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Abstract
Background Tumor-associated macrophages participate in the complex network of support that favors tumor growth. Among the various strategies that have been developed to target these cells, the blockade of the colony-stimulating factor 1 receptor (CSF-1R) receptor is one of the most promising ones. Here, we characterize the resulting state of human macrophages exposed to a CSF-1R kinase inhibitor.
Methods Using RNA sequencing and metabolomics approach, we characterize the reprogramming of human monocyte-derived macrophages under CSF-1R targeting.
Results We find that CSF-1R receptor inhibition in human macrophages is able to impair cholesterol synthesis, fatty acid metabolism and hypoxia-driven expression of dihydropyrimidine dehydrogenase, an enzyme responsible for the 5-fluorouracil macrophage-mediated chemoresistance. We show that this inhibition of the CSF-1R receptor leads to a downregulation of the expression of sterol regulatory element-binding protein 2, a transcription factor that controls cholesterol and fatty acid synthesis. We also show that the inhibition of extracellular signal-regulated kinase 1/2 phosphorylation resulting from targeting the CSF-1R receptor destabilizes the expression of hypoxic induced factor 2 alpha in hypoxia resulting in the downregulation of dihydropyrimidine dehydrogenase expression restoring the sensitivity to 5-fluorouracil in colorectal cancer.
Conclusions These results reveal the unexpected metabolic rewiring resulting from the CSF-1R receptor targeting of human macrophages and its potential to reverse macrophage-mediated chemoresistance in colorectal tumors.
- Cholesterol
- Chemotherapy
- Colorectal Cancer
- Macrophage
- Tumor microenvironment - TME
Data availability statement
Data are available upon reasonable request. The data generated and analyzed will be made available from the corresponding author upon reasonable request. RNA sequencing data are deposited in the NCBI Gene Expression Omnibus under accession number: GSE263919.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Colony-stimulating factor 1 receptor (CSF-1R) targeting is a promising strategy to modulate the innate immune response in cancer. However, the effect of this targeting on human macrophage phenotype is not fully understood.
WHAT THIS STUDY ADDS
In this study, we report that CSF-1R targeting affects the metabolic state of tumor-associated macrophages notably the cholesterol synthesis pathway, the fatty acid synthesis pathway and the hypoxic induced factor 2a-mediated response involving dihydropyrimidine dehydrogenase expression.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
CSF-1R targeting appears to be a promising strategy to circumvent the macrophage-mediated chemoresistance to 5-fluorouracil in colorectal cancer.
Background
A large body of work has been reported providing compelling evidence that tumor-associated macrophages (TAMs) are involved in tumor growth, treatment resistance and metastasis.1 2 Indeed, TAMs are associated with poor prognosis in the vast majority of solid tumors.3 Consequently, great efforts have been made to target TAMs in order to direct the immune response against the tumor.4 Colony-stimulating factor 1 receptor (CSF-1R) is a receptor with intrinsic tyrosine kinase activity that recognizes CSF-1 (M-CSF, macrophage colony-stimulating factor) and interleukin (IL)-34. The CSF-1/CSF-1R signaling pathway is involved in macrophage survival, proliferation, differentiation and chemotaxis.5 This pivotal role opens the way to use CSF-1R receptor targeting in various pathological contexts and especially in cancer to modulate macrophages.6 CSF-1R receptor targeting has been used in various tumor mouse models with promising results but only modest beneficial effects in humans when used alone.4 Furthermore, the recognition that the type of tumor model used7 and the modification of the cellular environment such as oxygen availability,8 affect the efficiency of the CSF-1R targeting highlights the need for a better understanding of the functional consequences of CSF-1R receptor targeting on human macrophages.
The importance of CSF-1R receptor blockade beyond the induction of apoptosis has been recognized in animal models that advocate the possibility of achieving an antitumor phenotypic reprogramming.9 However, the mechanisms involved in macrophage’s reprogramming by CSF-1R targeting are unclear.
Here, we characterize the functional consequences of CSF-1R receptor inhibitors on human macrophages. We show that CSF-1R receptor inhibition is associated with impaired cholesterol and fatty acid synthesis under the control of the transcription factor sterol regulatory element-binding protein 2 (SREBP2). Furthermore, CSF-1R receptor blockade leads to an inhibition of the phosphorylated state of extracellular signal-regulated kinase 1/2 (ERK1/2) resulting in a decrease in the expression of hypoxic induced factor 2 alpha (HIF-2α), a hypoxic response transcription factor. A consequence of the HIF-2α-dependent hypoxic response is the downregulation of dihydropyrimidine dehydrogenase expression, the limiting rate enzyme of the first step of the pyrimidine catabolic pathway, which is responsible for a hypoxia-driven macrophage-mediated chemoresistance to 5-fluorouracil (5-FU) in colorectal cancer (CRC).10
Methods
Human samples
Human blood samples from healthy de-identified donors were obtained from EFS (French national blood service) as part of an authorized protocol (CODECOH DC-2018–3114). Donors gave signed consent for the use of their blood in this study. Tumoral and non-tumoral tissues were obtained from surgically resected colons at the university hospital of Grenoble Alpes from patients included in the CRC-ORGA2 clinical trial (ClinicalTrial.gov, NCT05038358). Inclusion criteria comprise adult patients suffering from colorectal adenocarcinoma treated by surgery without neoadjuvant chemotherapy (online supplemental table S1).
Supplemental material
Cell culture
THP-1, RKO and HT-29, were purchased from ATCC. THP-1, HT-29 and RKO were maintained in RPMI (Gibco) supplemented with 10% FBS (Gibco) at 37°C. All cells were routinely tested for Mycoplasma contamination using a MycoAlert Detection Kit (Lonza).
Human macrophage differentiation from monocytes
Monocytes were isolated from the leukoreduction system chambers of healthy EFS donors using differential centrifugation (Histopaque 1077, Sigma) to obtain peripheral blood mononuclear cells (PBMCs). CD14+ microbeads (Miltenyi Biotec) were used to select monocytes according to the manufacturer’s instructions. Monocytes were plated in RPMI (Life Technologies) supplemented with 10% SAB (Sigma), 10 mM HEPES (Life Technologies), MEM non-essential amino acids (Life Technologies) and 25 ng/mL M-CSF (Miltenyi Biotec). Differentiation was obtained after 6 days of culture. Hypoxic cultures were performed in a hypoxic chamber authorizing an oxygen partial pressure control (HypoxyLab, Oxford Optronix, UK). Hypoxia experiments were performed at 25 mm Hg of oxygen (~3%). CD3+ T lymphocytes and CD20+ B lymphocytes were sorted from PBMCs using CD3+ and CD20+ microbeads (Miltenyi Biotec) according to the manufacturer’s instructions.
