HLA-E Binding Peptide as a Potential Therapeutic Candidate for High-Risk Multiple Myeloma.
Ontology highlight
ABSTRACT:
SUBMITTER: Yang Y
PROVIDER: S-EPMC8219970 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Our main objective was to identify abundantly expressed tyrosine kinases in multiple myeloma (MM) as potential therapeutic targets. We first compared the transcriptomes of malignant plasma cells from newly diagnosed MM patients who were risk-categorized based on the patient-specific EMC-92/SKY-92 gene expression signature values vs. normal plasma cells from healthy volunteers using archived datasets from the HOVON65/GMMG-HD4 randomized Phase 3 study evaluating the clinical efficacy of bortezomib induction/maintenance versus classic cytotoxic drugs and thalidomide maintenance. In particular, ERBB1/EGFR was significantly overexpressed in MM cells in comparison to normal control plasma cells, and it was differentially overexpressed in MM cells from high-risk patients. Amplified expression of EGFR/ERBB1 mRNA in MM cells was positively correlated with increased expression levels of mRNAs for several DNA binding proteins and transcription factors with known upregulating activity on EGFR/ERBB1 gene expression. MM patients with the highest ERBB1/EGFR expression level had significantly shorter PFS and OS times than patients with the lowest ERBB1/EGFR expression level. High expression levels of EGFR/ERBB1 were associated with significantly increased hazard ratios for unfavorable PFS and OS outcomes in both univariate and multivariate Cox proportional hazards models. The impact of high EGFR/ERBB1 expression on the PFS and OS outcomes remained significant even after accounting for the prognostic effects of other covariates. These results regarding the prognostic effect of EGFR/ERBB1 expression were validated using the MMRF-CoMMpass RNAseq dataset generated in patients treated with more recently applied drug combinations included in contemporary induction regimens. Our findings provide new insights regarding the molecular mechanism and potential clinical significance of upregulated EGFR/ERBB1 expression in MM.
| S-EPMC9610889 | biostudies-literature
Project description: Not available
| S-EPMC5134914 | biostudies-literature
Project description:The transcription factor forkhead box M1 (FOXM1) is a validated oncoprotein in solid cancers, but its role in malignant plasma cell tumors such as multiple myeloma (MM) is unknown. We analyzed publicly available MM data sets and found that overexpression of FOXM1 prognosticates inferior outcome in a subset (~15%) of newly diagnosed cases, particularly patients with high-risk disease based on global gene expression changes. Follow-up studies using human myeloma cell lines (HMCLs) as the principal experimental model system demonstrated that enforced expression of FOXM1 increased growth, survival and clonogenicity of myeloma cells, whereas knockdown of FOXM1 abolished these features. In agreement with that, constitutive upregulation of FOXM1 promoted HMCL xenografts in laboratory mice, whereas inducible knockdown of FOXM1 led to growth inhibition. Expression of cyclin-dependent kinase 6 (CDK6) and NIMA-related kinase 2 (NEK2) was coregulated with FOXM1 in both HMCLs and myeloma patient samples, suggesting interaction of these three genes in a genetic network that may lend itself to targeting with small-drug inhibitors for new approaches to myeloma therapy and prevention. These results establish FOXM1 as high-risk myeloma gene and provide support for the design and testing of FOXM1-targeted therapies specifically for the FOXM1(High) subset of myeloma.
| S-EPMC4826574 | biostudies-literature
Project description: Not available
| S-EPMC8168486 | biostudies-literature
Project description:Multiple myeloma (MM) is a plasma cell malignancy that is currently incurable. Finding new targets and designing drugs are crucial for the treatment of MM. The two datasets (GSE6691 and GSE39754) are used to screen highly expressed antigen on MM cells. HLA-E was an ideal target for it was a hub gene, and also located in one of the key clusters. Highly expression of HLA-E mRNA on MM cells was also confirmed by real-time qPCR testing the MM patients' samples in Shengjing hospital. Crystal structure of HLA-E was obtained from Protein Data Bank (PDB ID: 3CDG) which was used to design targeting peptides with Molecular Operating Environment software. By analyzing interaction between CD94/NKG2A and HLA-E, a peptide with twelve amino acids was screened as a model peptide. Peptides library was constructed by randomly replaced non-key amino acid. Peptide-protein docking method was used to identify high affinity peptides. PEPTIDE 1-3 and model peptide were synthesized and identified the affinity to HLA-E by flow cytometer and confocal laser microscopy. At last, PEPTIDE3 (NALDEYCEDKNR) was found with the highest affinity. Taking all, HLA-E is a new treatment target, and PEPTIDE 3 is an ideal high affinity target-binding peptide candidate.
| S-EPMC7655190 | biostudies-literature
Project description:Multiple myeloma (MM) is a devastating cancer with a highly heterogeneous outcome. Because of the heterogeneity of myeloma cells, risk stratification is important for making therapeutic regimens. Nevertheless, no immunohistochemical predictive and prognostic marker has been constructed yet. In the present study, we explored the prognostic value of proteolipid protein 2 (PLP2) in MM patients using immunohistochemistry (IHC). We assessed PLP2 expression in bone marrow (BM) biopsy specimens obtained from 87 newly diagnosed MM (NDMM) patients. Correlations between PLP2 expression and clinicopathological features were analyzed. PLP2 expression was present in high-risk MM patients, which was increased with disease progression and poor prognosis. PLP2 was increasing in parallel with high beta-2 microglobulin (β2-MG) and lactate dehydrogenase (LDH). Furthermore, MM patients with low PLP2 expression could achieve a favorable treatment response. PLP2 may be a novel biomarker for prognostic prediction and a therapeutic target for anti-MM treatments.
