HPV16 RNA patterns defined by novel high-throughput RT-qPCR as triage marker in HPV-based cervical cancer precursor screening

• To triage HPV16 DNA-positive women by transformation-specific viral RNA patterns we developed RT-qPCR for E6*I, E1^E4 and E1C.
• 85% of 58 ≤ CIN1 samples were correctly identified as advanced lesion-negative and 90% of 59 ≥ CIN3 samples as positive.
• 3 of 4 RNA patterns-positive initial ≤ CIN1 lesions 5-24 months later had progressed to ≥ CIN2.

ObjectiveCervical cancer precursor screening by HPV testing has a low positive predictive value for advanced lesion. HPV16 RNA patterns characteristic for HPV16-transformed cells but based on laborious, cost-intensive singleplex NASBA reactions promised high value in triaging HPV16 DNA-positive women.MethodsWe developed two high-throughput reverse transcriptase quantitative (RT-q) PCR assays for the HPV16 transcripts E6*I, E1^E4 and E1C and the cellular transcript ubiquitin C and analysed RNA of 158 singly HPV16 DNA-positive cervical cell samples archived in PreservCyt buffer for the presence of transformation-associated HPV16 RNA patterns, i.e., upregulation of E6*I relative to E1^E4 and/or presence of E1C.ResultsHPV16 RNA pattern analyses classified 85% of 58 samples diagnosed ≤ CIN1 (no cytologically and histologically detectable cervical lesion or CIN grade 1) as negative and 90% of 59 samples diagnosed as ≥ CIN3 (CIN grade 3 or invasive cancer) as positive. Among 41 CIN grade 2 samples representing an intermediate lesion group, 49% were HPV16 RNA patterns-positive. Interestingly, 3 of 4 HPV16 RNA patterns-positive lesions initially diagnosed as ≤ CIN1 at follow-up 5–24 months later had progressed to ≥ CIN2.ConclusionsWe successfully developed and validated a second generation of HPV16 RNA patterns assay by rapid RT-qPCR as triage marker for HPV16 DNA-positive women offering clinical utility to distinguish between the need for immediate colposcopy and continued observation. Limited follow-up data suggests that HPV16 RNA patterns-positivity in ≤ CIN1 lesions can predict disease progression.