Skip to main content

Sampling strategies for tissue microarrays to evaluate biomarkers in ovarian cancer.

Publication ,  Journal Article
Permuth-Wey, J; Boulware, D; Valkov, N; Livingston, S; Nicosia, S; Lee, J-H; Sutphen, R; Schildkraut, J; Narod, S; Parker, A; Coppola, D ...
Published in: Cancer Epidemiol Biomarkers Prev
January 2009

INTRODUCTION: Tissue microarrays (TMA) enable rapid analysis of biomarkers in large-scale studies involving archival tumor specimens, however, their utility in heterogeneous tumors such as ovarian cancer is limited. METHODS: In this study, immunohistochemical analysis was done on TMAs comprised of epithelial ovarian cancer (EOC) to estimate the prevalence of loss of expression of three mismatch repair proteins. TMAs were initially created using cores sampled from the center of donor tissue blocks from 59 EOC cases. Full sections were subsequently created and levels of expression were compared between tissues sampled from the central portion versus the periphery. Follow-up analyses were done by obtaining cores from the periphery of up to five additional donor blocks per case. A linear mixed model for each protein was used to investigate differences between results from the initial and follow-up blocks. RESULTS: In the original TMAs created using centrally sampled cores, loss of mismatch repair expression was noted in 17 (29%) of the 59 cases. By comparison, analyses from peripherally sampled cores revealed loss of expression in only 6 of these 17 cases. For each protein, significant differences (P < 0.05) were detected between results from the initial donor block and the majority of the follow-up blocks. CONCLUSIONS: Our investigations, based on EOC, suggest that sampling variability in protein expression may result when TMAs are used. Thus, at least for EOC, it is important to preferentially sample from the periphery of tumor blocks where exposure to tissue fixatives is optimal.

Duke Scholars

Published In

Cancer Epidemiol Biomarkers Prev

DOI

ISSN

1055-9965

Publication Date

January 2009

Volume

18

Issue

1

Start / End Page

28 / 34

Location

United States

Related Subject Headings

  • Population Surveillance
  • Ovarian Neoplasms
  • Oligonucleotide Array Sequence Analysis
  • Middle Aged
  • Linear Models
  • Immunohistochemistry
  • Humans
  • Florida
  • Female
  • Epidemiology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Permuth-Wey, J., Boulware, D., Valkov, N., Livingston, S., Nicosia, S., Lee, J.-H., … Pal, T. (2009). Sampling strategies for tissue microarrays to evaluate biomarkers in ovarian cancer. Cancer Epidemiol Biomarkers Prev, 18(1), 28–34. https://doi.org/10.1158/1055-9965.EPI-08-0713
Permuth-Wey, Jenny, David Boulware, Nikola Valkov, Sandra Livingston, Santo Nicosia, Ji-Hyun Lee, Rebecca Sutphen, et al. “Sampling strategies for tissue microarrays to evaluate biomarkers in ovarian cancer.Cancer Epidemiol Biomarkers Prev 18, no. 1 (January 2009): 28–34. https://doi.org/10.1158/1055-9965.EPI-08-0713.
Permuth-Wey J, Boulware D, Valkov N, Livingston S, Nicosia S, Lee J-H, et al. Sampling strategies for tissue microarrays to evaluate biomarkers in ovarian cancer. Cancer Epidemiol Biomarkers Prev. 2009 Jan;18(1):28–34.
Permuth-Wey, Jenny, et al. “Sampling strategies for tissue microarrays to evaluate biomarkers in ovarian cancer.Cancer Epidemiol Biomarkers Prev, vol. 18, no. 1, Jan. 2009, pp. 28–34. Pubmed, doi:10.1158/1055-9965.EPI-08-0713.
Permuth-Wey J, Boulware D, Valkov N, Livingston S, Nicosia S, Lee J-H, Sutphen R, Schildkraut J, Narod S, Parker A, Coppola D, Sellers T, Pal T. Sampling strategies for tissue microarrays to evaluate biomarkers in ovarian cancer. Cancer Epidemiol Biomarkers Prev. 2009 Jan;18(1):28–34.

Published In

Cancer Epidemiol Biomarkers Prev

DOI

ISSN

1055-9965

Publication Date

January 2009

Volume

18

Issue

1

Start / End Page

28 / 34

Location

United States

Related Subject Headings

  • Population Surveillance
  • Ovarian Neoplasms
  • Oligonucleotide Array Sequence Analysis
  • Middle Aged
  • Linear Models
  • Immunohistochemistry
  • Humans
  • Florida
  • Female
  • Epidemiology