supplementary material for€¦ · 7/9/2016 · 3 15n-leu amino acid defined diet: 50%...
TRANSCRIPT
www.sciencemag.org/content/353/6304/1161/suppl/DC1
Supplementary Material for
Tissue of origin dictates branched-chain amino acid metabolism in mutant Kras-driven cancers
Jared R. Mayers, Margaret E. Torrence, Laura V. Danai, Thales Papagiannakopoulos, Shawn M. Davidson, Matthew R. Bauer, Allison N. Lau, Brian W. Ji, Purushottam D. Dixit, Aaron M. Hosios, Alexander Muir, Christopher R. Chin, Elizaveta Freinkman,
Tyler Jacks, Brian M. Wolpin, Dennis Vitkup, Matthew G. Vander Heiden*
*Corresponding author. Email: [email protected]
Published 9 September 2016, Science 353, 1161 (2016) DOI: 10.1126/science.aaf5171
This PDF file includes:
Materials and Methods Figs. S1 to S10 Tables S1 to S8 Full Reference List
2
Materials and Methods Experimental Mice
All studies were approved by the MIT committee on animal care (IACUC). All experimental groups were assigned based on genotype. All animals were numbered and experiments conducted blinded. After data collection genotypes were revealed and animals assigned to groups for analysis.
KPC: Experimental KPC mice were male mice on a pure C57BL/6J background. Experimental mice were heterozygous for the conditional lox–stop–lox KrasG12D allele, heterozygous for the conditional lox–stop–lox Trp53R172H allele and expressed Cre–recombinase under control of the Pdx–1–promoter (Tg(Ipf1-cre)1Tuv) (26). Littermate controls lacked either the LSL–KrasG12D allele, the Cre allele, or both. Control mice were sacrificed at the same time as their tumor–bearing littermates.
KP–/–C (PDAC): Experimental KP–/–C mice were male mice on a pure C57BL/6J background. Experimental mice were heterozygous for the conditional lox–stop–lox KrasG12D allele, homozygous for loxP sites flanking exons 2–10 of Trp53 and expressed Cre–recombinase under control of the Pdx–1–promoter (Tg(Ipf1-cre)1Tuv) (19). Littermate control mice lacked either the Cre–recombinase allele, LSL–KrasG12D allele, or both as previously described (18), such that control pancreas samples used throughout were derived from a combination of p53 wildtype and null pancreata. Cancer cell lines derived from these mice were used for syngenic implantation studies. For FACS sorting, mixed background male mice with the KP–/–C alleles plus a LSL-tdTomato reporter gene expressed under control of the Rosa-26 promoter (Gt(ROSA)26Sor tm9(CAG-tdTomato)Hze/+) were used. Five-week old mice were used for the experiment presented in fig. S1, whereas 8-10-week-old mice were used for all other experiments presented in the study.
KP Non–small cell lung cancer: Experimental NSCLC mice were male mice on a pure C57BL/6J background. Experimental mice were heterozygous for the conditional lox–stop–lox KrasG12D allele, homozygous for loxP sites flanking exons 2–10 of Trp53 were administered 2.5x107 pfu of Cre–expressing adenovirus intratracheally as previously described (20). Control mice lacked the lox–stop–lox KrasG12D allele, but contained the floxed-Trp53 allele. High–titer adenovirus was obtained from the Gene Transfer Vector Core (University of Iowa). Cre was administered when the mice were 8-12 weeks of age. Cancer cell lines derived from these mice were used for syngenic implantation studies. Mice 8-weeks post-infection were used for the experiment presented in fig. S1, whereas mice 12-14-weeks post-infection were used for all other experiments presented in the study.
Subcutaneous and orthotopic implantation studies: Male C57BL/6J mice aged 6-12 weeks at the start of the study were used for these experiments.
Diets
Standard Chow Diet: RMH 3000 (Prolab). Amino Acid Defined Diet: Control (unlabeled) amino acid-defined diet (TD.110839) was
designed in consultation with and subsequently obtained from Harlan Teklad. 13C-BCAA Amino Acid Defined Diet: 20% 13C–leucine and 20% 13C–valine labeled diet was
based on diet TD.110839 and produced by Cambridge Isotopes and Harlan Teklad. KP–/–C PDAC mice and NSCLC mice were fed this diet for 7 days beginning at seven weeks of age (PDAC) and 12-weeks post infection with adenoviral Cre-recombinase (NSCLC).
3
15N-Leu Amino Acid Defined Diet: 50% 15N–leucine labeled diet was based on diet TD.110839 and produced by Cambridge Isotopes and Harlan Teklad. KP–/–C PDAC mice were fed this diet for 7 days beginning at seven weeks of age (PDAC). NSCLC mice were fed this diet for 6 days, beginning 12-weeks post infection with adenoviral Cre-recombinase (NSCLC).
Plasma Collection
Mice were anesthetized under 2% isofluorane–oxygen mixture and retro–orbitally bled approximately 4.5 hours after the onset of the light cycle. Blood was immediately placed in EDTA-tubes and centrifuged to separate plasma. Plasma was aliquoted and frozen at -80˚C for further analysis.
LC–MS Plasma Amino Acid Measurements
Plasma amino acids were measured by LC–MS at the Koch Institute at the Massachusetts Institute of Technology (Cambridge, MA) using methods previously described (18). Raw data were analyzed as peak area tops using the open–access MAVEN software tool (40). GC–MS Assessment of Stable Isotope Labeling
Plasma polar metabolites were extracted in ice–cold 4:1 methanol:water with norvaline internal standard (5µL plasma in 200µL extraction solution). Extracts were clarified by centrifugation and the supernatant evaporated under nitrogen and frozen at –80˚C for subsequent derivitization. Dried polar metabolites were dissolved in 20µL of 2% methoxyamine hydrochloride in pyridine (Thermo) and held at 37˚C for 1.5hr. After dissolution and reaction, tert–butyldimethylsilyl derivatization was initiated by adding 25µL N–methyl–N–(tert–butyldimethylsilyl)trifluoroacetamide + 1% tert–butyldimethylchlorosilane (Sigma) and incubating at 37˚C for 1hr.
All tissues used for metabolomic analysis were snap frozen using a BioSpec Biosquezer (#1210). To extract free polar metabolites, 10-30 mg of tissue was pulverized in liquid nitrogen using at Retsch Cryomill (#20.749.0001) and Retsch Cryomill Grinding Balls (#22.455.0002) for 2x 2min cycles at 25 Hz. Powdered tissue was extracted with 5:3:5 ice-cold methanol:water (with 13.3ng/µL Norvaline internal standard):chloroform. Extract was vortexted for 10min at 4˚C and centrifuged at for 10min at 20,000g at 4˚C in a benchtop centrifuge. An equal volume of the top (aqueous) phase was removed for each sample and evaporated under nitrogen and frozen at –80˚C for subsequent derivitization. Dried polar metabolites were dissolved in 1µL/mg tissue of 2% methoxyamine hydrochloride in pyridine (Thermo) and held at 37˚C for 1.5hr. After dissolution and reaction, tert–butyldimethylsilyl derivatization was initiated by adding 1.25µL/mg tissue N–methyl–N–(tert–butyldimethylsilyl)trifluoroacetamide + 1% tert–butyldimethylchlorosilane (Sigma) and incubating at 60˚C for 1hr.
The acid hydrolysis protocol was adapted from Antoniewicz and colleagues (41). Briefly, acid hydrolysis of tissue proteins was performed on snap frozen tissues by placing 1–5mg tissue in 1mL 18% hydrochloric acid overnight at 100˚C. 50µL supernatant was evaporated under nitrogen and frozen at –80˚C for subsequent derivitization. Dried hydrolysates were re–dissolved in pyridine (10µL/1mg tissue) prior to tert–butyldimethylsilyl derivatization, which was initiated by adding N–methyl–N–(tert–butyldimethylsilyl)trifluoroacetamide + 1% tert–butyldimethylchlorosilane (12.5µL/1mg tissue, Sigma) and incubating at 60˚C for 1h.
GC/MS analysis was performed using an Agilent 7890 GC equipped with a 30m DB–35MS capillary column connected to an Agilent 5975B MS operating under electron impact ionization
4
at 70eV. One microliter of sample was injected in splitless mode at 270°C, using helium as the carrier gas at a flow rate of 1mlmin−1. For measurement of amino acids, the GC oven temperature was held at 100°C for 3min and increased to 300°C at 3.5°Cmin−1. The MS source and quadrupole were held at 230°C and 150°C, respectively, and the detector was run in scanning mode, recording ion abundance in the range of 100–605 m/z. MIDs were determined by integrating the appropriate ion fragments (41) listed in table S7 and corrected for natural isotope abundance using an algorithm adapted from Ferandez and colleagues (42).
LC-MS Assessment of Stable Isotope Labeling
Tissue samples were collected and extracted as before. After drying the polar fraction, samples were resuspended in ice-cold 1:1 Acetonitrile:Water mix at 40µL/10mg tissue. LC/MS analyses were conducted on a QExactive benchtop orbitrap mass spectrometer equipped with a heated electrospray ionization (HESI) probe, which was coupled to a Dionex UltiMate 3000 UPLC system (Thermo Fisher Scientific, San Jose, CA). External mass calibration was performed using the standard calibration mixture every 7 days. For 13C-BCAA tracing in tissues, 2.5 µl of each sample was injected into the LC/MS. For 15N-BCAA tracing into nucleotides, 10 µl of each sample was injected into the LC/MS.
LC separation was performed on a ZIC-pHILIC 2.1 x 150 mm (5 µm particle size) column (EMD). Buffer A was 20 mM ammonium carbonate, 0.1% ammonium hydroxide; buffer B was acetonitrile. The chromatographic gradient was run at a flow rate of 0.150 ml/min as follows: 0-20 min.: linear gradient from 80% to 20% B; 20-20.5 min.: linear gradient from 20% to 80% B; 20.5-28 min.: hold at 80% B.
The mass spectrometer was operated with the spray voltage set to 3.0 kV, the heated capillary held at 275°C, and the HESI probe held at 350°C. The sheath gas flow was set to 40 units, the auxiliary gas flow was set to 15 units, and the sweep gas flow was set to 1 unit. For 13C-BCAA tracing in tissues, the MS data acquisition was performed in full-scan, polarity switching mode in a range of 70-1000 m/z, with the resolution set at 70,000, the AGC target at 106, and the maximum injection time at 20 msec. For 15N-BCAA tracing into nucleotides, the MS data were acquired in either positive or negative ion mode in a range of 285-385 m/z, with the resolution set at 140,000, the AGC target at 106, and the maximum injection time at 250 msec.
Relative quantitation of polar metabolites was performed with XCalibur QuanBrowser 2.2 (Thermo Fisher Scientific) using a 5 ppm mass tolerance and referencing an in-house library of chemical standards.
Tracer enrichment measurements were corrected for natural abundance for either 13C or 15N tracers as described by Yuan et al. (43).
Relative Abundance of Amino Acids in Tissue Samples
To determine the relative abundance of amino acids in the samples, protein hydrolysis with 18% hydrochloric acid was modified to include an amino acid internal standard mixture of U-13C and U-15N species (Cambridge Isotopes, # MSK-A2-1.2) at a final concentration of 100µM. The ratio of ion counts of unlabeled and fully labeled isotopomers of each amino acid was calculated. The fully labeled standards contain each amino acid at equal concentrations, so these calculated ratios represent their relative abundances. We therefore normalized the sum of these ratios to equal one to calculate the fraction of protein amino acids represented by each individual amino
5
acid. Cysteine and tryptophan residues are acid labile and not recoverable from the hydrolyzed samples.
DNA Isolation and Enzymatic DNA Digest
DNA was extracted using Phenol/Chloroform/Isoamyl extract mix (25:24:1 pH 8.0, Sigma P3803). DNA was precipitated with 0.1 volumes of 3M Sodium Acetate pH 5.2 and 3 volumes isopropanol overnight at -20°C. After pelleting and washing, DNA was resuspended in water. 20µL DNA was mixed with 6µL 100mM Succinic Acid-NaOH 50mM CaCl2 pH5.9, 0.1µL 0.02U/µL Bovine Spleen Phosphodiesterase II (Sigma P9041), 0.1µL 2000GelUnits/µL Micrococcal Nuclease (NEB 0247) and incubated at 37°C for 2.5 hrs. Reaction was then extracted with 90µL 2:1 Chloroform:Methanol and the resulting methanol fraction was evaporated under nitrogen. Sample was resuspended in 50:50 Acetonitrile:Water at 100ng/µL for Q-Exactive Mass Spectroscopic Analysis.
RNA Extraction and qPCR
Approximately 10-20mg of frozen tissue was homogenized (ProScientific Pro200) in Trizol (Life Technologies) and RNA extracted according to the manufacturer’s instructions. RNA concentration was determined using a Nanodrop (#ND1000) and 1µg of cDNA synthesized using iScript cDNA synthesis kit (BioRad). Quantitative-RT PCR was carried out on 5ng of cDNA using a final concentration of 2µM each of forward and reverse primers (table S8) with LuminoCt SYBR Green qPCR ReadyMix on a Roche Lightcycler II qPCR machine. Samples were normalized to the geometric mean of a panel of endogenous control genes (table S8) as previously described (44).
FACS Sorting and RNA isolation from Sorted Cells
Tumors were digested with 3mg/mL Dispase II (Roche), 1 mg/mL Collagenase I (Sigma), and 0.1mg/mL DNAse I (Sigma) in PBS for 30 mins at 37°C. To halt digestion, EDTA was then added to a final concentration of 10mM EDTA. Cells were strained through 70uM strainers and resuspended in flow cytometry staining buffer (eBioscience). Sytox Red (Life Technologies) was used for live/dead staining. Cell sorting was performed with a BD FACSAria III. RNA was isolated using the Ambion RNAqueous-Micro Total RNA Isolation Kit.
