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000132739 0247_ $$2doi$$a10.1158/1078-0432.CCR-17-2243
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000132739 1001_ $$aGómez, Soledad$$b0
000132739 245__ $$aA Novel Method for Rapid Molecular Subgrouping of Medulloblastoma.
000132739 260__ $$aPhiladelphia, Pa. [u.a.]$$bAACR$$c2018
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000132739 520__ $$aPurpose: The classification of medulloblastoma into WNT, SHH, group 3, and group 4 subgroups has become of critical importance for patient risk stratification and subgroup-tailored clinical trials. Here, we aimed to develop a simplified, clinically applicable classification approach that can be implemented in the majority of centers treating patients with medulloblastoma.Experimental Design: We analyzed 1,577 samples comprising previously published DNA methylation microarray data (913 medulloblastomas, 457 non-medulloblastoma tumors, 85 normal tissues), and 122 frozen and formalin-fixed paraffin-embedded medulloblastoma samples. Biomarkers were identified applying stringent selection filters and Linear Discriminant Analysis (LDA) method, and validated using DNA methylation microarray data, bisulfite pyrosequencing, and direct-bisulfite sequencing.Results: Using a LDA-based approach, we developed and validated a prediction method (EpiWNT-SHH classifier) based on six epigenetic biomarkers that allowed for rapid classification of medulloblastoma into the clinically relevant subgroups WNT, SHH, and non-WNT/non-SHH with excellent concordance (>99%) with current gold-standard methods, DNA methylation microarray, and gene signature profiling analysis. The EpiWNT-SHH classifier showed high prediction capacity using both frozen and formalin-fixed material, as well as diverse DNA methylation detection methods. Similarly, we developed a classifier specific for group 3 and group 4 tumors, based on five biomarkers (EpiG3-G4) with good discriminatory capacity, allowing for correct assignment of more than 92% of tumors. EpiWNT-SHH and EpiG3-G4 methylation profiles remained stable across tumor primary, metastasis, and relapse samples.Conclusions: The EpiWNT-SHH and EpiG3-G4 classifiers represent a new simplified approach for accurate, rapid, and cost-effective molecular classification of single medulloblastoma DNA samples, using clinically applicable DNA methylation detection methods. Clin Cancer Res; 24(6); 1355-63. ©2018 AACR.
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000132739 7001_ $$aGarrido-Garcia, Alícia$$b1
000132739 7001_ $$aGarcia-Gerique, Laura$$b2
000132739 7001_ $$aLemos, Isadora$$b3
000132739 7001_ $$aSuñol, Mariona$$b4
000132739 7001_ $$ade Torres, Carmen$$b5
000132739 7001_ $$aKulis, Marta$$b6
000132739 7001_ $$aPérez-Jaume, Sara$$b7
000132739 7001_ $$aCarcaboso, Ángel M$$b8
000132739 7001_ $$aLuu, Betty$$b9
000132739 7001_ $$aKieran, Mark W$$b10
000132739 7001_ $$aJabado, Nada$$b11
000132739 7001_ $$aKozlenkov, Alexey$$b12
000132739 7001_ $$aDracheva, Stella$$b13
000132739 7001_ $$aRamaswamy, Vijay$$b14
000132739 7001_ $$0P:(DE-He78)744146d3b5a3df1e0ac555e5bf1ee5cc$$aHovestadt, Volker$$b15$$udkfz
000132739 7001_ $$0P:(DE-He78)3fdc3623477264cb5d0e14f256dbfbb8$$aJohann, Pascal$$b16$$udkfz
000132739 7001_ $$0P:(DE-He78)551bb92841f634070997aa168d818492$$aJones, David$$b17$$udkfz
000132739 7001_ $$0P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9$$aPfister, Stefan$$b18$$udkfz
000132739 7001_ $$aMorales La Madrid, Andrés$$b19
000132739 7001_ $$aCruz, Ofelia$$b20
000132739 7001_ $$aTaylor, Michael D$$b21
000132739 7001_ $$aMartin-Subero, Jose-Ignacio$$b22
000132739 7001_ $$aMora, Jaume$$b23
000132739 7001_ $$aLavarino, Cinzia$$b24
000132739 773__ $$0PERI:(DE-600)2036787-9$$a10.1158/1078-0432.CCR-17-2243$$gVol. 24, no. 6, p. 1355 - 1363$$n6$$p1355 - 1363$$tClinical cancer research$$v24$$x1557-3265$$y2018
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