|
1.
|
Ferlay J, Shin HR, Bray F, Forman D,
Mathers C and Parkin DM: Estimates of worldwide burden of cancer in
2008: GLOBOCAN 2008. Int J Cancer. 127:2893–2917. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
2.
|
Lin Y, Totsuka Y, He Y, et al:
Epidemiology of esophageal cancer in Japan and China. J Epidemiol.
23:233–242. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
3.
|
Toh Y, Oki E, Ohgaki K, et al: Alcohol
drinking, cigarette smoking, and the development of squamous cell
carcinoma of the esophagus: molecular mechanisms of carcinogenesis.
Int J Clin Oncol. 15:135–144. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
4.
|
Motoyama S, Jin M, Matsuhashi T, et al:
Outcomes of patients receiving additional esophagectomy after
endoscopic resection for clinically mucosal, but pathologically
submucosal, squamous cell carcinoma of the esophagus. Surg Today.
43:638–642. 2013. View Article : Google Scholar
|
|
5.
|
Urabe Y, Hiyama T, Tanaka S, Yoshihara M,
Arihiro K and Chayama K: Advantages of endoscopic submucosal
dissection versus endoscopic oblique aspiration mucosectomy for
superficial esophageal tumors. J Gastroenterol Hepatol. 26:275–280.
2011. View Article : Google Scholar
|
|
6.
|
Isomoto H, Yamaguchi N, Nakayama T, et al:
Management of esophageal stricture after complete circular
endoscopic submucosal dissection for superficial esophageal
squamous cell carcinoma. BMC Gastroenterol. 11:462011. View Article : Google Scholar
|
|
7.
|
Umar SB and Fleischer DE: Esophageal
cancer: epidemiology, pathogenesis and prevention. Nat Clin Pract
Gastroenterol Hepatol. 5:517–526. 2008. View Article : Google Scholar
|
|
8.
|
Wong GS: Periostin and its role in
promoting invasion in the tumor microenvironment of esophageal
cancer. ProQuest. Paper AAI3551813.
|
|
9.
|
Bhatnagar J, Heroman W, Murphy M and
Austin GE: Immunohistochemical detection of carcinoembryonic
antigen in esophageal carcinomas: a comparison with other
gastrointestinal neoplasms. Anticancer Res. 22:1849–1857. 2002.
|
|
10.
|
Cheung L, Lai K, Lam A, et al: Gene
expression profiling identified high-mobility group AT-hook 2
(HMGA2) as being frequently upregulated in esophageal squamous cell
carcinoma. Br J Med Med Res. 3:407–419. 2013. View Article : Google Scholar
|
|
11.
|
Spies M, Dasu MR, Svrakic N, et al: Gene
expression analysis in burn wounds of rats. Am J Physiol Regul
Integr Comp Physiol. 283:R918–R930. 2002.PubMed/NCBI
|
|
12.
|
Hu N, Clifford R, Yang H, et al: Genome
wide analysis of DNA copy number neutral loss of heterozygosity
(CNNLOH) and its relation to gene expression in esophageal squamous
cell carcinoma. BMC Genomics. 11:5762010. View Article : Google Scholar : PubMed/NCBI
|
|
13.
|
Marques FZ, Campain AE, Tomaszewski M, et
al: Gene expression profiling reveals renin mRNA overexpression in
human hypertensive kidneys and a role for microRNAs. Hypertension.
58:1093–1098. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
14.
|
Fujita A, Sato J, Rodrigues L, Ferreira C
and Sogayar M: Evaluating different methods of microarray data
normalization. BMC Bioinformatics. 7:4692006. View Article : Google Scholar : PubMed/NCBI
|
|
15.
|
Smyth GK: Limma: linear models for
microarray data. Bioinformatics and Computational Biology Solutions
Using R and Bioconductor. Gentleman R, Carey V, Dudoit S, Irizarry
R and Huber W: Springer; New York: pp. 397–420. 2005, View Article : Google Scholar
|
|
16.
|
Benjamini Y and Hochberg Y: Controlling
the false discovery rate: a practical and powerful approach to
multiple testing. J R Stat Soc Ser B Stat Methodol. 289–300.
