1 research outputs found
Retrospective analysis of alphaâhuman papillomavirus (HPV) types in tissue samples from anogenital dysplasias â introduction of the RICH (Risk of HPVârelated Carcinoma in HIV+/â patients) score
Background
Chronic viral infections caused by highly contagious human papillomaviruses (HPVs) from the alpha genus are a substantial risk factor for tumour diseases.
Objectives
The goal of this study was to compare the HPV infection pattern with histology in a patient group of immunocompromised HIV+ and nonâimmunocompromised patients with anal intraepithelial neoplasia.
Materials and Methods
Tissue samples (n = 210) from the anogenital area of 121 patients underwent retrospective histological and molecular examination for HPV DNA prevalence by chip analysis. The study was part of a cancer screening from the Dermatology Department of the LMU Munich, Germany. All data were collected and processed anonymously.
Results
HPV 6 or 11 are more abundant in tissue samples from histologically diagnosed condylomata acuminata (47.7%) compared to grade 1, 2, and 3 intraepithelial neoplasias (IN 1â3). Detection of highârisk (hr) alphaâHPV DNA was significantly higher in tissue samples from IN 3 (67.5%) compared to IN 1 and 2 (12.9%), and compared to condylomata acuminata (29.5%). No HPV types were detected in histologically unremarkable tissue samples. There was a significant association between the prevalence of HPV 16 and the classifications IN 1 to IN 3 (Ï2 (2) = 13.62, P = 0.001). We identified a significant correlation between the prevalence of highârisk and lowârisk (lr) HPV types and HIV, especially mixed infections of different HPV types correlated with highâgrade IN. Based on the present data, we suggest the risk of carcinoma in HIV+/â patients (RICH) score and test it in the 121 patients.
Conclusions
hr alphaâHPVs, mainly HPV 16, are associated with increased oncogenic potential of premalignant lesions (IN 1â3), especially in HIV+ patients. Based on the combination of HIV/HPVâtesting and histological analysis, we identified correlations that could potentially forecast the risk of malignant transformation and summarized them in the form of RICH score