|
1
|
Napier KJ, Scheerer M and Misra S:
Esophageal cancer: A Review of epidemiology, pathogenesis, staging
workup and treatment modalities. World J Gastrointest Oncol.
6:112–120. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Abnet CC, Arnold M and Wei WQ:
Epidemiology of esophageal squamous cell carcinoma.
Gastroenterology. 154:360–373. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Mandard AM, Hainaut P and Hollstein M:
Genetic steps in the development of squamous cell carcinoma of the
esophagus. Mutat Res. 462:335–342. 2000. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Ohashi S, Miyamoto S, Kikuchi O, Goto T,
Amanuma Y and Muto M: Recent advances from basic and clinical
studies of esophageal squamous cell carcinoma. Gastroenterology.
149:1700–1715. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Halestrap AP and Price NT: The
proton-linked monocarboxylate transporter (MCT) family: Structure,
function and regulation. Biochem J. 343:281–299. 1999. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Halestrap AP and Wilson MC: The
monocarboxylate transporter family - role and regulation. IUBMB
Life. 64:109–119. 2012. View
Article : Google Scholar : PubMed/NCBI
|
|
7
|
Juel C and Halestrap AP: Lactate transport
in skeletal muscle - role and regulation of the monocarboxylate
transporter. J Physiol. 517:633–642. 1999. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Bonen A: The expression of lactate
transporters (MCT1 and MCT4) in heart and muscle. Eur J Appl
Physiol. 86:6–11. 2001. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Bergersen L, Rafiki A and Ottersen OP:
Immunogold cytochemistry identifies specialized membrane domains
for monocarboxylate transport in the central nervous system.
Neurochem Res. 27:89–96. 2002. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Lunt SY and Vander Heiden MG: Aerobic
glycolysis: Meeting the metabolic requirements of cell
proliferation. Annu Rev Cell Dev Biol. 27:441–464. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Doyen J, Trastour C, Ettore F, Peyrottes
I, Toussant N, Gal J, Ilc K, Roux D, Parks SK, Ferrero JM, et al:
Expression of the hypoxia-inducible monocarboxylate transporter
MCT4 is increased in triple negative breast cancer and correlates
independently with clinical outcome. Biochem Biophys Res Commun.
451:54–61. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Kwon JE, Jung WH and Koo JS: The
expression of metabolism-related proteins in phyllodes tumors.
Tumour Biol. 34:115–124. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Witkiewicz AK, Whitaker-Menezes D,
Dasgupta A, Philp NJ, Lin Z, Gandara R, Sneddon S,
Martinez-Outschoorn UE, Sotgia F and Lisanti MP: Using the ‘reverse
Warburg effect’ to identify high-risk breast cancer patients:
Stromal MCT4 predicts poor clinical outcome in triple-negative
breast cancers. Cell Cycle. 11:1108–1117. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Gao HJ, Zhao MC, Zhang YJ, Zhou DS, Xu L,
Li GB, Chen MS and Liu J: Monocarboxylate transporter 4 predicts
poor prognosis in hepatocellular carcinoma and is associated with
cell proliferation and migration. J Cancer Res Clin Oncol.
141:1151–1162. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Ohno A, Yorita K, Haruyama Y, Kondo K,
Kato A, Ohtomo T, Kawaguchi M, Marutuska K, Chijiiwa K and Kataoka
H: Aberrant expression of monocarboxylate transporter 4 in tumour
cells predicts an unfavourable outcome in patients with
hepatocellular carcinoma. Liver Int. 34:942–952. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Baek G, Tse YF, Hu Z, Cox D, Buboltz N,
McCue P, Yeo CJ, White MA, DeBerardinis RJ, Knudsen ES, et al: MCT4
defines a glycolytic subtype of pancreatic cancer with poor
prognosis and unique metabolic dependencies. Cell Reports.
