Clinical, histopathologic, and molecular markers of prognosis: Toward a new disease risk stratification system for medulloblastoma

Amar Gajjar, Roberto Hernan, Mehmet Kocak, Christine Fuller, Youngsoo Lee, Peter J. McKinnon, Dana Wallace, Ching Lau, Murali Chintagumpala, David M. Ashley, Stewart J. Kellie, Larry Kun, Richard J. Gilbertson

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Abstract

Purpose: To assess the feasibility of performing central molecular analyses of fresh medulloblastomas obtained from multiple institutions and using these data to identify prognostic markers for contemporaneously treated patients. Materials and Methods: Ninety-seven samples of medulloblastoma were collected. Tumor content in samples was judged by frozen section review. Tumor ERBB2 protein and MYCC, MYCN, and TRKC mRNA levels were measured blind to clinical details using Western blotting and real-time polymerase chain reaction, respectively. Histopathologic and clinical review of each case was also performed. All data were subjected to independent statistical analysis. Results: Sample acquisition and analysis times ranged from 3 to 6 days. Eighty-six samples contained sufficient tumor for analysis, including 38 classic, 30 nodular desmoplastic, and 18 large-cell anaplastic (LCA) medulloblastomas. Protein and mRNA were extracted from 81 and 49 tumors, respectively. ERBB2 was detected in 40% (n = 32 of 81) of tumors, most frequently in LCA disease (P = .005), and was independently associated with a poor prognosis (P = .031). A combination of clinical characteristics and ERBB2 expression provided a highly accurate means of discriminating disease risk. One hundred percent (n = 26) of children with clinical average-risk, ERBB2-negative disease were alive at 5 years, with a median follow-up of 5.6 years, compared with only 54% for children with average-risk, ERBB2-positive tumors (n = 13; P = .0001). TRKC, MYCC, and MYCN expression and histopathologic subtype were not associated with prognosis in this study. Conclusion: Central and rapid molecular analysis of frozen medulloblastomas collected from multiple institutions is feasible. ERBB2 expression and clinical risk factors together constitute a highly accurate disease risk stratification tool.

Original languageEnglish (US)
Pages (from-to)984-993
Number of pages10
JournalJournal of Clinical Oncology
Volume22
Issue number6
DOIs
StatePublished - Dec 1 2004

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Medulloblastoma
Neoplasms
Messenger RNA
Frozen Sections
Real-Time Polymerase Chain Reaction
Western Blotting
Proteins

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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Clinical, histopathologic, and molecular markers of prognosis : Toward a new disease risk stratification system for medulloblastoma. / Gajjar, Amar; Hernan, Roberto; Kocak, Mehmet; Fuller, Christine; Lee, Youngsoo; McKinnon, Peter J.; Wallace, Dana; Lau, Ching; Chintagumpala, Murali; Ashley, David M.; Kellie, Stewart J.; Kun, Larry; Gilbertson, Richard J.

In: Journal of Clinical Oncology, Vol. 22, No. 6, 01.12.2004, p. 984-993.

Research output: Contribution to journalArticle

Gajjar, A, Hernan, R, Kocak, M, Fuller, C, Lee, Y, McKinnon, PJ, Wallace, D, Lau, C, Chintagumpala, M, Ashley, DM, Kellie, SJ, Kun, L & Gilbertson, RJ 2004, 'Clinical, histopathologic, and molecular markers of prognosis: Toward a new disease risk stratification system for medulloblastoma', Journal of Clinical Oncology, vol. 22, no. 6, pp. 984-993. https://doi.org/10.1200/JCO.2004.06.032
Gajjar, Amar ; Hernan, Roberto ; Kocak, Mehmet ; Fuller, Christine ; Lee, Youngsoo ; McKinnon, Peter J. ; Wallace, Dana ; Lau, Ching ; Chintagumpala, Murali ; Ashley, David M. ; Kellie, Stewart J. ; Kun, Larry ; Gilbertson, Richard J. / Clinical, histopathologic, and molecular markers of prognosis : Toward a new disease risk stratification system for medulloblastoma. In: Journal of Clinical Oncology. 2004 ; Vol. 22, No. 6. pp. 984-993.
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T1 - Clinical, histopathologic, and molecular markers of prognosis

T2 - Toward a new disease risk stratification system for medulloblastoma

AU - Gajjar, Amar

AU - Hernan, Roberto

AU - Kocak, Mehmet

AU - Fuller, Christine

AU - Lee, Youngsoo

AU - McKinnon, Peter J.

AU - Wallace, Dana

AU - Lau, Ching

AU - Chintagumpala, Murali

AU - Ashley, David M.

AU - Kellie, Stewart J.

AU - Kun, Larry

AU - Gilbertson, Richard J.

PY - 2004/12/1

Y1 - 2004/12/1

N2 - Purpose: To assess the feasibility of performing central molecular analyses of fresh medulloblastomas obtained from multiple institutions and using these data to identify prognostic markers for contemporaneously treated patients. Materials and Methods: Ninety-seven samples of medulloblastoma were collected. Tumor content in samples was judged by frozen section review. Tumor ERBB2 protein and MYCC, MYCN, and TRKC mRNA levels were measured blind to clinical details using Western blotting and real-time polymerase chain reaction, respectively. Histopathologic and clinical review of each case was also performed. All data were subjected to independent statistical analysis. Results: Sample acquisition and analysis times ranged from 3 to 6 days. Eighty-six samples contained sufficient tumor for analysis, including 38 classic, 30 nodular desmoplastic, and 18 large-cell anaplastic (LCA) medulloblastomas. Protein and mRNA were extracted from 81 and 49 tumors, respectively. ERBB2 was detected in 40% (n = 32 of 81) of tumors, most frequently in LCA disease (P = .005), and was independently associated with a poor prognosis (P = .031). A combination of clinical characteristics and ERBB2 expression provided a highly accurate means of discriminating disease risk. One hundred percent (n = 26) of children with clinical average-risk, ERBB2-negative disease were alive at 5 years, with a median follow-up of 5.6 years, compared with only 54% for children with average-risk, ERBB2-positive tumors (n = 13; P = .0001). TRKC, MYCC, and MYCN expression and histopathologic subtype were not associated with prognosis in this study. Conclusion: Central and rapid molecular analysis of frozen medulloblastomas collected from multiple institutions is feasible. ERBB2 expression and clinical risk factors together constitute a highly accurate disease risk stratification tool.

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