased IL6 protein levels, and in combination with cytokine treatment led to a synergistic upregulation of IL6 in the media (Fig. 2C). Next, we combined the iCAF reporter with a myCAF reporter in which DsRed expression is driven by the murine αSMA promoter region (24). Consistent with the prior observation that PSCs in monoculture on plastic display characteristics of myCAFs (4, 10), high expression of αSMA-DsRed was detected in untreated PSCs cultured in normoxia, while IL6-EGFP was undetectable (Fig. 2D). Cytokine treatment reduced αSMA-DsRed levels, and in combination with hypoxia resulted in suppression of the αSMA-DsRed signal (Fig. 2D). In contrast, both cytokines and hypoxia increased IL6-EGFP levels individually to similar levels and when combined led to marked accumulation of the IL6-EGFP signal (Fig. 2D), indicating a switch in the expression of myCAF and iCAF markers under these conditions.

Figure 2.

Hypoxia potentiates the cytokine-induced inflammatory fibroblast phenotype. A and B, Fluorescence intensity of IL6-EGFP expressing PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines (IL1/TNFα) for 48 hours. A, Histogram of IL6-EGFP fluorescence intensity. B, Quantification of the relative median fluorescence intensity (MFI) of IL6-EGFP. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. C, Quantification of IL6 levels in media conditioned by PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. D, Representative images of IL6-EGFP and αSMA-DsRed expressing PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. Scale bar, 200 μm. E–I, MEMIC experiment. E, Schematic of the MEMIC, adapted from refs. 26, 35. PSCs expressing IL6-EGFP were plated in the inner chamber and treated with cytokines the next day. Gradients were allowed to form for 48 hours. Representative images of MEMIC experiments with PSCs expressing HRE-dUnaG (F) or IL6-EGFP and αSMA-DsRed (H) treated with cytokines and cultured in the MEMIC for 48 hours. Scale bar, 500 μm. Quantification of HRE-dUnaG (G) or IL6-EGFP and αSMA-DsRed (I) fluorescence intensity with increasing distance from the oxygen-rich opening. A.U., arbitrary units; px, pixel. J and K, PSC/Tumor organoid coculture experiment. PSCs expressing IL6-EGFP and αSMA-DsRed were cultured alone or together with KPC organoids in Matrigel for 5 days. In the last 48 hours, part of the cultures was incubated in hypoxia. J, Histogram of IL6-EGFP fluorescence intensity in PSCs. K, Quantification of the relative MFI of IL6-EGFP in PSCs. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA.

Figure 2.

Hypoxia potentiates the cytokine-induced inflammatory fibroblast phenotype. A and B, Fluorescence intensity of IL6-EGFP expressing PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines (IL1/TNFα) for 48 hours. A, Histogram of IL6-EGFP fluorescence intensity. B, Quantification of the relative median fluorescence intensity (MFI) of IL6-EGFP. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. C, Quantification of IL6 levels in media conditioned by PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. D, Representative images of IL6-EGFP and αSMA-DsRed expressing PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. Scale bar, 200 μm. E–I, MEMIC experiment. E, Schematic of the MEMIC, adapted from refs. 26, 35. PSCs expressing IL6-EGFP were plated in the inner chamber and treated with cytokines the next day. Gradients were allowed to form for 48 hours. Representative images of MEMIC experiments with PSCs expressing HRE-dUnaG (F) or IL6-EGFP and αSMA-DsRed (H) treated with cytokines and cultured in the MEMIC for 48 hours. Scale bar, 500 μm. Quantification of HRE-dUnaG (G) or IL6-EGFP and αSMA-DsRed (I) fluorescence intensity with increasing distance from the oxygen-rich opening. A.U., arbitrary units; px, pixel. J and K, PSC/Tumor organoid coculture experiment. PSCs expressing IL6-EGFP and αSMA-DsRed were cultured alone or together with KPC organoids in Matrigel for 5 days. In the last 48 hours, part of the cultures was incubated in hypoxia. J, Histogram of IL6-EGFP fluorescence intensity in PSCs. K, Quantification of the relative MFI of IL6-EGFP in PSCs. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA.

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In tumors, there are gradients of oxygen and nutrient availability (34). To better model these gradients, we cultured PSCs together with cytokines in a MEMIC, which allows the establishment of oxygen and nutrient gradients within the same culture well (Fig. 2E; refs. 26, 35). Using PSCs expressing the hypoxia reporter HRE-dUnaG (36), we confirmed establishment of an oxygen gradient along the MEMIC (Fig. 2F and G; Supplementary Fig. S2B). While αSMA-DsRed reporter levels gradually declined along the gradient, the IL6-EGFP reporter signal increased toward ischemic regions (Fig. 2H and I; Supplementary Fig. S2C–S2F), indicating that PSCs lose myCAF but acquire iCAF markers in ischemic conditions.

