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KOS 2007: From Oncogenome Mining to Functional Validation of Multiple Myeloma Cancer Genes
By Giovanni Tonon, MD
Giovanni Tonon, MD
Dana Farber Cancer Institute
Medical Oncology Dept.
Boston, MA, USA
06.27.07



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Dana Farber Cancer Institute
Medical Oncology Dept.
Boston, MA, USA

SUMMARY:
by Lynne Lederman, PhD

An aCGH platform and GEP were used to analyzed cells from newly diagnosed patients with myeloma before and after treatment, revealing at least 4 distinct genomic patterns. These were further divided into subgroups based on chromosomal abnormalities (non-negative matrix factorization or gNMF analysis of aCGH profiles). These subgroups were associated with different prognoses. Additional approaches included Significance Analysis of Microarrays (SAM), Gene-eight measure of RNA expression, and Gene Set Enrichment Analysis (GSEA) in specific myeloma subgroups defined by the gNMF analysis. GSEA comparing myeloma and normal cells identified pathways with increased levels of expression, including some altered in all myeloma cells independent of subgroup. These included the proteasome pathway, suggesting that proteasome inhibitors might be active in all myeloma subgroups, as well as p53, K-ras, and mTOR (mammalian target of rapamycin) pathways. Other pathways altered in some but not all subgroups included those involved with interleukin and growth factors, and the Wnt and Akt pathways.


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