Protein Immunoblots
Approximately 20-30mg of frozen tissue was homogenized in RIPA buffer containing Protease Inhibitor Cocktail Tablets (Roche). Lysates were clarified by centrifugation in a benchtop centrifuge (Eppendorf Centrifugre 5145R) at 4˚C. Following clarification, protein concentration was determined using Bradford Protein Assay Dye (BioRad). All samples were run on SDS-acrylamide gels. After transfer to PVDF membrane and blocking in 5% BSA, blotting was performed using primary antibodies against Slc7a5 (Bioss, #bs-10125R), Bcat1 (Abcam, #ab110761), Bcat2 (Pierce Biotechnology, #PA5-21549), Bckdha (Novus Biologicals, #NBP1-79616), Hsp90 (Cell Signaling, #4877) and Vinculin (Sigma, # V9131). Secondary antibodies were goat anti-rabbit-HRP and goat-anti mouse (EMG Millipore). Western blot quantification was performing using ImageJ Image Analysis Software (NIH). Levels of BCAA catabolic enzymes were normalized to levels of vinculin and Hsp90.
6
Microarray expression data sets Microarray expression data sets for pancreatic ductal adenocarcinoma, non-small cell lung
cancer, and normal tissue were obtained from the NCBI GEO database (30) (accession numbers GSE15471, GSE16515, GSE71989 for pancreas samples and GSE18842 for lung samples) and were restricted to those using Affymetrix U133 Plus 2.0 GeneChips. The affyQCReport package from Bioconductor was used to search for poor quality chips. GeneChip arrays that passed quality control checks were normalized using the GCRMA (45) algorithm from Bioconductor. For each cancer type, tumor and normal samples from the same study were processed together.
The limma (46) method from Bioconductor was used to calculate differential expression of metabolic genes with results reported as ratios on the log2 scale. P-values for differential expression were corrected for multiple hypothesis testing using the Benjamini and Hochberg method (47), controlling for false discovery rate at 5%. Expression changes of all human genes assigned to metabolic pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) (48) database were analyzed in addition to those assigned to the BCAA catabolic pathway.
TCGA RNA-seq data sets
Raw read counts were obtained from the Broad Firehose (https://gdac.broadinstitute.org/) LUAD and LUSQ January 28, 2016 data runs. Differential expression analysis was performed using the voom-limma (48) method from Bioconductor with results reported as ratios on the log2 scale. The Benjamini and Hochberg method was use to control the false discovery rate at 5%. Expression changes of metabolic genes in the KEGG database were analyzed in addition to those assigned to the BCAA catabolic pathway. Principal Component Analysis and Hierarchical Cluster Analysis
Principal component analysis (PCA) was performed on qPCR expression data from mouse tumors and normal control tissues. The principal components were obtained by first mean-centering each variable and then scaling by the respective standard deviation. The correlation matrix was then calculated, along with the corresponding eigenvalues and eigenvectors.
Hierarchical cluster analysis was performed on log-transformed qPCR expression data from mouse tumors and normal control tissues. The complete linkage method and Euclidean distance metric were adopted for clustering. Cell Lines
C57BL/6J KP NSCLC and PDAC (KP–/–C) cell lines were derived as previously described (18). Briefly, end-stage tumors were dissected from indicated mice and mechanically chopped before trypsin disaggregation. Tumor cells were propagated in DMEM with 10% FBS, 4 mM glutamine and penicillin/streptomycin. Cell lines were tested and determined to be negative for mycoplasma.
Cell Culture
Isotope Tracing Experiments. For labeled-glutamine tracing, DMEM lacking glutamine was supplemented with [α-15N]-glutamine (Cambridge Isotopes) to the standard DMEM concentration and with 10% dialyzed FBS. For leucine tracing, DMEM lacking leucine and containing either 4mM, 400µM or 40µM glutamine was supplemented with 15N-leucine (Cambridge Isotopes) to the standard DMEM concentration and with 10% dialyzed FBS. For 3-
7
and 24-hr tracing experiment, 1x105 cells were plated six hours prior to the start of the experiment.
Proliferation Assay. 1x104 cells/well were plated and grown for four days in standard DMEM (without pyruvate) conditions with 10% FBS. Growth rate (in doublings/day) was calculated by the following equation:
Doublings/day = [log2(#cells day 4/#cells day0)]/4days
Tracing Experiments for Bcat KO lines. DMEM media lacking leucine was supplemented
with 15N-leucine (Cambridge Isotopes) to the standard DMEM concentration and with 10% dialyzed FBS. For 24-hr tracing experiment, 1.5x105 cells were plated six hours prior to the start of the experiment.
Slc7a5 Overexpression
The murine Slc7a5 open reading frame was PCR amplified from a cDNA library obtained from Origene Technologies (Rockville, MD). The Slc7a5 open reading frame was subcloned into pLHCX (Clontech, Mountain View, CA) by standard laboratory methods using the HindIII and ClaI restriction sites. The entire coding sequence of this construct was confirmed by sequencing analysis. Target PDAC cells were infected with either control empty vector or Slc7a5-expressing vector. Two Slc7a5 cell lines (Lines A and B) were generated in parallel from different bacterial clones. Post-infection, cell lines were selected with hygromycin B for further experiments. Leucine Uptake Assay
1x105 cells were plated the day before the experiment. At the start of the experiment, cells were washed once in PBS before exposure to PBS containing 200µM Leucine with 1µCi/mL [1-14C]-leucine (American Radiolabeled Chemicals) for 0 min. or 2 min. at 37°C. Labeled media was aspirated and cells were washed 3x with excess ice-cold PBS before freezing in liquid nitrogen. Cells were extracted in 80% MetOH for measurement of radioactivity using scintillation counting. Macropinocytosis Assay
Procedure. Macropinocytosis experiments were conducted as previously described (49) with the following modifications. Briefly, 2.5 x 104 NSCLC or PDAC cells were plated into 24-well plates containing fibronectin coated coverslips. Cells were cultured for 12 hours in 0.5mL DMEM containing 10% FBS, then media was removed and replaced with serum free DMEM for 24 hours. After serum starvation the media was replaced with serum free DMEM containing 10 ug/mL DQ Red BSA (Thermo-Fisher, D12051) and incubated for 30 minutes at 37°C. The media was then aspirated and the plate was washed 5 times with 2 mL ice cold PBS. Cells were fixed with 4% PFA for 15 minutes. Coverslips were removed and PDAC cells stained with 1ug/mL WGA 647 (Thermo-Fisher, W32466) for 15 minutes room temperature (NSCLC cells express GFP), and then both cell lines were stained with DAPI (Thermo-Fisher, D3571) for 10 minutes and mounted in Prolong Gold mounting media (Invitrogen P36934). Cells were then imaged on an applied precision DeltaVision Spectris Imaging System with a 60X objective. Macropinocytic index was calculated by field of view as described previously (49).
Analysis. Cell area was determined based on GFP fluorescence (NSCLC) or WGA-647 staining (PDAC) imaged in the FITC channel. DQ Red BSA was imaged in the Rhodamine
8
channel. Images were converted to 8-bit, Z-stacked, and thresholded using ImageJ. Cell area was read out using the “Measure” function, while DQ Red BSA area was calculated with the “Analyze Particles” function. The macropinocytic index was calculated by dividing the area of the particles by the cell area for each image.
CRISPR-Cas9 genome editing
SgRNA to Bcat1 and Bcat2 was designed by identifying exon sequence homology in Bcat1 and Bcat2 followed by an NGG PAM sequence (fig. S8A). An additional G was added to sgRNAs lacking a 5’G for U6 transcriptional initiation. U6-sgRNA-EFS-CAS9-2A-Puro vector was digested with BsmB1 and ligated with annealed sgRNAs. Lentivirus was produced by co-transfection of 293T cells with lentiviral backbone constructs and packaging vectors (delta8.2 and VSV-G) using TransIT-LT1 (Mirus Bio).
Implantation studies
Subcutaneous. For subcutaneous implantation studies, recipient mice were anesthetized with inhaled 2% isoflurane-oxygen mixture. 100µL of PBS containing 2.0 x 105 cells was delivered into the subcutaneous space on the hindflank of the animal. Volume estimates in vivo were calculated according to a modified ellipsoid volume equation:
Tumor volume = (4/3)π(length/2)(width/2)2
Lung. For orthotopic implantation studies, recipient mice were anesthetized with inhaled
2% isoflurane-oxygen mixture. A catheter was inserted into the trachea and 50µL of PBS containing 2.0 x 105 cells delivered.
Pancreas. For orthotopic implantation studies, recipient mice were anesthetized with inhaled 2% isoflurane-oxygen mixture, a vertical incision made in the abdomen at the left mid-calvicular line, the spleen mobilized, and 50µL of either PBS or PBS containing 2.0 × 105 cells was injected into the tail of the pancreas. After sacrifice, tumors were dissected and calipered to get measurements of length, width and height. Tumor volume was then calculated for ellipsoid shaped tumors:
Tumor volume = (4/3)π(length/2)(width/2)(height/2)
Statistics
Appropriate statistical tests were performed where required. Two–sided unpaired student’s t–tests were performed for all statistical analyses unless otherwise specified using Mircosoft Excel for Mac:2011 (Microsoft) or GraphPad Prism 6 (GraphPad Software). For example, two-way repeated measures ANOVA was used to assess for differences in subcutaneous allograft tumor growth over time and one-way ANOVA with Dunnett’s multiple comparisons test used for tumor weight comparisons across three groups. No statistical method was used to pre-determine sample size.
9
A B
Control PDACTo
tal B
CAA
s (µ
M)
Control NSCLC0
200
400
600
800
Tota
l BC
AAs
(µM
)
Pancreas Lung
PBS NSCLC
Tota
l BC
AAs
(µM
)
0
200
400
600
800
0
200
400
600
800
PBS PDAC
Tota
l BC
AAs
(µM
)
0
200
400
600
800
E F
C D
**
*
PDAC SubcutaneousAllograft
NSCLC SubcutaneousAllograft
Fig. S1. Early pancreatic cancer and lung cancer have different effects on plasma BCAA levels. (A) Plasma BCAA concentration in five-week-old control and PDAC mice. Data are presented as mean ± SEM. N = 8 control and N = 6 PDAC. (B) Plasma BCAA concentration eight weeks post-infection in control and NSCLC mice. Data are presented as mean ± SEM. N = 7 control and N = 11 NSCLC. (C) Representative H&E section from a five-week-old PDAC mouse showing areas of normal pancreas and tumor. Scale bar = 100µm. (D) Representative H&E section from an eight-weeks post-infection NSCLC mouse showing areas of normal lung and tumor. Scale bar = 100µm. (E) Plasma BCAA concentration in C57BL/6J mice four weeks after subcutaneous implantation of syngenic PDAC cells. Data are presented as mean ± SEM. N = 5 control, N = 5 PDAC. (F) Plasma BCAA concentration in C57BL/6J mice four weeks after subcutaneous implantation of syngenic NSCLC cells. Data are presented as mean ± SEM. N = 6 control, N = 7 NSCLC. Two-tailed t test was used for all comparisons between two groups. * P<0.05