While PSCs cultured on plastic are considered myCAFs, PSCs cultured in Matrigel become quiescent and can acquire an iCAF state when cocultured with PDAC organoids in Matrigel (4), a process dependent on organoid-derived cytokines (10). Consistent with this, we observed higher levels of IL6-EGFP but lower levels of αSMA-DsRed in PSCs cocultured with KPC organoids in Matrigel for 5 days (Supplementary Fig. S2G–S2J). Next, cocultures of PSCs and KPC organoids were placed in hypoxia for the last 48 hours of the culture period. Hypoxia was sufficient to elevate expression of IL6-EGFP in PSCs to similar levels as did organoid coculture, and exposure of cocultures to hypoxia further elevated IL6-EGFP reporter levels in PSCs (Fig. 2J and K).

The above data suggest that hypoxia can induce an iCAF-like state in PSCs and that hypoxia potentiates the ability of cancer cell-secreted cytokines to promote an iCAF phenotype in PSCs while suppressing expression of myCAF markers. Next, we sought to determine the underlying mechanism. Among factors known to induce the iCAF state (10), we found a significant upregulation of Lif expression after culturing PSCs for 4 hours in hypoxia, while the iCAF marker IL6 was induced only after 24 hours exposure to hypoxia (Supplementary Fig. S3A). To test whether Lif expression plays a role in promoting an iCAF-like state in hypoxia, we cultured PSCs for 24 hours in hypoxia in the presence of an anti-LIF neutralizing antibody. Blocking LIF reduced the IL6-EGFP reporter signal induced by hypoxic culture, while in turn, rescuing downregulation of the αSMA-DsRed reporter in hypoxia (Supplementary Fig. S3B). IL1α-induced LIF has been shown to promote the iCAF state by activating JAK/STAT signaling in PSCs (10). Hypoxia increased activation of STAT3 and expression of the JAK/STAT target Socs3, peaking at 4 to 24 hours after exposure to hypoxia (Supplementary Fig. S3C and S3D). STAT3 activation and Socs3 expression were reduced in the presence of an anti-LIF neutralizing antibody (Supplementary Fig. S3E and S3F). Consistent with the role of JAK/STAT signaling in regulating the iCAF state, we found that the JAK inhibitor AZD1480 reduced IL6 expression induced by hypoxia, while rescuing hypoxia-mediated repression of αSMA (Supplementary Fig. S3G and S3H). These data implicate a role for LIF and JAK/STAT signaling in the acquisition of an iCAF-like state in PSCs following exposure to hypoxia.

Previous analysis of transcription factor activity in human PDAC scRNA-seq data (5) indicated that in addition to the known iCAF regulators STAT3 and REL (NFκB), HIF1α activity is enriched in iCAFs (Supplementary Fig. S3I). To test whether HIF1α is active in CAFs accumulating in hypoxic regions in PDAC, we stained tumors from pimonidazole-injected mice (Fig. 1B) with a HIF1α antibody. Indeed, nuclear HIF1α was found in PDPN+αSMA CAFs in pimonidazole+ regions, but not in PDPN+αSMA+ CAFs accumulating outside of pimonidazole+ regions (Fig. 3A). Hif1a is not transcribed in resting fibroblasts and its transcription is induced by growth factor and/or cytokine stimulation (37). Even when transcription is induced, fibroblasts like other cells do not accumulate HIF1α protein due to the oxygen-dependent degradation by Von Hippel–Lindau (VHL) tumor suppressor (38). Like fibroblasts, PSCs accumulated little HIF1α under hypoxia; however, when stimulated by cytokines under hypoxic conditions, HIF1α was upregulated synergistically over time, and we observed increased expression of the HIF1α target LDHA compared with hypoxia alone (Fig. 3B). Hif1a transcription has been shown to be induced by NFκB signaling as a result of cytokine stimulation (37, 39). To test the role of NFκB signaling in hypoxia and cytokine-induced HIF1α upregulation, we treated PSCs with the IKKβ inhibitor (IKKβi) MLN120B. Cytokine stimulation resulted in nuclear accumulation of the NFκB subunit p65, which was inhibited by IKKβi (Supplementary Fig. S3J). While hypoxia did not alter Hif1a mRNA expression, Hif1a transcript and protein were induced by cytokine treatment in hypoxic PSCs in an NFκB-dependent fashion (Fig. 3C; Supplementary Fig. S3J). In contrast, hypoxia reduced Hif2a mRNA expression, and Hif2a did not respond to additional stimulation by cytokines (Supplementary Fig. S3K). Higher levels of HIF1α were also found in PSCs cotreated with cytokines and CoCl2, a known inducer of HIF1α stabilization and signaling (38), compared with CoCl2 treatment alone (Supplementary Fig. S3L). While CoCl2 treatment alone increased levels of the IL6-EGFP reporter, combined treatment with CoCl2 and cytokines elevated the IL6-EGFP signal even more (Supplementary Fig. S3L–S3N).

