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Original Research| Volume 11, ISSUE 5, P1405-1436, 2021

Pharmacologic Normalization of Pancreatic Cancer-Associated Fibroblast Secretome Impairs Prometastatic Cross-Talk With Macrophages

  • Rémi Samain
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Alexia Brunel
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Thibault Douché
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Marjorie Fanjul
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Stéphanie Cassant-Sourdy
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Julia Rochotte
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Jérôme Cros
    Affiliations
    Department of Pathology, Beaujon-Bichat University Hospital–Paris Diderot University, Clichy, France
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  • Cindy Neuzillet
    Affiliations
    Medical Oncology Department, Curie Institute, Versailles Saint-Quentin University, Saint Cloud, France
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  • Jérôme Raffenne
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Camille Duluc
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Aurélie Perraud
    Affiliations
    Equipe d'Accueil EA 3842 Laboratory, Medicine and Pharmacy Faculties, University of Limoges, Limoges, France
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  • Jérémy Nigri
    Affiliations
    INSERM U1068/UMR 7258 CNRS, Cancer Research Center of Marseille, Marseille, France
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  • Véronique Gigoux
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Ivan Bieche
    Affiliations
    Department of Genetics, Institut Curie, Paris Descartes University, Paris, France
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  • Matteo Ponzo
    Affiliations
    Growth, Reparation and Tissue Regeneration Laboratory, Equipe de Recherche Labellisée ERL-CNRS 9215, University of Paris-Est, Créteil, France
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  • Gilles Carpentier
    Affiliations
    Growth, Reparation and Tissue Regeneration Laboratory, Equipe de Recherche Labellisée ERL-CNRS 9215, University of Paris-Est, Créteil, France
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  • Ilaria Cascone
    Affiliations
    Growth, Reparation and Tissue Regeneration Laboratory, Equipe de Recherche Labellisée ERL-CNRS 9215, University of Paris-Est, Créteil, France
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  • Richard Tomasini
    Affiliations
    INSERM U1068/UMR 7258 CNRS, Cancer Research Center of Marseille, Marseille, France
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  • Herbert A. Schmid
    Affiliations
    Novartis Pharmaceuticals, Basel, Switzerland
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  • Muriel Mathonnet
    Affiliations
    Equipe d'Accueil EA 3842 Laboratory, Medicine and Pharmacy Faculties, University of Limoges, Limoges, France
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  • Rémy Nicolle
    Affiliations
    Programme Cartes d’Identité des Tumeurs, Ligue Nationale Contre Le Cancer, Paris, France
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  • Marie-Pierre Bousquet
    Affiliations
    Institute for Pharmacology and Structural Biology, University of Toulouse, Toulouse, France
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  • Yvan Martineau
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Stéphane Pyronnet
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Christine Jean
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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  • Corinne Bousquet
    Correspondence
    Correspondence Address correspondence to: Corinne Bousquet, VMD, PhD, INSERM U1037, Cancer Research Center of Toulouse, 2 Avenue Hubert Curien, CS53717, 31037 Toulouse Cedex 1, France. fax: (33) (0) 56131-9752.
    Affiliations
    Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM Unité Mixte de Recherche UMR-1037, CNRS Equipe de Recherche Labellisée ERL5294, Equipe de Recherche Labellisée "Ligue Contre le Cancer" & "LabEx Toucan", Toulouse, France
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Open AccessPublished:January 19, 2021DOI:https://doi.org/10.1016/j.jcmgh.2021.01.008

      Background & Aims

      Cancer-associated fibroblasts (CAFs) from pancreatic adenocarcinoma (PDA) present high protein synthesis rates. CAFs express the G-protein–coupled somatostatin receptor sst1. The sst1 agonist SOM230 blocks CAF protumoral features in vitro and in immunocompromised mice. We have explored here the therapeutic potential of SOM230, and underlying mechanisms, in immunocompetent models of murine PDA mimicking the heavy fibrotic and immunosuppressive stroma observed in patient tumors.

      Methods

      Large-scale mass spectrometry analyses were performed on media conditioned from 9 patient PDA-derived CAF primary cultures. Spontaneous transgenic and experimental (orthotopic co-graft of tumor cells plus CAFs) PDA-bearing mice were longitudinally ultrasound-monitored for tumor and metastatic progression. Histopathology and flow cytometry analyses were performed on primary tumors and metastases. Stromal signatures were functionally validated through bioinformatics using several published, and 1 original, PDA database.

      Results

      Proteomics on the CAF secretome showed that SOM230 controls stromal activities including inflammatory responses. Among the identified secreted proteins, we validated that colony-stimulating factor 1 (CSF-1) (a macrophage growth factor) was reduced by SOM230 in the tumor and plasma of PDA-harboring mice, alongside intratumor stromal normalization (reduced CAF and macrophage activities), and dramatic metastasis reduction. In transgenic mice, these SOM230 benefits alleviate the chemotherapy-induced (gemcitabine) immunosuppressive stroma reshaping. Mechanistically, SOM230 acts in vivo on CAFs through sst1 to disrupt prometastatic CAF production of CSF-1 and cross-talk with macrophages. We found that in patients, stromal CSF-1 was associated with aggressive PDA forms.

      Conclusions

      We propose SOM230 as an antimetastatic therapy in PDA for its capacity to remodel the fibrotic and immunosuppressive myeloid stroma. This pharmacotherapy should benefit PDA patients treated with chemotherapies.

      Graphical abstract

      Keywords

      Abbreviations used in this paper:

      αSMA (α smooth muscle actin), BSA (bovine serum albumin), CAF (cancer-associated fibroblast), CAFhTERT (human Telomerase reverse transcriptase), CSF-1 (colony stimulating factor 1), CSF-1-R (colony stimulating factor 1 receptor), ECM (extracellular matrix), ELISA (enzyme-linked immunosorbent assay), FFPE (formalin-fixed paraffin-embedded), GBSS (Grey’s balanced salt solution), GPCR (G-protein–coupled receptor subtype), GSEA (gene set enrichment analysis), KOsst1 (Knock-out), KPC (Pdx-1-Cre), LSL-KrasG12D/+ (LSL-Trp53R172H/+), LAR (long-acting release), LNR (lymph node ratio), mRNA (messenger RNA), MS (mass-spectrometry), mTOR (mechanistic target of rapamycin), PBS (phosphate-buffered saline), PCR (polymerase chain reaction), PDA (pancreatic ductal adenocarcinoma), PSC (pancreatic stellate cell), PDX (patient-derived xenograft), RNAseq (RNA sequencing), sst1 (somatostatin receptor subtype 1), TAM (tumor-associated macrophage), WT (wild type)
      Cancer-associated fibroblasts orchestrate pancreatic adenocarcinoma (PDA) aggressiveness. We show that the Food and Drug Administration–approved somatostatin analog SOM230 inhibits metastasis in murine PDA models by acting through its receptor sst1 to disrupt the cancer-associated fibroblast production of colony stimulating factor 1, a prometastatic and macrophage-attracting chemokine whose stromal expression is associated with PDA aggressiveness.
      Pancreatic ductal adenocarcinoma (PDA) remains one of the deadliest neoplasms. Most patients die from metastatic disease within the first year after diagnosis.
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      Anti-metastatic potential of somatostatin analog SOM230: indirect pharmacological targeting of pancreatic cancer-associated fibroblasts.
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      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      ,
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      and involved in inflammatory responses. Accordingly, SOM230 showed antimetastatic activity in relevant PDA-harboring mice, normalizing the fibrotic and immunosuppressive myeloid stroma, including the cytokinic storm reaction induced by chemotherapy (gemcitabine).
      • Principe D.R.
      • Narbutis M.
      • Kumar S.
      • Park A.
      • Viswakarma N.
      • Dorman M.J.
      • Kamath S.D.
      • Grippo P.J.
      • Fishel M.L.
      • Hwang R.F.
      • Thummuri D.
      • Underwood P.W.
      • Munshi H.G.
      • Trevino J.G.
      • Rana A.
      Long-term gemcitabine treatment reshapes the pancreatic tumor microenvironment and sensitizes murine carcinoma to combination immunotherapy.
      Mechanistically, SOM230 acts through the CAF-expressed sst1 receptor to disrupt a prometastatic cross-talk between CAFs and immunosuppressive TAMs involving the chemokine colony-stimulating factor (CSF-1), whose specific expression in the stroma of patient tumors was found to be associated with aggressive and metastatic forms of PDA.

      Results

      SOM230 Decreases CAF Production of Secreted Proteins Enriched in PDA Stroma-Activated Signatures

