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IL-1β+ macrophages fuel pathogenic inflammation in pancreatic cancer

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with high resistance to therapies1. Inflammatory and immunomodulatory signals co-exist in the pancreatic tumour microenvironment, leading to dysregulated repair and cytotoxic responses. Tumour-associated macrophages (TAMs) have key roles in PDAC2, but their diversity has prevented therapeutic exploitation. Here we combined single-cell and spatial genomics with functional experiments to unravel macrophage functions in pancreatic cancer. We uncovered an inflammatory loop between tumour cells and interleukin-1β (IL-1β)-expressing TAMs, a subset of macrophages elicited by a local synergy between prostaglandin E2 (PGE2) and tumour necrosis factor (TNF). Physical proximity with IL-1β+ TAMs was associated with inflammatory reprogramming and acquisition of pathogenic properties by a subset of PDAC cells. This occurrence was an early event in pancreatic tumorigenesis and led to persistent transcriptional changes associated with disease progression and poor outcomes for patients. Blocking PGE2 or IL-1β activity elicited TAM reprogramming and antagonized tumour cell-intrinsic and -extrinsic inflammation, leading to PDAC control in vivo. Targeting the PGE2–IL-1β axis may enable preventive or therapeutic strategies for reprogramming of immune dynamics in pancreatic cancer.

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Fig. 1: IL1B+ TAMs correlate with poor prognosis in human PDAC and are conserved in mouse models.
Fig. 2: PGE2 and TNF cooperatively elicit the IL-1β+ TAM state.
Fig. 3: The PGE2–IL-1β axis elicits IL-1β+ TAMs and promotes PDAC growth.
Fig. 4: Inflammatory reprogramming occurs early during pancreatic tumorigenesis.
Fig. 5: IL-1β+ TAMs spatially colocalize with T1RS+ PDAC cells in patients with PDAC.

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Data availability

Single-cell, spatial transcriptomic and bulk RNA-seq data have been deposited at NCBI GEO data repository under accession number GSE217847. Data reanalysed for this study are available under the following accession codes: CRA001160 (scRNA-seq of human PDAC and NAT), GSE165045 (scRNA-seq of patients with pancreatitis), GSE207943 (scRNA-seq of mouse PDAC GEMM), GSE226829 (GeoMX data of human PDAC), GSE132326 and GSE154543 (RNA-seq of epithelial cells from mouse PDAC), GSE180211 (RNA-seq of pancreatic spheroids), and E-MTAB-11190 (RNA-seq of blood monocytes from patients with PDAC). Source data are provided with this paper.

Code availability

Codes used for the analyses is available at https://github.com/ostunilab/PDAC_Nature_2023.

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Acknowledgements

The authors thank M. A. Cappelluti and A. Lombardo for help with CRISPR–Cas9 gene targeting experiments; G. Bhat and D. Bonanomi for help with immunofluorescence analyses; C. Garlanda for providing Il1r1−/− mice; I. Zanoni, G. Natoli, B. Amati, A. Hidalgo, A. Ditadi and all members of the R.O. laboratory for discussions and/or critical reading of the manuscript. We thank the following Centers and facilities of Ospedale San Raffaele: Center for Omics Sciences (COSR), Proteomics and Metabolomics Facility (ProMeFa), Flow cytometry Resource, Advanced Cytometry Technical Applications Laboratory (FRACTAL), Advanced Light and Electron Microscopy BioImaging Center (ALEMBIC); Preclinical Imaging Facility, Centro Risorse Biologiche (CRB-OSR); Centro Universitario di Statistica per le Scienze Biomediche (CUSSB) at Vita-Salute San Raffaele University. Figures were created with Adobe Illustrator and BioRender.com. F.M.V., L.M. and V. Cuzzola conducted this study as partial fulfilment of a PhD in Molecular Medicine at Vita-Salute San Raffaele University. F.L.T. and C.L. conducted this study as partial fulfilment of a PhD in Complex Systems for Quantitative Biomedicine at University of Turin. N.C. and E.M. received support from fellowships from Fondazione Umberto Veronesi (FUV). P. Cappello and F.N. are supported by grants from the Italian Association for Cancer Research (AIRC) (IG 19931 and 26341) and Fondazione CRT (2019-1887 and 2020-0719). This study was supported by grants to R.O. from the European Research Council (ERC) (ERC Starting Grant 759532, X-TAM), AIRC (MFAG 20247, Bridge Grant 27844, and AIRC 5×1000 special program 22737), and the Italian Ministry of Health (GR-201602362156, GR-2021-12374094). Research in the R.O. laboratory is supported by grants from the Italian Telethon Foundation (SR-Tiget Grant Award F04).

