title: Detection of allelic imbalance in ascitic supernatant by digital single nucleotide polymorphism analysis.
abstract: OBJECTIVE
  Cytological examination of ascitic fluid is critical for clinical management of patients with peritoneal or pelvic diseases. Such morphological examination can only achieve a sensitivity of <62%, and thus a molecular test that is able to distinguish benign versus malignant ascites could be clinically useful. In this study we determined the presence of allelic imbalance (AI) in tumor-released DNA in ascitic supernatant by directly counting the alleles using a newly developed technology, digital single nucleotide polymorphism (SNP) analysis.
  
  
  METHODS
  Allelic status was assessed using a total of seven SNP markers that commonly demonstrated AI in ovarian, colorectal, and pancreatic cancers.
  
  
  RESULTS
  With digital SNP analysis, AI in at least one SNP marker was found in 19 of 20 (95%) ascitic fluid DNA samples obtained from patients with cytologically proven carcinomas in ascitic fluid. In contrast, AI was detected in only 1 of 20 patients with negative cytology. This latter patient with AI in her ascites had known stage III ovarian carcinoma at the time of cytology sampling. The ascitic specimen of this patient demonstrated the presence of carcinoma cells in culture with an identical AI pattern found in the ascitic supernatant and surgical specimen.
  
  
  CONCLUSIONS
  These findings suggest that detection of AI using digital SNP analysis can be a useful adjunct for the detection of ovarian and other types of cancer in ascitic fluid.
authors.affiliation: Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21231, USA.
authors.forename: Hsueh-Wei
authors.initials: HW
authors.lastname: Chang
authors.forename: Syed Z
authors.initials: SZ
authors.lastname: Ali
authors.forename: Sarah K R
authors.initials: SK
authors.lastname: Cho
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Kurman
authors.forename: Ie-Ming
authors.initials: IeM
authors.lastname: Shih
mesh_terms: D000483:Alleles; D001201:Ascites / Q000378:metabolism*; D014408:Biomarkers, Tumor / Q000378:metabolism*; D015179:Colorectal Neoplasms / Q000175:diagnosis / Q000235:genetics; D005260:Female; D005819:Genetic Markers; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D010051:Ovarian Neoplasms / Q000175:diagnosis / Q000235:genetics; D010190:Pancreatic Neoplasms / Q000175:diagnosis / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D012680:Sensitivity and Specificity; D012984:Software
chemical_list: D014408:Biomarkers, Tumor; D005819:Genetic Markers