Introduction: In early cervical cancer (EEC), 10 to 15% of patients without nodal metastasis (N-) will suffer from recurrences with further similar survival as N+ patients. However, no clinical, imaging or pathological risk-factor is today available to identify them. In the present study, we hypothesized that the N- histologically characterized patients who present a poor prognosis could be patients for whom metastasis are missed by classical procedure. Therefore, we propose to research HPV tumoral DNA (HPVtDNA) in pelvic Sentinel Lymph Nodes (SLN) biopsy using ultrasensitive droplet-based digital PCR (ddPCR) to detect eventual occult metastasis.
Materials and methods: Sixty HPV16, HPV18 or HPV33 positive EEC N- patients with available SLN were included. In SLN, HPV16 E6, HPV18 E7 and HPV33 E6 gene were respectively detected using ultrasensitive ddPCR technology. Survival data were analysed using Kaplan-Meier-curves and log-rank-test to compare progression-free survival (PFS) and disease-specific survival (DSS) in two groups according to their HPVtDNA status in SLN.
Results: More than half (51.7%) of the patients finally showed HPVtDNA positivity in SLN initially diagnosed as negative by histology. Two patients with negative HPVtDNA SLN and 6 with positive HPVtDNA SLN group presented recurrence. Finally, all of the 4 deaths listed in our study occurred in the positive HPVtDNA SLN group.
Conclusion: These observations hint that the use of ultrasensitive ddPCR to detect HPVtDNA in SLN could allow the identification of two subgroups of histologically N- patients that may have different prognosis and outcome. To our knowledge, our study is the first one to evaluate the detection of HPVtDNA in SLN in early cervical cancer using ddPCR highlighting its interest as a complementary tool for N- specific early cervical cancer diagnosis.
Keywords: Droplet-based digital PCR; HPV tumoral DNA; N- early cervical cancer; New prognosis biomarker; Sentinel lymph nodes.
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