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Authors and Affiliations

Authors

Contributions

N.C., F.L.T., F.M.V. and G.B. contributed to the design of the study, analysed data, prepared figures and edited the manuscript. N.C. and F.M.V. performed or contributed to all experiments, with help from L.M., S. Barresi, E.M., E.D., A.C., M.S.F.N., S. Brugiapaglia, A.S. and P. Cappello. F.L.T. and G.B. performed all computational analyses, with help from C.L. and E.L. V. Cuzzola and M.G. performed spatial gene expression experiments, with help from M.S.L. and C.D. M.P. and P. Canevazzi performed spheroid and organoid culture experiments. G.D. performed lineage tracing experiments. D.D. and A.A. performed mass spectrometry analyses. S.C. and M.F. selected and recruited study participants. A. Mortellaro, V. Corbo, Z.L. and A. Mondino provided resources. P.D., L.P., C.T., F.N., M.I., L.G.N., F.G., C.B. and L.N. provided key scientific inputs. R.O. conceptualized and coordinated the study, acquired funding, analysed the data and wrote the paper. All authors read and edited the manuscript.

Corresponding authors

Correspondence to Nicoletta Caronni or Renato Ostuni.

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Nature thanks Cecilia Garlanda, Elvira Mass and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer review reports are available.

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Extended data figures and tables

Extended Data Fig. 1 scRNA-seq analyses of PDAC patients.

a, UMAP of scRNA-Seq of all cells from PDAC patients. Colors and numbers indicate scRNA-Seq clusters (left) or cell type annotations (right). b, Heatmap of scaled expression of top 25 marker genes for each scRNA-Seq cluster. Selected transcripts are indicated. c, UMAP of scRNA-Seq of mononuclear phagocytes (MNPs) from PDAC patients. Colors and numbers indicate scRNA-Seq clusters (left) or cell type annotations (right). d, Dot plot of scaled expression of selected marker genes for each MNP cluster. e, Relative abundance (scRNA-Seq) of the indicated cell types for individual naïve or chemotherapy-treated PDAC patients. GEM+Nab-Pacl., gemcitabine+Nab-paclitaxel; FOLFIR., FOLFIRINOX; PAXG, cisplatin+Nab-paclitaxel, capecitabine, gemcitabine. f, Frequencies of diploid or aneuploid cells for each cluster, as predicted by copy number variation (CNV) analysis with CopyKAT. g, Frequencies of TAM subsets (scRNA-Seq) for individual naïve or chemotherapy-treated PDAC patients. GEM+Nab-Pacl., gemcitabine+Nab-paclitaxel; FOLFIR., FOLFIRINOX; PAXG, cisplatin+Nab-paclitaxel, capecitabine, gemcitabine. h, Number of differentially expressed genes (DEGs) in TAM subsets between chemotherapy-treated and naïve PDAC patients. i) GSEA (Gene Ontologies biological processes, GO BP) on genes ranked by log2FC between each TAM subset versus other TAMs. NES, Normalized Enrichment Score. j, Calculated frequencies of macrophages (CIBERSORTx deconvolution) in TCGA PDAC patients stratified according to expression levels of the IL1B+ TAM gene signature. Significance is computed by two-sided Mann-Whitney test. The box extends from the lower to upper quartile values of the data, with a line at the median. The whiskers extend from the box to show the range of the data no further than 1.5 * IQR (Inter-quartile range) from the hinges. k, Mean expression of the IL1B+ TAM gene signature in blood monocytes (bulk RNA-Seq) from healthy donors (Ctrl, n = 10) and PDAC patients (left, n = 11), and in blood or tumor monocytes or IL-1β+ TAMs from PDAC patients (right). Significance is computed by two-sided Mann-Whitney test. Sample size is indicated. The box extends from the lower to upper quartile values of the data, with a line at the median. The whiskers extend from the box to show the range of the data no further than 1.5 * IQR (Inter-quartile range) from the hinges.

