|
1
|
Diaz-Gil D, Fintelmann FJ, Molaei S, Elmi
A, Hedgire SS and Harisinghani MG: Prediction of 5-year survival in
advanced-stage ovarian cancer patients based on computed tomography
peritoneal carcinomatosis index. Abdom Radiol. 41:2196–2202. 2016.
View Article : Google Scholar
|
|
2
|
Lowe KA, Chia VM, Taylor A, O'Malley C,
Kelsh M, Mohamed M, Mowat FS and Goff B: An international
assessment of ovarian cancer incidence and mortality. Gynecol
Oncol. 130:107–114. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Kehoe S, Hook J, Nankivell M, Jayson GC,
Kitchener H, Lopes T, Luesley D, Perren T, Bannoo S, Mascarenhas M,
et al: Primary chemotherapy versus primary surgery for newly
diagnosed advanced ovarian cancer (CHORUS): An open-label,
randomised, controlled, non-inferiority trial. Lancet. 386:249–257.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Schmid BC and Oehler MK: New perspectives
in ovarian cancer treatment. Maturitas. 77:128–136. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Gao Y, Foster R, Yang X, Feng Y, Shen JK,
Mankin HJ, Hornicek FJ, Amiji MM and Duan Z: Up-regulation of CD44
in the development of metastasis, recurrence and drug resistance of
ovarian cancer. Oncotarget. 6:9313–9326. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Chen WT, Gao X, Han XD, Zheng H, Guo L and
Lu RQ: HE4 as a serum biomarker for ROMA prediction and prognosis
of epithelial ovarian cancer. Asian Pac J Cancer Prev. 15:101–105.
2014. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Avril S, Dincer Y, Malinowsky K, Wolff C,
Gündisch S, Hapfelmeier A, Boxberg M, Bronger H, Becker KF and
Schmalfeldt B: Increased PDGFR-beta and VEGFR-2 protein levels are
associated with resistance to platinum-based chemotherapy and
adverse outcome of ovarian cancer patients. Oncotarget.
8:97851–97861. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Meng X, Muller V, Milde-Langosch K,
Trillsch F, Pantel K and Schwarzenbach H: Circulating cell-free
miR-373, miR-200a, miR-200b and miR-200c in patients with
epithelial ovarian cancer. Adv Exp Med Biol. 924:3–8. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Koutsaki M, Libra M, Spandidos DA and
Zaravinos A: The miR-200 family in ovarian cancer. Oncotarget.
8:66629–66640. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Ulitsky I: Evolution to the rescue: Using
comparative genomics to understand long non-coding RNAs. Nat Rev
Genet. 17:601–614. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Luo P, Liu XF, Wang YC, Li ND, Liao SJ, Yu
MX, Liang CZ and Tu JC: Prognostic value of abnormally expressed
lncRNAs in ovarian carcinoma: A systematic review and
meta-analysis. Oncotarget. 8:23927–23936. 2017.PubMed/NCBI
|
|
12
|
Wang P, Liu YH, Yao YL, Li Z, Li ZQ, Ma J
and Xue YX: Long non-coding RNA CASC2 suppresses malignancy in
human gliomas by miR-21. Cell Signal. 27:275–282. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Yang K, Hou Y, Li A, Li Z, Wang W, Xie H,
Rong Z, Lou G and Li K: Identification of a six-lncRNA signature
associated with recurrence of ovarian cancer. Sci Rep. 7:7522017.
View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Guo Q, Cheng Y, Liang T, He Y, Ren C, Sun
L and Zhang G: Comprehensive analysis of lncRNA-mRNA co-expression
patterns identifies immune-associated lncRNA biomarkers in ovarian
cancer malignant progression. Sci Rep. 5:176832015. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Zhou M, Wang X, Shi H, Cheng L, Wang Z,
Zhao H, Yang L and Sun J: Characterization of long non-coding
RNA-associated ceRNA network to reveal potential prognostic lncRNA
biomarkers in human ovarian cancer. Oncotarget. 7:12598–12611.
