期刊
HAEMATOLOGICA-THE HEMATOLOGY JOURNAL
卷 97, 期 4, 页码 622-630出版社
FERRATA STORTI FOUNDATION
DOI: 10.3324/haematol.2011.046821
关键词
spike (sub)bands; myeloma; molecular biology; survival; prognosis
类别
资金
- ICMJE
- Biological Research Centre at the Royal Marsden Hospital
- Ligue Nationale Contre le Cancer (equipe labellisee), Paris, France
- ARC (France)
- EU (OVERMYR)
- Hopp-Foundation, Germany
- University of Heidelberg, Germany
- National Centre for Tumor Diseases, Heidelberg, Germany
- Tumorzentrum Heidelberg/Mannheim, Germany
- Deutsche Krebshilfe, Bonn, Germany
- Deutsche Forschungsgemeinschaft, Bonn, Germany
Background Genetic abnormalities are common in patients with multiple myeloma, and may deregulate gene products involved in tumor survival, proliferation, metabolism and drug resistance. In particular, translocations may result in a high expression of targeted genes (termed spike expression) in tumor cells. We identified spike genes in multiple myeloma cells of patients with newly-diagnosed myeloma and investigated their prognostic value. Design and Methods Genes with a spike expression in multiple myeloma cells were picked up using box plot probe set signal distribution and two selection filters. Results In a cohort of 206 newly diagnosed patients with multiple myeloma, 2587 genes/expressed sequence tags with a spike expression were identified. Some spike genes were associated with some transcription factors such as MAF or MMSET and with known recurrent translocations as expected. Spike genes were not associated with increased DNA copy number and for a majority of them, involved unknown mechanisms. Of spiked genes, 36.7% clustered significantly in 149 out of 862 documented chromosome (sub) bands, of which 53 had prognostic value (35 bad, 18 good). Their prognostic value was summarized with a spike band score that delineated 23.8% of patients with a poor median overall survival (27.4 months versus not reached, P<0.001) using the training cohort of 206 patients. The spike band score was independent of other gene expression profiling-based risk scores, t(4; 14), or del17p in an independent validation cohort of 345 patients. Conclusions We present a new approach to identify spike genes and their relationship to patients' survival.
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