10
A B
H
E F
Val M+5 Leu M+60
5
10
15La
belin
g (%
)Pancreas - Plasma
Val M+5 Leu M+6
Val M+5 Leu M+6 Val Leu
Rel
ativ
e Io
n Co
unts
Lung Tissue Protein
Val M+5 Leu M+6 Val Leu
Rel
ativ
e Io
n C
ount
s
Pancreas Tissue Protein
MID
ControlNSCLC
ControlPDAC
020406080
100
0.01.02.03.04.05.0
M+0 M+1 M+2 M+3 M+4 M+5 M+60
20406080
100
0.01.02.03.04.05.0
Pancreas
Lung
I
ControlNSCLC
ControlPDAC
Val Leu0.0
0.5
1.0
1.5
2.0
2.5
Rel
ativ
e Io
n C
ount
s
0.0
0.5
1.0
1.5
2.0
2.5
Rel
ativ
e Io
n C
ount
s
Lung - Plasma
0.0
0.5
1.0
1.5
0.0
0.5
1.0
1.5
ControlNSCLC
ControlPDAC
Rel
ativ
e Io
n C
ount
-5
0
5
10
0.00.51.01.52.0
Pancreas
Lung
ControlNSCLC
ControlPDAC
C D Lung Free Amino AcidsPancreas Free Amino Acids
G
Val Leu
Val M+5 Leu M+6
ControlPDAC
Rel
ativ
e Io
n C
ount
s
Val Leu Val M+5 Leu M+6
ControlNSCLC
0
1
2
3
4
5
Val Leu
Rel
ativ
e Io
n C
ount
s
***
C5-carnitine
M+5C2-carnitine
M+1C2-carnitine
M+2 Citrate M+1
Citrate M+2
PDAC SEM p-value
C5-carnitine M+5 7.9 0.7 7.0 1.0 NS 1.000 0.123 2.873 1.039C2-carnitine M+1 0.0 0.1 0.0 0.0C2-carnitine M+2 0.5 0.0 0.4 0.1Citrate M+1 1.5 0.1 0.8 0.2 0.049Citrate M+2 1.1 0.1 0.2 0.2 0.006
0.084
Relative Total Ion Count
1.000 0.161 0.705 0.063
1.000 0.121 1.253
Control SEM PDAC SEM p-valueControl SEM
NSNS
NS
NS
NS
5.9 1.2 4.2 0.2 1.000 0.153 1.208 0.189-0.2 0.0 -0.1 0.00.1 0.0 0.2 0.00.0 0.1 -0.1 0.10.4 0.0 0.4 0.0
1.000 0.050 0.903 0.073
1.000 0.177 0.783 0.160
NSCLC SEM p-valueRelative Total Ion Count
Control SEM NSCLC SEM p-valueControl SEM
NSNSNS
NS
NS
NSNSNS
LungPancreas
*** *** **** *
*
* **
KIC M+6 6.3 0.5 6.4 0.6 NS 1.000 0.199 1.193 0.327 NS 4.9 0.8 6.2 0.5 NS 1.000 0.241 1.795 0.366 NS
Labeling % from [U- C]-Leu13 Labeling % from [U- C]-Leu13
Labe
ling
(%)
Labe
ling
(%)
Labe
ling
(%)
Labe
ling
(%)
Labe
ling
(%)
Citr
ate
Labe
ling
(%) f
rom
[U-
C]-L
eu13
0
5
10
15
0
5
10
15
0
5
10
15
0
5
10
15
0
5
10
15
0
1
2
3
4
5
Fig. S2
11
Fig. S2. Mice with NSCLC display increased BCAA uptake and metabolism. (A-I) Mice were fed 13C-BCAA containing diet for seven days. (A) Percent plasma enrichment of fully labeled BCAAs (left panel) and relative ion counts of total BCAAs (right panel) in control and PDAC mice. Data are presented as mean ± SEM. N = 4 control and N = 4 PDAC. (B) Percent plasma enrichment of fully labeled BCAAs (left panel) and relative ion counts of total BCAAs (right panel) in control and NSCLC mice. Data are presented as mean ± SEM. N = 4 control and N = 4 NSCLC. (C) Percent enrichment of labeled free BCAAs (left panel) and relative ion counts of total free BCAAs (right panel) in control mouse pancreas tissues and PDAC mouse tumors. Data are presented as mean ± SEM. N = 4 control and N = 4 PDAC. (D) Percent enrichment of labeled free BCAAs (left panel) and relative ion counts of total free BCAAs (right panel) in control mouse lung tissues and NSCLC mouse tumors. Data are presented as mean ± SEM. N = 4 control and N = 4 NSCLC. (E) Percent enrichment of labeled BCAAs (left panel) and relative ion counts of total BCAAs (right panel) in protein hydrolysates of control mouse pancreas tissues and PDAC mouse tumors. Data are presented as mean ± SEM. N = 4 control and N = 4 PDAC. (F) Percent enrichment of labeled BCAAs (left panel) and relative ion counts of total BCAAs (right panel) in protein hydrolysates of control mouse lung tissues and NSCLC mouse tumors. Data are presented as mean ± SEM. N = 4 control and N = 4 NSCLC. (G) Labeling (%) from [U-13C]-leucine and relative total ion count of downstream leucine metabolites (Fig. 1B) in tumors from PDAC and NSCLC mice and normal tissues from their respective control mice. Data are presented as mean ± SEM. N = 4 control and N = 4 PDAC; N = 4 control and N = 4 NSCLC. (H) Relative ion counts of labeled species downstream of KIC. Data are presented as mean ± SEM. Top panel, control mouse pancreas tissues and PDAC mouse tumors (N = 4 control and N = 4 PDAC) and bottom panel, control mouse lung tissues and NSCLC mouse tumors (N = 4 control and N = 4 NSCLC). (I) Citrate labeling (%) from [U-13C]-leucine in PDAC and NSCLC. Data are presented as mean ± SEM. Top panel, N = 4 control and N = 4 PDAC. Bottom panel, N = 4 control and N = 4 NSCLC. MID = mass isotopomer distribution. Two-tailed t test was used for all comparisons between two groups. * P<0.05, ** P<0.01, *** P<0.001
12
A
B
Pancreas
0.0
5.0
10.0
15.0
Amino Acid
Perc
ent of T
ota
l P
rote
in A
min
o A
cid
Pool
Control
PDAC
Ala Arg Asp+
Asn
Glu+
Gln
Gly His Ile Leu Lys Met Phe Pro Ser Thr Tyr Val
Lung
Ala Arg Asp+
Asn
Glu+
Gln
Gly His Ile Leu Lys Met Phe Pro Ser Thr Tyr Val
Amino Acid
Perc
ent of T
ota
l P
rote
in A
min
o A
cid
Pool
Control
NSCLC
0.0
5.0
10.0
15.0
Fig. S3
Fig. S3. Amino acid composition of PDAC and NSCLC tumors compared to control normal tissue. (A) Percent of each amino acid in total tissue protein determined following acid hydrolysis of control pancreas and PDAC tumors. Data are presented as mean ± SEM. N = 7 control and N = 5 PDAC. (B) Percent of each amino acid in total tissue protein determined following acid hydrolysis of normal lung and NSCLC tumors. Data are presented as mean ± SEM. N = 6 control and N = 6 NSCLC.
13
0
2
4
6
Control NSCLC
Plasma KIC
Control NSCLC0.0
0.5
1.0
1.5R
elat
ive
Ion
Cou
nts
(M+6
)
A
0.0
0.5
1.0
1.5
2.0
Control NSCLC
Rel
ativ
e Io
n C
ount
s
M+6
Lab
elin
g (%
) fro
m
[U-
C]-L
eu13
B
Liver Muscle WAT
Rel
ativ
e Io
n C
ount
s (M
+6)
Liver Muscle WAT
Rel
ativ
e Io
n C
ount
sLiver Muscle WATM
+6 L
abel
ing
(%) f
rom
[U-
C]-L
eu13
Tissue KIC
Liver Muscle WATLiver Muscle WAT0
1
2
3
Liver Muscle WAT0
1
2
3
Rel
ativ
e Io
n C
ount
s (M
+5)
Rel
ativ
e Io
n C
ount
s
0
2
4
6
8
M+5
Lab
elin
g (%
) fro
m [U
- C
]-Leu
13
Tissue C5-CarnitineC
*
**
ControlNSCLC
ControlNSCLC
0
1
2
3
4
5
0
1
2
3
0
10
20
30
40
50
Fig. S4
14
Fig. S4. Evidence for liver oxidation of BCAA-derived carbon in NSCLC tumor-bearing mice. (A-C) NSCLC mice were fed 13C-BCAA containing diet for seven days. (A) Relative labeled ion counts of M+6 isotopomer (left), M+6 labeling (%) from [U-13C]-leucine (center), and relative total ion counts (right) of KIC in the plasma of mice with NSCLC and their controls. Data are presented as mean ± SEM. N = 4 control and N = 4 NSCLC. (B) Relative labeled ion counts of M+6 isotopomer (left), M+6 labeling (%) from [U-13C]-leucine (center), and relative total ion counts (right) of KIC in the liver, muscle (gastrocnemius) and perigonadal white adipose tissue (WAT) of mice with NSCLC and their controls. Data are presented as mean ± SEM. N = 4 control and N = 4 NSCLC. (C) Relative labeled ion counts of M+5 isotopomer (left), M+5 labeling (%) from [U-13C]-leucine (center), and relative total ion counts (right) of C5-carnitine in the liver, muscle (gastrocnemius) and perigonadal white adipose tissue (WAT) of mice with NSCLC and their controls. Data are presented as mean ± SEM. N = 4 control and N = 4 NSCLC. Two-tailed t test was used for all comparisons between two groups. * P<0.05, ** P<0.01.
15
A Pancreas Free Leucine
Control PDAC0.0
0.5
1.0
1.5
2.0R
elat
ive
Ion
Cou
nts
(M+1
)
Control PDAC0.0
2.0
4.0
6.0
8.0
10.0
Control PDAC0.0
0.5
1.0
1.5
Rel
ativ
e Io
n C
ount
s
B Pancreas Tissue Protein
Ala Asp+Asn
Glu+Gln
Val Ile0.0
0.5
1.0
1.5
2.0
Rel
ativ
e Io
n C
ount
s (M
+1)
ControlPDAC
P = 0.05
0.0
0.5
1.0
1.5
Amino Acid Amino AcidC Lung Free Amino Acids
Leu
0
5
10
15
Ala Asp+Asn
Glu+Gln
Val Ile Leu
Ala Asp Glu Val Ile Leu0
2
4
6
Amino Acid
Rel
ativ
e Io
n C
ount
s (M
+1)
ControlNSCLC *** *** *** *
***
Ala Asp Glu Val Ile LeuAmino Acid
******
02468
10
****
D Lung - Plasma E Lung Tissue Protein Amino Acids
Rel
ativ
e Io
n C
ount
s
0.00.51.01.52.0
Ala Asp Glu Val Ile LeuAmino Acid
*
***
***
02468
10
0.00.51.01.52.0
Ala Asp Glu Val Ile LeuAmino Acid
*** *** ***** **
*
* *
* *
**
M+1
Lab
elin
g (%
) fro
m
[ N
]-Leu
15
M+1
Lab
elin
g (%
) fro
m [
N]-L
eu15
0
5
10
15
0
5
10
15
Rel
ativ
e Io
n C
ount
sM
+1 L
abel
ing
(%)
from
[ N
]-Leu
15
Rel
ativ
e Io
n C
ount
sM
+1 L
abel
ing
(%)
from
[ N
]-Leu
15R
elat
ive
Ion
Cou
nts
M+1
Lab
elin
g (%
) fro
m [
N]-L
eu15
Fig. S5
16
Fig. S5. BCAA-derived nitrogen supports non-essential amino acid and DNA synthesis in NSCLC tumors. (A-E) PDAC mice were fed 15N-leucine containing diet for seven days and NSCLC mice were fed 15N-leucine diet for six days. (A) Relative labeled ion counts of M+1 isotopomer (left), M+1 labeling (%) from 15N-leucine (center), and relative total ion counts (right) of free leucine in control mouse pancreas tissues and PDAC mouse tumors. Data are presented as mean ± SEM. N = 6 control and N = 6 PDAC. (B) Relative labeled ion counts of M+1 isotopomers (left), M+1 labeing (%) from 15N-leucine (top right), and relative total ion counts (bottom right) of amino acids from tissue protein hydrolysates in control mouse pancreas tissues and PDAC mouse tumors. Data are presented as mean ± SEM. N = 6 control and N = 6 PDAC. (C) Relative labeled ion counts of M+1 isotopomers (left), M+1 labeing (%) from 15N-leucine (top right), and relative total ion counts (bottom right) of free amino acids in control mouse lung tissues and NSCLC mouse tumors. Data are presented as mean ± SEM. N = 6 control and N = 5 NSCLC. (D) M+1 labeing (%) from 15N-leucine (top) and relative total ion counts (bottom) of free plasma amino acids in control and NSCLC mice. Data are presented as mean ± SEM. N = 5 control and N = 6 NSCLC. (E) M+1 labeing (%) from 15N-leucine (top) and relative total ion counts (bottom) of free tissue amino acids in control mouse lung tissues and NSCLC mouse tumors. Data are presented as mean ± SEM. N = 6 control and N = 6 NSCLC. Two-tailed t test was used for all comparisons between two groups. * P<0.05, ** P<0.01, *** P<0.001
17
A
C
Ile Leu Val0
5
10
15
Amino Acid
NSCLCPDAC
M+1
Lab
elin
g (%
) fro
m
[α-
N]-G
ln15
B
*
**
**
4mM 400µM 40µM0
5
10
15
Glutamine Concentration
Isoleucine M+1
4mM 400µM 40µM0
2
4
6
8
10
Glutamine Concentration
Valine M+1
M+1
Lab
elin
g (%
) fro
m
[ N
]-Leu
15
M+1
Lab
elin
g (%
) fro
m
[ N
]-Leu
15
* *
**
NSCLCPDAC
4mM 400µM 40µM0
10
20
30
40
Glutamine Concentration
M+1
Lab
elin
g (%
) fro
m
[ N
]-Leu
15
4mM 400µM 40µM
Glutamine Concentration
0
10
20
30
40
M+1
Lab
elin
g (%
) fro
m
[ N
]-Leu
15
4mM 400µM 40µM
Glutamine Concentration
0
10
20
30
40
M+1
Lab
elin
g (%
) fro
m
[ N
]-Leu
15
Alanine M+1 Aspartate M+1 Glutamate M+1
**
***
NSCLCPDAC
**
**
Fig. S6
Fig. S6. Relationship between BCAA transamination and glutamine level in vitro. (A) M+1 isoleucine (Ile), leucine (Leu) and valine (Val) labeling (%) from [α-15N]-glutamine
