|
1
|
Lin D, Meng X, Xu L, Ding L, Garg M, Yang
H, Liu L, Hao J, Wang M, Nagata Y, et al: Comprehensive molecular
characterization of esophageal squamous cell carcinoma. Cancer Res.
74:22252014. View Article : Google Scholar
|
|
2
|
Lee CH, Lee JM, Wu DC, Hsu HK, Kao EL,
Huang HL, Wang TN, Huang MC and Wu MT: Independent and combined
effects of alcohol intake, tobacco smoking and betel quid chewing
on the risk of esophageal cancer in Taiwan. Int J Cancer.
113:475–482. 2005. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Znaor A, Brennan P, Gajalakshmi V, Mathew
A, Shanta V, Varghese C and Boffetta P: Independent and combined
effects of tobacco smoking, chewing and alcohol drinking on the
risk of oral, pharyngeal and esophageal cancers in Indian men. Int
J Cancer. 105:681–686. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Stahl M, Mariette C, Haustermans K,
Cervantes A and Arnold D; ESMO Guidelines Working Group, :
Oesophageal cancer: ESMO Clinical Practice Guidelines for
diagnosis, treatment and follow-up. Ann Oncol. 24 Suppl
6:vi51–vi56. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Enzinger PC and Mayer RJ: Esophageal
cancer. N Engl J Med. 349:2241–2252. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Lee JM, Yang PW, Chiang TH, Huang YC and
Hsieh CY: The genetic polymorphisms of ATG5 and COL4A3 are
associated with the prognosis of patients with esophageal squamous
cell carcinoma. Cancer Res. 74:28592014. View Article : Google Scholar
|
|
7
|
Yang PW, Hsieh MS, Huang YC, Chiang TH and
Lee JM: AXL receptor tyrosine kinase is associated with the
prognosis of patients with esophageal squamous cell carcinoma.
Cancer Res. 74:44052014. View Article : Google Scholar
|
|
8
|
Mandard AM, Hainaut P and Hollstein M:
Genetic steps in the development of squamous cell carcinoma of the
esophagus. Mutation Research/Reviews in Mutation Research.
462:335–342. 2000. View Article : Google Scholar
|
|
9
|
Ma S, Bao JY, Kwan PS, Chan YP, Tong CM,
Fu L, Zhang N, Tong AH, Qin YR, Tsao SW, et al: Identification of
PTK6, via RNA sequencing analysis, as a suppressor of esophageal
squamous cell carcinoma. Gastroenterology. 143:675–686. e12. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Zhao Y, Schetter AJ, Yang GB, Nguyen G,
Mathé EA, Li P, Cai H, Yu L, Liu F, Hang D, et al: microRNA and
inflammatory gene expression as prognostic marker for overall
survival in esophageal squamous cell carcinoma. Int J Cancer.
132:2901–2909. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Nohata N, Hanazawa T, Kikkawa N, Mutallip
M, Sakurai D, Fujimura L, Kawakami K, Chiyomaru T, Yoshino H,
Enokida H, et al: Tumor suppressive microRNA-375 regulates oncogene
AEG-1/MTDH in head and neck squamous cell carcinoma (HNSCC). J Hum
Genet. 56:595–601. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Kano M, Seki N, Kikkawa N, Fujimura L,
Hoshino I, Akutsu Y, Chiyomaru T, Enokida H, Nakagawa M and
Matsubara H: miR-145, miR-133a and miR-133b: Tumor-suppressive
miRNAs target FSCN1 in esophageal squamous cell carcinoma. Int J
Cancer. 127:2804–2814. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Ni Y, Meng L, Wang L, Dong W, Shen H, Wang
G, Liu Q and Du J: MicroRNA-143 functions as a tumor suppressor in
human esophageal squamous cell carcinoma. Gene. 517:197–204. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Zhang J, Cheng C, Yuan X, He JT, Pan QH
and Sun FY: microRNA-155 acts as an oncogene by targeting the tumor
protein 53-induced nuclear protein 1 in esophageal squamous cell
carcinoma. Int J Clin Exp Pathol. 7:6022014.PubMed/NCBI
|
|
15
|
Ma WJ, Lv GD, Tuersun A, Liu Q, Liu H,
Zheng ST, Huang CG, Feng JG, Wang X, Lin RY, et al: Role of
microRNA-21 and effect on PTEN in Kazakh's esophageal squamous cell
carcinoma. Mol Biol Rep. 38:3253–3260. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Zhang T, Wang Q, Zhao D, Cui Y, Cao B, Guo
L and Lu SH: The oncogenetic role of microRNA-31 as a potential
biomarker in oesophageal squamous cell carcinoma. Clin Sci (Lond).
