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Compartmentalized activities of the pyruvate dehydrogenase complex sustain lipogenesis in prostate cancer

Nature Genetics volume 50, pages 219–228 (2018)Cite this article

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A Publisher Correction to this article was published on 08 August 2018

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Abstract

The mechanisms by which mitochondrial metabolism supports cancer anabolism remain unclear. Here, we found that genetic and pharmacological inactivation of pyruvate dehydrogenase A1 (PDHA1), a subunit of the pyruvate dehydrogenase complex (PDC), inhibits prostate cancer development in mouse and human xenograft tumor models by affecting lipid biosynthesis. Mechanistically, we show that in prostate cancer, PDC localizes in both the mitochondria and the nucleus. Whereas nuclear PDC controls the expression of sterol regulatory element-binding transcription factor (SREBF)-target genes by mediating histone acetylation, mitochondrial PDC provides cytosolic citrate for lipid synthesis in a coordinated manner, thereby sustaining anabolism. Additionally, we found that PDHA1 and the PDC activator pyruvate dehydrogenase phosphatase 1 (PDP1) are frequently amplified and overexpressed at both the gene and protein levels in prostate tumors. Together, these findings demonstrate that both mitochondrial and nuclear PDC sustain prostate tumorigenesis by controlling lipid biosynthesis, thus suggesting this complex as a potential target for cancer therapy.

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Fig. 1: Pdha1 knockout induces tumor suppression in mice and in human prostate tumors.
Fig. 2: Pdha1 inactivation induces tumor suppression by downregulating lipogenic genes.
Fig. 3: Pdha1 knockdown induces tumor suppression by abrogating lipogenesis.
Fig. 4: Nuclear PDC regulates the expression of lipid-biosynthesis genes independently of mitochondrial PDC.
Fig. 5: Nuclear PDC regulates fatty acid synthesis in the presence of mitochondrial citrate.

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  • 08 August 2018

    In the HTML version of this article initially published, the name of author Diletta Di Mitri was miscoded in the XML such that Di was included as part of the given name instead of the family name. The error has been corrected in the HTML version of the article.

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Acknowledgements

We thank all members of the IOR/IRB animal core facility for technical assistance and animal work, and M. Yuan and S.B. Breitkopf for help with metabolomic analysis. The mass spectrometry work was partially supported by NIH grants P01-CA120964 (J.M.A.) and P30-CA006516 (J.M.A.). Cholesterol measurements in prostate cancer cell lines were supported by an AIRC Investigator Grant (IG 2016 ID 19104) and a CARIPARO Pediatric Research Grant. The work of A.M. was funded by Fondazione Umberto Veronesi and Associazione Italiana Ricerca sul Cancro and Fondazione Cassa di Risparmio di Firenze (grant 19515 to P.C. and A.M.) and AIRC (grant 8797 to P.C.). We thank E. Ragazzi (Department of Pharmaceutical and Pharmacological Sciences, University of Padova) for multivariate statistical analysis. The work of A. Carracedo was supported by the Department of Education of the Basque Government (IKERTALDE IT1106-16), the BBVA Foundation, the MINECO (SAF2016-79381-R (FEDER/EU), Severo Ochoa Excellence Accreditation SEV-2016-0644) and the European Research Council (Starting Grant 336343, PoC 754627). The participation of A. Carracedo as part of CIBERONC was cofunded with FEDER funds. This work was supported by a Swiss National Science Foundation (SNF) grant Ambizione (PZ00P3_136612/1), a European Research Council Starting Grant (ERCsg 261342), a European Society for Medical Oncology (ESMO) Translational Research Award to A. Alimonti, a Dr. Josef Steiner Cancer Research Award and a Swiss Bridge Award to A. Alimonti, and a Fondazione IBSA fellowship award to J.C. We thank N.J. Maitland (University of York) and D. Peeper (Netherlands Cancer Institute) for providing reagents.

