Abstract
Metabolic rewiring is often considered an adaptive pressure limiting metastasis formation; however, some nutrients available at distant organs may inherently promote metastatic growth. We find that the lung and liver are lipid-rich environments. Moreover, we observe that pre-metastatic niche formation increases palmitate availability only in the lung, whereas a high-fat diet increases it in both organs. In line with this, targeting palmitate processing inhibits breast cancer-derived lung metastasis formation. Mechanistically, breast cancer cells use palmitate to synthesize acetyl-CoA in a carnitine palmitoyltransferase 1a-dependent manner. Concomitantly, lysine acetyltransferase 2a expression is promoted by palmitate, linking the available acetyl-CoA to the acetylation of the nuclear factor-kappaB subunit p65. Deletion of lysine acetyltransferase 2a or carnitine palmitoyltransferase 1a reduces metastasis formation in lean and high-fat diet mice, and lung and liver metastases from patients with breast cancer show coexpression of both proteins. In conclusion, palmitate-rich environments foster metastases growth by increasing p65 acetylation, resulting in a pro-metastatic nuclear factor-kappaB signaling.
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Data availability
Mouse scRNA-seq, RNA-seq and ChIP-seq data generated in this study have been deposited in the GEO under accession code GSE196993. The human expression data from patients with primary breast cancer from the publicly available TCGA Research Network and METABRIC are available in TCGA (http://tumorsurvival.org/download.html) and cBioportal (https://www.cbioportal.org/datasets). The dataset for gene expression from breast cancer metastases at different organ sites was downloaded from GEO under accession code GSE14018. Source data and gel source images are provided with this paper. All other data supporting the findings of this study are available within the Article and the Supplementary Information and from the corresponding author on reasonable request. Source data are provided with this paper.
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Acknowledgements
We thank P. Carmeliet (VIB-KU Leuven) for providing shRNA against Cpt1a, D. Nittner (VIB Histology and Imaging Core) for histology services and J. Lamote (VIB FACS Core) for providing advice and expertise for flow cytometry experiments. We thank T. Killian and V. van Hoef (VIB Bioinformatics Core) for their help with the RNA-seq analysis and L. Tora for advice on ChIP-seq analysis. In addition, we thank S. El Kharraz and A. Farag for performing blinded analyses of several H&E staining experiments shown in this manuscript. We acknowledge all physicians from the Multidisciplinary Breast Center Leuven (especially P. Neven, A. Smeets, I. Nevelsteen and K. Punie) for their clinical contribution to the UPTIDER and/or CHEMOREL cohorts. The authors also acknowledge the patients who accepted to donate tissues postmortem in the context of the UPTIDER program, as well as the entire multidisciplinary UPTIDER team. Figure 7h was created with BioRender.com. In terms of funding, P.A.M. is supported by a Marie Sklodowska-Curie Actions individual fellowship and has received Beug Foundation funding. Y.L. has received a Chinese Scholarship Council fellowship. A.C. is a Boehringer Ingelheim PhD fellow. G.D., J.F.G., T.G. and F.R. are Research Foundation – Flanders (FWO) PhD and senior postdoctoral fellows. G.D. has previously received a Kom op tegen Kanker and J.F.G. a FWO junior fellowship. X.