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Investigation of possibly related genes determined from bioinformatic analysis of multiple myeloma whole-genome transcriptome data

2020
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Advisor: Doç. Dr. Neslihan Abacı

Abstract (EN)

Taking a part of the plasma cell dyscrasias group, Multiple Myeloma (MM) is characterized by uncontrolled proliferation of malignant plasma cells originating from bone marrow. Monoclonal Gammopathy of undetermined significance (MGUS) is an asymptomatic premalignant plasma dyscrasias. The expression levels of genes have been investigated in our previous study by transcriptome from cell pools of multiple myeloma patients and healthy bone marrow controls. 13 candidate genes detected out of transcriptome data are very valuable and specific. In order to reveal the direct or indirect relevancy of these genes in MM pathogenesis, we validated these genes in new patient and control groups. In our study, expression levels of candidate genes acquired from the bone marrow of 38 untreated newly diagnosed MM patients, 23 MGUS and 16 control group were examined by qRT-PCR. The results were analyzed in SPSS.25 statistical program. The expression of ERAP1, HYOU1 and OTUD1 genes were not statistically significant according to MM, MGUS and control group. Expression levels of the remaining 10 genes that we investigated in myeloma pathogenesis showed statistically significant elevation compared to control group. Particularly, COPE and ISG20 may be suggested as early diagnostic markers in malignant transformation from MGUS to MM. Performing the validation of candidate genes, our study has added up new insights into the pathogenesis of MM which is still unclear. Our investigations have promising features in terms of containing new therapeutic targets such as TRIB1 needed in MM treatment and TMED9 which may have prognostic value in the diagnosis of MM. Key Words: Multiple Myeloma, MGUS, Transcriptome, qRT-PCR, Plasma Cell Dyscrasia

Author

Dr. Melda Sarıman

How to Cite

Melda Sarıman (Doctorate thesis). Investigation of possibly related genes determined from bioinformatic analysis of multiple myeloma whole-genome transcriptome data, 2020, İstanbul University.

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