121:437–447. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Guo Y, Chen Z, Zhang L, Zhou F, Shi S,
Feng X, Li B, Meng X, Ma X, Luo M, et al: Distinctive microRNA
profiles relating to patient survival in esophageal squamous cell
carcinoma. Cancer Res. 68:26–33. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Lin RJ, Xiao DW, Liao LD, Chen T, Xie ZF,
Huang WZ, Wang WS, Jiang TF, Wu BL, Li EM and Xu LY: MiR-142-3p as
a potential prognostic biomarker for esophageal squamous cell
carcinoma. J Surg Oncol. 105:175–182. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Chen Z, Li J, Tian L, Zhou C, Gao Y, Zhou
F, Shi S, Feng X, Sun N, Yao R, et al: MiRNA expression profile
reveals a prognostic signature for esophageal squamous cell
carcinoma. Cancer Lett. 350:34–42. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Barrett T and Edgar R: Gene expression
omnibus: Microarray data storage, submission, retrieval, and
analysis. Methods Enzymol. 411:352–369. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Altman NS: An introduction to kernel and
nearest-neighbor nonparametric regression. The American
Statistician. 46:175–185. 1992. View Article : Google Scholar
|
|
22
|
Hastie T, Tibshirani R, Narasimhan B and
Chu G: Impute: Imputation for microarray data. R package version.
2001.
|
|
23
|
Bolstad B: PreprocessCore: A collection of
pre-processing functions. R package version 1.20.0. 2013.
|
|
24
|
Smyth GK: Limma: linear models for
microarray dataBioinformatics and computational biology solutions
using R and Bioconductor. Springer; pp. 397–420. 2005, View Article : Google Scholar
|
|
25
|
Benjamini Y and Hochberg Y: Controlling
the false discovery rate: A practical and powerful approach to
multiple testing. Journal of the Royal Statistical Society. Series
B (Methodological). 57:289–300. 1995.
|
|
26
|
Robin X, Turck N, Hainard A, Tiberti N,
Lisacek F, Sanchez JC and Müller M: pROC: An open-source package
for R and S+ to analyze and compare ROC curves. BMC Bioinformatics.
12:772011. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
KMsurv: Data sets from Klein and
Moeschberger, . 1997, Survival Analysis. R package version 0.1–5,
2012. https://cran.r-project.org/web/packages/KMsurv/KMsurv.pdfFebuary
19–2015
|
|
28
|
Therneau TM and Grambsch PM: Modeling
Survival Data: Extending the Cox model. New York, NY: Springer;
2000, View Article : Google Scholar
|
|
29
|
Xiao F, Zuo Z, Cai G, Kang S, Gao X and Li
T: miRecords: An integrated resource for microRNA-target
interactions. Nucleic Acids Res. 37:D105–D110. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Dweep H, Sticht C, Pandey P and Gretz N:
miRWalk-database: Prediction of possible miRNA binding sites by
‘walking’ the genes of three genomes. J Biomed Inform. 44:839–847.
2011. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Enright AJ, John B, Gaul U, Tuschl T,
Sander C and Marks DS: MicroRNA targets in Drosophila. Genome Biol.
5:R12003. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Wang X and El Naqa IM: Prediction of both
conserved and nonconserved microRNA targets in animals.
Bioinformatics. 24:325–332. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Krek A, Grün D, Poy MN, Wolf R, Rosenberg
L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M
and Rajewsky N: Combinatorial microRNA target predictions. Nat
Genet. 37:495–500. 2005. View
Article : Google Scholar : PubMed/NCBI
|
|
34
|
Kertesz M, Iovino N, Unnerstall U, Gaul U
and Segal E: The role of site accessibility in microRNA target
recognition. Nat Genet. 39:1278–1284. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Lewis BP, Shih IH, Jones-Rhoades MW,
Bartel DP and Burge CB: Prediction of mammalian microRNA targets.
Cell. 115:787–798. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Shannon P, Markiel A, Ozier O, Baliga NS,
Wang JT, Ramage D, Amin N, Schwikowski B and Ideker T: Cytoscape: A
software environment for integrated models of biomolecular
interaction networks. Genome Res. 13:2498–2504. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Schriml LM, Arze C, Nadendla S, Chang YW,
Mazaitis M, Felix V, Feng G and Kibbe WA: Disease Ontology: A
backbone for disease semantic integration. Nucleic Acids Res.
