Skip to main content

Sample type bias in the analysis of cancer genomes.

Publication ,  Journal Article
Solomon, DA; Kim, J-S; Ressom, HW; Sibenaller, Z; Ryken, T; Jean, W; Bigner, D; Yan, H; Waldman, T
Published in: Cancer Res
July 15, 2009

There is widespread agreement that cancer gene discovery requires high-quality tumor samples. However, whether primary tumors or cultured samples are superior for cancer genomics has been a longstanding subject of debate. This debate has recently become more important because federally funded cancer genomics has been centralized under The Cancer Genome Atlas, which has chosen to focus exclusively on primary tumors. Here, we provide a data-driven "perspective" on the effect of sample type selection on cancer genomics research. We show that, in the case of glioblastoma multiforme, primary tumors and xenografts are best for the identification of amplifications, whereas xenografts and cell lines are superior for the identification of homozygous deletions. We also note that many of the most important oncogenes and tumor suppressor genes have been discovered through the use of cell lines and xenografts, and highlight the lack of published evidence supporting the dogma that ex vivo culture generates artifactual genetic lesions. Based on this analysis, we suggest that cancer genomics projects such as The Cancer Genome Atlas should include a variety of sample types such as xenografts and cell lines in their integrated genomic analysis of cancer.

Duke Scholars

Published In

Cancer Res

DOI

EISSN

1538-7445

Publication Date

July 15, 2009

Volume

69

Issue

14

Start / End Page

5630 / 5633

Location

United States

Related Subject Headings

  • Xenograft Model Antitumor Assays
  • Oncology & Carcinogenesis
  • Neoplasms
  • Humans
  • Glioblastoma
  • Genomics
  • Genome, Human
  • Gene Expression Regulation, Neoplastic
  • Gene Expression Profiling
  • Gene Deletion
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Solomon, D. A., Kim, J.-S., Ressom, H. W., Sibenaller, Z., Ryken, T., Jean, W., … Waldman, T. (2009). Sample type bias in the analysis of cancer genomes. Cancer Res, 69(14), 5630–5633. https://doi.org/10.1158/0008-5472.CAN-09-1055
Solomon, David A., Jung-Sik Kim, Habtom W. Ressom, Zita Sibenaller, Timothy Ryken, Walter Jean, Darell Bigner, Hai Yan, and Todd Waldman. “Sample type bias in the analysis of cancer genomes.Cancer Res 69, no. 14 (July 15, 2009): 5630–33. https://doi.org/10.1158/0008-5472.CAN-09-1055.
Solomon DA, Kim J-S, Ressom HW, Sibenaller Z, Ryken T, Jean W, et al. Sample type bias in the analysis of cancer genomes. Cancer Res. 2009 Jul 15;69(14):5630–3.
Solomon, David A., et al. “Sample type bias in the analysis of cancer genomes.Cancer Res, vol. 69, no. 14, July 2009, pp. 5630–33. Pubmed, doi:10.1158/0008-5472.CAN-09-1055.
Solomon DA, Kim J-S, Ressom HW, Sibenaller Z, Ryken T, Jean W, Bigner D, Yan H, Waldman T. Sample type bias in the analysis of cancer genomes. Cancer Res. 2009 Jul 15;69(14):5630–5633.

Published In

Cancer Res

DOI

EISSN

1538-7445

Publication Date

July 15, 2009

Volume

69

Issue

14

Start / End Page

5630 / 5633

Location

United States

Related Subject Headings

  • Xenograft Model Antitumor Assays
  • Oncology & Carcinogenesis
  • Neoplasms
  • Humans
  • Glioblastoma
  • Genomics
  • Genome, Human
  • Gene Expression Regulation, Neoplastic
  • Gene Expression Profiling
  • Gene Deletion