|
1
|
Siegel RL, Miller KD and Jemal A: Cancer
Statistics, 2017. CA Cancer J Clin. 67:7–30. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Scully OJ, Bay BH, Yip G and Yu Y: Breast
cancer metastasis. Cancer Genomics Proteomics. 9:311–320.
2012.PubMed/NCBI
|
|
3
|
Chiang AC and Massagué J: Molecular basis
of metastasis. N Engl J Med. 359:2814–2823. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Vanharanta S and Massagué J: Origins of
metastatic traits. Cancer Cell. 24:410–421. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Peinado H, Zhang H, Matei IR, Costa-Silva
B, Hoshino A, Rodrigues G, Psaila B, Kaplan RN, Bromberg JF, Kang
Y, et al: Pre-metastatic niches: Organ-specific homes for
metastases. Nat Rev Cancer. 17:302–317. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Lukanidin E and Sleeman JP: Building the
niche: The role of the S100 proteins in metastatic growth. Semin
Cancer Biol. 22:216–225. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Salama I, Malone PS, Mihaimeed F and Jones
JL: A review of the S100 proteins in cancer. Eur J Surg Oncol.
34:357–364. 2008. View Article : Google Scholar
|
|
8
|
Mei Y, Yang JP and Qian CN: For robust big
data analyses: A collection of 150 important pro-metastatic genes.
Chin J Cancer. 36:162017. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Pang X, Min J, Liu L, Liu Y, Ma N and
Zhang H: S100B protein as a possible participant in the brain
metastasis of NSCLC. Med Oncol. 29:2626–2632. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Choi H, Puvenna V, Brennan C, Mahmoud S,
Wang XF, Phillips M, Janigro D and Mazzone P: S100B and S100B
auto-antibody as biomarkers for early detection of brain metastases
in lung cancer. Transl Lung Cancer Res. 5:413–419. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Bonfrer JM, Korse CM, Nieweg OE and Rankin
EM: The luminescence immunoassay S-100: a sensitive test to measure
circulating S-100B: its prognostic value in malignant melanoma. Br
J Cancer. 77:2210–2214. 1998. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Heizmann CW: S100B protein in clinical
diagnostics: Assay specificity. Clin Chem. 50:249–251. 2004.
View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Schlagenhauff B, Schittek B, Ellwanger U,
Stroebel W, Blum A, Schwarz M, Rassner G and Garbe C: Significance
of serum protein S100 levels in screening for melanoma metastasis:
Does protein S100 enable early detection of melanoma recurrence?
Melanoma Res. 10:451–459. 2000. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Lin J, Yang Q, Wilder PT, Carrier F and
Weber DJ: The calcium-binding protein S100B down-regulates p53 and
apoptosis in malignant melanoma. J Biol Chem. 285:27487–27498.
2010. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Yoshimura C, Miyafusa T and Tsumoto K:
Identification of small-molecule inhibitors of the human S100B-p53
interaction and evaluation of their activity in human melanoma
cells. Bioorg Med Chem. 21:1109–1115. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Bechmann T, Madsen JS, Brandslund I, Lund
ED, Ormstrup T, Jakobsen EH, Jylling AM, Steffensen KD and Jakobsen
A: Predicting brain metastases of breast cancer based on serum
S100B and serum HER2. Oncol Lett. 6:1265–1270. 2013.PubMed/NCBI
|
|
17
|
Darlix A, Lamy PJ, Lopez-Crapez E,
Braccini AL, Firmin N, Romieu G, Thézenas S and Jacot W: Serum NSE,
MMP-9 and HER2 extracellular domain are associated with brain
metastases in metastatic breast cancer patients: Predictive
biomarkers for brain metastases? Int J Cancer. 139:2299–2311. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Charmsaz S, Hughes É, Bane FT, Tibbitts P,
McIlroy M, Byrne C, Cocchiglia S, McBryan J, Hennessy BT, Dwyer RM,
et al: S100β as a serum marker in endocrine resistant breast
cancer. BMC Med. 15:792017. View Article : Google Scholar
|
|
19
|
Livak KJ and Schmittgen TD: Analysis of
relative gene expression data using real-time quantitative PCR and
the 2(−Delta Delta C(T)) Method. Methods. 25:402–408. 2001.
