Evidence map›Paper›PMID 41910939›Full record

ReviewMolecular diagnosis & therapy2026

The Evolving Role of Genomic Technologies in Multiple Myeloma: Implications for Diagnosis, Risk Stratification and Resistance.

Klára Baďurová, Veronika Kapustová, Jana Kotulová, Vítězslav Brinsa, Lenka Piherová, Václav Janoušek, Michal Pohludka, Michal Richtář, Tomáš Jelínek, Roman Hájek and 2 more

Abstract readReview
In one paragraph

Review in Molecular diagnosis & therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Klára Baďurová *Department of Hematooncology, University Hospital Ostrava, Dvořákova 7, 701 03, Ostrava, Czech Republic.
Veronika Kapustová *Department of Hematooncology, University Hospital Ostrava, Dvořákova 7, 701 03, Ostrava, Czech Republic.
Jana KotulováDepartment of Hematooncology, University Hospital Ostrava, Dvořákova 7, 701 03, Ostrava, Czech Republic.
Vítězslav BrinsaGeneSpector s.r.o., Prague, Czech Republic.
Lenka PiherováGeneSpector s.r.o., Prague, Czech Republic.
Václav JanoušekDepartment of Pediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University, Prague, Czech Republic.
Michal PohludkaGeneSpector s.r.o., Prague, Czech Republic.
Michal RichtářDepartment of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czech Republic.
Tomáš JelínekDepartment of Hematooncology, University Hospital Ostrava, Dvořákova 7, 701 03, Ostrava, Czech Republic.
Roman HájekDepartment of Hematooncology, University Hospital Ostrava, Dvořákova 7, 701 03, Ostrava, Czech Republic.
Zuzana Chyra *Department of Hematooncology, University Hospital Ostrava, Dvořákova 7, 701 03, Ostrava, Czech Republic.
Tereza Ševčíková *Department of Hematooncology, University Hospital Ostrava, Dvořákova 7, 701 03, Ostrava, Czech Republic. tereza.sevcikova@osu.cz.ORCID 0000-0002-8704-0106

Funding

Agentura Pro Zdravotnický Výzkum České Republiky NU23-03-00374Ministerstvo Školství, Mládeže a Tělovýchovy CZ.02.01.01/00/22_008/0004644Ministerstvo Životního Prostředí No. CZ.10.03.01/00/22_003/0000003Technologická Agentura České Republiky LM2023067Technologická Agentura České Republiky TQ03000338
6 · The paper itself

Abstract

Plasma cell disorders range from indolent precursors to aggressive malignancies, with multiple myeloma as the most common malignant form. Multiple myeloma biology is highly complex and driven by genomic heterogeneity. Although recent genomic advances offer increasingly precise treatment strategies, routinely used conventional diagnostic methods sometimes fail to reflect the evolution of up-to-date multiple myeloma risk stratification models, and the implementation of genomic discoveries into clinical guidelines is hindered. We reviewed the current state and emerging roles of genomic diagnostics in multiple myeloma and related conditions, emphasizing the clinical utility. We summarized clinical presentation and diagnostic criteria, mapped the mutational landscape across disease stages, and tracked the evolution of risk stratification from clinical staging to integrated genomic models. We also highlighted recent recommendations that incorporate a quantitative assessment of cytogenetic abnormalities and tumor suppressor gene mutations. Further, we compared routinely used and state-of-the-art technologies including fluorescence in situ hybridization, targeted gene panels, whole-exome and whole-genome sequencing, long-read platforms, optical genome mapping, and analyses of circulating tumor DNA, focusing on their strengths, limitations, and complementary roles in the baseline work-up, longitudinal monitoring, and detection of resistance. Last, we discussed practical barriers to implementation and proposed a framework for proactive integration of novel approaches into clinics. In summary, comprehensive genomic profiling is becoming central to modern multiple myeloma diagnostics and a key step for precise and personalized medicine that will, if integrated into routine care, enable a more precise risk assessment, earlier detection of relapse, and improved therapy selection.

Indexed as

Drug Resistance, NeoplasmGenomicsMultiple MyelomaBiomarkers, TumorGenetic Predisposition to DiseaseHumansMutationRisk AssessmentBiomarkers, Tumor

Identifiers

PMID41910939
PMCPMC13171931

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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.