Evidence map›Paper›PMID 40132539›Full record

ArticleCell reports methods2025

AVID enables sensitive and accurate viral integration detection across human cancers.

Xueying Lyu, Russell Wing-Yeung Mok, Hoi-Ying Chan, Tina Suoangbaji, Qian Li, Fanhong Zeng, Renwen Long, Irene Oi-Lin Ng, Loey Lung-Yi Mak, Daniel Wai-Hung Ho

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xueying LyuState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Russell Wing-Yeung MokState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Hoi-Ying ChanState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Tina SuoangbajiState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Qian LiState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Fanhong ZengState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Renwen LongState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Irene Oi-Lin NgState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
Loey Lung-Yi MakState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China. Electronic address: lungyi@hku.hk.
Daniel Wai-Hung HoState Key Laboratory of Liver Research, The University of Hong Kong, Pokfulam, Hong Kong, China; Department of Pathology, School of Clinical Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China. Electronic address: dwhho@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oncovirus infection is a key etiological risk factor of human cancers, which triggers virus integration in the host genome. Viral integration can lead to structural variation, gene dysfunction, and genome instability, promoting tumorigenesis. To support the investigation of virus-associated cancer and improve the detection of virus infection, we developed an algorithm called AVID (accurate viral integration detector) for viral integration detection. AVID was built by overcoming the existing detection limitations, enhancing sensitivity and accuracy, and expanding additional functions of viral integration detection. The performance of AVID was estimated in simulated datasets and experimentally validated datasets compared with other tools. To demonstrate its wide applicability, we also tested AVID on viral integration detection in multiple oncovirus-associated human cancers, including hepatocellular carcinoma (HCC), cervical cancer, and nasopharyngeal carcinoma. Taken together, our study developed an improved and applicable tool for viral integration detection and visualization to facilitate further exploration of virus-infected diseases.

Indexed as

NeoplasmsVirus IntegrationAlgorithmsFemaleHumansCP: Cancer biologyCP: Geneticsdetectiononcovirusperformance comparisonviral integrationvisualization

Identifiers

PMID40132539
PMCPMC12049714

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Registered trials

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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.