Cytogenetic prognostication within medulloblastoma subgroups

David J.H. Shih, Paul A. Northcott, Marc Remke, Andrey Korshunov, Vijay Ramaswamy, Marcel Kool, Betty Luu, Yuan Yao, Xin Wang, Adrian M. Dubuc, Livia Garzia, John Peacock, Stephen C. Mack, Xiaochong Wu, Adi Rolider, A. Sorana Morrissy, Florence M.G. Cavalli, David T.W. Jones, Karel Zitterbart, Claudia C. Faria & 73 others Ulrich Schüller, Leos Kren, Toshihiro Kumabe, Teiji Tominaga, Young Shin Ra, Miklós Garami, Peter Hauser, Jennifer A. Chan, Shenandoah Robinson, László Bognár, Almos Klekner, Ali Saad, Linda M. Liau, Steffen Albrecht, Adam Fontebasso, Giuseppe Cinalli, Pasqualino De Antonellis, Massimo Zollo, Michael K. Cooper, Reid C. Thompson, Simon Bailey, Janet C. Lindsey, Concezio Di Rocco, Luca Massimi, Erna M.C. Michiels, Stephen W. Scherer, Joanna J. Phillips, Nalin Gupta, Xing Fan, Karin M. Muraszko, Rajeev Vibhakar, Charles G. Eberhart, Maryam Fouladi, Boleslaw Lach, Shin Jung, Robert J. Wechsler-Reya, Michelle Fèvre-Montange, Anne Jouvet, Nada Jabado, Ian F. Pollack, William A. Weiss, Ji Yeoun Lee, Byung Kyu Cho, Seung Ki Kim, Kyu Chang Wang, Jeffrey R. Leonard, Joshua B. Rubin, Carmen De Torres, Cinzia Lavarino, Jaume Mora, Yoon Jae Cho, Uri Tabori, James M. Olson, Amar Gajjar, Roger J. Packer, Stefan Rutkowski, Scott L. Pomeroy, Pim J. French, Nanne K. Kloosterhof, Johan M. Kros, Erwin G. Van Meir, Steven C. Clifford, Franck Bourdeaut, Olivier Delattre, François F. Doz, Cynthia E. Hawkins, David Malkin, Wieslawa A. Grajkowska, Marta Perek-Polnik, Eric Bouffet, James T. Rutka, Stefan M. Pfister, Michael D. Taylor

Research output: Contribution to journalArticle

124 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)886-896
Number of pages11
JournalJournal of Clinical Oncology
Volume32
Issue number9
DOIs
StatePublished - Mar 20 2014

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Medulloblastoma
Cytogenetics
Biomarkers
Fluorescence In Situ Hybridization
Chromosomes, Human, Pair 11
Paraffin
Formaldehyde
Therapeutics
Clinical Trials

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

Cite this

Shih, D. J. H., Northcott, P. A., Remke, M., Korshunov, A., Ramaswamy, V., Kool, M., ... Taylor, M. D. (2014). Cytogenetic prognostication within medulloblastoma subgroups. Journal of Clinical Oncology, 32(9), 886-896. https://doi.org/10.1200/JCO.2013.50.9539

