Author
Mignon L. Loh
Other affiliations: Children's Oncology Group, Brigham and Women's Hospital, Harvard University ...read more
Bio: Mignon L. Loh is an academic researcher from University of California, San Francisco. The author has contributed to research in topics: Leukemia & Juvenile myelomonocytic leukemia. The author has an hindex of 82, co-authored 407 publications receiving 35918 citations. Previous affiliations of Mignon L. Loh include Children's Oncology Group & Brigham and Women's Hospital.
Papers published on a yearly basis
Papers
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TL;DR: A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
Abstract: Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case. A class discovery procedure automatically discovered the distinction between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) without previous knowledge of these classes. An automatically derived class predictor was able to determine the class of new leukemia cases. The results demonstrate the feasibility of cancer classification based solely on gene expression monitoring and suggest a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
12,530 citations
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St. Jude Children's Research Hospital1, Washington University in St. Louis2, Memorial Sloan Kettering Cancer Center3, Katholieke Universiteit Leuven4, University of California, San Francisco5, University of Toronto6, University of Padua7, University of Colorado Denver8, University of Florida9, Boston Children's Hospital10, University of New Mexico11, University of Virginia12
TL;DR: The mutational spectrum is similar to myeloid tumours, and moreover, the global transcriptional profile of ETP ALL was similar to that of normal andMyeloid leukaemia haematopoietic stem cells, suggesting that addition of myeloids-directed therapies might improve the poor outcome of E TP ALL.
Abstract: Early T-cell precursor acute lymphoblastic leukaemia (ETP ALL) is an aggressive malignancy of unknown genetic basis. We performed whole-genome sequencing of 12 ETP ALL cases and assessed the frequency of the identified somatic mutations in 94 T-cell acute lymphoblastic leukaemia cases. ETP ALL was characterized by activating mutations in genes regulating cytokine receptor and RAS signalling (67% of cases; NRAS, KRAS, FLT3, IL7R, JAK3, JAK1, SH2B3 and BRAF), inactivating lesions disrupting haematopoietic development (58%; GATA3, ETV6, RUNX1, IKZF1 and EP300) and histone-modifying genes (48%; EZH2, EED, SUZ12, SETD2 and EP300). We also identified new targets of recurrent mutation including DNM2, ECT2L and RELN. The mutational spectrum is similar to myeloid tumours, and moreover, the global transcriptional profile of ETP ALL was similar to that of normal and myeloid leukaemia haematopoietic stem cells. These findings suggest that addition of myeloid-directed therapies might improve the poor outcome of ETP ALL.
1,425 citations
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St. Jude Children's Research Hospital1, University of Washington2, University of New Mexico3, National Institutes of Health4, Washington University in St. Louis5, University of Florida6, Ohio State University7, New York University8, University of Alabama at Birmingham9, University of Texas Southwestern Medical Center10, University of Pennsylvania11, Royal Children's Hospital12, University of Toronto13, Texas A&M University14, University of Utah15, Emory University16, Mayo Clinic17, University of Chicago18, University of Texas Health Science Center at San Antonio19, University of Texas MD Anderson Cancer Center20, Yeshiva University21, University of California, San Francisco22, University of Colorado Denver23
TL;DR: Ph-like ALL was found to be characterized by a range of genomic alterations that activate a limited number of signaling pathways, all of which may be amenable to inhibition with approved tyrosine kinase inhibitors.