2016.PubMed/NCBI
|
|
16
|
Carvalho B, Bengtsson H, Speed TP and
Irizarry RA: Exploration, normalization, and genotype calls of
high-density oligonucleotide SNP array data. Biostatistics.
8:485–499. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Eyre TA, Ducluzeau F, Sneddon TP, Povey S,
Bruford EA and Lush MJ: The HUGO gene nomenclature database, 2006
updates. Nucleic Acids Res. 34:D319–D321. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Chen Y, Lun ATL and Smyth GK: Differential
expression analysis of complex RNA-seq experiments using edgeR.
Springer International Publishing; Springer, Cham: pp. 51–74.
2014
|
|
19
|
Yue S: Clinical trial data analysis using
R. J Statistical Software. 43:2011.
|
|
20
|
Baur B and Bozdag S: A feature selection
algorithm to compute gene centric methylation from probe level
methylation data. PLoS One. 11:e01489772016. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Mavroforakis ME and Theodoridis S: A
geometric approach to support vector machine (SVM) classification.
IEEE Trans Neural Netw. 17:671–682. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Jeggari A, Marks DS and Larsson E:
miRcode: A map of putative microRNA target sites in the long
non-coding transcriptome. Bioinformatics. 28:2062–2063. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Li JH, Liu S, Zhou H, Qu LH and Yang JH:
starBase v2.0: Decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA
interaction networks from large-scale CLIP-Seq data. Nucleic Acids
Res. 42:D92–D97. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Chou CH, Chang NW, Shrestha S, Hsu SD, Lin
YL, Lee WH, Yang CD, Hong HC, Wei TY, Tu SJ, et al: miRTarBase
2016: Updates to the experimentally validated miRNA-target
interactions database. Nucleic Acids Res. 44:D239–D247. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Hsu SD, Lin FM, Wu WY, Liang C, Huang WC,
Chan WL, Tsai WT, Chen GZ, Lee CJ, Chiu CM, et al: miRTarBase: A
database curates experimentally validated microRNA-target
interactions. Nucleic Acids Res. 39:D163–D169. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Chien J, Sicotte H, Fan JB, Humphray S,
Cunningham JM, Kalli KR, Oberg AL, Hart SN, Li Y, Davila JI, et al:
TP53 mutations, tetraploidy and homologous recombination
repair defects in early stage high-grade serous ovarian cancer.
Nucleic Acids Res. 43:6945–6958. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Zhang M, Zhuang G, Sun X, Shen Y, Wang W,
Li Q and Di W: TP53 mutation-mediated genomic instability induces
the evolution of chemoresistance and recurrence in epithelial
ovarian cancer. Diagn Pathol. 12:162017. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Báezvega PM, Vargas Echevarría IM,
Valiyeva F, Encarnación-Rosado J, Roman A, Flores J,
Marcos-Martínez MJ and Vivas-Mejía PE: Targeting miR-21-3p inhibits
proliferation and invasion of ovarian cancer cells. Oncotarget.
7:36321–36337. 2016.PubMed/NCBI
|
|
29
|
Kwon JY, Seo YR and Ahn WS: Recognition of
potential predictive markers for diagnosis in Korean serous ovarian
cancer patients at stage IIIc using array comparative genomic
hybridization with high resolution. Mol Cell Toxicol. 7:77–86.
2011. View Article : Google Scholar
|
|
30
|
Bierkens M, Krijgsman O, Wilting SM, Bosch
L, Jaspers A, Meijer GA, Meijer CJ, Snijders PJ, Ylstra B and
Steenbergen RD: Focal aberrations indicate EYA2 and hsa-miR-375 as
oncogene and tumor suppressor in cervical carcinogenesis. Genes
Chromosomes Cancer. 52:56–68. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Yu X, Zhang X, Bi T, Ding Y, Zhao J, Wang
C, Jia T, Han D, Guo G, Wang B, et al: MiRNA expression signature
for potentially predicting the prognosis of ovarian serous
carcinoma. Tumour Biol. 34:3501–3508. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Zhang X, Yan Z, Zhang J, Gong L, Li W, Cui
J, Liu Y, Gao Z, Li J, Shen L and Lu Y: Combination of hsa-miR-375
and hsa-miR-142-5p as a predictor for recurrence risk in gastric
cancer patients following surgical resection. Ann Oncol.
22:2257–2266. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Xu L, Li Q, Xu D, Wang Q, An Y, Du Q,
Zhang J, Zhu Y and Miao Y: hsa-miR-141 downregulates TM4SF1 to
inhibit pancreatic cancer cell invasion and migration. Int J Oncol.
44:459–466. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Wang L, Zhu MJ, Ren AM, Wu HF, Han WM, Tan
RY and Tu RQ: A ten-microRNA signature identified from a
genome-wide microRNA expression profiling in human epithelial
ovarian cancer. PLoS One. 9:e964722014. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Waltering KK, Porkka KP, Jalava SE,
Urbanucci A, Kohonen PJ, Latonen LM, Kallioniemi OP, Jenster G and
Visakorpi T: Androgen regulation of micro-RNAs in prostate cancer.
Prostate. 71:604–614. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Chen J, Wang L, Matyunina LV, Hill CG and
McDonald JF: Overexpression of miR-429 induces
mesenchymal-to-epithelial transition (MET) in metastatic ovarian
cancer cells. Gynecol Oncol. 121:200–205. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Hu X, Macdonald DM, Huettner PC, Feng Z,
El Naqa IM, Schwarz JK, Mutch DG, Grigsby PW, Powell SN and Wang X:
A miR-200 microRNA cluster as prognostic marker in advanced ovarian
cancer. Gynecol Oncol. 114:457–464. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Park YT, Jeong JY, Lee MJ, Kim KI, Kim TH,
Kwon YD, Lee C, Kim OJ and An HJ: MicroRNAs overexpressed in
ovarian ALDH1-positive cells are associated with chemoresistance. J
Ovarian Res. 6:182013. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Li Z, Hu S, Wang J, Cai J, Xiao L, Yu L
and Wang Z: MiR-27a modulates MDR1/P-glycoprotein expression by
targeting HIPK2 in human ovarian cancer cells. Gynecol Oncol.
119:125–130. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Fuchs H, Theuser M, Wruck W and Adjaye J:
miR-27 negatively regulates pluripotency-associated genes in human
embryonal carcinoma cells. PLoS One. 9:e1116372014. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Halytskiy V: Shifts in microRNA expression
pattern can facilitate the cancer cell stemness. Eur J Cancer.
50:1742014. View Article : Google Scholar
|
|
42
|
Hylander B, Repasky E, Shrikant P,
Intengan M, Beck A, Driscoll D, Singhal P, Lele S and Odunsi K:
Expression of Wilms tumor gene (WT1) in epithelial ovarian cancer.
Gynecol Oncol. 101:12–17. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Dallosso AR, Hancock AL, Malik S, Salpekar
A, King-Underwood L, Pritchard-Jones K, Peters J, Moorwood K, Ward
A, Malik KT and Brown KW: Alternately spliced WT1 antisense
transcripts interact with WT1 sense RNA and show epigenetic
and splicing defects in cancer. RNA. 13:2287–2299. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Garzon R, Volinia S, Papaioannou D,
Nicolet D, Kohlschmidt J, Yan PS, Mrózek K, Bucci D, Carroll AJ,
Baer MR, et al: Expression and prognostic impact of lncRNAs in
acute myeloid leukemia. Proc Natl Acad Sci USA. 111:18679–18684.
2014. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Du T, Zhang B, Zhang S, Jiang X, Zheng P,
Li J, Yan M, Zhu Z and Liu B: Decreased expression of long
non-coding RNA WT1-AS promotes cell proliferation and invasion in
gastric cancer. Biochim Biophys Acta. 1862:12–19. 2016. View Article : Google Scholar : PubMed/NCBI
|
