{"title":"Gene Expression Profiling Identifies CAV1, CD44, and TFRC as Potential Diagnostic Markers and Therapeutic Targets for Multiple Myeloma.","authors":"Awais Ali, Syed Luqman Ali, Waseef Ullah, Asifullah Khan","doi":"10.1007/s12013-025-01743-0","DOIUrl":null,"url":null,"abstract":"<p><p>Multiple myeloma (MM) is a highly malignant hematological tumor with a low overall survival rate, making the identification of innovative prognostic markers essential due to its complex and heterogeneous nature. Ferroptosis, an iron-dependent form of cell death driven by lipid peroxidation, is now recognized as crucial in tumor development and progression. Consequently, ferroptosis-related genes (FRGs) are emerging as promising therapeutic targets and prognostic indicators. However, the specific roles and predictive value of FRGs in MM still remain unclear. The current study was therefore conceived to examine the possible involvement of FRGs in MM. FRGs data was obtained from the FerrDb resource. The datasets GSE133346 and GSE166122, sourced from the Gene Expression Omnibus (GEO), provided gene expression data for both healthy and MM individuals. The differentially expressed-FRGs (DE-FRGs) were identified using the limma and DESeq2 packages in R. Functional pathways were analyzed through Gene Ontology (GO) and KEGG enrichment analyses. The miRWalk database was used for miRNA association and enrichment analysis with hub genes. Prognosis-related genes were evaluated using Kaplan-Meier survival analyses. We identified 1400 differentially expressed genes and cross-referenced them with FRGs, ultimately selecting 17 as DE-FRGs or hub genes. GO analysis revealed that the primary enriched functions of these hub genes are sister chromatid segregation, condensed chromosome centromeric region, C-C chemokine receptor activity, and C-C chemokine binding. KEGG pathway analysis showed that these overlapped genes were enriched in several pathways, including cell cycle, viral protein interaction with cytokine and cytokine receptor, as well as breast and prostate cancers involved pathways. Furthermore, significant enrichment was observed in glycolysis, gluconeogenesis, and the citrate cycle pathways based on miRNAs association with the candidate genes. The CAV1, CD44, TFRC, DPP4, and GJA1 are identified as top five significant hub DE-FRGs based on protein-protein interaction (PPI) analysis from multiple resources. Survival analysis eventually identified CAV1, CD44, and TFRC as the top-ranked DE-FRGs associated with overall survival, underscoring their crucial role in MM. This study identifies CAV1, CD44, and TFRC as key FRGs associated with the prognosis of MM, suggesting their potential as valuable prognostic markers and therapeutic targets to improve patient outcomes.</p>","PeriodicalId":510,"journal":{"name":"Cell Biochemistry and Biophysics","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Biochemistry and Biophysics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s12013-025-01743-0","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Multiple myeloma (MM) is a highly malignant hematological tumor with a low overall survival rate, making the identification of innovative prognostic markers essential due to its complex and heterogeneous nature. Ferroptosis, an iron-dependent form of cell death driven by lipid peroxidation, is now recognized as crucial in tumor development and progression. Consequently, ferroptosis-related genes (FRGs) are emerging as promising therapeutic targets and prognostic indicators. However, the specific roles and predictive value of FRGs in MM still remain unclear. The current study was therefore conceived to examine the possible involvement of FRGs in MM. FRGs data was obtained from the FerrDb resource. The datasets GSE133346 and GSE166122, sourced from the Gene Expression Omnibus (GEO), provided gene expression data for both healthy and MM individuals. The differentially expressed-FRGs (DE-FRGs) were identified using the limma and DESeq2 packages in R. Functional pathways were analyzed through Gene Ontology (GO) and KEGG enrichment analyses. The miRWalk database was used for miRNA association and enrichment analysis with hub genes. Prognosis-related genes were evaluated using Kaplan-Meier survival analyses. We identified 1400 differentially expressed genes and cross-referenced them with FRGs, ultimately selecting 17 as DE-FRGs or hub genes. GO analysis revealed that the primary enriched functions of these hub genes are sister chromatid segregation, condensed chromosome centromeric region, C-C chemokine receptor activity, and C-C chemokine binding. KEGG pathway analysis showed that these overlapped genes were enriched in several pathways, including cell cycle, viral protein interaction with cytokine and cytokine receptor, as well as breast and prostate cancers involved pathways. Furthermore, significant enrichment was observed in glycolysis, gluconeogenesis, and the citrate cycle pathways based on miRNAs association with the candidate genes. The CAV1, CD44, TFRC, DPP4, and GJA1 are identified as top five significant hub DE-FRGs based on protein-protein interaction (PPI) analysis from multiple resources. Survival analysis eventually identified CAV1, CD44, and TFRC as the top-ranked DE-FRGs associated with overall survival, underscoring their crucial role in MM. This study identifies CAV1, CD44, and TFRC as key FRGs associated with the prognosis of MM, suggesting their potential as valuable prognostic markers and therapeutic targets to improve patient outcomes.
期刊介绍:
Cell Biochemistry and Biophysics (CBB) aims to publish papers on the nature of the biochemical and biophysical mechanisms underlying the structure, control and function of cellular systems
The reports should be within the framework of modern biochemistry and chemistry, biophysics and cell physiology, physics and engineering, molecular and structural biology. The relationship between molecular structure and function under investigation is emphasized.
Examples of subject areas that CBB publishes are:
· biochemical and biophysical aspects of cell structure and function;
· interactions of cells and their molecular/macromolecular constituents;
· innovative developments in genetic and biomolecular engineering;
· computer-based analysis of tissues, cells, cell networks, organelles, and molecular/macromolecular assemblies;
· photometric, spectroscopic, microscopic, mechanical, and electrical methodologies/techniques in analytical cytology, cytometry and innovative instrument design
For articles that focus on computational aspects, authors should be clear about which docking and molecular dynamics algorithms or software packages are being used as well as details on the system parameterization, simulations conditions etc. In addition, docking calculations (virtual screening, QSAR, etc.) should be validated either by experimental studies or one or more reliable theoretical cross-validation methods.