      To exhaustively identify CAF-secreted proteins, we performed MS analyses on media conditioned by 9 CAF explants, treated or not with SOM230 for 48 hours (Figure 1A). A total of 272 proteins were identified as being significantly (P < .05) down-regulated (threshold of 2-fold) by SOM230, but none were up-regulated (Figure 1B, Table 1). These proteins are graphically represented for each CAF in heatmaps with box plots for global levels (Figure 1C), and averaged in the secretomes of the 9 CAF cultures (Figure 1D) where pairs between SOM230-treated and control untreated conditions are indicated. Gene set enrichment analysis (GSEA) for this SOM230-regulated secretomic signature identified pathways including Phosphoinositide 3-kinase (PI3K–AKT) and mTOR signalings and the inflammatory response pathway (Figure 1E). Among the 272 identified proteins, 75 and 54 were common to the “stroma-activated” signature from Moffitt et al,
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      or from Puleo et al,
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      respectively (Figure 1F), with a significant normalized enrichment score (Figure 1G), and 47 proteins were common to both signatures (listed in Figure 1F). Dependency on sst1 expression of several of the identified SOM230-regulated secretomic signatures (biglycan, connective tissue growth factor, and thrombospondin 2 in Table 1) was confirmed in human CAFs knocked-down for sst1 (Figure 1H). These results suggest that SOM230 normalizes numerous cross-talks originating from sst1-expressing CAFs, putatively regulating both tumor cells and stromal biology.
      Figure thumbnail gr1
      Figure 1SOM230 decreases CAF production of secreted proteins enriched in PDA activated stroma signatures. (A) Experimental design of CAF secretome analysis. (B) Graphic representation of quantitative proteomics data. Proteins are ranked in a volcano plot according to their statistical P value (y-axis) and their relative abundance ratio (log fold change) between untreated (NT) and SOM230-treated CAFs (x-axis). (C) SOM230-modulated protein secretion. Heatmap showing the differentially secreted proteins in 9 CAF cultures treated (SOM) or not (NT) with SOM230. Proteins are ordered by the level of significance of the differential test. The first 2 columns indicate if each protein was associated previously with an activated form of stroma in human primary tumors (Moffit et al
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      or Puleo et al
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      databases). The 2 main heatmaps show the level of quantification, normalized by pairs of treated/untreated CAFs as log
      • Collisson E.A.
      • Sadanandam A.
      • Olson P.
      • Gibb W.J.
      • Truitt M.
      • Gu S.
      • Cooc J.
      • Weinkle J.
      • Kim G.E.
      • Jakkula L.
      • Feiler H.S.
      • Ko A.H.
      • Olshen A.B.
      • Danenberg K.L.
      • Tempero M.A.
      • Spellman P.T.
      • Hanahan D.
      • Gray J.W.
      Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy.
      ratios, in each experiment. Upper box plots show the global levels of these differentially secreted proteins. The 2 right panels illustrate the P value of the differential analysis and the log fold change (FC). (D) Box plot of the average of all secreted protein quantification measured in each sample. Pairs between SOM230-treated and untreated conditions are indicated by a gray segment. The Wilcoxon matched-pairs signed rank test was used to generate P values. ∗∗P < .01. (E) Gene set enrichment analysis for down-regulated pathways in SOM230-treated CAF secretomes, as compared with untreated CAFs. (F) Venn diagram of the overlap of down-regulated proteins in secretome analysis and activated stroma signatures from the Moffitt et al
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      or Puleo et al
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      databases. Common proteins are listed in the right panel. (G) Gene set enrichment analysis comparing secretome genes and activated stroma signatures from Moffitt et al
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      and Puleo et al.
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      (H) CAF primary cultures (n = 5) were transfected with a small interfering RNA targeting sst1 (siSst1) or a control nontargeting siRNA (siCTR), and treated or not (NT) with SOM230. Biglycan, connective tissue growth factor (CTGF), and thrombospondin (THBS 2) were quantified in the CAF conditioned media by ELISA (n = 5, Kruskal–Wallis test followed with the Dunn multiple comparison post-test was used to generate P values, ∗∗∗P < .001). Representative Western blot showing expression of sst1 and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (internal loading control for protein expression in each condition) in CAFs. LC, liquid chromatography; NES, normalized enriched score; SDS-PAGE, sodium dodecyl sulfate–polyacrylamide gel electrophoresis.
      Table 1Listing of Significantly Down-Regulated Proteins in CAF’s Secretome: Untreated Vs SOM230
      Protein namesGene namesMoy ratio NT/SOM230P value
      DecorinDCN3565.20.0037699
      BiglycanBGN2416.98.0105944
      Thrombospondin-2THBS2993.52.0002836
      Glia-derived nexinSERPINE2944.33.0002733
      Adipocyte enhancer-binding protein 1AEBP1629.64.0053412
      AgrinAGRN618.31.0478032
      Fibulin-1FBLN1572.34.0065804
      Peroxidasin homologPXDN468.76.0481937
      Carboxypeptidase ECPE448.97.0017332
      HLA class I histocompatibility antigenHLA-A412.95.0003536
      Protein-lysine 6-oxidaseLOX405.09.0007965
      Elongation factor 1-δEEF1D401.99.0015514
      Stromelysin-1MMP3369.77.0387783
      SPARCSPARC334.84.0028440
      Glyceraldehyde-3-phosphate dehydrogenase, testis-specificGAPDHS302.95.0125467
      Coiled-coil domain-containing protein 80CCDC80269.82.0124452
      CalumeninCALU244.86.0154646
      Out at first protein homologOAF232.27.0072591
      Fibrillin-1FBN1223.43.0085725
      Testican-1SPOCK1202.29.0041202
      Connective tissue growth factorCTGF189.63.0180345
      Fibulin-2FBLN2160.13.0030805
      Collagen α-1(V) chainCOL5A1153.20.0376581
      Syndecan-4SDC4142.77.0181431
      Phospholipid transfer proteinPLTP140.32.0027074
      A disintegrin and metalloproteinase with thrombospondin motifs 1ADAMTS1139.38.0020889
      Sushi repeat-containing protein SRPX2SRPX2131.96.0014868
      Complement C1r subcomponentC1R129.50.0073546
      Sushi repeat-containing protein SRPXSRPX116.75.0239367
      Vitamin K–dependent protein SPROS1115.14.0483223
      Actin, cytoplasmic 1; actin, cytoplasmic 1, N-terminally processedACTB112.36.0005106
      Plasma α-L-fucosidaseFUCA2108.05.0004376
      Laminin subunit γ-1LAMC197.78.0000042
      Inhibin β A chainINHBA93.39.0471213
      Proliferating cell nuclear antigenPCNA89.42.0306750
      Stanniocalcin-2STC284.81.0108231
      Tumor necrosis factor–receptor superfamily member 11BTNFRSF11B82.61.0418658
      Tryptophan–transfer RNA ligaseWARS79.58.0028410
      Latent-transforming growth factor β-binding protein 1LTBP178.27.0084952
      Myosin-14MYH1476.43.0017097
      GelsolinGSN76.16.0128688
      Latent-transforming growth factor β-binding protein 2LTBP274.59.0008218
      Netrin-4NTN467.79.0026525
      Protein transport protein Sec23ASEC23A65.55.0023638
      Coagulation factor IXF964.96.0289241
      Septin-7SEPT-764.92.0419335
      Microfibrillar-associated protein 2MFAP264.75.0011975
      Collagen α-2(I) chainCOL1A264.69.0013190
      Serine protease HTRA1HTRA162.57.0039875
      Collagen α-1(III) chainCOL3A157.28.0010022
      γ-enolaseENO256.15.0059011
      Tripeptidyl-peptidase 1TPP153.61.0135799
      β-hexosaminidase subunit βHEXB51.51.0000029
      T-complex protein 1 subunit γCCT351.00.0011871
      Amyloid-like protein 2APLP248.18.0001436
      Urotensin-2UTS247.26.0307781
      60S acidic ribosomal protein P1RPLP145.66.0020590
      Angiopoietin-related protein 2ANGPTL243.54.0396281
      Nascent polypeptide-associated complex subunit αNACA43.35.0397871
      Complement C1s subcomponentC1S43.01.0212752
      Glutathione S-transferase PGSTP142.75.0005148
      Calsyntenin-1; soluble Alc-α; CTF1-αCLSTN141.57.0000025
      Ras-related protein Rab-6ARAB6A38.84.0354047
      Proactivator polypeptide; saposin-APSAP37.12.0000017
      Dickkopf-related protein 3DKK337.04.0064695
      F-actin-capping protein subunit βCAPZB36.85.0006800
      Tubulin α-4A chainTUBA4A36.76.0029517
      Clathrin heavy chain 1CLTC36.73.0172379
      Deoxyuridine 5-triphosphate nucleotidohydrolase, mitochondrialDUT36.34.0021730
      Proteasome subunit β type-6PSMB635.95.0444021
      Proprotein convertase subtilisin/kexin type 9PCSK935.87.0432914
      72-kilodalton type IV collagenase; PEXMMP235.79.0004569
      Prolyl 3-hydroxylase 1LEPRE135.26.0496856
      Lactadherin; lactadherin short form; medinMFGE832.58.0003940
      Elongation factor 1-γEEF1G31.24.0469751
      Ferritin light chainFTL29.77.0450262
      Lupus La proteinSSB29.38.0002821
      Follistatin-related protein 5FSTL529.37.0034505
      Matrix-remodeling-associated protein 5MXRA527.17.0056534
      Eukaryotic initiation factor 4A-IIEIF4A227.13.0271990
      WD repeat-containing protein 65WDR6527.05.0052157
      Extracellular sulfatase Sulf-1SULF126.38.0003432
      Calponin-3CNN326.17.0014325
      Protein phosphatase 2 scaffold subunit αPPP2R1A25.84.0446915
      β-1,4-galactosyltransferase 5B4GALT525.78.0196639
      Serum albuminALB25.68.0000003
      Synaptic vesicle membrane protein VAT-1 homologVAT125.46.0000100
      Splicing factor, proline- and glutamine-richSFPQ24.92.0079895
      Glucose-6-phosphate 1-dehydrogenaseG6PD24.56.0146303
      CochlinCOCH24.14.0038765
      Platelet-activating factor acetylhydrolase IB subunit αPAFAH1B123.88.0003566
      Extracellular matrix protein 1ECM123.79.0160787
      Vacuolar protein sorting-associated protein 35VPS3523.12.0179969
      Exostosin-1EXT122.83.0080334
      Protein S100-A6S100A621.49.0386695
      Neutral α-glucosidase ABGANAB21.27.0012394
      PodocanPODN20.85.0020030
      FascinFSCN120.41.0002658
      Olfactomedin-like protein 3OLFML319.10.0087429
      T-complex protein 1 subunit ηCCT719.08.0349927
      Membrane-bound transcription factor site-1 proteaseMBTPS118.28.0444638
      Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3PLOD318.25.0290330
      Heterogeneous nuclear ribonucleoprotein KHNRNPK18.10.0055013
      Peroxiredoxin-4PRDX417.52.0163462
      Heat shock protein 75 kilodaltons, mitochondrialTRAP116.80.0203181
      ANK repeat and PH domain-containing protein 1ACAP115.73.0465981
      Clusterin; clusterin β chain; clusterin α chainCLU15.19.0000107
      Macrophage colony-stimulating factor 1CSF115.06.0234921
      EMILIN-1EMILIN114.74.0335435
      Low-density lipoprotein receptorLDLR14.45.0122306
      Laminin subunit β-2LAMB214.41.0025413
      Carbonyl reductase [reduced nicotinamide adenine dinucleotide phosphate] 3CBR314.29.0040576
      Serpin B6SERPINB613.24.0184994
      60-kilodalton heat shock protein, mitochondrialHSPD112.71.0000572
      Adenosine triphosphate-citrate synthaseACLY12.46.0495593
      Glypican-1; secreted glypican-1GPC111.88.0054106
      PeriostinPOSTN11.34.0000412
      45-kilodalton calcium-binding proteinSDF411.31.0000878
      Importin-5IPO511.24.0232329
      Inositol monophosphatase 1IMPA111.10.0017802
      Fibulin-5FBLN511.09.0004997
      Collagen triple-helix repeat-containing protein 1CTHRC110.55.0246140
      Glutathione S-transferase Ω-1GSTO110.24.0134160
      β-2-microglobulinB2M9.94.0032569
      Actin-related protein 3ACTR39.67.0003930
      Transcriptional activator protein Pur-βPURB9.53.0046924
      Elongation factor 1-βEEF1B29.41.0125778
      Protein phosphatase 1 regulatory subunit 12APPP1R12A9.11.0201546
      Nucleobindin-2NUCB28.99.0004586
      FibronectinFN18.92.0001491
      Collagen α-2(VI) chainCOL6A28.87.0018644
      6-phosphogluconate dehydrogenase, decarboxylatingPGD8.79.0040032
      Amyloid β A4 proteinAPP8.77.0005750
      Transferrin-receptor protein 1TFRC8.65.0001086
      Annexin A2ANXA28.64.0301342
      Elongation factor 2EEF28.11.0000368
      Acetyl-CoA acetyltransferase, cytosolicACAT28.05.0340549
      α-soluble NSF (attachment proteinNAPA7.90.0118155
      Epidermal growth factor–containing fibulin-like extracellular matrix protein 2EFEMP27.84.0003193
      Heat shock 70-kilodalton protein 1A/1BHSPA1A7.64.0088805
      Ubiquitin-like modifier-activating enzyme 1UBA17.44.0052055
      Talin-1TLN17.41.0000026
      Tropomyosin α-3 chainTPM37.41.0022479
      NucleophosminNPM17.14.0005244
      Thrombospondin-1THBS16.59.0008619
      β-hexosaminidase subunit αHEXA6.47.0001968
      Cysteine–transfer RNA ligase, cytoplasmicCARS6.47.0033002
      C-type lectin domain family 11 member ACLEC11A6.34.0002634
      Cysteine and glycine-rich protein 1CSRP16.23.0157997
      Galectin-3-binding proteinLGALS3BP6.20.0003411
      Nucleobindin-1NUCB16.19.0000158
      Proteasome subunit β type-4PSMB45.86.0014785
      Follistatin-related protein 1FSTL15.86.0002589
      Ras guanosine triphosphatase-activating-like protein IQGAP1 (IQ Motif Containing GTPase Activating Protein 1)IQGAP15.68.0108885
      Ribonuclease inhibitorRNH15.63.0057533
      Actin, α cardiac muscle 1ACTC15.55.0002417
      Cathepsin BCTSB5.53.0145813
      Protein disulfide-isomerase A4PDIA45.51.0109743
      Myosin light polypeptide 6MYL65.45.0013450
      Serine/threonine-protein phosphatase 1 (PP1)-β catalytic subunitPPP1CB5.36.0194514
      Hsp90 co-chaperone Cdc37CDC375.34.0088745
      Transforming growth factor-β–induced protein ig-h3TGFBI5.33.0004158
      Purine nucleoside phosphorylasePNP5.26.0437861
      Collagen α-1(XII) chainCOL12A15.22.0030738
      T-complex protein 1 subunit θCCT85.14.0419163
      Peroxiredoxin-2PRDX25.03.0113992
      Epidermal growth factor–containing fibulin-like extracellular matrix protein 1EFEMP15.00.0000249
      Nucleosome assembly protein 1-like 4NAP1L44.88.0008493
      Myosin-9MYH94.88.0021392
      Tubulin β chainTUBB4.85.0006886
      Hsc70-interacting proteinST134.81.0047255
      Importin subunit α-3KPNA44.81.0059251
      Sulfhydryl oxidase 1QSOX14.74.0163887
      Tubulin β-4B chainTUBB4B4.68.0000303
      Nidogen-1NID14.58.0176328
      Cathepsin DCTSD4.57.0000334
      Adenylyl cyclase-associated protein 1CAP14.51.0000022
      Importin subunit β-1KPNB14.51.0011822
      Laminin subunit β-1LAMB14.46.0016507
      WD repeat-containing protein 1WDR14.45.0000318
      Tubulin α-1B chainTUBA1B4.43.0000209
      Aspartate aminotransferase, mitochondrialGOT24.42.0044962
      Proteasome subunit α type-6PSMA64.39.0317503
      Heat shock protein HSP 90-αHSP90AA14.33.0000011
      Coronin-1CCORO1C4.26.0000013
      Eukaryotic initiation factor 4A-IEIF4A14.24.0059134
      Transgelin-2TAGLN24.20.0022821
      Heat shock cognate 71-kilodalton proteinHSPA84.20.0125521
      Nucleoside diphosphate kinase BNME24.15.0049568
      Actin, cytoplasmic 2ACTG14.08.0000034
      Neuropilin-2NRP24.06.0175685
      Pentraxin-related protein PTX3PTX34.04.0007182
      NucleolinNCL4.01.0276738
      Filamin-AFLNA4.01.0003733
      FibromodulinFMOD3.98.0092232
      Plasminogen activator inhibitor 1SERPINE13.97.0000854
      Chloride intracellular channel protein 4CLIC43.92.0008258
      Multiple inositol polyphosphate phosphatase 1MINPP13.91.0418345
      Neuropilin-1NRP13.91.0167928
      Heat shock protein HSP 90-βHSP90AB13.91.0000448
      14-3-3 protein ΣSFN3.88.0010093
      Heterogeneous nuclear ribonucleoprotein D0HNRNPD3.84.0028596
      Reticulocalbin-1RCN13.83.0001862
      VimentinVIM3.81.0081098
      Putative elongation factor 1-α-like 3EEF1A1P53.80.0005683
      LumicanLUM3.80.0000514
      Exostosin-2EXT23.79.0233352
      Puromycin-sensitive aminopeptidaseNPEPPS3.79.0045265
      Glutaminyl-peptide cyclotransferaseQPCT3.76.0074783
      Pyruvate kinase PKMPKM3.76.0006099
      C-Jun-amino-terminal kinase-interacting protein 4SPAG93.74.0003581
      Poly(rC)-binding protein 1PCBP13.71.0004751
      Farnesyl pyrophosphate synthaseFDPS3.55.0033517
      Tropomyosin α-4 chainTPM43.53.0022587
      Transitional endoplasmic reticulum adenosine triphosphataseVCP3.52.0000575
      Hyaluronan-binding protein 2HABP23.50.0021050
      SerglycinSRGN3.49.0041091
      Metalloproteinase inhibitor 2TIMP23.46.0000760
      Phosphoglucomutase-1PGM13.43.0083578
      Filamin-CFLNC3.42.0073859
      Heat shock 70-kilodalton protein 6HSPA63.42.0002413
      78-kilodalton glucose-regulated proteinHSPA53.36.0206891
      Dihydropyrimidinase-related protein 2DPYSL23.36.0000008
      Protein CYR61CYR613.33.0021073
      Chloride intracellular channel protein 1CLIC13.32.0000008
      α-actinin-1ACTN13.29.0025329
      Histone H2A type 2-C; histone H2A type 2-AHIST2H2AC3.29.0061036
      Ubiquitin carboxyl-terminal hydrolase isozyme L1UCHL13.28.0423517
      Proteasome subunit α type-1PSMA13.20.0008972
      Ras-related protein Rap-1ARAP1A3.19.0000007
      Gremlin-1GREM13.18.0497429
      γ-glutamyl hydrolaseGGH3.17.0003584
      14-3-3 protein ηYWHAH3.17.0004627
      Peroxiredoxin-1PRDX13.14.0000143
      Protein SETSET3.14.0011534
      Protein CutACUTA3.09.0021038
      Peptidyl-prolyl cis-trans isomerase APPIA3.09.0071350
      Galectin-1LGALS13.08.0000155
      Protein disulfide-isomeraseP4HB3.08.0009140
      F-actin-capping protein subunit α-1CAPZA13.05.0000032
      Histone H2B type 1-LHIST1H2BL3.01.0104479
      Thrombospondin-3THBS33.01.0061737
      α-actinin-4ACTN42.99.0006276
      Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 1PLOD12.99.0000104
      Acylamino-acid–releasing enzymeAPEH2.97.0382093
      Lysyl oxidase homolog 2LOXL22.96.0002226
      Thrombospondin-4THBS42.92.0017107
      Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2PLOD22.90.0165680
      Glyceraldehyde-3-phosphate dehydrogenaseGAPDH2.89.0000848
      CalmodulinCALM12.89.0223212
      X-ray repair cross-complementing protein 5XRCC52.88.0123259
      Phosphoglycerate kinase 1PGK12.81.0111379
      14-3-3 protein γYWHAG2.77.0000012
      Collagen α-1(VI) chainCOL6A12.72.0001905
      Rho guanine nucleotide exchange factor 18ARHGEF182.66.0000016
      Malate dehydrogenase, cytoplasmicMDH12.66.0185247
      Triosephosphate isomeraseTPI12.63.0036592
      Fructose-bisphosphate aldolase AALDOA2.59.0288449
      VinculinVCL2.54.0021035
      α-enolaseENO12.51.0004602
      Apolipoprotein C-IIIAPOC32.46.0180784
      Secernin-1SCRN12.45.0288882
      Ubiquitin-60S ribosomal protein L40UBA522.39.0001326
      14-3-3 protein β/αYWHAB2.38.0002045
      DnaJ homolog subfamily C member 13DNAJC132.38.0120707
      14-3-3 protein epsilonYWHAE2.37.0002483
      MoesinMSN2.35.0003671
      Phosphoglycerate mutase 1PGAM12.24.0024083
      Nicotinamide N-methyltransferaseNNMT2.22.0153174
      Ferritin heavy chainFTH12.20.0224213
      Aldose 1-epimeraseGALM2.18.0006598
      Nuclear receptor subfamily 1 group D member 2NR1D22.02.0248565
      NOTE. n = 9 CAF primary cultures, P < .05.
      IQGAP1, IQ Motif Containing GTPase Activating Protein 1; NSF, N-Ethylmaleimide-Sensitive Factor.

