Molecular characterization of the pediatric preclinical testing panel

Geoffrey Neale, Xiaoping Su, Christopher L. Morton, Doris Phelps, Richard Gorlick, Richard B. Lock, C. Patrick Reynolds, John M. Maris, Henry S. Friedman, Jeffrey Dome, Joseph Khoury, Timothy J. Triche, Robert C. Seeger, Richard Gilbertson, Javed Khan, Malcolm A. Smith, Peter J. Houghton

Research output: Contribution to journalArticlepeer-review

100 Scopus citations


Purpose: Identifying novel therapeutic agents for the treatment of childhood cancers requires preclinical models that recapitulate the molecular characteristics of their respective clinical histotypes. Experimental Design and Results: Here, we have applied Affymetrix HG-U133Plus2 profiling to an expanded panel of models in the Pediatric Preclinical Testing Program. Profiling led to exclusion of two tumor lines that were of mouse origin and five osteosarcoma lines that did not cluster with human or xenograft osteosarcoma samples. We compared expression profiles of the remaining 87 models with profiles from 112 clinical samples representing the same histologies and show that model tumors cluster with the appropriate clinical histotype, once " immunosurveillance" genes (contributed by infiltrating immune cells in clinical samples) are eliminated from the analysis. Analysis of copy number alterations using the Affymetrix 100K single nucleotide polymorphism GeneChip showed that the models have similar copy number alterations to their clinical counterparts. Several consistent copy number changes not reported previously were found (e.g., gain at 22q11.21 that was observed in 5 of 7 glioblastoma samples, loss at 16q22.3 that was observed in 5 of 9 Ewing's sarcoma and 4 of 12 rhabdomyosarcoma models, and amplification of 21q22.3 that was observed in 5 of 7 osteosarcoma models). We then asked whether changes in copy number were reflected by coordinate changes in gene expression. We identified 493 copy number-altered genes that are nonrandom and appear to identify histotype-specific programs of genetic alterations. Conclusions: These data indicate that the preclinical models accurately recapitulate expression profiles and genetic alterations common to childhood cancer, supporting their value in drug development.

Original languageEnglish (US)
Pages (from-to)4572-4583
Number of pages12
JournalClinical Cancer Research
Issue number14
StatePublished - Jul 15 2008
Externally publishedYes

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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