Human papillomavirus and cervical cancer: biomarkers for improved prevention efforts

Abstract

While organized screening programs in industrialized countries have significantly reduced cervical cancer incidence, cytology-based screening has several limitations. Equivocal or mildly abnormal Pap tests require costly retesting or diagnostic work-up by colposcopy and biopsy. In low-resource countries, it has been difficult to establish and sustain cytology-based programs. Advances in understanding human papillomavirus biology and the natural history of human papillomavirus-related precancers and cancers have led to the discovery of a range of novel biomarkers in the past decade. In this article, we will discuss the potential role of new biomarkers for primary screening, triage and diagnosis in high-resource countries and their promise for prevention efforts in resource constrained settings.

Figures

Figure 1. Human papillomavirus natural history and cellular and viral biomarkers used in cervical cancer screening

HPV infection happens shortly after sexual initiation. Most infections clear spontaneously, but a few carcinogenic HPV infections may persist and initiate oncogenic changes in epithelial cells at the cervical transformation zone. In a small fraction of cases, these persistent abnormalities may progress to invasive cervical cancer in the absence of early detection and treatment. Viral and cellular biomarkers indicating key steps of the functional progression model (HPV infection, precancer and invasive cancer) have been discovered, with some currently in early discovery stages, while others have already been commercialized. HPV: Human papillomavirus.

Figure 2. Graphical representation of the range of estimates of sensitivity and specificity of studies evaluating commercially available biomarkers at the cervical intraepithelial neoplasia grade 2+ threshold

The sensitivity ranges are plotted along the y-axis and specificity along the x-axis. The median values of the range of estimates of sensitivity and specificity are used as the points of convergence of the sensitivity and specificity range lines. The circles around each graph reflect the combined total number of samples used in the studies that were summarized. This graphical representation does not weigh the studies by sample size, and the median value does not reflect a computed summary/pooled measure. The purpose of this graph is to visualize the wide range of performance estimates reported in studies evaluating these biomarkers. The heterogeneity is related to various factors, including but not limited to differences in targeted populations, differences in clinical end points and heterogeneity of biomarker performance.