Article detail · 2019
Investigation of Gene Expressions of Myeloma Cells in the Bone Marrow of Multiple Myeloma Patients by Transcriptome Analysis
- Year
- 2019
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Balkan Medical Journal
- Catalog match (ISSN) Balkan Medical Journal
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
English (OpenAlex)
Background: Multiple myeloma is a plasma cell dyscrasia characterized by transformation of B cells into malignant cells. Although there are data regarding the molecular pathology of multiple myeloma, the molecular mechanisms of the disease have not been fully elucidated. Aims: To investigate the gene expression profiles in bone marrow myeloma cells via RNA-sequencing technology. Study Design: Cell study. Methods: Myeloma cells from four patients with untreated multiple myeloma and B cells from the bone marrow of four healthy donors were sorted using a FACSAria II flow cytometer. The patient pool of myeloma cells and the control pool of B cells were the two comparative groups. A transcriptome analysis was performed and the results were analyzed using bioinformatics tools. Results: In total, 18.806 transcripts (94.4%) were detected in the pooled multiple myeloma patient cells. A total of 992 regions were detected as new exon candidates or alternative splicing regions. In addition, 490 mutations (deletions or insertions), 1.397 single nucleotide variations, 415 fusion transcripts, 132 frameshift mutations, and 983 fusions, which were reported before in the National Center for Biotechnology Information, were detected with unknown functions in patients. A total of 35.268 transcripts were obtained (71%) (25.355 transcripts were defined previously) in the control pool. In this preliminary study, the first 50 genes were analyzed with the MSigDB, Enrichr, and Panther gene set enrichment analysis programs. The molecular functions, cellular components, pathways, and biological processes of the genes were obtained and statistical values were determined using bioinformatics tools and are presented as a supplemental file. Conclusion: are identified as possible candidate genes associated with myelomagenesis.
Topics
- Multiple Myeloma Research and Treatments
- vaccines and immunoinformatics approaches
- Biological Research and Disease Studies
Primary topic Multiple Myeloma Research and Treatments