title: Sampling strategies for tissue microarrays to evaluate biomarkers in ovarian cancer.
abstract: BACKGROUND
  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.
authors.affiliation: H. Lee Moffitt Cancer Center, Tampa, FL, USA.
authors.forename: Jenny
authors.initials: J
authors.lastname: Permuth-Wey
authors.forename: David
authors.initials: D
authors.lastname: Boulware
authors.forename: Nikola
authors.initials: N
authors.lastname: Valkov
authors.forename: Sandra
authors.initials: S
authors.lastname: Livingston
authors.forename: Santo
authors.initials: S
authors.lastname: Nicosia
authors.forename: Ji-Hyun
authors.initials: JH
authors.lastname: Lee
authors.forename: Rebecca
authors.initials: R
authors.lastname: Sutphen
authors.forename: Joellen
authors.initials: J
authors.lastname: Schildkraut
authors.forename: Steven
authors.initials: S
authors.lastname: Narod
authors.forename: Alex
authors.initials: A
authors.lastname: Parker
authors.forename: Domenico
authors.initials: D
authors.lastname: Coppola
authors.forename: Thomas
authors.initials: T
authors.lastname: Sellers
authors.forename: Tuya
authors.initials: T
authors.lastname: Pal
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000032:analysis*; D005260:Female; D005431:Florida / Q000453:epidemiology; D006801:Humans; D007150:Immunohistochemistry; D016014:Linear Models; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010051:Ovarian Neoplasms / Q000737:chemistry* / Q000453:epidemiology / Q000473:pathology; D011159:Population Surveillance
chemical_list: D015415:Biomarkers