Evidence mapPaperPMID 41831174Full record

ReviewDiscover oncology2026

Genomic profiling enables personalized strategies to overcome drug resistance in multiple myeloma.

Fengbo Zeng, Azin Taki

Abstract readReview
In one paragraph

Review in Discover oncology, 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

2 authors.

Fengbo ZengDepartment of Clinical Laboratory, Chengdu BOE Hospital, Chengdu, 610200, Sichuan, P.R. China.ORCID http://orcid.org/0009-0000-5711-9051
Azin TakiFaculty of Medicine, Najafabad Branch, Islamic Azad University, Najafabad, 61357-15794, Iran. hamedpublish@gmail.com.ORCID http://orcid.org/0000-0002-2451-9216

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM) is a hematologic malignancy characterized by the clonal proliferation of malignant plasma cells within the bone marrow. It is a complex and heterogeneous disease that primarily affects older adults and is associated with significant morbidity and mortality. Despite advances in treatment, including proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies, MM remains largely incurable, with most patients experiencing relapse and disease progression. The disease’s biological complexity is driven by a multitude of genetic and molecular alterations, which contribute to its clinical variability and resistance to therapy. The development of drug resistance is a major obstacle in the management of MM, often leading to treatment failure and disease relapse. Resistance mechanisms can be intrinsic, present before therapy initiation, or acquired, emerging during the course of treatment. These mechanisms involve complex molecular pathways, genetic mutations, and interactions within the bone marrow microenvironment that enable malignant plasma cells to evade therapeutic effects. A comprehensive understanding of these resistance pathways is crucial for designing strategies to overcome or prevent resistance, thereby improving patient outcomes. Integrating insights from molecular pathways and genomic profiling into clinical practice holds promise for tailoring personalized therapies that can effectively target resistant disease clones and prolong remission. Additionally, exploring combination therapies that target multiple pathways simultaneously, informed by molecular profiling, holds promise for overcoming intrinsic and acquired resistance. Continued innovation in predictive modeling and functional assays will facilitate the translation of molecular insights into effective, individualized treatment plans.

Indexed as

Genomic profilingImmunomodulatory drugMultiple myelomaPlasma cell

Identifiers

PMID41831174
PMCPMC13100182

What Socratic holds

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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 Socratic graph.