-Z.L. is an EMBO fellow and has received funding from the Gilead Foundation. H.F.A. has received funding from Stiching Tegen Kanker and King Baudouin funds. V.B. received funding from Fondation Nelia et Amadeo Barletta, Switzerland, 12 Rounds contre le Cancer and Université de Paris. A.M. received doctoral funding from Fondation Nelia et Amadeo Barletta, Switzerland. E.N. and I.M. received Francis Crick Institute core funding from Cancer Research UK (CRUK) (FC001112), Medical Research Council (FC001112) and the Wellcome Trust (FC001112) and the European Research Council (ERC) CoG-2020-725492. X.L. is an EMBO postdoctoral fellow. O.M.-B. is supported by a 12T1217N project by FWO at the program under the Marie Sklodowska-Curie grant agreement no. 665501. G.F. is a recipient of a postdoctoral mandate of the University Hospitals Leuven (KOOR). M.M. was supported by an ERC Consolidator grant (ImmunoFit; no. 773208). S.Z. acknowledges funding from CRUK (A17196), Stand Up to Cancer campaign for CRUK (A29800) and Breast Cancer Now (2019AugPR1307). The laboratory of T.G.P.G. is supported by the Barbara and Wilfried Mohr Foundation. V.P. acknowledges funding from a Wallenberg Academy Fellowship (KAW 2016.0123), the Swedish Research Council (VR 2020-01480), the Ragnar Söderberg Foundation) and Karolinska Institutet (SciLifeLab and KI funds). Research of the laboratory of C.D. is supported by an ERC Consolidator grant (FATLAS, 101003153), by the Fondation Cancer Luxembourg (FC/2018/07), the Belgian Foundation Against Cancer (C/2020/1441, PhD grant to S.L.) and the Funds Nadine de Beauffort (PhD grants to K.V.B. and M.D.S.). The UPTIDER program is supported by a grant from the University Hospitals from Leuven (KOOR 2021), as well as a C1 grant (14/21/114) from KU Leuven. S.M.F. acknowledges funding from the ERC under Consolidator grant agreement no. 771486–MetaRegulation, FWO Projects (G0B4122N), Beug Foundation, Fonds Baillet Latour, KU Leuven FTBO/Internal Funding/CELSA, and Stichting tegen Kanker.
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Conception and design was carried out by P.A.M., G.D. and S.-M.F. Development of methodology was carried out by P.A.M., G.D., A.C., M.P. and C.R.D. Acquisition of data (including providing animals, acquiring and managing patient samples and providing facilities) was conducted by P.A.M., G.D., Y.L., A.C., E.N., A.M., M.P., J.V.E., I.V., D.B., X.L., H.F.A., M.D., N.R., X.S., T.G., M.D.S., S.L., F.R., S.H., Y.L., Q.W., E.K., C.C.A., V.G., G.F., J.-C.M., D.L., M.M., V.P., S.R.Z., J.C., J.S., H.W., U.B.-D., V.B., C.D., T.G.P.G. and I.M. Analysis and interpretation of data (for example, statistical analysis, biostatistics and computational analysis) was conducted by P.A.M., J.F.G., F.C.A., M.P., O.M.-B., Q.W., K.J.L., F.R., B.B., S.D., A.A., V.P. and S.-M.F. Writing, review and/or revision of the manuscript was carried out by P.A.M. and S.-M.F. Administrative, technical or material support (reporting or organizing data and constructing databases) was the responsibility of P.A.M., D.B., M.P. and J.V.E. Study supervision was carried out by S.-M.F.
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S.-M.F. has received funding from Bayer, Merck, Gilead, Black Belt Therapeutics and Alesta Therapeutics, has consulted for Fund+ and is on the advisory board of Alesta Therapeutics. T.G.P.G. has consulted for Boehringer Ingelheim. All other authors declare no competing interests.
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Extended data
Extended Data Fig. 1 High fat diet enhances several fatty acids, while during pre-metastatic niche formation only palmitate increases.
