Dataset Information

HPV16 and HPV18 type-specific APOBEC3 and integration profiles in different diagnostic categories of cervical samples.

ABSTRACT: Human papillomavirus (HPV) 16 and 18 are the most predominant types in cervical cancer. Only a small fraction of HPV infections progress to cancer, indicating that additional factors and genomic events contribute to the carcinogenesis, such as minor nucleotide variation caused by APOBEC3 and chromosomal integration. We analysed intra-host minor nucleotide variants (MNVs) and integration in HPV16 and HPV18 positive cervical samples with different morphology. Samples were sequenced using an HPV whole genome sequencing protocol TaME-seq. A total of 80 HPV16 and 51 HPV18 positive samples passed the sequencing depth criteria of 300× reads, showing the following distribution: non-progressive disease (HPV16 n = 21, HPV18 n = 12); cervical intraepithelial neoplasia (CIN) grade 2 (HPV16 n = 27, HPV18 n = 9); CIN3/adenocarcinoma in situ (AIS) (HPV16 n = 27, HPV18 n = 30); cervical cancer (HPV16 n = 5). Similar numbers of MNVs in HPV16 and HPV18 samples were observed for most viral genes, with the exception of HPV18 E4 with higher numbers across clinical categories. APOBEC3 signatures were observed in HPV16 lesions, while similar mutation patterns were not detected for HPV18. The proportion of samples with integration was 13% for HPV16 and 59% for HPV18 positive samples, with a noticeable portion located within or close to cancer-related genes.

SUBMITTER: Lagstrom S

PROVIDER: S-EPMC8287217 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background/objectiveHuman papillomavirus (HPV) genotyping and cytology have been recommended for colposcopy triage, but it is unclear which combinations of high-risk HPV (hrHPV) types and cytology with various thresholds provide clinically useful information for the triage after primary HPV screening on self-collected samples.MethodChinese Multi-site Screening Trial (CHIMUST) database focused on self-collected samples was reviewed using the results of Cobas4800 HPV assay. Absolute risks of each genotype for cervical intraepithelial neoplasia 2 or worse/ 3 or worse (CIN2+/CIN3+) were calculated. Triage of atypical squamous cells of undetermined significance (ASCUS) or worse cytology was used as the comparator, and diagnostic accuracy for paired comparisons between algorithms was obtained using McNemar's test.ResultsA total of 10, 498 women were included, the overall prevalence of hrHPV, HPV16, HPV18, and Other hrHPV genotypes were 13.7%, 2.4%, 0.8%, and 10.5%, respectively. HPV16-positive women had the highest absolute risk among various genotypes for CIN2+/CIN3+ whether in normal or abnormal cytology (ASCUS or worse) and among all age groups. When compared with the comparator, combining HPV16 positivity and/or high-grade squamous intraepithelial lesion (HSIL) or worse yielded higher specificity (97.7% vs. 97.0%, p<0.0001), similar sensitivity (90.7% vs. 96.3%, p = 0.256) for detection of CIN3+, and a decrease in colposcopy referral rate from 3.5% to 2.7%, similar results were found for CIN2+. Positivity for HPV16 and/or (ASCUS or worse), and positivity for (HPV16 and/or HPV18) and/or (ASCUS or worse) achieved favorable sensitivity compared with the comparator (80.6% and 81.3% vs. 70.1% respectively for CIN2+, p<0.0001; both 96.3% vs. 96.3% for CIN3+, p = 1.000), these algorithms would reduce the colposcopy referral rate to 5.0% and 5.6% respectively, compared with 13.7% of that for HPV alone.ConclusionsTriage of HPV-positive women on self-collected samples by combining HPV16 or HPV16/18 genotyping with different thresholds of cytology could provide tradeoffs in sensitivity for detecting cervical lesions and colposcopy referral rates, and tailor management in various circumstances of clinical practice.

Dataset Information

HPV16 and HPV18 type-specific APOBEC3 and integration profiles in different diagnostic categories of cervical samples.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets