MCT1 Modulates Cancer Cell Pyruvate Export and Growth of Tumors that Co-express MCT1 and MCT4 - PubMed (original) (raw)

. 2016 Feb 23;14(7):1590-1601.

doi: 10.1016/j.celrep.2016.01.057. Epub 2016 Feb 11.

Nicholas A Graham 2, Wen Gu 1, Carolina Espindola Camacho 1, Vei Mah 3, Erin L Maresh 3, Mohammed Alavi 3, Lora Bagryanova 3, Pascal A L Krotee 1, Brian K Gardner 4, Iman Saramipoor Behbahan 5, Steve Horvath 6, David Chia 7, Ingo K Mellinghoff 8, Sara A Hurvitz 9, Steven M Dubinett 10, Susan E Critchlow 11, Siavash K Kurdistani 12, Lee Goodglick 7, Daniel Braas 13, Thomas G Graeber 14, Heather R Christofk 15

Affiliations

MCT1 Modulates Cancer Cell Pyruvate Export and Growth of Tumors that Co-express MCT1 and MCT4

Candice Sun Hong et al. Cell Rep. 2016.

Abstract

Monocarboxylate transporter 1 (MCT1) inhibition is thought to block tumor growth through disruption of lactate transport and glycolysis. Here, we show MCT1 inhibition impairs proliferation of glycolytic breast cancer cells co-expressing MCT1 and MCT4 via disruption of pyruvate rather than lactate export. MCT1 expression is elevated in glycolytic breast tumors, and high MCT1 expression predicts poor prognosis in breast and lung cancer patients. Acute MCT1 inhibition reduces pyruvate export but does not consistently alter lactate transport or glycolytic flux in breast cancer cells that co-express MCT1 and MCT4. Despite the lack of glycolysis impairment, MCT1 loss-of-function decreases breast cancer cell proliferation and blocks growth of mammary fat pad xenograft tumors. Our data suggest MCT1 expression is elevated in glycolytic cancers to promote pyruvate export that when inhibited, enhances oxidative metabolism and reduces proliferation. This study presents an alternative molecular consequence of MCT1 inhibitors, further supporting their use as anti-cancer therapeutics.

Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1

Figure 1. Unbiased gene expression analysis finds that MCT1 correlates with glycolytic phenotype in breast cancer

a, Breast tumors with high and low FDG uptake have distinct gene expression signatures. Transcript levels from 11 human breast cancers were ranked by the average correlation with tumor FDG maximum standardized uptake value (SUVmax) and cell line glycolytic phenotype (nmol lactate produced/nmol oxygen consumed) and arranged from left to right in order of increasing FDG uptake. Red and green denote high and low average correlation coefficients, respectively. MCT1 is the top-ranked of 13,374 genes. The inset table lists metabolic pathways enriched in highly glycolytic tumors and cell lines (PPP, pentose phosphate pathway; Glyc/Gluc, glycolysis/gluconeogenesis). b, Highly glycolytic tumors and cell lines demonstrate coordinate upregulation of glycolysis genes and MCT1. Genes within the glycolysis pathway are colored red or green to denote high and low correlation coefficients with glycolytic phenotype, respectively. c, Levels of MCT1, but not other MCT family members, are highly correlated with glycolytic phenotype in breast tumors and cell lines. The Pearson correlation coefficient with FDG uptake in human breast tumors (left) and glycolytic phenotype in human breast cancer cell lines (right) is depicted for microarray probes recognizing MCT1-4 family members. d, Scatter plots of MCT1 and MCT4 expression demonstrate that MCT1 but not MCT4 is highly correlated with glycolytic phenotypes. Transcript levels are plotted versus FDG uptake for human breast tumors (left) and glycolytic phenotype for human breast cancer cell lines (right). P-values are the two-tailed significance of the Pearson correlation coefficient. See also Figure S1.

Figure 2

Figure 2. Elevated MCT1 levels are indicative of tumor malignancy and poor breast and lung cancer patient survival

a, Immunohistochemistry of human normal breast and breast invasive ductal carcinoma (IDC) with an antibody towards MCT1 indicates higher MCT1 expression in the malignant tissue. Images are shown at X 100 magnification. b, The mean integrated MCT1 expression as determined by immunohistochemistry on a breast tissue microarray is compared across breast histologies and histopathologies. MCT1 expression is significantly increased in ductal carcinoma in situ (DCIS, P = 0.003), invasive ductal carcinoma (IDC, P < 0.001), and lymph node metastatic lesions (LN mets, P = 0.004) compared to adjacent non-malignant glandular epithelium (“normal”) or epithelium from voluntary breast reductions (BR). There is no significant difference between normal breast glandular epithelium and ductal hyperplasia (Ductal Hyper.) lesions. **c**, The mean integrated MCT1 expression as determined by immunohistochemistry on a lung tissue microarrary is compared across lung histologies and histopathologies. MCT1 expression is significantly increased in adenocarcinoma (Adeno, P < 0.001), adeno-squamous (Adeno-Squam, P < 0.001), squamous cell (P < 0.001) and large cell (P < 0.001) compared to adjacent non-malignant bronchial epithelium. Expression of MCT1 is significantly elevated in squamous and large cell tumors compared to adenocarcinomas and adeno-squamous tumors (P < 0.001 for both). For **b, c**, error bars denote standard error of the mean, and n = number of tissue array spots analyzed. **d**, Higher MCT1 expression levels predicts poorer survival in women with invasive ductal carcinoma of the breast. Kaplan-Meier survival plot shows patients with lower MCT1 expression (< 2.0 mean integrated intensity) depicted as a green line, and higher MCT1 expression (≥ 2.0 mean integrated intensity) depicted as a red line. **e**, Higher MCT1 expression levels predict poorer survival in individuals with NSCLC. Kaplan-Meier survival plot shows patients with lower MCT1 expression (≤ 1.0 mean integrated intensity) depicted as a green line and higher MCT1 expression (> 1.0 mean integrated intensity) depicted as a red line. f, Serum lactate (left) and pyruvate (right) concentrations from Stage I versus Stage IV lung cancer patients. For d, e, f, n = number of individuals in each category.

Figure 3

Figure 3. MCT1 is critical for pyruvate export in breast cancer cell lines

a, Gene expression profiles from SUM149PT cells expressing scrambled shRNA (control) and shRNA towards MCT1 (knockdown) were used to generate a ranked list of transcripts that are differentially expressed upon MCT1 knockdown. This ranked list was compared to a ranked list of transcripts that correlate with high FDG uptake in breast tumors from patients using the rank-rank hypergeometric overlap (RRHO) algorithm. The resulting overlap from the ranked lists, represented as a hypergeometric heat map, indicates that MCT1 knockdown renders glycolytic SUM149PT breast cancer cells less similar to tumors with high FDG uptake. The direction-signed log10-transformed hypergeometric p-values are indicated in the accompanying color scale. b, Heatmap indicating fold changes in expression levels of genes in the oxidative phosphorylation gene set from SUM149PT cells treated with DMSO or AZD3965 (MCT1i) for 24 hr. c, Cellular oxygen consumption rates 24 hrs post treatment with DMSO versus 250 nM AZD3965 (MCT1i). d, Lactate and pyruvate export rates 4 hours post treatment of the indicated cell lines with DMSO or 250 nM AZD3965 (MCT1i). e, Percentage of the 13C-labeled M1 lactate isotopomer from cells 24 hr post labeling with 1-13C-lactate and treatment with DMSO or 250 nM AZD3965 (MCT1i) in the presence or absence of 4 mM glutamine as determined by LC-MS/MS. f, Percentage of the 13C-labeled M2 lactate isotopomer from cells 24 hr post labeling with 1,2-13C-glucose and treatment with DMSO or 250 nM AZD3965 (MCT1i) as determined by LC-MS/MS. g, Intracellular pyruvate levels from the indicated cell lines treated with DMSO, 250 nM MCT1i, or 5 mM methyl-pyruvate for 30min. h, Relative abundance of media lactate and pyruvate post treatment of SUM149PT cells with 250 nM AZD3965 (MCT1i) for the indicated times as determined by GC-MS. Error bars in c denote standard error of mean (n=5). Error bars in d–g denote standard deviation (n=3). * denotes p < 0.05; ** denotes p < 0.01. See also Figure S2 and S3

Figure 4

Figure 4. MCT1 loss-of-function reduces breast cancer cell proliferation and tumor growth

a, Proliferation rates of the indicated breast cancer cell lines stably expressing shRNA that knocks down MCT1 expression (MCT1 shRNA) versus control scrambled shRNA (scramble shRNA), and vehicle (DMSO) treated cells versus 250 nM AZD3965 (MCT1i). b, Proliferation rates of the indicated cell lines treated for 4 days with DMSO or 5mM methyl-pyruvate. c, Percentage of MCT1 knockdown cells (MCT1 shRNA) versus control cells (scramble shRNA) in the G0/G1 phase of the cell cycle. d and e, Relative tumor volumes (d) and FDG-PET/CT images (e) from NSG mice with mammary fat pad xenograft tumors derived from SUM149PT cells treated by oral gavage twice daily with either 0.5% hydroxypropyl methyl cellulose/0.1%tween (vehicle) or 0.1ml/10g AZD3965 (MCT1i) for seven days. In (e) T indicates tumor, and values shown represent mean injected dose per gram (%ID/g) calculated from tumor regions of interest. f, Proliferation rates of indicated breast cancer cell lines after five days of treatment with DMSO, MCT1i (IC50), metformin (IC50), metformin + MCT1i (IC50 for both), or phenformin (IC50), phenformin + MCT1i (IC50 for both). MCT1i was replenished every day. g, Schematic representation of the impact of MCT1 inhibition on breast cancer cell metabolism and proliferation. AZD3965 consistently reduces pyruvate export, increases oxygen consumption, and reduces proliferation rates. Dual treatment of AZD3965 with metformin or phenformin further reduces proliferation rates, presumably by blocking the compensatory switch to oxidative metabolism caused by MCT1 inhibition to sustain proliferation. Error bars in a–c denote standard deviation n=3). Error bars in e denote standard error of mean. For a–c and f, * denotes p < 0.05, and ** denotes p < 0.01. See Figure S4.

Similar articles

Cited by

References

    1. Bonen A, Miskovic D, Tonouchi M, Lemieux K, Wilson MC, Marette A, Halestrap AP. Abundance and subcellular distribution of MCT1 and MCT4 in heart and fast-twitch skeletal muscles. American journal of physiology. Endocrinology and metabolism. 2000;278:E1067–1077. - PubMed
    1. Chang HY, Nuyten DS, Sneddon JB, Hastie T, Tibshirani R, Sorlie T, Dai H, He YD, van’t Veer LJ, Bartelink H, et al. Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. Proc Natl Acad Sci U S A. 2005;102:3738–3743. - PMC - PubMed
    1. Chen H, Wang L, Beretov J, Hao J, Xiao W, Li Y. Co-expression of CD147/EMMPRIN with monocarboxylate transporters and multiple drug resistance proteins is associated with epithelial ovarian cancer progression. Clin Exp Metastasis. 2010;27:557–569. - PubMed
    1. Choi JW, Kim Y, Lee JH, Kim YS. Prognostic significance of lactate/proton symporters MCT1, MCT4, and their chaperone CD147 expressions in urothelial carcinoma of the bladder. Urology. 2014;84:245 e249–215. - PubMed
    1. Doherty JR, Yang C, Scott KE, Cameron MD, Fallahi M, Li W, Hall MA, Amelio AL, Mishra JK, Li F, et al. Blocking lactate export by inhibiting the Myc target MCT1 Disables glycolysis and glutathione synthesis. Cancer Res. 2014;74:908–920. - PMC - PubMed

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources