Cytogenetic prognostication within medulloblastoma subgroups

TY - JOUR

T1 - Cytogenetic prognostication within medulloblastoma subgroups

AU - Shih, David J H

AU - Northcott, Paul A

AU - Remke, Marc

AU - Korshunov, Andrey

AU - Ramaswamy, Vijay

AU - Kool, Marcel

AU - Luu, Betty

AU - Yao, Yuan

AU - Wang, Xin

AU - Dubuc, Adrian M

AU - Garzia, Livia

AU - Peacock, John

AU - Mack, Stephen C

AU - Wu, Xiaochong

AU - Rolider, Adi

AU - Morrissy, A Sorana

AU - Cavalli, Florence M G

AU - Jones, David T W

AU - Zitterbart, Karel

AU - Faria, Claudia C

AU - Schüller, Ulrich

AU - Kren, Leos

AU - Kumabe, Toshihiro

AU - Tominaga, Teiji

AU - Shin Ra, Young

AU - Garami, Miklós

AU - Hauser, Peter

AU - Chan, Jennifer A

AU - Robinson, Shenandoah

AU - Bognár, László

AU - Klekner, Almos

AU - Saad, Ali G

AU - Liau, Linda M

AU - Albrecht, Steffen

AU - Fontebasso, Adam

AU - Cinalli, Giuseppe

AU - De Antonellis, Pasqualino

AU - Zollo, Massimo

AU - Cooper, Michael K

AU - Thompson, Reid C

AU - Bailey, Simon

AU - Lindsey, Janet C

AU - Di Rocco, Concezio

AU - Massimi, Luca

AU - Michiels, Erna M C

AU - Scherer, Stephen W

AU - Phillips, Joanna J

AU - Gupta, Nalin

AU - Fan, Xing

AU - Muraszko, Karin M

AU - Vibhakar, Rajeev

AU - Eberhart, Charles G

AU - Fouladi, Maryam

AU - Lach, Boleslaw

AU - Jung, Shin

AU - Wechsler-Reya, Robert J

AU - Fèvre-Montange, Michelle

AU - Jouvet, Anne

AU - Jabado, Nada

AU - Pollack, Ian F

AU - Weiss, William A

AU - Lee, Ji-Yeoun

AU - Cho, Byung-Kyu

AU - Kim, Seung-Ki

AU - Wang, Kyu-Chang

AU - Leonard, Jeffrey R

AU - Rubin, Joshua B

AU - de Torres, Carmen

AU - Lavarino, Cinzia

AU - Mora, Jaume

AU - Cho, Yoon-Jae

AU - Tabori, Uri

AU - Olson, James M

AU - Gajjar, Amar

AU - Packer, Roger J

AU - Rutkowski, Stefan

AU - Pomeroy, Scott L

AU - French, Pim J

AU - Kloosterhof, Nanne K

AU - Kros, Johan M

AU - Van Meir, Erwin G

AU - Clifford, Steven C

AU - Bourdeaut, Franck

AU - Delattre, Olivier

AU - Doz, François F

AU - Hawkins, Cynthia E

AU - Malkin, David

AU - Grajkowska, Wieslawa A

AU - Perek-Polnik, Marta

AU - Bouffet, Eric

AU - Rutka, James T

AU - Pfister, Stefan M

AU - Taylor, Michael D

PY - 2014/3/20

Y1 - 2014/3/20

N2 - PURPOSE: 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.

AB - PURPOSE: 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.

KW - Adolescent

KW - Child

KW - Child, Preschool

KW - Chromosomes, Human, Pair 11

KW - Chromosomes, Human, Pair 14

KW - Cytogenetics

KW - Female

KW - Gene Expression Profiling

KW - Gene Expression Regulation, Neoplastic

KW - Hedgehog Proteins

KW - Humans

KW - In Situ Hybridization, Fluorescence

KW - Infant

KW - Kruppel-Like Transcription Factors

KW - Male

KW - Medulloblastoma

KW - Nuclear Proteins

KW - Predictive Value of Tests

KW - Prognosis

KW - Proportional Hazards Models

KW - Proto-Oncogene Proteins c-myc

KW - Reproducibility of Results

KW - Risk Assessment

KW - Risk Factors

KW - Tissue Array Analysis

KW - Tumor Markers, Biological

KW - Wnt Proteins

KW - Young Adult

U2 - 10.1200/JCO.2013.50.9539

DO - 10.1200/JCO.2013.50.9539

M3 - SCORING: Journal article

C2 - 24493713

VL - 32

SP - 886

EP - 896

JO - J CLIN ONCOL

JF - J CLIN ONCOL

SN - 0732-183X

IS - 9

ER -