Evidence map›Paper›PMID 34325497›Full record

ArticleCancer research and treatment2022

Plasma Circulating Tumor DNA in Patients with Primary Central Nervous System Lymphoma.

Sang Eun Yoon, Yeon Jeong Kim, Joon Ho Shim, Donghyun Park, Junhun Cho, Young Hyeh Ko, Woong-Yang Park, Yeung-Chul Mun, Kyoung Eun Lee, Duck Cho and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Cancer research and treatment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.6field-weighted citation impact, top 14% of its field
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

12 citing papers in PubMed, 21 citations in OpenAlex.

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  11. Circulating Tumor DNA Profiling for Detection, Risk Stratification, and Classification of Brain Lymphomas.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023
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  12. 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

12 authors at 4 institutions in 1 country.

Sang Eun YoonDivision of Hematology-oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Yeon Jeong KimSamsung Genome Institute, Samsung Medical Center, Seoul, Korea.
Joon Ho ShimSamsung Genome Institute, Samsung Medical Center, Seoul, Korea.
Donghyun ParkSamsung Genome Institute, Samsung Medical Center, Seoul, Korea.
Junhun ChoDepartment of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Young Hyeh KoDepartment of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Woong-Yang ParkSamsung Genome Institute, Samsung Medical Center, Seoul, Korea.
Yeung-Chul MunDivision of Hematology-Oncology, Department of Internal Medicine, Ewha Medical Research Center, School of Medicine, Ewha Womans University, Seoul, Korea.
Kyoung Eun LeeDivision of Hematology-Oncology, Department of Internal Medicine, Ewha Medical Research Center, School of Medicine, Ewha Womans University, Seoul, Korea.
Duck ChoDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Won Seog KimDivision of Hematology-oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Seok Jin KimDivision of Hematology-oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Samsung Medical Center · KRSungkyunkwan University · KREwha Womans University Medical Center · KRSamsung (South Korea) · KR

Funding

Korea Health Industry Development InstituteMinistry of Health and Welfare HR20C0025National Research Foundation of Korea 2021R1A2C1007531
6 · The paper itself

Abstract

purposeAnalysis of circulating tumor DNA (ctDNA) in blood could allow noninvasive genetic analysis of primary tumors. Although there have been unmet needs for noninvasive methods in patients with primary central nervous system lymphoma (PCNSL), it is still not determined whether plasma ctDNA analysis could be useful for patients with PCNSL. MATERIALS AND

methodsTargeted deep sequencing of 54 genes was performed in cell-free DNA isolated from plasma samples collected pretreatment, during treatment, and at the end of treatment in 42 consecutively diagnosed PCNSL patients between January 2017 and December 2018.

resultsTargeted sequencing of plasma cell-free DNA detected somatic mutations representing ctDNA in 11 cases (11/41, 27%). The detection of ctDNA was not related to the concentration of cell-free DNA or tumor volume. The mutation profiles of these 11 cases varied between patients. The most frequently mutated gene was PIM1 (4/11, 36.4%), whereas KMT2D, PIK3CA, and MYD88 were each observed in three patients (3/11, 27%). The mutations of 13 genes were concordantly found in primary tumor tissue and plasma ctDNA, giving a detection sensitivity of 45%. During the serial tracking of seven patients with complete response, the disappearance of ctDNA mutations was found in four patients, whereas three patients had detected ctDNA mutation at the end of treatment.

conclusionThe plasma ctDNA mutation analysis still has limited value for surveillance and predicting treatment outcomes of PCNSL because the detection efficiency was lower than other systemic lymphomas. Thus, analytical platforms should be improved to overcome anatomical hurdles associated with PCNSL.

Indexed as

Circulating Tumor DNALymphomaBiomarkers, TumorCentral Nervous SystemHigh-Throughput Nucleotide SequencingHumansMutationBiomarkers, TumorCirculating Tumor DNACirculating tumor DNAPrimary CNS lymphomaPrognosis

Identifiers

PMID34325497
PMCPMC9016302
OpenAlexW3183432243

What OpenQuestion holds

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LicenceCC BY-NC
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.