Skip to main content
PMC home page
Brain Pathology logoLink to Brain Pathology
. 2006 Apr 5;12(1):108–116. doi: 10.1111/j.1750-3639.2002.tb00427.x

Molecular Classification of Human Diffuse Gliomas by Multidimensional Scaling Analysis of Gene Expression Profiles Parallels Morphology‐Based Classification, Correlates with Survival, and Reveals Clinically‐Relevant Novel Glioma Subsets

Gregory N Fuller 1,✉, Kenneth R Hess 2, Chang Hun Rhee *, W K Alfred Yung 3, Raymond A Sawaya 4, Janet M Bruner 1, Wei Zhang 1
PMCID: PMC8096049  PMID: 11771519

Abstract

There are several currently employed classification systems for diffuse gliomas that sort tumors based on histological features. Contemporary molecular techniques, however, offer the promise of improved tumor classification and resultant patient stratification for treatment and prognosis. In particular, gene expression profiling has shown exceptional promise for providing an alternative and more objective molecular approach to glioma classification. In this study, we used cDNA array technology to profile the gene expression of 30 primary human glioma tissue samples comprising 4 different glioma subtypes as defined by current World Health Organization (WHO 2000) criteria: glioblastoma (GM, WHO grade IV), anaplastic astrocytoma (AA, WHO grade III), anaplastic oligodendroglioma (AO, WHO grade III), and oligodendroglioma (OL, WHO grade II). Gene expression data alone were used to group the tumors using multidimensional scaling, which is an unsupervised statistical method. Results show that impressive separation of the 4 glioma subtypes can be achieved solely on the basis of molecular data. In addition, a subcluster of 3 glioblastomas was identified as distinct from other GMs and from the oligodendroglial tumors. These 3 patients have shown extended survival compared to other GMs in the study. Survival analysis of the full data set revealed a good correlation with the molecular classification. Results of this proof‐of‐principle study demonstrate that molecular profiling alone can recapitulate conventional histologic classification and grading with high fidelity. In addition, results show that the molecular approach to tumor classification can generate clinically meaningful patient stratification, and, more importantly, is an efficient class‐discovery tool for human gliomas, permitting the identification of previously unrecognized, clinically relevant tumor subsets.

Full Text

The Full Text of this article is available as a PDF (69.0 KB).

A preliminary report of some of the data in this study was presented at the annual meeting of the American Association of Neuropathologists in Atlanta on June 10, 2000.

