|
1
|
Sung H, Ferlay J, Siegel RL, Laversanne M,
Soerjomataram I, Jemal A and Bray F: Global cancer statistics 2020:
GLOBOCAN estimates of incidence and mortality worldwide for 36
cancers in 185 countries. CA Cancer J Clin. 71:209–249. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Pruitt SL, Zhu H, Heitjan DF, Rahimi A,
Maddineni B, Tavakkoli A, Halm EA, Gerber DE, Xiong D and Murphy
CC: Survival of women diagnosed with breast cancer and who have
survived a previous cancer. Breast Cancer Res Treat. 187:853–865.
2021. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Hendrick RE, Helvie MA and Monticciolo DL:
Breast cancer mortality rates have stopped declining in U.S. women
younger than 40 years. Radiology. 299:143–149. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Tchounwou PB, Dasari S, Noubissi FK, Ray P
and Kumar S: Advances in our understanding of the molecular
mechanisms of action of cisplatin in cancer therapy. J Exp
Pharmacol. 13:303–328. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Liu L and Bian K: Advance in studies on
molecular mechanisms of cisplatin resistance and intervention with
traditional Chinese medicines. Zhongguo Zhong Yao Za Zhi.
39:3216–3220. 2014.(In Chinese). PubMed/NCBI
|
|
6
|
Wang S, Li MY, Liu Y, Vlantis AC, Chan JY,
Xue L, Hu BG, Yang S, Chen MX, Zhou S, et al: The role of microRNA
in cisplatin resistance or sensitivity. Expert Opin Ther Targets.
24:885–897. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Safi A, Bastami M, Delghir S, Ilkhani K,
Seif F and Alivand MR: miRNAs modulate the dichotomy of cisplatin
resistance or sensitivity in breast cancer: An update of
therapeutic implications. Anticancer Agents Med Chem. 21:1069–1081.
2021. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Hatzidaki E, Daikopoulou V, Apostolou P,
Ntanovasilis DA and Papasotiriou I: Increased breast cancer cell
sensitivity to cisplatin using a novel small molecule inhibitor. J
Cancer Res Ther. 16:1393–1401. 2020.PubMed/NCBI
|
|
9
|
Sun Y, Wang X, Wen H, Zhu B and Yu L:
Expression and clinical significance of the NCAPH, AGGF1, and FOXC2
proteins in serous ovarian cancer. Cancer Manag Res. 13:7253–7262.
2021. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Kim JH, Youn Y, Kim KT, Jang G and Hwang
JH: Non-SMC condensin I complex subunit H mediates mature
chromosome condensation and DNA damage in pancreatic cancer cells.
Sci Rep. 9:178892019. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Qiu X, Gao Z, Shao J and Li H: NCAPH is
upregulated in endometrial cancer and associated with poor
clinicopathologic characteristics. Ann Hum Genet. 84:437–446. 2020.
View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Kim B, Kim SW, Lim JY and Park SJ: NCAPH
is required for proliferation, migration and invasion of
non-small-cell lung cancer cells. Anticancer Res. 40:3239–3246.
2020. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Lu H, Shi C, Wang S, Wan X, Luo Y, Tian L
and Li L: Identification of NCAPH as a biomarker for prognosis of
breast cancer. Mol Biol Rep. 47:7831–7842. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Szklarczyk D, Gable AL, Nastou KC, Lyon D,
Kirsch R, Pyysalo S, Doncheva NT, Legeay M, Fang T, Bork P, et al:
The STRING database in 2021: Customizable protein-protein networks,
and functional characterization of user-uploaded gene/measurement
sets. Nucleic Acids Res. 49((D1)): D605–D612. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Greene CS, Krishnan A, Wong AK, Ricciotti
E, Zelaya RA, Himmelstein DS, Zhang R, Hartmann BM, Zaslavsky E,
Sealfon SC, et al: Understanding multicellular function and disease
with human tissue-specific networks. Nat Genet. 47:569–576. 2015.
View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Warde-Farley D, Donaldson SL, Comes O,
Zuberi K, Badrawi R, Chao P, Franz M, Grouios C, Kazi F, Lopes CT,
et al: The GeneMANIA prediction server: Biological network
integration for gene prioritization and predicting gene function.
Nucleic Acids Res 38(Web Server Issue). W214–W220. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Tang Z, Li C, Kang B, Gao G, Li C and
Zhang Z: GEPIA: A web server for cancer and normal gene expression
profiling and interactive analyses. Nucleic Acids Res. 45((W1)):
W98–W102. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
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 : PubMed/NCBI
|
|
19
|
Loibl S, Poortmans P, Morrow M, Denkert C
and Curigliano G: Breast cancer. Lancet. 397:1750–1769. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Raigon-Ponferrada A, Recio MED,
Guerrero-Orriach JL, Malo-Manso A, Escalona-Belmonte JJ, Aliaga MR,
Fernández AR, García FJF, Conejo EA and Cruz-Mañas J: Breast cancer
and anesthesia. Curr Pharm Des. 25:2998–3004. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Waks AG and Winer EP: Breast cancer
treatment: A review. JAMA. 321:288–300. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Wöckel A, Albert US, Janni W, Scharl A,
Kreienberg R and Stüber T: The screening, diagnosis, treatment, and
follow-up of breast cancer. Dtsch Arztebl Int. 115:316–323.
2018.PubMed/NCBI
|
|
23
|
Harbeck N and Gnant M: Breast cancer.
Lancet. 389:1134–1150. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Abdel-Hafiz HA: Epigenetic mechanisms of
tamoxifen resistance in luminal breast cancer. Diseases. 5:162017.
View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Yu S, Kim T, Yoo KH and Kang K: The T47D
cell line is an ideal experimental model to elucidate the
progesterone-specific effects of a luminal A subtype of breast
cancer. Biochem Biophys Res Commun. 486:752–758. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Marima R, Hull R, Penny C and Dlamini Z:
Mitotic syndicates Aurora Kinase B (AURKB) and mitotic arrest
deficient 2 like 2 (MAD2L2) in cohorts of DNA damage response (DDR)
and tumorigenesis. Mutat Res Rev Mutat Res. 787:1083762021.
View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Xiao J and Zhang Y: AURKB as a promising
prognostic biomarker in hepatocellular carcinoma. Evol Bioinform
Online. 17:117693432110575892021. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Nie M, Wang Y, Yu Z, Li X, Deng Y, Wang Y,
Yang D, Li Q, Zeng X, Ju J, et al: AURKB promotes gastric cancer
progression via activation of CCND1 expression. Aging (Albany NY).
12:1304–1321. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Tada K, Susumu H, Sakuno T and Watanabe Y:
Condensin association with histone H2A shapes mitotic chromosomes.
Nature. 474:477–483. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Wang Z, Yu Z, Wang GH, Zhou YM, Deng JP,
Feng Y, Chen JQ and Tian L: AURKB promotes the metastasis of
gastric cancer, possibly by inducing EMT. Cancer Manag Res.
12:6947–6958. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Yu J, Zhou J, Xu F, Bai W and Zhang W:
High expression of Aurora-B is correlated with poor prognosis and
drug resistance in non-small cell lung cancer. Int J Biol Markers.
33:215–221. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Mossmann D, Park S and Hall MN: mTOR
signalling and cellular metabolism are mutual determinants in
cancer. Nat Rev Cancer. 18:744–757. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Alzahrani AS: PI3K/Akt/mTOR inhibitors in
cancer: At the bench and bedside. Semin Cancer Biol. 59:125–132.
2019. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Wang C, Chen J, Cao W, Sun L, Sun H and
Liu Y: Aurora-B and HDAC synergistically regulate survival and
proliferation of lymphoma cell via AKT, mTOR and Notch pathways.
Eur J Pharmacol. 779:1–7. 2016. View Article : Google Scholar : PubMed/NCBI
|
