Evidence map›Paper›PMID 41703564›Full record

ArticleJournal of translational medicine2026

Growth differentiation factor 15 promotes the malignant progression of multiple myeloma via activation of PI3K/Akt/NF-κB signaling pathway.

Hongjie Fan, Yiwen Wu, Yuanyuan Peng, Lingzhi Wang, Shengke Tu, Hui Peng, Jing Yang, Xiaolan Li, Ziwei Shi, Min Li and 1 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 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

11 authors.

Hongjie Fan *Department of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, 524000, China.
Yiwen Wu *Department of Pharmacy, The First Affiliated Hospital of Jishou University, Jishou, 416000, China.
Yuanyuan PengMedical College, Jishou University, Jishou, 416000, China.
Lingzhi WangDepartment of Pharmacy, The First Affiliated Hospital of Jishou University, Jishou, 416000, China.
Shengke TuDepartment of Hematology, The First Affiliated Hospital of Jishou University, Jishou, 416000, China.
Hui PengMedical College, Jishou University, Jishou, 416000, China.
Jing YangMedical College, Jishou University, Jishou, 416000, China.
Xiaolan LiDepartment of Hematology, The First Affiliated Hospital of Jishou University, Jishou, 416000, China.
Ziwei ShiDepartment of Hematology, The First Affiliated Hospital of Jishou University, Jishou, 416000, China.
Min LiDepartment of Pharmacy, The First Affiliated Hospital of Jishou University, Jishou, 416000, China. lucyminmin@163.com.
Kui SongDepartment of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, 524000, China. js_hematology@163.com.ORCID 0009-0006-3156-7159

Funding

the Innovation Platform and Talent Program of Hunan Province 2021SK4050the Natural Science Foundation of Hunan Province 2023JJ30608the Natural Science Foundation of Hunan Province 2023JJ30609the Natural Science Foundation of Hunan Province 2025JJ81142the Scientific Research Foundation of Hunan Provincial Education Department QL20220240
6 · The paper itself

Abstract

objectiveExtramedullary disease (EMD) in multiple myeloma (MM) is associated with poor prognosis and presents considerable treatment challenges. However, the underlying molecular mechanisms remain incompletely understood. This study aimed to identify prognostic biomarkers through bioinformatics analysis and investigate the mechanisms governing proliferation and metastasis in MM.

methodsDifferentially expressed genes (DEGs) between MM and control samples were identified from datasets GSE146649 and GSE24870 through differential expression analysis. Prognostic biomarkers associated with MM were subsequently screened using weighted gene co-expression network analysis (WGCNA), support vector machine recursive feature elimination (SVM-RFE), and gene set enrichment analysis (GSEA). The biological effects and underlying mechanisms of growth differentiation factor 15 (GDF15) in MM were further evaluated using enzyme-linked immunosorbent assay (ELISA), CCK-8 assay, flow cytometry, cell adhesion assay, transwell migration assay, Western blotting, and co-immunoprecipitation (Co-IP).

resultsFour prognostic biomarkers—BIRC3, PRDX1, BCAP31, and GDF15 were identified as being involved in MM proliferation and metatasis. GDF15 was selected as the key gene for further investigation. Serum GDF15 levels were significantly elevated in MM patients with EMD compared to those without EMD and healthy controls. Inhibition of GFRAL, the specific receptor for GDF15, reversed the activation of the PI3K/Akt/NF-κB signaling pathway and attenuated upregulation of CXC chemokine receptors 4 (CXCR4) and matrix metalloproteinases 9 (MMP9). Treatment with uprosertib, a Akt inhibitor, abrogated the GDF15-induced increases in CXCR4 and MMP9 expression.

conclusionUpregulation of GDF15 is positively correlated with MM progression. Moreover, GDF15 enhances the migratory and invasive capacities of MM cells via the PI3K/Akt/NF-κB signaling pathway, mediated by CXCR4 and MMP9. Thus, GDF15 may represent a potential therapeutic target for EMD in multiple myeloma.

Indexed as

Disease ProgressionGrowth Differentiation Factor 15Multiple MyelomaNF-kappa BPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktSignal TransductionBiomarkers, TumorCell Line, TumorCell MovementCell ProliferationGene Expression Regulation, NeoplasticHumansPrognosisReceptors, CXCR4Biomarkers, TumorGDF15 protein, humanGrowth Differentiation Factor 15NF-kappa BPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktReceptors, CXCR4BioinformaticsExtramedullary diseaseGDF15Machine learningMultiple myeloma

Identifiers

PMID41703564
PMCPMC13015019

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.