following exposure of PDAC or NSCLC cells for 24-hours to media containing [α-15N]-glutamine. Data are presented as mean ± SEM. N = 3 per group. (B) M+1 isoleucine (left panel) and valine (right panel) labeling (%) from 15N-leucine following exposure of PDAC or NSCLC cells for 3-hours to media containing 15N-leucine and the indicated concentration of glutamine. Data are presented as mean ± SEM. N = 3 per group. (C) M+1 alanine (left panel), aspartate (middle panel) and glutamate (right panel) labeling (%) from 15N-leucine following exposure of PDAC or NSCLC cells for 3-hours to media containing 15N-leucine and the indicated concentration of glutamine. Data are presented as mean ± SEM. N = 3 per group. Two-tailed t test was used for all comparisons between two groups. * P<0.05, ** P<0.01, *** P<0.001
18
A
C D
B
Lung
Control
PDAC
Pancreas
Acadsb Auh Hadhb Pcca
0.0
0.5
1.0
1.5
2.0
Re
lative
Expre
ssio
n
NSCLC
Control
Acadsb Auh Hadhb Pcca
0.0
0.5
1.0
1.5
2.0
Re
lative
Expre
ssio
n
Control
KPC
Slc7a5 Bcat1 Bcat2 Bckdha Bckdhb Acadsb Auh Hadhb Pcca
0.0
0.5
1.0
1.5
2.0R
ela
tive
Expre
ssio
nPancreas
Re
lative
Expre
ssio
n
Slc7a5 Bcat1 Bcat2 Bckdha Bckdhb
0
1
2
3
Whole Tumor
Cancer Cells
PDAC
Glut1 Eno1
0
5
10
15
20
25
Glut1 Eno1
Re
lative
Expre
ssio
n
0
1
2
3
4
E
Re
lative
Expre
ssio
n
FLung Pancreas
* * * ***
*
*
*
**
*******
PC1 (40.6%)
PC
2 (
29.6
%)
−2 0 2 4 6
−3−2
−10
12
3
●
●●
●
●● ●
●●●●●
●●
●
●
●●
●
●● ●●●●●
●●●
●●
Control
PDAC
Pancreas Lung
Control
NSCLC
G H I
−0.05
0.0
6
0.1
6
0.2
7
0.3
7
0.4
8
0.5
8
0.6
8
0.7
90.91
GS
E15471
GS
E16515
GS
E71989
GS
E18842
LU
AD
_T
CG
A
LU
SQ
_T
CG
A
GSE15471
GSE16515
GSE71989
GSE18842
LUAD_TCGA
LUSQ_TCGA
Bck
dhb
Bca
t2
Hadhb
Auh
Aca
dsb
Pcc
a
Slc7a5
Bck
dha
Bca
t1−6 −4 −2log(expr)
Fig. S7
19
Fig. S7. Gene expression in both mouse and human tumors reflects tumor tissue-specific BCAA metabolism. (A) Relative expression of BCAA metabolic pathway genes in KPC PDAC tumors and normal pancreas. Data are presented as mean ± SEM. N = 3 control and N = 4 KPC. (B) Relative expression of BCAA metabolic pathway genes in FACS sorted tumor cells compared with parental whole tumor from KP-/-C PDAC mice. Data are presented as mean ± SEM. N = 5 tumors. Two-tailed paired-sample t test used for comparison. (C) Relative expression of downstream BCAA metabolic pathway genes in normal lung and NSCLC tumors from KP mice. Data are presented as mean ± SEM. N = 6 control and N = 6 NSCLC. (D) Relative expression of downstream BCAA metabolic pathway genes in normal pancreas and PDAC tumors from KP-/-C mice. Data are presented as mean ± SEM. N = 7 control and N = 5 PDAC. (E) Relative expression of glycolytic genes in normal lung and NSCLC tumors from KP mice. Data are presented as mean ± SEM. N = 6 control and N = 6 NSCLC. (F) Relative expression of glycolytic genes in normal pancreas and PDAC tumors from KP-/-C mice. Data are presented as mean ± SEM. N = 7 control and N = 5 PDAC. (G) Principal component analysis (PCA) of mouse BCAA catabolic gene expression in normal lung, NSCLC tumors, normal pancreas and PDAC tumors from Figs. 3, A and B and figs. S7, C and D. The first two principal components explained ~41% and ~30% of the variance respectively. (H) Hierarchical cluster analysis of mouse BCAA catabolic gene expression data. Colors on the side bar correspond to tissue samples given in fig. S7G. (I) Correlation of tumor expression fold-changes for branched-chain amino acid degradation pathway genes in human studies involving pancreas (GSE15471, GSE16515, GSE71989) and lung (GSE18842, LUAD_TCGA, LUSQ_TCGA). Average Spearman R was 0.84 for pancreas data. Spearman R with GSE18842 was 0.61 for lung adenocarcinoma and 0.86 for squamous cell carcinoma. Two-tailed t test was used for all comparisons unless otherwise stated. * P<0.05, ** P<0.01, *** P<0.001
20
A
E
B
C
Bcat1 CDS
Bcat2 CDS
sgBcat total
G C T G G T C T T T G G A G C T A C G T T T A C T G A C C A C A T G C T G A C G G T G G A G T G G T C C T C T G C G T C T G G A T G
A C T G C T G T T T G G G A A G A C C T T C A C A G A C C A C A T G C T G A T G G T G G A G T G G A A T A A C A A G G C T G G A T G
- - - - - - - - - - - - - - - - - - - - - - - - - - - C C A C A T G C T G A C G G T G G A G - - - - - - - - - - - - - - - - - - - -
Allele 1 Allele 2
NSCLC Clone A 1bp insertion 8bp deletion 8bp deletion 5bp deletion
NSCLC Clone B 1bp deletion 19bp deletion 25bp deletion 8bp deletion
PDAC 8bp deletion 8bp deletion 1bp deletion 2bp insertion
Allele 1 Allele 2
Bcat1 Bcat2
Bcat1 Bcat20.0
0.5
1.0
1.5
Gene
Re
lative
Expre
ssio
n
pLenti Control
Bcat Clone A
Bcat Clone B
Bcat1 Bcat20.0
0.5
1.0
1.5
Gene
Re
lative
Expre
ssio
n
D
pLenti Control
Bcat null
F
pLenti
Control
Bcat null
0
200
400
600
800
1000
Tum
or
Volu
me
(m
m3)
PDAC Pancreas
Orthotopic Allografts
**
I
pLenti
Control
Bcat null
Clone A
pLenti
Control
Bcat null
Clone B
***
0
5
10
15
20
***
pLenti
Control
Bcat null
M+1 G
lu L
abelin
g (%
)
from
[ N
]-Leu
15
0
2
4
6
8 ***M
+1 G
lu L
abelin
g (%
)
from
[ N
]-Leu
15
NSCLC Subcutaneous
Allografts
PDAC Subcutaneous
Allografts
pLenti
Control
Bcat null
Clone A
Bcat null
Clone B
0
200
400
600
Tum
or
We
ight (m
g)
Cell Line Cell Line
G
***
***
Cell Line Cell Line
pLenti
Control
Bcat null
0
100
200
300
Tum
or
We
ight (m
g)
H
Cell Line
Fig. S8
0
100
200
300
400
pLenti
Control
Bcat null
Cell Line
21
Fig. S8. Branched-chain amino acid transaminase (Bcat) activity is required for NSCLC tumor growth. (A) Schematic of common exon sequence of Bcat1 and Bcat2 targeted with sgRNA for CRISPR-Cas9 genome editing. Red “T” highlights a 1bp sequence difference between the two isoforms. (B) Summary of sequence analyses of Bcat1 and Bcat2 in Bcat null clones derived from syngenic NSCLC and PDAC cell lines following sgRNA targeting with CRISPR-Cas9. (C) Normalized expression measured by qPCR of Bcat1 and Bcat2 in NSCLC Bcat null Clones A and B confirming decreased expression of both genes. (D) Normalized expression measured by qPCR of Bcat1 and Bcat2 in PDAC Bcat null cells confirming decreased expression of both genes. (E) M+1 Glu labeling (%) from 15N-leucine following 24-hour 15N-leucine tracing in control infected compared with NSCLC Bcat null Clone A and B cells. Data are presented as mean ± SEM. N = 3 per group. Representative experiment from ≥2 repeats. (F) M+1 Glu labeling (%) from 15N-leucine following 24-hour 15N-leucine tracing in control infected compared with PDAC Bcat null cells. Data are presented as mean ± SEM. N = 3 per group. (G) Tumor weight of subcutaneous allograft tumors generated from control infected and Bcat null syngenic NSCLC cell lines in C57BL/6J mice. Data are presented as mean ± SEM. N = 6 per group. (H) Two independent experiments determining tumor weight of subcutaneous allograft tumors derived from control infected and Bcat null syngenic PDAC cells in C57BL/6J mice. Data are presented as mean ± SEM. Left panel corresponds to mice in Fig. 4D. N = 5 pLenti control and N = 6 Bcat null. Right panel, N = 3 pLenti control and N = 3 Bcat null. (I) Calculated tumor volumes of orthotopically implanted syngenic PDAC pLenti control and Bcat null tumors. Data are presented as mean ± SEM. N = 8 per group. Two-tailed t test was used for all comparisons between two groups. * P<0.05, ** P<0.01, *** P<0.001
22
A B
Fig. S9
***
NSCLC PDAC
Cell Type
Mac
ropi
nocy
tic In
dex
0.0
0.2
0.4
0.6
0.8
1.0NSCLC PDACDAPIDQBSA
Fig. S9. NSCLC cells exhibit decreased macropinocytosis relative to PDAC cells. (A) Representative images used to quantify macropinocytic uptake in NSCLC and PDAC cells. Cells were exposed to DQ Red BSA (DQBSA) and stained with DAPI. Scale bar = 10µm. (B) Quantified macropinocytic index based on fluorescence from DQBSA. Data were obtained from N = 7 fields-of-view (29 cells) for NSCLC and N = 6 fields-of-view (49 cells) for PDAC.
23
Control Vector
Slc7a5 Line A
Slc7a5 Line B
Cell Line
Dou
blin
gs/2
4hrs
in vitro proliferation
0
10
20
30
Rel
ativ
e Ex
pres
sion
Slc7a5 Expression
Control Vector
Slc7a5 Line A
Slc7a5 Line B
Cell Line
A B C
Fig. S10
Dfm
ol /
(cel
l * m
in)
Leucine Uptake
Control Vector
Slc7a5 Line A
Slc7a5 Line B
Cell Line
0.0
0.5
1.0
1.5
2.0
2.5***
***
E
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 5 10 15 200
200
400
600
800
1000
Time (days)
Tum
or V
olum
e (m
m )3
PDAC Subcutaneous Allografts
Control VectorSlc7a5 Line ASlc7a5 Line B
0
200
400
600
Tum
or W
eigh
t (m
g)
PDAC Subcutaneous Allografts
Control Vector
Slc7a5 Line A
Slc7a5 Line B
Cell Line
P = 0.06
Fig. S10. Overexpression of Slc7a5 in PDAC cells does not affect proliferation. (A) Relative expression of Slc7a5 in control infected PDAC cells and two PDAC cells lines overexpressing Slc7a5. (B) Uptake rate of leucine in vector control infected PDAC cells and PDAC cells overexpressing Slc7a5. Data are presented as mean ± SEM. N = 3 per group. One-way ordinary ANOVA with Dunnett’s multiple comparisons for control vector versus each overexpression vector. (C) Doubling time in vitro of control infected and Slc7a5 overexpressing PDAC cells. Data are presented as mean ± SEM. N = 3 per group. (D) Estimated tumor volume (mm3) of subcutaneous allografts derived from control vector infected and Slc7a5 overexpressing syngenic PDAC cell lines in C57BL/6J mice. Data are presented as mean ± SEM. N = 6 control vector and N = 5 each Slc7a5 Vectors A and B. Two-way repeated measures ANOVA used for comparison between groups. (E) Tumor weight of subcutaneous allografts derived from control vector and Slc7a5 overexpressing syngenic PDAC cells in C57BL/6J mice. Data are presented as mean ± SEM. N = 6 control vector and N = 5 each Slc7a5 Vectors A and B. One-way ordinary ANOVA (P = 0.0137) with Dunnett’s multiple comparisons for control vector versus each overexpression vector. * P<0.05, ** P<0.01, *** P<0.001
24
Table S1. Human expression data comparing PDAC to adjacent normal pancreatic tissue (GSE15471). Gene ID Gene Symbol Gene Name log2 fold
change p-value
8140 SLC7A5 solute carrier family 7 (amino acid transporter light chain, L system), member 5
0.879502861 0.00122176
587 BCAT2 branched chain amino-acid transaminase 2, mitochondrial -0.90281329 7.65E-05
586 BCAT1 branched chain amino-acid transaminase 1, cytosolic -1.684103972 0.00477334
259307 IL4I1 interleukin 4 induced 1 0.232279522 0.034091294
593 BCKDHA branched chain keto acid dehydrogenase E1, alpha polypeptide -0.613720584 0.000701634
594 BCKDHB branched chain keto acid dehydrogenase E1, beta polypeptide -0.735076396 2.48E-06
1629 DBT dihydrolipoamide branched chain transacylase E2 -0.587540291 0.000331659
1738 DLD dihydrolipoamide dehydrogenase -0.469580173 4.03E-08
35 ACADS acyl-CoA dehydrogenase, C-2 to C-3 short chain -0.877723342 1.46E-06
34 ACADM acyl-CoA dehydrogenase, C-4 to C-12 straight chain -0.928974891 9.48E-10
3712 IVD isovaleryl-CoA dehydrogenase -0.367787174 0.000388408
36 ACADSB acyl-CoA dehydrogenase, short/branched chain -1.373555807 4.44E-08
27034 ACAD8 acyl-CoA dehydrogenase family, member 8 -0.519219647 0.000294208
3030 HADHA hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit
-0.584595254 0.001003697
1962 EHHADH enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase -0.658770531 0.003790345
1892 ECHS1 enoyl CoA hydratase, short chain, 1, mitochondrial -0.048319001 0.745579334
3033 HADH hydroxyacyl-CoA dehydrogenase -0.547844188 0.001603