1995.
|
|
17.
|
Szklarczyk D, Franceschini A, Kuhn M, et
al: The STRING database in 2011: functional interaction networks of
proteins, globally integrated and scored. Nucleic Acids Res.
39:D561–D568. 2011. View Article : Google Scholar
|
|
18.
|
Albert R: Scale-free networks in cell
biology. J Cell Sci. 118:4947–4957. 2005. View Article : Google Scholar : PubMed/NCBI
|
|
19.
|
Bruckner S, Hüffner F, Karp RM, Shamir R
and Sharan R: Topology-free querying of protein interaction
networks. J Comput Biol. 17:237–252. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
20.
|
Wu X-R, Zhu Y and Li Y: Analyzing protein
interaction networks via random graph model. Int J Inform Technol.
11:125–132. 2005.
|
|
21.
|
Miller GA, Shi YY, Qian H and Bomsztyk K:
Clustering coefficients of protein-protein interaction networks.
Phys Rev E. 75:0519102007. View Article : Google Scholar : PubMed/NCBI
|
|
22.
|
Xu K, Bezakova I, Bunimovich L and Yi SV:
Path lengths in protein-protein interaction networks and biological
complexity. Proteomics. 11:1857–1867. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
23.
|
Willis RC and Hogue CW: Searching,
viewing, and visualizing data in the Biomolecular Interaction
Network Database (BIND). Curr Protoc Bioinformatics. 8.9. 1–8.9.
30. 2006.PubMed/NCBI
|
|
24.
|
Breitkreutz B-J, Stark C and Tyers M: The
GRID: the general repository for interaction datasets. Genome Biol.
4:R232003. View Article : Google Scholar : PubMed/NCBI
|
|
25.
|
Breitkreutz B-J, Stark C and Tyers M:
Osprey: a network visualization system. Genome Biol. 4:R222003.
View Article : Google Scholar
|
|
26.
|
Nam D and Kim SY: Gene-set approach for
expression pattern analysis. Brief Bioinform. 9:189–197. 2008.
View Article : Google Scholar : PubMed/NCBI
|
|
27.
|
Allison DB, Cui X, Page GP and Sabripour
M: Microarray data analysis: from disarray to consolidation and
consensus. Nat Rev Genet. 7:55–65. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
28.
|
Huang da W, Sherman BT and Lempicki RA:
Systematic and integrative analysis of large gene lists using DAVID
bioinformatics resources. Nat Protoc. 4:44–57. 2008.PubMed/NCBI
|
|
29.
|
Huang da W, Sherman BT and Lempicki RA:
Bioinformatics enrichment tools: paths toward the comprehensive
functional analysis of large gene lists. Nucleic Acids Res.
37:1–13. 2009.PubMed/NCBI
|
|
30.
|
Scarf AM, Ittner LM and Kassiou M: The
translocator protein (18 kDa): central nervous system disease and
drug design. J Med Chem. 52:581–592. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
31.
|
Papadopoulos V, Baraldi M, Guilarte TR, et
al: Translocator protein (18 kDa): new nomenclature for the
peripheral-type benzodiazepine receptor based on its structure and
molecular function. Trends Pharmacol Sci. 27:402–409. 2006.
View Article : Google Scholar : PubMed/NCBI
|
|
32.
|
Veenman L, Alten J, Linnemannstöns K, et
al: Potential involvement of F0F1-ATP (synth) ase and reactive
oxygen species in apoptosis induction by the antineoplastic agent
erucylphosphohomocholine in glioblastoma cell lines. Apoptosis.
15:753–768. 2010. View Article : Google Scholar
|
|
33.
|
Veenman L and Gavish M: The role of 18 kDa
mitochondrial translocator protein (TSPO) in programmed cell death,
and effects of steroids on TSPO expression. Curr Mol Med.
