1
|
Ostrom QT, Bauchet L, Davis FG, Deltour I,
Fisher JL, Langer CE, Pekmezci M, Schwartzbaum JA, Turner MC, Walsh
KM, et al: The epidemiology of glioma in adults: A ‘state of the
science’ review. Neuro oncol. 16:896–913. 2014. View Article : Google Scholar : PubMed/NCBI
|
2
|
Chen W, Zheng R, Baade PD, Zhang S, Zeng
H, Bray F, Jemal A, Yu XQ and He J: Cancer statistics in China,
2015. CA Cancer J Clin. 66:115–132. 2016. View Article : Google Scholar : PubMed/NCBI
|
3
|
Coppola D, Balducci L, Chen DT, Loboda A,
Nebozhyn M, Staller A, Fulp WJ, Dalton W, Yeatman T and Brem S:
Senescence-associated-gene signature identifies genes linked to
age, prognosis, and progression of human gliomas. J Geriatr Oncol.
5:389–399. 2014. View Article : Google Scholar : PubMed/NCBI
|
4
|
Chen JW, Zhou CF and Lin ZX: The influence
of different classification standards of age groups on prognosis in
high-grade hemispheric glioma patients. J Neurol Sci. 356:148–152.
2015. View Article : Google Scholar : PubMed/NCBI
|
5
|
Cancer Genome Atlas Research Network, .
Comprehensive genomic characterization defines human glioblastoma
genes and core pathways. Nature. 455:1061–1068. 2008. View Article : Google Scholar : PubMed/NCBI
|
6
|
Cancer Genome Atlas Research Network, ;
Brat DJ, Verhaak RG, Aldape KD, Yung WK, Salama SR, Cooper LA,
Rheinbay E, Miller CR, Vitucci M, Morozova O, et al: Comprehensive,
integrative genomic analysis of diffuse lower-grade gliomas. N Engl
J Med. 372:2481–2498. 2015. View Article : Google Scholar : PubMed/NCBI
|
7
|
Yan H, Parsons DW, Jin G, McLendon R,
Rasheed BA, Yuan W, Kos I, Batinic-Haberle I, Jones S, Riggins GJ,
et al: IDH1 and IDH2 mutations in gliomas. N Engl J Med.
360:765–773. 2009. View Article : Google Scholar : PubMed/NCBI
|
8
|
Esmaeili M, Hamans BC, Navis AC, van
Horssen R, Bathen TF, Gribbestad IS, Leenders WP and Heerschap A:
IDH1 R132H mutation generates a distinct phospholipid metabolite
profile in glioma. Cancer Res. 74:4898–4907. 2014. View Article : Google Scholar : PubMed/NCBI
|
9
|
Shibahara I, Sonoda Y, Kanamori M, Saito
R, Yamashita Y, Kumabe T, Watanabe M, Suzuki H, Kato S, Ishioka C
and Tominaga T: IDH1/2 gene status defines the prognosis and
molecular profiles in patients with grade III gliomas. Int J Clin
Oncol. 17:551–561. 2012. View Article : Google Scholar : PubMed/NCBI
|
10
|
Thomas L, Di Stefano AL and Ducray F:
Predictive biomarkers in adult gliomas: the present and the future.
Curr Opin Oncol. 25:689–694. 2013. View Article : Google Scholar : PubMed/NCBI
|
11
|
Cohen AL and Colman H: Glioma biology and
molecular markers. Cancer Treat Res. 163:15–30. 2015. View Article : Google Scholar : PubMed/NCBI
|
12
|
Wang HJ, Gao Y, Chen L, Li YL and Jiang
CL: RAB34 was a progression- and prognosis-associated biomarker in
gliomas. Tumour Biol. 36:1573–1578. 2015. View Article : Google Scholar : PubMed/NCBI
|
13
|
Cai H, Xue Y, Liu W, Li Z, Hu Y, Li Z,
Shang X and Liu Y: Overexpression of roundabout4 predicts poor
prognosis of primary glioma patients via correlating with
microvessel density. J Neurooncol. 123:161–169. 2015. View Article : Google Scholar : PubMed/NCBI
|
14
|
Gao H, Zhao H and Xiang W: Expression
level of human miR-34a correlates with glioma grade and prognosis.
J Neurooncol. 113:221–228. 2013. View Article : Google Scholar : PubMed/NCBI
|
15
|
Wu X, Weng L, Li X, Guo C, Pal SK, Jin JM,
Li Y, Nelson RA, Mu B, Onami SH, et al: Identification of a
4-microRNA signature for clear cell renal cell carcinoma metastasis
and prognosis. PloS One. 7:e356612012. View Article : Google Scholar : PubMed/NCBI
|
16
|
Bou Samra E, Klein B, Commes T and Moreaux
J: Identification of a 20-gene expression-based risk score as a
predictor of clinical outcome in chronic lymphocytic leukemia
patients. Biomed Res Int. 2014:4231742014. View Article : Google Scholar : PubMed/NCBI
|
17
|
Liu Q, Diao R, Feng G, Mu X and Li A: Risk
score based on three mRNA expression predicts the survival of
bladder cancer. Oncotarget. 8:61583–61591. 2017.PubMed/NCBI
|
18
|
Cardoso F, van't Veer LJ, Bogaerts J,
Slaets L, Viale G, Delaloge S, Pierga JY, Brain E, Causeret S,
DeLorenzi M, et al: 70-Gene signature as an aid to treatment
decisions in early-stage breast cancer. N Engl J Med. 375:717–729.