9:2233–2249. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Nakayama Y, Torigoe T, Inoue Y, Minagawa
N, Izumi H, Kohno K and Yamaguchi K: Prognostic significance of
monocarboxylate transporter 4 expression in patients with
colorectal cancer. Exp Ther Med. 3:25–30. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Zhu J, Wu YN, Zhang W, Zhang XM, Ding X,
Li HQ, Geng M, Xie ZQ and Wu HM: Monocarboxylate transporter 4
facilitates cell proliferation and migration and is associated with
poor prognosis in oral squamous cell carcinoma patients. PLoS One.
9:e879042014. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Zhao Z, Han F, He Y, Yang S, Hua L, Wu J
and Zhan W: Stromal-epithelial metabolic coupling in gastric
cancer: Stromal MCT4 and mitochondrial TOMM20 as poor prognostic
factors. Eur J Surg Oncol. 40:1361–1368. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Vander Heiden MG, Cantley LC and Thompson
CB: Understanding the Warburg effect: The metabolic requirements of
cell proliferation. Science. 324:1029–1033. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Shlomi T, Benyamini T, Gottlieb E, Sharan
R and Ruppin E: Genome-scale metabolic modeling elucidates the role
of proliferative adaptation in causing the Warburg effect. PLOS
Comput Biol. 7:e10020182011. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Gatenby RA and Gillies RJ: Why do cancers
have high aerobic glycolysis? Nat Rev Cancer. 4:891–899. 2004.
View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Dimmer KS, Friedrich B, Lang F, Deitmer JW
and Bröer S: The low-affinity monocarboxylate transporter MCT4 is
adapted to the export of lactate in highly glycolytic cells.
Biochem J. 350:219–227. 2000. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Cairns RA, Harris IS and Mak TW:
Regulation of cancer cell metabolism. Nat Rev Cancer. 11:85–95.
2011. View
Article : Google Scholar : PubMed/NCBI
|
|
25
|
Parks SK, Chiche J and Pouyssegur J: pH
control mechanisms of tumor survival and growth. J Cell Physiol.
226:299–308. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Blanker MH, Norg RJ and van der Heide WK:
A new approach to patients with lower urinary tract symptoms. Br J
Gen Pract. 62:344–345. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Manning BD and Cantley LC: AKT/PKB
signaling: Navigating downstream. Cell. 129:1261–1274. 2007.
View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Youle RJ and Strasser A: The BCL-2 protein
family: Opposing activities that mediate cell death. Nat Rev Mol
Cell Biol. 9:47–59. 2008. View
Article : Google Scholar : PubMed/NCBI
|
|
29
|
Cory S, Huang DC and Adams JM: The Bcl-2
family: Roles in cell survival and oncogenesis. Oncogene.
22:8590–8607. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Oltvai ZN, Milliman CL and Korsmeyer SJ:
Bcl-2 heterodimerizes in vivo with a conserved homolog, Bax, that
accelerates programmed cell death. Cell. 74:609–619. 1993.
View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Riedl SJ and Salvesen GS: The apoptosome:
Signalling platform of cell death. Nat Rev Mol Cell Biol.
8:405–413. 2007. View
Article : Google Scholar : PubMed/NCBI
|
|
32
|
Fan TJ, Han LH, Cong RS and Liang J:
Caspase family proteases and apoptosis. Acta Biochim Biophys Sin
(Shanghai). 37:719–727. 2005. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Hsieh FY and Lavori PW: Sample-size
calculations for the Cox proportional hazards regression model with
nonbinary covariates. Control Clin Trials. 21:552–560. 2000.
View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Gerlinger M, Santos CR, Spencer-Dene B,
Martinez P, Endesfelder D, Burrell RA, Vetter M, Jiang M, Saunders
RE, Kelly G, et al: Genome-wide RNA interference analysis of renal
carcinoma survival regulators identifies MCT4 as a Warburg effect
metabolic target. J Pathol. 227:146–156. 2012. View Article : Google Scholar : PubMed/NCBI
|
