2003
DOI: 10.3892/ijo.23.3.617
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Identification of signature genes by microarray for acute myeloid leukemia without maturation and acute promyelocytic leukemia with t(15;17)(q22;q12)(PML/RARα)

Abstract: Acute myeloid leukemia (AML) has distinct subgroups characterized by different maturation and specific chromosomal translocation. In order to gain insight into the gene expression activities in AML, we carried out a gene expression profiling study with 21 AML samples using cDNA microarrays, focusing on acute promyelocytic leukemia with specific translocation t(15;17)(q22;q12) [French-American-British or FAB-M3 with t(15;17)] and AML without maturation (FAB-M1) characterized by morphologically and phenotypicall… Show more

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Cited by 16 publications
(19 citation statements)
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References 45 publications
(44 reference statements)
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“…As opposed to using expression levels of either significantly increased or decreased genes, we applied novel mRNA-based noninvasive methods to identify the best single genes and two- to three-gene combinations for distinguishing polyps, IR, and exposure to a chemoprotective legume-enriched diet. Similar to previous studies (20, 21, 32, 49), we report that by using combinations of genes, the classification error rate can be significantly lowered. Two- and three-gene combinations thus provide robust classifiers with potential to noninvasively identify discriminative molecular signatures for differential diagnostic purposes.…”
Section: Resultssupporting
confidence: 90%
“…As opposed to using expression levels of either significantly increased or decreased genes, we applied novel mRNA-based noninvasive methods to identify the best single genes and two- to three-gene combinations for distinguishing polyps, IR, and exposure to a chemoprotective legume-enriched diet. Similar to previous studies (20, 21, 32, 49), we report that by using combinations of genes, the classification error rate can be significantly lowered. Two- and three-gene combinations thus provide robust classifiers with potential to noninvasively identify discriminative molecular signatures for differential diagnostic purposes.…”
Section: Resultssupporting
confidence: 90%
“…A number of laboratories using supervised learning algorithms have identified unique gene expression signatures associated with karyotypic abnormalities, normal karyotypes, and NPM1 mutation status. [31][32][33][34][35][36][37][38][39] In contrast, we wished to determine whether gene expression profiling using an entirely unsupervised approach could reveal intrinsic biologic groups of AML among a set of wellcharacterized older AML patients, with a high frequency of normal and unfavorable cytogenetic abnormalities. We further wished to determine whether the gene expression signatures we derived were useful in risk classification and therapeutic targeting in this poor-risk disease.…”
Section: Introductionmentioning
confidence: 99%
“…La translocation t(15;17) (q22;q21) est pré-sente dans 8,5 % des LAM : il s'agit dans tous les cas de leucémie aiguë promyélocytaire : dix cas de la forme hypergranulaire (LAM 3/FAB), douze cas de la forme variante microgranulaire (M3v), deux cas de LAM 3 avec blastes basophiles dans le sang (M3/M3v) et un cas de la forme basophile diagnostiqué initialement comme LAM 1 (Tableau 3). En effet, plus de 90 % des patients atteints de LAM 3 (FAB) ont la translocation spécifique t(15;17) (q22;q21) [29]. L'inversion du 16 est retrouvée dans quatre cas (1,4 %) : un cas de LAM 4 et trois cas de LAM 4 Eo (LAM avec composante monocytaire associée à une maturation éosinophile) (Tableau 3).…”
Section: Discussionunclassified