Cytogenetic prognostication within medulloblastoma subgroups. / Shih, David J.H.; Northcott, Paul A.; Remke, Marc; Korshunov, Andrey; Ramaswamy, Vijay; Kool, Marcel; Luu, Betty; Yao, Yuan; Wang, Xin; Dubuc, Adrian M.; Garzia, Livia; Peacock, John; Mack, Stephen C.; Wu, Xiaochong; Rolider, Adi; Morrissy, A. Sorana; Cavalli, Florence M.G.; Jones, David T.W.; Zitterbart, Karel; Faria, Claudia C.; Schüller, Ulrich; Kren, Leos; Kumabe, Toshihiro; Tominaga, Teiji; Ra, Young Shin; Garami, Miklós; Hauser, Peter; Chan, Jennifer A.; Robinson, Shenandoah; Bognár, László; Klekner, Almos; Saad, Ali; Liau, Linda M.; Albrecht, Steffen; Fontebasso, Adam; Cinalli, Giuseppe; De Antonellis, Pasqualino; Zollo, Massimo; Cooper, Michael K.; Thompson, Reid C.; Bailey, Simon; Lindsey, Janet C.; Di Rocco, Concezio; Massimi, Luca; Michiels, Erna M.C.; Scherer, Stephen W.; Phillips, Joanna J.; Gupta, Nalin; Fan, Xing; Muraszko, Karin M.; Vibhakar, Rajeev; Eberhart, Charles G.; Fouladi, Maryam; Lach, Boleslaw; Jung, Shin; Wechsler-Reya, Robert J.; Fèvre-Montange, Michelle; Jouvet, Anne; Jabado, Nada; Pollack, Ian F.; Weiss, William A.; Lee, Ji Yeoun; Cho, Byung Kyu; Kim, Seung Ki; Wang, Kyu Chang; Leonard, Jeffrey R.; Rubin, Joshua B.; De Torres, Carmen; Lavarino, Cinzia; Mora, Jaume; Cho, Yoon Jae; Tabori, Uri; Olson, James M.; Gajjar, Amar; Packer, Roger J.; Rutkowski, Stefan; Pomeroy, Scott L.; French, Pim J.; Kloosterhof, Nanne K.; Kros, Johan M.; Van Meir, Erwin G.; Clifford, Steven C.; Bourdeaut, Franck; Delattre, Olivier; Doz, François F.; Hawkins, Cynthia E.; Malkin, David; Grajkowska, Wieslawa A.; Perek-Polnik, Marta; Bouffet, Eric; Rutka, James T.; Pfister, Stefan M.; Taylor, Michael D.

In: Journal of Clinical Oncology, Vol. 32, No. 9, 20.03.2014, p. 886-896.