12:398–412. 2012.PubMed/NCBI
|
|
34.
|
Veenman L, Shandalov Y and Gavish M: VDAC
activation by the 18 kDa translocator protein (TSPO), implications
for apoptosis. J Bioenerg Biomembr. 40:199–205. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
35.
|
Zeno S, Zaaroor M, Leschiner S, Veenman L
and Gavish M: CoCl2 induces apoptosis via the 18 kDa translocator
protein in U118MG human glioblastoma cells. Biochemistry.
48:4652–4661. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
36.
|
Veenman L, Weizman A, Weisinger G and
Gavish M: Expression and functions of the 18 kDa mitochondrial
translocator protein (TSPO) in health and disease. Target Drug
Deliv Cancer Ther. 2010.
|
|
37.
|
Veenman L, Papadopoulos V and Gavish M:
Channel-like functions of the 18-kDa translocator protein (TSPO):
regulation of apoptosis and steroidogenesis as part of the
host-defense response. Curr Pharm Des. 13:2385–2405. 2007.
View Article : Google Scholar : PubMed/NCBI
|
|
38.
|
Medzhitov R, Preston-Hurlburt P and
Janeway CA: A human homologue of the Drosophila toll protein
signals activation of adaptive immunity. Nature. 388:394–397. 1997.
View Article : Google Scholar
|
|
39.
|
Takeda K, Kaisho T and Akira S: Toll-like
receptors. Annu Rev Immunol. 21:335–376. 2003. View Article : Google Scholar
|
|
40.
|
Hennessy EJ, Parker AE and O’Neill LA:
Targeting toll-like receptors: emerging therapeutics? Nat Rev Drug
Discov. 9:293–307. 2010. View
Article : Google Scholar : PubMed/NCBI
|
|
41.
|
Lim DM and Wang ML: Toll-like receptor 3
signaling enables human esophageal epithelial cells to sense
endogenous danger signals released by necrotic cells. Am J Physiol
Gastrointest Liver Physiol. 301:G91–G99. 2011. View Article : Google Scholar
|
|
42.
|
Ho N, Punturieri A, Wilkin D, et al:
Mutations of CTSK result in pycnodysostosis via a reduction in
cathepsin K protein. J Bone Miner Res. 14:1649–1653. 1999.
View Article : Google Scholar : PubMed/NCBI
|
|
43.
|
Asagiri M, Hirai T, Kunigami T, et al:
Cathepsin K-dependent toll-like receptor 9 signaling revealed in
experimental arthritis. Science. 319:624–627. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
44.
|
Hirai T, Kanda T, Sato K, et al: Cathepsin
K is involved in development of psoriasis-like skin lesions through
TLR-dependent Th17 activation. J Immunol. 190:4805–4811. 2013.
View Article : Google Scholar : PubMed/NCBI
|
|
45.
|
Todorović-Raković N and Milovanović J:
Interleukin-8 in breast cancer progression. J Interferon Cytokine
Res. 33:563–570. 2013.PubMed/NCBI
|
|
46.
|
Lim DM, Narasimhan S, Michaylira CZ and
Wang ML: TLR3-mediated NF-κB signaling in human esophageal
epithelial cells. Am J Physiol Gastrointest Liver Physiol.
297:G1172–G1180. 2009.
|
|
47.
|
Sun Y, Ishibashi M, Seimon T, et al: Free
cholesterol accumulation in macrophage membranes activates
Toll-like receptors and p38 mitogen-activated protein kinase and
induces cathepsin K. Circ Res. 104:455–465. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
48.
|
Xie L, Moroi Y, Hayashida S, et al:
Cathepsin K-upregulation in fibroblasts promotes matrigel invasive
ability of squamous cell carcinoma cells via tumor-derived IL-1α. J
Dermatol Sci. 61:45–50. 2011.PubMed/NCBI
|