Author information

Authors and Affiliations

  1. Institute of Oncology Research, Oncology Institute of Southern Switzerland, Università della Svizzera Italiana, Bellinzona, Switzerland

    Jingjing Chen, Ilaria Guccini, Diletta Di Mitri, Daniela Brina, Ajinkya Revandkar, Manuela Sarti, Emiliano Pasquini, Abdullah Alajati, Sandra Pinton, Marco Losa, Gianluca Civenni, Carlo V. Catapano, Andrea Rinaldi, Francesco Bertoni & Andrea Alimonti

  2. Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland

    Jingjing Chen, Ajinkya Revandkar & Andrea Alimonti

  3. Computational Structural Biology, Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland

    Jacopo Sgrignani & Andrea Cavalli

  4. Imaging Facility, Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland

    Rocco D’Antuono

  5. Division of Signal Transduction, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA

    John M. Asara

  6. Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence, Italy

    Andrea Morandi & Paola Chiarugi

  7. Nano-inspired Biomedicine Lab, Institute of Paediatric Research–Città della Speranza, Padova, Italy

    Sara Crotti & Marco Agostini

  8. Surgical Clinic, Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, Padova, Italy

    Marco Agostini

  9. Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy

    Monica Montopoli

  10. CNR Institute of Neuroscience and Department of Biomedical Sciences, University of Padova, Padova, Italy

    Ionica Masgras & Andrea Rasola

  11. Molecular Oncology Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain

    Ramon Garcia-Escudero

  12. Biomedical Research Institute I+12, University Hospital 12 de Octubre, Madrid, Spain

    Ramon Garcia-Escudero

  13. Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain

    Ramon Garcia-Escudero & Arkaitz Carracedo

  14. Roegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway

    Nicolas Delaleu

  15. Drug Development Unit, Division of Cancer Therapeutics and Division of Clinical Studies, Royal Marsden NHS Foundation Trust and Institute of Cancer Research, London, UK

    Johann de Bono

  16. CIC bioGUNE, Bizkaia Technology Park, Bizkaia, Spain

    Arkaitz Carracedo

  17. Ikerbasque, Basque Foundation for Science, Bilbao, Spain

    Arkaitz Carracedo

  18. Biochemistry and Molecular Biology Department, University of the Basque Country, Bilbao, Spain

    Arkaitz Carracedo

  19. Department of Medicine, Venetian Institute of Molecular Medicine, University of Padova, Padova, Italy

    Andrea Alimonti

Authors
  1. Jingjing Chen
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  2. Ilaria Guccini
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  3. Diletta Di Mitri
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  4. Daniela Brina
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  8. Abdullah Alajati
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  27. Francesco Bertoni
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  28. Johann de Bono
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  29. Arkaitz Carracedo
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  30. Andrea Alimonti
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Contributions

J.C. and A. Alimonti conceived the project, designed the experiments, interpreted the data and wrote the paper. J.C., I.G., D.D.M., D.B., A. Revandkar and A. Alajati performed experiments and analyzed the data. J.C. performed crosses and generated the transgenic mouse model. G.C., E.P., C.V.C. and J.C. performed experiments on the xenograft mouse model. A. Alajati, S.P., M.L., M.S. and J.d.B. performed immunohistochemical experiments and analysis. R.D. and J.C. established and carried out fluorescence microscopy. J.M.A. and J.C. conducted metabolomic and lipidomic analysis on mouse prostate tumors. S.C., M.A., M.M. and J.C. performed cholesterol measurements in prostate cancer cell lines. A.M. and P.C. performed 14C tracing experiments and interpreted the data. I.M. and A. Rasola carried out mitochondrial OCR measurements. J.S. and A. Cavalli conducted computational structural analysis. A. Rinaldi, N.D. and F.B. performed gene expression profiling on mouse tumors and GSEA analysis of metabolic pathways on mouse tumors. R.G.-E. provided bioinformatic analysis on PDHA1 and PDP1 amplification and overexpression in human prostate cancer datasets. A. Carracedo provided support on metabolic analysis, interpretation of results and discussion.

Corresponding author

Correspondence to Andrea Alimonti.

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Integrated supplementary information

Supplementary Figure 1 Pdha1 knockout induces tumor suppression in mouse prostate tumors.

