Evidence map›Paper›PMID 31641155›Full record

ArticleScientific reports2019

eVIDENCE: a practical variant filtering for low-frequency variants detection in cell-free DNA.

Kei Mizuno, Shusuke Akamatsu, Takayuki Sumiyoshi, Jing Hao Wong, Masashi Fujita, Kazuaki Maejima, Kaoru Nakano, Atushi Ono, Hiroshi Aikata, Masaki Ueno and 7 more

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Network approach in liquidomics landscape.Journal of experimental & clinical cancer research : CR · 2023
    Review
  6. Review
  7. Article
  8. 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

17 authors.

Kei MizunoDepartment of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Shusuke AkamatsuDepartment of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Takayuki SumiyoshiDepartment of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Jing Hao WongDepartment of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Masashi FujitaLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.ORCID http://orcid.org/0000-0002-1457-6233
Kazuaki MaejimaLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Kaoru NakanoLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Atushi OnoDepartment of Gastroenterology and Metabolism, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Hiroshi AikataDepartment of Gastroenterology and Metabolism, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Masaki UenoSecond Department of Surgery, Wakayama Medical University, Wakayama, Japan.
Shinya HayamiSecond Department of Surgery, Wakayama Medical University, Wakayama, Japan.
Hiroki YamaueSecond Department of Surgery, Wakayama Medical University, Wakayama, Japan.
Kazuaki ChayamaDepartment of Gastroenterology and Metabolism, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Takahiro InoueDepartment of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Osamu OgawaDepartment of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Hidewaki NakagawaLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan. hidewaki@ims.u-tokyo.ac.jp.
Akihiro FujimotoDepartment of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan. afujimoto@m.u-tokyo.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plasma cell-free DNA (cfDNA) testing plays an increasingly important role in precision medicine for cancer. However, circulating cell-free tumor DNA (ctDNA) is highly diluted by cfDNA from non-cancer cells, complicating ctDNA detection and analysis. To identify low-frequency variants, we developed a program, eVIDENCE, which is a workflow for filtering candidate variants detected by using the ThruPLEX tag-seq (Takara Bio), a commercially-available molecular barcoding kit. We analyzed 27 cfDNA samples from hepatocellular carcinoma patients. Sequencing libraries were constructed and hybridized to our custom panel targeting about 80 genes. An initial variant calling identified 36,500 single nucleotide variants (SNVs) and 9,300 insertions and deletions (indels) across the 27 samples, but the number was much greater than expected when compared with previous cancer genome studies. eVIDENCE was applied to the candidate variants and finally 70 SNVs and 7 indels remained. Of the 77 variants, 49 (63.6%) showed VAF of < 1% (0.20-0.98%). Twenty-five variants were selected in an unbiased manner and all were successfully validated, suggesting that eVIDENCE can identify variants with VAF of ≥ 0.2%. Additionally, this study is the first to detect hepatitis B virus integration sites and genomic rearrangements in the TERT region from cfDNA of HCC patients. We consider that our method can be applied in the examination of cfDNA from other types of malignancies using specific custom gene panels and will contribute to comprehensive ctDNA analysis.

Indexed as

Mutation RateSoftwareBiomarkers, TumorCarcinoma, HepatocellularCell-Free Nucleic AcidsHumansLiver NeoplasmsSequence Analysis, DNABiomarkers, TumorCell-Free Nucleic Acids

Identifiers

PMID31641155
PMCPMC6805874

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.