Coinfections by multiple Human Papillomaviruses (HPVs) are observed in approximately 6-8% of invasive cervical cancer (ICC) cases worldwide. But neither the presence of persistent HPVs coinfections nor their etiological role in the development of ICC is well understood. Cervical HPVs coinfections have been observed randomly, mostly in women with preneoplastic lesions, and only few studies have globally analyzed ICC cases. Here we explored the HPVs multiple infection patterns in a large worldwide sample of cross-sectional ICC cases. Paraffin-embedded ICC biopsy samples were tested using stringent HPV genotyping. Logistic regression models were used to identify the most likely pairwise HPV types in multiple infections. Multivariate analysis was applied to detect significant HPV coinfection patterns beyond pairwise HPVs comparison. Among 8780 HPV DNA-positive ICC cases worldwide, 6.7% (N = 587) contained multiple HPVs. Pairwise analysis revealed that HPV16|74, HPV31|33, HPV31|44, HPV33|44 and HPV45|70 pairs were significantly more frequently found together in multiple infections compared to any other HPV type combination, which supports the occasional role of Alpha-10 LR-HPVs in cervical cancers. In contrast, HPV16|31, HPV16|45, HPV16|51 and HPV18|HPV45 pairs were significantly less frequently found together than with any other HPV pair combination. Multivariate analysis sustained the results and revealed for the first time a distinct coinfection pattern in African ICCs stemming from the clustering of oncogenic HPV51/35/18/52 coinfections in African women. We suggest that the differential geographic HPVs coinfections clustering observed might be compatible with a specific modulation of the natural history/oncogenic potential of particular HPVs multiple infections and warrant monitoring for post-vaccinated.
Keywords: geographic clustering; invasive cervical cancer; multiple HPVs infections.
© 2018 UICC.