(a) The efficiency of Probasin-Cre4 (Pb-Cre4) mediated recombination of the PtenloxP/loxP and Pdha1loxP/Y allele as scored by PCR amplification in wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours. (n = 3, independent prostate samples) (b) Quantitative real time-PCR analysis of mRNA expression of Pdha1, Dlat, Dld and Pdha1 regulator genes in Ptenpc-/- prostate tumours versus wild type prostate tissues (n = 3, independent prostate samples). (c-d) Representative micrographs in histopathological analysis (haematoxylin/eosin staining and indicated proteins) of anterior prostates (AP) (n = 3, independent prostate samples, 5 fields for each group, scale bar represents 50 µm) (c) and representative micrographs of senescence associated β-Gal (SA- β-Gal) staining (n = 3 independent prostate samples, 5 fields for each group and scale bar represents 50 µm) (d) in wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours. (e, f) Apoptosis analysis by cleaved caspase 3 (e) and quantification of the percentage of cleaved caspase 3 positive cells (f) of anterior prostates (AP) in 12-week-old Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y tumours (N: small necrotic foci, n = 3 mice, 5 fields for each group and scale bar represents 50 µm). (g-j) Relative cell number quantification by crystal violet staining (g), senescence associated β-Gal (SA-β-Gal) staining (h), cellular apoptosis assay by Annexin V staining (i) and western blot analysis of indicated proteins (j) of wild type, Pdha1-/-, Pten-/- and Pten-/-; Pdha1-/- MEFs on 6th day after retroviral Cre infection and selection. Uncropped images are in Supplementary Figure 13. (n = 3, independent cell cultures). Error bars indicate s.e.m. *P < 0.05; **P < 0.01. n.s, not significant.

Supplementary Figure 2 PDHA1 and PDP1 are frequently amplified and overexpressed in human prostate cancer.

(a-c) The number of datasets (a), bar graph of amplification or overexpression of these datasets and underlined are comparisons (7 out of 24) where both genes are gained/amplified or overexpressed (b) and sample number in indicated comparison and P value (c) from Oncomine or cBioPortal cohorts by which significant copy-number gain or amplifications (DNA) or overexpression (mRNA) exits when the following comparisons are computed: i, DNA, primary versus normal germline; ii, DNA, metastasis versus primary; iii, DNA, metastasis versus normal germline; iv, mRNA, primary versus normal prostate glands and v, mRNA, metastasis versus primary. Significant overexpression or copy number values are computed using T-test (two-tailed, P<0.05, in ii, iv and v), or using GISTIC or RAE (in i and iii). (d,e) Alteration frequency analysis of PDHA1 (d) and PDP1 (e) from 11 studies on prostate cancers available on cBioPortal.

Supplementary Figure 3 PDHA1 and PDP1 are overexpressed in human prostate cancer cell lines and tumors.

(a) Representative immune-histochemical staining for PDHA1, phospho-PDHA1293 and PDP1 in a prostate cancer tissue microarray (TMA) of 128 patients (5 fields acquired for each sample, PIN indicates prostatic intraepithelial neoplasia, HGPIN indicates high-grade prostatic intraepithelial neoplasia, PCA indicates invasive prostate cancer, and scale bar represents 50 µm) (b-d) Evaluation and quantification of immune-histochemical staining for PDHA1 (b), PDP1 (c) and phospho-PDHA1293(d) in human tumour samples in panel (a). (e) Quantification of immune-histochemical staining of phospho-PDHA1293 in PDHA1 or PDP1 moderate/high expression samples. The gray frames highlighted the numbers of PDHA1 or PDP1 moderate/high expression samples (f) Upper panel, PDC activity measurements in prostate cancer cells using a standard quantitative dipstick assay (n = 3, independent cell cultures). Lower panel, western blot analysis of indicated proteins in prostate cancer cell lines. Uncropped images are in Supplementary Figure 14. (n = 3, independent cell cultures). (g) Quantification of western blots for PDHA1 and PDP1 in panel (f) (n = 3, independent cell cultures). (h) Mitochondrial oxygen consumption rate analysis of the indicated prostate cancer cell lines (n = 3, independent cell cultures). (i) Mitochondrial oxygen consumption rate analysis of 22Rv1 prostate cancer cell line in the media supplemented with glucose (11 mM), glutamine (2 mM) or a combination of these two (n = 3, independent cell cultures). (j,k) Cellular proliferation assay by BrdU staining (j) and cellular apoptosis assay by Annexin V staining (k) in cell lines infected with indicated shPDHA1 or scramble shRNA control (n = 3, independent cell cultures). (l) Mitochondrial oxygen consumption rate analysis of 22Rv1 prostate cancer cell line infected with shPDHA1 or scramble control. (n = 3, independent cell cultures). (m) Western blot analysis of PDHA1 in cell lines infected with doxycycline-induced Tripz-shPDHA1 or scramble control in Fig. 1 panel (h-j). Uncropped images are in Supplementary Figure 14. (n = 3, independent cell cultures). Error bars indicate s.e.m. *P < 0.05; **P < 0.01. n.s, not significant.

