ArticleThe oncologist2024
Characterization of driver mutations identifies gene signatures predictive of prognosis and treatment sensitivity in multiple myeloma.
Article in The oncologist, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Correlation analysis of serum CCL3, TRACP-5b, and sclerostin with the prognosis of multiple myeloma patients.Journal of medical biochemistry · 2026Article
- Epigenetic paradigm of DNA methylation for understanding the pathophysiology, diagnostics, and therapeutics in sarcomas.Epigenomics · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
In multiple myeloma (MM), while frequent mutations in driver genes are crucial for disease progression, they traditionally offer limited insights into patient prognosis. This study aims to enhance prognostic understanding in MM by analyzing pathway dysregulations in key cancer driver genes, thereby identifying actionable gene signatures. We conducted a detailed quantification of mutations and pathway dysregulations in 10 frequently mutated cancer driver genes in MM to characterize their comprehensive mutational impacts on the whole transcriptome. This was followed by a systematic survival analysis to identify significant gene signatures with enhanced prognostic value. Our systematic analysis highlighted 2 significant signatures, TP53 and LRP1B, which notably outperformed mere mutation status in prognostic predictions. These gene signatures remained prognostically valuable even when accounting for clinical factors, including cytogenetic abnormalities, the International Staging System (ISS), and its revised version (R-ISS). The LRP1B signature effectively distinguished high-risk patients within low/intermediate-risk categories and correlated with significant changes in the tumor immune microenvironment. Additionally, the LRP1B signature showed a strong association with proteasome inhibitor pathways, notably predicting patient responses to bortezomib and the progression from monoclonal gammopathy of unknown significance to MM. Through a rigorous analysis, this study underscores the potential of specific gene signatures in revolutionizing the prognostic landscape of MM, providing novel clinical insights that could influence future translational oncology research.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.