ArticleHeliyon2023
Characterization of monoclonal gammopathy of undetermined significance progression to multiple myeloma through meta-analysis of GEO data.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
3 citing papers in PubMed, 4 citations in OpenAlex.
- Exploiting artificial intelligence in precision oncology: an updated comprehensive review.Journal of translational medicine · 2025Review
- Multi-omics profiling and AI-driven clinically deployable risk models in MGUS and smoldering myeloma.Clinical and experimental medicine · 2025Review
- CREB1 promotes expression of immune checkpoint HLA-E leading to immune escape in multiple myeloma.Leukemia · 2024Article
Corrections and comments
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Authors and funding
13 authors at 9 institutions in 1 country.
Funding
Abstract
The etiology of monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) is still obscure as are the processes that enable the progression of MGUS to MM. Understanding the unique vs. shared transcriptomes can potentially elucidate why individuals develop one or the other. Furthermore, highlighting key pathways and genes involved in the pathogenesis of MM or the development of MGUS to MM may allow the discovery of novel drug targets and therapies. We employed STARGEO platform to perform three separate meta-analysis to compare MGUS and MM transcriptomes. For these analyses we tagged (1) 101 MGUS patient plasma cells from bone marrow samples and 64 plasma cells from healthy controls (2) 383 MM patient CD138+ cells from bone marrow and the 101 MGUS samples in the first analysis as controls (3) 517 MM patient peripheral blood samples and 97 peripheral blood samples from healthy controls. We then utilized Ingenuity Pathway Analysis (IPA) to analyze the unique genomic signatures within and across these samples. Our study identified genes that may have unique roles in MGUS (GADD45RA and COMMD3), but also newly identified signaling pathways (EIF2, JAK/STAT, and MYC) and gene activity (NRG3, RBFOX2, and PARP15) in MGUS that have previously been shown to be involved in MM suggesting a spectrum of molecular overlap. On the other hand, genes such as DUSP4, RN14, LAMP5, differentially upregulated in MM, may be seen as tipping the scales from benignity to malignancy and could serve as drug targets or novel biomarkers for risk of progression. Furthermore, our analysis of MM identified newly associated gene/pathway activity such as inhibition of Wnt-signaling and defective B cell development. Finally, IPA analysis, suggests the multifactorial, oncogenic qualities of IFNγ signaling in MM may be a unifying pathway for these diverse mechanisms and prompts the need for further studies.
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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.