Journal ArticleDOI
Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning
Margaret A. Shipp,Kenneth N. Ross,Pablo Tamayo,Andrew P. Weng,Jeffery L. Kutok,Ricardo C.T. Aguiar,Michelle Gaasenbeek,Michael Angelo,Michael R. Reich,Geraldine S. Pinkus,Tane S. Ray,Margaret A. Koval,Andrew Norton,T. Andrew Lister,Jill P. Mesirov,Donna Neuberg,Eric S. Lander,Jon C. Aster,Todd R. Golub +18 more
TLDR
Genes implicated in DLBCL outcome included some that regulate responses to B-cell–receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis, and identify rational targets for intervention.Abstract:
Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of pa- tients with very different five-year overall survival rates (70% versus 12%). The model also ef- fectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention. © 2002 Nature Publishing Group http://medicine.nature.comread more
Citations
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Journal ArticleDOI
Gene expression profiling predicts clinical outcome of breast cancer
Laura J. van't Veer,Hongyue Dai,Marc J. van de Vijver,Yudong D. He,Augustinus A. M. Hart,Mao Mao,Hans Peterse,Karin van der Kooy,Matthew J. Marton,Anke T. Witteveen,George J. Schreiber,Ron M. Kerkhoven,Christopher J. Roberts,Peter S. Linsley,René Bernards,Stephen H. Friend +15 more
TL;DR: DNA microarray analysis on primary breast tumours of 117 young patients is used and supervised classification is applied to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis, providing a strategy to select patients who would benefit from adjuvant therapy.
Journal ArticleDOI
Repeated observation of breast tumor subtypes in independent gene expression data sets
Therese Sørlie,Robert Tibshirani,Joel S. Parker,Trevor Hastie,James Stephen Marron,Andrew B. Nobel,Shibing Deng,Hilde Johnsen,Robert Pesich,Stephanie Geisler,Janos Demeter,Charles M. Perou,Per Eystein Lønning,Patrick O. Brown,Anne Lise Børresen-Dale,David Botstein +15 more
TL;DR: The results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.
Journal ArticleDOI
Confirmation of the molecular classification of diffuse large B-cell lymphoma by immunohistochemistry using a tissue microarray
Christine P. Hans,Dennis D. Weisenburger,Timothy C. Greiner,Randy D. Gascoyne,Jan Delabie,German Ott,H. Konrad Muller-Hermelink,Elias Campo,Rita M. Braziel,Elaine S. Jaffe,Zenggang Pan,Pedro Farinha,Lynette M. Smith,Brunangelo Falini,Alison H. Banham,Andreas Rosenwald,Louis M. Staudt,Joseph M. Connors,James O. Armitage,Wing C. Chan +19 more
TL;DR: In summary, immunostains can be used to determine the GCB and non-GCB subtypes of DLBCL and predict survival similar to the cDNA microarray.
Journal ArticleDOI
A molecular signature of metastasis in primary solid tumors.
TL;DR: It is found that solid tumors carrying the gene-expression signature were most likely to be associated with metastasis and poor clinical outcome, suggesting that the metastatic potential of human tumors is encoded in the bulk of aPrimary tumor, thus challenging the notion that metastases arise from rare cells within a primary tumor that have the ability to metastasize.
Journal ArticleDOI
Extrinsic versus intrinsic apoptosis pathways in anticancer chemotherapy.
TL;DR: Understanding the molecular events that regulate apoptosis in response to anticancer chemotherapy, and how cancer cells evade apoptotic death, provides novel opportunities for a more rational approach to develop molecular-targeted therapies for combating cancer.
References
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Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Ash A. Alizadeh,Michael B. Eisen,R. Eric Davis,Izidore S. Lossos,Andreas Rosenwald,Jennifer C. Boldrick,Hajeer Sabet,Truc Tran,Xin Yu,John Powell,Liming Yang,Gerald E. Marti,Troy Moore,James I. Hudson,Li-Sheng Lu,David B. Lewis,Robert Tibshirani,Gavin Sherlock,Wing C. Chan,Timothy C. Greiner,Dennis D. Weisenburger,James O. Armitage,Roger A. Warnke,Ronald Levy,Wyndham H. Wilson,M. R. Grever,John C. Byrd,David Botstein,Patrick O. Brown,Louis M. Staudt +29 more
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A predictive model for aggressive non-Hodgkin's lymphoma
Margaret A. Shipp,D. P. Harrington,James R. Anderson,James Olen Armitage,Gianni Bonadonna,G. Brittinger,Fernando Cabanillas,George P. Canellos,Bertrand Coiffier,Joseph M. Connors,R. A. Cowan,D. Crowther,Steve Dahlberg,M. Engelhard,Richard I. Fisher,Christian Gisselbrecht,Sandra J. Horning,Eric Lepage,T. A. Lister,J. H. Meerwaldt,Emili Montserrat,Nis I. Nissen,M. M. Oken,Bruce A. Peterson,Carlo Tondini,W. A. Velasquez,B. Y. Yeap +26 more
TL;DR: The international index and the age-adjusted international index should be used in the design of future therapeutic trials in patients with aggressive non-Hodgkin's lymphoma and in the selection of appropriate therapeutic approaches for individual patients.
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