      SOM230 Reduces Metastasis in PDA Mouse Models Through the GPCR sst1 Expressed on CAFs

      We previously showed that SOM230 is antimetastatic in immunocompromised mice, by indirectly, through its action on CAFs, inhibiting epithelial-to-mesenchymal transition in PDA tumor cells.
      • Moatassim-Billah S.
      • Duluc C.
      • Samain R.
      • Jean C.
      • Perraud A.
      • Decaup E.
      • Cassant-Sourdy S.
      • Bakri Y.
      • Selves J.
      • Schmid H.
      • Martineau Y.
      • Mathonnet M.
      • Pyronnet S.
      • Bousquet C.
      Anti-metastatic potential of somatostatin analog SOM230: indirect pharmacological targeting of pancreatic cancer-associated fibroblasts.
      To evaluate whether SOM230 normalized the PDA stroma in models closer to the clinic, we developed an immunocompetent murine model consisting of the orthotopic co-graft of syngeneic C57BL/6 tumor cells (derived from Pdx-1-Cre; LSL-KrasG12D/+; LSL-Trp53R172H/+ tumors [KPC tumors]),
      • Hingorani S.R.
      • Wang L.
      • Multani A.S.
      • Combs C.
      • Deramaudt T.B.
      • Hruban R.H.
      • Rustgi A.K.
      • Chang S.
      • Tuveson D.A.
      Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice.
      with PSCs isolated from either wild-type (WT) or sst1 knock-out (KOsst1) C57BL/6 mouse pancreata
      • Videau C.
      • Hochgeschwender U.
      • Kreienkamp H.J.
      • Brennan M.B.
      • Viollet C.
      • Richter D.
      • Epelbaum J.
      Characterisation of [125I]-Tyr0DTrp8-somatostatin binding in sst1- to sst4- and SRIF-gene-invalidated mouse brain.
      (Figure 2A and B). First, these PSCs were characterized phenotypically. Ex vivogrown WT mice PSCs were activated (as attested by up-regulation of α smooth muscle actin [αSMA] expression) and spontaneously acquired the expression of GPCR sst1 (Figure 2C). They also presented high protein synthesis rates (monitored by surface sensing of translation [SUnSET]),
      • Schmidt E.K.
      • Clavarino G.
      • Ceppi M.
      • Pierre P.
      SUnSET, a nonradioactive method to monitor protein synthesis.
      as we previously published in human CAFs,
      • Duluc C.
      • Moatassim-Billah S.
      • Chalabi-Dchar M.
      • Perraud A.
      • Samain R.
      • Breibach F.
      • Gayral M.
      • Cordelier P.
      • Delisle M.B.
      • Bousquet-Dubouch M.P.
      • Tomasini R.
      • Schmid H.
      • Mathonnet M.
      • Pyronnet S.
      • Martineau Y.
      • Bousquet C.
      Pharmacological targeting of the protein synthesis mTOR/4E-BP1 pathway in cancer-associated fibroblasts abrogates pancreatic tumour chemoresistance.
      these rates were reduced by SOM230, as was the expression of the extracellular matrix (ECM) protein and CAF marker periostin (Figure 2D).
      • Neuzillet C.
      • Tijeras-Raballand A.
      • Ragulan C.
      • Cros J.
      • Patil Y.
      • Martinet M.
      • Erkan M.
      • Kleeff J.
      • Wilson J.
      • Apte M.
      • Tosolini M.
      • Wilson A.S.
      • Delvecchio F.R.
      • Bousquet C.
      • Paradis V.
      • Hammel P.
      • Sadanandam A.
      • Kocher H.M.
      Inter- and intra-tumoural heterogeneity in cancer-associated fibroblasts of human pancreatic ductal adenocarcinoma.
      Accordingly, periostin was identified in the SOM230-regulated, patient-derived CAF secretomic signature (Table 1). KOsst1 mice PSCs showed equivalent high intrinsic protein synthesis rates and periostin expression as WT PSCs, but were not responsive to SOM230 treatment (Figure 2D). WT or KOsst1 PSCs then were co-grafted with tumor cells in C57BL/6 mice, which were later treated or not with SOM230 once tumors were formed, as indicated (Figure 2E). No SOM230 effect was observed on primary tumor growth in any group (Figure 2F), whereas the drug significantly reduced lung metastasis incidence and tumor load (defined as the cumulative lung metastatic area, less than or more than 0.1% of the total lung area) in mice co-grafted with tumor cells and WT PSCs (Figure 2G and H). No liver metastases were observed in this model. SOM230 did not significantly inhibit metastasis in mice co-grafted with KOsst1 PSCs. Altogether, these results show that SOM230 is antimetastatic in a novel immunocompetent PDA model because of its action on sst1 expressed by CAFs.
      Figure thumbnail gr2
      Figure 2SOM230 reduces metastasis dependently on CAF-expressed sst1 in a murine PDA model. (A–D) Characterization of WT and KOsst1 murine PSCs. (A) The abundance of sstr1 mRNA was analyzed by real-time quantitative PCR in WT or KOsst1 PSCs, and in spleen as a positive control, and normalized to the housekeeping rps16 mRNA. (B) Western blot analyses of the indicated proteins in PSCs, either WT, heterozygous (Het sst1), or KO sst1. β-actin was used as an internal loading control. (C) Western blot analyses of the indicated proteins in PSCs freshly isolated from mouse pancreata and cultured for 5, 9, and 13 days. (D) Western blot analyses of the indicated proteins in WT or KOsst1 PSCs, treated or not with SOM230 (10-7 mol/L; 24 h). β-actin was used as an internal loading control. (E) Experimental design of the study. Cancer cells (CC) were syngeneically and orthotopically co-grafted with murine sst1-WT or sst1-KO PSCs (PSC KOsst1). After 3 weeks, mice were randomized and treated or not (NT) with SOM230–long-acting releasing form (LAR) for 3 weeks. After 6 weeks, mice were killed (n = 4–6 mice/group). (F) Tumor volume evolution from treatment day 1 to day 21, monitored weekly by ultrasound, in mice grafted with CCs plus WT or KOsst1 PSCs. (G) Metastasis incidence in mouse lungs and distribution of mice according to their metastatic lung load (cumulative metastatic lung area less than or greater than 0.1% of total lung area). The chi-squared test was used to generate P values. ∗P < .05. (H) Representative H&E staining of mouse lungs. Dashed lines encircle metastases. Scale bars: 100 μm.

      SOM230 Inhibits Metastasis by Decreasing CAF-Secreted CSF-1

      To identify CAF-secreted proteins involved in the drug antimetastatic effect, we searched for factors down-regulated by SOM230 both in the CAF secretome (Table 1) and in the plasma of mice grafted with KPC tumor cells plus PSCs and treated with SOM230 (from Figure 2) (Figure 3A and B, Table 2). Five common proteins were identified (Figure 3C), including periostin and the chemokine CSF-1.
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      We focused on CAF-secreted CSF-1. We confirmed by enzyme-linked immunosorbent assay (ELISA) that SOM230 decreased CSF-1 in patient CAF-conditioned media (Figure 3D). Importantly, we found that sst1-expressing CAFs also co-expressed CSF-1, as assessed by confocal immunofluorescence imaging of patient PDA tissues (Figure 3E). In the plasma of grafted and SOM230-treated mice (from Figure 2), we confirmed that SOM230 decreased the CSF-1 concentration in a dependent manner to CAF-expressed sst1 (Figure 3F). CSF-1 expression also was reduced by SOM230 in the primary tumors of treated mice (Figure 3G) (the different 50- to 60-kilodalton-weight bands visualized by Western blot are consistent with the described spliced and matured forms of CSF-1).
      • Yagiz K.
      • Rittling S.R.
      Both cell-surface and secreted CSF-1 expressed by tumor cells metastatic to bone can contribute to osteoclast activation.
      To test the role of CAF-secreted CSF-1 on the antimetastatic effect of SOM230, KPC tumor cells then were co-grafted in the pancreas of syngeneic mice with WT or CSF-1–overproducing and secreting PSCs (CSF-1 PSCs). We confirmed by ELISA a high CSF-1 production in conditioned media of CSF-1 PSCs (122 ± 5 ng/mL), which SOM230 was unable to reduce (Figure 3H). Upon orthotopic co-graft in C57BL/6 mice of tumor cells with WT or CSF-1 PSCs, no significant difference in tumor growth or in metastatic potential was observed in the untreated condition, and SOM230 did not impact primary tumor growth in WT PSCs or in CSF-1–transduced PSCs (Figure 3I and J). However, the expected SOM230 inhibitory effect on lung metastasis incidence and load observed with WT PSCs was abrogated when PSCs overexpressed secreted CSF-1 (Figure 3J and K). These results show the critical role of CAF-derived CSF-1 in the antimetastatic effect of SOM230.
      Figure thumbnail gr3
      Figure 3SOM230 reduces tumoral and plasmatic CSF-1 expression dependently on CAF-expressed sst1, explaining its antimetastatic effect in murine PDA models. (A) Membrane antibody arrays using plasma from mice grafted with cancer cells (CCs) plus PSCs, and treated or not (NT) with SOM230 (pool of n = 5 mice/membrane). (B) Cytokine array quantification of plasma proteins in CCs plus PSC grafted mice and treated with SOM230 as compared with untreated (NT), showing down-regulated proteins (pool of n = 5 mice/group). (C) Venn diagram of the overlap of down-regulated plasma proteins from grafted mice identified in cytokine arrays (A, B) and from CAF secretome analysis (). Common proteins are listed underneath. (D and H) CSF-1 ELISA quantification in (D) conditioned media of human CAF (n = 5 CAF primary cultures), or (H) murine PSC overexpressing CSF-1 or not (mock) (performed in quadruplicate), treated or not (NT) with SOM230, and expressed relative to NT. The paired or unpaired Student t test was used. (E) Immunofluorescence confocal analysis of CSF-1 (green), sst1 (red), and cytokeratin-19 (CK-19; purple) expression in 2 patient-derived PDA tissues, showing co-localization in the stroma (at distance from tumor epithelial CK-19–positive cells) of sst1 and CSF-1. Scale bars: 50 μm. (F) Plasma CSF-1 ELISA quantification at death of ungrafted mice (first condition), or grafted mice treated or not with SOM230 (from , n = 4 per group). Each dot represents the CSF-1 plasma concentration measured in 1 mouse. Analysis of variance followed by the Bonferroni multiple comparison post-test was used to generate P values. (G) Western blot analysis of tumor lysates from grafted mice (from , mouse tumors 1-to-6) treated or not (NT) with SOM230 (n = 6 mice/treatment condition), with anti–CSF-1 or Akt (loading control) antibody, and quantification (densitometric analysis) of CSF-1 normalized to Akt expression (A.U., arbitrary unit). The unpaired Student t test was used to generate P values. (I–K) CCs were syngeneically and orthotopically co-grafted with murine PSCs overexpressing or not (MOCK) a secreted CSF-1 form (PSC–CSF-1). After 3 weeks, mice were randomized and treated or not (NT) with SOM230-LAR for 3 weeks. After 6 weeks, mice were killed (n = 6 mice/group). (I) Tumor volume evolution from treatment day 1 to 21, monitored weekly by ultrasound. (J) Metastasis incidence in mouse lungs and distribution of mice according to their metastatic lung load (cumulative metastatic lung area less than or greater than 0.1% of the total lung area). The chi-squared test was used to generate P values. (K) Representative H&E staining of mouse lungs. Dashed lines encircle metastases. Scale bars: 100 μm. ∗P < .05, ∗∗P < .01, and ∗∗∗P < .001
      Table 2Listing of Down-Regulated Proteins in Cancer Cell–PSC Grafted Mice Plasma: SOM230 vs Untreated
      Protein nameLog ratio SOM230/NT
      CD14-0.836393
      IFN-γ-0.257125
      TIM-1-0.2522933
      IL5-0.2357543
      Chemerin-0.2076414
      PDGF-BB-0.2058304
      IL10-0.2005681
      Leptin-0.1993592
      Serpin F1-0.1981243
      Flt-3 ligand-0.1887131
      CD160-0.1865666
      CXCL9-0.1772411
      TNF-α-0.1492109
      Myeloperoxidase-0.1471288
      Pentraxin 2-0.1347746
      E-selectin-0.1293948
      IL12p40-0.121981
      FGF acidic-0.1169429
      IL13-0.1077902
      LDL R-0.1072964
      VCAM-1-0.1065818
      IL11-0.09950715
      PD-ECGF-0.09708886
      M-CSF-0.09599823
      RBP4-0.095954
      LIF-0.09346522
      PCSK9-0.09068561
      CCL11-0.08666945
      IL1 α-0.08475557
      IGFBP-3-0.08151417
      IL27p28-0.0749929
      CXCL11-0.07498571
      RAGE-0.06808221
      CXCL10-0.05732954
      Pentraxin 3-0.05685075
      Endoglin-0.05549461
      IL7-0.05403424
      Pref-1/DLK-1-0.0525299
      P-selectin-0.05165642
      IGFBP-5-0.04817382
      IL15-0.04627419
      Periostin-0.04173948
      Lipocalin-2-0.03777582
      IL28-0.03427079
      Osteopontin-0.033357
      IL33-0.02293778
      IL4-0.02049208
      IL6-0.01649792
      NOTE. Pool of n = 5 mice/group.
      CCL, CC chemokine ligand; CXCL, (C-X-C) motif ligand; DLK-1, delta-like protein 1; FGF, fibroblast growth factor; Flt-3, fms like tyrosine kinase 3; IFN, interferon; IGFBP, insulin-like growth factor- binding protein; IL, interleukin; LDL, low-density lipoprotein; LIF, leukemia inhibitory factor; PCSK9, proprotein convertase subtilisin/kexin type-9; PD-ECGF, platelet-derived endothelial cell growth factor; PDGF-BB, platelet-derived growth factor-BB; RAGE, receptor for advanced glycation end products; RBP-4, retinol-binding protein 4; TIM-1, T cell Ig and mucin 1; TNF, tumor necrosis factor; VCAM-1, vascular cell adhesion molecule 1.

      SOM230, Acting Through the CAF-Expressed GPCR sst1, Normalizes the Inflammatory PDA Stroma

      Because the CSF-1 chemokine is involved in monocyte recruitment and activation,
      • DeNardo D.G.
      • Ruffell B.
      Macrophages as regulators of tumour immunity and immunotherapy.
      we performed fluorescence-activated cell sorter analysis on pancreatic tumors grown in mice co-grafted with tumor cells plus WT or KOsst1 PSCs (Figure 4A and B). SOM230 treatment did not significantly impact intratumor load of total CD45, but decreased that of F4/80+ macrophages, and of the F4/80+CD11b+CD206+ macrophage subset, whereas the CD11b+Gr1+ subset myeloid-derived suppressor cell was not affected (Figure 4C–F). In contrast, no significant effect of SOM230 on macrophage subsets was observed when KOsst1 PSCs were co-grafted (Figure 4D–F). SOM230 treatment did not impact the proportions of CD3+, CD4+, and CD8+ lymphoid cell populations (Figure 4G–I). These results indicate that SOM230 decreases the intratumor macrophage load, including the F4/80+CD11b+CD206+ subset comprising TAMs.
      Figure thumbnail gr4
      Figure 4SOM230 reduces TAM presence. (A and B) Experimental design of the study. (A) Cancer cells were syngeneically and orthotopically co-grafted with murine WT or KOsst1 PSCs. One week after graft, mice were randomized and treated or not with SOM230-LAR. Three weeks after graft, mice were killed. (B) Gating strategy to identify viable cells, total CD45-positive cells, total macrophages, CD206high macrophages, and myeloid-derived suppressor cell immune populations (i, red boxes), or total CD45-positive cells, total lymphocytes, helper CD4 lymphocytes, and cytotoxic CD8 lymphocytes immune populations (ii, blue boxes). (C–I) Proportions of (C) total immune cells (CD45+ cells), (D) total macrophages (CD45+; F4/80+; CD11b+ cells), (E) CD206hi macrophages, (F) myeloid-derived suppressor cell (CD45+; CD11b; lymphocyte antigen 6 complex locus G [Ly6g]+ cells), (G) T lymphocytes (CD45+; CD3+ cells), (H) helper T lymphocytes (CD4+ T lymphocytes), and (I) cytotoxic T lymphocytes (CD8+ T lymphocytes) were quantified (in % of total cells) by flow cytometry on tumors from cancer cells + PSC-injected mice (n = 4–5 mice/group). The Kruskal–Wallis test followed by the Dunn multiple comparison post-test was used to generate P values. ∗P < .05.

