Evidence map›Paper›PMID 41306907›Full record

ReviewFrontiers in bioengineering and biotechnology2025

Methodological landscape in the field of integration site identification of retroviruses and retroviral vectors.

Konstantin Kochergin-Nikitsky, Alexander Lavrov, Svetlana Smirnikhina

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 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. Review
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

3 authors.

Konstantin Kochergin-NikitskyLaboratory of Genome Editing, Research Centre for Medical Genetics, Moscow, Russia.
Alexander LavrovLaboratory of Genome Editing, Research Centre for Medical Genetics, Moscow, Russia.
Svetlana SmirnikhinaLaboratory of Genome Editing, Research Centre for Medical Genetics, Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detailed mapping of viral vector integration sites, including retroviral and particularly lentiviral vectors, is critical for assessing their safety in preclinical and clinical studies. Although integration into the host genome follows certain virus-specific patterns, it remains a stochastic event and can cause insertional mutagenesis with diverse consequences, such as oncogene activation. In this review, we trace the evolution of ISA methods applied to retroviruses and derived vectors, from early labor-intensive approaches with limited coverage-such as combined strategies involving restriction analysis, Southern blotting, and subcloning-to modern high-throughput strategies. We discuss key methodologies that shaped the field, including inverse PCR (iPCR), ligation-mediated PCR (LM-PCR), and linear amplification-mediated PCR (LAM-PCR), highlighting their contributions to more comprehensive and unbiased mapping, along with limitations associated with systematic errors stemming from dependence on restriction endonuclease digestion and amplification biases. We also examine recent approaches designed to overcome these limitations, independent of PCR and restriction analysis, which enable a more accurate and undistorted representation of retroviral vector integration profiles. Despite the emergence of new techniques, classical methods-particularly LAM-PCR and its modifications, such as nrLAM-PCR-remain widely used and continue to serve as the standard in many commercial platforms.

Indexed as

clonal expansiongene therapyinsertional mutagenesisintegration siteprovirus mappingretroviral vectors

Identifiers

PMID41306907
PMCPMC12644088

What OpenQuestion holds

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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.