a. Fraction of free fatty acids (gray) over total fatty acid content (black) of the liver interstitial fluid of healthy BALB/c mice (n = 7). b. Mouse weight gain upon high fat or control diet over the course of the experiment. Data are presented as mean ± SEM (n =60 mice). Mixed-effects analysis with Sidak’s multiple comparisons. c. Palmitate and oleate abundance in the lung interstitial fluid of BALB/c mice after 16 weeks on control (CD) or high fat (HFD) diet (n = 11 mice). Data are presented as mean ± SEM of absolute concentration measured by mass spectrometry. Unpaired two-tailed t-tests with Welch correction. d. Palmitate and oleate abundance in the liver interstitial fluid of BALB/c mice after 16 weeks on CD or HFD diet (n = 8 mice). Data are presented as mean ± SEM of absolute concentration measured by mass spectrometry. Unpaired two-tailed t-tests with Welch correction. e. Schematic illustration for experimental pre-metastatic niche formation procedure. CM, control media; TCM, tumor conditioned media; i.v. intravenous. f. Changes in gene expression in lung populations upon TCM injection relative to CM injections, for genes whose upregulation has been previously linked to pre-metastatic niche formation, such as S100a8, S100a9, Mmp988,89 and Tlr3 and Cxcl2 in lung alveolar type II cells88, Tlr4 and Saa3 in lung endothelial cells and macrophages90; Slc2a1, Pdk1, and Ldha in macrophages91, and S100 genes in lung fibroblasts92. The color scale denotes log2 fold changes in TCM vs. CM. g. Relative glucose concentration in the lung interstitial fluid of healthy BALB/c mice exposed to control media (n = 10 mice) or tumor condition media (n = 8 mice). Data are presented as mean ± SEM. Unpaired two-tailed t-tests with Welch correction. h. Granulocytes population (which includes neutrophils) present in the lungs after induction of pre-metastatic niche formation using tumor conditioned media or control media. Data are presented as mean ± SEM (n = 3 mice). Unpaired two-tailed t-tests with Welch correction. i. Palmitate and oleate abundance in the lung (n = 16) and liver (n≥7) interstitial fluid of BALB/c mice injected with control media (CM) or 4T1 tumor conditioned media (TCM) (3 weeks, 3 times/week). Data are presented as mean ± SEM. Unpaired two-tailed t-tests with Welch correction. j. Palmitate concentration in the liver interstitial fluid of healthy (n = 11 mice) or 4T1 tumor-bearing (PT) (n = 19 mice) BALB/c mice. Data are presented as mean ± SEM.
Extended Data Fig. 2 High fat diet moderately impacts gene expression but increases the fraction of lung resident alveolar type II cells.
a. UMAP plots for the scRNA-seq data corresponding to lungs preconditioned with control media (CM) and tumor conditioned media (TCM), or control diet (CD) and high fat diet (HFD). Color-coded based on GSVA-based marker scores for gene sets corresponding to alveolar type I (AT1) and II (AT2) marker genes. Identified clusters are indicated within black circles. Marker scores are scaled to the range 0–1 for each market set (see Methods). b. scRNA-seq-based gene expression vs. cell type and diet condition profiles for known marker for AT1 and AT2 cells and lipid-related genes indicated on the left-hand side. Scaled expression levels are indicated by the color scale, where \(\overline {CP100k}\) denotes the average gene expression level (in counts per 100k reads) over all cells of a given type in each condition, and \(\overline {CP100k}\) the average of the latter over all cell types and condition media. The areas of the circles represent the percentage of cells with non-zero expression of each gene among all cells of each type and in each dietary condition. CD, control diet; HFD, high fat diet. c. Fractions of cells corresponding to AT2 cells, among all cells present in the lung of mice exposed to control (CD) or high fat (HFD) diet, as determined from scRNA-seq data.
Extended Data Fig. 3 Lung metastases show an increase in lipid species enriched in palmitoyl acyl chains typically found in the pulmonary surfactant.