      SOM230 Is Antimetastatic in a Murine Spontaneous Model of PDA

      The therapeutic and stroma-normalizing benefits of SOM230 were tested in KPC mice, developing a spontaneous PDA recognized to closely mimic the human pathology and its fibrotic immune stroma.
      • Hingorani S.R.
      • Wang L.
      • Multani A.S.
      • Combs C.
      • Deramaudt T.B.
      • Hruban R.H.
      • Rustgi A.K.
      • Chang S.
      • Tuveson D.A.
      Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice.
      We showed by immunohistochemistry that sst1 was expressed in the αSMA-positive KPC tumor stroma (Figure 5A). Because all PDA patients receive chemotherapy and to get closest to clinical reality, SOM230 treatment of KPC mice also was evaluated in a chemotherapy background (gemcitabine), as indicated (Figure 5B), starting at equal ultrasound-calculated mean volumes between treatment groups (Figure 5C). We observed that tumor volume progression, which was exponential from day 1 to 21 in untreated mice, was reduced significantly in the combination-treated group (gemcitabine plus SOM230), but not by gemcitabine or SOM230 alone (Figure 5D–H). The combination therapy also significantly reduced tumor growth and extended survival, compared with untreated or gemcitabine-treated mice, in another spontaneous transgenic mouse PDA model (Pdx1-Cre; LSL-KrasG12D; Ink4afl/fl), in which gemcitabine alone also was efficient (Figure 5I). In KPC mice, metastatic incidence and load were analyzed in the liver (only rare lung micrometric metastases were visualized). This was comparatively quantified in KPC mice presenting equivalent primary tumor volume after killing (Table 3), to avoid the evaluation of a drug antimetastatic potential directly linked to its delaying effect on primary tumor growth. The combination therapy significantly reduced liver metastatic incidence and load because only 4 of 8 mice in this group presented liver metastases with a low metastatic load (defined as <3% of cumulative liver metastatic area), against 7 of 8 in the untreated or gemcitabine-treated group, which presented in most cases a high metastatic load (Figure 5K and L). In contrast, SOM230 did not have an antimetastatic effect when administered alone, although 2 of 8 SOM230-treated mice, whose tumor growth was delayed by SOM230 (mice number 734 and 1027) (Figure 5G, Table 3), also were nonmetastatic. Only the combination therapy significantly extended mouse survival, as compared with no treatment (Figure 5M). These results show that SOM230 is inefficient to inhibit metastatic spread in KPC mice when used alone, but is antimetastatic in a gemcitabine-treated background.
      Figure thumbnail gr5
      Figure 5SOM230 delays the growth and metastasis of spontaneous pancreatic tumors generated in the immunocompetent KPC mouse model. (A) Representative immunostaining of αSMA and sst1 receptor in serial sections of a KPC primary tumor (untreated mice) showing expression of sst1 receptor in αSMA-positive cell areas. Scale bars: 200 μm. (B–H) Experimental design. (B) KPC mice had an ultrasound weekly from 8 weeks of age until tumor size enrollment was reached (homogenous treatment group tumor volumes, 31–200 mm3; mean, 103.9 mm3; analysis of variance followed by the Bonferroni multiple comparison post-test was used). (C) Mice were randomized into treatment groups (PBS-treated [NT], SOM230-long-acting release [LAR], gemcitabine [Gem], or gemcitabine plus SOM230-LAR [Gem-SOM230], n = 8 mice per group). (D–H) Tumor volume was quantified by ultrasound until ethical end point (when maximal-authorized volume of the primary tumor, or clinical end points, were reached). Tumor volume progression from treatment day 1 to 21. Analysis of variance followed by the Bonferroni multiple comparison post-test was used to generate P values. (D) Representation of tumor volume progression from treatment day 1 until death for each mouse in the 4 treatment conditions. (E–H) KPC mouse identity numbers are indicated, according to . (I and J) Pdx1-Cre; LSL-KrasG12D; Ink4afl/fl mice (KIC) were treated as indicated. (I) Tumor weight was measured at euthanasia (n = 4–5 mice/group) (analysis of variance followed by the Bonferroni multiple comparison post-test was used to generate P values). (J) Survival analysis (Kaplan–Meier) was analyzed using a log-rank test. (K–M) KPC liver metastasis and mouse survival analyses. (K) Representative H&E staining. Arrows indicate metastases. Scale bars: 2.5 mm. Metastasis incidence in KPC livers and distribution of mice according to their metastatic liver load (cumulative metastatic liver area less than or greater than 3% of the total liver area). (L) Significance of liver metastatic overload (>3% of the total liver area) was determined with the chi-squared test. (M) Survival analysis of KPC mice treated as indicated. Kaplan–Meier survival data were analyzed using a log-rank test. ∗P < .05, ∗∗P < .01, and ∗∗∗P < .001.
      Table 3Characteristics of KPC Mice
      DrugIDAge at treatment start, dTumor volume on treatment day 1, mm3Tumor volume at death, mm3Survival, dLiver metastasisLiver metastatic area, %Ascites
      No30203150∼100021Yes0.02Yes
      72203146∼100035Yes0.24No
      11316134∼100042No0.00No
      20013366∼100035Yes0.11No
      748131167∼100030Yes4.72Yes
      73517540∼100021Yes6.94Yes
      244210113∼100020Yes36.40Yes
      1002114115∼100023Yes4.98Yes
      SOM230828205145∼100021Yes0.06No
      862210101∼100016No0.00No
      102716453∼100056No0.00No
      82424741∼100052Yes2.92No
      954238170∼100022Yes5.79Yes
      719143113∼100021Yes10.74Yes
      73415699∼100021No0.00No
      69012672∼100024Yes7.35No
      Gemcitabine310162200∼100020Yes28.15No
      22216231∼100037Yes0.04No
      26917214956050Yes59.03No
      462205195∼100046Yes11.89Yes
      488273108∼100013Yes9.75Yes
      947204144∼100021No0Yes
      9012335070060Yes1.44No
      109614853∼100080Yes5.99No
      Gemcitabine SOM230104210158∼100031No0.00No
      254145123∼100039Yes0.05No
      125267190∼100032Yes0.46No
      1401923280091No0.00No
      19421280∼100042Yes2.86Yes
      95319490∼100077No0.00No
      600197111∼100037Yes0.35Yes
      87215078∼100051No0.00Yes
      Immunopathology of KPC primary tumors showed that SOM230 treatment, when combined with chemotherapy, did not increase the cytotoxicity of gemcitabine, which significantly triggers DNA damage (phospho-γ-H2AX index, H2A histone family member X), and did not affect tumor cell proliferation (Ki-67 index) (Figure 6A–C). When exploring drug effects on the stroma, we observed that the combination therapy did not affect the presence of intratumor CD8-positive lymphocytes, or myeloid lymphocyte antigen 6 complex locus G–positive and myeloperoxidase-positive granulocytes, as compared with gemcitabine (Figure 6D–F), but significantly decreased CD206-positive myeloid cell number, a read-out of TAMs (Figure 6G and H). αSMA-positive CAFs and ECM (glycosaminoglycan and collagen) deposits (quantified in turquoise blue/green using the Movat Pentachrome stain) were robustly decreased with the combination therapy, as compared with gemcitabine (Figure 6I–L). Tumor cell STAT3 (signal transducer and activator of transcription member 3) phosphorylation, a reported marker of ECM-induced mechanical stress and of increased tumor cell invasiveness,
      • Laklai H.
      • Miroshnikova Y.A.
      • Pickup M.W.
      • Collisson E.A.
      • Kim G.E.
      • Barrett A.S.
      • Hill R.C.
      • Lakins J.N.
      • Schlaepfer D.D.
      • Mouw J.K.
      • LeBleu V.S.
      • Roy N.
      • Novitskiy S.V.
      • Johansen J.S.
      • Poli V.
      • Kalluri R.
      • Iacobuzio-Donahue C.A.
      • Wood L.D.
      • Hebrok M.
      • Hansen K.
      • Moses H.L.
      • Weaver V.M.
      Genotype tunes pancreatic ductal adenocarcinoma tissue tension to induce matricellular fibrosis and tumor progression.
      followed the same pattern as ECM deposits (Figure 6M). Gemcitabine tends to increase vessel area (using a monoclonal mouse-specific panendothelial cell antigen antibody [MECA32]), and to decrease pericyte recruitment around tumor vessels (as quantified using the co-stain of MECA32 and neuron-glial antigen 2 [NG2]), effects that are significantly reversed when SOM230 is combined (Figure 6N–P). Interestingly, pericyte depletion was reported to induce metastasis.
      • Keskin D.
      • Kim J.
      • Cooke V.G.
      • Wu C.C.
      • Sugimoto H.
      • Gu C.
      • De Palma M.
      • Kalluri R.
      • LeBleu V.S.
      Targeting vascular pericytes in hypoxic tumors increases lung metastasis via angiopoietin-2.
      In liver metastases, CD206-positive myeloid cell number also was decreased by the combination therapy as compared with gemcitabine (Figure 7A and B), as well as αSMA-positive cells (Figure 7C and D), whose number increased with metastasis size (Figure 7E). Altogether, our results show in KPC mice that SOM230 normalizes the immune monocytic, fibrotic, and vascular stroma, in correlation with its antimetastatic potential.
      Figure thumbnail gr6
      Figure 6Macrophage polarization, ECM deposit, and angiogenesis are decreased in primary KPC tumors upon combination treatment as compared with gemcitabine. Quantification and representative pictures of markers analyzed by immunohistochemistry using the indicated antibodies in KPC primary tumors (Tum.). Each value represents the marker quantification in each tumor (n = 8 mice/group). (A and B) Phospho-γH2AX–positive cells (in % of total cells). Scale bars: 50 μm. (C–F) Quantification of (C) Ki-67–positive cells (in % of total cells), and of (D) CD8-positive cells, (E) lymphocyte antigen 6 complex locus G [Ly6G]-positive cells, or (F) myeloperoxidase (MPO)-positive cells (number/field). (G and H) CD206 mean fluorescence intensity (in intensity of each field). Scale bars: 100 μm. (I and J) αSMA-positive area (in % of each total field area). (K and L) Turquoise blue/green-positive area from Movat pentachrome staining (in % of each total field area). (M) Quantification of phospho-STAT3–positive cells (in number/mm2). (N) Representative pictures. (O) Quantification of MECA32-positive cells (in % of 4′,6-diamidino-2-phenylindole [DAPI]-positive cells) (n = 4–6 mice/group). (P) Quantification of NG2/MECA32 double-positive cells (% of NG2-positive pericytic cells in the Meca32-positive cell population, as in
      • Gilles M.E.
      • Maione F.
      • Cossutta M.
      • Carpentier G.
      • Caruana L.
      • Di Maria S.
      • Houppe C.
      • Destouches D.
      • Shchors K.
      • Prochasson C.
      • Mongelard F.
      • Lamba S.
      • Bardelli A.
      • Bouvet P.
      • Couvelard A.
      • Courty J.
      • Giraudo E.
      • Cascone I.
      Nucleolin targeting impairs the progression of pancreatic cancer and promotes the normalization of tumor vasculature.
      (n = 4–6 mice/group). Kruskal–Wallis test followed by the Dunn multiple comparison post-test was used to generate P values. ∗P < .05, ∗∗P < .01. p-STAT3, phospho-signal transducer and activator of transcription.
      Figure thumbnail gr7
      Figure 7Stroma analyses of KPC metastases, and quantification of tumor and plasmatic CSF-1 expression according to mouse treatment and metastasis size. (A–D) Quantification and representative immunohistochemistry pictures of (A and B) CD206-positive cells (number/field), and of (C and D) αSMA-positive area (in % of each metastasis area). Each value represents the marker quantification per liver metastasis (n = 6–38 metastases/group). L, liver; M, metastasis. Kruskal–Wallis test followed by the Dunn multiple comparison post-test was used to generate P values. (E) Representation of αSMA-positive area (in % of each metastasis area) for each KPC liver metastasis (Met.), and according to metastasis size (<0.7 mm2 or >0.7 mm2). The unpaired Student t test was used to generate P values. (F and G) Cytokine array quantification of plasma proteins in KPC mice treated with the combination (gemcitabine plus SOM230) compared with gemcitabine alone (pool of n = 5 mouse plasma/treatment condition), (F) showing the membranes, and (G) down-regulated proteins (pool of n = 5 mice/group). (H) Venn diagram of the overlap of SOM230 down-regulated plasma proteins from KPC (treatment Gem-SOM230 vs Gem) (), from grafted mice (A and B, ), both identified using cytokine arrays, and from CAF secretome analysis (, ). Common proteins are listed in the right panel. (I) Plasma CSF-1 ELISA quantification in KPC mice treated or not (NT) with gemcitabine (Gem) or SOM230 or gemcitabine + SOM230 (n = 8 mice/treatment condition), at death. Each dot represents CSF-1 plasma concentration measured in 1 mouse. Analysis of variance followed by the Bonferroni multiple comparison post-test was used to generate P values. (J) Western blot analysis of tumor lysates from KPC mice, treated or not (NT) with gemcitabine (Gem), SOM230, or gemcitabine + SOM230 (n = 5–6 mice/treatment condition, randomly chosen from the n = 8 mice enrolled in each treatment group), with anti–CSF-1 and Akt (loading control) antibody, and underneath, quantification (densitometric analysis) of CSF-1 normalized to Akt expression (A.U., arbitrary unit). Analysis of variance followed by the Bonferroni multiple comparison post-test was used to generate P values. (K) Correlation between plasma CSF-1 concentrations and metastasis liver area in KPC mice (untreated mice, n = 12). (L and M) Immunofluorescence confocal images of αSMA (red), CSF-1 (green), and CK-19 (white) on formalin-fixed, paraffin-embedded tissue slides of (L) KPC primary tumors, scale bar: 20 μm (except for the lower-right panel, which is a magnification of the lower-left panel [dashed-lined box], scale bar: 10 μm), and (M) in liver metastases, either stroma-rich (3 upper panels) or stroma-poor (3 lower panels), scale bar: 50 μm. ∗P < .05, ∗∗P < .01, and ∗∗∗P < .001. IL, interleukin.
      When searching for factors commonly down-regulated by SOM230 in the CAF secretome (Table 1), in the plasma of drug-treated grafted mice (Table 2), and in the plasma of KPC mice also treated with gemcitabine (Figure 7F–H, Table 4), we again retrieved CSF-1 among 5 other proteins, also including periostin (Figure 7H). Hence, in KPC mice, SOM230 reduced plasma or intratumor CSF-1 expression when combined with gemcitabine compared with gemcitabine alone (Figure 7I and J). Interestingly, CSF-1 plasmatic concentration in KPC mice correlated with the extent of liver metastatic load (Figure 7K). In KPC primary tumors, αSMA-positive CAFs, but barely tumor cells, expressed CSF-1 (Figure 7L). However, in KPC liver metastases, CSF-1 was expressed heterogeneously, mainly in stromal cells (cytokeratin-19–negative but also αSMA-negative) in large metastases (>0.7 mm2) (Figure 7M, 3 upper panels), but mainly in tumor cells (cytokeratin-19–positive), with a membranous localization, in smaller metastases (<0.7 mm2) (Figure 7M, 3 lower panels). Altogether, in a spontaneous PDA murine model, these results confirmed that SOM230 provides a therapeutic antimetastatic benefit when given in combination with gemcitabine, in correlation with a drug inhibitory effect on the chemokine CSF-1. Our results also show that the CSF-1 plasmatic concentration correlates with the metastatic potential in KPC mice, and that CSF-1 is expressed mainly in the stroma in KPC primary tumors and large stroma-rich metastases.
      Table 4Listing of Down-Regulated Proteins in KPC Plasma: Gemcitabine-SOM230 Vs Gemcitabine
      Protein namesLog ratio Gem-SOM230/Gem
      Osteoprotegerin-0.4554106
      WISP-1-0.3132871
      CD14-0.2991138
      Myeloperoxidase-0.2927159
      Serpin F1-0.2775624
      Angiopoietin-2-0.2744032
      CCL21-0.2670901
      Endoglin-0.2538754
      Serpin E1-0.2071946
      MMP-3-0.1980219
      M-CSF-0.1955245
      CCL22-0.1905704
      BAFF-0.1831733
      Adiponectin-0.1755342
      CCL17-0.1687388
      Gas 6-0.1684436
      IL23-0.1624154
      TNF-α-0.1563117
      Proliferin-0.1550597
      LDL R-0.1511058
      IL17A-0.1482403
      C1q R1-0.1431448
      Pref-1-0.1390524
      E-selectin-0.1310115
      IGFBP-3-0.1281087
      VEGF-0.1134834
      CD160-0.1099336
      IL6-0.1047299
      MMP-9-0.1046919
      CXCL13-0.1005212
      IL3-0.09737246
      MMP-2-0.0957026
      Periostin-0.09313533
      PCSK9-0.09101482
      Osteopontin-0.08783475
      IGFBP-5-0.08713286
      CXCL16-0.08686412
      Complement component C5-0.08671959
      CCL6-0.08508948
      CD40-0.08502961
      CXCL1-0.08414122
      CX3CL1-0.08342186
      Pentraxin 3-0.08190633
      IGFBP-2-0.07113896
      RBP4-0.06947069
      IL15-0.0686098
      Thrombopoietin-0.06512675
      TIM-1-0.06420811
      GDF-15-0.06296449
      VCAM-1-0.05980025
      IL1β-0.05504656
      CXCL10-0.05379479
      ICAM-1-0.0524515
      Complement factor D-0.05201
      Fetuin A-0.05186915
      FGF-21-0.05006535
      Chitinase 3-like 1-0.0484128
      IL1α-0.04661465
      EGF-0.04635749
      IGFBP-6-0.04144023
      Angiopoietin-like 3-0.04035782
      PD-ECGF-0.03923278
      P-selectin-0.03810753
      Flt-3 ligand-0.03448458
      IL7-0.03444469
      Chemerin-0.02659499
      CCL12-0.02634445
      CXCL9-0.02562579
      Endostatin-0.02464836
      HGF-0.01868339
      IFN-γ-0.0183519
      IL1ra-0.0171957
      DPPIV-0.01625448
      Lipocalin-2-0.01578041
      IGFBP-1-0.01393292
      CXCL11-0.01046351
      CCL11-0.004502624
      NOTE. Pool of n = 5 mice/group.
      BAFF, B-cell activating factor; CCL, CC chemokine ligand; CXCL, (C-X-C) motif ligand; DPPIV, dipeptidyl-peptidase IV; EGF, epidermal growth factor; FGF, fibroblast growth factor; Flt-3, fms like tyrosine kinase 3; GDF, glial-derived factor; HGF, hepatocyte growth factor; ICAM-1, intercellular adhesion molecule-1; IFN, interferon; IGFBP, insulin-like growth factor binding-protein; IL, interleukin; LDL, low-density lipoprotein; MMP, matrix metalloproteinase; PCSK9, proprotein convertase subtilisin/kexin type-9; PD-ECGF, platelet-derived endothelial cell growth factor; RBP, retinol binding protein; TIM-1, T cell Ig and Mucin 1; TNF, tumor necrosis factor; VCAM-1, vascular cell adhesion molecule 1; VEGF, vascular endothelial growth factor; WISP, Wnt-1 inducible signaling pathway.