Figure 3.

HIF1α mediates the hypoxia-induced inflammatory phenotype in fibroblasts. A, IF staining of pimonidazole, PDPN, αSMA, and HIF1a in mouse PDAC tumors. Representative image. Nuclei were labeled with DAPI. Scale bar, 500 μm. Yellow arrows, PDPN+HIF1a+ cells. B, Western blot analysis of PSCs cultured in normoxia or in hypoxia in the presence or absence of cytokines for 15 minutes, 1 hour, or 4 hours. Cytokine treatment and hypoxia were started at the same time. Representative experiments are shown. C, qPCR for Hif1a in PSCs cultured in normoxia or hypoxia for 4 hours and treated with cytokines in the presence or absence of the IKKβ inhibitor MLN120B. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. D, Western blot analysis of PSCs expressing IL6-EGFP and control or Hif1a sgRNA and cultured in hypoxia. Cells were mock-treated or treated with cytokines for 48 hours. Representative experiment. E, qPCR for the indicated transcripts in PSCs expressing control or Hif1a sgRNA and cultured in normoxia or hypoxia for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. F, GSEA comparing PSCs expressing control or Hif1a sgRNA and cultured in hypoxia for 48 hours. iCAF signature derived from ref. 4. Other signatures represent Hallmark signatures from MSigDB. N = 3 biological replicates. G and H, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Hif1a sgRNA cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. G, Histogram of IL6-EGFP fluorescence intensity in mock-treated cells. H, Quantification of the relative median fluorescence intensity (MFI) of IL6-EGFP. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. I and J, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Hif1a sgRNA cocultured with KPC organoids for 5 days. In the last 48 hours, part of the cultures was incubated in hypoxia. I, Histogram of IL6-EGFP fluorescence intensity in PSCs cultured with organoids in hypoxia. J, Quantification of relative MFI of IL6-EGFP in PSCs. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA.

Figure 3.

HIF1α mediates the hypoxia-induced inflammatory phenotype in fibroblasts. A, IF staining of pimonidazole, PDPN, αSMA, and HIF1a in mouse PDAC tumors. Representative image. Nuclei were labeled with DAPI. Scale bar, 500 μm. Yellow arrows, PDPN+HIF1a+ cells. B, Western blot analysis of PSCs cultured in normoxia or in hypoxia in the presence or absence of cytokines for 15 minutes, 1 hour, or 4 hours. Cytokine treatment and hypoxia were started at the same time. Representative experiments are shown. C, qPCR for Hif1a in PSCs cultured in normoxia or hypoxia for 4 hours and treated with cytokines in the presence or absence of the IKKβ inhibitor MLN120B. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. D, Western blot analysis of PSCs expressing IL6-EGFP and control or Hif1a sgRNA and cultured in hypoxia. Cells were mock-treated or treated with cytokines for 48 hours. Representative experiment. E, qPCR for the indicated transcripts in PSCs expressing control or Hif1a sgRNA and cultured in normoxia or hypoxia for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. F, GSEA comparing PSCs expressing control or Hif1a sgRNA and cultured in hypoxia for 48 hours. iCAF signature derived from ref. 4. Other signatures represent Hallmark signatures from MSigDB. N = 3 biological replicates. G and H, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Hif1a sgRNA cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. G, Histogram of IL6-EGFP fluorescence intensity in mock-treated cells. H, Quantification of the relative median fluorescence intensity (MFI) of IL6-EGFP. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. I and J, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Hif1a sgRNA cocultured with KPC organoids for 5 days. In the last 48 hours, part of the cultures was incubated in hypoxia. I, Histogram of IL6-EGFP fluorescence intensity in PSCs cultured with organoids in hypoxia. J, Quantification of relative MFI of IL6-EGFP in PSCs. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA.