Source Data

Extended Data Fig. 2 scRNA-seq analyses of mouse PDAC models.

a, UMAP of scRNA-Seq of all cells from mouse PDAC (orthotopic KPC). Colors and numbers indicate scRNA-Seq clusters (left) or cell type annotations (right). b, Heatmap of scaled expression of top 25 marker genes for each scRNA-Seq cluster. Selected transcripts are indicated. c, Frequencies (scRNA-Seq) of cells from the indicated experimental conditions and time points in each cluster. d, UMAP of scRNA-Seq of mononuclear phagocytes (MNPs) (left) or macrophages (right) from mouse PDAC (orthotopic KPC). e, Heatmap of scaled expression of top 25 marker genes for each mouse TAM subset. Selected transcripts are indicated. f, GSEA (marker genes of human TAM subsets) on genes ranked by log2FC between each mouse TAM subset versus other TAMs. NES, Normalized Enrichment Score. g, Heatmap of scaled gene expression of species-conserved marker genes in human or mouse TAM subsets (left), or in mouse TAM subsets from the indicated PDAC models (right). Only clusters of TAMs conserved between species are reported. h, Expression (flow cytometry) of the indicated markers (CD11b, Ly6C and F4/80, n = 8; CD80 and PD-L2, n = 27) by IL-1β+ TAMs (red) and IL-1β- TAMs (grey). Representative histograms and median fluorescence intensity (MFI) values are shown. Black lines represent fluorescence minus one control (FMO).

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Extended Data Fig. 3 Ontogeny of IL-1β+ TAMs.

a, Scaled mean fate probabilities (Optimal Transport Analysis, OTA) to acquire IL-1β+ TAM identity (at day 30) for the indicated cell populations in mouse PDAC (orthotopic KPC). b-j, Fate probabilities (OTA) to acquire the transcriptional programs of the indicated TAM subsets in mouse PDAC (orthotopic KPC) by blood monocytes (b), tissue monocytes (c), Folr2+ macrophages (d), Clps+ macrophages (e), Cxcl9+ macrophages (f), Marco+ macrophages (g), Mki67+ macrophages (h), Spp1+ TAMs (i) and Il1b+ TAMs (j). Probability values are shown for all time points. k, Cells identified as terminal states (CellRank) in tSNE embedding of mouse macrophages and monocytes from tissue and blood samples. i, Mean expression (scRNA-Seq) of Il1b in monocytes and IL-1β+ TAMs from control pancreas (Ctrl) and PDAC (orthotopic KPC) at the indicated time points (left), or in human monocytes and IL-1β+ TAMs from blood and tumor samples of PDAC patients (right).

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Extended Data Fig. 4 Elicitation of the IL-1β+ TAM state by PGE2 and TNF-α.

