Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes

Jun Kong*, Lee A D Cooper, Fusheng Wang, David A. Gutman, Jingjing Gao, Candace Chisolm, Ashish Sharma, Tony Pan, Erwin G. Van Meir, Tahsin M. Kurc, Carlos S. Moreno, Joel H. Saltz, Daniel J. Brat

*Corresponding author for this work

Research output: Contribution to journalArticle

41 Scopus citations

Abstract

Multimodal, multiscale data synthesis is becoming increasingly critical for successful translational biomedical research. In this letter, we present a large-scale investigative initiative on glioblastoma, a high-grade brain tumor, with complementary data types using in silico approaches. We integrate and analyze data from The Cancer Genome Atlas Project on glioblastoma that includes novel nuclear phenotypic data derived from microscopic slides, genotypic signatures described by transcriptional class and genetic alterations, and clinical outcomes defined by response to therapy and patient survival. Our preliminary results demonstrate numerous clinically and biologically significant correlations across multiple data types, revealing the power of in silico multimodal data integration for cancer research.

Original languageEnglish (US)
Article number6025272
Pages (from-to)3469-3474
Number of pages6
JournalIEEE Transactions on Biomedical Engineering
Volume58
Issue number12 PART 2
DOIs
StatePublished - Dec 2011

Keywords

  • Cluster analysis
  • glioblastoma (GBM)
  • in silico
  • multimodal data process
  • translational integration

ASJC Scopus subject areas

  • Biomedical Engineering

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    Kong, J., Cooper, L. A. D., Wang, F., Gutman, D. A., Gao, J., Chisolm, C., Sharma, A., Pan, T., Van Meir, E. G., Kurc, T. M., Moreno, C. S., Saltz, J. H., & Brat, D. J. (2011). Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes. IEEE Transactions on Biomedical Engineering, 58(12 PART 2), 3469-3474. [6025272]. https://doi.org/10.1109/TBME.2011.2169256