      CSF-1 Is a Stromal Marker of Patient PDA Aggressiveness and Metastasis

      To link CSF-1 expression with clinical parameters and biological tumor phenotypes in PDA patients, and because CSF-1 mRNA may be expressed by both human tumor cells and stromal CAFs, we investigated 2 public RNA sequencing (RNAseq) databases, in which epithelial and stromal genes are quantified separately
      • Nicolle R.
      • Blum Y.
      • Marisa L.
      • Loncle C.
      • Gayet O.
      • Moutardier V.
      • Turrini O.
      • Giovannini M.
      • Bian B.
      • Bigonnet M.
      • Rubis M.
      • Elarouci N.
      • Armenoult L.
      • Ayadi M.
      • Duconseil P.
      • Gasmi M.
      • Ouaissi M.
      • Maignan A.
      • Lomberk G.
      • Boher J.M.
      • Ewald J.
      • Bories E.
      • Garnier J.
      • Goncalves A.
      • Poizat F.
      • Raoul J.L.
      • Secq V.
      • Garcia S.
      • Grandval P.
      • Barraud-Blanc M.
      • Norguet E.
      • Gilabert M.
      • Delpero J.R.
      • Roques J.
      • Calvo E.
      • Guillaumond F.
      • Vasseur S.
      • Urrutia R.
      • de Reynies A.
      • Dusetti N.
      • Iovanna J.
      Pancreatic adenocarcinoma therapeutic targets revealed by tumor-stroma cross-talk analyses in patient-derived xenografts.
      ,
      • Maurer C.
      • Holmstrom S.R.
      • He J.
      • Laise P.
      • Su T.
      • Ahmed A.
      • Hibshoosh H.
      • Chabot J.A.
      • Oberstein P.E.
      • Sepulveda A.R.
      • Genkinger J.M.
      • Zhang J.
      • Iuga A.C.
      • Bansal M.
      • Califano A.
      • Olive K.P.
      Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.
      : first, the Maurer et al
      • Maurer C.
      • Holmstrom S.R.
      • He J.
      • Laise P.
      • Su T.
      • Ahmed A.
      • Hibshoosh H.
      • Chabot J.A.
      • Oberstein P.E.
      • Sepulveda A.R.
      • Genkinger J.M.
      • Zhang J.
      • Iuga A.C.
      • Bansal M.
      • Califano A.
      • Olive K.P.
      Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.
      database, in which RNAseq were run on patient PDA microdissected-stromal and epithelial lesions (n = 65 patients) (Figure 8A–G); and, second, the patient-derived xenograft RNAseq (PaCaOmics patient-derived xenografts [PDX], n = 30), in which human and mouse gene sequences, originating from the tumor’s epithelial or stromal compartment, respectively, are distinguishable
      • Nicolle R.
      • Blum Y.
      • Marisa L.
      • Loncle C.
      • Gayet O.
      • Moutardier V.
      • Turrini O.
      • Giovannini M.
      • Bian B.
      • Bigonnet M.
      • Rubis M.
      • Elarouci N.
      • Armenoult L.
      • Ayadi M.
      • Duconseil P.
      • Gasmi M.
      • Ouaissi M.
      • Maignan A.
      • Lomberk G.
      • Boher J.M.
      • Ewald J.
      • Bories E.
      • Garnier J.
      • Goncalves A.
      • Poizat F.
      • Raoul J.L.
      • Secq V.
      • Garcia S.
      • Grandval P.
      • Barraud-Blanc M.
      • Norguet E.
      • Gilabert M.
      • Delpero J.R.
      • Roques J.
      • Calvo E.
      • Guillaumond F.
      • Vasseur S.
      • Urrutia R.
      • de Reynies A.
      • Dusetti N.
      • Iovanna J.
      Pancreatic adenocarcinoma therapeutic targets revealed by tumor-stroma cross-talk analyses in patient-derived xenografts.
      (Figure 8H–L). In both databases, we found CSF-1 mRNA to be significantly more abundant in the stromal than in the epithelial compartment (Figure 8A and H). Moreover, high levels of stromal CSF-1 mRNA correlated significantly with high American Joint Committee on Cancer tumor staging (patient cohort) (Table 5), or with clinical parameters of disease progression, that is, nonresectability status (PDX cohort) (Figure 8I), which is not the case for epithelial CSF-1 mRNA (Table 5, Figure 8J). Molecularly, high stromal CSF-1 mRNA expression correlated positively with signatures of aggressive “stroma-activated” (Figure 8B) and “epithelial basal-like” tumors (Figure 8C and K), and negatively with more-differentiated “epithelial classical-like” signatures (Figure 8D).
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      • Nicolle R.
      • Blum Y.
      • Marisa L.
      • Loncle C.
      • Gayet O.
      • Moutardier V.
      • Turrini O.
      • Giovannini M.
      • Bian B.
      • Bigonnet M.
      • Rubis M.
      • Elarouci N.
      • Armenoult L.
      • Ayadi M.
      • Duconseil P.
      • Gasmi M.
      • Ouaissi M.
      • Maignan A.
      • Lomberk G.
      • Boher J.M.
      • Ewald J.
      • Bories E.
      • Garnier J.
      • Goncalves A.
      • Poizat F.
      • Raoul J.L.
      • Secq V.
      • Garcia S.
      • Grandval P.
      • Barraud-Blanc M.
      • Norguet E.
      • Gilabert M.
      • Delpero J.R.
      • Roques J.
      • Calvo E.
      • Guillaumond F.
      • Vasseur S.
      • Urrutia R.
      • de Reynies A.
      • Dusetti N.
      • Iovanna J.
      Pancreatic adenocarcinoma therapeutic targets revealed by tumor-stroma cross-talk analyses in patient-derived xenografts.
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      High epithelial CSF-1 mRNA expression also was associated significantly with stroma-activated signatures (Figure 8E), but not consistently with signatures of the tumoral epithelium (basal, classic) because the link was observed in PDX (Figure 8L), but not in microdissected, lesions (Figure 8F and G). Such correlative analyses then were validated using a third patient cohort (PDA resected tissues from n = 38 patients) in which a CSF-1 protein immunohistochemistry score was quantified in both the tumor epithelial and stromal compartments (Figure 8M–Y). CSF-1 protein was expressed in both the epithelial and stromal compartments, the latter also was αSMA positive (Figure 8M). Clinically, patients with a high metastatic lymph node ratio (LNR) presented with significantly higher stromal, but not epithelial, CSF-1 scores (Figure 8N). Accordingly, patients with high stromal CSF-1 scores tended to have a shorter life expectancy (P = .11) (Figure 8X), which was not the case for high epithelial CSF-1 patients (Figure 8Y). Pathologically, tumors classified with a high activated stroma index
      • Erkan M.
      • Michalski C.W.
      • Rieder S.
      • Reiser-Erkan C.
      • Abiatari I.
      • Kolb A.
      • Giese N.A.
      • Esposito I.
      • Friess H.
      • Kleeff J.
      The activated stroma index is a novel and independent prognostic marker in pancreatic ductal adenocarcinoma.
      or CD163 (TAM marker) scores also presented with significantly increased stromal, but not epithelial, CSF-1 scores (Figure 8O and P). Conversely, CD8 scores were not linked to either stromal or epithelial CSF-1 scores (Figure 8Q). Molecularly, high stromal or epithelial CSF-1 scores correlated positively with stromal RNAseq signatures of activated stroma or of activated/inflamed stroma, respectively (Figure 8R and S), whereas high stromal CSF-1 scores only correlated negatively with RNAseq signatures of inactivated/structured stroma (Figure 8T) and of epithelial classic-like tumors (Figure 8V). No correlation was found between stromal or epithelial CSF-1 scores with RNAseq signatures of immune stroma (Figure 8U) or of epithelial basal-like tumor (Figure 8W). Altogether, these results show that a high stromal CSF-1 score correlated consistently with stromal activities recognized as being of poor prognosis for PDA patients,
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      ,
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      alongside increased tumor cell aggressiveness (less-differentiated phenotype), which, however, was not the case for the epithelial CSF-1 score.
      Figure thumbnail gr8
      Figure 8Stromal CSF-1 is a factor of poor prognosis in human PDA. (A–G) Analyses of stromal and of tumor epithelial CSF-1 mRNA expression in correlation with functional molecular signatures of PDA stroma and tumor cells, in the Maurer et al
      • Maurer C.
      • Holmstrom S.R.
      • He J.
      • Laise P.
      • Su T.
      • Ahmed A.
      • Hibshoosh H.
      • Chabot J.A.
      • Oberstein P.E.
      • Sepulveda A.R.
      • Genkinger J.M.
      • Zhang J.
      • Iuga A.C.
      • Bansal M.
      • Califano A.
      • Olive K.P.
      Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.
      data set (RNAseq analyses of laser-microdissected PDA lesions [n = 65 tumors] of the tumor epithelium [tumor Epith.] and of the stroma). (A) Differential expression of CSF-1 mRNA in laser-microdissected PDA lesions of the stroma or of the tumor epithelium (tumor Epith.) (n = 65 tumors) from Maurer et al.
      • Maurer C.
      • Holmstrom S.R.
      • He J.
      • Laise P.
      • Su T.
      • Ahmed A.
      • Hibshoosh H.
      • Chabot J.A.
      • Oberstein P.E.
      • Sepulveda A.R.
      • Genkinger J.M.
      • Zhang J.
      • Iuga A.C.
      • Bansal M.
      • Califano A.
      • Olive K.P.
      Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.
      The unpaired t test with Welch correction was used to generate P values. (B and E) GSEA for activated stromal signature, as defined by Moffitt et al,
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      or for (C and F) epithelial cancer basal-like signature, or for (D and G) epithelial cancer classic-like signature, in (B–D) high vs low stromal or (E–G) tumor epithelial CSF-1 mRNA-expressing lesions from Maurer et al.
      • Maurer C.
      • Holmstrom S.R.
      • He J.
      • Laise P.
      • Su T.
      • Ahmed A.
      • Hibshoosh H.
      • Chabot J.A.
      • Oberstein P.E.
      • Sepulveda A.R.
      • Genkinger J.M.
      • Zhang J.
      • Iuga A.C.
      • Bansal M.
      • Califano A.
      • Olive K.P.
      Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.
      (H–L) Analyses of stromal and tumor epithelial CSF-1 mRNA expression in correlation with functional molecular signatures of PDA stroma and tumor cells, in the Nicolle et al data set (PaCaOmics, n = 30 PDX).
      • Nicolle R.
      • Blum Y.
      • Marisa L.
      • Loncle C.
      • Gayet O.
      • Moutardier V.
      • Turrini O.
      • Giovannini M.
      • Bian B.
      • Bigonnet M.
      • Rubis M.
      • Elarouci N.
      • Armenoult L.
      • Ayadi M.
      • Duconseil P.
      • Gasmi M.
      • Ouaissi M.
      • Maignan A.
      • Lomberk G.
      • Boher J.M.
      • Ewald J.
      • Bories E.
      • Garnier J.
      • Goncalves A.
      • Poizat F.
      • Raoul J.L.
      • Secq V.
      • Garcia S.
      • Grandval P.
      • Barraud-Blanc M.
      • Norguet E.
      • Gilabert M.
      • Delpero J.R.
      • Roques J.
      • Calvo E.
      • Guillaumond F.
      • Vasseur S.
      • Urrutia R.
      • de Reynies A.
      • Dusetti N.
      • Iovanna J.
      Pancreatic adenocarcinoma therapeutic targets revealed by tumor-stroma cross-talk analyses in patient-derived xenografts.
      (H) Differential expression of CSF-1 mRNA in stromal (of murine origin) or tumor epithelial (of human origin) cells. The unpaired t test with Welch correction was used to generate P values. (I and J) Correlation between (I) stromal or (J) tumor epithelial level of CSF-1 mRNA with resectability of patients. The Mann–Whitney test was used to generate P values. (K and L) GSEA for pancreatic cancer cell basal signature in high vs low (K) stromal or (L) tumor epithelial CSF-1 mRNA PDX. (M–Y) Analyses of stromal and of tumor epithelial CSF-1 protein expression, in correlation with clinical data of patients, with pathologic data of PDA tumors, and with functional molecular signatures of PDA stroma and tumor cells (RNAseq analyses), in a personal PDA cohort (n = 38 primary tumors). (M) Representative images of CSF-1 and αSMA expression analyzed by immunohistochemistry on formalin-fixed, paraffin-embedded tissue slides of 2 PDA patient primary tumors (PDA1 and PDA2). (N–W) Quantification using Definiens Tissue Studio of CSF-1 immunohistochemistry (IHC) scores in the stromal (left panels) or in the tumor epithelial (right panels) compartment, and (N) plotted in correlation with a high vs low (based on the median) positive lymph node ratio (LNR), (O) with pathologic markers of the tumors quantified by IHC, that is, activated stroma index (ASI), (P) CD163-positive cells, or (Q) CD8-positive cells. (R–W) RNAseq analyses of the n = 38 PDA tumors generated transcriptomic signature index, as defined by
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      , of the (R) activated stroma index, (S) activated/inflamed stroma index, (T) inactivated/structured stroma index, and (U) immune stroma index, and of the tumor epithelium, (V) classic-like index or (W) basal-like index, which were compared in CSF-1high vs CSF-1low (based on the median) IHC scores quantified in the stroma (left panel) or in the tumor epithelium (right panel). The unpaired t test was used to generate P values. (X and Y) Survival analysis of patients presenting a (X) high vs low stromal or (Y) tumor epithelial CSF-1 immunohistochemistry score. Kaplan–Meier survival data were analyzed using a log-rank test. ∗P < .05, ∗∗P < .01, and ∗∗∗P < .001
      Table 5Links Between Stromal or Tumor Epithelial High Vs Low CSF-1 mRNA Quantified in Microdissected Lesions From the Maurer et al
      • Maurer C.
      • Holmstrom S.R.
      • He J.
      • Laise P.
      • Su T.
      • Ahmed A.
      • Hibshoosh H.
      • Chabot J.A.
      • Oberstein P.E.
      • Sepulveda A.R.
      • Genkinger J.M.
      • Zhang J.
      • Iuga A.C.
      • Bansal M.
      • Califano A.
      • Olive K.P.
      Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.
      Patient Cohort (n = 65), With Clinical Features of Patient Disease
      StromaTumoral
      CSF-1 highCSF-1 lowPCSF-1 highCSF-1 lowP
      Age, mean, y (minimum–maximum)68.4 (48–86)69.6 (50–85).614Age, mean, y (minimum–maximum)67.4 (48–86)70.6 (48–86).047
      AJCC stage.0358AJCC stage.2664
       2A512 2A107
       2B2817 2B2025
       302 310
       401 402
      Surgical margins.8281Surgical margins.2812
       Negative2524 Negative2128
       Positive88 Positive106
      Race.7332Race.4392
       Asian01 Asian10
       Black21 Black21
       Hispanic Latino11 Hispanic Latino02
       Other11 Other20
       White2527 White2329
       White Latino11 White Latino11
       White non-Hispanic10 White non-Hispanic10
       Unknown20 Unknown20
      Sex.1701Sex.7221
       Female1912 Female1615
       Male1420 Male1519
      Location.2935Location.2249
       Body03 Body03
       Body tail10 Body tail01
       Diffuse01 Diffuse01
       Head2724 Head2625
       Head body10 Head body01
       Neck01 Neck01
       Tail Tail52
      Tumor grade.5944Tumor grade.0819
       Moderate1812 Moderate1218
       Moderate to poor88 Moderate to poor106
       Poor46 Poor46
       Well23 Well14
       Well to moderate13 Well to moderate40
      Histology.9876Histology.9629
       Ductal Adenocarcinoma3331 Ductal adenocarcinoma3034
       IPMN carcinoma01 IPMN carcinoma10
      Solid pattern.6973Solid pattern.0428
       Yes3029 Yes3128
       No33 No06
      Mucinous features.9782Mucinous features.2057
       Yes3230 Yes2834
       No12 No30
      Clear cell features.6487Clear cell features.4867
       Yes566 Yes2831
       No30 No33
      Micropapillary growth.9507Micropapillary growth.9144
       Yes546 Yes2832
       No50 No32
      Features of possible concomitant IPMN.8399Features of possible concomitant IPMN.3521
       Yes526 Yes2632
       No70 No52
      Stroma subtype.0769Tumoral subtype.6025
       ECM-rich1216 Basal-like913
       Immune-rich178 Classic2221
       NA48
      NOTE. Clinical variables were compared in CSF-1 high vs CSF-1 low groups (comprising tumors with higher or lower CSF-1 mRNA expression than the median, respectively), both in the stroma and in the tumor epithelial compartments, using the unpaired t test or the chi-squared test for continuous or categoric variables, respectively. Underline indicates P < .1. Boldface indicates P < .05.
      AJCC, American Joint Committee on Cancer; IPMN, Intraductal Papillary Mucinous Neoplasm.