a, GSEA (GO BP) on genes ranked by correlation with absorption probability of the monocyte-to-Il1b+ TAM transition. Selected terms are shown. b, GSEA on genes ranked by log2FC between each mouse TAM subset versus other TAMs. Gene sets: IL-1β-induced or TNF-α-induced genes. NES, Normalized Enrichment Score. c, Concentration (mean ± SEM) of TNF-α (n = 18) and IL-1β (n = 17) in plasma and tumor of PDAC patients (n = 12). ***p < 0.001 ****p < 0.0001 (unpaired student’s two-tailed t test). d, Expression of IL-1β (intracellular staining) in mouse BMDMs treated for 6 h with IL-1β or TNF-α. e, Quantification of PGE2 in human PDAC samples and control (Ctrl) matched normal adjacent tissue (n = 7/group) by mass spectrometry (left), or in culture supernatants of KPC (n = 14), KC (n = 10) and PANC02 (n = 3) PDAC cells by ELISA (mean±SD, right). *p < 0.05 (paired student’s two-tailed t test). f, GSEA (PGE2-induced genes) on genes ranked by log2FC between each mouse TAM subset versus other TAMs (orthotopic KPC). NES, Normalized Enrichment Score. g, Transcript (mean ± SD, left) or protein (intracellular staining, right) expression of IL-1β in BMDMs stimulated as indicated (n = 2). h, Expression (intracellular staining) of IL-1β in BMDMs (n = 6, left) or BM monocytes (n = 3, right) stimulated as indicated. ****p < 0.0001 (one-way ANOVA).

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Extended Data Fig. 5 Spatial distribution of IL-1β+ TAMs.

a, Left panels. Selected regions of interest showing signal intensity (IF staining) of KRT19 (tumor cells), F4/80 (macrophages), PDGFR-α (fibroblasts) and IL-1β in mouse PDAC (orthotopic KPC, end-stage). Right panels. Quantification of macrophages (cells/mm2) in stromal or tumor areas (n = 2 mice, n = 4 sections/mouse, n = 10 ROI/area). ****p < 0.0001 (unpaired student’s two-tailed t test). b, Left panels. Selected regions of interest showing signal intensity (IF staining) of FOLR2, F4/80, IL-1β, and DAPI in control pancreas (day 0), mouse PDAC (orthotopic KPC), or normal adjacent tissue (NAT) at the indicated time points. Right panels. Quantification of IL-1β+ and FOLR2+ macrophages (cells/mm2) in stromal, tumor areas or NAT areas. Ctrl pancreas, n = 2 mice, n = 2 sections/mouse, n = 10 ROI/section; Day 15 PDAC, n = 4 mice, n = 2 sections/mouse, n = 5 ROI/areas; Day 30 PDAC, n = 5 mice, n = 2 sections/mouse, n = 10 ROI/areas. c, Selected regions of interest with inset magnifications showing signal intensity (IF staining) of KRT8-18, CD163, NLRP3, and DAPI (middle), or CD163, FOLR2 and DAPI (right) on consecutive sections of human PDAC samples. d, Annotation (see Methods) of tumor or stromal areas in spatial transcriptomics data (Visium) for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). e, Signal intensity (IF staining) of KRT19, F4/80, PDGFR-α and DAPI for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). f, Percentages (DestVI deconvolution) of tumor cells (left), macrophages (middle) and fibroblasts (right) in spatial transcriptomics data (Visium) for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). g, Percentage of spots with concordant annotation as stroma or tumor by spatial transcriptomics (Visium) and IF staining for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). h, Correlation values (red, positive; blue, negative; white, non-significant) between mean gene expression (Visium) of marker genes of the indicated TAM subsets (DestVI generative model, see Methods) and spatial principal components (sPC) coordinates for spots of a selected tissue section (A1) of mouse PDAC (orthotopic KPC, end-stage). i, Coordinates of spatial Principal Component 1 (sPC1) of macrophage-enriched spots (DestVI deconvolution) in spatial transcriptomics data (Visium) for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). j, Scaled mean expression of marker genes of IL-1β+ TAMs (DestVI generative model) in macrophage-enriched spots (DestVI deconvolution) in spatial transcriptomics data (Visium) for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). k, Enrichment (PAGE) of expression of marker genes of IL-1β+ TAMs (left) or FOLR2+ TAMs (right) in macrophage-enriched spots (DestVI deconvolution) in spatial transcriptomics data (Visium) for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). Colors indicate macrophage-enriched ST spots with significance (estimated on all spots) of p < 0.001. l, Enrichment (PAGE) of expression of PGE2 + TNF-α synergized genes in macrophage-enriched spots (DestVI deconvolution) in spatial transcriptomics data (Visium) for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). Colors indicate macrophage-enriched ST spots with significance (estimated on all spots) of p < 0.001. m, Louvain clustering of spots in spatial transcriptomics data (Visium) for a selected tissue section (A1) of mouse PDAC (orthotopic KPC, end-stage). n, Enrichment (PAGE) of expression of genes belonging to the indicated GO BPs in spatial transcriptomics data (Visium) for the indicated tissue sections of mouse PDAC (orthotopic KPC, end-stage). GSEA was performed on genes ranked by log2FC between cluster 4 versus other spots. Colors indicate spots with significance (estimated on all spots) of p < 0.001. o, Signal intensity (IF staining) of F4/80, IL-1β, and DAPI (left), or of CD31, VEGFR2 and KRT19 (middle) in consecutive sections of mouse PDAC (orthotopic KPC, end-stage). Arrows indicate IL-1β+ F4/80+ cells (left) and CD31+ VEGFR2+ cells (middle). Quantification of IL-1β+ F4/80+ cells in areas with high and low density of CD31+ VEGFR2+ cells (right, n = 5 mice, n = 2 sections/mouse). ***p < 0.001 (unpaired student’s two tailed t test). p, Signal intensity (IF staining) of F4/80, IL-1β and KRT19 (left), or of anti-Hypoxyprobe (middle) in consecutive sections of mouse PDAC (orthotopic KPC, end-stage). Quantification of IL-1β+ F4/80+ cells in hypoxic and non-hypoxic areas (right, n = 3 mice, n = 2 sections/mouse). *p < 0.05 (unpaired student’s two tailed t test).

