1. Volume 26, Issue 5, Pages 778-787.e5 (November 2017)
PGC-1α Promotes Breast Cancer Metastasis and Confers Bioenergetic Flexibility against Metabolic Drugs 
Sylvia Andrzejewski, Eva Klimcakova, Radia M. Johnson, Sébastien Tabariès, Matthew G. Annis, Shawn McGuirk, Jason J. Northey, Valérie Chénard, Urshila Sriram, David J. Papadopoli, Peter M. Siegel, Julie St-Pierre 
Cell Metabolism 
Volume 26, Issue 5, Pages e5 (November 2017)
DOI: /j.cmet
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2. Cell Metabolism 2017 26, 778-787.e5DOI: (10.1016/j.cmet.2017.09.006)
Copyright © 2017 Elsevier Inc. Terms and Conditions

3. Figure 1
PGC-1α Expression Is Elevated in Breast Cancer Cells that Metastasize to the Lung and Bone
(A) Schematic of murine breast cancer cell lines of varying metastatic potential. 67NR are non-metastatic, 66cl4 are specifically lung metastatic, and 4T1 variants are metastatic to the bone (592, 590, and 593), liver (2776 and 2792), or lung (526, 533, and 537).
(B) Expression of Ppargc1a in derived cell lines of varying metastatic potential (n = 3).
(C) Expression of Ppargc1a in 4T1 variants that metastasize to the bone (592, 590, and 593), liver (2776 and 2792), and lung (526, 533, and 537) (n = 4).
(D) Mitochondrial respiration of 4T1 variants (n = 4).
(E) Schematic of the human MDA-MB-231 breast cancer cell variants that preferentially colonize the bone (1833), liver (6113), or lung (4175).
(F) Expression of PPARGC1A in MDA-MB-231 variants (n = 3). All data are represented as means ± SEM (∗p < 0.05 from parentals, one-way ANOVA, Dunnett’s multiple comparisons post-test).
(G) Schematic for developing a PGC-1α gene expression signature from human breast cancer cells. MDA-MB-231 lung metastatic variants (4175) were treated with an siRNA targeting PGC-1α or control and subjected to global gene expression profiling. The signature contains 1,329 differentially expressed genes. Heatmap shows differentially expressed genes clustered by Pearson dissimilarity (1-cor) distance using Ward clustering as the agglomeration method. Fold change in PPARGC1A mRNA expression in human lung metastatic MDA-MB-231 variant (4175) treated with siControl or siPGC-1α (n = 3, ∗p < 0.05, paired Student’s t test).
(H) PGC-1α signature (Table S3) gene set variation analysis (GSVA) enrichment scores in metastatic patient tissue samples from GEO: GSE14020 (Zhang et al., 2009). GSVA analysis calculates the relative enrichment of the PGC-1α signature across the sample space rather than the absolute enrichment with respect to a phenotype (Hänzelmann et al., 2013). This gives an enrichment score for each individual patient sample. The patient sample enrichment scores were divided into quartiles and separated by tissue compartment.
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4. Figure 2 PGC-1α Promotes Metastasis of Mammary Tumors to the Lung
(A and B) Representative migration (A) and invasion (B) assays of ErbB2-transformed murine breast cancer cells overexpressing PGC-1α (clones: PGC-1α-1.1 and PGC-1α-1.2) compared to empty vector control (Control).
(C and D) Quantification of migration (C) (n = 6) and invasion (D) (n = 10) as a function of cell index over time (one-way ANOVA, Tukey’s multiple comparison test).
(E) Mammary tumor growth of ErbB2-transformed murine breast cancer cells overexpressing PGC-1α (PGC-1α-1.1, n = 6) injected into the fat pads of SCID beige mice compared to empty vector controls (Control, n = 6). Mammary tumors were grown to a volume of 350 mm3 and resected (horizontal line). Average tumor volumes are plotted.