Preparation of tumor-associated macrophages
Tumoral and non-tumoral tissues obtained from the colon of patients with CRC. Tissues were kept and transported in ice in Roswell Park Memorial Institute (RPMI) medium supplemented with non-essential amino acids and 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) as well as antibiotics including penicillin-streptomycin and gentamicin and antifungal amphotericin B. Tissues were minced in pieces of 2–4 mm3 and deposited on cell culture inserts (four pieces by insert). These inserts were deposited in 6-well plates on 2 mL of RPMI+10% human serum for 24 hours. The resulting medium produced by tumoral and non-tumoral tissues was then used to culture human monocyte-derived macrophages for 48 hours to obtain TAMs.
Macrophage conditioned medium
THP1 macrophages were plated (12-well plates) and differentiated at 500,000 cells with 50 nM of phorbol 12-myristate 13-acetate (PMA) for 24 hours. THP1 macrophages were cultured at 3% oxygen and treated with Edicotinib at 3 µM or Dimethyl sulfoxide (DMSO) acting as a vehicle for 48 hours. Then 1 µg/mL of 5-FU was used to generate the 5-FU Edicotinib macrophage conditioned medium (MCM) or 5-FU vehicle MCM for 24 hours. MCM was added for 48 hours to two distinct colon cancer cell lines, RKO and HT-29 cells, which were plated previously at 100,000 cells per well (12-well plates) for 24 hours. Then cancerous cells were collected and counted and the percentage of growth inhibition was assessed for each condition.
RNA sequencing
RNA extraction was performed using the NucleoSpin RNA Kit components (Macherey Nagel) according to the manufacturer’s instructions. RNA sequencing was performed using an Illumina HiSeq 4000 sequencer (Integragen). Gene expression quantification was performed using the STAR software. STAR obtains the number of reads associated with each gene in the GENCODE V.31 annotation (restricted to protein-coding genes, antisense and lincRNAs). Raw counts for each sample were imported into R statistical software. The extracted count matrix was normalized for library size and coding length of genes to compute fragments per kilobase million (FPKM) expression levels. The Bioconductor edgeR package was used to import raw counts into R statistical software. Differential expression analysis was performed using the Bioconductor limma package and the voom transformation. Gene Ontology analysis was performed using the GONet software (https://tools.dice-database.org/GOnet/). Gene list from the differential analysis was ordered by decreasing log2 fold change. Gene Set Enrichment Analysis (GSEA) was performed by clusterProfiler::GSEA function using the fgsea algorithm.
Lipidomics
Human macrophages were metabolically quenched in dry ice—ethanol for 1 min then washed three times in cold phosphate-buffered saline. Then total lipids were extracted in chloroform/methanol/water (1:3:1, v/v/v) containing PC (C13:0/C13:0), 10 nmol and C21:0 (10 nmol) as internal standards for extraction) for 1 hour at 4°C, with periodic sonication. Then polar and apolar metabolites were separated by phase partitioning by adding chloroform and water to give the ratio of chloroform/methanol/water, 2:1:0.8 (v/v/v). For lipid analysis, the organic phase was dried under N2 gas and dissolved in 1-butanol to obtain 1 µL butanol/107 macrophages.
Total lipid analysis—total lipid was then added with 1 nmol pentadecanoic acid (C15:0) as internal standard and derivatized to give fatty acid methyl ester (FAME) using trimethylsulfonium hydroxide (Machenery Nagel) for total glycerolipid content. Resultant FAMEs were then analyzed by gas chromatography-mass spectrometry (GC-MS) as previously described.11 All FAME were identified by comparison of retention time and mass spectra from GC-MS with authentic chemical standards. The concentration of FAMEs was quantified after initial normalization to different internal standards and finally to macrophage number.
Immunoblotting
Cells were lyzed in Radioimmunoprecipitation assay (RIPA) buffer supplemented with protease inhibitors (AEBSF 4 mM, Pepstatin A 1 µM and leupeptin 0.4 mM; Sigma-Aldrich) and HIF-hydroxylase inhibitor (DMOG 1 mM, Sigma Aldrich) for total lysate or direct lysis in Laemmli buffer (2×). Proteins were quantified by BCA assay (Thermo Fischer) and 15 µg of total protein were run on SDS-PAGE gels. Proteins were transferred from SDS-PAGE gels to PVDF membrane (Bio-Rad), blocked with TBS-Tween supplemented with 5% milk, primary antibodies were incubated at 1 µg/mL overnight at 4°C. After washing with TBS, the membrane was incubated with a horseradish peroxidase-conjugated secondary antibody (Jackson ImmunoResearch). The signal was detected by chemoluminescence (Fusion FX imaging system, Vilber) after exposition to Clarity ECL Substrate (Bio-Rad).
Flow cytometry
Flow cytometry data was acquired on an Accuri C6 (BD) flow cytometer. Doublet cells were gated out by comparing forward scatter signal height and area. At least 10,000 events were collected in the analysis gate. Median fluorescence intensity was determined using Accuri C6 software (BD).
DPD activity measurements
These analyses were performed in the Pharmacology Laboratory of Institut Claudius-Regaud (France) using an HPLC system composed of Alliance 2695 and diode array detector 2996 (Waters). Uracil (U), Dihydrouracil (UH2), ammonium sulfate 99%, acetonitrile gradient chromasolv for HPLC and 2-propanol were purchased from Sigma. Ethyl acetate Scharlau was of HPLC grade and purchased from ICS (Lapeyrouse-Fossat, France). Water from Milli-Q Advantage A10 and MultiScreen-HV 96-well plates were used (Merck Millipore). Calibration ranges were 3.125–200 ng/mL for U and 25–500 ng/mL for UH2 and 5-FU (5 µg/mL) was used as an internal standard.