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Extended Data Fig. 6 Targeting PGE2 reprograms the pancreatic TME.

a, Quantification of PGE2 (mass spectrometry) in lysates of mouse PDAC (subcutaneous KPC, end-stage) from mice treated with celecoxib (CXB, n = 3) or vehicle (n = 4). ***p < 0.001 (unpaired student’s two tailed t test). b, Expression of IL-1β (intracellular staining) in macrophages and monocytes in mouse PDAC (subcutaneous KPC, end-stage) from mice treated with celecoxib (CXB, n = 8) or vehicle (n = 10). **p < 0.01 (unpaired t test). c, Contour plots (left) and frequency (right) of GZMB+ CD8+ T cells in mouse PDAC (subcutaneous KPC, end-stage) from mice treated with celecoxib (CXB, n = 8) or vehicle (n = 10). *p < 0.05 (unpaired student’s two tailed t test). d, Growth curves (mean±SEM) of mouse PDAC (subcutaneous KPC) in mice treated with celecoxib (CXB, n = 10) or vehicle (n = 10). ***p < 0.001 (two-way ANOVA). e, Expression (western blot) of COX-2 and β-Actin in the indicated control and COX-2 ko mouse PDAC cell lines. f, Quantification of PGE2 (ELISA, mean±SD) in the culture supernatant of the indicated control (KC, n = 6; KPC, n = 6; PANC02, n = 2) and COX-2 KO (KC, n = 5; KPC, n = 5; PANC02, n = 2) mouse PDAC cell lines. ****p < 0.0001 (2-way ANOVA). g, Expression (mean±SD) of Annexin V and/or 7AAD cells by the indicated control (n = 2) and COX-2 ko (n = 2) mouse PDAC cells. h, Proliferation in vitro (WST-1 assay, mean±SEM) of the indicated control (n = 2) and COX-2 ko (n = 2) mouse PDAC cells. i, Growth curves (mean±SD) of control (subcutaneous KC, n = 8; subcutaneous PANC02, n = 10) and COX-2 ko PDAC cells (subcutaneous KC, n = 10; subcutaneous PANC02, n = 7) in wild-type mice. ****p < 0.0001 (two-way ANOVA). j, Growth curves (mean ± SEM) of control (Ctrl) and COX-2 ko PDAC cells (orthotopic KPC, n = 5/group, left; orthotopic KC, n = 4/group, middle) or spheroids (3D, orthotopic KPC, n = 9/group, right) in wild-type mice. **p < 0.01, ***p < 0.001 (two-way ANOVA). k, Frequencies (flow cytometry) of the indicated cell types in control or COX-2 ko PDAC (subcutaneous KPC, day 6, n = 5/group). *p < 0.05, ****p < 0.0001 (two-way ANOVA). l, UMAP showing clustering (left) and bar plots showing frequencies (right, scRNA-Seq) of the indicated cell types in control or COX-2 ko PDAC (subcutaneous KPC, day 7). m, Number of differentially expressed genes (DEG, scRNA-Seq) for the indicated cell types between control and COX-2 ko PDAC (subcutaneous KPC, day 7). n, Volcano plots of differentially expressed genes for macrophages (left), fibroblasts (middle) and activated T cells (right) between control (Ctrl) and COX-2 ko PDAC (subcutaneous KPC, day 7). Selected genes for each population are highlighted. FC, fold change. FDR, false discovery rate. o, GSEA (IFN-γ response genes,) on genes ranked by log2FC between IL-1β+ TAMs from control (Ctrl) versus COX-2 ko PDAC (subcutaneous KPC, day 7). NES, Normalized Enrichment Score. p, Growth curves (mean ± SD) of control (Ctrl) and COX-2 ko PDAC cells (subcutaneous KPC) in wild-type mice (n = 4 Ctrl, n = 5 COX-2 ko, left) or Ifnar1−/− (n = 5 Ctrl, n = 5 COX-2 ko, right) mice. ****p < 0.0001 (two-way ANOVA).