      Discussion

      CAFs are master players in the secretion of proteins regulating the tumor microenvironment. Through secretome MS analyses on media conditioned by 9 primary CAF cultures, here we identified CAF-secreted proteins, which are under the negative control of SOM230. Among them, 47 were found commonly in stroma-activated signatures published for human PDA.
      • Moffitt R.A.
      • Marayati R.
      • Flate E.L.
      • Volmar K.E.
      • Loeza S.G.
      • Hoadley K.A.
      • Rashid N.U.
      • Williams L.A.
      • Eaton S.C.
      • Chung A.H.
      • Smyla J.K.
      • Anderson J.M.
      • Kim H.J.
      • Bentrem D.J.
      • Talamonti M.S.
      • Iacobuzio-Donahue C.A.
      • Hollingsworth M.A.
      • Yeh J.J.
      Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma.
      ,
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      Such concurrent inhibition by SOM230 of several CAF protumoral signals was consistent with the robust antimetastatic effect that we obtained in 2 different immunocompetent mouse PDA models, and most certainly provided a therapeutic advantage in comparison with specific pharmacologic inhibitors or blocking antibodies, which are directed against 1 specific factor or receptor. This is particularly essential in PDA, in which many single-target drug therapies thus far have failed, even when combined with chemotherapies (eg, hedgehog pathway inhibitor,
      • Catenacci D.V.
      • Junttila M.R.
      • Karrison T.
      • Bahary N.
      • Horiba M.N.
      • Nattam S.R.
      • Marsh R.
      • Wallace J.
      • Kozloff M.
      • Rajdev L.
      • Cohen D.
      • Wade J.
      • Sleckman B.
      • Lenz H.J.
      • Stiff P.
      • Kumar P.
      • Xu P.
      • Henderson L.
      • Takebe N.
      • Salgia R.
      • Wang X.
      • Stadler W.M.
      • de Sauvage F.J.
      • Kindler H.L.
      Randomized phase Ib/II study of gemcitabine plus placebo or vismodegib, a hedgehog pathway inhibitor, in patients with metastatic pancreatic cancer.
      or pegvorhyaluronidase alfa [PEGPH20]
      • Hakim N.
      • Patel R.
      • Devoe C.
      • Saif M.W.
      Why HALO 301 failed and implications for treatment of pancreatic cancer.
      ). A combination of several drugs seems necessary to reach efficacy in PDA, at the cost of safety and adverse effects for patients. SOM230 represents a safe drug (Food and Drug Administration–approved for neuroendocrine Cushing tumors and safely tested in a phase-I PDA trial in combination with gemcitabine
      • Suleiman Y.
      • Mahipal A.
      • Shibata D.
      • Siegel E.M.
      • Jump H.
      • Fulp W.J.
      • Springett G.M.
      • Kim R.
      Phase I study of combination of pasireotide LAR + gemcitabine in locally advanced or metastatic pancreatic cancer.
      ), with a pharmacologic inhibitory action on sst1-expressing CAFs, abrogating CAF cross-talk with tumor and other stromal cells.
      Why SOM230 alone is not as effective at inhibiting metastasis in KPC mice as when it is combined with gemcitabine is intriguing. Gemcitabine was reported to alter the pancreatic immune, fibrotic, and vascular stroma,
      • Principe D.R.
      • Narbutis M.
      • Kumar S.
      • Park A.
      • Viswakarma N.
      • Dorman M.J.
      • Kamath S.D.
      • Grippo P.J.
      • Fishel M.L.
      • Hwang R.F.
      • Thummuri D.
      • Underwood P.W.
      • Munshi H.G.
      • Trevino J.G.
      • Rana A.
      Long-term gemcitabine treatment reshapes the pancreatic tumor microenvironment and sensitizes murine carcinoma to combination immunotherapy.
      ,
      • Miller B.W.
      • Morton J.P.
      • Pinese M.
      • Saturno G.
      • Jamieson N.B.
      • McGhee E.
      • Timpson P.
      • Leach J.
      • McGarry L.
      • Shanks E.
      • Bailey P.
      • Chang D.
      • Oien K.
      • Karim S.
      • Au A.
      • Steele C.
      • Carter C.R.
      • McKay C.
      • Anderson K.
      • Evans T.R.
      • Marais R.
      • Springer C.
      • Biankin A.
      • Erler J.T.
      • Sansom O.J.
      Targeting the LOX/hypoxia axis reverses many of the features that make pancreatic cancer deadly: inhibition of LOX abrogates metastasis and enhances drug efficacy.
      ,
      • Takeuchi S.
      • Baghdadi M.
      • Tsuchikawa T.
      • Wada H.
      • Nakamura T.
      • Abe H.
      • Nakanishi S.
      • Usui Y.
      • Higuchi K.
      • Takahashi M.
      • Inoko K.
      • Sato S.
      • Takano H.
      • Shichinohe T.
      • Seino K.
      • Hirano S.
      Chemotherapy-derived inflammatory responses accelerate the formation of immunosuppressive myeloid cells in the tissue microenvironment of human pancreatic cancer.
      de novo triggering a metastatic microenvironment.
      • Karagiannis G.S.
      • Condeelis J.S.
      • Oktay M.H.
      Chemotherapy-induced metastasis: molecular mechanisms, clinical manifestations, therapeutic interventions.
      ,
      • Pothula S.P.
      • Xu Z.
      • Goldstein D.
      • Biankin A.V.
      • Pirola R.C.
      • Wilson J.S.
      • Apte M.V.
      Hepatocyte growth factor inhibition: a novel therapeutic approach in pancreatic cancer.
      SOM230 did not improve gemcitabine-induced cytotoxicity in tumor cells, but normalized the gemcitabine-remodeled stroma, reducing stellate cell activity, tumor-associated macrophage presence, ECM deposits, and angiogenesis.
      We focused on the CSF-1 chemokine, which was down-regulated by SOM230 in CAF secretomes and in PDA harboring mouse plasma. CSF-1 is involved in intratumor recruitment of monocytes, and in their polarization into macrophages, endowed with pro-angiogenic and ECM remodeling features that favor tumor cell metastasis.
      • DeNardo D.G.
      • Ruffell B.
      Macrophages as regulators of tumour immunity and immunotherapy.
      ,
      • Bonelli S.
      • Geeraerts X.
      • Bolli E.
      • Keirsse J.
      • Kiss M.
      • Pombo Antunes A.R.
      • Van Damme H.
      • De Vlaminck K.
      • Movahedi K.
      • Laoui D.
      • Raes G.
      • Van Ginderachter J.A.
      Beyond the M-CSF receptor - novel therapeutic targets in tumor-associated macrophages.
      In PDA patients, high serum CSF-1 levels were correlated with advanced tumor stages.
      • Mroczko B.
      • Szmitkowski M.
      • Wereszczynska-Siemiatkowska U.
      • Jurkowska G.
      Hematopoietic cytokines in the sera of patients with pancreatic cancer.
      Accordingly, we observed that the plasma CSF-1 level correlated with liver metastatic load in KPC mice. SOM230 treatment decreased intratumor and plasma CSF-1 levels, consistent with fewer intratumor macrophages. In vitro, CAFs were reported to cross-talk with macrophages pushing toward the M2 phenotype through CAF-derived CSF-1.
      • Zhang A.
      • Qian Y.
      • Ye Z.
      • Chen H.
      • Xie H.
      • Zhou L.
      • Shen Y.
      • Zheng S.
      Cancer-associated fibroblasts promote M2 polarization of macrophages in pancreatic ductal adenocarcinoma.
      ,
      • Kuen J.
      • Darowski D.
      • Kluge T.
      • Majety M.
      Pancreatic cancer cell/fibroblast co-culture induces M2 like macrophages that influence therapeutic response in a 3D model.
      We showed that the SOM230 antimetastatic effect relied on CAF-expressed sst1, and on the drug inhibitory effect of CAF-secreted CSF-1.
      In preclinical studies, CSF-1 receptor (CSF-1-R) blockade using CSF-1-R inhibitors or blocking antibodies resulted in a shift from mostly immunosuppressive to improved antigen presentation capacities of tumor-associated macrophage subsets, with a therapeutic benefit for different solid tumors including PDA, when associated with chemotherapy or radiotherapy.
      • Bonelli S.
      • Geeraerts X.
      • Bolli E.
      • Keirsse J.
      • Kiss M.
      • Pombo Antunes A.R.
      • Van Damme H.
      • De Vlaminck K.
      • Movahedi K.
      • Laoui D.
      • Raes G.
      • Van Ginderachter J.A.
      Beyond the M-CSF receptor - novel therapeutic targets in tumor-associated macrophages.
      In PDA, the CSF-1-R blockade decreased tumor growth through increased intratumor cytotoxic CD8 T-cell recruitment,
      • Mitchem J.B.
      • Brennan D.J.
      • Knolhoff B.L.
      • Belt B.A.
      • Zhu Y.
      • Sanford D.E.
      • Belaygorod L.
      • Carpenter D.
      • Collins L.
      • Piwnica-Worms D.
      • Hewitt S.
      • Udupi G.M.
      • Gallagher W.M.
      • Wegner C.
      • West B.L.
      • Wang-Gillam A.
      • Goedegebuure P.
      • Linehan D.C.
      • DeNardo D.G.
      Targeting tumor-infiltrating macrophages decreases tumor-initiating cells, relieves immunosuppression, and improves chemotherapeutic responses.
      and synergized with checkpoint-based immunotherapies.
      • Zhu Y.
      • Knolhoff B.L.
      • Meyer M.A.
      • Nywening T.M.
      • West B.L.
      • Luo J.
      • Wang-Gillam A.
      • Goedegebuure S.P.
      • Linehan D.C.
      • DeNardo D.G.
      CSF1/CSF1R blockade reprograms tumor-infiltrating macrophages and improves response to T-cell checkpoint immunotherapy in pancreatic cancer models.
      SOM230 alone or in combination with gemcitabine did not increase intratumor CD8 T-cell recruitment in 2 PDA mouse models, even though it decreased plasma and intratumor CSF-1, and was antimetastatic. CSF-1-R blockade recently was shown to trigger transcriptomic reprogramming of PDA tumor cells to a more differentiated and less-aggressive PDA subtype,
      • Candido J.B.
      • Morton J.P.
      • Bailey P.
      • Campbell A.D.
      • Karim S.A.
      • Jamieson T.
      • Lapienyte L.
      • Gopinathan A.
      • Clark W.
      • McGhee E.J.
      • Wang J.
      • Escorcio-Correia M.
      • Zollinger R.
      • Roshani R.
      • Drew L.
      • Rishi L.
      • Arkell R.
      • Evans T.R.J.
      • Nixon C.
      • Jodrell D.I.
      • Wilkinson R.W.
      • Biankin A.V.
      • Barry S.T.
      • Balkwill F.R.
      • Sansom O.J.
      CSF1R(+) macrophages sustain pancreatic tumor growth through T cell suppression and maintenance of key gene programs that define the squamous subtype.
      stressing the critical role of CSF-1-R–expressing macrophages in driving PDA tumor cell plasticity, in addition to their role in blocking T-cell responses. This is consistent with our observation that CSF-1 mRNA or protein expression, when quantified specifically in the stroma, correlates with markers of aggressiveness, that is, clinical markers (tumor stage, LNR), pathologic markers (activated stroma index, CD163-positive macrophage presence), and molecular markers (activated status of the stroma, increased basal-like and/or decreased classic-like tumor cell phenotype). However, we could not correlate epithelial CSF-1 mRNA or protein expression with an inactivated status of the stroma as it was recently reported in pure (stroma-poor) basal-like tumors.
      • Steins A.
      • van Mackelenbergh M.G.
      • van der Zalm A.P.
      • Klaassen R.
      • Serrels B.
      • Goris S.G.
      • Kocher H.M.
      • Waasdorp C.
      • de Jong J.H.
      • Tekin C.
      • Besselink M.G.
      • Busch O.R.
      • van de Vijver M.J.
      • Verheij J.
      • Dijk F.
      • van Tienhoven G.
      • Wilmink J.W.
      • Medema J.P.
      • van Laarhoven H.W.
      • Bijlsma M.F.
      High-grade mesenchymal pancreatic ductal adenocarcinoma drives stromal deactivation through CSF-1.
      A possible explanation is that our immunohistochemistry PDA cohort did not include rare pure basal-like tumors. Indeed, it comprised 29% of basal-like tumors and 71% of classic-like tumors, which harbor either an activated stroma (19% and 17%, respectively) or a desmoplastic stroma (10% and 32%, respectively), or poor stroma content for 22% of pure classic tumors, as previously described.
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      We observed that epithelial CSF-1 expression correlated with the presence of CD163-positive macrophages and with a molecular “activated/inflamed“ stroma status recognized to be of bad prognosis in classic tumors.
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      PDA stroma seemed to be the principal source of CSF-1, at least when quantified at the mRNA level in 2 independent PDA cohorts, which was consistent with a recently described CSF-1–expressing immunomodulatory CAF subset identified in melanomas.
      • Davidson S.
      • Efremova M.
      • Riedel A.
      • Mahata B.
      • Pramanik J.
      • Huuhtanen J.
      • Kar G.
      • Vento-Tormo R.
      • Hagai T.
      • Chen X.
      • Haniffa M.A.
      • Shields J.D.
      • Teichmann S.A.
      Single-cell RNA sequencing reveals a dynamic stromal niche that supports tumor growth.
      CSF-1 protein quantification (by immunohistochemistry) from a third PDA cohort indicated a higher epithelial rather than stromal source, although this may have been biased by differences in antibody recognition of the membranous (uncleaved) and soluble (cleaved) CSF-1 forms, which could be distributed differently in the epithelial and stromal compartments (eg, we observed a membranous expression of CSF-1 in KPC liver metastatic tumor cells) (Figure 7M). How and where the membranous CSF-1 protein is cleaved, releasing the soluble chemoattractant factor, and whether membranous and soluble CSF-1 have similar functions in tumors, are as yet unresolved but important issues to understand.
      Altogether, our results show that antimetastatic SOM230 pharmacotherapy should benefit PDA patients enrolled in chemotherapeutic protocols, the effect of SOM230 could be explained mechanistically by a broad inhibitory action on CAF cross-talk with tumor and nontumor cells, including macrophages through CSF-1.