3028 HSD17B10 hydroxysteroid (17-beta) dehydrogenase 10 0.160472939 0.07307885
30 ACAA1 acetyl-CoA acyltransferase 1 -0.334432109 0.015971732
10449 ACAA2 acetyl-CoA acyltransferase 2 -0.566448642 4.78E-06
3032 HADHB hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), beta subunit
-0.246013864 0.009645609
5095 PCCA propionyl CoA carboxylase, alpha polypeptide -0.482286092 0.00036024
5096 PCCB propionyl CoA carboxylase, beta polypeptide -0.553229461 0.000186867
84693 MCEE methylmalonyl CoA epimerase -0.769948801 6.22E-05
4594 MUT methylmalonyl CoA mutase -0.454059405 7.59E-05
26275 HIBCH 3-hydroxyisobutyryl-CoA hydrolase -0.725551273 2.74E-05
11112 HIBADH 3-hydroxyisobutyrate dehydrogenase -0.346119019 0.005247236
4329 ALDH6A1 aldehyde dehydrogenase 6 family, member A1 -1.531300679 7.64E-09
217 ALDH2 aldehyde dehydrogenase 2 family (mitochondrial) 0.017059544 0.914989371
224 ALDH3A2 aldehyde dehydrogenase 3 family, member A2 -0.830408387 0.000415913
219 ALDH1B1 aldehyde dehydrogenase 1 family, member B1 -0.160216402 0.171935365
501 ALDH7A1 aldehyde dehydrogenase 7 family, member A1 -0.492505985 0.000172935
223 ALDH9A1 aldehyde dehydrogenase 9 family, member A1 -0.38849919 7.85E-06
316 AOX1 aldehyde oxidase 1 -1.714514255 0.001243926
18 ABAT 4-aminobutyrate aminotransferase -1.913909607 3.47E-05
56922 MCCC1 methylcrotonoyl-CoA carboxylase 1 (alpha) -0.807017307 2.65E-05
64087 MCCC2 methylcrotonoyl-CoA carboxylase 2 (beta) -0.272774313 0.049069198
25
549 AUH AU RNA binding protein/enoyl-CoA hydratase -0.295488655 0.052464302
3155 HMGCL 3-hydroxymethyl-3-methylglutaryl-CoA lyase -0.337595694 0.004458408
5019 OXCT1 3-oxoacid CoA transferase 1 0.537053005 0.003720935
64064 OXCT2 3-oxoacid CoA transferase 2 -0.533796167 4.00E-06
39 ACAT2 acetyl-CoA acetyltransferase 2 0.574014232 0.000803098
38 ACAT1 acetyl-CoA acetyltransferase 1 -1.309218369 5.31E-09
3157 HMGCS1 3-hydroxy-3-methylglutaryl-CoA synthase 1 (soluble) 0.08709899 0.513755372
3158 HMGCS2 3-hydroxy-3-methylglutaryl-CoA synthase 2 (mitochondrial) -2.009941821 0.006996665
26
Table S2. Human expression data comparing lung adenocarcinoma to adjacent normal lung tissue (GSE18842) Gene ID Gene
Symbol Gene Name log2 fold
change p-value
8140 SLC7A5 solute carrier family 7 (amino acid transporter light chain, L system), member 5 2.526891751 6.23E-13
587 BCAT2 branched chain amino-acid transaminase 2, mitochondrial 0.453635541 0.003881953
586 BCAT1 branched chain amino-acid transaminase 1, cytosolic 0.807841298 0.013203348
259307 IL4I1 interleukin 4 induced 1 1.554637499 1.11E-06
593 BCKDHA branched chain keto acid dehydrogenase E1, alpha polypeptide 0.226473838 0.073768274
594 BCKDHB branched chain keto acid dehydrogenase E1, beta polypeptide 0.405589777 0.10000218
1629 DBT dihydrolipoamide branched chain transacylase E2 0.711942322 0.000365403
1738 DLD dihydrolipoamide dehydrogenase 0.322748437 0.005217065
35 ACADS acyl-CoA dehydrogenase, C-2 to C-3 short chain -0.372841503 0.000793325
34 ACADM acyl-CoA dehydrogenase, C-4 to C-12 straight chain -0.446473763 0.000226808
3712 IVD isovaleryl-CoA dehydrogenase -0.628354316 0.000721463
36 ACADSB acyl-CoA dehydrogenase, short/branched chain -1.695405701 2.78E-08
27034 ACAD8 acyl-CoA dehydrogenase family, member 8 -0.056757202 0.843774235
3030 HADHA hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit
-0.135673055 0.071471145
1962 EHHADH enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase 0.78441437 0.000216506
1892 ECHS1 enoyl CoA hydratase, short chain, 1, mitochondrial 0.485018276 2.15E-05
3033 HADH hydroxyacyl-CoA dehydrogenase 0.219528794 0.207298092
3028 HSD17B10 hydroxysteroid (17-beta) dehydrogenase 10 0.670151503 4.40E-08
30 ACAA1 acetyl-CoA acyltransferase 1 -0.628902526 3.62E-07
10449 ACAA2 acetyl-CoA acyltransferase 2 -1.39255237 1.34E-07
3032 HADHB hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), beta subunit
-0.120032456 0.109495435
5095 PCCA propionyl CoA carboxylase, alpha polypeptide -0.428606571 0.013017158
5096 PCCB propionyl CoA carboxylase, beta polypeptide 1.421420616 2.85E-11
84693 MCEE methylmalonyl CoA epimerase 0.19575875 0.231716118
4594 MUT methylmalonyl CoA mutase -0.565339317 0.000718517
26275 HIBCH 3-hydroxyisobutyryl-CoA hydrolase 0.106494012 0.632709265
11112 HIBADH 3-hydroxyisobutyrate dehydrogenase 0.445133888 0.00299894
4329 ALDH6A1 aldehyde dehydrogenase 6 family, member A1 -0.656789044 0.001646638
217 ALDH2 aldehyde dehydrogenase 2 family (mitochondrial) -1.742763109 1.15E-12
224 ALDH3A2 aldehyde dehydrogenase 3 family, member A2 -0.923729478 0.005218013
219 ALDH1B1 aldehyde dehydrogenase 1 family, member B1 0.960176481 5.93E-06
501 ALDH7A1 aldehyde dehydrogenase 7 family, member A1 -0.272075532 0.496164225
223 ALDH9A1 aldehyde dehydrogenase 9 family, member A1 -0.162836719 0.116324462
316 AOX1 aldehyde oxidase 1 -3.32817822 3.40E-20
18 ABAT 4-aminobutyrate aminotransferase -0.64764613 0.125137447
56922 MCCC1 methylcrotonoyl-CoA carboxylase 1 (alpha) 0.388764727 0.051035278
27
64087 MCCC2 methylcrotonoyl-CoA carboxylase 2 (beta) 1.190292844 1.38E-09
549 AUH AU RNA binding protein/enoyl-CoA hydratase -0.3176852 0.044189772
3155 HMGCL 3-hydroxymethyl-3-methylglutaryl-CoA lyase -0.097602498 0.570041016
5019 OXCT1 3-oxoacid CoA transferase 1 0.59930603 0.009009518
64064 OXCT2 3-oxoacid CoA transferase 2 -0.087938141 0.196592754
39 ACAT2 acetyl-CoA acetyltransferase 2 0.858717018 0.001369506
38 ACAT1 acetyl-CoA acetyltransferase 1 -0.823341597 3.09E-07
3157 HMGCS1 3-hydroxy-3-methylglutaryl-CoA synthase 1 (soluble) 1.414457463 0.000322578
3158 HMGCS2 3-hydroxy-3-methylglutaryl-CoA synthase 2 (mitochondrial) -0.727162773 0.005448621
28
Table S3. Human expression data comparing PDAC to adjacent normal pancreatic tissue (GSE16515). Gene ID Gene Symbol Gene Name log2 fold
change p-value
8140 SLC7A5 solute carrier family 7 (amino acid transporter light chain, L system), member 5
0.695729277 0.055891107
587 BCAT2 branched chain amino-acid transaminase 2, mitochondrial -0.587343204 0.014782749
586 BCAT1 branched chain amino-acid transaminase 1, cytosolic -0.89134623 0.097513629
259307 IL4I1 interleukin 4 induced 1 0.66088088 0.002497734
593 BCKDHA branched chain keto acid dehydrogenase E1, alpha polypeptide -0.396066507 0.097724294
594 BCKDHB branched chain keto acid dehydrogenase E1, beta polypeptide -0.29063685 0.075005553
1629 DBT dihydrolipoamide branched chain transacylase E2 -0.55337088 0.010313609
1738 DLD dihydrolipoamide dehydrogenase -0.321787985 0.021112408
35 ACADS acyl-CoA dehydrogenase, C-2 to C-3 short chain -0.476142339 0.019639656
34 ACADM acyl-CoA dehydrogenase, C-4 to C-12 straight chain -0.823919118 3.92E-05
3712 IVD isovaleryl-CoA dehydrogenase 0.109736254 0.497366466
36 ACADSB acyl-CoA dehydrogenase, short/branched chain -1.120427046 0.001225893
27034 ACAD8 acyl-CoA dehydrogenase family, member 8 -0.473503698 0.007574222
3030 HADHA hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit
-0.396494941 0.019975795
1962 EHHADH enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase -0.245081107 0.374528225
1892 ECHS1 enoyl CoA hydratase, short chain, 1, mitochondrial 0.278663082 0.111478307
3033 HADH hydroxyacyl-CoA dehydrogenase -0.571526558 0.004666048
3028 HSD17B10 hydroxysteroid (17-beta) dehydrogenase 10 0.181845127 0.27170365
30 ACAA1 acetyl-CoA acyltransferase 1 0.092593182 0.690004538
10449 ACAA2 acetyl-CoA acyltransferase 2 -0.290889954 0.038773312
3032 HADHB hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), beta subunit
-0.152380334 0.298839704
5095 PCCA propionyl CoA carboxylase, alpha polypeptide -0.305848101 0.184914773
5096 PCCB propionyl CoA carboxylase, beta polypeptide -0.275083765 0.205200373
84693 MCEE methylmalonyl CoA epimerase -0.605450867 0.005927251
4594 MUT methylmalonyl CoA mutase -0.480169785 0.008284053
26275 HIBCH 3-hydroxyisobutyryl-CoA hydrolase -0.230225489 0.292635698
11112 HIBADH 3-hydroxyisobutyrate dehydrogenase 0.193265533 0.361841563
4329 ALDH6A1 aldehyde dehydrogenase 6 family, member A1 -1.075354733 0.000108423
217 ALDH2 aldehyde dehydrogenase 2 family (mitochondrial) 0.191732118 0.389622882
224 ALDH3A2 aldehyde dehydrogenase 3 family, member A2 -0.638248983 0.014127821
219 ALDH1B1 aldehyde dehydrogenase 1 family, member B1 0.278048635 0.328069203
501 ALDH7A1 aldehyde dehydrogenase 7 family, member A1 -0.320432564 0.020145041
223 ALDH9A1 aldehyde dehydrogenase 9 family, member A1 -0.174329959 0.245888753
316 AOX1 aldehyde oxidase 1 -3.327431917 1.24E-05
18 ABAT 4-aminobutyrate aminotransferase -1.997962017 0.000256669
56922 MCCC1 methylcrotonoyl-CoA carboxylase 1 (alpha) -0.761894863 0.001967284
64087 MCCC2 methylcrotonoyl-CoA carboxylase 2 (beta) 0.369865204 0.069242708
29
549 AUH AU RNA binding protein/enoyl-CoA hydratase -0.426569359 0.012611638
3155 HMGCL 3-hydroxymethyl-3-methylglutaryl-CoA lyase -0.253656494 0.086247239
5019 OXCT1 3-oxoacid CoA transferase 1 0.313890739 0.241161483
64064 OXCT2 3-oxoacid CoA transferase 2 -0.199144447 0.048316157
39 ACAT2 acetyl-CoA acetyltransferase 2 0.803807309 0.000849972
38 ACAT1 acetyl-CoA acetyltransferase 1 -1.556269919 8.38E-06
3157 HMGCS1 3-hydroxy-3-methylglutaryl-CoA synthase 1 (soluble) 1.430259689 0.004019182
3158 HMGCS2 3-hydroxy-3-methylglutaryl-CoA synthase 2 (mitochondrial) -0.2944216 0.184121111
30
Table S4. Human expression data comparing PDAC to adjacent normal pancreatic tissue (GSE71989). Gene ID Gene Symbol Gene Name log2 fold
change p-value
8140 SLC7A5 solute carrier family 7 (amino acid transporter light chain, L system), member 5
1.834506135 0.048832563
587 BCAT2 branched chain amino-acid transaminase 2, mitochondrial -0.915125942 0.005263568
586 BCAT1 branched chain amino-acid transaminase 1, cytosolic -3.353061454 0.000450364
259307 IL4I1 interleukin 4 induced 1 1.418006166 0.015636205
593 BCKDHA branched chain keto acid dehydrogenase E1, alpha polypeptide -1.148444992 0.001727003
594 BCKDHB branched chain keto acid dehydrogenase E1, beta polypeptide -0.687946873 0.156787101
1629 DBT dihydrolipoamide branched chain transacylase E2 -2.138467417 4.04E-05
1738 DLD dihydrolipoamide dehydrogenase -0.309437161 0.194182069
35 ACADS acyl-CoA dehydrogenase, C-2 to C-3 short chain -0.781921247 0.001681216
34 ACADM acyl-CoA dehydrogenase, C-4 to C-12 straight chain -0.227530954 0.339717236
3712 IVD isovaleryl-CoA dehydrogenase 0.364308007 0.136514652
36 ACADSB acyl-CoA dehydrogenase, short/branched chain -1.370334091 0.001696882
27034 ACAD8 acyl-CoA dehydrogenase family, member 8 -0.547440131 0.091116266
3030 HADHA hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit
-1.199004767 0.000134058
1962 EHHADH enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase -0.456118174 0.175235142
1892 ECHS1 enoyl CoA hydratase, short chain, 1, mitochondrial 0.104757048 0.61074395
3033 HADH hydroxyacyl-CoA dehydrogenase -0.817026808 0.000522358
3028 HSD17B10 hydroxysteroid (17-beta) dehydrogenase 10 -0.218220037 0.082112071
30 ACAA1 acetyl-CoA acyltransferase 1 -0.243165988 0.078837838