RNA isolation and quantitative PCR analysis for gene expression
Cells were directly lyzed and RNA was extracted using the NucleoSpin RNA Kit components (Macherey Nagel) according to the manufacturer’s instructions. Reverse transcription was performed using the iScript Ready-to-use cDNA supermix components (Bio-Rad). Quantitative PCR (qPCR) was then performed with the iTaq universal SYBR green supermix components (Bio-Rad) on a CFX96 (Bio-Rad). Quantification was performed using the ΔΔCt method using two different housekeeping genes.
Quantification of cholesterol
Macrophages were treated with 10 µM of Edicotinib or simvastatin for 72 hours after which cells and supernatants were retrieved. Supernatants were stored at −80°C. Lipids were extracted from cells using choloroform:isopropanol:NP-40 (7:11:0.1). Organic phase was taken and air-dried at 50°C and stored at −80°C. The amount of cholesterol in cells and supernatants was assessed using the Cholesterol/Cholesteryl Ester Assay Quantification Kit (ab65359, Abcam) according to the manufacturer’s instructions.
Silencing of endothelial PAS domain-containing protein 1 and sterol regulatory element binding transcription factor 2
Fully differentiated macrophages were transfected with siEPAS1 (L-004814-00-0005, Dharmacon) or siSREBF2 (L-009549-00-0005, Dharmacon) at a final concentration of 5 nmol/L using Lipofectamine (RNAiMAX, Life Technologies).
Statistical analysis
Statistics were performed using GraphPad Prism V.7 (GraphPad Software). When two groups were compared, we used a paired or unpaired two-tailed Student’s t-test when appropriate. When more than two groups were compared, we used a one-way analysis of variance analysis with Sidak’s multiple comparison test on paired data when appropriate. The likelihood of data according to a null-hypothesis (p value) is presented in the figures. The number of independent experiments used to generate the data is shown on each figure.
Results
Complete CSF-1R inhibition is associated with a profound phenotypic change without death induction in human macrophages
On ligation of CSF-1, the CSF-1 receptor dimerizes, resulting in multiple site phosphorylation of the intracellular tail of the receptor.5 To investigate the resulting effect of inhibition of the CSF-1R receptor-dependent signaling pathway, we first evaluated the response of tyrosine 723 phosphorylation to increasing doses of Edicotinib, a selective CSF-1R tyrosine kinase inhibitor.12–14 We found that Edicotinib at 10 µM is able to completely inhibit CSF-1R’s phosphorylation (figure 1A). Targeting the CSF-1R receptor with tyrosine kinase inhibitors is a strategy used in mice to deplete macrophages.15 However, we found that the complete inhibition of CSF-1R phosphorylation in human primary macrophages was not associated with cell death induction (7-Aminoactinomycin D (7-AAD) and annexin V) (figure 1B, online supplemental figure S1) or disruption of cellular metabolic activity (MTT assay) (figure 1C). The importance of CSF-1 in macrophage differentiation and polarization prompted us to evaluate the effect of CSF-1R receptor blockade on human macrophage phenotype. To achieve this goal, we performed a global gene expression analysis by RNA sequencing (RNAseq) on bulk macrophages 48 hours after exposure to vehicle and Edicotinib. To extract differentially expressed genes between treated and naïve macrophages, we used a moderated t-test with an adjusted p value (Benjamini-Hochberg procedure with a threshold set at q value<0.05) and a fold change threshold set at 2 (log2 FC <–1 or log2 FC>1). CSF-1R receptor inhibition by Edicotinib was associated with 740 downregulated and 481 upregulated genes (figure 1D). We then used a Gene Ontology (GO) enrichment analysis to identify pathways affected by Edicotinib. The GO terms associated with genes downregulated by Edicotinib indicated that the regulation of the cholesterol metabolic pathway, the inhibition of the ERK1/2 pathway, and lipid synthesis were the main of biological processes identified as a result of CSF-1R receptor blockade (figure 1E).
Complete CSF-1R inhibition is associated with a profound phenotypic change. (A) Immunoblot of phosphorylated CSF-1R at site tyrosine 723, CSF-1R total protein and β-actin (upper panel) in human macrophages. Quantification of the level of phosphorylation normalized to β-actin from three independent experiments. (B) Flow cytometry analysis of 7-AAD+human macrophages treated for 48 hours. Each condition has its own vehicle control (DMSO) at the same concentration than Edicotinib (Ed) (n=3). (C) MTT assay on human macrophages exposed to Edicotinib for 48 hours (n=3). (D) Volcano-plot analysis of differentially expressed genes between Edicotinib versus vehicle (n=4). Human macrophages were treated with Edicotinib (10 µM) or vehicle for 48 hours. (E) GO (Gene Ontology)-term analysis of biological processes associated with downregulated genes under Edicotinib exposure. Number of genes associated with each GO-terms are indicated. 7-AAD, 7-Aminoactinomycine D; CSF-1R, Colony-stimulating factor 1 receptor DMSO, Dimethyl Sulfoxide; ERK1/2, Extracellular signal-regulated kinase 1/2, MAPK, Mitogen activated protein kinase.
