The effectiveness of cervical screening programs is hampered by suboptimal participation rates. Offering cervicovaginal self-sampling for high-risk HPV (hrHPV) testing has been shown to increase the participation. Since only a minority of hrHPV-positive women is at risk of cervical cancer, further stratification (triage) is needed to avoid overtreatment. MicroRNAs (miRNAs) represent a potential class of triage markers and their deregulation has been implicated in cervical cancer. At present, little is known about genome-wide miRNA expression patterns in cervical precancerous lesions (CIN3) and, most importantly, it is unknown whether deregulated miRNA expression is detectable in self-samples. In this study we set out to determine genome-wide miRNA profiles in hrHPV-positive self-samples in order to identify miRNAs detectable in self-samples that can predict the presence of CIN3 and cervical cancer.
Small RNA sequencing (sRNA-Seq) was conducted to determine genome-wide miRNA expression profiles in 77 hrHPV-positive self-samples (36 of women without cervical disease during follow-up (≤CIN1), 37 of women with CIN3 lesions, and 4 of women with squamous cervical carcinomas (SCC)). Logistic regression analysis was performed to identify the best miRNA panel with the highest combined sensitivity and specificity for CIN3 detection. Candidate miRNAs were validated by qPCR in an independent cohort of 164 hrHPV-positive self-samples (101 ≤CIN1, 49 CIN3, 14 cervical cancers).
Classification of sRNA-Seq data resulted in the identification of 8 differentially expressed miRNAs with an area under the curve (AUC) of 0.89 for CIN3 detection. Six out of eight miRNAs could be validated in an independent self-sample series by qPCR, showing that CIN3 and cervical cancer associated miRNAs can be detected in hrHPV-positive self-samples.
This study is the first to determine genome-wide miRNA profiles in self-samples and reveals that miRNA expression analysis offers a promising novel molecular strategy for CIN3 and cervical cancer detection in hrHPV-positive self-samples. Moreover, our small RNA-Seq data will lead to a better understanding of the contribution of miRNA diversification in cervical carcinogenesis.