MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia

By Scott A. Armstrong, J. Staunton, L. Silverman, R. Pieters, M. L. Boer, M. Minden, S. Sallan, Eric S. Lander, Todd R. Golub, S. Korsmeyer. Nature Genetics, 2002

1,548 citations recorded by the source corpus.

Subfields: Hematology, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/f5f2e3a5d70a7d1fe428b5172cdd52460099fc39

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In Hematology

1. Scott A. Armstrong

In Public Health, Environmental and Occupational Health

1. Dacheng Tao
2. Stefano Canali

Citations in the corpus

• Biclustering in data mining (2008, background): “…point out: • ALL vs. AML data set [51,52]; • HuGE (Human GEnome) data set [53,54]; • Colon Cancer data set [55]; • B-cell lymphoma data set [56,57]; • Yeast Microarray data set [58,59]; • Lung Cancer data set [60]; • MLL Leukemia data set [61].”
• Clustering cancer gene expression data: a comparative study (2008, neutral): “Armstrong-V1 [52] Affy Blood 72 2 24,48 12582 1081 Armstrong-V2 [52] Affy Blood 72 3 24,20,28 12582 2194 Bhattacharjee [9] Affy Lung 203 5 139,17,6,21,20 12600 1543 Chowdary [13] Affy Breast, Colon 104 2 62,42 22283 182 Dyrskjot [14] Affy Bladder 40 3 9,20,11 7129 1203 Golub-V1 [3] Affy Bone marrow ”
• Linear discriminant analysis for the small sample size problem: an overview (2014, positive): “The training data contains 57 leukemia samples (20 ALL, 17 MLL and 20 AML) whereas the testing data contains 15 samples (4 ALL, 3 MLL and 8 AML).”
• Leukemia Proto-Oncoprotein MLL Forms a SET1-Like Histone Methyltransferase Complex with Menin To Regulate Hox Gene Expression (2004, background): “HoxA9 is a critical target gene of MLL fusion proteins and is consistently expressed in leukemic cells carrying MLL translocations, serving as a molecular signature for this subtype of acute leukemia (5, 7, 48, 63).”
• MLL-rearranged Leukemia is Dependent on Aberrant H3K79 Methylation by DOT1L (2011, neutral): “Genome-wide analysis of MLL-rearranged leukemia samples has revealed unique transcriptional and H3K79 methylation profiles that can distinguish MLL-rearranged leukemias from MLL-germline leukemias (Armstrong et al., 2002; Ross et al., 2004; Krivtsov et al., 2008).”
• Feature Selection Based on Structured Sparsity: A Comprehensive Study (2017, methodology): “We did our experiments on 11 data sets: one WebKB data set WebKB-WC,2 one image classification data set coil20 [153], two face data sets including AR and Umist,3 two UCI data sets4 including protein and vehicle, and five microarray data sets including CAR [154], LUNG [155], MLL [156], GLA [157], and”
• Novel Unsupervised Feature Filtering of Biological Data (2006, methodology): “Nevertheless, since GLY, THR, LYS and MET (the fourth ranked AAC, according to the FS1 method) represent different functional groups, we conclude that the FS1/BE ranking is consistent with selecting amino acids that carry different physico-chemical properties. of Armstrong et al .”
• QUBIC: a qualitative biclustering algorithm for analyses of gene expression data (2009, background): “We found that these subtype-specific biclusters are informative and in most cases consistent with results reported in previous studies (35,36).”
• Prognostically useful gene-expression profiles in acute myeloid leukemia. (2004, background): “(%) <35 yr 35–60 yr ≥60 yr 76 (27) 177 (62) 32 (11)”
• Supervised, Unsupervised, and Semi-Supervised Feature Selection: A Review on Gene Selection (2016, methodology): “2012b) [98] Null LDA technique & SRBCT [76]; NNC Sensitivity analysis; k-fold CV & Lung [68]; & Leukemia [66], [67];”
• Relation Between Permutation-Test P Values and Classifier Error Estimates (2003, methodology): “…between the permutation-test p value and the error estimates, we begin with a simulation study involving the kNN rule, which has been used in a number of expression-based classification studies (Pomeroy et al., 2002; Lesnick, Dacwag, & Golub, 2002; Armstrong et al., 2002; Yeang et al., 2001).”
• Selective Killing of Mixed Lineage Leukemia Cells by a Potent Small-Molecule DOT1L Inhibitor (2011, positive): “HOXA9 andMEIS1 overex- pression is a hallmark of MLL-rearranged leukemias (Armstrong et al., 2002; Ferrando et al., 2003; Ross et al., 2003, 2004; Rozov- skaia et al., 2001; Yeoh et al., 2002).”
• Autoantibody signatures in prostate cancer. (2005, methodology): “A prediction model was built using the 22 phage peptides selected from leave-one-out-crossvalidation strategy of GA/KNN.(32) The column “call” is the prediction of a sample by the model along with the confidence value.”