CSF-1/CSF-1R regulates cholesterol synthesis in human macrophages via the transcription factor SREBP2
To explore the GO identification of cholesterol synthesis regulation under CSF-1R targeting, we examined the expression of all the enzymes involved in cholesterol synthesis starting from acetyl-CoA. Cholesterol, an essential lipid component of mammalian cells, is mainly obtained by endogenous synthesis or uptake. Endogenous synthesis relies on nearly 30 enzymatic reactions.16 We found that genes coding for enzymes involved in cholesterol synthesis ACAT2, HMGCS1, HMGCR, MVK, PMVK, MVD, IDI1, FDPS, FDFT1, SQLE, LSS, CYP15A1, TMF7SF2, NSDHL, HSD17B7, MSMO1, SC5D, EBP, DCHR7, DCHR24 are downregulated under edicotonib exposure (figure 2A) and except for two of them (PMVK, LSS) the fold change is greater than 2 (figure 2B). The control of cholesterol synthesis genes by the CSF-1/CSF-1R pathway was confirmed by the stimulation of human macrophages by CSF-1, which showed the upregulation of HMGCR and DHCR7 (figure 2C). SREBP2 (sterol regulatory element-binding protein 2) is a helix-loop-helix leucine zipper transcription factor that regulates the synthesis and cellular uptake of cholesterol.17 Using the ENCODE data set,18 we have explored the known targets of this transcription factor and found that the cholesterol synthesis genes are under the control of SREBP2 (figure 2D). Interestingly, the LDL receptor (LDLR) which is responsible for cellular uptake of cholesterol from the extracellular milieu and the fatty acid synthetase (FASN) are also SREBP2 target genes (figure 2D). We validated the SREBP2 dependent expression of cholesterol synthesis genes (HMGCR, DHRC7) and LDLR using RNAi targeting against sterol regulatory element binding transcription factor 2 (SREBF2), the gene encoding the SREBP2 protein (figure 2E). We demonstrated the control of SREBF2 by the CSF-1/CSF-1R pathway by showing that SREBF2 expression is increased under CSF-1 stimulation (figure 2F) and decreased when CSF-1R is blocked by Edicotinib (figure 2G). We confirmed that the active form of SREBP2 expression is downregulated by the CSF-1R blockade (figure 2H), resulting in the decrease of HMGCR at the protein level (online supplemental figure S2A). In addition, LDLR, a target of SREBP2, is downregulated by Edicotinib (figure 2I). We observed the resulting decrease in cellular cholesterol levels under Edicotinib exposure similar to what is found using RNAi targeting of SREBF2 or blockade of HMGCR activity with simvastatin, a specific inhibitor (figure 2J). The cellular homeostasis of cholesterol is a balance between synthesis, uptake and efflux. The impairment of cholesterol synthesis and uptake by CSF-1R receptor blockade could be compensated by a decrease in cholesterol efflux. To evaluate this possibility, we studied the expression of the two major cholesterol efflux transporters expressed in macrophages ATP binding cassette A1 (ABCA1) and ATP binding cassette subfamily G member 1 (ABCG1). We found that the CSF-1R targeting did not decrease the expression of these transporters in macrophages (online supplemental figure S2B) and that the decrease in intracellular cholesterol levels induced by CSF-1R receptor blockade resulted in a global decrease in macrophage cholesterol secretion (online supplemental figure S2C).
CSF-1/CSF-1R controls cholesterol synthesis in human tumor-associated macrophages. (A) Gene expression of cholesterol synthesis enzymes in human macrophages treated by Edicotinib (in red) compared with controls (vehicle in black) (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. (B) The cholesterol synthesis pathway with intermediate products. Enzymes that present a downregulation with a fold change >2 are represented in red. (C) Expression of HMGCR and DHRC7 genes after 6 hours stimulation by CSF-1 50 ng/mL on previously starved human macrophages determined by RT-qCPR (n=3). Housekeeping genes used are β2M and HPRT1. (D) Representation of SREBP2 target genes based on ChIP analysis (ENCODE study). (E) Expression of SREBF2, HMGCR, DHCR7 and LDLR genes in RNAi-treated macrophages against SREBF2 determined by RT-qPCR (n=5). Housekeeping genes used are β2M and HPRT1. (F) Expression of SREBF2 gene after 6 hours stimulation by CSF-1 50 ng/mL on previously starved human macrophages determined by RT-qCPR (n=3). Housekeeping genes used are β2M and HPRT1. (G) Gene expression of SREBF2 in human macrophages treated by Edicotinib (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. Human macrophages were treated with Edicotinib (10 µM) or vehicle for 48 hours. (H) Representative immunoblot of mature SREBP2 in human macrophages treated with Edicotinib compared with controls (left panel) using actin as a control loading. Quantification of SREBP2 normalized to the control loading is represented in the right panel (n=3). (I) Gene expression of LDLR in human macrophages treated by Edicotinib (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. (J) Quantification of intracellular cholesterol in macrophages treated by Edicotinib (10 µM) or simvastatin (10 µM) for 48 hours and in RNAi against SREBF2 treated macrophages compared with vehicle (DMSO) or RNAi control, respectively (n=3). The amount of decrease is represented in % of the appropriate control (DMSO for Edicotinib and simvastatin; siCTRL for SiSREBF2). (K) Macroscopic view of a colon adenocarcinoma and HES staining of tumoral and non-tumoral tissues used in a co-culture with human macrophages. (L) Expression of SREBF2, HMGCR, DHCR7 and LDLR genes in hypoxic macrophages cultured with non-tumoral and tumoral tissues determined by RT-qPCR (n=5). Tumor-associated macrophages were also treated with Edicotinib. Relative expression compared with control macrophages in normoxia. Housekeeping genes used are β2M and HPRT1. (M) ELISA quantification of CSF-1 secreted by tumoral and non-tumoral tissues (n=4). (N) Flow cytometry quantification of membrane CSF-1R expression on macrophages treated by Edicotinib compared with controls (DMSO) (n=3). Human macrophages were treated with Edicotinib (10 µM) or vehicle for 48 hours. (O) Gene expression of CSF-1 in human macrophages treated by Edicotinib (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. Human macrophages were treated with Edicotinib (10 µM) or vehicle for 48 hours. (P) Expression of CSF-1 gene in hypoxic macrophages cultured with non-tumoral and tumoral tissues determined by RT-qPCR (n=4). Tumor-associated macrophages were also treated by Edicotinib (10 µM) or vehicle for 48 hours. Relative expression compared with control macrophages in normoxia. Housekeeping genes used are β2M and HPRT1. ChIP, Chromatine immunoprecipitation; CSF-1R, colony-stimulating factor 1 receptor; DMSO, Dimethyl sulfoxide; HES, Hematoxylin Eosin Safran; LDLR, LDL receptor; M-CSF, macrophage colony-stimulating factor; MFI, median fluorescence intensity; SREBF2, sterol regulatory element binding transcription factor 2; SREBP2, sterol regulatory element-binding protein 2, RT-qPCR, Reverse transcriptase quantitative polymerizing chain reaction.