40:D940–D946. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Chen YA, Tripathi LP and Mizuguchi K:
TargetMine, an integrated data warehouse for candidate gene
prioritisation and target discovery. PLoS One. 6:e178442011.
View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Wu XL, Cheng B, Li PY, Huang HJ, Zhao Q,
Dan ZL, Tian DA and Zhang P: MicroRNA-143 suppresses gastric cancer
cell growth and induces apoptosis by targeting COX-2. World J
Gastroenterol. 19:7758–7765. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Wu BL, Xu LY, Du ZP, Liao LD, Zhang HF,
Huang Q, Fang GQ and Li EM: MiRNA profile in esophageal squamous
cell carcinoma: Downregulation of miR-143 and miR-145. World J
Gastroenterol. 17:79–88. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Liu R, Liao J, Yang M, Sheng J, Yang H,
Wang Y, Pan E, Guo W, Pu Y, Kim SJ and Yin L: The cluster of
miR-143 and miR-145 affects the risk for esophageal squamous cell
carcinoma through co-regulating fascin homolog 1. PLoS One.
7:e339872012. View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Segura MF, Hanniford D, Menendez S, Reavie
L, Zou X, Alvarez-Diaz S, Zakrzewski J, Blochin E, Rose A,
Bogunovic D, et al: Aberrant miR-182 expression promotes melanoma
metastasis by repressing FOXO3 and microphthalmia-associated
transcription factor. Proc Natl Acad Sci USA. 106:pp. 1814–1819.
2009; View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Xu X, Wu J, Li S, Hu Z, Xu X, Zhu Y, Liang
Z, Wang X, Lin Y, Mao Y, et al: Downregulation of microRNA-182-5p
contributes to renal cell carcinoma proliferation via activating
the AKT/FOXO3a signaling pathway. Mol Cancer. 13:1092014.
View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Jiang L, Mao P, Song L, Wu J, Huang J, Lin
C, Yuan J, Qu L, Cheng SY and Li J: miR-182 as a prognostic marker
for glioma progression and patient survival. Am J Pathol.
177:29–38. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Swingler TE, Wheeler G, Carmont V, Elliott
HR, Barter MJ, Abu-Elmagd M, Donell ST, Boot-Handford RP,
Hajihosseini MK, Münsterberg A, et al: The expression and function
of microRNAs in chondrogenesis and osteoarthritis. Arthritis Rheum.
64:1909–1919. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
46
|
Hiroki E, Akahira J, Suzuki F, Nagase S,
Ito K, Suzuki T, Sasano H and Yaegashi N: Changes in microRNA
expression levels correlate with clinicopathological features and
prognoses in endometrial serous adenocarcinomas. Cancer Sci.
101:241–249. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Gholamin M, Moaven O, Memar B, Farshchian
M, Naseh H, Malekzadeh R, Sotoudeh M, Rajabi-Mashhadi MT, Forghani
MN, Farrokhi F and Abbaszadegan MR: Overexpression and interactions
of interleukin-10, transforming growth factor beta, and vascular
endothelial growth factor in esophageal squamous cell carcinoma.
World J Surg. 33:1439–1445. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
48
|
Sheyhidin I, Nabi G, Hasim A, Zhang RP,
Ainiwaer J, Ma H and Wang H: Overexpression of TLR3, TLR4, TLR7 and
TLR9 in esophageal squamous cell carcinoma. World J Gastroenterol.
17:3745–3751. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Baxter LT and Jain RK: Transport of fluid
and macromolecules in tumors: III. Role of binding and metabolism.
Microvasc Res. 41:5–23. 1991. View Article : Google Scholar : PubMed/NCBI
|
|
50
|
Hsu PP and Sabatini DM: Cancer cell
metabolism: Warburg and beyond. Cell. 134:703–707. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Masoudi-Nejad A and Asgari Y: Metabolic
cancer biology: Structural-based analysis of cancer as a metabolic
disease, new sights and opportunities for disease treatment.
Journal. 30:21–29. 2015.
|
|
52
|
Ward PS and Thompson CB: Metabolic
reprogramming: A cancer hallmark even warburg did not anticipate.
Cancer cell. 21:297–308. 2012. View Article : Google Scholar : PubMed/NCBI
|