Supplementary Figure 4 Pdha1 inactivation decreases mitochondrial intermediates.

(a) Representative intermediates level in glycolysis and tricarboxylic acid (TCA) cycle of wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours (n = 3, independent prostate samples). (b-d) Determination of relative NADH/NAD+ ratio (b), ATP/ADP ratio (c) and acetyl coA levels (d) in wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours (n = 3, independent prostate samples). (e,f) Determination of extracellular lactate levels (e) and acetyl coA levels (f) in wild type, Pdha1-/-, Pten-/- and Pten-/-; Pdha1-/- MEFs (n = 3, independent cell cultures). (g) Representative data depict abundance of selected labelled metabolites from [U-13C6]-Glucose, [U-13C5]-Glutamine and [U-13C16]-palmitate respectively in mouse prostate epithelial cells derived from wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours. Glucose, glutamine and Palmitate metabolism profiles were presented as actual intensities. (n = 3, independent prostate samples). Error bars indicate s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001. n.s, not significant.

Supplementary Figure 5 PDC controls histone acetylation and the expression of genes that link reductive carboxylation to lipogenesis.

(a) Upper left panel, PDC activity measurements of nuclear and cytoplasmic fractions of Ptenpc-/- tumours loaded in different amount in standard dipstick assay. Upper right panel, fractionation was validated by western blot analysis for the indicated proteins. Lower panel, quantification of the optical density of dipstick bands from the upper left panel. The dash line represents the amount of lysate (80 μg) used in all the measurements performed in the paper, which fall in the linear range of the assay (n = 3, independent prostate samples). Uncropped images are in Supplementary Figure 14. (b) PDC activity measurements in nuclear fractions of Ptenpc-/- tumour cells incubated in presence of pyruvate at the indicated concentration in the activity buffer (n = 3, independent prostate samples). (c) Western blot analysis of indicated proteins in nuclear and cytoplasmic fractions in wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours (n = 3, independent prostate samples). Uncropped images are in Supplementary Figure 14. (d-f) Quantitative real time-PCR analysis of mRNA expression for Isocitrate dehydrogenase isozymes in mouse prostate tissues of indicated genotypes (n = 3, independent prostate samples) (d) and 22Rv1(e) and PC3(f) cells infected with shPDHA1 or scramble shRNA control (n = 3, independent cell cultures). (g) Schematic overview of Pyruvate dehydrogenase, tricarboxylic acid cycle, β-oxidation, glutaminolysis and lipogenesis pathways (The green represents down-regulated genes). (h,i) Schematic overview of primer sites of for H3K9Ac and the binding of SREBP1 detection on the ACLY (h) and SQLE (i) promoters. H3K27Ac profile (UCSC Genome Browser on Human Feb. 2009 (GRCh37/hg19) Assembly) was used for prediction of H3K9Ac status. (j,k) Chromatin immunoprecipitation analysis of H3K9Ac levels on the promoter of E2F1 (j) and CCND1 (k) in 22Rv1 and PC3 cells infected with doxycycline-induced Tripz-shPDHA1 or scramble control (n = 3, independent cell cultures). (l) Western blot analysis of indicated proteins in shPDHA1 or scramble control 22Rv1 cells infected with ACLY over-expressing lentivirus vector or empty vector control (EV) and treated with 100 μM citrate or vehicle over a 9-day period. Uncropped images are in Supplementary Figure 15. (n = 3, independent cell cultures). (m,n) Relative cell number quantification by crystal violet staining of shPDHA1 or scramble control 22Rv1 (m) and PC3 (n) cells infected with ACLY over-expressing lentivirus vector or empty vector control (EV) and treated with 100 μM citrate or vehicle over a 9-day period (n = 3, independent cell cultures). Error bars indicate s.e.m. *P < 0.05; **P < 0.01; n.s, not significant.

