In an attempt to determine whether the fluorescent in situ hybridization (FISH) can be used as a rapid approach for the identification of aneuploidy in premalignant cervical smears, a centromeric probe for chromosome 1 was used. The results from the FISH experiments were compared with measurements of the overall DNA content obtained by means of an image analysis system. With progression to neoplasia, a decrease of the frequency of cells with two spots was observed, due to an increasing polysomy of chromosome 1. As far as the DNA content was concerned, an increasing DNA index and 5C-exceeding ratio (fraction of cells with a DNA content higher than 5C) was observed. Classification of the FISH results by a linear discriminant analysis revealed that 67.6% of the cases were classified in agreement with the CIN classification. These data suggest that chromosome I may be considered as a marker chromosome for pre-malignant cervical lesions and that the DNA content measurements are complementary to the FISH results.

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Background: Resistance testing is increasingly accepted as a tool in guiding the selection of human immunodeficiency virus type 1 (HIV-1) antiretroviral therapy in HIV-1 infected individuals who fail their current regimen. Objectives: To descriptively compare the correlation between virologic treatment response and results using three genotypic HIV-1 drug resistance interpretation systems: the VERSANT ® HIV-1 Resistance Assay (LiPA) system and two sequence-based interpretation systems. Study design: Specimens from 213 HIV-1-infected subjects, either starting (n = 104) or switching to (n = 109) a regimen of three or four anti retroviral drugs, were collected retrospectively at baseline and after 3 months of uninterrupted therapy. The correlation between viral load change and the number of predicted active drugs in the treatment regimen was assessed. An interpretation algorithm was recently developed to process VERSANT ® HIV-1 Resistance Assay (LiPA) data. The number of active drugs predicted using this algorithm was rank correlated with the viral load change over a 3-month treatment period. For comparison, a similar calculation was made using two sequence-based algorithms (REGA version 5.5 and VGI GuideLines™ Rules 4.0), both applied on the same sequences. Results: Statistically significant (p<0.05) correlation coefficients for each of the three HIV-1 drug resistance interpretation systems were observed in the treatment-experienced subjects on a 3-drug regimen (-0.39, -0.38, and -0.42, respectively) as well as on a 4-drug regimen (-0.33, -0.31, and -0.37, respectively). However, no significant correlation was observed in treatment-naïve subjects, probably due to the very low frequency of drug resistance in these subjects. Conclusion: All three genotypic drug resistance interpretation systems (LiPA version 1, REGA version 5.5, and VGI GuideLines™ Rules 4.0) were statistically significantly correlated with virologic therapy response as measured by viral load testing.

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