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The above data suggested a role of HIF1α in the hypoxia-mediated regulation of the iCAF state. To investigate this possibility, we expressed Hif1a single-guide RNAs (sgRNA), which reduced protein levels of HIF1α and its target LDHA in mock-treated as well as cytokine-treated PSCs in hypoxia (Fig. 3D). Hypoxic induction of IL6 and Ldha as well as repression of αSMA in PSCs was dependent on HIF1α (Fig. 3E; Supplementary Fig. S3O). In addition, Hif1a sgRNA reduced IL6 accumulation in the media of PSCs cultured in hypoxia (Supplementary Fig. S3P). On a global gene expression level, the iCAF signature as well as inflammatory response, IL6/JAK/STAT signaling signatures in hypoxic PSCs were dependent on HIF1α (Fig. 3F). The expression of the myCAF signature was unchanged in HIF1α deleted PSCs in hypoxia (Supplementary Fig. S3Q). Furthermore, the hypoxia-induced increase in IL6-EGFP fluorescence required HIF1α (Fig. 3G and H). Given the further upregulation of HIF1α in hypoxic cells by cytokine treatment, we also analyzed Hif1a sgRNA expressing PSCs in the presence of cytokines. Hif1a sgRNA prevented the synergistic accumulation of IL6-EGFP in cytokine-treated PSCs cultured in hypoxia (Fig. 3D and H). Similar results were obtained in Hif1a sgRNA expressing PSCs treated with CoCl2 (Supplementary Fig. S3R and S3S). Moreover, the hypoxia-induced upregulation of IL6-EGFP reporter levels in PSCs cocultured with KPC organoids without addition of exogenous cytokines beyond those produced by organoid cultures was also dependent on HIF1α (Fig. 3I and J).

Next, we investigated whether HIF1α stabilization can be sufficient to shift fibroblasts toward an iCAF-like state. To induce HIF1α accumulation under normoxic conditions, we deleted Vhl, which targets hydroxylated HIF1α for proteasomal degradation (Fig. 4A; ref. 38). Vhl-deleted PSCs displayed higher expression of IL6 and Ldha mRNA, while αSMA expression was reduced (Fig. 4B). We also detected higher levels of IL6 in spent media of Vhl-deleted PSCs (Fig. 4C). Vhl deletion alone increased IL6-EGFP levels more than cytokine treatment, and when combined, Vhl deletion and cytokines elevated IL6-EGFP reporter signals 10-fold (Fig. 4A, D, and E). Vhl deletion also promoted the IL6-EGFP signal in PSCs cocultured with KPC organoids without addition of exogenous cytokines (Fig. 4F and G).

Figure 4.

HIF1α stabilization in fibroblasts can be sufficient to promote an inflammatory phenotype and tumor growth. A, Western blot analysis of PSCs expressing control or Vhl sgRNAs and cultured in normoxia. A representative experiment is shown. B, qPCR for the indicated transcripts in PSCs expressing control or Vhl sgRNA cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by Student t test. C, Quantification of IL6 levels in media conditioned by PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. N = 6 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. D and E, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Vhl sgRNA cultured in normoxia and mock-treated or treated with cytokines for 48 hours. D, Histogram of IL6-EGFP fluorescence intensity in mock-treated cells. E, Quantification of the relative median fluorescence intensity (MFI) of IL6-EGFP. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. F and G, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Vhl sgRNA cocultured with KPC organoids for 5 days in normoxia. F, Histogram of IL6-EGFP fluorescence intensity in PSCs. G, Quantification of the relative MFI of IL6-EGFP in PSCs. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. H–J, Subcutaneous coinjection of KPC cells alone or together with PSCs expressing control of Vhl sgRNA. H, αSMA fluorescence intensity of CD31CD45EpCAM cells. I, Quantification of CD31CD45EpCAM cells expressing low levels of αSMA. N = 8 (Ctrl) or 9 (Vhl sg2) biological replicates. Data represent mean + SD. P values were calculated by Student t test. J, Tumor volume. N = 9 biological replicates. Data represent mean ± SEM. P values were calculated by one-way ANOVA.

Figure 4.

HIF1α stabilization in fibroblasts can be sufficient to promote an inflammatory phenotype and tumor growth. A, Western blot analysis of PSCs expressing control or Vhl sgRNAs and cultured in normoxia. A representative experiment is shown. B, qPCR for the indicated transcripts in PSCs expressing control or Vhl sgRNA cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by Student t test. C, Quantification of IL6 levels in media conditioned by PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. N = 6 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. D and E, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Vhl sgRNA cultured in normoxia and mock-treated or treated with cytokines for 48 hours. D, Histogram of IL6-EGFP fluorescence intensity in mock-treated cells. E, Quantification of the relative median fluorescence intensity (MFI) of IL6-EGFP. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. F and G, Fluorescence intensity of PSCs expressing IL6-EGFP and control or Vhl sgRNA cocultured with KPC organoids for 5 days in normoxia. F, Histogram of IL6-EGFP fluorescence intensity in PSCs. G, Quantification of the relative MFI of IL6-EGFP in PSCs. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. H–J, Subcutaneous coinjection of KPC cells alone or together with PSCs expressing control of Vhl sgRNA. H, αSMA fluorescence intensity of CD31CD45EpCAM cells. I, Quantification of CD31CD45EpCAM cells expressing low levels of αSMA. N = 8 (Ctrl) or 9 (Vhl sg2) biological replicates. Data represent mean + SD. P values were calculated by Student t test. J, Tumor volume. N = 9 biological replicates. Data represent mean ± SEM. P values were calculated by one-way ANOVA.

