ArticleFrontiers in microbiology2023
Multiple HPV integration mode in the cell lines based on long-reads sequencing.
Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Comparative Evaluation of the Cytotoxic Effect of Dysphania ambrosioides Extracts Against Human Breast and Cervical Cancer Cells.Chemistry & biodiversity · 2026Article
- Dual-dimensional profiling of host genomic variations and HPV integration in PD-L1-stratified cervical cancer via Oxford Nanopore Technology.Journal of translational medicine · 2026Article
- Article
- Novel Avenues for the Detection of Cancer-Associated Viral Genome Integrations Using Long-Read Sequencing Technologies.Cancers · 2025Review
- Electrochemical Duplex Detection of E2 and E6 Genes of Human Papillomavirus Type 16 and Determination of Physical Status in High-Risk Cervical Carcinoma.Journal of medical virology · 2025Article
- Viral genome sequencing methods: benefits and pitfalls of current approaches.Biochemical Society transactions · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The integration of human papillomavirus (HPV) is closely related to the occurrence of cervical cancer. However, little is known about the complete state of HPV integration into the host genome. Methods: In this study, three HPV-positive cell lines, HeLa, SiHa, and CaSki, were subjected to NANOPORE long-read sequencing to detect HPV integration. Analysis of viral integration patterns using independently developed software (HPV-TSD) yielded multiple complete integration patterns for the three HPV cell lines. Results: We found distinct differences between the integration patterns of HPV18 and HPV16. Furthermore, the integration characteristics of the viruses were significantly different, even though they all belonged to HPV16 integration. The HPV integration in the CaSki cells was relatively complex. The HPV18 integration status in HeLa cells was the dominant, whereas the percentage of integrated HPV 16 in SiHa and CaSki cells was significantly lower. In addition, the virus sequences in the HeLa cells were incomplete and existed in an integrated state. We also identified a large number of tandem repeats in HPV16 and HPV18 integration. Our study not only clarified the feasibility of high-throughput long-read sequencing in the study of HPV integration, but also explored a variety of HPV integration models, and confirmed that viral integration is an important form of HPV in cell lines. Conclusion: Elucidating HPV integration patterns will provide critical guidance for developing a detection algorithm for HPV integration, as well as the application of virus integration in clinical practice and drug research and development.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.