Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme

Hang Chang, Gerald V. Fontenay, Cemal C. Bilgin, Alexander Borowsky, Paul Spellman, Bahram Parvin

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Integrated analysis of tissue histology with the genome-wide array and clinical data has the potential to generate hypotheses as well as be prognostic. However, due to the inherent technical and biological variations, automated analysis of whole mount tissue sections is impeded in very large datasets, such as The Cancer Genome Atlas (TCGA), where tissue sections are collected from different laboratories. We aim to characterize tumor architecture from hematoxylin and eosin (H&E) stained tissue sections, through the delineation of nuclear regions on a cell-by-cell basis. Such a representation can then be utilized to derive intrinsic morphometric subtypes across a large cohort for prediction and molecular association. Our approach has been validated on manually annotated samples, and then applied to a Glioblastoma Multiforme (GBM) cohort of 377 whole slide images from 146 patients. Further bioinformatics analysis, based on the multidimensional representation of the nuclear features and their organization, has identified (i) statistically significant morphometric sub types; (ii) whether each subtype can be predictive or not and (iii) that the molecular correlates of predictive subtypes are consistent with the literature. The net result is the realization of the concept of pathway pathology through analysis of a large cohort of whole slide images.

Original languageEnglish (US)
Title of host publicationComputational Systems Biology: From Molecular Mechanisms to Disease: Second Edition
PublisherElsevier Inc.
Pages423-454
Number of pages32
ISBN (Print)9780124059269
DOIs
StatePublished - Dec 2013

Fingerprint

Glioblastoma
Tissue
Genes
Genome
Histology
Atlases
Pathology
Hematoxylin
Eosine Yellowish-(YS)
Bioinformatics
Computational Biology
Tumors
Neoplasms

Keywords

  • Glioblastoma multiforme
  • Histology classification
  • Molecular pathology
  • Morphometric subtyping
  • Nuclear segmentation
  • Tumor heterogeneity
  • Tumor histopathology

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Chang, H., Fontenay, G. V., Bilgin, C. C., Borowsky, A., Spellman, P., & Parvin, B. (2013). Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme. In Computational Systems Biology: From Molecular Mechanisms to Disease: Second Edition (pp. 423-454). Elsevier Inc.. https://doi.org/10.1016/B978-0-12-405926-9.00018-6

Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme. / Chang, Hang; Fontenay, Gerald V.; Bilgin, Cemal C.; Borowsky, Alexander; Spellman, Paul; Parvin, Bahram.

Computational Systems Biology: From Molecular Mechanisms to Disease: Second Edition. Elsevier Inc., 2013. p. 423-454.

Research output: Chapter in Book/Report/Conference proceedingChapter

Chang, H, Fontenay, GV, Bilgin, CC, Borowsky, A, Spellman, P & Parvin, B 2013, Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme. in Computational Systems Biology: From Molecular Mechanisms to Disease: Second Edition. Elsevier Inc., pp. 423-454. https://doi.org/10.1016/B978-0-12-405926-9.00018-6
Chang H, Fontenay GV, Bilgin CC, Borowsky A, Spellman P, Parvin B. Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme. In Computational Systems Biology: From Molecular Mechanisms to Disease: Second Edition. Elsevier Inc. 2013. p. 423-454 https://doi.org/10.1016/B978-0-12-405926-9.00018-6
Chang, Hang ; Fontenay, Gerald V. ; Bilgin, Cemal C. ; Borowsky, Alexander ; Spellman, Paul ; Parvin, Bahram. / Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme. Computational Systems Biology: From Molecular Mechanisms to Disease: Second Edition. Elsevier Inc., 2013. pp. 423-454
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