|
1
|
Al-Hajj M, Wicha MS, Benito-Hernandez A,
Morrison SJ and Clarke MF: Prospective identification of
tumorigenic breast cancer cells. Proc Natl Acad Sci USA.
100:3983–3988. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Yang XR, Sherman ME, Rimm DL, Lissowska J,
Brinton LA, Peplonska B, Hewitt SM, Anderson WF,
Szeszenia-Dabrowska N, Bardin-Mikolajczak A, et al: Differences in
risk factors for breast cancer molecular subtypes in a
population-based study. Cancer Epidemiol Biomarkers Prev.
16:439–443. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Cho EY, Chang MH, Choi YL, Lee JE, Nam SJ,
Yang JH, Park YH, Ahn JS and Im YH: Potential candidate biomarkers
for heterogeneity in triple-negative breast cancer (TNBC). Cancer
Chemother Pharmacol. 68:753–761. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
He J, Yang J, Chen W, Wu H, Yuan Z, Wang
K, Li G, Sun J and Yu L: Molecular features of triple negative
breast cancer: Microarray evidence and further integrated analysis.
PLoS One. 10:e01298422015. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Anders CK and Carey LA: Biology,
metastatic patterns, and treatment of patients with triple-negative
breast cancer. Clin Breast Cancer. 9 Suppl 2:S73–S81. 2009.
View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Petricoin EF III, Hackett JL, Lesko LJ,
Puri RK, Gutman SI, Chumakov K, Woodcock J, Feigal DW Jr, Zoon KC
and Sistare FD: Medical applications of microarray technologies: A
regulatory science perspective. Nat Genet. 32:S474–S479. 2002.
View Article : Google Scholar
|
|
7
|
Yang L, Wu X, Wang Y, Zhang K, Wu J, Yuan
YC, Deng X, Chen L, Kim CC, Lau S, et al: FZD7 has a critical role
in cell proliferation in triple negative breast cancer. Oncogene.
30:4437–4446. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Mathe A, Wong-Brown M, Morten B, Forbes
JF, Braye SG, Avery-Kiejda KA and Scott RJ: Novel genes associated
with lymph node metastasis in triple negative breast cancer. Sci
Rep. 5:158322015. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Wang Y, Zhang T, Kwiatkowski N, Abraham
BJ, Lee TI, Xie S, Yuzugullu H, Von T, Li H, Lin Z, et al:
CDK7-dependent transcriptional addiction in triple-negative breast
cancer. Cell. 163:174–186. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Abramovitz M, Barwick BG, Willis S, Young
B, Catzavelos C, Li Z, Kodani M, Tang W, Bouzyk M, Moreno CS, et
al: Molecular characterisation of formalin-fixed paraffin-embedded
(FFPE) breast tumour specimens using a custom 512-gene breast
cancer bead array-based platform. Br J Cancer. 105:1574–1581. 2011.
View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Al-Ejeh F, Simpson PT, Sanus JM, Klein K,
Kalimutho M, Shi W, Miranda M, Kutasovic J, Raghavendra A, Madore
J, et al: Meta-analysis of the global gene expression profile of
triple-negative breast cancer identifies genes for the
prognostication and treatment of aggressive breast cancer.
Oncogenesis. 3:e1002014. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Tauber E, Miller-Fleming L, Mason RP, Kwan
W, Clapp J, Butler NJ, Outeiro TF, Muchowski PJ and Giorgini F:
Functional gene expression profiling in yeast implicates
translational dysfunction in mutant huntingtin toxicity. J Biol
Chem. 286:410–419. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Warnes GR, Bolker B, Bonebakker L,
Gentleman R, Huber W, Liaw A, Lumley T, Maechler M, Magnusson A,
Moeller S, et al: Package ‘gplots’: Various R programming tools for
plotting data. R package version 2. 2009.https://scholar.google.com/citations?view_op=view_citation&hl=en&user=o7GsfJwAAAAJ&citation_for_view=o7GsfJwAAAAJ:u-x6o8ySG0sC
|
|
14
|
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 : PubMed/NCBI
|
|
15
|
Xu Z, Zhou Y, Cao Y, Dinh TLA, Wan J and
Zhao M: Identification of candidate biomarkers and analysis of
prognostic values in ovarian cancer by integrated bioinformatics
analysis. Med Oncol. 33:1302016. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Arocho A, Chen B, Ladanyi M and Pan Q:
Validation of the 2-DeltaDeltaCt calculation as an alternate method
of data analysis for quantitative PCR of BCR-ABL P210 transcripts.
Diagn Mol Pathol. 15:56–61. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Paranjpe SS, Jacobi UG, van Heeringen SJ
and Veenstra GJ: A genome-wide survey of maternal and embryonic
transcripts during Xenopus tropicalis development. BMC Genomics.
