An Integrative Approach for in Silico Glioma Research

IEEE Trans Biomed Eng. 2010 Oct;57(10):2617-21. doi: 10.1109/TBME.2010.2060338. Epub 2010 Jul 23.

Abstract

The integration of imaging and genomic data is critical to forming a better understanding of disease. Large public datasets, such as The Cancer Genome Atlas, present a unique opportunity to integrate these complementary data types for in silico scientific research. In this letter, we focus on the aspect of pathology image analysis and illustrate the challenges associated with analyzing and integrating large-scale image datasets with molecular characterizations. We present an example study of diffuse glioma brain tumors, where the morphometric analysis of 81 million nuclei is integrated with clinically relevant transcriptomic and genomic characterizations of glioblastoma tumors. The preliminary results demonstrate the potential of combining morphometric and molecular characterizations for in silico research.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Nucleus / pathology
  • Computational Biology / methods*
  • Computer Simulation
  • Databases, Factual
  • Glioma / pathology*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Immunohistochemistry