Edicotinib interferes with the macrophage-tumor communication resulting in modulation of cholesterol synthesis in colorectal cancers
Membrane cholesterol efflux from macrophages has been reported to be involved in tumor growth.19 This efflux relies on the ability of macrophages to express efflux transporters but also on the maintenance of their intracellular cholesterol pool based on synthesis and uptake. To further understand the importance of cholesterol synthesis in the cross-talk between macrophages and tumors, we performed a co-culture between human macrophages and tumor or non-tumor tissues from the same colon obtained from surgical resection of colorectal adenocarcinomas (figure 2K and online supplemental figure S2D). We observed that macrophages under the influence of tumor tissue upregulate their cholesterol synthesis genes as well as the cholesterol uptake receptor LDLR under the control of SREBF2 which is upregulated by the tumor (figure 2L and online supplemental figure S2E). We also demonstrated that Edicotinib is able to counteract this tumor-driven metabolic reprogramming by interfering with cholesterol synthesis and uptake (figure 2L). This communication between tumors and macrophages suggested the involvement of the CSF-1/CSF-1R pathway. We confirmed that tumors secrete significantly more CSF-1 than non-tumor tissues, which drives cholesterol synthesis and uptake in macrophages (figure 2M). Nevertheless, we sought to verify whether Edicotinib could also affect the expression of the CSF-1R receptor on the surface of macrophages but found no decrease in receptor following CSF-1R blockade (figure 2N). Interestingly, we found that the ability of macrophages to produce their own CSF-1 is impaired in human macrophages exposed to Edicotinib (figure 2O). Even when tumors do not increase the autocrine-associated production in macrophages, Edicotinib is able to downregulate this production in macrophages, enhancing the blockade of the CSF-1/CSF-1R pathway (figure 2P).
CSF-1R receptor targeting downregulates HIF-2α expression in hypoxia through inhibition of ERK1/2 phosphorylation
Previous studies have shown that several environmental factors can modulate the cellular response to CSF-1R receptor targeting.8 Among these factors, hypoxia is of particular interest because the tumor environment is associated with low oxygen availability.20 To assess the interplay between hypoxia and CSF-1R receptor targeting, we performed the study of differentially expressed genes in hypoxia compared with normoxia and analyzed the impact of Edicotinib on the hypoxic response (figure 3A). The cell survival profile of CSF-1R receptor blockade in hypoxia was similar to what we found in normoxia (online supplemental figure S3A). Heat-map analysis revealed that specific hypoxia-sensitive genes exhibited two distinct patterns: specific hypoxia-sensitive genes that maintained their expression profile under CSF-1R receptor blockade (clusters 1 and 3) and genes with a modified profile under CSF-1R receptor blockade (clusters 2, 4 and 5). Among the hypoxia upregulated genes (cluster 3), we found several genes LDHA, NDRG1, P4HA1 and SLC2A1 (figure 3B), which are part of the HIF-1α target gene set identified by Chromatine immunoprecipitation (ChIP) enrichment analysis21 suggesting that the HIF-1α-dependent hypoxic response is mainly independent of the CSF-1R pathway. Of particular interest, we observed that the downregulation of some hypoxic genes is abolished by CSF-1R receptor blockade (cluster 2) with an increased expression profile in normoxia (figure 3A). One of these genes is endothelial PAS domain-containing protein 1 (EPAS1) (figure 3C). The EPAS1 gene encodes the transcription factor HIF-2α, which plays an essential role in the cellular response to low oxygen environments.22 The downregulation of EPAS1 messenger RNA (mRNA) in hypoxia contrasts with the stabilization of HIF-2α protein in the same condition (figure 3D). To understand the role of CSF-1R in the HIF-2α-dependent hypoxic response, we sought to elucidate the function of HIF-2α by studying FLT1 (VEGFR1), an HIF-2α target gene.23 Indeed, FLT1 expression is increased in hypoxic macrophages (figure 3E) under the control of HIF-2α transcriptional activity, as demonstrated by RNAi targeting of EPAS1 in hypoxic macrophages (online supplemental figure S3B). The decrease of FLT1 (figure 3E) and the corresponding increase of EPAS1 mRNA level on CSF-1R receptor blockade by Edicotinib in hypoxic macrophages (figure 3C) supports a decrease of HIF-2α expression in hypoxia under CSF-1R receptor blockade, a pattern that we confirmed by immunoblot (figure 3F). Interestingly, the activation of HIF-2α leading to its translocation to the nucleus and fixation on hypoxic response elements gene promoters is ERK1/2 dependent.24 The identification of the ERK1/2 pathway as a target of CSF-1R blockade in normoxia (figure 1E) suggested the possibility of a similar pattern in hypoxia. Indeed, we confirmed this pattern by a GSEA (figure 3G) and by immunoblotting of phosphorylated sites p-ERK1/2 sites in hypoxia (figure 3H). Inhibition of ERK1/2 with the MEK1 inhibitor U0126 was able to downregulate the expression of HIF-2α similar to that observed with Edicotinib (figure 3I). In addition, HIF-2α protein expression is a direct sensor of intracellular oxygen availability. Oxygen diffusion from the cellular environment into the cell is primarily controlled by the plasma membrane permeability which is profoundly affected by the membrane concentration of cholesterol.25 A decrease in membrane cholesterol will favor oxygen diffusion into the cell. Therefore, the decrease in cholesterol synthesis induced by CSF-1R blockade suggested a complementary involvement of the cellular cholesterol in HIF-2α expression. Indeed, the RNAi targeting of SREBF2, which led to a decrease in cholesterol synthesis and cellular uptake, showed a small decrease in HIF-2α (figure 3J), suggesting a possible combined effect between SREBF2-dependent and ERK1/2-dependent processes. Examination of the expression of cholesterol synthesis genes (HMGCR, DHCR7) and cellular uptake (LDLR) confirms that these two mechanisms are independent as ERK1/2 inhibition did not downregulate these genes, in contrast to Edicotinib exposure (online supplemental figure S3C).