(F and G) Representative images of hematoxylin and eosin (H&E)-stained lung tissues using two experimental approaches: a spontaneous lung metastasis assay (F) in which control or PGC-1α-overexpressing cells were injected into the fat pads of SCID beige mice, breast tumors formed, and lung metastases were visualized, and a tail vein injection assay (G) in which control or PGC-1α-overexpressing cells were injected into the tail vein of SCID beige mice and lung metastases were visualized. Yellow lines outline metastatic regions; scale bar, 2 mm.
(H) Quantification of spontaneous lung metastasis in control or PGC-1α-overexpressing cells as measured by the metastatic lesion area as a percentage of total lung area (n = 6).
(I) Quantification of lung metastasis via tail vein injection assay in control or PGC-1α-overexpressing cells as measured by the metastatic lesion area as a percentage of total lung area (n = 8).
(J) Quantification of percent (%) positive nuclei after Ki67 staining in lung tissue from tail vein injections of control or PGC-1α-overexpressing cells as an indicator of proliferative index. Representative images of Ki67-stained lungs are shown; scale bar, 50 μM (control, n = 9; PGC-1α, n = 9).
(K) Ppargc1a expression in explanted cells from primary mammary tumors (n = 3), lung metastasis (spontaneous n = 6), and lung metastasis of tail vein injection assay (n = 8), for both control (Control) and PGC-1α-overexpressing cells (PGC-1α) compared to control clones (∗significant from respective control, #significant from primary tumors, one-way ANOVA, Dunnett’s multiple comparisons post-test).
(L) Total and uncoupled respiration of lung metastatic explants (1 and 2) overexpressing PGC-1α from a spontaneous lung metastasis assay normalized to controls (n = 6).
(M) Total and uncoupled respiration of lung explants (1 and 2) from tail vein injection normalized to controls (n = 4). All data are represented as means ± SEM; unpaired Student’s t test unless otherwise specified, ∗p < 0.05, #p < 0.05.
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5. Figure 3
PGC-1α Promotes Breast Cancer Lung Metastasis Independently of Mitochondrial Oxidative Phosphorylation and Stimulates Bioenergetic Flexibility
(A) Quantification of lung metastasis area in SCID beige mice injected with ErbB2-transformed murine breast cancer cells overexpressing PGC-1α (PGC-1α) or empty vector controls (Control) by tail vein injection, treated daily with phenformin or control (PBS). Metastatic lesion area is quantified as a percentage of total lung area. Each point represents an average of four individual steps quantified per mouse (n = 8, control/PBS; n = 8, control/phenformin; n = 7, PGC-1α/PBS; n = 7, PGC-1α/phenformin).
(B) Principal component analysis (PCA) of gene expression data from metastatic lung lesions of experiments shown in (A) with the percentage of variation shown for the three first principle components.
(C) Venn diagram showing differentially expressed and overlap of genes across all experimental conditions. The number of significant genes is indicated.
(D) Enrichment scores for significantly upregulated pathways upon phenformin exposure.
(E) Mitochondrial respiration of NMuMG-ErbB2/VC (control) or NMuMG-ErbB2/PGC-1α (PGC-1α) cells treated with metformin (0.5 or 5.0 mM) or control (ddH2O) for 24 hr, normalized to untreated control (ddH2O) (n = 3, ∗compared to respective untreated condition, #compared to respective condition in control cells).
(F and G) Fold change in glucose consumption (F) and lactate production (G) upon metformin treatment (0.5 and 5 mM) for 24 hr. Data are normalized to untreated control (ddH2O) (n = 4, ∗compared to respective untreated condition, #compared to respective condition in control cells).
(H and I) Proportional ion abundance of DHAP, pyruvate, and lactate (H) and citrate, malate, and fumarate (I) following a pulse with [3-13C]-glucose (n = 3).