References

  • 1. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson J Jr, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Staudt LM (2000) Distinct types of diffuse large B‐cell lymphoma identified by gene expression profiling. Nature 403:503–11. [DOI] [PubMed] [Google Scholar]
  • 2. Bittner M, Meltzer P, Chen Y, Jiang Y, Seftor E, Hendrix M, Radmacher M, Simon R, Yakhini Z, Ben‐Dor A, Sampas N, Dougherty E, Wang E, Marincola F, Gooden C, Lueders J, Glatfelter A, Pollock P, Carpten J, Gillanders E, Leja D, Dietrich K, Beaudry C, Berens M, Alberts D, Sondak V (2000) Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 406:536–540. [DOI] [PubMed] [Google Scholar]
  • 3. Borg I, Groenen P (1977) Modern multidimensional scaling: theory and applications. New York : Springer‐Verlag. [Google Scholar]
  • 4. Burger PC, Vogel FS, Green SB, Strike TA (1985) Glioblastoma multiforme and anaplastic astrocytoma. Pathologic criteria and prognostic implications. Cancer 56:1106–1111. [DOI] [PubMed] [Google Scholar]
  • 5. Cairncross JG, Ueki K, Zlatescu MC, Lisle DK, Finkelstein DM, Hammond RR, Silver JS, Stark PC, MacDonald DR, Ino Y, Ramsay DA, Louis DN (1998) Specific genetic predictors of chemotherapeutic response and survival in pateints with anaplastic oligodendrogliomas. Journal of the National Cancer Institute 90:1473–1479. [DOI] [PubMed] [Google Scholar]
  • 6. Caskey LS, Fuller GN, Bruner JM, Yung WKA, Yung WKA, Sawaya RA, Holland EC, Zhang W (2000) Toward a molecular classification of the gliomas: histopathologies, molecular genetics, and gene expression profiling. Histology and Histopathology 15:971–981. [DOI] [PubMed] [Google Scholar]
  • 7. Daumas‐Duport C, Scheithauer BW, O'Fallon J, Kelly P (1988) Grading of astrocytomas. A simple and reproducible method. Cancer 62:2152–2165. [DOI] [PubMed] [Google Scholar]
  • 8. DeRisi J, Penland L, Brown PO, Bittner ML, Meltzer PS, Ray M, Chen Y, Su YA, Trent JM (1996) Use of a cDNA microarray to analyze gene expression patterns in human cancer. Nat Genet 14:457–460. [DOI] [PubMed] [Google Scholar]
  • 9. Duggan DJ, Bittner M, Chen Y, Meltzer P, Trent JM (1999) Expression profiling using cDNA microarrays. Nat Genet (suppl) 21:10–14. [DOI] [PubMed] [Google Scholar]
  • 10. Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome‐wide expression patterns. Proc Natl Acad Sci USA 95:14863–14868. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Everitt BS (1993) Cluster Analysis, 3rd edition. London : Arnold. [Google Scholar]
  • 12. Fuller GN, Hess KR, Rhee, Bruner JM, Sawaya R, Yung WKA, Zhang W (2000) Molecular classification of human gliomas by gene expression profiling. J Neuropathol Exp Neurol 59:422 (Abstract). [Google Scholar]
  • 13. Fuller GN, Rhee CH, Hess K, Caskey L, Wang RP, Bruner JM, Yung A, Zhang W (1999) Reactivation of insulin‐like growth factor binding protein II expression during glioblastoma transformation revealed by parallel gene expression profiling. Cancer Res 59:4228–4232. [PubMed] [Google Scholar]
  • 14. Golub TR, Slonim D, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 285:531–537. [DOI] [PubMed] [Google Scholar]
  • 15. Johnson RA, Wichern DW (1982) Applied Multivariate Statistical Analysis. Englewood Cliffs : Prentice‐Hall. [Google Scholar]
  • 16. Khan J, Simon R, Bittner M, Chen Y, Leighton SB, Pohida T, Smith PD, Jiang Y, Gooden GC, Trent JM, Meltzer PS (1999) Gene expression profiling of alveolar rhabdomysarcoma with cDNA microarrays. Cancer Res 58:5009–5013. [PubMed] [Google Scholar]
  • 17. Kleihues P, Cavenee WK (2000) Pathology and genetics of tumours of the nervous system. World Health Organization Classification of Tumours of the Nervous System. Lyon : IARC Press. [Google Scholar]
  • 18. Nelson JS, Tsukada Y, Schoenfeld D, Fulling K, Lamarche J, Peress N. Necrosis as a prognostic criterion in malignant supratentorial astrocytic gliomas. Cancer (1983) 52:550–554. [DOI] [PubMed] [Google Scholar]
  • 19. Pison G, Struyf A, Rousseeuw PJ (1999) Displaying a clustering with CLUSPLOT. Computational Statistics and Data Analysis 30:381–391. [Google Scholar]
  • 20. Rhee CH, Hess K, Jabbur J, Ruiz M, Yang Y, Chen S, Chenchik A, Fuller GN, Zhang W (1999) cDNA expression array reveals heterogeneous gene expression profiles in three glioblastoma cell lines. Oncogene 18:2711–2717. [DOI] [PubMed] [Google Scholar]
  • 21. Rhee CH, Ruan S, Chen S, Chenchik A, Levin VA, Yung AW, Fuller GN, Zhang W (1999) Characterization of cellular pathways involved in glioblastoma response to the chemotherapeutic agent 1,3‐bis(2‐chloroethyl)‐1‐nitrosourea (BCNU) by gene expression profiling. Oncology Reports 6:393–401. [PubMed] [Google Scholar]
  • 22. Ringertz N (1950) Grading of gliomas. Acta Pathol Microbiol Scand 27:51–64. [PubMed] [Google Scholar]
  • 23. Sallinen S‐L, Sallinen PK, Haapasalo HK, Helin HJ, Helen PT, Schraml P, Kallioniemi O‐P, Kononen J (2000) Identification of differentially expressed genes in human gliomas by DNA microarray and tissue chip techniques. Cancer Res 60:6617–6622. [PubMed] [Google Scholar]
  • 24. Scheibler D, Schneider W (1985) Monte Carlo Tests of the accuracy of cluster analysis algorithms: a comparison of hierarchical and nonhierarchial methods. Multivar Behav Res 20:282–304. [DOI] [PubMed] [Google Scholar]
  • 25. Smith JS, Perry A, Borell TJ, Lee HK, O'Fallon J, Hosek SM, Kimmel D, Yates A, Burger PC, Scheithauer BW, Jenkins RB (2000) Alterations of chromosome arms 1p and 19q as predictors of survival in oligodendrogliomas, astrocytomas, and mixed oligoastrocytomas. J Clin Oncol 18:636–645. [DOI] [PubMed] [Google Scholar]
  • 26. Venables WN, Ripley BD (1999) Modern Applied Statistics with S‐Plus. London : Springer. [Google Scholar]
  • 27. Watson MA, Perry A, Budhjara V, Hicks C, Shannon WD, Rich KM. (2001) Gene expression profiling with oligonu‐cleotide microarrays distinguishes World Health Organization grade of oligodendrogliomas. Cancer Research 61:1825–1829. [PubMed] [Google Scholar]

Articles from Brain Pathology are provided here courtesy of Wiley

RESOURCES