Supplementary Figure 6 PDC inactivation decreases lipid and cholesterol levels in prostate cancer.

a) A scatterplot Log10 intensity of Ptenpc-/-; Pdha1pc-/Y tumours vs. Log2 Ratio of Ptenpc-/-; Pdha1pc-/Y tumours versus Ptenpc-/- tumours showing the distribution of 2,062 identified lipid ions (blue dots) including cholesterol esters (red dots) via LipidSearch from lipids extracted from three biological replicates of Ptenpc-/-; Pdha1pc-/Y tumours and Ptenpc-/- tumours tissue extracts (~5 mg injected). ChE represents Cholesteryl esters (n = 3, independent prostate samples) (b,c) The relative abundance of lipid species by intensity in wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours (n = 3, independent prostate samples). The top three lipids in fold change between Ptenpc-/- tumours and wild type prostate were labeled as red. The lipid classes and abbreviations: Ceramide (Cer), Cholesteryl ester (ChE), Diradylglycerolipids (DG), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), lysylphosphatidylglycerol (LPG), lysophosphatidylinositol (LPI), lysophosphatidylserine (LPS), lysodimethylphosphatidylethanolamine (LdMeP), Monoradylglycerolipids (MG), (O-acyl)-omega-hydroxy fatty acids (OAHFA), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylethanolamine (PE), Phosphatidylglycerol (PG), phosphatidylinositol (PI), phosphomonoesters (PMe), phosphatidylserine (PS), Sphingomyelin (SM), Triglyceride (TG), dimethylphosphatidylethanolamine (dMePE). (d-f) The relative abundance of lysylphosphatidylglycerol (LPG) (d), phosphomonoesters (PMe) (e), Cholesteryl ester (ChE) (f) species in wild type, Pdha1pc-/Y, Ptenpc-/- and Ptenpc-/-; Pdha1pc-/Y prostates and tumours (n = 3, independent prostate samples). (g,h) Significantly changed levels of cholesterol (COH) and 14 Cholesteryl esters (CE) in 22Rv1 (g) and PC3 (h) cells infected with two shPDHA1 or a scramble shRNA control (n = 3, independent cell cultures). The Variable Importance in Projection (VIP) scores depicting the top-ranked metabolites that contributed to the separation of prostate cancer cells infected with two shPDHA1 and a scramble control. A value of VIP score greater than 1 suggests actual contribution of the considered lipid to the group separation. The coloured boxes on the right indicate the relative concentrations of the corresponding metabolite in each group under study. The scale bar depicts the relative metabolite levels (red, high abundance; blue, low abundance). Error bars indicate s.e.m. *P < 0.05; n.s, not significant.

Supplementary Figure 7 Pdha1 inactivation mainly affects de novo lipid synthesis in prostate cancer.