(J) Quantification of total ATP production (J ATP total) for NMuMG-ErbB2/VC (control) and NMuMG-ErbB2/PGC-1α (PGC-1α) cells under basal conditions (minimal XF media) as well as after the addition of glucose (10 mM), using a Seahorse XF24 Extracellular Analyzer. J ATP total is the sum of J ATP oxidative and J ATP glycolytic, where J ATP oxidative is ATP derived from oxidative phosphorylation and J ATP glycolytic is ATP derived from glycolysis (n = 4, ∗for J ATP oxidative and #for J ATP total, paired Student’s t test).
(K) Bioenergetic capacity of NMuMG-ErbB2/VC (control, dark yellow box) and NMuMG-ErbB2/PGC-1α (PGC-1α, light yellow box). Circles (control) and squares (PGC-1α) represent points in the bioenergetic space as a function of J ATP glycolytic and J ATP oxidative under basal conditions (white), addition of glucose (red), FCCP (orange), and monensin (yellow).
(L) Quantification of bioenergetic capacity for control and PGC-1α-overexpressing cells as a function of maximum J ATP glycolytic and maximum J ATP oxidative (n = 4, paired Student’s t test).
(M and N) Supply flexibility index for control (M) and PGC-1α (N) cells, calculated from the bioenergetic capacity graph in (K). The solid lines represent movement under various substrate conditions while maintaining constant total J ATP. The angle shown is used to calculate the supply flexibility index. All data are represented as means ± SEM; two-way ANOVA, Tukey’s multiple comparison test, unless otherwise specified, ∗p < 0.05, #p < 0.05.
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6. Figure 4 PGC-1α Promotes Resistance to Bioenergetic Stressors
(A) Schematic describing the generation of metformin-resistant cells using lung metastatic 4T1 variant cell population (537). 537 cells were passaged into two plates, where one was maintained in media with vehicle (ddH2O: control) and the other was treated with increasing doses of metformin (2.5, 5, 10, 15, and 25 mM) for a period of 28 days (resistant model). Resistant cells were maintained in 25 mM metformin.
(B) Ppargc1a expression in 537 control (sensitive) and resistant cells (n = 6).
(C) Fold change in Ppargc1a expression in resistant cells upon acute removal of metformin (n = 3).
(D) Fold change in mitochondrial respiration in 537 resistant cells, normalized for control (sensitive) cells (n = 6).
(E) Fraction of mitochondrial respiration devoted to coupled respiration that represents respiration coupled to the production of ATP and uncoupled respiration that drives proton leak reactions (n = 4).
(F and G) Glucose consumption (F) and lactate production (G) of 537 control and resistant cells, normalized to control cells (n = 3).
(H) Stable isotope tracing analysis of glycolytic metabolites in 537 control and resistant cells following a pulse with [U-13C]-glucose (n = 3).
(I) Live cell counts of control and resistant cells, as well as control cells grown for 3 days in 5 and 25 mM metformin (n = 3).
(J) Quantification of live cell counts on day 3 of the growth curve presented in (I), represented as a fold change of untreated control cells (n = 3, one-way ANOVA, Tukey’s multiple comparison test).
(K) Stable isotope tracing analysis of citric acid cycle metabolites in 537 control and resistant cells following a pulse with [U-13C]-glucose. m+2 isotopomers (green) represent canonical citric acid cycle, while m+3 isotopomers (blue) are indicative of anaplerotic reactions (n = 3).
(L) Schematic describing the generation of 537 shControl and shPGC-1α metformin-resistant cell lines.
(M) Fold change of Ppargc1a expression in 537 shControl and shPGC-1α cells sensitive or resistant to metformin, normalized to their respective control (n = 3).
(N and O) Live cell counts of 537 shControl and shPGC-1α cells under normal culturing conditions (N) or upon acute exposure to 25 mM metformin (n = 3) (O).
(P) Live cell counts of 537 shControl and shPGC-1α-resistant cells (n = 3). All data are represented as means ± SEM; ∗p < 0.05, paired Student’s t test unless otherwise specified.
Cell Metabolism  , e5DOI: ( /j.cmet )
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