      Methods

      Cell Lines and Primary CAF Cultures

      KPC cells were derived from PDA tumor tissue obtained from LSL-KrasG12D/+; LSL-Trp53R172H/+; p48-Cre+/- mice (C57BL/6 background, a generous gift from Professor D. Saur, Technische University of Munich). PSCs were isolated from mouse pancreata, either WT or KOsst1 (a generous gift from Dr C. Viollet, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris)
      • Videau C.
      • Hochgeschwender U.
      • Kreienkamp H.J.
      • Brennan M.B.
      • Viollet C.
      • Richter D.
      • Epelbaum J.
      Characterisation of [125I]-Tyr0DTrp8-somatostatin binding in sst1- to sst4- and SRIF-gene-invalidated mouse brain.
      (C57BL/6J background), as described.
      • Vonlaufen A.
      • Phillips P.A.
      • Yang L.
      • Xu Z.
      • Fiala-Beer E.
      • Zhang X.
      • Pirola R.C.
      • Wilson J.S.
      • Apte M.V.
      Isolation of quiescent human pancreatic stellate cells: a promising in vitro tool for studies of human pancreatic stellate cell biology.
      In brief, pancreata were minced and digested for 30 minutes at 37°C in a dissociation buffer containing 0.05% collagenase P (Sigma-Aldrich, Lyon, France), 0.1% DNase I (Sigma-Aldrich), and 0.02% Pronase (Sigma-Aldrich) in Grey’s balanced salt solution (GBSS; Sigma-Aldrich). Digested pancreata were filtered through a 100-μm nylon mesh and washed in GBSS with 0.3% bovine serum albumin (BSA). After spinning, the cell pellet was resuspended in 12 mL GBSS with 0.3% BSA and 10 mL 43.75% Nicodenz (Sigma-Aldrich). A total of 11 mL cell suspension was layered below 4.5 mL of GBSS with 0.3% BSA, and the gradient was centrifuged for 20 minutes at 2600 rpm (with break switched off). The cells in the fuzzy band just above the interface between the Nicodenz and GBSS were harvested, washed in phosphate-buffered saline (PBS), and plated. PSCs were transduced with a lentivector expressing a full-length human CSF-1 (a gift from M. Roussel and C. Sherr, plasmid 86797; Addgene, Watertown, MA).
      • Roussel M.F.
      • Dull T.J.
      • Rettenmier C.W.
      • Ralph P.
      • Ullrich A.
      • Sherr C.J.
      Transforming potential of the c-fms proto-oncogene (CSF-1 receptor).
      Lentivector pLoc CSF1-181 Ires tGFP Blast was obtained by ligating digested polymerase chain reaction (PCR) product of CSF-1 (AA 1-181) with into BamHI/NheI-digested pLoc-Ires tGFP Blast (Dharmacon, Horizon Discovery LTD, Cambridge UK). CAFs were isolated from human pancreatic tumor tissues by outgrowth, using the explant techniques from histologically fibrotic areas of pancreas surgically resected from PDA patients.
      • Duluc C.
      • Moatassim-Billah S.
      • Chalabi-Dchar M.
      • Perraud A.
      • Samain R.
      • Breibach F.
      • Gayral M.
      • Cordelier P.
      • Delisle M.B.
      • Bousquet-Dubouch M.P.
      • Tomasini R.
      • Schmid H.
      • Mathonnet M.
      • Pyronnet S.
      • Martineau Y.
      • Bousquet C.
      Pharmacological targeting of the protein synthesis mTOR/4E-BP1 pathway in cancer-associated fibroblasts abrogates pancreatic tumour chemoresistance.
      Human pancreatic tumor tissues were obtained from the Pathology Department of Limoges Hospital (Limoges, France), from patients undergoing pancreatic resections for pancreatic adenocarcinoma (convention CRB/MAD-CC-2013-002). Small tissue blocks were cut (0.5–1 mm3) using a razor blade and were seeded in 10 cm2 uncoated culture wells in the presence of Dulbecco’s modified Eagle medium–F12 containing 10% fetal calf de-complemented serum. Tissue blocks were cultured at 37°C in a 5% CO2–air humidified atmosphere. Eighteen hours after seeding, culture medium was changed. CAFs grew out from the tissue blocks 1–3 days later. An authorization for collecting and conserving this collection was given by the Comité de Protection des Personnes Sud-Ouest et Outre-Mer II (Déclaration de Conservation et Préparation de Collections DC-2016-2654). This study was approved by the Ethic Committee of the Institution.

      Secretome Liquid Chromatography MS/MS Analysis

      Ten to 15 mL of secretomes from CAFs (from n = 9 tumor patients), treated or not for 48 hours with SOM230 (10-7 mol/L), and from CAF culture immortalized with hTERT (human telomerase reverse transcriptase [CAFhTERT]), were analyzed in biological duplicates by nano-liquid chromatography-MS/MS using an Ultimate3000 system (Dionex, ThermoFisher Scientific) coupled to an Orbitrap Tribrid Fusion mass spectrometer (Thermo Fisher Scientific). To take into account the variabilities arising from secretome biochemical preparation and liquid chromatography MS/MS analyses, normalization across the compared samples was performed by adjusting the medians of the distribution of heavy-labeled protein intensities arising from CAFhTERT (used as an internal standard) for all runs. To do so, a primary CAFhTERT culture was labeled with heavy amino acids (L-arginine and L-lysine) through stable labeling with amino acids in cell culture. Proteins with a fold change of more than 2 and a Student t test P value less than .05 were reported as potentially regulated secreted proteins under SOM230 treatment.

      Animal Models

      Transgenic mice

      KPC, LSL-KrasG12D/+; Ink4afl/fl; Pdx-1-Cre+/-, and KOsst1 mice have been described previously.
      • Hingorani S.R.
      • Wang L.
      • Multani A.S.
      • Combs C.
      • Deramaudt T.B.
      • Hruban R.H.
      • Rustgi A.K.
      • Chang S.
      • Tuveson D.A.
      Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice.
      ,
      • Videau C.
      • Hochgeschwender U.
      • Kreienkamp H.J.
      • Brennan M.B.
      • Viollet C.
      • Richter D.
      • Epelbaum J.
      Characterisation of [125I]-Tyr0DTrp8-somatostatin binding in sst1- to sst4- and SRIF-gene-invalidated mouse brain.
      ,
      • Aguirre A.J.
      • Bardeesy N.
      • Sinha M.
      • Lopez L.
      • Tuveson D.A.
      • Horner J.
      • Redston M.S.
      • DePinho R.A.
      Activated Kras and Ink4a/Arf deficiency cooperate to produce metastatic pancreatic ductal adenocarcinoma.

      KPC model

      Because the kinetic of tumor onset is heterogeneous in the KPC model,
      • Hingorani S.R.
      • Wang L.
      • Multani A.S.
      • Combs C.
      • Deramaudt T.B.
      • Hruban R.H.
      • Rustgi A.K.
      • Chang S.
      • Tuveson D.A.
      Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice.
      mice were enrolled when 30–200 mm3 tumor was detected by weekly ultrasound monitoring (Vevo 2100; Fujifilm VisualSonics Amsterdam NL, or Aixplorer; Supersonic Imagine Aix-en-Provence France), as indicated (Figure 5B). Treatments were started at homogeneous tumor sizes (Figure 5C). Mice were treated subcutaneously with SOM230-LAR (80 mg/kg, once every 28 days) and/or intraperitoneally with gemcitabine (100 mg/kg, twice per week). Mouse ages and tumor volumes at treatment start and death (ethical end points) are reported (Table 3, Figure 5B and C). All mice were killed when primary tumor volume reached 1 cm3, or when mice developed ethical clinical end points (Table 3). Age at death was not statistically different between treatment groups (Table 3), except for untreated mice, which lived for a shorter length of time. Survival events were scored when 1 ethical end point was reached (tumor burden >1000 mm3, or body weight loss >20%, or reaching any clinical end point defined by our institutional guidelines and European animal protection law).

      Orthotopic graft models

      Age-matched 8-week-old female C57BL/6J mice were used (Charles River Laboratories, Ecully France). Syngeneic orthotopic tumors were established by surgical implantation of a 1:3 mix of pancreatic cancer KPC cells (2.104) and PSCs (6.104). Mice were treated subcutaneously with SOM230-long-acting release (LAR) (80 mg/kg, once every 28 days) and/or intraperitoneally with gemcitabine (100 mg/kg, twice per week) or PBS. SOM230-LAR was provided by Novartis. Gemcitabine was obtained from the Institut Universitaire du Cancer de Toulouse pharmacy and diluted in PBS. Treatments started 3 weeks after grafting when mice were randomly placed in one of the treatment groups (untreated, PBS; and SOM230-LAR–treated). Tumor volumes were measured by ultrasound using the 3-dimensional reconstruction tool (Vevo 2100; VisualSonics), or with the following formula tumor area × tumor diameter × (2/3) (Aixplorer; Supersonic Imagine). For metastasis analysis, formalin-fixed paraffin-embedded lungs or livers were cut (5-μm–thick sections), and 5 slides (every 100 μm) were colored (hematoxylin and eosin) and examined for the presence of metastasis foci. Metastasis foci were identified in each organ section, the corresponding area was quantified, and the metastatic load was calculated as the cumulated area of metastases quantified per section and expressed as the percentage of the total organ area per section, using the NanoZoomer Digital Pathology Virtual Slide Viewer (Hamamatsu Photonics, Massy, France). A cut-off value equal to the calculated median of the cumulative metastatic lung or liver area (percentage of the total organ area) and quantified in the control untreated condition was set to discriminate between mice presenting with a low vs a high metastatic load. All experiments were in accordance with institutional guidelines and European animal protection law and approved by the responsible government agency (agreement number APAFIS21117 2019061900061441).

      Colorations and Immunostaining of Mouse Tissues

      Formalin-fixed, paraffin-embedded tumor tissue slides were deparaffinized/rehydrated and stained (H&E or Movat’s pentachrome). For immunostaining, slides subjected to antigen retrieval (10 mmol/L sodium citrate pH 6, or Tris-EDTA pH 8.8 and autoclaved), quenched for peroxidase activity, and blocked using blocking buffer (X0909; Dako, Agilent Technologies, Les Ulis, France). Slides were incubated with the following primary antibodies overnight at 4°C: anti-αSMA (ab7817, 1/200; Abcam, Amsterdam, NL), anti–CSF-1 (ab99178, 1/200; Abcam), anti–lymphocyte antigen 6 complex locus G (RB6-8C5, ab25377, 1/100; Abcam), antimyeloperoxidase (ab188211, 1/500; Abcam), anti–phospho-STAT3 (Tyr705, D3A7, CST9145, 1/200; Cell Signaling Technology, Danvers, MA), anti–Ki-67 (SP6, ab16667, 1/200; Abcam), anti–phospho-γH2AX (Ser139, 20E3, CST9718, 1/500; Signaling Technology), anti-CD8 (D4W2Z, CST98941, 1/400; Signaling Technology), anti-sst1 (a generous gift from Novartis Pharma, now commercialized by Bio-Rad (Marnes la Coquette, France) MCA5924, dilution 1/250). Slides were washed and incubated in ImmPRESS secondary antibody (mouse MP-7402, rabbit MP7401, or rat MP7404; Vector), and binding was visualized with 3,3’-diaminobenzidine substrate kit (SK4105; Vector, Eurobio Scientific, Les Ulis, France) or aminoethyl carbazole substrate chromogen (K3464; Dako), and counterstained with hematoxylin. Sections were imaged using NanoZoomer XR (Hamamatsu) (service provided by Imag’IN core from the Institut Universitaire du Cancer Toulouse). Quantifications were performed using ImageJ (National Institutes of Health, Bethesda, MD) or Qupath software (opensource software for digital pathology image) (5 fields per mouse, at least 5 mice per group, as indicated in the figure legends).
      For immunofluorescence staining, the following antibodies were used: anti–mannose receptor (anti-CD206, ab64693, 1/500; Abcam), anti-cytokeratin-19 (conjugated to Alexa Fluor 647, ab192980, 1/100; Abcam), and anti-αSMA, anti-sst1, and anti–CSF-1 as for immunohistochemistry, and then in 4′,6-diamidino-2-phenylindole (1/1000, D9545; Sigma-Aldrich), plus secondary antibodies goat anti-mouse Alexa Fluor 488 (1/1000, A-11001; Invitrogen, ThermoFisher Scientific) or goat anti-rabbit Alexa Fluor 647 (1/1000, A-21244; Invitrogen). Slides were mounted in fluorescent mounting medium (S3023; Dako), and images were acquired using a Cell Observer Videomicroscope (Zeiss) or a confocal microscope (LSM 780; Carl Zeiss Microscopy, Marly Le Roi, France). Quantification was performed using ImageJ software on multiple tissue sections (5 fields per mouse, at least 5 mice per group, as indicated in the figure legends).

      Blood Vessel Density and Pericyte Coverage

      Tumor sections were co-immunostained by anti-MECA32 for detecting tumor vessels and anti-nueron glial 2 (NG2) antibodies for staining pericytes. Tumor vessels and pericyte coverage analysis were performed as described by Gilles et al.
      • Gilles M.E.
      • Maione F.
      • Cossutta M.
      • Carpentier G.
      • Caruana L.
      • Di Maria S.
      • Houppe C.
      • Destouches D.
      • Shchors K.
      • Prochasson C.
      • Mongelard F.
      • Lamba S.
      • Bardelli A.
      • Bouvet P.
      • Couvelard A.
      • Courty J.
      • Giraudo E.
      • Cascone I.
      Nucleolin targeting impairs the progression of pancreatic cancer and promotes the normalization of tumor vasculature.
      Briefly, tumor blood vessel density and pericyte coverage were plotted as the percentage of the MECA32 staining normalized to nuclei or the percentage of the co-localization between MECA32 and NG2 normalized to nuclei. Immunofluorescence images of tumor sections of PDA were captured by using a FV1000 IX81 laser-scanning confocal microscope (Olympus, Thorlabs, Maisons-Laffitte, France), with a 10× or 40× oil objective. Acquisitions were performed with the same settings on multiple tissue sections (5 fields per mouse, at least 5 mice per group, as indicated in the figure legends) and included negative controls for determination of background staining, which was negligible.

      Flow-Cytometric Analysis

      Single-cell suspensions were prepared (Tumor Dissociation Kit, 130-096-730, Miltenyi Biotec, Paris, France) and incubated with fluorophore-conjugated anti-mouse antibodies (CD45 [30-F11], CD3 [17-A2], CD4 [RM4-5], CD8 [53-6.7], CD11b [M1/70], Ly-6g [1A8]; all from BD Biosciences, Le Pont de Claix, France), CD206 (C068C2) (from BioLegend EU Amsterdam, NL), and F4/80 (BM8; from ThermoFisher Scientific). Data acquisition was performed on the Fortessa LSR (BD Biosciences) and BD FacsDiva software was used for analysis, as published previously.
      • Zaghdoudi S.
      • Decaup E.
      • Belhabib I.
      • Samain R.
      • Cassant-Sourdy S.
      • Rochotte J.
      • Brunel A.
      • Schlaepfer D.
      • Cros J.
      • Neuzillet C.
      • Strehaiano M.
      • Alard A.
      • Tomasini R.
      • Rajeeve V.
      • Perraud A.
      • Mathonnet M.
      • Pearce O.M.
      • Martineau Y.
      • Pyronnet S.
      • Bousquet C.
      • Jean C.
      FAK activity in cancer-associated fibroblasts is a prognostic marker and a druggable key metastatic player in pancreatic cancer.

      Western Blot

      Cell lysis was performed in lysis buffer (20 mmol/L Tris, pH 7.5, 150 mmol/L NaCl, 1 mmol/L EDTA, 1% NP40, 1 mmol/L sodium orthovanadate, 1 mmol/L sodium fluoride, and a cocktail of protease inhibitors; Roche (Basel, Switzerland), and tumors were crushed with the Precellys device (Ozyme, Saint Cyr l'Ecole, France) in lysis buffer. The protein extract concentration was measured using the Protein Assay reagent (Bio-Rad). Equal amounts of proteins were resolved by sodium dodecyl sulfate–polyacrylamide gel electrophoresis and electroblotted onto nitrocellulose membranes. Membranes were blocked (5% powdered milk in Tris-buffered saline with 0.1% Tween 20) followed by incubation with primary antibodies (anti–CSF-1 [ab99178, dilution 1/1000] and anti-sst1 antibody [ab2366, dilution 1/1000] from Abcam; anti-Akt [CST9272, dilution 1/1000] and anti-phospho-Akt [p473-Akt, CST2013, dilution 1/1000] from Cell Signalling Technologies; anti–β-actin [A5441, dilution 1/1000] is from Millipore (Merck, Fontenay-sous-Bois, France); and anti-periostin [sc 67233, dilution 1/200] from Santa Cruz (SCBT, Dallas, TX). Membranes were incubated with horseradish-peroxidase–coupled secondary antibody and treated with Pierce ECL Western Blotting Substrate (ThermoFisher Scientific) before detection with the PXi imaging system (Syngene, Cambridge, UK). SUnSET assay, a nonradioactive equivalent of 35S-Met assay based on puromycin incorporation into nascent polypeptides, was used to monitor the rate of protein synthesis using an antipuromycin antibody (12D10, dilution 1/1000; Merck Millipore).
      • Schmidt E.K.
      • Clavarino G.
      • Ceppi M.
      • Pierre P.
      SUnSET, a nonradioactive method to monitor protein synthesis.

