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Exploring the dynamics and interplay of human papillomavirus and cervical tumorigenesis by integrating biological data into a mathematical model.

AbstractBACKGROUND:
Cervical cancer is the fourth most common tumor in women worldwide, mostly resulting from high-risk human papillomavirus (HR-HPV) with persistent infection.
RESULTS:
The present discoveries are comprised of the following: (i) A total of 16.64% of the individuals were positive for HR-HPV infection, with 13.04% having a single HR-HPV type and 3.60% having multiple HR-HPV types. (ii) Cluster analysis showed that the infection rate trends of HPV31 and HPV33 in all infections as well as HPV33 and HPV35 in single infections in precancerous stages were very similar. (iii) The single/multiple infection proportions of HR-HPV demonstrated a trend that the multiple infections rates of HR-HPV increased as the disease developed.
CONCLUSIONS:
The HR-HPV prevalence in outpatients was 16.64%, and the predominant HR-HPV types in the study were HPV52, HPV58 and HPV16. HR-HPV subtypes with common biological properties had similar infection rate trends in precancerous stages. Especially, as the disease development of precancer evolved, defense against HPV infection broke, meanwhile, the potential of more HPV infection increased, which resulted in increase of multiple infections of HPV.
AuthorsWenting Wu, Lei Song, Yongtao Yang, Jianxin Wang, Hongtu Liu, Le Zhang
JournalBMC bioinformatics (BMC Bioinformatics) Vol. 21 Issue Suppl 7 Pg. 152 (May 05 2020) ISSN: 1471-2105 [Electronic] England
PMID32366259 (Publication Type: Journal Article)
Topics
  • Carcinogenesis
  • Cell Transformation, Viral
  • Female
  • Humans
  • Models, Biological
  • Papillomaviridae
  • Papillomavirus Infections (complications, epidemiology)
  • Prevalence
  • Uterine Cervical Neoplasms (etiology, pathology)

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