2016. View Article : Google Scholar : PubMed/NCBI
|
19
|
Marisa L, de Reynies A, Duval A, Selves J,
Gaub MP, Vescovo L, Etienne-Grimaldi MC, Schiappa R, Guenot D,
Ayadi M, et al: Gene expression classification of colon cancer into
molecular subtypes: Characterization, validation, and prognostic
value. PLoS Med. 10:e10014532013. View Article : Google Scholar : PubMed/NCBI
|
20
|
You YN, Rustin RB and Sullivan JD:
Oncotype DX((R)) colon cancer assay for prediction of recurrence
risk in patients with stage II and III colon cancer: A review of
the evidence. Surg Oncol. 24:61–66. 2015. View Article : Google Scholar : PubMed/NCBI
|
21
|
Lee Y, Liu J, Patel S, Cloughesy T, Lai A,
Farooqi H, Seligson D, Dong J, Liau L, Becker D, et al: Genomic
landscape of meningiomas. Brain Pathol. 20:751–762. 2010.
View Article : Google Scholar : PubMed/NCBI
|
22
|
Gravendeel LA, Kouwenhoven MC, Gevaert O,
de Rooi JJ, Stubbs AP, Duijm JE, Daemen A, Bleeker FE, Bralten LB,
Kloosterhof NK, et al: Intrinsic gene expression profiles of
gliomas are a better predictor of survival than histology. Cancer
Res. 69:9065–9072. 2009. View Article : Google Scholar : PubMed/NCBI
|
23
|
Freije WA, Castro-Vargas FE, Fang Z,
Horvath S, Cloughesy T, Liau LM, Mischel PS and Nelson SF: Gene
expression profiling of gliomas strongly predicts survival. Cancer
Res. 64:6503–6510. 2004. View Article : Google Scholar : PubMed/NCBI
|
24
|
Joo KM, Kim J, Jin J, Kim M, Seol HJ,
Muradov J, Yang H, Choi YL, Park WY, Kong DS, et al:
Patient-specific orthotopic glioblastoma xenograft models
recapitulate the histopathology and biology of human glioblastomas
in situ. Cell Rep. 3:260–273. 2013. View Article : Google Scholar : PubMed/NCBI
|
25
|
Subramanian A, Tamayo P, Mootha VK,
Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub
TR, Lander ES and Mesirov JP: Gene set enrichment analysis: A
knowledge-based approach for interpreting genome-wide expression
profiles. Proc Natl Acad Sci USA. 102:15545–15550. 2005. View Article : Google Scholar : PubMed/NCBI
|
26
|
Ishwaran H and Kogalur UB: Consistency of
random survival forests. Stat Probab Lett. 80:1056–1064. 2010.
View Article : Google Scholar : PubMed/NCBI
|
27
|
Ishwaran H, Gerds TA, Kogalur UB, Moore
RD, Gange SJ and Lau BM: Random survival forests for competing
risks. Biostatistics. 15:757–773. 2014. View Article : Google Scholar : PubMed/NCBI
|
28
|
Robin X, Turck N, Hainard A, Tiberti N,
Lisacek F, Sanchez JC and Müller M: pROC: An open-source package
for R and S+ to analyze and compare ROC curves. BMC
Bioinformatics. 12:772011. View Article : Google Scholar : PubMed/NCBI
|
29
|
Li Z, Yan X, Sun Y and Yang X: Expression
of ADP-ribosyltransferase 1 is associated with poor prognosis of
glioma patients. Tohoku J Exp Med. 239:269–278. 2016. View Article : Google Scholar : PubMed/NCBI
|
30
|
Xu X, Wei Y, Wang S, Luo M and Zeng H:
Serine-arginine protein kinase 1 (SRPK1) is elevated in gastric
cancer and plays oncogenic functions. Oncotarget. 8:61944–61957.
2017.PubMed/NCBI
|
31
|
Morokoff A, Ng W, Gogos A and Kaye AH:
Molecular subtypes, stem cells and heterogeneity: Implications for
personalised therapy in glioma. J Clin Neurosci. 22:1219–1226.
2015. View Article : Google Scholar : PubMed/NCBI
|
32
|
Jamshidi N, Jonasch E, Zapala M, Korn RL,
Aganovic L, Zhao H, Tumkur Sitaram R, Tibshirani RJ, Banerjee S,
Brooks JD, et al: The radiogenomic risk score: Construction of a
prognostic quantitative, noninvasive image-based molecular assay
for renal cell carcinoma. Radiology. 277:114–123. 2015. View Article : Google Scholar : PubMed/NCBI
|