Centrosome associated genes pattern for risk sub-stratification in multiple myeloma



Rok publikování 2016
Druh Článek v odborném periodiku
Časopis / Zdroj Journal of Translational Medicine
Fakulta / Pracoviště MU

Lékařská fakulta

www https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4884414/pdf/12967_2016_Article_906.pdf
Doi http://dx.doi.org/10.1186/s12967-016-0906-9
Obor Genetika a molekulární biologie
Klíčová slova Multiple myeloma; Gene expression profiling; Risk stratification
Přiložené soubory
Popis Background: The genome of multiple myeloma (MM) cells is extremely unstable, characterized by a complex combination of structure and numerical abnormalities. It seems that there are several "myeloma subgroups" which differ in expression profile, clinical manifestations, prognoses and treatment response. In our previous work, the list of 35 candidate genes with a known role in carcinogenesis and associated with centrosome structure/function was used as a display of molecular heterogeneity with an impact in myeloma pathogenesis. The current study was devoted to establish a risk stratification model based on the aforementioned candidate genes. Methods: A total of 151 patients were included in this study. CD138+ cells were separated by magnetic-activated cell sorting (MACS). Gene expression profiling (GEP) and Interphase FISH with cytoplasmic immunoglobulin light chain staining (cIg FISH) were performed on plasma cells (PCs). All statistical analyses were performed using free-ware R and its additional packages. Training and validation cohort includes 73 and 78 patients, respectively. Results: We have finally established a model that includes 12 selected genes (centrosome associated gene pattern, CAGP) which appears to be an independent prognostic factor for MM stratification. We have shown that the new CAGP model can sub-stratify prognosis in patients without TP53 loss as well as in IMWG high risk patients' group. Conclusions: We assume that newly established risk stratification model complements the current prognostic panel used in multiple myeloma and refines the classification of patients in relation to the disease risks. This approach can be used independently as well as in combination with other factors.
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