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The above data indicate that Vhl deletion induces an iCAF-like state in PSCs. To test this in vivo, we used a subcutaneous allograft model. Tumors formed by KPC pancreatic cancer cells coinjected with Vhl-deleted compared with control PSCs had a lower abundance of αSMA+ CAFs (Supplementary Fig. S4A and S4B). Within the αSMA+ population, a higher proportion of cells that expressed only low levels of αSMA, a characteristic of iCAFs, was found in tumors formed by KPC cells coinjected with Vhl-deleted PSCs (Fig. 4H and I). Given that iCAFs are associated with tumor growth (10), we sought to test whether Vhl deletion in PSCs would increase their ability to promote tumor growth in the same model. Coinjection of PSCs together with KPC pancreatic cancer cells promoted tumor growth compared with KPC cells alone (Fig. 4J), as reported before (22). Notably, coinjection of Vhl-deleted PSCs increased tumor growth significantly more than did control PSCs (Fig. 4J).

Our data indicate that Vhl deletion-induced HIF1α stabilization in PSCs can be sufficient to promote an iCAF-like state and tumor growth. Given that VHL also targets HIF2α for degradation, we tested whether the Vhl deletion–induced effects in PSCs were HIF1α dependent. To this end, we generated Vhl/Hif1a double-knockout PSCs (Fig. 5A). Hif1a deletion rescued IL6 and Ldha induction as well as αSMA repression in Vhl-deleted PSCs (Fig. 5A and B). Similarly, upregulation of the IL6-EGFP reporter and accumulation of IL6 protein in Vhl-deleted PSCs was abolished by Hif1a deletion (Fig. 5C and D). To investigate the role of HIF1α in Vhl deletion–mediated tumor support of PSCs, we coinjected KPC cells with control, Vhl-deleted, and Vhl/Hif1a double-knockout PSCs. While Vhl-deleted PSCs promoted tumor growth compared with control PSCs, this effect was not observed upon injection Vhl/Hif1a double-knockout PSCs (Fig. 5E).

Figure 5.

Vhl deletion in PSC promotes an inflammatory phenotype and tumor growth via HIF1α. A, Western blot analysis of PSCs expressing control or Hif1a sgRNAs in the presence or absence of Vhl deletion. Representative experiment. B, qPCR for the indicated transcripts in PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by Student t test. C, Quantification of fluorescence intensity of PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. D, Quantification of IL6 levels in media conditioned by PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. E, Volume of tumors arising from subcutaneous coinjection of KPC cells alone or together with PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs. N = 10 biological replicates. Data represent mean ± SEM. P values were calculated by one-way ANOVA.

Figure 5.

Vhl deletion in PSC promotes an inflammatory phenotype and tumor growth via HIF1α. A, Western blot analysis of PSCs expressing control or Hif1a sgRNAs in the presence or absence of Vhl deletion. Representative experiment. B, qPCR for the indicated transcripts in PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by Student t test. C, Quantification of fluorescence intensity of PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. D, Quantification of IL6 levels in media conditioned by PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. E, Volume of tumors arising from subcutaneous coinjection of KPC cells alone or together with PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs. N = 10 biological replicates. Data represent mean ± SEM. P values were calculated by one-way ANOVA.

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Next, we sought to understand how HIF1α stabilization in PSCs promotes tumor growth. In a coculture model, Vhl deletion in PSCs added only a minimal benefit to organoid growth promoted by cocultured PSCs (Supplementary Fig. S4C), indicating the relevance of the in vivo context for tumor support by PSC HIF1α. Given the HIF1α-dependent expression of IL6 described above, and the critical role of IL6 in PDAC progression (14), we hypothesized that PSC-derived IL6 is involved in tumor growth induced by PSC HIF1α. To test this, we first coinjected KPC cells and Vhl-deleted PSCs into the flanks of wildtype mice, and 1 week later treated the mice with an anti-IL6 mAb or IgG control every 3 days for 2 weeks (Supplementary Fig. S4D). No significant reduction in tumor growth following anti-IL6 treatment was observed (Supplementary Fig. S4D).

