Tracking myeloma tumor DNA in peripheral blood.

Johannes M Waldschmidt, Tushara Vijaykumar, Birgit Knoechel, Jens G Lohr

Abstract readReview

In one paragraph

Review in Best practice & research. Clinical haematology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it

0cells of the map it votes in

5citing 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

5 citing papers in PubMed.

Liquid biopsy-based monitoring of residual disease in multiple myeloma by analysis of the rearranged immunoglobulin genes-A feasibility study.PloS one · 2023
Article
Detection of Measurable Residual Disease Biomarkers in Extracellular Vesicles from Liquid Biopsies of Multiple Myeloma Patients-A Proof of Concept.International journal of molecular sciences · 2022
Article
Circulating Tumour Cells, Cell Free DNA and Tumour-Educated Platelets as Reliable Prognostic and Management Biomarkers for the Liquid Biopsy in Multiple Myeloma.Cancers · 2022
Review
The Minimal Residual Disease Using Liquid Biopsies in Hematological Malignancies.Cancers · 2022
Review
Copy number evolution and its relationship with patient outcome-an analysis of 178 matched presentation-relapse tumor pairs from the Myeloma XI trial.Leukemia · 2021
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

4 authors.

Johannes M WaldschmidtDepartment of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Tushara VijaykumarDepartment of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.

Birgit KnoechelHarvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.

Jens G LohrDepartment of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: jensg_lohr@dfci.harvard.edu.

Funding

Determining the mutational landscape of circulating multiple myeloma cellsK08CA191026 · NCI · DANA-FARBER CANCER INST · PI LOHR, JENS G · 2015 to 2019

$886k

Epigenetic mechanisms of drug resistance in T-cell acute lymphoblastic leukemiaK08CA191091 · NCI · DANA-FARBER CANCER INST · PI KNOECHEL, BIRGIT · 2015 to 2019

$886k

NCI NIH HHS K08 CA191026NCI NIH HHS K08 CA191091

6 · The paper itself

Abstract

Over the past years, the emergence of liquid biopsy technologies has dramatically expanded our ability to assess multiple myeloma without the need for invasive sampling. Interrogation of cell-free DNA from the peripheral blood recapitulates the mutational landscape at excellent concordance with matching bone marrow aspirates. It can quantify disease burden and identify previously undetected resistance mechanisms which may inform clinical management in real-time. The convenience of sample acquisition and storage provides strong procedural benefits over currently available testing. Further investigations will have to define the role of cell-free DNA as a diagnostic measure by determining clinically relevant tumor thresholds in comparison to existing routine parameters. This review presents an overview of currently available assays and discusses the clinical value, potential and limitations of cell-free DNA technologies for the assessment of this challenging disease.

Indexed as

Genome, HumanMutationAntineoplastic AgentsBiomarkers, TumorCirculating Tumor DNAGene Expression ProfilingGTP PhosphohydrolasesHigh-Throughput Nucleotide SequencingHumansLiquid BiopsyMembrane ProteinsMultiple MyelomaNeoplasm, ResidualPlasma CellsProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)Antineoplastic AgentsBiomarkers, TumorBRAF protein, humanCirculating Tumor DNAGTP PhosphohydrolasesKRAS protein, humanMembrane ProteinsNRAS protein, humanProto-Oncogene Proteins B-rafProto-Oncogene Proteins p21(ras)TP53 protein, humanTumor Suppressor Protein p53Cell-free DNAEarly cancer detectionGenomic profilingLiquid biopsyMRDNext-generation sequencing

Identifiers

PMID32139012

DOI10.1016/j.beha.2020.101146

PMCPMC7060910

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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.