Literature DB >> 7617654

Quantitative DNA analysis of fresh solid tumors by flow and image cytometric methods: a comparison using the Roche Pathology Workstation Image Analyzer.

D A Ellison1, S J Maygarden, D B Novotny.   

Abstract

The clinical utility of DNA ploidy and cell cycle parameters as prognostic indicators has been demonstrated for selected malignant tumors. Previous quantitative DNA analysis studies have used various tumor sample preparation methods and analyzers. We undertook a pilot study to compare the results of DNA analysis of fresh solid tumors by flow cytometry with the new Roche Pathology Workstation Image Analyzer. Flow cytometric DNA analysis was done on cell suspensions of fine needle aspirates from fresh tumor specimens and analyzed for ploidy and cell cycle statistics with a Becton-Dickinson FACScan Analyzer, using a rectangular model. Small aliquots from these same aspirates were prepared as direct cytologic smears and Feulgen stained for DNA analysis with the Roche Image Analyzer. Additional smears were stained with Diff-Quik for morphologic correlation with DNA histograms. The study group consisted of 40 malignant neoplasms. There was a high correlation between the flow and image DNA indices (R = 0.93, slope = 1.0036, P < 0.001) but a weaker relationship between the flow and image estimated S-phase fractions (R = 0.57, slope = 0.5401, P < 0.01). DNA ploidy categorization for the two methods was concordant in 30 (75%) cases, discordant in seven (17.5%) cases, and equivocal in three (7.5%) cases. In our experience, quantitative DNA analysis of fresh tumor aspirates by flow and image cytometric methods yielded comparable and/or complementary results, with each method having certain advantages and disadvantages. Proposed reasons for false and true discordances and an approach for evaluation are discussed.

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Year:  1995        PMID: 7617654

Source DB:  PubMed          Journal:  Mod Pathol        ISSN: 0893-3952            Impact factor:   7.842


  5 in total

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5.  Gross genomic damage measured by DNA image cytometry independently predicts gastric cancer patient survival.

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  5 in total

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