a. Fatty acid composition of the lipid classes phosphatidylcholine, phosphatidylglycerol and phosphatidylethanolamine in breast primary tumor and lung metastasis tissues from BALB/c mice orthotopically injected with 4T1 breast cancer cells. Data are presented as mean ± SEM (n = 6 mice). Unpaired nonparametric two-tailed Mann–Whitney U-tests. b. Intracellular oleate abundance from mouse (4T1, EMT6.5) and human (MCF10A H-RasV12, MCF7) breast cancer cells cultured on soft-agar (3D) or attached (2D) conditions. Data are presented as mean ± SEM (n = 3 and 4 biological replicates). c. Palmitate uptake measured by 13C16-Palmitate intracellular incorporation in 3D spheroids (n = 5 biological replicates) and 2D (n = 6 and 4 biological replicates) cultured breast cancer cells after 5 d of incubation with BSA-conjugated 13C16-Palmitic acid. Data are presented as mean ± SEM. Unpaired two-tailed t-tests with Welch correction. d. Fraction on newly synthesized fatty acids estimated by fatty acid isotopomer spectral analysis based on mass isotopomer distribution (MID) of 13C6-glucose incorporation in 3D spheroids and 2D cultured breast cancer cells in the presence of extra palmitate (75μm) for 5 d. Data are presented as mean ± 95% confidence interval (n = 4 biological replicates). Unpaired two-tailed t-tests with Welch correction. e. Intracellular palmitate and oleate abundance from 3D spheroids mouse (4T1) and human (MCF7) breast cancer cells. Data are presented as mean ± SEM (n = 4 biological replicates). One-way ANOVA with Holm-Sidak’s multiple comparison test. f. Representative pictures of 4T1 spheroids cultured in 10% FBS, or 10% FBS in the presence of palmitate (75 μm) or oleate (116 μm). Scale bar, 0.5 μm. A representative of n = 3 experiments is shown. g. Relative proliferation of 2D cultured 4T1 cells (with or without extra palmitate) normalized to condition without extra palmitate. Data are presented as mean ± SEM (n = 6 biological replicates). h. Representative pictures of 4T07 spheroids cultured in 10% FBS with or without extra palmitate (75 μm). Scale bar, 0.5 μm. A representative of n = 3 experiments is shown. i-j. 3D spheroids growth of 4T1 cells upon palmitate + oleate sup (i) and stearate (j) supplementation compared to control or palmitate supplementation, represented by the average spheroids area of >100 spheroids. Data are presented as mean ± SEM (n = 4 and 5 biological replicates). One-way ANOVA with Holm-Sidak’s multiple comparison test.
Extended Data Fig. 4 CPT1a expression is upregulated in metastases and is associated with poor prognosis in breast cancer patients.
a. Mitochondrial mass represented by mean relative fluorescence (MFI) of MitoTracker in 3D spheroids 4T1 cells growing in the absence or presence of palmitate or oleate for 5 d. MFI is shown relative to the level of MitoTracker fluorescence of 10% FBS condition. Data are presented as mean ± SD (n = 4 biological replicates). b-c. Differentially expressed genes in (b) 4T1 cells cultured in 3D spheroids or 2D monolayer in the presence of extra palmitate, or (c) in 3D spheroid 4T1 in the presence or absence of extra palmitate (10% FBS + palmitate or 10% FBS). Calculated differences in gene expression are presented by plotting the negative log10 of false discovery rate (Y-axis) against the log2 fold change of gene expression (X-axis). Each dot represents an individual gene. In red, genes belong to the GEO term lipid metabolic process (GO:0006629). The highest-ranking (top 10) overexpressed genes or genes above the established cutoff are annotated. d. CPT1a expression in 3D spheroid 4T1 cells growing for 5 d in the presence of additional palmitate, oleate and stearate. A representative image of n = 3 experiments is shown. e. Forest plot depicting the hazard ratio (HR) (x-axis) and corresponding 95% confidence intervals (denoted by error bars) for overall survival of patients with primary breast cancer according to CPT1A expression from two different cohorts: TCGA (n = 1,221 patients) and METABRIC (n = 1,904 patients). Cox proportional hazards models were applied, controlling for age, tumor stage (cTNM-staging system), and tumor subtype in both datasets. Panel complementary to Fig. 3i. f. 3D spheroids growth of MCF7 cells upon CPT1a knockdown compared to scrambled control upon palmitate supplementation (75 μm) represented by the average spheroids area of >100 spheroids. Data are presented as mean ± SEM (n = 4 and 5 biological replicates). One-way ANOVA with Tukey’s multiple comparison test. g. 3D spheroids growth (5 d) of 4T1 cells upon CPT1a inhibition using etomoxir (50 μm) in the presence of extra palmitate (75 μm) represented by the average spheroids area of >100 spheroids. Data are presented as mean ± SEM (n = 4 and 8 biological replicates). One-way ANOVA with Tukey’s multiple comparison test. h. 3D spheroids number per well of 4T1 cells upon palmitate supplementation (75 μm), CPT1a genetic inhibition performed by shRNA (shCpt1a) and CRISPR (sgCpt1a), and upon metabolic rescue by acetate (5mM). Data are presented as mean ± SEM (n = 6, 8, 6, 5, 4, and 8 biological replicates respectively). One-way ANOVA with Tukey’s multiple comparison test.
