Evidence map›Paper›PMID 30901326›Full record

ArticlePloS one2019

Baseline identification of clonal V(D)J sequences for DNA-based minimal residual disease detection in multiple myeloma.

Even H Rustad, Malin Hultcrantz, Venkata D Yellapantula, Theresia Akhlaghi, Caleb Ho, Maria E Arcila, Mikhail Roshal, Akshar Patel, Denise Chen, Sean M Devlin and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 32 citations in OpenAlex.

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  7. Capture Rate of V(D)J Sequencing for Minimal Residual Disease Detection in Multiple Myeloma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022
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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

15 authors at 1 institution in 2 countries.

Even H RustadMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.ORCID 0000-0002-9320-4963
Malin HultcrantzMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Venkata D YellapantulaDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Theresia AkhlaghiMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Caleb HoDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Maria E ArcilaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Mikhail RoshalDepartment of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Akshar PatelCenter for Hematological Malignancies, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Denise ChenMarie-Josee and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Sean M DevlinDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Austin JacobsenInvivoscribe, Inc, San Diego, CA, United States of America.
Ying HuangInvivoscribe, Inc, San Diego, CA, United States of America.
Jeffrey E MillerInvivoscribe, Inc, San Diego, CA, United States of America.
Elli PapaemmanuilDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Ola LandgrenMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Memorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Tracking of clonal immunoglobulin V(D)J rearrangement sequences by next generation sequencing is highly sensitive for minimal residual disease in multiple myeloma. However, previous studies have found variable rates of V(D)J sequence identification at baseline, which could limit tracking. Here, we aimed to define the factors influencing the identification of clonal V(D)J sequences. Bone marrow mononuclear cells from 177 myeloma patients underwent V(D)J sequencing by the LymphoTrack assays (Invivoscribe). As a molecular control for tumor cell content, we sequenced the samples using our in-house myeloma panel myTYPE. V(D)J sequence clonality was identified in 81% of samples overall, as compared with 95% in samples where tumor-derived DNA was detectable by myTYPE. Clonality was detected more frequently in patients with lambda-restricted disease, mainly because of increased detection of kappa gene rearrangements. Finally, we describe how the tumor cell content of bone marrow aspirates decrease gradually in sequential pulls because of hemodilution: From the initial pull used for aspirate smear, to the final pull that is commonly used for research. In conclusion, baseline clonality detection rates of 95% or higher are feasible in multiple myeloma. Optimal performance depends on the use of good quality aspirates and/or subsequent tumor cell enrichment.

Indexed as

V(D)J RecombinationAgedBone Marrow CellsFemaleHumansImmunoglobulin Heavy ChainsImmunoglobulin kappa-ChainsMaleMiddle AgedMultiple MyelomaNeoplasm, ResidualSequence Analysis, DNAImmunoglobulin Heavy ChainsImmunoglobulin kappa-Chains

Identifiers

PMID30901326
PMCPMC6430394
OpenAlexW2991321296

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.