MACCD - Multifactor analysis of HPV infected cells in cervical cancer development
Cervical cancer (CC) is the 4th cancer in women worldwide and even in Europe causing ~13,000 deaths annually. Although CC screening and human papillomavirus (HPV) vaccination offer significant protection, each has specific issues. Vaccination is ineffective if administered after HPV exposure, and even if offered according to recommendations, it does not protect against all HPV types causing CC. CC screening programmes, depending on the method used, cytology or HPV testing, have either reduced sensitivity or specificity, respectively, but still have high negative predictive values and effectively reduce mortality. Positive predictive value (PPV) for detecting women at high-risk of CC development, however, remains poor, making them less efficient since large number of women are referred to costly treatments that might not be needed. Besides costs, over-treating women, often of reproductive age, incurs treatment risks as well as complications in pregnancy including miscarriage. With this project, we aim to explore a panel of 30 potentially relevant cellular markers that are likely to correlate with disease course using state-of-the-art mass cytometry profiling. The method allows parallel identification of markers on single cells using a combination of flow cytometry and mass-spectrometry analysis of heavy metal isotope labels. Women with different stages of cervical lesions (n=250) will be enrolled and followed for up to 2 years. Mass cytometry will be done on best representative 100 patients as well as CC and normal cell lines. Resulting data will be correlated with cervical lesion and viral persistence changes. Potential biomarkers will be assessed by immunocytochemistry for validation on all collected samples. Finding biomarkers with high PPV will open the way for improving the efficacy of CC screening and thus significantly alleviate socioeconomic burden of CC as well as lessen the over-treatmetnt risks for future patients.