CSF-1R targeting downregulates HIF-2α expression in hypoxia through inhibition of ERK1/2 phosphorylation. (A) Hierarchical clustering (Ward methodology) of hypoxic responsive genes (log2 FC <–1 and log2 FC >–1 and q value<0.05) for normoxic and hypoxic macrophages exposed to Edicotinib (10 µM) or vehicle (DMSO) for 48 hours. Normoxic data are the same as in figure 1. (B) Gene expression of LDHA, NDRG1, P4HA1 and SLC2A1 genes in normoxic and hypoxic human macrophages treated by Edicotinib (10 µM) or vehicle for 48 hours (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. Normoxia is in blue and hypoxia is in red. (C) Gene expression of endothelial PAS domain-containing protein 1 gene in normoxic and hypoxic human macrophages treated by Edicotinib (10 µM) or vehicle for 48 hours (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. Normoxia is in blue and hypoxia is in red. (D) Immunoblot of HIF-2α in normoxic and hypoxic macrophages (representative of five independent experiments). (E) Gene expression of FLT1 gene in normoxic and hypoxic human macrophages treated by Edicotinib (10 µM) or vehicle for 48 hours (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. Normoxia is in blue and hypoxia is in red. (F) Immunoblot of HIF-2α in normoxic and hypoxic macrophages treated by vehicle or Edicotinib with a representative experiment (left panel) and quantification of the expression of HIF-2α compared with β-actin (right panel) (n=4). (G) Gene Set Enrichment Analysis of the Gene Ontology—Biological Process ERK1 and ERK2 cascade for hypoxic macrophages treated by Edicotinib. (H) Immunoblot of phosphorylated ERK1/2, total ERK1/2 and β-actin in Edicotinib treated macrophages (representative of three independent experiments). (I) Immunoblot of HIF-2α in normoxic and hypoxic macrophages treated by vehicle, Edicotinib (10 µM) or U0126 (10 µM) for 48 hours with a representative experiment (left panel) and quantification of the expression of HIF-2α compared with β-actin (right panel) (n=3). (J) Immunoblot of HIF-2α in normoxic and hypoxic macrophages treated by siRNA against sterol regulatory element binding transcription factor 2 or using siRNA scrambled with a representative experiment (left panel) and quantification of the expression of HIF-2α compared with β-actin (right panel) (n=3). CSF-1R, colony-stimulating factor 1 receptor; DMSO, Dimethyl Sulfoxide; ERK1/2, extracellular signal-regulated kinase 1/2; HIF-2α, hypoxic induced factor 2 alpha.
Hypoxia-induced increase in fatty acid synthesis reversed by CSF-1R targeting in human macrophages
The recent recognition that hypoxia activates SREBP2 in hypoxic THP1-monocytes raised the possibility that the ability of CSF-1R receptor blockade to dampen cholesterol synthesis could be antagonized in hypoxic macrophages.26 However, these authors reported a small or absent effect in hypoxic differentiated THP1-macrophages.26 We sought to address this issue in our primary human macrophages. Examination of differentially repressed genes in exposed hypoxic macrophages confirmed the results obtained in normoxia with a downregulation of the cholesterol synthesis and the ERK1/2 pathway under CSF-1R blockade (figure 4A). In addition to cholesterol synthesis and cellular uptake under the control of SREBF2, we observed that SREBF1 and FASN were similarly downregulated in hypoxia under CSF-1R blockade (figure 4B). SREBP1, the transcription factor encoded by the SREBF1 gene, is involved in fatty acid synthesis and FASN is under the control of SREBPs transcription factors. Furthermore, the analysis of the hypoxia-specific response genes modulated by Edicotinib (cluster 4 in figure 3A) revealed that lipid transport, localization is associated with the hypoxia response (figure 4C), and that this response could be disrupted by CSF-1R blockade. FASN, a gene under the control of SREBF1 and SREBF2, is the major enzymatic complex responsible for the synthesis of palmitic acid (C16:0) and stearic acid (C18:0) from malonyl-CoA, which are subsequently converted to palmitoleic acid (C16:1 cis) and oleic acid (C18:1 cis), respectively (figure 4D). Fatty acids, particularly oleic acid, have been implicated in macrophage commitment to an immunosuppressive CD206+CD38+ phenotype in TAMs.27 Using GC-MS, we confirmed the significant increase of fatty acids (palmitic acid and stearic acid) in hypoxic macrophages and the ability of the CSF-1R blockade to attenuate this synthesis (figure 4E), we only found a trend for palmitoleic acid and oleic acid (online supplemental figure S4A). We also confirmed the downregulation of CD206 expression in tumor-educated macrophages (figure 4F, online supplemental figure S4B) and CD206, CD38 gene expression in hypoxic macrophages exposed to Edicotinib (online supplemental figure S4C). We also found that inhibition of FASN by a specific inhibitor (C75) in hypoxic macrophages was sufficient to prevent IL-4 driven CD206 expression (figure 4G). These results support for a fatty acid synthase-mediated inhibition of CD206 following CSF-1R targeting.
Fatty acid synthesis in hypoxia is reversed by targeting CSF-1R. (A) GO (Gene Ontology)-term analysis of biological processes associated with downregulated genes under Edicotinib exposure in hypoxia. Number of genes associated with each GO-terms are indicated. (B) Heat map of cholesterol synthesis genes associated with SREBF1, FASN and SREBF2 for hypoxic macrophages treated by Edicotinib compared with vehicle. (C) GO (Gene Ontology)-term analysis of biological processes associated with genes identified in cluster 4 of figure 3A. Number of genes associated with each GO-terms are indicated. (D) Fatty acid synthesis pathway involving the fatty acid synthetase (FASN). (E) Quantification by GC-MS of palmitic acid (C16:0), stearic acid (C18:0) in macrophages in normoxia, in hypoxia and in hypoxia treated by Edicotinib (10 µM) for 48 hours (n=4). (F) Quantification by flow cytometry of CD206 membrane expression in co-cultured macrophages with RKO cells and IL-4 (25 ng/mL) for 48 hours with vehicle (DMSO) or Edicotinib (n=3). Representative panel on the left and quantification on the right. (G) Expression of CD206 (MRC1) gene in hypoxic macrophages stimulated by IL-4 for 4 hours and a specific inhibitor of FASN (C75 50 µM) determined by RT-qPCR (n=3). Housekeeping genes used are β2M and HPRT1. CSF-1R, colony-stimulating factor 1 receptor; DMSO, Dimethyl sulfoxide; ERK1/2, extracellular signal-regulated kinase 1/2; FDR, False discovery rate; GC-MS, Gas chromatography mass spectrography; IL, interleukin; SREBF, sterol regulatory element binding transcription factor, RT-qPCR, Reverse transcriptase quantitative polymerizing chain reaction.