      ELISA and Cytokine Arrays

      CSF-1 detection in plasma was performed using the Mouse Macrophage CSF Quantikine ELISA Kit (MMC00; R&D Systems, Minneapolis, MN) according to the manufacturer’s instructions. Cytokine detection in patient CAF culture supernatant was performed using ELISA kits (macrophage-CSF, DMC00B; connective tissue growth factor, DY9190-05; THSB2 (thrombospondin-2), DTSP20; all from R&D Systems, and biglycan ab245709; Abcam), according to the manufacturer’s instructions. Cytokine assay was performed using the Proteome Profiler Mouse XL Cytokine Array Kit (ARY028; R&D Systems) according to the manufacturer’s instructions. Membrane chemiluminescences were captured with the PXi imaging system (Syngene, Cambridge, UK)). Data acquisition and quantification was performed using Quick Spots Tool software (Western Vision Software, Salt Lake City, UT).

      Quantitative Real-Time PCR

      Total RNA from PSCs and spleen was isolated using TRIzol (ThermoFisher Scientific). Reverse-transcription quantitative PCR reactions were performed using RevertAid H Minus Reverse Transcriptase (ThermoFisher Scientific) and SoFast EvaGreen Supermix (Bio-Rad) according to the manufacturer’s instructions and measured with the StepOne Real-Time PCR Systems (ThermoFisher Scientific). Relative quantitation values were normalized using the comparative Ct (cycle threshold) method. Primers for mouse SSTR1 (somatostatin receptor subtype 1) were as follows: forward: 5’-TGCCCTTTCTGGTCACTTCC-3’, reverse: 5’-AGCGGTCCACACTAAGCACA-3’, and for mouse housekeeping RPS16 (40S ribosomal protein S16) were as follows: forward: 5’-AATGGGCTCATCAAGGTGAACGGA-3’, reverse: 5’-TATCCACACCAGCAAATCGCTCCT-3’.

      Patient Pancreatic Cancer Tissues for Immunohistochemistry and RNAseq Analyses

      Thirty-eight consecutive patients were selected from a retrospective cohort of patients with localized (nonmetastatic) PDA who underwent complete surgical resection between December 2011 and January 2014 at Beaujon University Hospital (Clichy, France; Biobank registration number BB-0033-00078).
      • Neuzillet C.
      • Tijeras-Raballand A.
      • Ragulan C.
      • Cros J.
      • Patil Y.
      • Martinet M.
      • Erkan M.
      • Kleeff J.
      • Wilson J.
      • Apte M.
      • Tosolini M.
      • Wilson A.S.
      • Delvecchio F.R.
      • Bousquet C.
      • Paradis V.
      • Hammel P.
      • Sadanandam A.
      • Kocher H.M.
      Inter- and intra-tumoural heterogeneity in cancer-associated fibroblasts of human pancreatic ductal adenocarcinoma.
      All participants provided their informed consent before taking part. Exclusion criteria were as follows: neoadjuvant chemotherapy and/or radiotherapy, macroscopically incomplete resection (R2), tumor histology other than PDA, and insufficient tumor material available for research. Clinical and pathologic variables were collected retrospectively, including sex, age at diagnosis, tumor site, preoperative assessment of tumor extension, surgical procedure, resection margins (R0, negative; R1, positive), differentiation grade, tumor size, tumor stage, lymph node status (negative, N-; positive, N+), LNR (ie, the ratio of lymph nodes with tumor metastasis to the total lymph nodes analyzed), TNM classification, and the presence of vascular and perineural invasion. The outcome variable was overall survival, defined as the time interval between the day of surgical resection and death (all causes) or date of last follow-up evaluation, at which point data were censored. Survival curves were estimated using the Kaplan–Meier method and compared using the log-rank test. For immunohistochemistry analyses, whole formalin-fixed paraffin-embedded (FFPE) slides were stained with each indicated antibody, after manual selection by a specialist pancreatic pathologist (J.C.) of tumoral areas on scanned slides. For αSMA (M0851; Dako) and pan-cytokeratin (MSK098-05; Zytomed, Berlin, Germany), the Precision image analysis software (Aperio, Leica Biosystems, Nanterre, France) was used for automated biomarker quantification. The activated stroma index was adapted from Erkan et al
      • Erkan M.
      • Michalski C.W.
      • Rieder S.
      • Reiser-Erkan C.
      • Abiatari I.
      • Kolb A.
      • Giese N.A.
      • Esposito I.
      • Friess H.
      • Kleeff J.
      The activated stroma index is a novel and independent prognostic marker in pancreatic ductal adenocarcinoma.
      by considering the following formula: 1 – pan-cytokeratin-stained area, as a surrogate for the collagen deposit area and calculated using the following formula: αSMA-stained surface/(1 – pan-cytokeratin-stained surface). Anti-CD8–stained (M710301; Dako) and anti-CD163–stained (NCL-CD163; Leica) tumor slides were assessed visually by 2 observers (J.C. and C.N.), to score according to the localization (peritumoral or intratumoral) and frequency of respective positive cell aggregates (low score, no intratumoral aggregate with possible low frequency of peritumoral aggregates; high score, low or high frequency of intratumoral aggregates with possible high frequency of peritumoral aggregates). For CSF-1 stain quantification in stromal or tumoral areas, the calculated CSF-1 immunohistochemistry score takes into account the stain intensity and the percentage of the stained cell area. Percentages of cells expressing low, medium, and high CSF-1 stain were quantified using Definiens Tissue Studio (Imag’IN core Institut Universitaire du Cancer, Toulouse, France) in stromal or tumor compartments, as we published previously,
      • Zaghdoudi S.
      • Decaup E.
      • Belhabib I.
      • Samain R.
      • Cassant-Sourdy S.
      • Rochotte J.
      • Brunel A.
      • Schlaepfer D.
      • Cros J.
      • Neuzillet C.
      • Strehaiano M.
      • Alard A.
      • Tomasini R.
      • Rajeeve V.
      • Perraud A.
      • Mathonnet M.
      • Pearce O.M.
      • Martineau Y.
      • Pyronnet S.
      • Bousquet C.
      • Jean C.
      FAK activity in cancer-associated fibroblasts is a prognostic marker and a druggable key metastatic player in pancreatic cancer.
      and a CSF-1 score was calculated as follows: 1 × % low CSF-1 cells + 2 × % medium CSF-1 cells + 3 × % high CSF-1 cells. Associations between the activated stroma index, CD163, or CD8 scores (high vs low, ie, higher than or less than the median, respectively), and CSF-1 immunohistochemistry scores in the stroma or in the tumor were assessed using unpaired Student t tests.
      For RNAseq analyses, FFPE blocks were selected by a specialist pancreatic pathologist (J.C.). The presence of neoplastic cells was confirmed and tumor-enriched zones after examination of H&E–stained slides were macrodissected for nucleic acid extraction. For all samples, RNA was extracted using the Qiagen RNeasy FFPE kit following the manufacturer’s instructions (Qiagen, Hilden, Germanyia). A total of 150 ng RNA was used as starting material for the preparation of RNAseq libraries using the QuantSeq 3’ REV kit (Lexogen, Vienna, Austria). Libraries were sequenced on an Illumina (San Diego, CA) NovaSeq platform aiming for 7Millions read pairs.

      Bioinformatics

      For secretome analysis, GSEA was performed using the fast GSEA implementation (10.18129/B9.bioc.fgsea; Bioconductor, open source software), using the matrix of the measurable proteins identified in CAF conditioned media (n = 9) preranked by the significance of the differential test (untreated vs SOM230-treated condition). Therefore, secretome GSEA results show enrichments, induced by SOM230, among the proteins identified in CAF conditioned media. PDX transcriptome analyses were obtained from the processed data set of the PaCaOmics clinical trial (NCT01692873).
      • Nicolle R.
      • Blum Y.
      • Marisa L.
      • Loncle C.
      • Gayet O.
      • Moutardier V.
      • Turrini O.
      • Giovannini M.
      • Bian B.
      • Bigonnet M.
      • Rubis M.
      • Elarouci N.
      • Armenoult L.
      • Ayadi M.
      • Duconseil P.
      • Gasmi M.
      • Ouaissi M.
      • Maignan A.
      • Lomberk G.
      • Boher J.M.
      • Ewald J.
      • Bories E.
      • Garnier J.
      • Goncalves A.
      • Poizat F.
      • Raoul J.L.
      • Secq V.
      • Garcia S.
      • Grandval P.
      • Barraud-Blanc M.
      • Norguet E.
      • Gilabert M.
      • Delpero J.R.
      • Roques J.
      • Calvo E.
      • Guillaumond F.
      • Vasseur S.
      • Urrutia R.
      • de Reynies A.
      • Dusetti N.
      • Iovanna J.
      Pancreatic adenocarcinoma therapeutic targets revealed by tumor-stroma cross-talk analyses in patient-derived xenografts.
      Laser-microdissected stromal and epithelial compartments of RNAseq analyses from 65 PDA patients were obtained from the gene omnibus database (GSE93326).
      • Maurer C.
      • Holmstrom S.R.
      • He J.
      • Laise P.
      • Su T.
      • Ahmed A.
      • Hibshoosh H.
      • Chabot J.A.
      • Oberstein P.E.
      • Sepulveda A.R.
      • Genkinger J.M.
      • Zhang J.
      • Iuga A.C.
      • Bansal M.
      • Califano A.
      • Olive K.P.
      Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.
      Patient clinical data were available and correlation with stromal and tumoral CSF-1 mRNA expression was assessed. The transcriptomic data set from the Beaujon cohort RNAseq analyses on PDA FFPE tissues (n = 38 patients) was characterized according to the 6 robust transcriptomic components of the tumor and of the stroma, identified by independent component analysis in a published cohort of 309 PDA patients
      • Puleo F.
      • Nicolle R.
      • Blum Y.
      • Cros J.
      • Marisa L.
      • Demetter P.
      • Quertinmont E.
      • Svrcek M.
      • Elarouci N.
      • Iovanna J.
      • Franchimont D.
      • Verset L.
      • Galdon M.G.
      • Deviere J.
      • de Reynies A.
      • Laurent-Puig P.
      • Van Laethem J.L.
      • Bachet J.B.
      • Marechal R.
      Stratification of pancreatic ductal adenocarcinomas based on tumor and microenvironment features.
      (ie, tumoral basal, tumoral classic, stromal activated, stromal inflammatory, stromal structured vascularized, and stromal immune), assigning a weight of each component to each FFPE sample. Associations between CSF-1 immunohistochemistry scores in the stroma or in the tumor (high vs low) and transcriptomic components were assessed using unpaired Student t tests.

      Statistics

      All statistical analyses were performed using GraphPad Prism 6 software (GraphPad Software, Inc, San Diego, CA). The number of animals and replicate in vitro experiments are specified in each figure legend. Results are presented as the means ± SEM. The Kaplan–Meier method was used to estimate survival rates, and significance was determined by the log-rank test. Normal distribution of variables was computed using the D’Agostino–Pearson normality test. Comparison of a continuous variable in 2 groups or more than 2 groups with normal distribution was performed using the parametric test (ie, t test or analysis of variance, respectively), and with a Bonferroni post-test for multiparametric analyses. If the variable was not distributed normally, a nonparametric test (ie, Mann–Whitney or Kruskal–Wallis), was applied for comparison in 2 or more groups, respectively, with a Dunn post-test for multiparametric analyses. The significance of metastasis frequency was determined by the Fisher exact test. All P values were 2-sided, and P < .05 was considered statistically significant.
      All authors had access to the study data and reviewed and approved the final manuscript.

      Acknowledgments

      The authors thank Dr N. Dusetti for providing access to the PaCaOmics database.
      • Nicolle R.
      • Blum Y.
      • Marisa L.
      • Loncle C.
      • Gayet O.
      • Moutardier V.
      • Turrini O.
      • Giovannini M.
      • Bian B.
      • Bigonnet M.
      • Rubis M.
      • Elarouci N.
      • Armenoult L.
      • Ayadi M.
      • Duconseil P.
      • Gasmi M.
      • Ouaissi M.
      • Maignan A.
      • Lomberk G.
      • Boher J.M.
      • Ewald J.
      • Bories E.
      • Garnier J.
      • Goncalves A.
      • Poizat F.
      • Raoul J.L.
      • Secq V.
      • Garcia S.
      • Grandval P.
      • Barraud-Blanc M.
      • Norguet E.
      • Gilabert M.
      • Delpero J.R.
      • Roques J.
      • Calvo E.
      • Guillaumond F.
      • Vasseur S.
      • Urrutia R.
      • de Reynies A.
      • Dusetti N.
      • Iovanna J.
      Pancreatic adenocarcinoma therapeutic targets revealed by tumor-stroma cross-talk analyses in patient-derived xenografts.
      The authors thank Dr V. Sanz-Moreno (Barts Cancer Institute–Queen Mary University of London) for her critical reading of the manuscript.
      The authors thank Laetitia Ligat and Manon Farce (Cancer Research Center of Toulouse, Pôle Technologique) for their help and expertise in microscopy and flow cytometry, respectively. The authors also thank the animal CREFRE facility (Centre Régional d'Exploration Fonctionnelle et de Ressources) for their expertise in ultrasound exploration, and their help in acquiring the Aixplorer, funded by AVIESAN (Alliance Nationale pour les Sciences de la Vie et de la Santé) within the framework of the Cancer Plan.
      English proofreading was performed by Greenland scientific proofreading.

      CRediT Authorship Contributions

      Rémi Samain, PharmD, PhD (Conceptualization: Supporting; Formal analysis: Equal; Investigation: Equal; Methodology: Equal; Writing – original draft: Supporting; Writing – review & editing: Supporting)
      Alexia Brunel, MS (Formal analysis: Supporting; Investigation: Supporting; Methodology: Supporting)
      Thibault Douché, MS (Investigation: Supporting; Methodology: Supporting)
      Marjorie Fanjul, PhD (Methodology: Supporting)
      Julia Rochotte, PhD (Formal analysis: Supporting; Investigation: Supporting; Methodology: Supporting)
      Stéphanie Cassant-Sourdy, Tech (Investigation: Supporting)
      Jérôme Cros, MD, PhD (Investigation: Supporting; Resources: Lead)
      Cindy Neuzillet, MD, PhD (Investigation: Supporting; Methodology: Supporting)
      Jérôme Raffenne, PhD (Investigation: Supporting; Methodology: Supporting)
      Camille Duluc, PhD (Investigation: Supporting; Methodology: Supporting)
      Aurélie Perraud, PhD (Methodology: Supporting)
      Jérémy Nigri, PhD (Methodology: Supporting)
      Véronique Gigoux, PhD (Methodology: Supporting)
      Ivan Bieche, PhD (Methodology: Supporting)
      Mattéo Ponzo, MS (Methodology: Supporting)
      Gilles Carpentier, PhD (Methodology: Supporting)
      Ilaria Cascone, PhD (Investigation: Supporting; Methodology: Supporting)
      Richard Tomasini, PhD (Investigation: Supporting; Methodology: Supporting)
      Herbert A Schmid, PhD (Conceptualization: Supporting; Funding acquisition: Supporting)
      Muriel Mathonnet, MD, PhD (Resources: Supporting)
      Rémy Nicolle, PhD (Conceptualization: Supporting; Investigation: Supporting; Methodology: Supporting; Writing – review & editing: Supporting)
      Marie-Pierre Bousquet, PhD (Conceptualization: Supporting; Investigation: Equal; Methodology: Supporting; Supervision: Supporting; Writing – review & editing: Supporting)
      Yvan Martineau, PhD (Conceptualization: Supporting; Funding acquisition: Supporting; Investigation: Supporting; Methodology: Supporting; Supervision: Supporting; Writing – review & editing: Supporting)
      Stéphane Pyronnet, PhD (Conceptualization: Supporting; Funding acquisition: Equal; Supervision: Supporting; Writing – review & editing: Supporting)
      Christine Jean, PhD (Conceptualization: Supporting; Formal analysis: Supporting; Funding acquisition: Supporting; Investigation: Supporting; Methodology: Supporting; Supervision: Equal; Writing – review & editing: Supporting)
      Corinne Bousquet, VMD, PhD (Conceptualization: Lead; Formal analysis: Lead; Funding acquisition: Lead; Investigation: Supporting; Methodology: Supporting; Project administration: Lead; Supervision: Lead; Validation: Lead; Writing – original draft: Lead)

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