View Article : Google Scholar
|
|
20
|
Ma XJ, Dahiya S, Richardson E, Erlander M
and Sgroi DC: Gene expression profiling of the tumor
microenvironment during breast cancer progression. Breast Cancer
Res. 11:R72009. View
Article : Google Scholar : PubMed/NCBI
|
|
21
|
Ciriello G, Gatza ML, Beck AH, Wilkerson
MD, Rhie SK, Pastore A, Zhang H, McLellan M, Yau C, Kandoth C, et
al: TCGA Research Network: Comprehensive molecular portraits of
invasive lobular breast cancer. Cell. 163:506–519. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Ringnér M, Fredlund E, Häkkinen J, Borg Å
and Staaf J: GOBO: Gene expression-based outcome for breast cancer
online. PLoS One. 6:e179112011. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Györffy B, Lanczky A, Eklund AC, Denkert
C, Budczies J, Li Q and Szallasi Z: An online survival analysis
tool to rapidly assess the effect of 22,277 genes on breast cancer
prognosis using microarray data of 1,809 patients. Breast Cancer
Res Treat. 123:725–731. 2010. View Article : Google Scholar
|
|
24
|
Aguirre-Gamboa R, Gomez-Rueda H,
Martínez-Ledesma E, Martínez-Torteya A, Chacolla-Huaringa R,
Rodriguez-Barrientos A, Tamez-Peña JG and Treviño V: SurvExpress:
An online biomarker validation tool and database for cancer gene
expression data using survival analysis. PLoS One. 8:e742502013.
View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Chanrion M, Negre V, Fontaine H, Salvetat
N, Bibeau F, Mac Grogan G, Mauriac L, Katsaros D, Molina F,
Theillet C, et al: A gene expression signature that can predict the
recurrence of tamoxifen-treated primary breast cancer. Clin Cancer
Res. 14:1744–1752. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Sarrió D, Rodriguez-Pinilla SM, Hardisson
D, Cano A, Moreno-Bueno G and Palacios J: Epithelial-mesenchymal
transition in breast cancer relates to the basal-like phenotype.
Cancer Res. 68:989–997. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Chavez KJ, Garimella SV and Lipkowitz S:
Triple negative breast cancer cell lines: One tool in the search
for better treatment of triple negative breast cancer. Breast Dis.
32:35–48. 2010. View Article : Google Scholar
|
|
28
|
Lamouille S, xu J and Derynck R: Molecular
mechanisms of epithelial-mesenchymal transition. Nat Rev Mol Cell
Biol. 15:178–196. 2014. View
Article : Google Scholar : PubMed/NCBI
|
|
29
|
Dominguez C, David JM and Palena C:
Epithelial-mesenchymal transition and inflammation at the site of
the primary tumor. Semin Cancer Biol. 47:177–184. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Demirkan B: The roles of
epithelial-to-mesenchymal transition (EMT) and
mesenchymal-to-epithelial transition (MET) in breast cancer bone
metastasis: Potential targets for prevention and treatment. J Clin
Med. 2:264–282. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Giri D, Ozen M and Ittmann M:
Interleukin-6 is an autocrine growth factor in human prostate
cancer. Am J Pathol. 159:2159–2165. 2001. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Horiguchi K, Fujiwara K, Higuchi M,
Yoshida S, Tsukada T, Ueharu H, Chen M, Hasegawa R, Takigami S,
Ohsako S, et al: Expression of chemokine CxCL10 in
dendritic-cell-like S100β-positive cells in rat anterior pituitary
gland. Cell Tissue Res. 357:757–765. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Villarreal A, Seoane R, González Torres A,
Rosciszewski G, Angelo MF, Rossi A, Barker PA and Ramos AJ: S100B
protein activates a RAGE-dependent autocrine loop in astrocytes:
Implications for its role in the propagation of reactive gliosis. J
Neurochem. 131:190–205. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Nieman KM, Romero IL, Van Houten B and
Lengyel E: Adipose tissue and adipocytes support tumorigenesis and
metastasis. Biochim Biophys Acta. 1831:1533–1541. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Gonçalves CA, Leite MC and Guerra MC:
Adipocytes as an important source of serum S100B and possible roles
of this protein in adipose tissue. Cardiovasc Psychiatry Neurol.
2010:7904312010. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Lim SY, Yuzhalin AE, Gordon-Weeks AN and
Muschel RJ: Tumor-infiltrating monocytes/macrophages promote tumor
invasion and migration by upregulating S100A8 and S100A9 expression
in cancer cells. Oncogene. 35:5735–5745. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Luo X, Sharff KA, Chen J, He TC and Luu
HH: S100A6 expression and function in human osteosarcoma. Clin
Orthop Relat Res. 466:2060–2070. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Bianchi R, Giambanco I and Donato R:
S100B/RAGE-dependent activation of microglia via NF-kappaB and AP-1
Co-regulation of COx-2 expression by S100B, IL-1beta and TNF-alpha.
Neurobiol Aging. 31:665–677. 2010. View Article : Google Scholar
|
|
39
|
Yang T, Cheng J, Yang Y, Qi W, Zhao Y,
Long H, xie R and Zhu B: S100B mediates stemness of ovarian cancer
stem-like cells through inhibiting p53. Stem Cells. 35:325–336.
2017. View Article : Google Scholar
|