Next, we sought to identify factors beyond IL6 that could mediate PSC HIF1α-promoted tumor growth. Analysis of signaling molecule activity in human PDAC scRNA-seq data (5) indicated that in addition to IL6, the HIF1α target VEGFA is among the highest enriched signaling molecules in iCAFs (Fig. 6A). Both Vegfa mRNA and VEGF protein accumulated in PSC cultured in hypoxia and further increased upon cytokine treatment (Fig. 6B and C). Upregulation of Vegfa mRNA and VEGF protein in hypoxia was HIF1α dependent (Fig. 6D and E). Vegfa and VEGF were also upregulated by Vhl deletion in PSCs cultured in normoxia in a HIF1α-dependent fashion (Fig. 6FH). Consistent with these findings, an angiogenesis expression signature was upregulated in hypoxic PSCs in a HIF1α-dependent fashion (Supplementary Fig. S4E), indicating a role for PSC HIF1α in remodeling the tumor vasculature. While no difference was observed in the abundance of CD31+ endothelial cells in tumors arising from coinjection of Vhl-deleted compared with control PSCs (Supplementary Fig. S4F and S4G), there was a significant correlation between the number of CD31+ cells and tumor weight at endpoint (Fig. 6I). Thus, we sought to test the role of VEGF signaling in PSC HIF1α-mediated tumor growth. Mice coinjected with KPC and Vhl-deleted PSCs were treated with an anti-VEGFR2 mAb or IgG control for 2 weeks (Supplementary Fig. S4D). Consistent with the previous experiment, the number of CD31+ cells correlated with tumor weight at endpoint (Supplementary Fig. S4H). Anti-VEGFR2 treatment reduced the abundance of CD31+ cells (Fig. 6J and K) and slowed down tumor growth that was promoted by Vhl-deleted PSCs (Fig. 6L). Taken together, these data indicate hypoxia-induced HIF1α as a regulator of the iCAF state and promotor of tumor growth in PDAC at least in part via VEGF secretion.

Figure 6.

VEGF derived from hypoxia-induced iCAFs promotes tumor growth. A, Activity of a selected set of signaling molecules in myCAFs and iCAFs based on scRNA-seq data from human PDAC. Data from ref. 5. B and C, Expression of Vefga mRNA (B) and protein (C) in PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. D and E, Expression of Vefga mRNA (D) and protein (E) in PSCs expressing control of Hif1a sgRNAs cultured in normoxia or hypoxia for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA (D) or two-way ANOVA (E). F, Quantification of VEGF in media conditioned by PSCs expressing control or Vhl sgRNA. N = 6 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. G and H, Expression of Vefga mRNA (G) and protein (H) in PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. I, Correlation of the number of CD31+CD45 cells with tumor weight in tumors arising from subcutaneous coinjection of KPC cells together with PSCs expressing control or Vhl sgRNA. J–L, Subcutaneous coinjection of KPC cells together with PSCs expressing Vhl sgRNA and treated with an anti-VEGFR2 mAb or IgG control. J and K, Gating (J) for and quantification (K) of CD31+CD45 cells among live cells. L, Tumor volume as percent of change since onset of treatment.

Figure 6.

VEGF derived from hypoxia-induced iCAFs promotes tumor growth. A, Activity of a selected set of signaling molecules in myCAFs and iCAFs based on scRNA-seq data from human PDAC. Data from ref. 5. B and C, Expression of Vefga mRNA (B) and protein (C) in PSCs cultured in normoxia or hypoxia and mock-treated or treated with cytokines for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by two-way ANOVA. D and E, Expression of Vefga mRNA (D) and protein (E) in PSCs expressing control of Hif1a sgRNAs cultured in normoxia or hypoxia for 48 hours. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA (D) or two-way ANOVA (E). F, Quantification of VEGF in media conditioned by PSCs expressing control or Vhl sgRNA. N = 6 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. G and H, Expression of Vefga mRNA (G) and protein (H) in PSCs expressing control, Vhl sgRNA, or Vhl and Hif1a sgRNAs cultured in normoxia. N = 3 biological replicates. Data represent mean + SD. P values were calculated by one-way ANOVA. I, Correlation of the number of CD31+CD45 cells with tumor weight in tumors arising from subcutaneous coinjection of KPC cells together with PSCs expressing control or Vhl sgRNA. J–L, Subcutaneous coinjection of KPC cells together with PSCs expressing Vhl sgRNA and treated with an anti-VEGFR2 mAb or IgG control. J and K, Gating (J) for and quantification (K) of CD31+CD45 cells among live cells. L, Tumor volume as percent of change since onset of treatment.

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Hypoxia is has long been recognized as a characteristic of the PDAC TME and is associated with poor outcomes of patients with PDAC, which is at least in part due to its influence on the cancer cell state (15, 18). Whether hypoxia also affects the stromal cell state in the PDAC TME and their influence on tumor progression is less well understood. Here, we show that hypoxia-induced HIF1α signaling shifts pancreatic CAFs toward acquisition of an iCAF-like state. While hypoxia by itself induces an inflammatory program, this is likely a hybrid state in which cells also display some myCAF features, consistent with upregulation of the iCAF signature in hypoxia while the myCAF signature was unchanged. Our observations that hypoxia potentiates the effects of cytokines secreted by PDAC cells suggests that when both hypoxia and cytokines are present, there is a switch from a myCAF to an iCAF state. This is consistent with our observations that iCAFs accumulate biochemical markers of hypoxia and that αSMA+ CAFs are largely absent from hypoxic regions in murine PDAC. Furthermore, iCAFs display a hypoxic gene expression profile in human patients with PDAC. The selective accumulation of hypoxia markers in iCAFs has also been confirmed in a separate study (40). These data provide evidence for hypoxia as an environmental regulator of fibroblast heterogeneity in PDAC. Given that hypoxia and fibroblast heterogeneity is a feature of the microenvironment of many solid tumors (9), the findings of this study could be relevant to a wide range of solid tumors.

