Combining gene mutation with gene expression data improves outcome prediction in myelodysplastic syndromes

[1]  G. Schmidt,et al.  New insights , 2004 .

[2]  C Haferlach,et al.  Landscape of genetic lesions in 944 patients with myelodysplastic syndromes , 2013, Leukemia.

[3]  Beau Dabbs,et al.  Summary and discussion of : “ Controlling the False Discovery Rate : A Practical and Powerful Approach to Multiple Testing , 2014 .

[4]  M. Stratton,et al.  Clinical and biological implications of driver mutations in myelodysplastic syndromes. , 2013, Blood.

[5]  Masao Nagasaki,et al.  Recurrent mutations in multiple components of the cohesin complex in myeloid neoplasms , 2012, Nature Genetics.

[6]  G. Mufti,et al.  Recent advances in understanding the molecular pathogenesis of myelodysplastic syndromes , 2013, British journal of haematology.

[7]  P. Greenberg.  The multifaceted nature of myelodysplastic syndromes: clinical, molecular, and biological prognostic features. , 2013, Journal of the National Comprehensive Cancer Network : JNCCN.

[8]  Benjamin J. Raphael,et al.  Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. , 2013, The New England journal of medicine.

[9]  M. Cazzola,et al.  The transporter ABCB7 is a mediator of the phenotype of acquired refractory anemia with ring sideroblasts , 2013, Leukemia.

[10]  K. Kinzler,et al.  Cancer Genome Landscapes , 2013, Science.

[11]  P. Woll,et al.  Silencing of ASXL1 impairs the granulomonocytic lineage potential of human CD34+ progenitor cells , 2013, British journal of haematology.

[12]  Benjamin L Ebert,et al.  Molecular pathophysiology of myelodysplastic syndromes. , 2013, Annual review of pathology.

[13]  A. Raza,et al.  The genetic basis of phenotypic heterogeneity in myelodysplastic syndromes , 2012, Nature Reviews Cancer.

[14]  Iannis Aifantis,et al.  ASXL1 mutations promote myeloid transformation through loss of PRC2-mediated gene repression. , 2012, Cancer cell.

[15]  Claude Preudhomme,et al.  Mutations affecting mRNA splicing define distinct clinical phenotypes and correlate with patient outcome in myelodysplastic syndromes. , 2012, Blood.

[16]  A. Jankowska,et al.  Mutations in the spliceosome machinery, a novel and ubiquitous pathway in leukemogenesis. , 2012, Blood.

[17]  M. Walter,et al.  Genetics of myelodysplastic syndromes: new insights. , 2011, Hematology. American Society of Hematology. Education Program.

[18]  Peter J Campbell,et al.  Clinical significance of SF3B1 mutations in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms , 2011, Blood.

[19]  R. Levine,et al.  Molecular biology of myelodysplastic syndromes. , 2011, Seminars in oncology.

[20]  A Kohlmann,et al.  Gene expression profiling in MDS and AML: potential and future avenues , 2011, Leukemia.

[21]  M. Stratton.  Exploring the Genomes of Cancer Cells: Progress and Promise , 2011, Science.

[22]  Trevor Hastie,et al.  Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent. , 2011, Journal of statistical software.

[23]  Timothy J. Durham,et al.  "Systematic" , 1966, Comput. J..

[24]  Benjamin L Ebert,et al.  Unraveling the molecular pathophysiology of myelodysplastic syndromes. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[25]  Renato Paro,et al.  Silencing chromatin: comparing modes and mechanisms , 2011, Nature Reviews Genetics.

[26]  T. Mikkelsen,et al.  The NIH Roadmap Epigenomics Mapping Consortium , 2010, Nature Biotechnology.

[27]  M Cazzola,et al.  Deregulated gene expression pathways in myelodysplastic syndrome hematopoietic stem cells , 2010, Leukemia.

[28]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[29]  Robert Tibshirani,et al.  Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression. , 2009, Blood.

[30]  Torsten Haferlach,et al.  Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome. , 2009, Blood.

[31]  Joshua M. Korn,et al.  Comprehensive genomic characterization defines human glioblastoma genes and core pathways , 2008, Nature.

[32]  M. Minden,et al.  Myelodysplastic syndromes: the complexity of stem-cell diseases , 2007, Nature Reviews Cancer.

[33]  B. Göttgens,et al.  The SCL transcriptional network and BMP signaling pathway interact to regulate RUNX1 activity , 2007, Proceedings of the National Academy of Sciences.

[34]  Li Wang,et al.  Gene expression profiles of CD34+ cells in myelodysplastic syndromes: involvement of interferon-stimulated genes and correlation to FAB subtype and karyotype. , 2006, Blood.

[35]  S. Kajigaya,et al.  Distinctive gene expression profiles of CD34 cells from patients with myelodysplastic syndrome characterized by specific chromosomal abnormalities. , 2004, Blood.

[36]  K. Kinzler,et al.  Cancer genes and the pathways they control , 2004, Nature Medicine.

[37]  Gordon K Smyth,et al.  Statistical Applications in Genetics and Molecular Biology Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments , 2011 .

[38]  A. Hutchinson,et al.  Mutation of a Putative Mitochondrial Iron Transporter Gene (ABC7) in X-Linked Sideroblastic Anemia and Ataxia (XLSA/A) , 1999, Human molecular genetics.

[39]  T Hamblin,et al.  International scoring system for evaluating prognosis in myelodysplastic syndromes. , 1997, Blood.

[40]  F. Harrell,et al.  Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors , 2005 .

[41]  Daniel B. Mark,et al.  TUTORIAL IN BIOSTATISTICS MULTIVARIABLE PROGNOSTIC MODELS: ISSUES IN DEVELOPING MODELS, EVALUATING ASSUMPTIONS AND ADEQUACY, AND MEASURING AND REDUCING ERRORS , 1996 .

[42]  J Alter,et al.  Progress and Promise , 1919, Nature.

[43]  D.,et al.  Regression Models and Life-Tables , 2022 .