Extended Data Fig. 5 Representative lung and liver H&E staining and primary tumor weight upon CPT1a and KAT2a loss.
a. Representative pictures of tissue from the lung of mice injected with 4T1 (m.f.) and EMT6.5 (i.v.) upon genetic inhibition of CPT1a compared to non-targeting sg/shRNA as a control, based on H&E staining. Arrowheads indicate metastasis tissue. Arrows are not shown in the liver pictures. Scale bars, 2 mm. b. Final primary tumor weight (grams) from individual breast tumors upon genetic inhibition of CPT1A (n = 19 and 12 mice) and KAT2A (n = 11 mice) or control (n = 13 and 11 mice) in the 4T1 model (m.f.). Data are presented as mean ± SEM. One-way ANOVA with Dunnett’s multiple comparison test.
Extended Data Fig. 6 Breast cancer spheroids in the presence of additional palmitate rely on CPT1a for acetyl-CoA production and for sustaining palmitate-induced 3D growth.
a. Invasive ability in a 3D matrix of 4T1 cells upon CPT1a knockout (sgCpt1a) compared to control (Scrambled) cells. Invasion was assessed by measuring the invasive area of cancer cells stained with calcein green. Representative images are depicted in the left panel (scale bar, 500 μm), and quantification in the right panel. Each dot represents a different, randomly selected microscopy field (n = 5 field). b. Migratory ability of 4T1 upon CPT1a knockout (sgCpt1a) compared to control (Scrambled) cells. Migration was assessed by analyzing the total cells migrated through transwells coated with endothelial cells. Blue, DAPI nuclear staining. Representative images are depicted in the left panel (scale bar, 500 μm), and quantification in the right panel. Each dot represents a different, randomly selected microscopy field (n = 5 field). c. Relatives changes in acetyl-CoA abundance in human MCF10A H-RasV12 and MCF7 breast cancer spheroids transduced with a lentiviral vector with shRNA against CPT1A (knockdown) compared to scrambled control sequences in the presence of extra palmitate. Data are presented as mean ± SEM (n = 4 biological replicates). Unpaired two-tailed t-tests with Welch correction. d-e. Relatives changes in acetyl-CoA abundance in mouse 4T1 breast cancer spheroids transduced with a lentiviral vector with RNA against Cpt1a (c, knockdown and d, knockout) compared to non-targeting sh/sgRNA control in the presence or absence of extra palmitate. Data are presented as mean ± SEM (n = 4 biological replicates). One-way ANOVA with Dunnett’s multiple comparison test or two-tailed unpaired Student’s t-test. f. 3D spheroids growth (5 d) of 4T1 cells upon palmitate supplementation (75 μm), CPT1a genetic inhibition (shCpt1a) and metabolic rescue with octanoate (130 μm) compared to non-targeting shRNA control, represented by the average of spheroids area of >100 spheroids. Data are presented as mean ± SEM (n = 4 biological replicates). One-way ANOVA with Dunnett’s multiple comparison test. g. Schematic representation of the palmitate flux into the mitochondria via CPT1A and the ACLY-dependent export of the mitochondrial acetyl-CoA pool to the cytosol via citrate. h. Intracellular levels of ATP in CPT1a knockout and control 4T1 3D spheroids cultured for 5 d in medium containing extra palmitate (75 μm) or acetate as metabolic rescue (5 mM). Data are presented as mean ± SEM (n = 8 and 4 biological replicates). i. Heatmap display of the log2 transformed ratios obtained for the indicated histone acetylation for CPT1a knockdown and control 4T1 3D spheroids cultured for 5 d in medium containing extra palmitate (75 μm). Relative abundances ratios, light/SILAC heavy, were obtained with the SILAC (Stable Isotope Labeling with Amino acids in Cell culture) internal standard strategy93.