The idea that hypoxia promotes an inflammatory response has been supported by several studies. In mice, short-term exposure to hypoxia is sufficient to promote accumulation of inflammatory cells in several tissues and increases serum levels of various cytokines (41). In addition to being observed in tumors, hypoxia is also a feature of wounds, and fibroblast heterogeneity has been observed in wound healing (42). Thus, our observations further support the idea that cancer cell metabolism can co-opt the normal stromal regenerative response to support tumor growth (43).

Our data suggest that the hypoxia-induced shift of PSCs toward an iCAF-like state is mediated in part by upregulation of LIF in hypoxia, which activates JAK/STAT signaling in a cell-autonomous fashion. LIF is also induced in PSCs by IL1a via NFκB, and PSC-derived LIF promotes PDAC progression (10, 44). Together, these data indicate a role for hypoxia in PDAC progression via the induction of LIF in the tumor stroma, by promoting the inflammatory fibroblast state, as well as by acting non-cell autonomously on cancer cells.

Hypoxia also potentiates the ability of cytokines to promote acquisition of an iCAF phenotype in PSCs in a HIF1α-dependent fashion. Elevated HIF1α levels in hypoxic PSCs stimulated with cytokines results from increased Hif1α transcription as a consequence of cytokine induced NFκB signaling, consistent with prior reports (37, 39). Furthermore, cytokine signaling and HIF1α cooperate to activate HIF1α transcriptional activity by cobinding of STAT3 to promoter regions of HIF1α target genes (45), further supporting the idea that cytokine signaling can cooperate with hypoxic signaling to influence the cell state. In addition, hypoxia can promote inflammatory cytokine production in cancer cells (46), suggesting the possibility of a feed forward mechanism resulting in autocrine cytokine signaling that might influence CAFs. This is supported by observations that PDAC cells produce higher levels of the iCAF inducer IL1α in hypoxic culture conditions (40). While in this study we considered tumor cells as a major source of cytokines that synergize with hypoxia to alter the CAF state, it is possible that other stromal cell types in the TME are involved in this process. Hypoxia is known to induce secretion of IL1 and TNFα in macrophages (41). Interestingly, tumor-associated macrophages accumulate in hypoxic PDAC regions, resulting in polarization into distinct subtypes (35), similar to our observations in CAFs. Taken together, these findings argue that hypoxia can result in significant remodeling of the TME, altogether promoting a phenotypic change in CAFs toward a more inflammatory state via both cell autonomous and non-cell autonomous mechanisms.

We provide evidence that HIF1α stabilization in PSCs is sufficient to promote tumor growth in vivo in an allograft coinjection model. While Vhl-deleted PSCs secrete more IL6, blocking IL6 was insufficient to alleviate the tumor-promoting effect of these cells. IL6 is critical for PDAC progression (14); however, IL6 blockade or whole-body deletion of IL6 did not impact progression or overall survival (13, 47). Responsiveness to IL6 appears to be dependent on p53 status in the tumor compartment (48), and consistent with this notion, the PDAC cells used in this study were p53 mutant. Thus, in the model systems used here, IL6 acts primarily as a marker for iCAFs, rather than as the effector of PSC-induced tumor growth. Instead, we found VEGF as PSC-derived, HIF1α regulated molecule that is highly active in iCAFs, and implicate VEGF signaling as a mediator of the tumor promoting effects of PSC HIF1α. Our data support a role for CAF-derived VEGF in modulating endothelial cells and the angiogenic response in tumors, which is consistent with prior findings in breast cancer (20). Overall, these findings support the idea that HIF1α functions as tumor promoter in CAFs, but as tumor suppressor in cancer cells (49).

In this work, we identify a role for HIF1α in promoting an inflammatory state in CAFs and to support tumor growth. Interestingly, HIF2α but not HIF1α expression in αSMA+ myCAFs has been shown to accelerate PDAC progression by establishing an immunosuppressive TME (50). Consistently, we detected nuclear HIF1α only in αSMA CAFs in hypoxic PDAC regions, but not in αSMA+ CAFs outside hypoxic areas. Together, these data suggest that αSMA+ myCAFs rely on HIF2α, while αSMA/αSMALow iCAFs depend on HIF1α. To support this idea, future studies will be required that target HIF proteins in iCAFs in autochthonous tumor models, for example by using a dual recombinase approach including a Cre driver that is highly expressed in the iCAF population, such as Pdgfra or Fap (5, 47). Understanding the mechanism behind the differential dependence of CAF populations on HIF proteins will be an important area of investigation, and might involve selective modulation of cellular metabolism (51). Furthermore, the exclusion of αSMA+ CAFs from pimonidazole+ hypoxic PDAC regions reported in this study indicates that HIF2α might be activated in myCAFs via oxygen-independent mechanisms. These might involve reactive oxygen species (ROS), as myofibroblast induction by TGFβ has been shown to depend on ROS (52).