CSF-1R targeting downregulates the expression of dihydropyrimidine dehydrogenase preventing 5-FU hypoxic macrophage-driven chemoresistance
HIF-2α has been recognized as an important regulator of innate immunity in the context of tumors, in particular by controlling macrophage’s recruitment.28 In addition, we recently reported that HIF-2α controls the expression of dihydropyrimidine dehydrogenase (DPD) in hypoxia independently of its transcription factor activity. DPD expression in hypoxic macrophages is responsible for a resistance to 5-FU in human CRC.10 We have shown in the same study that rodent models are inadequate to mimic this mechanism, because the DPYD gene is epigenetically negatively regulated in rodent macrophages, in contrast to humans. Downregulation of HIF-2α expression under CSF-1R blockade offers a potential strategy to restore chemosensitivity in this context. Indeed, Edicotinib is able to downregulate the expression of DPD in hypoxic macrophages (figure 5A), resulting in the complete abrogation of its enzymatic activity, preventing the conversion of uracil to dihydrouracil (figure 5B). We confirmed the inhibition of the HIF-2α-dependent synthesis of DPD during the transition to hypoxia, which requires the continuous destabilization of HIF-2α during the transition (figure 5C). The previous demonstration that ERK1/2 phosphorylation controls HIF-2α expression implies an expected control of DPD expression in the same context as we confirmed (figure 5D) as well as the implication of the cellular cholesterol content in the hypoxia-induced DPD expression in macrophages (figure 5E). Consequently, the downregulation of DPD expression obtained by CSF-1R targeting allows the restoration of 5-FU sensitivity of HT-29 and RKO CRC cells in a co-culture setting (figure 5F). We have previously shown that DPD expression under the HIF-2α expression is not related to mRNA modulation,10 to ensure that this is still the case in the tumor environment we showed that Edicotinib downregulates DPD expression in hypoxic TAMs co-cultured with tumors (figure 5G) without downregulating its mRNA as expected (figure 5H). We have previously shown that macrophages are the major source of DPD expression in CRC.10 However, these macrophages are replenished by circulating monocytes and these hypoxic monocytes (CD14+) express DPD in contrast to other immune cells such as hypoxic T (CD3+) or B (CD19+) lymphocytes (figure 5I, online supplemental figure S5A), representing another source of immune-driven chemoresistance to 5-FU. Circulating monocytes are recruited to tumor sites by chemokine ligand 2/7 (CCL2/CCL7) chemokine secretion from tumor macrophages.29–31 Edicotinib may interfere with this process. Indeed, the GO—biological process associated with myeloid leukocyte migration was associated with differentially downregulated genes by CSF-1R blockade (figure 4A). We confirmed this pattern by the effect of CSF-1R targeting on the expression of CCL2 and CCL7 in macrophages (figure 5J) and the resulting secreted chemokines (online supplemental figure S5B). Similarly, CCL2 and CCL7 expressions are disrupted in hypoxic TAMs exposed to Edicotinib (figure 5K). These results demonstrate the ability of CSF-1R targeting to disrupt DPD expression in TAMs and prevent the recruitment of DPD-expressing myeloid cells to the tumor site.
CSF-1R targeting downregulates dihydropyrimidine dehydrogenase expression in tumor-associated macrophages. (A) Immunoblot of DPD in normoxic and hypoxic macrophages treated by vehicle (DMSO) and Edicotinib with a representative experiment (upper panel) and quantification of the expression of HIF-2α compared with β-actin (lower panel) (n=4). (B) Quantification of the reductive activity of DPD through the conversion of uracil (U) to dihydrouracil (UH2) (n=4). (C) Immunoblot of HIF-2α, DPD and β-actin for macrophages treated by Edicotinib (10 µM) for 48 hours then submitted to 6 hours hypoxia with or without maintaining the CSF-1R blockade (+6-hour condition). Representative of three independent experiments. (D) Immunoblot of DPD and β-actin for macrophages treated by Edicotinib or U0126 for 48 hours then submitted to 6 hours hypoxia with Edicotinib (10 µM) or U0126 (10 µM). A representative experiment is shown in the upper panel and the quantification compared with β actin appears in the lower panel (n=3). (E) Immunoblot of DPD and β-actin for macrophages treated by siRNA against SREBF2sterol regulatory element binding transcription factor 2 or SiRNA scrambled for 48 hours then submitted to 6 hours hypoxia. A representative experiment is shown in the upper panel and the quantification compared with β-actin appears in the lower panel (n=3). (F) Co-culture between colorectal cancer cells (HT-29, RKO) with human THP1-macrophages. 5-FU was used at 1 µg/mL for 48 hours. Edicotinib (5 µM) or vehicle (DMSO) was added during 48 hours (n=3). (G) Immunoblot of DPD and β-actin in hypoxic tumor-associated macrophages treated by Edicotinib or vehicle (DMSO) (representative of three experiments). (H) Expression of DPYD gene in hypoxic macrophages cultured with non-tumoral and tumoral tissues determined by RT-qPCR. Tumor-associated macrophages were also treated by Edicotinib (n=5). Relative expression compared with control macrophages in normoxia. Housekeeping genes used are β2M and HPRT1. (I) Immunoblot of DPD and β-actin in CD14+monocytes, CD3+T lymphocytes and CD20+B lymphocytes (representative of three independent healthy donors). (J) Gene expression of CCL2 and CCL7 in hypoxic human macrophages treated by Edicotinib (n=4). Gene expression levels are expressed in FPKM, fragments per kilobase million. (K) Expression of CCL2 and CCL7 genes in hypoxic macrophages cultured with non-tumoral and tumoral tissues determined by RT-qPCR (n=5). Tumor-associated macrophages were also treated by Edicotinib (10 µM) for 48 hours. Relative expression compared with control macrophages in normoxia. Housekeeping genes used are β2M and HPRT1. (L) Schematics of CSF-1 controlled tumor-associated macrophages involvement in tumor growth and consequences of CSF-1R targeting. Figure created using BioRender (BioRender.com). CCL, chemokine ligand; CSF-1R, colony-stimulating factor 1 receptor;DMSO, Dimethyl Sulfoxide; DPD, dihydropyrimidine dehydrogenase; HIF-2α, hypoxic induced factor 2 alpha; SREBP2, sterol regulatory element-binding protein 2; RT-qPCR, Reverse transcriptase quantitative polymerizing chain reaction; 5-FU, 5-fluorouracil.