| S-EPMC7303762 | biostudies-literature
Project description:Simple Summary Multiple myeloma (MM) is the second most common haematological malignancy. Despite huge progress associated with the introduction of new antimyeloma drugs, MM remains an incurable disease. In this review, we discuss the role of the innate lymphoid system, its role in the pathogenesis of the disease, and the mechanisms by which innate lymphoid cells (ILC) can theoretically achieve therapeutic benefit in MM treatment. Abstract Innate lymphoid cells (ILCs) are a recently identified family of lymphocyte-like cells lacking a specific antigen receptor. They are part of the innate immune system. They play a key role in tissue homeostasis and also control inflammatory and neoplastic processes. In response to environmental stimuli, ILCs change their phenotype and functions, and influence the activity of other cells in the microenvironment. ILC dysfunction can lead to a wide variety of diseases, including cancer. ILC can be divided into three subgroups: ILC Group 1, comprising NK cells and ILC1; Group 2, including ILC2 alone; and Group 3, containing Lymphoid Tissue inducers (LTi) and ILC3 cells. While Group 1 ILCs mainly exert antitumour activity, Group 2 and Group 3 ILCs are protumorigenic in nature. A growing body of preclinical and clinical data support the role of ILCs in the pathogenesis of multiple myeloma (MM). Therefore, targeting ILCs may be of clinical benefit. In this manuscript, we review the available data on the role of ILCs in MM immunology and therapy.
| S-EPMC8507621 | biostudies-literature
Project description:Glucocorticoids (GC) are a cornerstone of combination therapies for multiple myeloma. However, patients ultimately develop resistance to GCs frequently based on decreased glucocorticoid receptor (GR) expression. An understanding of the direct targets of GC actions, which induce cell death, is expected to culminate in potential therapeutic strategies for inducing cell death by regulating downstream targets in the absence of a functional GR. The specific goal of our research is to identify primary GR targets that contribute to GC-induced cell death, with the ultimate goal of developing novel therapeutics around these targets that can be used to overcome resistance to GCs in the absence of GR. Using the MM.1S glucocorticoid-sensitive human myeloma cell line, we began with the broad platform of gene expression profiling to identify glucocorticoid-regulated genes further refined by combination treatment with phosphatidylinositol-3'-kinase inhibition (PI3Ki). To further refine the search to distinguish direct and indirect targets of GR that respond to the combination GC and PI3Ki treatment of MM.1S cells, we integrated 1) gene expression profiles of combination GC treatment with PI3Ki, which induces synergistic cell death; 2) negative correlation between genes inhibited by combination treatment in MM.1S cells and genes over-expressed in myeloma patients to establish clinical relevance and 3) GR chromatin immunoprecipitation with massively parallel sequencing (ChIP-Seq) in myeloma cells to identify global chromatin binding for the glucocorticoid receptor (GR). Using established bioinformatics platforms, we have integrated these data sets to identify a subset of candidate genes that may form the basis for a comprehensive picture of glucocorticoid actions in multiple myeloma. As a proof of principle, we have verified two targets, namely RRM2 and BCL2L1, as primary functional targets of GR involved in GC-induced cell death.
| S-EPMC4693629 | biostudies-literature
Project description:BackgroundMultiple myeloma (MM) is an incurable hematological tumor, which is closely related to hypoxic bone marrow microenvironment. However, the underlying mechanisms are still far from fully understood. We took integrated bioinformatics analysis with expression profile GSE110113 downloaded from National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) database, and screened out major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) as a hub gene related to hypoxia in MM.MethodsDifferentially expressed genes (DEGs) were filtrated with R package "limma". Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed using "clusterProfiler" package in R. Then, protein-protein interaction (PPI) network was established. Hub genes were screened out according to Maximal Clique Centrality (MCC). PrognoScan evaluated all the significant hub genes for survival analysis. ScanGEO was used for visualization of gene expression in different clinical studies. P and Cox p value < 0.05 was considered to be statistical significance.ResultsHLA-DPA1 was finally picked out as a hub gene in MM related to hypoxia. MM patients with down-regulated expression of HLA-DPA1 has statistically significantly shorter disease specific survival (DSS) (COX p = 0.005411). Based on the clinical data of GSE47552 dataset, HLA-DPA1 expression showed significantly lower in MM patients than that in healthy donors (HDs) (p = 0.017).ConclusionWe identified HLA-DPA1 as a hub gene in MM related to hypoxia. HLA-DPA1 down-regulated expression was associated with MM patients' poor outcome. Further functional and mechanistic studies are need to investigate HLA-DPA1 as potential therapeutic target.
| S-EPMC7513295 | biostudies-literature
Project description:HLA-DRB alleles are class II alleles that are associated with CD4+ T-cell immune response. DRB alleles are polymorphic and currently there are about 622 named in the IMGT/HLA sequence database. Each allele binds short peptides with high sensitivity and specificity. However, it has been suggested that majority of HLA alleles can be covered within few HLA supertypes, where different members of a supertype bind similar peptides showing distinct repertoires. Definition of DRB supertypes using binding data is limited to few (about 29) known alleles (< 5% of all known DRB alleles). Hence, we describe a strategy using structurally defined virtual pockets to group all known DRB alleles with regard to their overlapping peptide binding specificity.
| S-EPMC2957767 | biostudies-literature