14:7622013. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Karagoz K, Sinha R and Arga KY: Triple
negative breast cancer: A multi-omics network discovery strategy
for candidate targets and driving pathways. OMICS. 19:115–130.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Elsamany S and Abdullah S: Triple-negative
breast cancer: Future prospects in diagnosis and management. Med
Oncol. 31:8342014. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Legrier M-E, Bièche I, Gaston J, Beurdeley
A, Yvonnet V, Déas O, Thuleau A, Château-Joubert S, Servely JL,
Vacher S, et al: Activation of IFN/STAT1 signalling predicts
response to chemotherapy in oestrogen receptor-negative breast
cancer. Br J Cancer. 114:177–187. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Nagelkerke A, Bussink J, Mujcic H, Wouters
BG, Lehmann S, Sweep FC and Span PN: Hypoxia stimulates migration
of breast cancer cells via the PERK/ATF4/LAMP3-arm of the unfolded
protein response. Breast Cancer Res. 15:R22013. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Stayrook KR, Mack JK, Cerabona D, Edwards
DF, Bui HH, Niewolna M, Fournier PG, Mohammad KS, Waning DL and
Guise TA: TGFβ-mediated induction of SphK1 as a potential
determinant in human MDA-MB-231 breast cancer cell bone metastasis.
Bonekey Rep. 4:7192015. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Frangou C, Li Y-W, Shen H, Yang N, Wilson
KE, Blijlevens M, Guo J, Nowak NJ and Zhang J: Molecular profiling
and computational network analysis of TAZ-mediated mammary
tumorigenesis identifies actionable therapeutic targets.
Oncotarget. 5:12166–12176. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Jiang J, Liu W, Guo X, Zhang R, Zhi Q, Ji
J, Zhang J, Chen X, Li J, Zhang J, et al: IRX1 influences
peritoneal spreading and metastasis via inhibiting BDKRB2-dependent
neovascularization on gastric cancer. Oncogene. 30:4498–4508. 2011.
View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Winslow S, Leandersson K, Edsjö A and
Larsson C: Prognostic stromal gene signatures in breast cancer.
Breast Cancer Res. 17:232015. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Watkins J, Weekes D, Shah V, Gazinska P,
Joshi S, Sidhu B, Gillett C, Pinder S, Vanoli F, Jasin M, et al:
Genomic complexity profiling reveals that HORMAD1 overexpression
contributes to homologous recombination deficiency in
triple-negative breast cancers. Cancer Discov. 5:488–505. 2015.
View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Komatsu M, Yoshimaru T, Matsuo T, Kiyotani
K, Miyoshi Y, Tanahashi T, Rokutan K, Yamaguchi R, Saito A, Imoto
S, et al: Molecular features of triple-negative breast cancer cells
by genome-wide gene expression profiling analysis. Int J Oncol.
42:478–506. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Chakrabarti R, Wei Y, Romano RA, DeCoste
C, Kang Y and Sinha S: Elf5 regulates mammary gland stem/progenitor
cell fate by influencing notch signaling. Stem Cells. 30:1496–1508.
2012. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Tordai A, Wang B, Andre F, Liedtke C,
Symmans W, Esteva F and Pusztai L: Screening for expression of
novel marker proteins for triple negative breast cancer in breast
cancer cell lines. Cancer Res. Suppl 9:67:19782007.http://cancerres.aacrjournals.org/content/67/9_Supplement/1978
|
|
30
|
Daniele V, Pasquale S, Frank J, Trerotola
M, Giudetti A, Capobianco L, Tinelli A, Bellomo C, Fournier I,
Gaballo A, et al: Translating epithelial mesenchymal transition
markers into the clinic: Novel insights from proteomics. EuPA Open
Proteom. 10:31–41. 2016.http://www.sciencedirect.com/science/article/pii/S2212968516300034
View Article : Google Scholar
|
|
31
|
He J, Peng R, Yuan Z, Wang S, Peng J, Lin
G, Jiang X and Qin T: Prognostic value of androgen receptor
expression in operable triple-negative breast cancer: A
retrospective analysis based on a tissue microarray. Med Oncol.
29:406–410. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Anders C, Deal AM, Abramson V, Liu MC,
Storniolo AM, Carpenter JT, Puhalla S, Nanda R, Melhem-Bertrandt A,
Lin NU, et al: TBCRC 018: Phase II study of iniparib in combination
with irinotecan to treat progressive triple negative breast cancer
brain metastases. Breast Cancer Res Treat. 146:557–566. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Jang P, Holleran T, Burns M, Gebizlioglu K
and Governale A: Identifying gene signatures associated with cancer
stem cells and drug resistance from triple negative breast cancer
cells after gene targeting treatment. Austin J Biomed Eng.
1:10182014.
|
|
34
|
Garczyk S, von Stillfried S, Antonopoulos
W, Hartmann A, Schrauder MG, Fasching PA, Anzeneder T, Tannapfel A,
Ergönenc Y, Knüchel R, et al: AGR3 in breast cancer: Prognostic
impact and suitable serum-based biomarker for early cancer
detection. PLoS One. 10:e01221062015. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Chen C, Zhou Z, Ross JS, Zhou W and Dong
JT: The amplified WWP1 gene is a potential molecular target in
breast cancer. Int J Cancer. 121:80–87. 2007. View Article : Google Scholar : PubMed/NCBI
|