10449 ACAA2 acetyl-CoA acyltransferase 2 -0.892178746 0.000406946
3032 HADHB hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), beta subunit
-0.176206766 0.336134576
5095 PCCA propionyl CoA carboxylase, alpha polypeptide -0.962865977 0.040167102
5096 PCCB propionyl CoA carboxylase, beta polypeptide -0.636381142 0.045189884
84693 MCEE methylmalonyl CoA epimerase -1.089729015 0.008120642
4594 MUT methylmalonyl CoA mutase -0.379457279 0.159824383
26275 HIBCH 3-hydroxyisobutyryl-CoA hydrolase -0.604614912 0.049045949
11112 HIBADH 3-hydroxyisobutyrate dehydrogenase -0.618580292 0.001237186
4329 ALDH6A1 aldehyde dehydrogenase 6 family, member A1 -1.980314485 0.006403709
217 ALDH2 aldehyde dehydrogenase 2 family (mitochondrial) 0.526938074 0.116496923
224 ALDH3A2 aldehyde dehydrogenase 3 family, member A2 -1.635199548 0.022669462
219 ALDH1B1 aldehyde dehydrogenase 1 family, member B1 -0.067959408 0.879445206
501 ALDH7A1 aldehyde dehydrogenase 7 family, member A1 -0.433351016 0.073731968
223 ALDH9A1 aldehyde dehydrogenase 9 family, member A1 -0.31800772 0.109525459
316 AOX1 aldehyde oxidase 1 -4.611602293 0.000559186
18 ABAT 4-aminobutyrate aminotransferase -2.334970307 0.014544169
56922 MCCC1 methylcrotonoyl-CoA carboxylase 1 (alpha) -1.16890529 0.001695464
64087 MCCC2 methylcrotonoyl-CoA carboxylase 2 (beta) -0.275297083 0.213689093
31
549 AUH AU RNA binding protein/enoyl-CoA hydratase -0.595108622 0.036469128
3155 HMGCL 3-hydroxymethyl-3-methylglutaryl-CoA lyase -0.160696682 0.441377191
5019 OXCT1 3-oxoacid CoA transferase 1 1.742802695 0.000484108
64064 OXCT2 3-oxoacid CoA transferase 2 -0.473291528 0.009046937
39 ACAT2 acetyl-CoA acetyltransferase 2 0.629875466 0.102936806
38 ACAT1 acetyl-CoA acetyltransferase 1 -1.624761864 0.001229512
3157 HMGCS1 3-hydroxy-3-methylglutaryl-CoA synthase 1 (soluble) 0.933801431 0.007789919
3158 HMGCS2 3-hydroxy-3-methylglutaryl-CoA synthase 2 (mitochondrial) -0.404657124 0.008328684
32
Table S5. Human expression data comparing lung adenocarcinoma to normal lung tissue (LUAD_TCGA) Gene ID Gene Symbol logFC AveExpr t P.Value adj.P.Val B
8140 SLC7A5 2.301489817 6.358231189 10.42262512 2.03E-23 1.99E-22 41.91341697
587 BCAT2 -0.022329943 5.405346113 -0.238943734 0.811234173 0.837543421 -7.962364892
586 BCAT1 -0.082200745 5.812571896 -0.390719929 0.696148682 0.734856037 -7.949366128
259307 IL4I1 1.802053865 3.662717891 7.146453383 2.70E-12 1.13E-11 16.96043713
593 BCKDHA -0.064986379 5.742374666 -0.805448303 0.420893276 0.471526877 -7.695807869
594 BCKDHB -0.089449287 3.848210819 -1.05811492 0.290446434 0.338490079 -7.215969219
1629 DBT -0.165486395 4.901371519 -2.308007721 0.021351989 0.030447339 -5.296980892
1738 DLD 0.037319195 6.153408635 0.518807164 0.604094408 0.648584069 -7.903129538
35 ACADS -0.396142929 4.654196909 -3.721228554 0.000217685 0.000404804 -1.096055568
34 ACADM -0.149175994 5.561180575 -1.893454362 0.058798186 0.078016723 -6.224218221
3712 IVD -0.454413704 6.120665928 -4.234544074 2.67E-05 5.56E-05 0.78537962
36 ACADSB -0.656685952 5.224157391 -5.221457536 2.48E-07 6.60E-07 5.310708694
27034 ACAD8 0.952248253 5.346434799 6.865131266 1.72E-11 6.71E-11 14.77617986
3030 HADHA -0.16085849 7.678322593 -3.398825913 0.000723518 0.001259949 -2.325968325
1962 EHHADH 0.029588819 3.912137766 0.267564907 0.789129991 0.818635495 -7.734194387
1892 ECHS1 0.496639082 6.83135147 6.780040815 2.98E-11 1.13E-10 14.08150294
3033 HADH -0.073366638 5.661570217 -0.888721427 0.374523663 0.425039729 -7.619794388
3028 HSD17B10 0.506258189 5.855151605 6.499293438 1.75E-10 6.21E-10 12.40300803
30 ACAA1 -0.407743414 5.772675264 -5.017906592 6.97E-07 1.77E-06 4.293828537
10449 ACAA2 -0.837258146 5.703806931 -8.277737019 8.78E-16 4.84E-15 24.34694946
3032 HADHB -0.021523161 6.805987063 -0.408996065 0.682694521 0.722433188 -7.971203158
5095 PCCA -0.246456074 3.753144879 -2.016385373 0.044223175 0.059868769 -5.753673006
5096 PCCB 0.343767432 5.710113172 4.699194071 3.27E-06 7.66E-06 2.850605682
84693 MCEE 0.132703208 2.801890502 1.308484783 0.191230609 0.232045672 -6.694952278
4594 MUT 0.11151478 5.342882293 1.519870588 0.129092016 0.161790721 -6.820741756
26275 HIBCH 0.207361423 4.500464409 2.463148936 0.014063513 0.020557426 -4.826842489
11112 HIBADH 0.546603418 5.672095469 6.273912746 6.92E-10 2.33E-09 11.07907501
4329 ALDH6A1 -0.143182697 3.97983577 -1.19603012 0.232176743 0.276353846 -7.092230071
217 ALDH2 -1.376449884 8.081884479 -10.37850121 2.99E-23 2.89E-22 41.38215198
224 ALDH3A2 -0.455354534 7.29385346 -3.207001887 0.001415631 0.002381613 -2.950344994
219 ALDH1B1 0.947103168 5.207573479 7.848908012 2.05E-14 1.02E-13 21.41181195
501 ALDH7A1 0.165878163 5.557560458 1.785293215 0.074739652 0.097505234 -6.400096771
223 ALDH9A1 -0.23186742 6.512121218 -3.239786141 0.00126511 0.002143239 -2.849056789
316 AOX1 -2.15049672 2.471108098 -12.67670724 1.18E-32 2.09E-31 63.05942585
18 ABAT -0.270201151 3.825653793 -1.616717801 0.106486521 0.135456773 -6.492303448
56922 MCCC1 -0.310875957 5.036842343 -3.089395627 0.002102324 0.003454369 -3.242611828
64087 MCCC2 0.60856239 6.249504932 7.598211993 1.22E-13 5.69E-13 19.51128747
549 AUH -0.307891419 3.26732002 -4.000960494 7.13E-05 0.000141411 0.193214559
33
3155 HMGCL 0.094091401 5.573266149 1.277615691 0.20189947 0.243699726 -7.181453788
5019 OXCT1 0.035856218 4.423932006 0.217854779 0.827619389 0.851982284 -7.835471736
64064 OXCT2 0.753014278 -1.341418463 3.932433184 9.43E-05 0.00018367 0.41322003
39 ACAT2 -0.435561364 4.614165503 -4.402822034 1.27E-05 2.77E-05 1.596491751
38 ACAT1 -0.637666221 5.665301524 -6.551388268 1.27E-10 4.55E-10 12.67279193
3157 HMGCS1 -1.093236292 6.104568228 -9.63348088 1.82E-20 1.43E-19 34.99752964
3158 HMGCS2 -3.494020182 -1.784574072 -8.586127586 8.40E-17 5.02E-16 27.27033633
34
Table S6. Human expression data comparing lung squamous cell carcinoma to normal lung tissue (LUSQ_TCGA) Gene ID Gene Symbol logFC AveExpr t P.Value adj.P.Val B
8140 SLC7A5 3.43564825 7.707835006 16.8420549 1.06E-51 1.70E-50 106.4644738
587 BCAT2 0.07009414 5.318307538 0.789526849 0.430141792 0.462844102 -7.897165607
586 BCAT1 -0.688161797 5.359877887 -3.719734352 0.000219746 0.000334717 -1.397369172
259307 IL4I1 1.296770374 3.453601085 6.269297405 7.30E-10 1.73E-09 11.21977782
593 BCKDHA 0.079824619 5.779109943 0.928442663 0.353582178 0.386300753 -7.802215369
594 BCKDHB -0.07226825 3.684809521 -0.840701212 0.400877901 0.433848221 -7.671861771
1629 DBT 0.164670241 5.022387251 2.257039152 0.024394191 0.030722493 -5.64125545
1738 DLD 0.472083711 6.473703967 5.931205524 5.30E-09 1.19E-08 8.827576396
35 ACADS -0.688906151 4.141312537 -8.68132614 4.38E-17 1.54E-16 27.21097897
34 ACADM -0.371239168 5.144530653 -4.691191107 3.43E-06 6.16E-06 2.582944004
3712 IVD -0.645242161 5.791703655 -6.78309739 3.03E-11 7.80E-11 13.8768321
36 ACADSB -0.937195974 4.796808291 -8.847962164 1.19E-17 4.34E-17 28.43082989
27034 ACAD8 -0.2502558 4.257898037 -3.025178338 0.002600091 0.003600605 -3.58739773
3030 HADHA -0.048020113 7.710428249 -0.821136923 0.411921353 0.444919058 -7.911004339
1962 EHHADH 1.034244319 4.674421838 8.219699856 1.45E-15 4.76E-15 23.86230287
1892 ECHS1 0.451173254 6.698471514 5.523701135 5.11E-08 1.08E-07 6.617537985
3033 HADH 0.009166245 5.628533204 0.10419606 0.917051457 0.925609627 -8.224064291
3028 HSD17B10 0.868935793 6.207759135 10.67223442 2.61E-24 1.33E-23 43.62216891
30 ACAA1 -0.833287959 5.297952201 -12.55693223 5.29E-32 3.90E-31 61.21244863
10449 ACAA2 -1.598338832 4.859858995 -11.46266038 1.91E-27 1.13E-26 50.77961214
3032 HADHB 0.085773364 6.782436419 1.478288742 0.1398986 0.16181226 -7.160907287
5095 PCCA -0.633654611 3.330750953 -7.456879784 3.44E-13 9.94E-13 18.47590952
5096 PCCB 0.842988114 6.090580657 9.092035539 1.72E-18 6.55E-18 30.34813146
84693 MCEE -0.141246973 2.454128328 -1.802403963 0.072025057 0.086354068 -6.183095022
4594 MUT 0.09017852 5.215313953 1.228996733 0.219594598 0.247453796 -7.445942964
26275 HIBCH 0.259467139 4.413522371 2.712491386 0.006885437 0.009149068 -4.440336234
11112 HIBADH 0.331576682 5.35150903 4.126505311 4.25E-05 6.89E-05 0.198328863
4329 ALDH6A1 -0.883081122 3.325422375 -9.281187504 3.75E-19 1.48E-18 31.99751141
217 ALDH2 -2.311539127 7.018829786 -17.05700482 9.50E-53 1.60E-51 108.8074819
224 ALDH3A2 -0.459840083 7.056178264 -3.137152311 0.001796571 0.002524887 -3.367434368
219 ALDH1B1 0.740029643 5.111153608 6.320069534 5.38E-10 1.29E-09 11.16559328
501 ALDH7A1 -0.906626359 4.440622329 -4.201445115 3.09E-05 5.08E-05 0.499215659
223 ALDH9A1 -0.10132745 6.470811855 -1.225070269 0.221069152 0.249042786 -7.501370219
316 AOX1 -3.443645528 1.534859041 -23.28947731 3.58E-84 1.74E-82 181.1221231
18 ABAT -0.815746782 3.178580439 -5.589189087 3.58E-08 7.66E-08 7.171077491
56922 MCCC1 0.554866022 5.692969451 4.016982659 6.71E-05 0.000107042 -0.247020887
64087 MCCC2 0.456443463 6.070667953 5.888844777 6.75E-09 1.51E-08 8.60376602
35
549 AUH -0.377647125 3.065586136 -5.361194814 1.22E-07 2.51E-07 6.064739271
3155 HMGCL -0.344838377 5.090438162 -4.626389578 4.64E-06 8.23E-06 2.296688655
5019 OXCT1 0.916244765 5.228583589 6.940823736 1.09E-11 2.90E-11 14.98423096
64064 OXCT2 0.136104799 -1.86673463 0.658902471 0.510232056 0.543357378 -7.109385516
39 ACAT2 0.588374543 5.528288775 4.66015788 3.96E-06 7.08E-06 2.469036769
38 ACAT1 -0.93819422 5.172873981 -11.63615179 3.76E-28 2.31E-27 52.39608243
3157 HMGCS1 0.255430691 7.291842146 1.752511445 0.080238867 0.095618141 -6.719621068
3158 HMGCS2 -4.265592639 -3.501736693 -10.30012009 6.98E-23 3.32E-22 40.98001202
36
Table S7. Metabolite Fragments Used for Isotope Quantification in GC/MS analysis Metabolite Carbons Formula m/z Leu 123456 C14H32O2NSi2 302 Ile 123456 C14H32O2NSi2 302 Val 12345 C13H30O2NSi2 288 Ala 123 C11H26O2NSi2 260 Asp 1234 C18H40O3NSi3 418 Glu 12345 C19H42O4NSi3 432 Lys 123456 C20H47O2N2Si3 431 Citrate 123456 C26H55O7Si4 591
37
Table S8. qRT-PCR Primer Sets Gene Forward (5’ à 3’) Reverse (5’ à 3’) Slc7a5 ATATCACGCTGCTCAACGGTG CTCCAGCATGTAGGCGTAGTC Bcat1 TCGGGGAGTTGATAACAAGATCC GGTCCTCACAGCAGATCGG Bcat2 AAAGCATACAAAGGTGGAGACC CGTAGAGGCTCGTTCCGTTG Bckdha CTCCTGTTGGGACGATCTGG CATTGGGCTGGATGAACTCAA Bckdhb AGTGCCCTGGATAACTCATTAGC GCATCGGAAGACTCCACCAAA Acadsb CCCAACCTGCTTGTCTCCTTG ATCCCTGGATCACCGATTTCT Pcca TTCATACCAATGCCTAGTGGTGT GACAGCCTCATCCGCCATTTT Auh AGCTGGCTCTAGCGTGTGA GTTCTGTTCTAACACATGGCTGA Hadhb ACTACATCAAAATGGGCTCTCAG AGCAGAAATGGAATGCGGACC Glut1 CAGTTCGGCTATAACACTGGTG GCCCCCGACAGAGAAGATG Eno1 TGCGTCCACTGGCATCTAC CAGAGCAGGCGCAATAGTTTTA 18s* CGCTTCCTTACCTGGTTGAT GAGCGACCAAAGGAACCATA Rpl13a* GGGCAGGTTCTGGTATTGGAT GGCTCGGAAATGGTAGGGG Gapdh* AGGTCGGTGTGAACGGATTTG TGTAGACCATGTAGTTGAGGTCA β-actin* GGCTGTATTCCCCTCCATCG CCAGTTGGTAACAATGCCATGT Rplp0* AGATTCGGGATATGCTGTTGGC TCGGGTCCTAGACCAGTGTTC B2m* TTCTGGTGCTTGTCTCACTGA CAGTATGTTCGGCTTCCCATTC Hprt* TCAGTCAACGGGGGACATAAA GGGGCTGTACTGCTTAACCAG Pgk1* ATGTCGCTTTCCAACAAGCTG GCTCCATTGTCCAAGCAGAAT * endogenous controls
References and Notes 1. L. A. Garraway, Genomics-driven oncology: Framework for an emerging paradigm. J. Clin.
