Human papillomaviruses: Diseases, diagnosis, and a possible vaccine

Human papillomavirus and oral disease - emerging evidence: a review

Human papillomavirus (HPV) infections have received considerable attention in recent years. Of the 120 or so known types of the virus, some cause a variety of benign wart-like lesions of the skin and genital and oral mucosae, whilst others are aetiologically associated with cervical and anogenital cancers. Recent epidemiologic evidence suggests that HPV may also be an independent risk factor for oropharyngeal cancer. In this context it has been suggested that HPV virus may modulate the process of carcinogenesis in some tobacco and alcohol induced oropharyngeal cancers and act as the primary oncogenic agent for inducing carcinogenesis among non-smokers. Dental practitioners have a major role in detecting all lesions of the oral mucosa caused, or possibly caused, by HPV. This paper briefly reviews the current state of knowledge of molecular and clinical aspects of HPV infections of the oral mucosa.

Zinc finger arrays binding human papillomavirus types 16 and 18 genomic DNA: precursors of gene-therapeutics for in-situ reversal of associated cervical neoplasia

Background

Human papillomavirus (HPV) types 16 and 18 are the high-risk, sexually transmitted infectious causes of most cervical intraepithelial neoplasias (CIN) or cancers. While efficacious vaccines to reduce the sexual acquisition of these high-risk HPVs have recently been introduced, no virus-targeted therapies exist for those already exposed and infected. Considering the oncogenic role of the transforming (E6 and E7) genes of high-risk HPVs in the slow pathogenesis of cervical cancer, we hypothesize that timely disruption or abolition of HPV genome expression within pre-cancerous lesions identified at screening may reverse neoplasia. We aimed to derive model zinc finger nucleases (ZFNs) for mutagenesis of the genomes of two high-risk HPV (types 16 & 18).

Methods and results

Using ZiFiT software and the complete genomes of HPV types16 and 18, we computationally generated the consensus amino acid sequences of the DNA-binding domains (F1, F2, & F3) of (i) 296 & 327 contextually unpaired (or single) three zinc-finger arrays (sZFAs) and (ii) 9 & 13 contextually paired (left and right) three- zinc-finger arrays (pZFAs) that bind genomic DNA of HPV-types 16 and 18 respectively, inclusive of the E7 gene (s/pZFA_HpV/E7). In the absence of contextually paired three-zinc-finger arrays (pZFAs) that bind DNA corresponding to the genomic context of the E6 gene of either HPV type, we derived the DNA binding domains of another set of 9 & 14 contextually unpaired E6 gene-binding ZFAs (sZFA_E6) to aid the future quest for paired ZFAs to target E6 gene sequences in both HPV types studied (pZFA_E6). This paper presents models for (i) synthesis of hybrid ZFNs that cleave within the genomic DNA of either HPV type, by linking the gene sequences of the DNA-cleavage domain of the FokI endonuclease F_N to the gene sequences of a member of the paired-HPV-binding ZFAs (pZFA_HpV/E7 + F_N), and (ii) delivery of the same into precancerous lesions using HPV-derived viral plasmids or vectors.

Conclusions

With further optimization, these model ZFNs offer the opportunity to induce target-mutagenesis and gene-therapeutic reversal of cervical neoplasia associated with HPV types 16 & 18.

Classification of cervical cancer cells using FTIR data

High false-negative rates of the Papanicolauo (so-called 'Pap') smear test and the shortage of colposcopists have led to the desire to find alternative non-expert (automated) approaches for accurately testing cervical smears for signs of cancer. Fourier-Transform Infra-Red (FTIR) spectroscopy has been shown to offer the potential for improving the accuracy (i.e. sensitivity and specificity) of these tests. This paper details the application of the machine learning methodology of Support Vector Machines (SVM) using FTIR data to enhance and improve upon the standard Pap test. A cohort of 53 subjects was used to test the veracity of both the Pap smear results and the FTIR based classifier against the findings of the colposcopists. The Pap test achieved an overall classification of 43 %, whereas our method achieved a rate of 72%