Research output: Contribution to journalArticle

Shih, DJH, Northcott, PA, Remke, M, Korshunov, A, Ramaswamy, V, Kool, M, Luu, B, Yao, Y, Wang, X, Dubuc, AM, Garzia, L, Peacock, J, Mack, SC, Wu, X, Rolider, A, Morrissy, AS, Cavalli, FMG, Jones, DTW, Zitterbart, K, Faria, CC, Schüller, U, Kren, L, Kumabe, T, Tominaga, T, Ra, YS, Garami, M, Hauser, P, Chan, JA, Robinson, S, Bognár, L, Klekner, A, Saad, A, Liau, LM, Albrecht, S, Fontebasso, A, Cinalli, G, De Antonellis, P, Zollo, M, Cooper, MK, Thompson, RC, Bailey, S, Lindsey, JC, Di Rocco, C, Massimi, L, Michiels, EMC, Scherer, SW, Phillips, JJ, Gupta, N, Fan, X, Muraszko, KM, Vibhakar, R, Eberhart, CG, Fouladi, M, Lach, B, Jung, S, Wechsler-Reya, RJ, Fèvre-Montange, M, Jouvet, A, Jabado, N, Pollack, IF, Weiss, WA, Lee, JY, Cho, BK, Kim, SK, Wang, KC, Leonard, JR, Rubin, JB, De Torres, C, Lavarino, C, Mora, J, Cho, YJ, Tabori, U, Olson, JM, Gajjar, A, Packer, RJ, Rutkowski, S, Pomeroy, SL, French, PJ, Kloosterhof, NK, Kros, JM, Van Meir, EG, Clifford, SC, Bourdeaut, F, Delattre, O, Doz, FF, Hawkins, CE, Malkin, D, Grajkowska, WA, Perek-Polnik, M, Bouffet, E, Rutka, JT, Pfister, SM & Taylor, MD 2014, 'Cytogenetic prognostication within medulloblastoma subgroups', Journal of Clinical Oncology, vol. 32, no. 9, pp. 886-896. https://doi.org/10.1200/JCO.2013.50.9539
Shih DJH, Northcott PA, Remke M, Korshunov A, Ramaswamy V, Kool M et al. Cytogenetic prognostication within medulloblastoma subgroups. Journal of Clinical Oncology. 2014 Mar 20;32(9):886-896. https://doi.org/10.1200/JCO.2013.50.9539
Shih, David J.H. ; Northcott, Paul A. ; Remke, Marc ; Korshunov, Andrey ; Ramaswamy, Vijay ; Kool, Marcel ; Luu, Betty ; Yao, Yuan ; Wang, Xin ; Dubuc, Adrian M. ; Garzia, Livia ; Peacock, John ; Mack, Stephen C. ; Wu, Xiaochong ; Rolider, Adi ; Morrissy, A. Sorana ; Cavalli, Florence M.G. ; Jones, David T.W. ; Zitterbart, Karel ; Faria, Claudia C. ; Schüller, Ulrich ; Kren, Leos ; Kumabe, Toshihiro ; Tominaga, Teiji ; Ra, Young Shin ; Garami, Miklós ; Hauser, Peter ; Chan, Jennifer A. ; Robinson, Shenandoah ; Bognár, László ; Klekner, Almos ; Saad, Ali ; Liau, Linda M. ; Albrecht, Steffen ; Fontebasso, Adam ; Cinalli, Giuseppe ; De Antonellis, Pasqualino ; Zollo, Massimo ; Cooper, Michael K. ; Thompson, Reid C. ; Bailey, Simon ; Lindsey, Janet C. ; Di Rocco, Concezio ; Massimi, Luca ; Michiels, Erna M.C. ; Scherer, Stephen W. ; Phillips, Joanna J. ; Gupta, Nalin ; Fan, Xing ; Muraszko, Karin M. ; Vibhakar, Rajeev ; Eberhart, Charles G. ; Fouladi, Maryam ; Lach, Boleslaw ; Jung, Shin ; Wechsler-Reya, Robert J. ; Fèvre-Montange, Michelle ; Jouvet, Anne ; Jabado, Nada ; Pollack, Ian F. ; Weiss, William A. ; Lee, Ji Yeoun ; Cho, Byung Kyu ; Kim, Seung Ki ; Wang, Kyu Chang ; Leonard, Jeffrey R. ; Rubin, Joshua B. ; De Torres, Carmen ; Lavarino, Cinzia ; Mora, Jaume ; Cho, Yoon Jae ; Tabori, Uri ; Olson, James M. ; Gajjar, Amar ; Packer, Roger J. ; Rutkowski, Stefan ; Pomeroy, Scott L. ; French, Pim J. ; Kloosterhof, Nanne K. ; Kros, Johan M. ; Van Meir, Erwin G. ; Clifford, Steven C. ; Bourdeaut, Franck ; Delattre, Olivier ; Doz, François F. ; Hawkins, Cynthia E. ; Malkin, David ; Grajkowska, Wieslawa A. ; Perek-Polnik, Marta ; Bouffet, Eric ; Rutka, James T. ; Pfister, Stefan M. ; Taylor, Michael D. / Cytogenetic prognostication within medulloblastoma subgroups. In: Journal of Clinical Oncology. 2014 ; Vol. 32, No. 9. pp. 886-896.
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title = "Cytogenetic prognostication within medulloblastoma subgroups",
abstract = "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.",
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language = "English (US)",
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pages = "886--896",
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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 - Ra, Young Shin

AU - Garami, Miklós

AU - Hauser, Peter

AU - Chan, Jennifer A.

AU - Robinson, Shenandoah

AU - Bognár, László

AU - Klekner, Almos

AU - Saad, Ali

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.

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U2 - 10.1200/JCO.2013.50.9539

DO - 10.1200/JCO.2013.50.9539

M3 - Article

VL - 32

SP - 886

EP - 896

JO - Journal of Clinical Oncology

JF - Journal of Clinical Oncology

SN - 0732-183X

IS - 9

ER -