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题目:: Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells.
作者:: Zhan(Fenghuang),Hardin(Johanna),Kordsmeier(Bob),Bumm(Klaus),Zheng(Mingzhong),Tian(Erming),Sanderson(Ralph),Yang(Yang),Wilson(Carla),Zangari(Maurizio),Anaissie(Elias),Morris(Christopher),Muwalla(Firas),van Rhee(Frits),Fassas(Athanasios),Crowley(John),Tricot(Guido),Barlogie(Bart),Shaughnessy(John)
状态:: 发布时间2002-02-25 , 更新时间 2007-11-14
期刊:: Blood
摘要:: Bone marrow plasma cells (PCs) from 74 patients with newly diagnosed multiple myeloma (MM), 5 with monoclonal gammopathy of undetermined significance (MGUS), and 31 healthy volunteers (normal PCs) were purified by CD138(+) selection. Gene expression of purified PCs and 7 MM cell lines were profiled using high-density oligonucleotide microarrays interrogating about 6800 genes. On hierarchical clustering analysis, normal and MM PCs were differentiated and 4 distinct subgroups of MM (MM1, MM2, MM3, and MM4) were identified. The expression pattern of MM1 was similar to normal PCs and MGUS, whereas MM4 was similar to MM cell lines. Clinical parameters linked to poor prognosis, abnormal karyotype (P =.002) and high serum beta(2)-microglobulin levels (P =.0005), were most prevalent in MM4. Also, genes involved in DNA metabolism and cell cycle control were overexpressed in a comparison of MM1 and MM4. In addition, using chi(2) and Wilcoxon rank sum tests, 120 novel candidate disease genes were identified that discriminate normal and malignant PCs (P <.0001); many are involved in adhesion, apoptosis, cell cycle, drug resistance, growth arrest, oncogenesis, signaling, and transcription. A total of 156 genes, including FGFR3 and CCND1, exhibited highly elevated ("spiked") expression in at least 4 of the 74 MM cases (range, 4-25 spikes). Elevated expression of these 2 genes was caused by the translocation t(4;14)(p16;q32) or t(11;14)(q13;q32). Thus, novel candidate MM disease genes have been identified using gene expression profiling and this profiling has led to the development of a gene-based classification system for MM.
语言:: eng
DOI:

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