Validation and use of a model system to investigate topical treatment of vulval intraepithelial neoplasia

The aims of this study were to develop novel in vitro models of Human Papillomavirus (HPV) -associated vulval and vaginal neoplasia and to use them to investigate the mechanism(s) of action of the nucleoside analogue, Cidofovir (CDV), for which a mechanism is unknown. Single cell clones were successfully isolated from heterogeneous vulval and vaginal parental populations. The clonal cell lines were characterised morphologically and in terms of cell proliferation; a range of growth rate and morphological variants were identified. Clonal lines were also characterised with respect to HPV integration state using Amplification of Papillomavirus Oncogene Transcripts (APOT) and Detection of Integrated Papillomavirus Sequences (DIPS). Cell lines were identified that represented naturally occurring episomal and integrated HPV infections. HPV gene expression analysis was also performed using quantitative real-time reverse transcription PCR (qRT-PCR) which displayed different expression profiles for each line. Patterns of HPV gene expression appeared to correlate with gene disruptions associated with integration. Characterised clonal lines were used to investigate the effects of CDV on cell viability, morphology and HPV gene expression. CDV (10 μM) reduced cell viability in all HPV-positive clonal lines and HPV negative HEK cells; viable cell counts showed that a more considerable response was detected in vulval lines compared to vaginal lines and that response in HEK lines was similar to vulval lines. Cell enlargement was observed in response to treatment in the clonal lines but not the HEK line. CDV treatment did not cause significant reduction in expression of HPV E6 or E7. mRNA sequencing confirmed HPV integration and gene expression profiles. Differentially Expressed Gene (DEG) analysis identified a large percentage of the top 20 most significant Gene Ontology (GO) categories to be involved in nucleotide synthesis and RNA polymerase activity. Gene Ontology Over Representation Analysis (GO-ORA) showed that 4 GO categories relating to cellular senescence were found in over 300 GO categories comprising the top 500 most significant gene transcripts