Evidence map›Paper›PMID 40465654›Full record

ArticlePloS one2025

Adaptation of PCR-based library preparation for MGI platform for cancer mutation testing in clinical setting.

P A Shatalov, M P Raygorodskaya, A P Shinkarkina, A A Traspov, A V Murzaeva, Y A Doroshenko, I A Leuhina, V A Mileyko, M V Ivanov, T V Grigoreva and 6 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

16 authors.

P A ShatalovNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
M P RaygorodskayaNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
A P ShinkarkinaNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
A A TraspovNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
A V MurzaevaNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
Y A DoroshenkoNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
I A LeuhinaNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
V A MileykoOncoAtlas LLC, Moscow, Russia.
M V IvanovOncoAtlas LLC, Moscow, Russia.ORCID https://orcid.org/0000-0002-9961-0129
T V GrigorevaOncoAtlas LLC, Moscow, Russia.
A A LebedevaOncoAtlas LLC, Moscow, Russia.ORCID https://orcid.org/0000-0003-1920-5076
E M VeselovskyOncoAtlas LLC, Moscow, Russia.
L D BelyaevaOncoAtlas LLC, Moscow, Russia.
E V BelovaOncoAtlas LLC, Moscow, Russia.ORCID https://orcid.org/0000-0002-7701-8765
A D KaprinNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.
P V ShegaiNational Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Obninsk, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MGI platforms hold promise to become a widespread instrument for various clinical next-generation sequencing applications, from whole genome sequencing to COVID-19 genotyping. However, in the clinical oncology setting it is still restricted to large panel sequencing limiting capacity for routine biomarker screening. In this article, we describe our experience of tailoring amplicon-based library construction for the MGI platform. Illumina compatible reagents served as a prototype in order to introduce platform specific adapters. Elaborated reagent kits were used for BRCA1/2 or 34 oncogenes testing both with whole blood and FFPE-derived DNA. Our data show that amplicon-based DNBSEQ-tailored library preparation demonstrates sufficient analytical efficiency in terms of coverage uniformity (average MAPD 1.08 and 1.19 for ABC plus and Atlas plus panels) and amplicon drop-out rate (ranging from 0.3% to 2.5%). Additionally, it shows efficiency in terms of single sample sensitivity, maintaining 99% sensitivity compared to 99% for the Illumina prototype. We show that it also outreaches expected diagnostic parameters of MGI exome sequencing (99% vs 95% for WES). Per-amplicon coverage of sticky-end libraries sequenced on Illumina and MGI were highly correlated demonstrating that the platform itself does not introduce any bias to amplicon coverage. Across three tested variations of library preparation protocol, discordances were related to ligation mix component composition and resulted in underrepresentation of GC-low and GC-high amplicons and low uniformity as a result. Overall, we outline the successful adaptation of PCR-based library preparation for MGI signifying the importance of tailoring component composition of reagent kit for uniform coverage.

Indexed as

Gene LibraryMutationNeoplasmsPolymerase Chain ReactionBRCA1 ProteinCOVID-19DNA Mutational AnalysisHigh-Throughput Nucleotide SequencingHumansSARS-CoV-2BRCA1 Protein

Identifiers

PMID40465654
PMCPMC12136352

What OpenQuestion holds

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LicenceCC BY
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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.