1. Detection of human telomerase gene (TERC) amplification in cervical neoplasia: A retrospective study of 79 patients Pap smear slides Renarta Crookes Sheffield Children's NHS Foundation Trust

2. Cervical Cancer Papanicolou test reduced mortality rate Papanicolou test reduced mortality rate 40,000 cases of mild/moderate dyskaryosis sent for further investigation 40,000 cases of mild/moderate dyskaryosis sent for further investigation HPV 16 or 18 accounts for 70% of cervical cancer, majority of mild regress HPV 16 or 18 accounts for 70% of cervical cancer, majority of mild regress

3. CGH – Amplification of TERC  CGH – 85% 3q26 TERC 3q26 The RNA component of the human telomerase The RNA component of the human telomerase 3q gain in interphase 3q gain in interphase FISH as an indicator FISH as an indicator of disease progression? of disease progression?

4. Categorisation of Smears Negative Negative Low Grade Low Grade Mild dyskaryosis means the outer 1/3 of the cervix is affected Mild dyskaryosis means the outer 1/3 of the cervix is affected High Grade High Grade Moderate dyskaryosis means up to 2/3 of the skin thickness is affected Moderate dyskaryosis means up to 2/3 of the skin thickness is affected CIN3 means the full thickness of the cervical skin is affected CIN3 means the full thickness of the cervical skin is affected

5. TERC – A new diagnostic marker? TERC gain is required for, and predicts, progression from mild/moderate dyskaryosis to CIN3  TERC gain is required for, and predicts, progression from mild/moderate dyskaryosis to CIN3  TERC gain observed in 33% of negative Pap smears that progressed to CIN3  100% of mild/moderate cases that regressed did not show TERC gains Heselmeyer-Haddad et al., 2005. Am J. Pathol. 166 1229-1238

6. The Present Study Aim – Can FISH for TERC copy number be used to improve the current system for cervical smear screening? Aim – Can FISH for TERC copy number be used to improve the current system for cervical smear screening? TERC 3q26 C-MYC 8q24 79 retrospective cases  79 retrospective cases  Negative, mild or moderate progressing to CIN3 or cervical cancer  Negative, mild or moderate regressing or remaining negative

7. Results- Negative progressing to CIN3 Normal diploid cell Increase in TERC copy number x100 x40

8. Results- Negative progressing to CIN3

9. Results- Mild progressing to CIN3 Increase in TERC Increase in C-MYC

10. Results- Mild progressing to CIN3

11. Results- Moderate progressing to CIN3  82.4% moderate cases showed gain of TERC  70.6% moderate cases showed gain of C-MYC

12. Results- Moderate progressing to CIN3

13. Summary of Progressors

14. Results- Negative remaining Negative

15. Results- Mild regressing to negative

16. Results- Moderate regressing to negative

17. Regressors Negative and mild dyskaryosis patients that regressed or remained negative showed no gains in TERC 2/8 patients classed as moderate dyskaryosis showed gains of TERC, with a high proportion of tetraploid cells.

18. Summary of Regressors

19. Study Summary 90 cases received 90 cases received 79 successful analyses 79 successful analyses 2 insufficient sample to score (min no. cells to score?) 2 insufficient sample to score (min no. cells to score?) 5 fails in progressors (thick smears) 5 fails in progressors (thick smears) 4 fails in regressors (from 2000 - ?bond) 4 fails in regressors (from 2000 - ?bond)

20. Application as a service Analysis of slides ranges from 30 mins to over an hour by eye per analyser Analysis of slides ranges from 30 mins to over an hour by eye per analyser Automation – Scanning, Capture + Relocation Automation – Scanning, Capture + Relocation Liquid based cytology slides – reducing cell clumping/false positive rate, no de-staining Liquid based cytology slides – reducing cell clumping/false positive rate, no de-staining

21. Conclusions TERC increases with severity of disease TERC increases with severity of disease Both negative and mild dyskaryosis regressors showed no gains in TERC Both negative and mild dyskaryosis regressors showed no gains in TERC Prospective work using liquid based cytology slides Prospective work using liquid based cytology slides Trial automation to reduce analysis Trial automation to reduce analysis Improve detection rate and reduce costs and patient anxiety Improve detection rate and reduce costs and patient anxiety

22. Acknowledgments Dr John H F Smith (Dept. of Histopathology, Royal Hallamshire Hospital) Dr John H F Smith (Dept. of Histopathology, Royal Hallamshire Hospital) Michael Dyson (Sheffield Cytogenetics Service) Michael Dyson (Sheffield Cytogenetics Service) Dr Edna L. Maltby (Sheffield Cytogenetics Service) Dr Edna L. Maltby (Sheffield Cytogenetics Service) Abbott Vysis Abbott Vysis