Extended Data Fig. 7 CPT1a deletion reduces NF-κB signaling pathway but does not affect p65 DNA binding.
a. Top 10 enriched pathways (p<0.05) obtained from gene set enrichment analysis (GSEA) of 4T1 spheroids upon CPT1a inhibition (sgCPT1a), in the presence of the extra palmitate (75 μm) or acetate as metabolic rescue (5 mM) using the Hallmark gene set from Molecular Signatures Database (MSigDB). NES, normalized enrichment score. b. Relative expression of genes implicated in invasion and metastasis, and that are known to be regulated via NF-κB activation in 4T1 spheroids. Fold change is calculated from normalized raw counts (RNA-sequencing) of CPT1a knockout and non-targeting sgRNA control 4T1 3D spheroids cultured for 5 d in medium containing extra palmitate (75 μm) or acetate (5 mM). Data are presented as mean ± SD (n = 3 biological replicates). Multiple testing correction with false discovery rate (FDR) estimation. c. Relative expression of genes implicated in invasion and metastasis, and that are known to be regulated via NF-κB activation in MCF10A H-RasV12 spheroids. Fold changes are calculated for CPT1a knockdown and non-targeting sgRNA control MCF10A H-RasV12 3D spheroids cultured for 5 d in medium containing extra palmitate (75 μm) or acetate (5 mM) and are normalized to gene expression in control cells. Data are presented as mean ± SEM (n = 3 biological replicates). One-way ANOVA with Dunnett’s multiple comparison test. d. Upstream regulator analysis performed using Ingenuity Pathway Analysis using the differential gene expression of CPT1A knockout (sgCpt1a) 4T1 3D spheroids in the presence or absence of acetate (metabolic rescue, 5 mM) as input. Activation score of the top 30 upstream regulators (left column) was compared to those predicted for the differential gene expression of CPT1A knockout versus control conditions (in the presence of extra palmitate). Genes related to the activation of the NF-κB pathway are framed. Asterisks represent the overlap P value calculated using one-sided Fisher’s Exact Test (****P<0.0001). e. GSEA enrichment plots comparing the gene expression profiles in 4T1 3D spheroids transduced with a lentiviral vector containing sgCpt1a or sgScrambled as a control (left panel) and sgCpt1a 4T1 3D spheroids cultured with or without acetate (right panel). NES, normalized enrichment score; the P value indicates the significance of the enrichment score (permutation test). f. Total p65 binding to DNA measured by electrophoretic mobility shift assay (EMSA). Arrow indicates the position of the NF-κB containing complex. A representative of n = 3 experiments is shown.
Extended Data Fig. 8 Global histone acetylation and chromatin accessibility are not consistently changed upon CPT1a and/or KAT2a loss.
a. KAT2a expression in 3D spheroid 4T1 cells growing for 5 d in the absence or presence of additional palmitate, oleate and stearate. A representative image of n = 3 experiments is shown. b. Intracellular levels of acetyl-CoA in 4T1 cells growing in 3D for 5 d in medium containing only 10% FBS, or supplemented with palmitate (75 mM), oleate (116 μm) or acetate (5 mM). Data are presented as mean ± SEM (n = 4 biological replicates). c. Heatmap of the signal intensity of H3K9ac-targeted gene loci in non-targeting RNA control, CPT1a and KAT2a knockout 4T1 3D spheroids cultured for 5 d in medium containing extra palmitate (75 μm) (n = 3 biological replicates). d. Correlation plot of H3K9 acetylation in 4T1 3D spheroids cultured in the presence of palmitate upon CPT1a inhibition with and without acetate (5 d). e. Heatmap and hierarchical clustering of top-scored downregulated genes of the NF-κB signaling pathway upon CPT1a deletion in 4T1 3D spheroids cultured in the presence of palmitate for 5 d, represented together with the expression status of the same genes upon acetate rescue and KAT2a deletion non-targeting sgRNA is used in control transfected samples (n = 3 biological replicates). f. Proliferation of 4T1 cells upon genetic inhibition of either Cpt1a or Kat2a in 2D culture measured using incucyte. Mean of growth rate ± SEM is shown (n = 6 biological replicates). One-way ANOVA with Dunnett’s multiple comparison test. g. 3D spheroids in 4T1 cells upon pharmacologic inhibition of either KAT2a using the inhibitor CPTH2 (2 μm) or CPT1A using etomoxir (50 μm) cultured for 5 d in medium with or without extra palmitate supplementation. Size quantification is represented by the average spheroids area of >100 spheroids. Data are presented as mean ± SEM (n = 3 biological replicates). One-way ANOVA with Tukey’s multiple comparison test. h. 3D spheroids number per well of 4T1 cells upon palmitate supplementation (75 μm), CPT1a or KAT2a genetic inhibition performed by CRISPR (sgCpt1a and sgKat2a) compared to non-targeting sgScrambled as a control, and upon metabolic rescue by acetate (5mM). Data are presented as mean ± SEM (n = 4 and 5 biological replicates). One-way ANOVA with Tukey’s multiple comparison test. i. Dose-response of 3D spheroid growth to the pharmacologic inhibition of KAT2a using CPTH2 inhibitor with or without extra supplementation of palmitate. Left panel, representative pictures. Right panel, spheroid size quantification is represented by the average spheroids area of >100 spheroids (n = 4 biological replicates). Two-way ANOVA with Tukey’s multiple comparison test. j. Total area and number of metastases in the lung of mice after 14 d of intravenous (i.v.) injections with 4T1 Kat2a knockout (sgKat2a, n = 8 mice) or non-targeting sgScrambled control cells (n = 10 mice) analyzed by H&E staining. Unpaired two-tailed t-tests with Welch correction.
Extended Data Fig. 9 Protein and RNA expression of genetically modified breast cancer cells.
a. Relative gene expression analysis of CPT1A in human (MCF10A H-RasV12 and MCF7), mouse (4T1, EO771-MCB3 and EMT6.5) breast cancer cells infected with either a control shRNA, or two different CPT1A, or Cpt1a shRNAs normalized to the control condition. Data are presented as mean ± SD (n = 3 biological replicates). Unpaired two-tailed t-tests. b. Protein expression in mouse 4T1 cancer cells infected with either a non-targeting sgScrambled as a control or two different sgRNA against Cpt1a and Kat2a gRNAs. A representative of n = 3 experiments is shown.
Extended Data Fig. 10 MS/MS validation of lipids detected in metastases by MALDI-MSI molecular imaging.
a. MS/MS spectrum of the ion at m/z 760.5842 detected from the metastatic areas within the lung tissue in positive ion mode using the timsTOF fleX. Ions supporting the assignment of PC O-18:1_16:0 are annotated with their corresponding mass accuracy. b. MS/MS spectrum of the ion at m/z 760.5842 detected from the metastatic areas within the lung tissue in positive ion mode using the timsTOF fleX. Ions supporting the assignment of PC 20:1_16:0 are annotated with their corresponding mass accuracy. c. MS/MS spectrum of the ion at m/z 760.5842 detected from the metastatic areas within the lung tissue in positive ion mode using the timsTOF fleX. Ions supporting the assignment of PC18:1_16:0 are annotated with their corresponding mass accuracy.
Supplementary information
Supplementary Information
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Supplementary Tables 1–5
Supplementary Table 1. Clinical data of human participants who donated healthy lung tissue, protocol S57123 (UZ Leuven). Supplementary Table 2. Clinical data of patients from the UPTIDER program. Supplementary Table 3. Clinical data comparison between primary metastasized and non-metastasized patients in the CHEMOREL study. Supplementary Table 4. Clinical information and uni/multivariate analysis of TCGA and METABRIC datasets. Supplementary Table 5. Primers used to analyze mRNA levels by qPCR.
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Altea-Manzano, P., Doglioni, G., Liu, Y. et al. A palmitate-rich metastatic niche enables metastasis growth via p65 acetylation resulting in pro-metastatic NF-κB signaling. Nat Cancer 4, 344–364 (2023). https://doi.org/10.1038/s43018-023-00513-2
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DOI: https://doi.org/10.1038/s43018-023-00513-2
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