(a) Scheme of radioactive 14C tracing using D- [U-14C6]-Glucose (14C-Glucose) and L-[U-14C5]-Glutamine (14C-Glutamine) measuring glucose and glutamine incorporation into lipids. (b,c) Radioactive tracing using 14C- glucose (b) and 14C-glutamine (c) for de novo lipogenesis in 22Rv1 and PC3 cells infected with two shPDHA1 and scramble shRNA control (n = 3, independent cell cultures). (d,e) Radioactive tracing using 14C- glucose (d) and 14C-glutamine (e) for de novo cholesterol synthesis in 22Rv1 and PC3 cells infected with two shPDHA1 and scramble shRNA control (n = 3, independent cell cultures). (f,g)Radioactive tracing using 14C- glucose (d) and 14C-glutamine (e) in protein synthesis in 22Rv1 and PC3 prostate cancer cell line infected with shPDHA1 or scramble shRNA control (n = 3, independent cell cultures). (h,i) Glucose uptake (h) and glutamine uptake (i) analysis in 22Rv1 and PC3 cells infected with shPDHA1 or scramble shRNA control (n = 3, independent cell cultures). (j-l) Confocal microscopy quantification of intra-tumour lipid droplets by average lipid droplets total fluorescence (a.u.) (j) average lipid droplets per mm2 (k) and average lipid droplet area in µm2 (l) in the indicated genotypes (n = 3 independent prostate samples, 5 fields acquired for each group) in Ptenpc-/-; Pdha1pc-/Y versus Ptenpc-/- prostate tumours. DAPI, blue. Scale bar: 20 µm (n = 3 independent prostate samples, 5 fields acquired). (m-o) Confocal microscopy quantification of intra-tumour lipid droplets by average lipid droplet total fluorescence (a.u.) (m) average lipid droplets per mm2 (n) and average lipid droplet area in µm2 (o) in 22Rv1 and PC3 shPDHA1 and shRNA xenograft tumours. DAPI, blue. (n = 3, independent prostate samples, 5 fields acquired and scale bar represents 20 µm). (p) Western blot analysis of indicated proteins in 22Rv1 cells infected with shPDHA1 or scramble control and treated with exogenous fatty acids in fatty acid-free media; oleate (25μM), palmitate (25 μM) or a combination of these two over a 6-day period. Uncropped images are in Supplementary Figure 15. (n = 3, independent cell cultures). Error bars indicate s.e.m. **P < 0.01; ***P < 0.001. n.s, not significant.

Supplementary Figure 8 Both nuclear PDC and mitochondrial PDC are required for prostate cancer cell proliferation.

a-g) Representative images of confocal microscopy for PDHA1 and the N-terminus mature form of SREBF1 (n = 3, independent cell cultures, 5 fields acquired for each group and scale bar represents 10 μm) (a), western blot analysis of indicated proteins (n = 3) (b), representative images of PDHA1 and lipid droplets in confocal microscopy. Uncropped images are in Supplementary Figure 15. (n = 3, independent cell cultures, 5 fields acquired for each group and scale bar represents 50 μm) (c), evaluation of tumour formation in xenotransplantation experiments (n = 6, independent tumour samples) (d), tumour mass in xenotransplantation experiments (n = 6, independent tumour samples) (e), representative micrographs in histopathological analysis (haematoxylin/eosin staining and indicated proteins) in xenotransplantation experiments (n = 6, independent tumour samples, 5 fields acquired for each group and scale bar represents 50 µm) (f) and quantification of the percentage of Ki-67 positive cells in xenotransplantation experiments (n = 6, independent tumour samples) (g) of shPDHA1 or shRNA control 22Rv1 cells infected with NES-PDHA1, NLS-PDHA1 alone or in combination. (h) Western blot analysis of indicated proteins in the 22Rv1 cells infected with two shPDHA1 and a scramble shRNA control and treated with SB-204990, a selective ACLY inhibitors at the dose of 30 μM which effectively arrest cell growth as shown in panel (i) in this figure or vehicle for 9 days (n = 3, independent cell cultures). Uncropped images are in Supplementary Figure 15. (i,j) the relative cell number quantification of the 22Rv1 cells (i) and PC3 cells (j) infected with two shPDHA1 and a scramble shRNA control and treated with SB-204990, a selective ACLY inhibitors at the dose of 30 μM for 9 days (n = 3, independent cell cultures). Error bars indicate s.e.m. *P < 0.05; **P < 0.01. n.s, not significant.