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Extended Data Fig. 7 Tumor cell-intrinsic IL-1β signaling promotes PDAC growth.

a, Growth curves (mean±SEM) of PDAC cells (subcutaneous KC) in mice treated with anti-IL-1β (n = 8) or isotype control (IgG, n = 10). ***p < 0.001 (two-way ANOVA). b, Frequencies (flow cytometry, mean±SD) of the indicated cell types in PDAC (subcutaneous KPC, end-stage) of mice treated with anti-IL-1β (n = 7) or isotype control (IgG, n = 10). **p < 0.01 (two-way ANOVA). c, Expression of IL-1β (intracellular staining) in monocytes (left) or macrophages (right) in PDAC (subcutaneous KPC, end-stage) of mice treated with anti-IL-1β or isotype control (IgG). d, Dot plots of scaled IL1B expression (scRNA-Seq) in the indicated cell populations (top) or myeloid cell subsets (bottom) in human PDAC samples. e, Schematic representation (left) and growth curves (mean ± SEM) of PDAC (subcutaneous KPC) in the indicated bone marrow (BM) chimeric mice (n = 10 WT > WT, Il1r1−/−>WT; n = 11 WT> Il1r1−/) (two-way ANOVA). f, Expression of IL-1R1 and β-actin (western blot) in whole cell lysates of the indicated parental, control (Ctrl) or IL-1R1 ko PDAC cells. g, Expression of IκBα (western blot) in whole cell lysates of control or IL-1R1 ko PDAC cells (KPC) upon stimulation with IL-1β for the indicated time points. h, Growth curves of tumors (mean ± SEM, right) and expression of IL-1β in tumor-infiltrating monocytes (intracellular staining, right) from control (Ctrl) or IL1-R1 ko PDAC (subcutaneous KPC, n = 8/group). ****p < 0.0001 (two-way ANOVA). i, Contour plots (left) and frequencies (right) of activated CD8+ T cells in tumors (subcutaneous KPC, n = 18 Ctrl, n = 11 IL-1R1 ko, left) or tumor-draining lymph nodes (subcutaneous KPC, n = 18 Ctrl, n = 18 IL-1R1 ko, right) from control (Ctrl) or IL1-R1 ko PDAC. ***p < 0.001, * p < 0.05 (unpaired student’s two-tailed t test). j, Expression of IL-1R1 and β-actin (western blot) in whole cell lysates of IL-1R1 ko or IL-1R1-reconstituted IL-1R1 ko (IL1R1 Rest) PDAC (KPC) cells. Numbers denote clone ID. k, Representative images (left) and quantification (mean ± SD, middle) of organoids generated from control (Ctrl) and IL-1R1 ko PDAC cells (KPC) treated with vehicle or with IL-1β for 5 days (n = 8 wells/condition; the entire Matrigel area was collected for each well). **p < 0.01 (2-way ANOVA). Representative images (right) of organoids generated from explanted control (Ctrl) and IL-1R1 ko PDAC (subcutaneous KPC, day 11).