Abstract: BACKGROUND Philadelphia chromosome–like acute lymphoblastic leukemia (Ph-like ALL) is characterized by a gene-expression profile similar to that of BCR–ABL1–positive ALL, alterations of lymphoid transcription factor genes, and a poor outcome. The frequency and spectrum of genetic alterations in Ph-like ALL and its responsiveness to tyrosine kinase inhibition are undefined, especially in adolescents and adults. METHODS We performed genomic profiling of 1725 patients with precursor B-cell ALL and detailed genomic analysis of 154 patients with Ph-like ALL. We examined the functional effects of fusion proteins and the efficacy of tyrosine kinase inhibitors in mouse pre-B cells and xenografts of human Ph-like ALL. RESULTS Ph-like ALL increased in frequency from 10% among children with standard-risk ALL to 27% among young adults with ALL and was associated with a poor outcome. Kinase-activating alterations were identified in 91% of patients with Ph-like ALL; rearrangements involving ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B, TSLP, or TYK2 and sequence mutations involving FLT3, IL7R, or SH2B3 were most common. Expression of ABL1, ABL2, CSF1R, JAK2, and PDGFRB fusions resulted in cytokine-independent proliferation and activation of phosphorylated STAT5. Cell lines and human leukemic cells expressing ABL1, ABL2, CSF1R, and PDGFRB fusions were sensitive in vitro to dasatinib, EPOR and JAK2 rearrangements were sensitive to ruxolitinib, and the ETV6–NTRK3 fusion was sensitive to crizotinib. CONCLUSIONS Ph-like ALL was found to be characterized by a range of genomic alterations that activate a limited number of signaling pathways, all of which may be amenable to inhibition with approved tyrosine kinase inhibitors. Trials identifying Ph-like ALL are needed to assess whether adding tyrosine kinase inhibitors to current therapy will improve the survival of patients with this type of leukemia. (Funded by the American Lebanese Syrian Associated Charities and others.)
1,077 citations
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TL;DR: It is shown that five different T cell oncogenes are often aberrantly expressed in the absence of chromosomal abnormalities, and HOX11L2 activation is identified as a novel event in T cell leukemogenesis.
1,063 citations
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Brigham and Women's Hospital1, Brown University2, University of Pennsylvania3, Leicester Royal Infirmary4, St Vincent Hospital5, Université de Montréal6, University of Michigan7, University of New Mexico8, Dartmouth College9, University of Virginia10, Harvard University11, Roosevelt Institute12, Howard Hughes Medical Institute13
TL;DR: The findings support a model for FPD/AML in which haploinsufficiency of CBFA2 causes an autosomal dominant congenital platelet defect and predisposes to the acquisition of additional mutations that cause leukaemia.
Abstract: Familial platelet disorder with predisposition to acute myelogenous leukaemia (FPD/AML, MIM 601399) is an autosomal dominant disorder characterized by qualitative and quantitative platelet defects, and propensity to develop acute myelogenous leukaemia (AML). Informative recombination events in 6 FPD/AML pedigrees with evidence of linkage to markers on chromosome 21q identified an 880-kb interval containing the disease gene. Mutational analysis of regional candidate genes showed nonsense mutations or intragenic deletion of one allele of the haematopoietic transcription factor CBFA2 (formerly AML1) that co-segregated with the disease in four FPD/AML pedigrees. We identified heterozygous CBFA2 missense mutations that co-segregated with the disease in the remaining two FPD/AML pedigrees at phylogenetically conserved amino acids R166 and R201, respectively. Analysis of bone marrow or peripheral blood cells from affected FPD/AML individuals showed a decrement in megakaryocyte colony formation, demonstrating that CBFA2 dosage affects megakaryopoiesis. Our findings support a model for FPD/AML in which haploinsufficiency of CBFA2 causes an autosomal dominant congenital platelet defect and predisposes to the acquisition of additional mutations that cause leukaemia.
1,028 citations
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
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TL;DR: It is shown that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation, and an algorithm called LARS‐EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lamba.
Abstract: Summary. We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation. In addition, the elastic net encourages a grouping effect, where strongly correlated predictors tend to be in or out of the model together.The elastic net is particularly useful when the number of predictors (p) is much bigger than the number of observations (n). By contrast, the lasso is not a very satisfactory variable selection method in the
16,538 citations
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TL;DR: Variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals were characterized using complementary DNA microarrays representing 8,102 human genes, providing a distinctive molecular portrait of each tumour.
Abstract: Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cell's identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.
14,768 citations
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TL;DR: The contributions of this special issue cover a wide range of aspects of variable selection: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
Abstract: Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene expression array analysis, and combinatorial chemistry. The objective of variable selection is three-fold: improving the prediction performance of the predictors, providing faster and more cost-effective predictors, and providing a better understanding of the underlying process that generated the data. The contributions of this special issue cover a wide range of aspects of such problems: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
14,509 citations
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TL;DR: In comparative timings, the new algorithms are considerably faster than competing methods and can handle large problems and can also deal efficiently with sparse features.
Abstract: We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multinomial regression problems while the penalties include l(1) (the lasso), l(2) (ridge regression) and mixtures of the two (the elastic net). The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.
13,656 citations