Supplementary Figure 9 Mitochondrial PDC inhibition compromises prostate cancer cell proliferation, decreasing citrate production.

(a) Relative cell number quantification by crystal violet staining of shPDHA1 or shRNA control 22Rv1 or PC3 cells infected with NES-PDHA1 and NLS-PDHA1 alone or in combination and treated with citrate (100 μM) or vehicle (n = 3, independent cell cultures). (b) Western blot analysis of indicated proteins in nuclear and cytoplasmic fractions in 22Rv1 cells infected with PDK1 or empty vector control. Uncropped images are in Supplementary Figure 15. (n = 3, independent cell cultures) (c-e) Tumour mass in xenotransplantation experiments (n = 6, independent tumour samples) (c), representative micrographs in histopathological analysis (haematoxylin/eosin staining and indicated proteins) (n = 6, independent tumour samples and scale bar represents 50 µm) (d) and relative cell number quantification by crystal violet (n = 3, independent cell cultures) (e) of shPDHA1 or shRNA control 22Rv1 cells infected with PDK1 or empty vector control. Error bars indicate s.e.m. *P < 0.05; **P < 0.01; ***P < 0.001. n.s, not significant.

Supplementary Figure 10 Pharmacological inhibition of PDHA1 arrests mouse and human prostate tumors.

(a,b) Representative structures, selected from MD simulations of the PDHA1/pyruvate (a) and PDHA1/3-FP (b) complexes. The a and b chains are represented as magenta and green ribbons, respectively. In the picture of PDHA1/3-FP complex, the fluorine atom is depicted in violet. Binding Delta G values, estimated by MM-GBSA, are also reported. (c) Upper panel, PDC activity measurements in the lysate from 22Rv1 cells treated with 3-FP or vehicle and supplemented with indicated amount of pyruvate in activity buffer of dipstick assay kit (n = 3, independent cell cultures). Lower panel, quantification of PDC activity by mean optical density of colored bands shown on dipsticks in upper panel (n = 3, independent cell cultures). (d) Body weight of mice of the indicated genotypes treated with 3-FP or vehicle from 8 weeks old for one month (n = 3, independent mice). (e) Upper panel, PDC activity measurements, and quantification in anterior prostate of indicated genotypes from mice treated with 3-FP or vehicle from 8 weeks old for one month (n = 3, independent prostate samples). Lower panel, quantification of PDC activity by mean optical density of colored bands shown on dipsticks in upper panel (n = 3, independent prostate samples). (f) Comparison of prostate lobe volumes from male mice at age of 12 weeks treated with 3-FP or vehicle for one month (mm3, 2 independent lobes per animal are presented. AP, anterior prostate; VP, ventral prostate; DLP, dorsal and lateral prostate, n = 3, independent prostate samples). (g-j) Representative micrographs of histopathological analysis (haematoxylin/eosin and Ki-67 staining) of anterior prostates (AP) in Ptenpc-/- prostate tumours (n = 3, independent prostate samples, 5 fields, and scale bar represents 50 µm) (g,h), quantification of the percentage of Ki-67 positive cells (n = 3 independent prostate samples, 5 fields) (i) and quantification of the percentage of invasive prostate cancer glands in Ptenpc-/- prostate tissue (n = 3, independent prostate samples, 5 fields) (j) from male mice at age of 8 weeks treated with 3-FP or vehicle for one month. (k) Upper panel, PDC activity measurements and quantification in nuclear and cytoplasmic fractions of prostate tumours of indicated genotypes from mice at age of 8 weeks treated with 3-FP or vehicle for one month (n = 3, independent prostate samples). Lower panel, fractionation was validated by western blot analysis for the indicated nuclear and cytosolic proteins. Uncropped images are in Supplementary Figure 15. (l) Western blot analysis of indicated proteins in prostate tumours from Ptenpc-/- mice at age of 8 weeks treated with 3-FP or vehicle for one month (n = 3, independent prostate samples). (m) Quantitative real time-PCR analysis of mRNA expression for Acly and Sqle from mice of indicated genotypes at age of 8 weeks treated with 3-FP or vehicle for one month (n = 3, independent prostate samples). Error bars indicate s.e.m. *P < 0.05; **P < 0.01. n.s, not significant.

