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Article: Cytogenetic prognostication within medulloblastoma subgroups

TitleCytogenetic prognostication within medulloblastoma subgroups
Authors
Issue Date2014
Citation
Journal of Clinical Oncology, 2014, v. 32, n. 9, p. 886-896 How to Cite?
AbstractPurpose: Medulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication. Patients and Methods: Molecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models. Results: Subgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas. Conclusion: Combining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials. © 2014 by American Society of Clinical Oncology.
Persistent Identifierhttp://hdl.handle.net/10722/313963
ISSN
2023 Impact Factor: 42.1
2023 SCImago Journal Rankings: 10.639
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShih, David J.H.-
dc.contributor.authorNorthcott, Paul A.-
dc.contributor.authorRemke, Marc-
dc.contributor.authorKorshunov, Andrey-
dc.contributor.authorRamaswamy, Vijay-
dc.contributor.authorKool, Marcel-
dc.contributor.authorLuu, Betty-
dc.contributor.authorYao, Yuan-
dc.contributor.authorWang, Xin-
dc.contributor.authorDubuc, Adrian M.-
dc.contributor.authorGarzia, Livia-
dc.contributor.authorPeacock, John-
dc.contributor.authorMack, Stephen C.-
dc.contributor.authorWu, Xiaochong-
dc.contributor.authorRolider, Adi-
dc.contributor.authorMorrissy, A. Sorana-
dc.contributor.authorCavalli, Florence M.G.-
dc.contributor.authorJones, David T.W.-
dc.contributor.authorZitterbart, Karel-
dc.contributor.authorFaria, Claudia C.-
dc.contributor.authorSchüller, Ulrich-
dc.contributor.authorKren, Leos-
dc.contributor.authorKumabe, Toshihiro-
dc.contributor.authorTominaga, Teiji-
dc.contributor.authorRa, Young Shin-
dc.contributor.authorGarami, Miklós-
dc.contributor.authorHauser, Peter-
dc.contributor.authorChan, Jennifer A.-
dc.contributor.authorRobinson, Shenandoah-
dc.contributor.authorBognár, László-
dc.contributor.authorKlekner, Almos-
dc.contributor.authorSaad, Ali G.-
dc.contributor.authorLiau, Linda M.-
dc.contributor.authorAlbrecht, Steffen-
dc.contributor.authorFontebasso, Adam-
dc.contributor.authorCinalli, Giuseppe-
dc.contributor.authorDe Antonellis, Pasqualino-
dc.contributor.authorZollo, Massimo-
dc.contributor.authorCooper, Michael K.-
dc.contributor.authorThompson, Reid C.-
dc.contributor.authorBailey, Simon-
dc.contributor.authorLindsey, Janet C.-
dc.contributor.authorDi Rocco, Concezio-
dc.contributor.authorMassimi, Luca-
dc.contributor.authorMichiels, Erna M.C.-
dc.contributor.authorScherer, Stephen W.-
dc.contributor.authorPhillips, Joanna J.-
dc.contributor.authorGupta, Nalin-
dc.contributor.authorFan, Xing-
dc.contributor.authorMuraszko, Karin M.-
dc.contributor.authorVibhakar, Rajeev-
dc.contributor.authorEberhart, Charles G.-
dc.contributor.authorFouladi, Maryam-
dc.contributor.authorLach, Boleslaw-
dc.contributor.authorJung, Shin-
dc.contributor.authorWechsler-Reya, Robert J.-
dc.contributor.authorFèvre-Montange, Michelle-
dc.contributor.authorJouvet, Anne-
dc.contributor.authorJabado, Nada-
dc.contributor.authorPollack, Ian F.-
dc.contributor.authorWeiss, William A.-
dc.contributor.authorLee, Ji Yeoun-
dc.contributor.authorCho, Byung Kyu-
dc.contributor.authorKim, Seung Ki-
dc.contributor.authorWang, Kyu Chang-
dc.contributor.authorLeonard, Jeffrey R.-
dc.contributor.authorRubin, Joshua B.-
dc.contributor.authorDe Torres, Carmen-
dc.contributor.authorLavarino, Cinzia-
dc.contributor.authorMora, Jaume-
dc.contributor.authorCho, Yoon Jae-
dc.contributor.authorTabori, Uri-
dc.contributor.authorOlson, James M.-
dc.contributor.authorGajjar, Amar-
dc.contributor.authorPacker, Roger J.-
dc.contributor.authorRutkowski, Stefan-
dc.contributor.authorPomeroy, Scott L.-
dc.contributor.authorFrench, Pim J.-
dc.contributor.authorKloosterhof, Nanne K.-
dc.contributor.authorKros, Johan M.-
dc.contributor.authorVan Meir, Erwin G.-
dc.contributor.authorClifford, Steven C.-
dc.contributor.authorBourdeaut, Franck-
dc.contributor.authorDelattre, Olivier-
dc.contributor.authorDoz, François F.-
dc.contributor.authorHawkins, Cynthia E.-
dc.contributor.authorMalkin, David-
dc.contributor.authorGrajkowska, Wieslawa A.-
dc.contributor.authorPerek-Polnik, Marta-
dc.contributor.authorBouffet, Eric-
dc.contributor.authorRutka, James T.-
dc.contributor.authorPfister, Stefan M.-
dc.contributor.authorTaylor, Michael D.-
dc.date.accessioned2022-07-06T11:28:38Z-
dc.date.available2022-07-06T11:28:38Z-
dc.date.issued2014-
dc.identifier.citationJournal of Clinical Oncology, 2014, v. 32, n. 9, p. 886-896-
dc.identifier.issn0732-183X-
dc.identifier.urihttp://hdl.handle.net/10722/313963-
dc.description.abstractPurpose: Medulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication. Patients and Methods: Molecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models. Results: Subgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas. Conclusion: Combining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials. © 2014 by American Society of Clinical Oncology.-
dc.languageeng-
dc.relation.ispartofJournal of Clinical Oncology-
dc.titleCytogenetic prognostication within medulloblastoma subgroups-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1200/JCO.2013.50.9539-
dc.identifier.pmid24493713-
dc.identifier.pmcidPMC3948094-
dc.identifier.scopuseid_2-s2.0-84899684426-
dc.identifier.volume32-
dc.identifier.issue9-
dc.identifier.spage886-
dc.identifier.epage896-
dc.identifier.eissn1527-7755-
dc.identifier.isiWOS:000335137900019-

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