Oncol. 31, 1806–1814 (2013). Medline doi:10.1200/JCO.2012.46.8934
2. N. Vasan, J. L. Boyer, R. S. Herbst, A RAS renaissance: Emerging targeted therapies for KRAS-mutated non-small cell lung cancer. Clin. Cancer Res. 20, 3921–3930 (2014). Medline doi:10.1158/1078-0432.CCR-13-1762
3. P. A. Muller, K. H. Vousden, Mutant p53 in cancer: New functions and therapeutic opportunities. Cancer Cell 25, 304–317 (2014). Medline doi:10.1016/j.ccr.2014.01.021
4. L. K. Boroughs, R. J. DeBerardinis, Metabolic pathways promoting cancer cell survival and growth. Nat. Cell Biol. 17, 351–359 (2015). Medline doi:10.1038/ncb3124
5. E. White, Exploiting the bad eating habits of Ras-driven cancers. Genes &. Development 27, 2065–2071 (2013).
6. F. Kruiswijk, C. F. Labuschagne, K. H. Vousden, p53 in survival, death and metabolic health: A lifeguard with a licence to kill. Nat. Rev. Mol. Cell Biol. 16, 393–405 (2015). Medline doi:10.1038/nrm4007
7. A. V. Biankin, N. Waddell, K. S. Kassahn, M. C. Gingras, L. B. Muthuswamy, A. L. Johns, D. K. Miller, P. J. Wilson, A. M. Patch, J. Wu, D. K. Chang, M. J. Cowley, B. B. Gardiner, S. Song, I. Harliwong, S. Idrisoglu, C. Nourse, E. Nourbakhsh, S. Manning, S. Wani, M. Gongora, M. Pajic, C. J. Scarlett, A. J. Gill, A. V. Pinho, I. Rooman, M. Anderson, O. Holmes, C. Leonard, D. Taylor, S. Wood, Q. Xu, K. Nones, J. L. Fink, A. Christ, T. Bruxner, N. Cloonan, G. Kolle, F. Newell, M. Pinese, R. S. Mead, J. L. Humphris, W. Kaplan, M. D. Jones, E. K. Colvin, A. M. Nagrial, E. S. Humphrey, A. Chou, V. T. Chin, L. A. Chantrill, A. Mawson, J. S. Samra, J. G. Kench, J. A. Lovell, R. J. Daly, N. D. Merrett, C. Toon, K. Epari, N. Q. Nguyen, A. Barbour, N. Zeps, N. Kakkar, F. Zhao, Y. Q. Wu, M. Wang, D. M. Muzny, W. E. Fisher, F. C. Brunicardi, S. E. Hodges, J. G. Reid, J. Drummond, K. Chang, Y. Han, L. R. Lewis, H. Dinh, C. J. Buhay, T. Beck, L. Timms, M. Sam, K. Begley, A. Brown, D. Pai, A. Panchal, N. Buchner, R. De Borja, R. E. Denroche, C. K. Yung, S. Serra, N. Onetto, D. Mukhopadhyay, M. S. Tsao, P. A. Shaw, G. M. Petersen, S. Gallinger, R. H. Hruban, A. Maitra, C. A. Iacobuzio-Donahue, R. D. Schulick, C. L. Wolfgang, R. A. Morgan, R. T. Lawlor, P. Capelli, V. Corbo, M. Scardoni, G. Tortora, M. A. Tempero, K. M. Mann, N. A. Jenkins, P. A. Perez-Mancera, D. J. Adams, D. A. Largaespada, L. F. Wessels, A. G. Rust, L. D. Stein, D. A. Tuveson, N. G. Copeland, E. A. Musgrove, A. Scarpa, J. R. Eshleman, T. J. Hudson, R. L. Sutherland, D. A. Wheeler, J. V. Pearson, J. D. McPherson, R. A. Gibbs, S. M. Grimmond, Australian Pancreatic Cancer Genome Initiative, Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes. Nature 491, 399–405 (2012). Medline doi:10.1038/nature11547
8. E. A. Collisson, J. D. Campbell, A. N. Brooks, A. H. Berger, W. Lee, J. Chmielecki, D. G. Beer, L. Cope, C. J. Creighton, L. Danilova, L. Ding, G. Getz, P. S. Hammerman, D. Neil Hayes, B. Hernandez, J. G. Herman, J. V. Heymach, I. Jurisica, R. Kucherlapati, D. Kwiatkowski, M. Ladanyi, G. Robertson, N. Schultz, R. Shen, R. Sinha, C. Sougnez, M.-S. Tsao, W. D. Travis, J. N. Weinstein, D. A. Wigle, M. D. Wilkerson, A. Chu, A. D. Cherniack, A. Hadjipanayis, M. Rosenberg, D. J. Weisenberger, P. W. Laird, A.
Radenbaugh, S. Ma, J. M. Stuart, L. Averett Byers, S. B. Baylin, R. Govindan, M. Meyerson, M. Rosenberg, S. B. Gabriel, K. Cibulskis, C. Sougnez, J. Kim, C. Stewart, L. Lichtenstein, E. S. Lander, M. S. Lawrence, G. Getz, C. Kandoth, R. Fulton, L. L. Fulton, M. D. McLellan, R. K. Wilson, K. Ye, C. C. Fronick, C. A. Maher, C. A. Miller, M. C. Wendl, C. Cabanski, L. Ding, E. Mardis, R. Govindan, C. J. Creighton, D. Wheeler, M. Balasundaram, Y. S. N. Butterfield, R. Carlsen, A. Chu, E. Chuah, N. Dhalla, R. Guin, C. Hirst, D. Lee, H. I. Li, M. Mayo, R. A. Moore, A. J. Mungall, J. E. Schein, P. Sipahimalani, A. Tam, R. Varhol, A. Gordon Robertson, N. Wye, N. Thiessen, R. A. Holt, S. J. M. Jones, M. A. Marra, J. D. Campbell, A. N. Brooks, J. Chmielecki, M. Imielinski, R. C. Onofrio, E. Hodis, T. Zack, C. Sougnez, E. Helman, C. Sekhar Pedamallu, J. Mesirov, A. D. Cherniack, G. Saksena, S. E. Schumacher, S. L. Carter, B. Hernandez, L. Garraway, R. Beroukhim, S. B. Gabriel, G. Getz, M. Meyerson, A. Hadjipanayis, S. Lee, H. S. Mahadeshwar, A. Pantazi, A. Protopopov, X. Ren, S. Seth, X. Song, J. Tang, L. Yang, J. Zhang, P.-C. Chen, M. Parfenov, A. Wei Xu, N. Santoso, L. Chin, P. J. Park, R. Kucherlapati, K. A. Hoadley, J. Todd Auman, S. Meng, Y. Shi, E. Buda, S. Waring, U. Veluvolu, D. Tan, P. A. Mieczkowski, C. D. Jones, J. V. Simons, M. G. Soloway, T. Bodenheimer, S. R. Jefferys, J. Roach, A. P. Hoyle, J. Wu, S. Balu, D. Singh, J. F. Prins, J. S. Marron, J. S. Parker, D. Neil Hayes, C. M. Perou, J. Liu, L. Cope, L. Danilova, D. J. Weisenberger, D. T. Maglinte, P. H. Lai, M. S. Bootwalla, D. J. Van Den Berg, T. Triche Jr., S. B. Baylin, P. W. Laird, M. Rosenberg, L. Chin, J. Zhang, J. Cho, D. DiCara, D. Heiman, P. Lin, W. Mallard, D. Voet, H. Zhang, L. Zou, M. S. Noble, M. S. Lawrence, G. Saksena, N. Gehlenborg, H. Thorvaldsdottir, J. Mesirov, M.-D. Nazaire, J. Robinson, G. Getz, W. Lee, B. Arman Aksoy, G. Ciriello, B. S. Taylor, G. Dresdner, J. Gao, B. Gross, V. E. Seshan, M. Ladanyi, B. Reva, R. Sinha, S. Onur Sumer, N. Weinhold, N. Schultz, R. Shen, C. Sander, S. Ng, S. Ma, J. Zhu, A. Radenbaugh, J. M. Stuart, C. C. Benz, C. Yau, D. Haussler, P. T. Spellman, M. D. Wilkerson, J. S. Parker, K. A. Hoadley, P. K. Kimes, D. Neil Hayes, C. M. Perou, B. M. Broom, J. Wang, Y. Lu, P. Kwok Shing Ng, L. Diao, L. Averett Byers, W. Liu, J. V. Heymach, C. I. Amos, J. N. Weinstein, R. Akbani, G. B. Mills, E. Curley, J. Paulauskis, K. Lau, S. Morris, T. Shelton, D. Mallery, J. Gardner, R. Penny, C. Saller, K. Tarvin, W. G. Richards, R. Cerfolio, A. Bryant, D. P. Raymond, N. A. Pennell, C. Farver, C. Czerwinski, L. Huelsenbeck-Dill, M. Iacocca, N. Petrelli, B. Rabeno, J. Brown, T. Bauer, O. Dolzhanskiy, O. Potapova, D. Rotin, O. Voronina, E. Nemirovich-Danchenko, K. V. Fedosenko, A. Gal, M. Behera, S. S. Ramalingam, G. Sica, D. Flieder, J. Boyd, J. E. Weaver, B. Kohl, D. Huy Quoc Thinh, G. Sandusky, H. Juhl, E. Duhig, P. Illei, E. Gabrielson, J. Shin, B. Lee, K. Rogers, D. Trusty, M. V. Brock, C. Williamson, E. Burks, K. Rieger-Christ, A. Holway, T. Sullivan, D. A. Wigle, M. K. Asiedu, F. Kosari, W. D. Travis, N. Rekhtman, M. Zakowski, V. W. Rusch, P. Zippile, J. Suh, H. Pass, C. Goparaju, Y. Owusu-Sarpong, J. M. S. Bartlett, S. Kodeeswaran, J. Parfitt, H. Sekhon, M. Albert, J. Eckman, J. B. Myers, R. Cheney, C. Morrison, C. Gaudioso, J. A. Borgia, P. Bonomi, M. Pool, M. J. Liptay, F. Moiseenko, I. Zaytseva, H. Dienemann, M. Meister, P. A. Schnabel, T. R. Muley, M. Peifer, C. Gomez-Fernandez, L. Herbert, S. Egea, M. Huang, L. B. Thorne, L. Boice, A. Hill Salazar, W. K. Funkhouser, W. Kimryn Rathmell, R. Dhir, S. A. Yousem, S. Dacic, F. Schneider, J. M. Siegfried, R. Hajek, M. A. Watson, S. McDonald, B. Meyers, B. Clarke, I. A. Yang, K. M. Fong, L. Hunter, M. Windsor, R. V. Bowman, S. Peters, I. Letovanec, K. Z. Khan, M. A. Jensen, E. E. Snyder, D.