Supplementary Figure 11 Pharmacological inhibition of PDHA1 arrests mouse and human prostate tumors.

(a) Integrating enrichment analysis and pathway topology analysis of metabolic pathways in prostate tumours from Ptenpc-/- mice at age of 8 weeks treated with or without 3-FP for one month (n = 3, independent prostate samples). (b-e) Quantification of confocal microscopy for lipid droplets (Lipidtox; red) by lipid droplet counts per cell (b), average lipid droplets fluorescence (a.u) (c), lipid droplet counts per mm2 (d), average lipid droplets area in µm2 (e) in wild type and Ptenpc-/- prostate tissues from 8 weeks old male mice treated with 3-FP or vehicle for one month (n = 3, independent prostate samples, 5 fields). (f,g) Relative cell number quantification by crystal violet staining (f) and PDC activity measurements (g) in indicated prostate cancer cell lines treated with 3-fluoropyruvic acid (3-FP) at the indicated concentration for 6 days (n = 3, independent cell cultures). (h-j) Evaluation of tumour formation and quantification of the percentage of Ki-67 positive cells in xenotransplantation experiment in LNCaP (h), 22Rv1 (i) and PC3 (j) cells treated with 3-FP or vehicle for two months (n = 6, independent tumour samples, 5 fields and scale bar represents 50 µm). (k) Schematic representation of the role of mitochondrial and nuclear PDH complex functions in regulating glucose influx of TCA cycle and controlling the diversion of TCA cycle intermediates (or glutamine derived anaplerosis pathway) into lipogenesis. (l) Metabolic landscape describing the functional relevance of PDC complex in regulating non-canonical tumour metabolism. Contrast to classic ‘Warburg effect' where cancers rely predominantly on glycolysis and catabolic TCA cycle gets restrained, tumours could achieve another ‘anabolism oriented' reprogramming/axis by upregulating PDC and promoting PDC nuclear translocation. Nuclear PDC controls the transitory process in TCA cycle by allowing the short-lived entry and exit of carbon pool in mitochondria to fuel citrate synthesis and lipogenesis. Taking advantage of this diversion caused by nuclear PDC, the tumour cells reduce carbon consumption in TCA cycle thereby benefiting proliferation. PDC inactivation arrests nuclear PDC active cancers by abrogating both glucose influx and potential anaplerosis pathways from reductive carboxylation and glutaminolysis. The blue represents the pathways controlled by PDC. Error bars indicate s.e.m. **P < 0.01; ***P < 0.001. n.s, not significant.

Supplementary Figure 12 Uncropped full-length pictures of western blotting membranes.

Uncropped full-length pictures of western blotting membranes presented in the main Fig. 1a, g, k, 2b and c. Membranes were often cut to enable blotting for multiple antibodies.

Supplementary Figure 13 Uncropped full-length pictures of western blotting membranes.

Uncropped full-length pictures of western blotting membranes presented in the main Fig. 4a, b, 5f and Supplementary Fig. 1j. Membranes were often cut to enable blotting for multiple antibodies.

Supplementary Figure 14 Uncropped full-length pictures of western blotting membranes.

Uncropped full-length pictures of Western blotting membranes presented in the Supplementary Fig. 3f, m, 5a and c. Membranes were often cut to enable blotting for multiple antibodies.

Supplementary Figure 15 Uncropped full-length pictures of western blotting membranes.

Uncropped full-length pictures of western blotting membranes presented in the Supplementary Fig. 5l, 7p, 8b, h, 9b and 10k. Membranes were often cut to enable blotting for multiple antibodies.

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Chen, J., Guccini, I., Di Mitri, D. et al. Compartmentalized activities of the pyruvate dehydrogenase complex sustain lipogenesis in prostate cancer. Nat Genet 50, 219–228 (2018). https://doi.org/10.1038/s41588-017-0026-3

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