Collectively, these data argue that hypoxic signaling via HIF1α or HIF2α alters the CAF phenotype to promote PDAC tumor growth by remodeling other stromal cell types including endothelial cells and macrophages. Given the presence of hypoxia and CAF heterogeneity in most solid tumors (9), targeting hypoxic signaling in the tumor stroma might be a generalizable strategy to impair cancer progression. Small molecules that can selectively target HIF1α or HIF2α are in clinical development, but their application will need to be considered in light of the tumor suppressive role of HIF1α in the tumor epithelium (49). Selective targeting of HIF proteins in the tumor stroma could involve the use of chimeric antigen receptor T-cells (CAR-T), in which CAR expression is driven by a hypoxia response element (HRE) and targeted against a surface molecule highly expressed in CAFs, such as fibroblast activation protein (FAP). Hypoxia-sensing CAR-T cells and targeting FAP with CAR-T have proven safe in mouse models of cancer (53, 54).

S. Schwörer reports grants from NCI, Alan and Sandra Gerry Metastasis and Tumor Ecosystems Center, Hirshberg Foundation, AGA Research Foundation, and American Cancer Society during the conduct of the study. K.M. Tsanov reports other support from Jane Coffin Childs Memorial Fund for Medical Research and Shulamit Katzman Endowed Postdoctoral Research Fellowship, and grants from MSKCC David Rubenstein Center for Pancreatic Research Pilot Project during the conduct of the study. S.W. Lowe reports nothing directly related to this work; however, indirectly, S.W. Lowe is a consultant for and has equity in Oric Pharmaceuticals, Blueprint Medicines, Mirimus Inc., Senecea Therapeutics, Faeth Therapeutics, and PMV Pharmaceuticals. C.B. Thompson reports grants from NCI during the conduct of the study and personal fees from Agios, Charles River Laboratories, and Regeneron outside the submitted work. No disclosures were reported by the other authors.

S. Schwörer: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. F.V. Cimino: Data curation, formal analysis, investigation. M. Ros: Data curation, formal analysis, investigation, methodology, writing–review and editing. K.M. Tsanov: Data curation, investigation, methodology, writing–review and editing. C. Ng: Data curation, formal analysis. S.W. Lowe: Resources, supervision, funding acquisition, writing–review and editing. C. Carmona-Fontaine: Resources, formal analysis, supervision, funding acquisition, methodology, writing–review and editing. C.B. Thompson: Resources, supervision, funding acquisition, writing–original draft, writing–review and editing.

The authors thank the members of the Thompson laboratory for helpful discussions. The authors are thankful to Tullia Lindsten for help with planning of and protocol preparation for mouse experiments, and to Natalya N. Pavlova for help with GMAP. They also thank Elisa De Stanchina, Inna Kudos, and Janelle Simon for help with orthotopic organoid injections into the pancreas, and Wenfei Kang and Eric Rosiek of the MSKCC Molecular Cytology Core for help with IF staining, microscopy and image analysis. S. Schwörer received support from the NCI (5K99CA259224) and the Alan and Sandra Gerry Metastasis and Tumor Ecosystems Center at MSKCC. S. Schwörer is also supported by a Hirshberg Foundation Seed Grant, the AGA Research Foundation's Caroline Craig Augustyn & Damian Augustyn Award in Digestive Cancer, and an ACS-IRG Pilot Grant from the University of Chicago Comprehensive Cancer Center. K.M. Tsanov was supported by the Jane Coffin Childs Memorial Fund for Medical Research and a Shulamit Katzman Endowed Postdoctoral Research Fellowship. This work was supported by MSKCC's David Rubenstein Center for Pancreatic Research Pilot Project (to S.W. Lowe) and NIH grant P01CA013106 (to S.W. Lowe). S.W. Lowe is the Geoffrey Beene Chair for Cancer Biology at MSKCC. C. Carmona-Fontaine receives support from the NCI at the NIH (DP2 CA250005), the American Cancer Society (RSG-21-179-01-TBE), and the Pew Charitable Trust (00034121). C.B. Thompson was supported by the NCI (R01CA201318). This work used core facilities at MSKCC that were supported by the cancer center support grant (P30CA008748).

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

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