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Extended Data Fig. 8 Consequences of IL-1β signaling in tumor cells.

a, Volcano plot (left) of genes up-regulated (red) or down-regulated (blue) in PDAC (KPC) cells treated with IL-1β for 24 h (UT n = 3, IL-1β n = 2). Selected genes are highlighted. Quantification (ELISA) of the indicated cytokines (mean ± SD, n = 3, unpaired two-tailed student’s t test, middle) or PGE2 (n = 7, paired two-tailed student’s t test, right) in the supernatant of PDAC cells (KPC) cells treated with IL-1β 24 h. *p < 0.5, **p < 0.01, ****p < 0.0001. b, Growth curves (mean±SEM) of PDAC cells (subcutaneous KPC) in wild-type and Ccr2−/− mice (left, n = 5/group) or in wild-type mice treated with an anti-CSF-1 antibody (αCSF-1, n = 8) or isotype control (IgG, n = 10). ****p < 0.0001 (two-way ANOVA). c, GSEA (GO BP) on genes ranked by log2FC between PDAC cells (KPC) treated with IL-1β versus untreated controls. NES, Normalized Enrichment Score. d, Scheme of the experiment (left) and expression of Il1b (RT-qPCR, mean±SD) in BMDMs treated for 2 h with tumor-conditioned media (TCM) of mouse PDAC cells (KPC) from the following conditions: untreated (KPCUT) or treated for 24 h with a COX-2 inhibitor (KPCCOX2i), IL-1β (KPCIL-1β), IL-1β + COX-2 inhibitor (KPCIL-1β+COX2i). A control condition of BMDMs stimulated with vehicle or COX-2 inhibitor (COX2i) is shown. Isotype control or an anti-TNF-α antibody (αTNF-α) groups were included for each condition (n = 3). *p < 0.05 **p < 0.01 ***p < 0.001 (two-way ANOVA).

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Extended Data Fig. 9 Inflammatory reprogramming of PDAC cells.

a, Venn diagram of genes up-regulated (bulk RNA-Seq or scRNA-Seq) upon treatment with IL-1β in the indicated mouse PDAC models. The tumor-intrinsic IL-1β response signature (T1RS) is composed by the 57 genes commonly up-regulated by IL-1β in all conditions. b, Heatmap of scaled expression (bulk RNA-Seq or scRNA-Seq) of T1RS genes in the indicated mouse PDAC models, left untreated or stimulated with IL-1β for the indicated time points. c, Mean expression of human orthologs of T1RS genes (TCGA) in PDAC patients stratified for the levels of expression of the IL1B+ TAM signature (left). The box extends from the lower to upper quartile values of the data, with a line at the median. The whiskers extend from the box to show the range of the data no further than 1.5 * IQR (Inter-quartile range) from the hinges. Hazard ratios (right) obtained by fitting univariate Cox model on gene expression of T1RS genes in TCGA PDAC cohort. Only genes with significant adjusted p-values are reported. d, Mean expression (scRNA-Seq) of T1RS genes in pancreatic epithelial cells and tumor cells from control pancreas or mouse PDAC (orthotopic KPC) in the indicated time points. e, GSEA (MSigDB hallmark genes) on genes ranked by log2FC between tumor versus healthy pancreas cells at the indicated time points (orthotopic KPC). NES, Normalized Enrichment Score. FDR, False Discovery Rate. f, Heatmap of scaled mean expression (GeoMx) of human orthologs of T1RS genes in the indicated regions of interest (ROIs) of healthy donors and PDAC patients. PanIN, pancreatic intraepithelial neoplasia. g, UMAP (left) and frequencies (scRNA-Seq, right) of the indicated macrophage subsets in the pancreas of healthy controls or patient with hereditary or idiopathic pancreatitis). Cells corresponding to IL-1β+ TAMs are annotated in red. h, Mean expression (scRNA-Seq) of IL-1β+ TAM marker genes in IL-1β+ TAMs (or other TAMs) from PDAC patients and in macrophages corresponding to IL-1β+ TAMs (or other macrophages) in pancreatitis patients. Significance is computed by two-sided Mann-Whitney test. i, Left, mean expression of T1RS genes in pancreatic epithelial cells from mice control or mutated Kras and treated with vehicle or IL-33. Significance (two-sided Mann-Whitney test) is shown. Sample size is indicated. The box extends from the lower to upper quartile values of the data, with a line at the median. The whiskers extend from the box to show the range of the data no further than 1.5 * IQR (Inter-quartile range) from the hinges. Right, GSEA (T1RS genes) on genes ranked by log2FC between spheroids generated from injured or control pancreas. NES, Normalized Enrichment Score.

