LILRB4 regulates multiple myeloma development through STAT3-PFKFB1 pathway
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1137918 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR29892052.fastq.gz | Fastqsanger.gz | |||
| SRR29892053.fastq.gz | Fastqsanger.gz | |||
| SRR29892054.fastq.gz | Fastqsanger.gz | |||
| SRR29892055.fastq.gz | Fastqsanger.gz | |||
| SRR29892056.fastq.gz | Fastqsanger.gz |
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Project description:To explore the cancdidate targets of LILRB4 in MM
2025-06-03 | GSE272664 | GEO
Project description:STAiR18, an mRNA-like STAT3-induced long noncoding RNA shows ubiquitous expression. RNAi-mediated knockdown of STAiR18 led to a dramatic decrease in INA-6 cell vitality. Furthermore, STAiR18 knockdown reduced the STAT3 RNA and protein levels in these cells, suggesting a positive feedback loop between STAT3 and its target ncRNA STAiR18. Microarray analyses of INA-6 cells after STAiR18 or STAT3 knockdown revealed overlapping changes of transcription patterns indicating a close functional interplay between the two molecules. Taken together, STAiR18 represents a novel noncoding RNA that is likely to play an important role for the oncogenic function of the STAT3 pathway. STAT3- and STAiR18-dependent gene expression in human multiple myeloma cell line INA-6 was measured 40 hours after transfection with either a negative control siRNA, an siRNA to STAT3 or an siRNA to STAiR18. Four independent experiments were performed for each siRNA approach, yielding 12 approaches in total.
2016-07-17 | E-GEOD-71092 | biostudies-arrayexpress
Project description:KDM6A Regulates Immunogenicity of Multiple Myeloma
| PRJNA1023289 | ENA
Project description:Although multiple myeloma (MM) responds well to immunotherapeutic treatment, certain portions of MM are still unresponsive or relapse after immunotherapy. Other immune molecules are needed for the immunotherapy of MM. Here, we revealed that leukocyte immunoglobulin-like receptor B4 (LILRB4) was highly expressed in multiple myeloma cell lines and patient samples and that the expression of LILRB4 was adversely correlated with the overall survival of MM patients. Knockdown of LILRB4 efficiently delayed the growth of MM cells both in vitro and in vivo. Mechanistically, IKZF1 transactivated LILRB4 expression to trigger the downstream of STAT3-PFKFB1 pathways to support MM cell proliferation. Blockade of LILRB4 signaling by blocking antibodies can effectively inhibit MM progression. Our data show that targeting LILRB4 is potentially an additional therapeutic strategy for the immunotherapeutic treatment of MM.
| S-EPMC11258265 | biostudies-literature
Project description:Interleukin 6 (IL-6) activates the transcription factor signal transducer and activator of transcription 3 (STAT3). We previously identified several STAT3-induced long noncoding RNAs (STAiRs) in INA-6 multiple myeloma cells (Hackermüller et al. 2014). Here, we analyze five STAiRs by CAPTURE- and ChIRP-RNA-sequencing, a pulldown of a target RNA by transcript tiling oligonucleotides. The CAPTURE technique allows the identification of different STAiR splice variants and shall give rise to the transcript architecture. ChIRP, a method first published by Chu et al 2011, is the original method on which the CAPTURE approach is based on and enables the identification of RNAs interacting with our STAiRs.
2017-08-01 | GSE95131 | GEO
Project description:The paper describes a model of multiple myeloma.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
A mathematical model of cell equilibrium and joint cell formation in multiple myeloma
M.A. Koenders, R. Saso
Journal of Theoretical Biology 390 (2016) 73–79
Abstract:
In Multiple Myeloma Bone Disease healthy bone remodelling is affected by tumour cells by means of paracrine cytokinetic signalling in such a way that osteoclast formation is enhanced and the growth of osteoblast cells inhibited. The participating cytokines are described in the literature. Osteoclast-induced myeloma cell growth is also reported. Based on existing mathematical models for healthy bone remo- delling a three-way equilibrium model is presented for osteoclasts, osteoblasts and myeloma cell populations to describe the progress of the illness in a scenario in which there is a secular increase in the cytokinetic interactive effectiveness of paracrine processes. The equilibrium state for the system is obtained. The paracrine interactive effectiveness is explored by parameter variation and the stable region in the parameter space is identified. Then recently-discovered joint myeloma–osteoclast cells are added to the model to describe the populations inside lytic lesions. It transpires that their presence expands the available parameter space for stable equilibrium, thus permitting a detrimental, larger population of osteoclasts and myeloma cells. A possible relapse mechanism for the illness is explored by letting joint cells dissociate. The mathematics then permits the evaluation of the evolution of the cell populations as a function of time during relapse.
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2024-09-02 | BIOMD0000000804 | BioModels
Project description:Chk1 inhiitors decrease the expressions of STAT3 downstream target genes in multiple myeloma cells
| PRJNA730521 | ENA
Project description:<h4><strong>BACKGROUND:</strong> Multiple myeloma is characterized by clonal proliferation of malignant plasma cells in the bone marrow that produce monoclonal immunoglobulins. N-glycosylation changes of these monoclonal immunoglobulins have been reported in multiple myeloma, but previous studies only detected limited serum N-glycan features.</h4><h4><strong>METHODS:</strong> Here, a more detailed study of the human serum N-glycome of 91 multiple myeloma patients and 51 controls was performed. We additionally analyzed sequential samples from patients (n = 7) which were obtained at different time points during disease development as well as 16 paired blood serum and bone marrow plasma samples. N-glycans were enzymatically released and measured by mass spectrometry after linkage specific derivatization of sialic acids.</h4><h4><strong>RESULTS:</strong> A decrease in both α2,3- and α2,6-sialylation, galactosylation and an increase in fucosylation within complex-type N-glycans were found in multiple myeloma patients compared to controls, as well as a decrease in difucosylation of diantennary glycans. The observed glycosylation changes were present in all ISS stages, including the 'low-risk' ISS I. In individual patients, difucosylation of diantennary glycans decreased with development of the disease. Protein N-glycosylation features from blood and bone marrow showed strong correlation. Moreover, associations of monoclonal immunoglobulin (M-protein) and albumin levels with glycan traits were discovered in multiple myeloma patients.</h4><h4><strong>CONCLUSIONS & GENERAL SIGNIFICANCE: </strong>In conclusion, serum protein N-glycosylation analysis could successfully distinguish multiple myeloma from healthy controls. Further studies are needed to assess the potential roles of glycan trait changes and the associations of glycans with clinical parameters in multiple myeloma early detection and prognosis.</h4>
2022-04-27 | MTBLS676 | MetaboLights