Discussion
TAMs are an essential component of the tumor immune microenvironment in the vast majority of cancers. Their involvement in angiogenesis, extracellular matrix remodeling, cancer cell proliferation, metastasis spreading and treatment resistance is leading to the development of macrophage-centered therapeutic strategies.4 The importance of the CSF-1/CSF-1R axis in macrophage survival, differentiation and activation makes CSF-1R targeting a favored approach to remodel TAMs. Two strategies have been pursued to achieve this goal: blocking the interaction between the ligand (CSF-1, IL-34) and its receptor using specific anti-CSF-1R antibodies or inhibiting the tyrosine kinase activity of CSF-1R using specific inhibitors. Various inhibitors have been developed over the years, and despite high specificity against CSF-1R, these molecules have failed to show a strong clinical effect when used as monotherapy.4 32 The unclear reasons for this lack of efficacy led us to design the current study to investigate in detail the molecular consequences of CSF-1R blockade using a selective CSF-1R kinase inhibitor (Edicotinib or JNJ40346527), which has already been validated in humans.13 14
We observe a clear metabolic shift in CSF-1R-targeted macrophages, mainly focused on cholesterol and fatty acid metabolism. The link between CSF-1 and cholesterol metabolism was suggested in a previous study.33 We confirm the ability of CSF-1 to induce cholesterol synthesis and show that CSF-1R blockade is able to downregulate SREBF2 expression leading to the inhibition of the cholesterol synthesis but also its cellular uptake. We observe that colorectal tumors favor SREBF2 expression and consequently drives the increase of cholesterol levels in human macrophages. Cholesterol efflux from macrophages under the control of transporter proteins such as ABCA1/ABCG1 has been associated with tumor growth.19 Tumor cells exposed to macrophage-secreted cholesterol secrete hyaluronic acid that drives macrophage reprogramming toward an M2 phenotype in mice.19 Even if cholesterol transporters are not suppressed in macrophages targeted by Edicotinib, the decreased total amount of cellular cholesterol induced by Edicotinib prevents the ability of macrophages to maintain their secretion, thereby breaking the feedback loop between TAMs and tumors.
Since cholesterol is synthesized by the metabolic synthesis starting from acetyl-coA, which is produced by the fatty acid β-oxidation pathway, we investigated the fatty acid synthesis in macrophages. We find that Edicotinib is able to prevent the increase in fatty acid accumulation driven by hypoxia in human macrophages (figure 4E), thereby preventing the appearance of an immunosuppressive phenotype CD206+CD38+ induced by oleate (online supplemental figure S4).
The CSF-1R blockade strategy is designed to occur in the low-oxygen tumor environment. The sensitivity of cholesterol synthesis and CSF-1 coupling in hypoxia is not known. A recent study highlighted the importance of hypoxia in the induction of cholesterol synthesis in monocytes but not in differentiated macrophages.26 The influence of CSF-1R targeting on the hypoxic response shows that EPAS1, which encodes HIF-2
is upregulated. In conjunction with this observation, we note the inverse correlation between EPAS1 mRNA and HIF-2
α
protein, revealing the counter-regulation of EPAS1 transcription by HIF-2
α
itself. A similar observation has been proposed for HIF-1
α
, based on miR-429, whose expression is promoted by HIF-1
α
.34 However, this negative feedback loop was associated with the decrease of HIF-1
α
in chronic hypoxia. Our observation was made in chronic hypoxia and no decrease of HIF-2
α
protein was observed. This observation needs to be further investigated to determine the direct or indirect mechanism. Our observation of the association between CSF-1R targeting and HIF-2
α
expression revealed the role of ERK1/2 activation in stabilizing this hypoxia-inducible factor in human macrophages. The downregulation of HIF-2
α
opens a promising avenue to target the recently identified mechanism leading to the chemoresistance to 5-FU driven by hypoxic macrophages in CRC.10 In this study, we show that targeting CSF-1R downregulates ERK1/2 phosphorylation, which in turn prevents HIF-2
α
expression in hypoxia, thereby preventing the expression of DPD, which can no longer degrade 5-FU. We further find that monocyte recruitment driven by the CCL2/CCL7 axis is also disrupted, preventing the contribution of other myeloid DPD-expressing cells to tumor infiltration (figure 5L).
Conclusions
In this study, we have provided compelling evidence showing that CSF-1R blockade is an effective strategy to prevent cancer cell-driven TAM recruitment and macrophage-induced resistance to chemotherapy. We have demonstrated the efficacy of an inhibitor of CSF-1R kinase activity to achieve metabolic reprogramming of TAMs by interfering with the cholesterol and fatty acid-mediated cross-talk between macrophages and cancer cells.
Data availability statement
Data are available upon reasonable request. The data generated and analyzed will be made available from the corresponding author upon reasonable request. RNA sequencing data are deposited in the NCBI Gene Expression Omnibus under accession number: GSE263919.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and was approved by Comité de protection des Personnes Ouest IV, ref: 25.05.18.57648. Participants gave informed consent to participate in the study before taking part.
Acknowledgments
We thank Malika Yakoubi for her technical support on DPD chromatographic activity measurement. We thank Dr Lemoigne, Dr Federspiel and Dr Plasse from the University Hospital of Grenoble-Alpes for kindly providing clinical grade 5-Fluorouracil.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors KG, CGP, MM, CH, RG and AM performed experiments and analyzed the data. AM supervised the data analysis. FT performed chromatography measurements. YY-B and CYB performed the lipidomics analysis. GR and EG recruited patients. M-HL performed the pathological analysis. AM wrote the original draft and all authors were involved in manuscript editing. Funding acquisition and supervision of the study were performed by AM. AM is the guarantor.
Funding KG has been supported by the ITN (International Training Network) Phys2Biomed project, which was funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 812772 and is supported by the ERiCAN program of Fondation MSD-Avenir (Reference DS-2018-0015). CGP is supported by the Innovative Research Initiative (IRGA 2022) of the university Grenoble Alpes. MM is supported by the APMC Fondation (Agir pour les Maladies Chroniques). This work is supported by the Comité de l’Isère de la Ligue Contre le Cancer . CYB and YY-B are supported by Agence Nationale de la Recherche, France (Project ApicoLipiAdapt grant ANR-21-CE44-0010; Project Apicolipidtraffic grant ANR-23-CE15-0009-01), The Fondation pour la Recherche Médicale (FRM EQU202103012700), Laboratoire d’Excellence Parafrap, France (grant ANR-11-LABX-0024), LIA-IRP CNRS Program (Apicolipid project), the Université Grenoble Alpes (IDEX ISP Apicolipid) and Région Auvergne Rhone-Alpes for the lipidomics analyses platform (Grant IRICE Project GEMELI), Collaborative Research Program Grant CEFIPRA (Project 6003-1) by the CEFIPRA (MESRI-DBT).
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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