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Extended Data Fig. 10 Spatial analyses of IL-1β+ TAMs and T1RS+ PDAC cells.

a, UMAP plot of scRNA-Seq data of PDAC cells from chemotherapy-naïve patients. Colors and numbers indicate cluster identity. b, Left panels. Selected region of interest (LPDAC30 B2_1) showing expression (Molecular Cartography) of all (563,761) detected transcripts or KRT19, as well as signal intensity (IF staining) of KRT19. Right panels. UMAP of spatial gene expression data (Molecular Cartography) of cells from all sections collected from patient LPDAC30. Colors and numbers indicate cluster identity and corresponding annotations. c, Heatmaps of spatial correlation of gene expression (see Methods) with CXCL1 of genes of the spatial transcriptome panel (left) or of marker genes of TAM subsets (right). d, Heatmap of spatial neighborhood significance between the indicated clusters (see Methods). e, Selected regions of interest (LPDAC30 C2_1, left. LPDAC30 D2_1, right) showing co-localization of IL-1β+ TAMs (red) and T1RS+ PDAC cells (light blue) in spatial gene expression analyses. Numbers indicate insets and their magnifications. f, UMAP showing expression (scRNA-Seq) of IL1R1 in PDAC cells from chemotherapy-naïve patients. g, UMAP of scRNA-Seq data (left) and violin plot showing mean expression of T1RS genes (right) of PDAC cells selected for pseudotime analysis. Colors and numbers indicate cluster identity. Significance is computed by two-sided Mann-Whitney test. h, Heatmaps (NicheNet) of ligand activity (Pearson correlation coefficient) of top-ranking ligands expressed by IL-1β+ TAMs (left) and their regulatory potential on predicted target genes expressed by T1RS+ PDAC cells (right).

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Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 (uncropped blots and gating strategies for flow cytometry analysis), and full descriptions for Supplementary Tables 1–10.

Reporting Summary

Supplementary Table 1

Single-cell and bulk RNA-seq analysis of human PDAC samples.

Supplementary Table 2

scRNA-seq data analysis of mouse PDAC.

Supplementary Table 3

CellRank analysis on scRNA-seq data of mouse PDAC.

Supplementary Table 4

RNA-seq data analysis of mouse BMDMs.

Supplementary Table 5

Spatial transcriptomics data analysis of mouse PDAC.

Supplementary Table 6

scRNA-seq data analysis of mouse wild-type or COX2-KO PDAC.

Supplementary Table 7

IL1R1-KO PDAC clones.

Supplementary Table 8

RNA-seq data analysis of mouse KPC cells.

Supplementary Table 9

RNA-seq data analysis of mouse tumour cells stimulated with IL-1B.

Supplementary Table 10

scRNA-seq of human PDAC tumour cells and spatial gene expression analysis.

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Caronni, N., La Terza, F., Vittoria, F.M. et al. IL-1β+ macrophages fuel pathogenic inflammation in pancreatic cancer. Nature 623, 415–422 (2023). https://doi.org/10.1038/s41586-023-06685-2

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