Flow Cytometric Analysis of DNA Ploidy in Liquid Based Cytology for Cervical Pre-Cancer and Cancer

Mishra, Sridhar; Awasthi, Namrata; Husain, Nuzhat; Anand, Akansha; Pradeep, Yahodhara; Ansari, Roohi; Saxena, Sarita

doi:10.22034/APJCP.2017.18.6.1595

Flow Cytometric Analysis of DNA Ploidy in Liquid Based Cytology for Cervical Pre-Cancer and Cancer

Document Type : Research Articles

Authors

¹ Department of Pathology, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhuti Khand, Gomti Nagar, Lucknow, India.

² Department of Obestrics and Gynaecology, Queen Merry Hospital, King George Medical University, Lucknow, UP, India.

³ Department of Bioengineering, Integral University, Lucknow, UP, India.

⁴ Department of Obestrics and Gynaecology, Ram Manohar Lohia Combined Hospital, Lucknow, UP, India.

10.22034/APJCP.2017.18.6.1595

Abstract

Background: DNA ploidy analysis of cervical intraepithelial neoplasia (CIN) and invasive cervical cancer samples by flow cytometry (FCM) has been established as an aid to prognostic assessment. Liquid based cytology (LBC) increases diagnostic specificity by using ancillary techniques that provide information beyond morphology. The present study was undertaken to assess DNA ploidy in LBC samples as an adjunct for early detection of cervical pre-cancer and cancer. Methods: DNA ploidy assessment was performed on LBC samples of 50 cases and 31 controls. Cell pellets were obtained by centrifugation and stained with Telford reagent. At least 20,000 R1 gate (G0-G1) events were acquired on a BD FACSCalibur by using a 575±10 nm filter. Results: Mean diploid G1 values were lowered significantly (p<0.01) while diploid S values were significantly elevated (p<0.01) in both high grade squamous intraepithelial lesions (HSILs) and squamous cell carcinomas (SCCs) as compared to controls. Receiver operating curve (ROC) analysis of the diploid G1 value was found to have significant diagnostic potential (AUC=0.682, Z=2.00, p=0.046) for distinction between control and low grade squamous intraepithelial lesion (LSIL) at a cut off value of ≤91.6 with a sensitivity and specificity of 50.0 and 87.1%, respectively. Conclusions: ROC analysis of diploid G1 and diploid S values allows discrimination between LSIL and HSIL with sensitivities and specificities of 65 and 100% and 70 and100%, respectively, and between LSIL and SCC cases with values of 71.4 and 100% and 64.3 and 100%, respectively.

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