Srinivasan, A. B. Kahn, J. Baboud, D. A. Pot, K. R. Mills Shaw, M. Sheth, T. Davidsen, J. A. Demchok, L. Yang, Z. Wang, R. Tarnuzzer, J. Claude Zenklusen, B. A. Ozenberger, H. J. Sofia, W. D. Travis, R. Cheney, B. Clarke, S. Dacic, E. Duhig, W. K. Funkhouser, P. Illei, C. Farver, N. Rekhtman, G. Sica, J. Suh, M.-S. Tsao, Cancer Genome Atlas Research Network, Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543–550 (2014). Medline doi:10.1038/nature13385
9. P. Vaupel, F. Kallinowski, P. Okunieff, Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: A review. Cancer Res. 49, 6449–6465 (1989). Medline
10. A. Hirayama, K. Kami, M. Sugimoto, M. Sugawara, N. Toki, H. Onozuka, T. Kinoshita, N. Saito, A. Ochiai, M. Tomita, H. Esumi, T. Soga, Quantitative metabolome profiling of colon and stomach cancer microenvironment by capillary electrophoresis time-of-flight mass spectrometry. Cancer Res. 69, 4918–4925 (2009). Medline doi:10.1158/0008-5472.CAN-08-4806
11. J. R. Mayers, M. G. Vander Heiden, Famine versus feast: Understanding the metabolism of tumors in vivo. Trends Biochem. Sci. 40, 130–140 (2015). Medline doi:10.1016/j.tibs.2015.01.004
12. C. Commisso, S. M. Davidson, R. G. Soydaner-Azeloglu, S. J. Parker, J. J. Kamphorst, S. Hackett, E. Grabocka, M. Nofal, J. A. Drebin, C. B. Thompson, J. D. Rabinowitz, C. M. Metallo, M. G. Vander Heiden, D. Bar-Sagi, Macropinocytosis of protein is an amino acid supply route in Ras-transformed cells. Nature 497, 633–637 (2013). Medline doi:10.1038/nature12138
13. J. J. Kamphorst, J. R. Cross, J. Fan, E. de Stanchina, R. Mathew, E. P. White, C. B. Thompson, J. D. Rabinowitz, Hypoxic and Ras-transformed cells support growth by scavenging unsaturated fatty acids from lysophospholipids. Proc. Natl. Acad. Sci. U.S.A. 110, 8882–8887 (2013). Medline doi:10.1073/pnas.1307237110
14. W. Palm, Y. Park, K. Wright, N. N. Pavlova, D. A. Tuveson, C. B. Thompson, The utilization of extracellular proteins as nutrients is suppressed by mTORC1. Cell 162, 259–270 (2015). Medline doi:10.1016/j.cell.2015.06.017
15. S. M. Davidson, T. Papagiannakopoulos, B. A. Olenchock, J. E. Heyman, M. A. Keibler, A. Luengo, M. R. Bauer, A. K. Jha, J. P. O’Brien, K. A. Pierce, D. Y. Gui, L. B. Sullivan, T. M. Wasylenko, L. Subbaraj, C. R. Chin, G. Stephanopolous, B. T. Mott, T. Jacks, C. B. Clish, M. G. Vander Heiden, Environment impacts the metabolic dependencies of Ras-driven non-small cell lung cancer. Cell Metab. 23, 517–528 (2016). Medline doi:10.1016/j.cmet.2016.01.007
16. J. Hu, J. W. Locasale, J. H. Bielas, J. O’Sullivan, K. Sheahan, L. C. Cantley, M. G. Vander Heiden, D. Vitkup, Heterogeneity of tumor-induced gene expression changes in the human metabolic network. Nat. Biotechnol. 31, 522–529 (2013). Medline doi:10.1038/nbt.2530
17. M. O. Yuneva, T. W. Fan, T. D. Allen, R. M. Higashi, D. V. Ferraris, T. Tsukamoto, J. M. Matés, F. J. Alonso, C. Wang, Y. Seo, X. Chen, J. M. Bishop, The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type. Cell Metab. 15, 157–170 (2012). Medline doi:10.1016/j.cmet.2011.12.015
18. J. R. Mayers, C. Wu, C. B. Clish, P. Kraft, M. E. Torrence, B. P. Fiske, C. Yuan, Y. Bao, M. K. Townsend, S. S. Tworoger, S. M. Davidson, T. Papagiannakopoulos, A. Yang, T. L. Dayton, S. Ogino, M. J. Stampfer, E. L. Giovannucci, Z. R. Qian, D. A. Rubinson, J. Ma, H. D. Sesso, J. M. Gaziano, B. B. Cochrane, S. Liu, J. Wactawski-Wende, J. E. Manson, M. N. Pollak, A. C. Kimmelman, A. Souza, K. Pierce, T. J. Wang, R. E. Gerszten, C. S. Fuchs, M. G. Vander Heiden, B. M. Wolpin, Elevation of circulating branched-chain amino acids is an early event in human pancreatic adenocarcinoma development. Nat. Med. 20, 1193–1198 (2014). Medline doi:10.1038/nm.3686
19. N. Bardeesy, A. J. Aguirre, G. C. Chu, K. H. Cheng, L. V. Lopez, A. F. Hezel, B. Feng, C. Brennan, R. Weissleder, U. Mahmood, D. Hanahan, M. S. Redston, L. Chin, R. A. Depinho, Both p16(Ink4a) and the p19(Arf)-p53 pathway constrain progression of pancreatic adenocarcinoma in the mouse. Proc. Natl. Acad. Sci. U.S.A. 103, 5947–5952 (2006). Medline doi:10.1073/pnas.0601273103
20. M. DuPage, A. L. Dooley, T. Jacks, Conditional mouse lung cancer models using adenoviral or lentiviral delivery of Cre recombinase. Nat. Protoc. 4, 1064–1072 (2009). Medline doi:10.1038/nprot.2009.95
21. A. E. Harper, R. H. Miller, K. P. Block, Branched-chain amino acid metabolism. Annu. Rev. Nutr. 4, 409–454 (1984). Medline doi:10.1146/annurev.nu.04.070184.002205
22. C. R. Green, M. Wallace, A. S. Divakaruni, S. A. Phillips, A. N. Murphy, T. P. Ciaraldi, C. M. Metallo, Branched-chain amino acid catabolism fuels adipocyte differentiation and lipogenesis. Nat. Chem. Biol. 12, 15–21 (2016). Medline doi:10.1038/nchembio.1961
23. J. T. Brosnan, Interorgan amino acid transport and its regulation. J. Nutr. 133 (suppl. 1), 2068S–2072S (2003). Medline
24. K. Birsoy, T. Wang, W. W. Chen, E. Freinkman, M. Abu-Remaileh, D. M. Sabatini, An essential role of the mitochondrial electron transport chain in cell proliferation is to enable aspartate synthesis. Cell 162, 540–551 (2015). Medline doi:10.1016/j.cell.2015.07.016
25. L. B. Sullivan, D. Y. Gui, A. M. Hosios, L. N. Bush, E. Freinkman, M. G. Vander Heiden, Supporting aspartate biosynthesis is an essential function of respiration in proliferating cells. Cell 162, 552–563 (2015). Medline doi:10.1016/j.cell.2015.07.017
26. S. R. Hingorani, L. Wang, A. S. Multani, C. Combs, T. B. Deramaudt, R. H. Hruban, A. K. Rustgi, S. Chang, D. A. Tuveson, Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice. Cancer Cell 7, 469–483 (2005). Medline doi:10.1016/j.ccr.2005.04.023
27. H. Friess, J. Langhans, M. Ebert, H. G. Beger, J. Stollfuss, S. N. Reske, M. W. Büchler, Diagnosis of pancreatic cancer by 2[18F]-fluoro-2-deoxy-D-glucose positron emission tomography. Gut 36, 771–777 (1995). Medline doi:10.1136/gut.36.5.771
28. K. Kubota, T. Matsuzawa, T. Fujiwara, M. Ito, J. Hatazawa, K. Ishiwata, R. Iwata, T. Ido, Differential diagnosis of lung tumor with positron emission tomography: A prospective study. J. Nucl. Med. 31, 1927–1932 (1990). Medline
29. K. B. Nolop, C. G. Rhodes, L. H. Brudin, R. P. Beaney, T. Krausz, T. Jones, J. M. Hughes, Glucose utilization in vivo by human pulmonary neoplasms. Cancer 60, 2682–2689
(1987). Medline doi:10.1002/1097-0142(19871201)60:11<2682::AID-CNCR2820601118>3.0.CO;2-H
30. T. Barrett, D. B. Troup, S. E. Wilhite, P. Ledoux, C. Evangelista, I. F. Kim, M. Tomashevsky, K. A. Marshall, K. H. Phillippy, P. M. Sherman, R. N. Muertter, M. Holko, O. Ayanbule, A. Yefanov, A. Soboleva, NCBI GEO: Archive for functional genomics data sets—10 years on. Nucleic Acids Res. 39 (database), D1005–D1010 (2011). Medline doi:10.1093/nar/gkq1184
31. J. J. Kamphorst, M. Nofal, C. Commisso, S. R. Hackett, W. Lu, E. Grabocka, M. G. Vander Heiden, G. Miller, J. A. Drebin, D. Bar-Sagi, C. B. Thompson, J. D. Rabinowitz, Human pancreatic cancer tumors are nutrient poor and tumor cells actively scavenge extracellular protein. Cancer Res. 75, 544–553 (2015). Medline doi:10.1158/0008-5472.CAN-14-2211
32. R. J. DeBerardinis, A. Mancuso, E. Daikhin, I. Nissim, M. Yudkoff, S. Wehrli, C. B. Thompson, Beyond aerobic glycolysis: Transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc. Natl. Acad. Sci. U.S.A. 104, 19345–19350 (2007). Medline doi:10.1073/pnas.0709747104
33. I. Marin-Valencia, C. Yang, T. Mashimo, S. Cho, H. Baek, X. L. Yang, K. N. Rajagopalan, M. Maddie, V. Vemireddy, Z. Zhao, L. Cai, L. Good, B. P. Tu, K. J. Hatanpaa, B. E. Mickey, J. M. Matés, J. M. Pascual, E. A. Maher, C. R. Malloy, R. J. Deberardinis, R. M. Bachoo, Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo. Cell Metab. 15, 827–837 (2012). Medline doi:10.1016/j.cmet.2012.05.001
34. K. Sellers, M. P. Fox, M. Bousamra 2nd, S. P. Slone, R. M. Higashi, D. M. Miller, Y. Wang, J. Yan, M. O. Yuneva, R. Deshpande, A. N. Lane, T. W. Fan, Pyruvate carboxylase is critical for non-small-cell lung cancer proliferation. J. Clin. Invest. 125, 687–698 (2015). Medline doi:10.1172/JCI72873
35. E. A. Maher, I. Marin-Valencia, R. M. Bachoo, T. Mashimo, J. Raisanen, K. J. Hatanpaa, A. Jindal, F. M. Jeffrey, C. Choi, C. Madden, D. Mathews, J. M. Pascual, B. E. Mickey, C. R. Malloy, R. J. DeBerardinis, Metabolism of [U-13 C]glucose in human brain tumors in vivo. NMR Biomed. 25, 1234–1244 (2012). Medline doi:10.1002/nbm.2794
36. S. Tardito, A. Oudin, S. U. Ahmed, F. Fack, O. Keunen, L. Zheng, H. Miletic, P. Ø. Sakariassen, A. Weinstock, A. Wagner, S. L. Lindsay, A. K. Hock, S. C. Barnett, E. Ruppin, S. H. Mørkve, M. Lund-Johansen, A. J. Chalmers, R. Bjerkvig, S. P. Niclou, E. Gottlieb, Glutamine synthetase activity fuels nucleotide biosynthesis and supports growth of glutamine-restricted glioblastoma. Nat. Cell Biol. 17, 1556–1568 (2015). Medline doi:10.1038/ncb3272
37. C. T. Hensley, B. Faubert, Q. Yuan, N. Lev-Cohain, E. Jin, J. Kim, L. Jiang, B. Ko, R. Skelton, L. Loudat, M. Wodzak, C. Klimko, E. McMillan, Y. Butt, M. Ni, D. Oliver, J. Torrealba, C. R. Malloy, K. Kernstine, R. E. Lenkinski, R. J. DeBerardinis, Metabolic Heterogeneity in Human Lung Tumors. Cell 164, 681–694 (2016). Medline doi:10.1016/j.cell.2015.12.034
38. M. Tönjes, S. Barbus, Y. J. Park, W. Wang, M. Schlotter, A. M. Lindroth, S. V. Pleier, A. H. Bai, D. Karra, R. M. Piro, J. Felsberg, A. Addington, D. Lemke, I. Weibrecht, V. Hovestadt, C. G. Rolli, B. Campos, S. Turcan, D. Sturm, H. Witt, T. A. Chan, C. Herold-
Mende, R. Kemkemer, R. König, K. Schmidt, W. E. Hull, S. M. Pfister, M. Jugold, S. M. Hutson, C. Plass, J. G. Okun, G. Reifenberger, P. Lichter, B. Radlwimmer, BCAT1 promotes cell proliferation through amino acid catabolism in gliomas carrying wild-type IDH1. Nat. Med. 19, 901–908 (2013). Medline doi:10.1038/nm.3217
39. W. D. Dewys, C. Begg, P. T. Lavin, P. R. Band, J. M. Bennett, J. R. Bertino, M. H. Cohen, H. O. Douglass Jr., P. F. Engstrom, E. Z. Ezdinli, J. Horton, G. J. Johnson, C. G. Moertel, M. M. Oken, C. Perlia, C. Rosenbaum, M. N. Silverstein, R. T. Skeel, R. W. Sponzo, D. C. Tormey, Eastern Cooperative Oncology Group, Prognostic effect of weight loss prior to chemotherapy in cancer patients. Am. J. Med. 69, 491–497 (1980). Medline doi:10.1016/S0149-2918(05)80001-3
40. M. F. Clasquin, E. Melamud, J. D. Rabinowitz, LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine (Wiley, 2002).
41. M. R. Antoniewicz, D. F. Kraynie, L. A. Laffend, J. González-Lergier, J. K. Kelleher, G. Stephanopoulos, Metabolic flux analysis in a nonstationary system: Fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol. Metab. Eng. 9, 277–292 (2007). Medline doi:10.1016/j.ymben.2007.01.003
42. C. A. Fernandez, C. Des Rosiers, S. F. Previs, F. David, H. Brunengraber, Correction of 13C mass isotopomer distributions for natural stable isotope abundance. J. Mass Spectrom. 31, 255–262 (1996). Medline doi:10.1002/(SICI)1096-9888(199603)31:3<255::AID-JMS290>3.0.CO;2-3
43. J. Yuan, B. D. Bennett, J. D. Rabinowitz, Kinetic flux profiling for quantitation of cellular metabolic fluxes. Nat. Protoc. 3, 1328–1340 (2008). Medline doi:10.1038/nprot.2008.131
44. J. Vandesompele, K. De Preter, F. Pattyn, B. Poppe, N. Van Roy, A. De Paepe, F. Speleman, Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3, research0034.1 (2002). Medline doi:10.1186/gb-2002-3-7-research0034
45. Z. Wu, R. A. Irizarry, Preprocessing of oligonucleotide array data. Nat. Biotechnol. 22, 656–658, author reply 658 (2004). Medline doi:10.1038/nbt0604-656b
46. G. K. Smyth, Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, e3 (2004). Medline doi:10.2202/1544-6115.1027
47. Y. Benjamini, Y. Hochberg, Controlling the false discovery rate—A practical and powerful approach to multiple testing. J.R. Stat. Soc. 57, 289–300 (1995).
48. M. Kanehisa, S. Goto, M. Furumichi, M. Tanabe, M. Hirakawa, KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 38 (Database), D355–D360 (2010). Medline doi:10.1093/nar/gkp896
49. C. Commisso, R. J. Flinn, D. Bar-Sagi, Determining the macropinocytic index of cells through a quantitative image-based assay. Nat. Protoc. 9, 182–192 (2014). Medline doi:10.1038/nprot.2014.004