Evidence map›Paper›PMID 40418254›Full record

ReviewClinical and experimental medicine2025

Impact of proteostasis workload on sensitivity to proteasome inhibitors in multiple myeloma.

Jindrich Sedlacek

Abstract readReview
In one paragraph

Review in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

1 author.

Jindrich SedlacekDepartment of Genetics and Microbiology, Charles University and Research Center BIOCEV, Průmyslová 595, 252 50, Vestec, Czech Republic. jindrich.sedlacek@uochb.cas.cz.

Funding

Grantová Agentura České Republiky GA22-16389SNational Institute Virology and Bacteriology (Program EXCELES) LX22NPO5103
6 · The paper itself

Abstract

Genomic alterations and enormous monoclonal immunoglobulin production cause multiple myeloma to heavily depend on proteostasis mechanisms, including protein folding and degradation. These findings support the use of proteasome inhibitors for treating multiple myeloma and mantle cell lymphoma. Myeloma treatment has evolved, especially with the availability of new drugs, such as proteasome inhibitors, into therapeutic strategies for both frontline and relapsed/refractory disease settings. However, proteasome inhibitors are generally not effective enough to cure most patients. Natural resistance and eventual acquired resistance led to relapsed/refractory disease and poor prognosis. Advances in the understanding of cellular proteostasis and the development of innovative drugs that also target other proteostasis network components offer opportunities to exploit the intrinsic vulnerability of myeloma cells. This review outlines recent findings on the molecular mechanisms regulating cellular proteostasis pathways, as well as resistance, sensitivity, and escape strategies developed against proteasome inhibitors and provides a rationale and examples for novel combinations of proteasome inhibitors with FDA-approved drugs and investigational drugs targeting the NRF1 (NFE2L1)-mediated proteasome bounce-back response, redox homeostasis, heat shock response, unfolding protein response, autophagy, and VCP/p97 to increase proteotoxic stress, which can improve the efficacy of antimyeloma therapy based on proteasome inhibitors.

Indexed as

Antineoplastic AgentsMultiple MyelomaProteasome InhibitorsProteostasisDrug Resistance, NeoplasmHumansAntineoplastic AgentsProteasome InhibitorsAutophagyHeat shock responseProteasome bounce-back responseRedox homeostasisUPRVCP/p97

Identifiers

PMID40418254
PMCPMC12106538

What OpenQuestion holds

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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.