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Transcription profiling of human CLL - a genomic approach to improve prognosis and predict therapeutic response in chronic lymphocytic leukemia - super series

ABSTRACT: This SuperSeries is composed of the following subset Series:; GSE10137: A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia (Mayo_Ohio); GSE10138: A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia (Duke_VA) Experiment Overall Design: Refer to individual Series

ORGANISM(S): Homo sapiens

SUBMITTER: Daphne Friedman

PROVIDER: E-GEOD-10139 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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A genomic approach to improve prognosis and predict therapeutic response in chronic lymphocytic leukemia.

Friedman Daphne R DR Weinberg J Brice JB Barry William T WT Goodman Barbara K BK Volkheimer Alicia D AD Bond Karen M KM Chen Youwei Y Jiang Ning N Moore Joseph O JO Gockerman Jon P JP Diehl Louis F LF Decastro Carlos M CM Potti Anil A Nevins Joseph R JR

Clinical cancer research : an official journal of the American Association for Cancer Research 20091027 22

<h4>Purpose</h4>Chronic lymphocytic leukemia (CLL) is a B-cell malignancy characterized by a variable clinical course. Several parameters have prognostic capabilities but are associated with altered response to therapy in only a small subset of patients.<h4>Experimental design</h4>We used gene expression profiling methods to generate predictors of therapy response and prognosis. Genomic signatures that reflect progressive disease and responses to chemotherapy or chemoimmunotherapy were created u ...[more]

PMID: 19861443

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Transcription profiling of human chronic lymphocytic leukemia samples to improve prognosis and predict therapeutic response

Project description:Chronic lymphocytic leukemia (CLL) is a heterogeneous malignancy, characterized by a variable clinical course. While clinical and laboratory parameters are increasingly being used to refine prognosis, they do not accurately predict response to commonly used therapy. We used gene expression profiling to generate and further refine prognostic and predictive markers. Genomic signatures that reflect progressive disease and responses to chemotherapy or chemo-immunotherapy were created using cancer cell lines and patient leukemia samples. We validated these signatures using independent clinical data from four separate cohorts representing a total of 301 CLL patients. A prognostic genomic signature created from patient leukemic cell gene expression data coupled with clinical parameters could statistically differentiate patients with stable or progressive disease in the training dataset. The progression signature was then validated in two independent datasets, demonstrating a capacity to accurately identify patients at risk for progressive disease. In addition, two distinct genomic signatures that predict response to chlorambucil or pentostatin, cyclophosphamide, and rituximab were also generated and were shown to accurately distinguish responding and non-responding CLL patients. Microarray analysis of CLL patientsâ lymphocytes can be used to refine prognosis and predict response to different therapies. These results have direct implications for standard and investigational therapeutics in CLL patients. Experiment Overall Design: For the predictive genomic signature or response to pentostatin, cyclophosphamide, and rituximab, 20 CLL leukemia samples were used in the training set, and 20 CLL leukemia samples were used in the validation set

2009-11-11 | E-GEOD-10137 | biostudies-arrayexpress

Transcription profiling of human chronic lymphocytic leukemia samples from patients with stable or progressive disease

Project description:Chronic lymphocytic leukemia (CLL) is a heterogeneous malignancy, characterized by a variable clinical course. While clinical and laboratory parameters are increasingly being used to refine prognosis, they do not accurately predict response to commonly used therapy. We used gene expression profiling to generate and further refine prognostic and predictive markers. Genomic signatures that reflect progressive disease and responses to chemotherapy or chemo-immunotherapy were created using cancer cell lines and patient leukemia samples. We validated these signatures using independent clinical data from four separate cohorts representing a total of 301 CLL patients. A prognostic genomic signature created from patient leukemic cell gene expression data coupled with clinical parameters could statistically differentiate patients with stable or progressive disease in the training dataset. The progression signature was then validated in two independent datasets, demonstrating a capacity to accurately identify patients at risk for progressive disease. In addition, two distinct genomic signatures that predict response to chlorambucil or pentostatin, cyclophosphamide, and rituximab were also generated and were shown to accurately distinguish responding and non-responding CLL patients. Microarray analysis of CLL patientsâ lymphocytes can be used to refine prognosis and predict response to different therapies. These results have direct implications for standard and investigational therapeutics in CLL patients. Experiment Overall Design: For the prognostic genomic signature, 68 CLL leukemia samples were used (36 from patients with stable disease and 32 from patients with progressive disease).

2009-11-11 | E-GEOD-10138 | biostudies-arrayexpress

Project description:A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia

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Homo sapiens

Project description:A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia (Duke_VA)

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Project description:A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia (Mayo_Ohio)

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Transcription profiling of human blood from chronic lymphocytic leukemia patients before and after Fludarabine treatment

Project description:Transcription profiling of blood from human chronic lymphocytic leukemia patients before and after Fludarabine treatment

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Expression analysis of genes located in the minimally deleted regions of 13q14 and 11q22-23 in chronic lymphocytic leukemia – unexpected expression pattern of the RHO GTPase activator ARHGAP20

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2011-10-13 | E-GEOD-25571 | biostudies-arrayexpress

Detection of chromothripsis-like patterns from custom array platform for chronic lymphocytic leukemia diagnosis (qchip Hemo custom array v3)

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2015-08-31 | E-GEOD-66922 | biostudies-arrayexpress

Nanda2013 - B cell chronic lymphocytic leukemia A model with immune response

Project description:B cell chronic lymphocytic leukemia - A model with immune response Seema Nanda 1, , Lisette dePillis 2, and Ami Radunskaya 3, 1. Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bangalore 560065, India 2. Department of Mathematics, Harvey Mudd College, Claremont, CA 91711 3. Department of Mathematics, Pomona College, Claremont, CA, 91711, United States Abstract B cell chronic lymphocytic leukemia (B-CLL) is known to have substantial clinical heterogeneity. There is no cure, but treatments allow for disease management. However, the wide range of clinical courses experienced by B-CLL patients makes prognosis and hence treatment a significant challenge. In an attempt to study disease progression across different patients via a unified yet flexible approach, we present a mathematical model of B-CLL with immune response, that can capture both rapid and slow disease progression. This model includes four different cell populations in the peripheral blood of humans: B-CLL cells, NK cells, cytotoxic T cells and helper T cells. We analyze existing data in the medical literature, determine ranges of values for parameters of the model, and compare our model outcomes to clinical patient data. The goal of this work is to provide a tool that may shed light on factors affecting the course of disease progression in patients. This modeling tool can serve as a foundation upon which future treatments can be based. Keywords: NK cell, chronic lymphocytic leukemia, mathematical model, T cell., B-CLL.

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Project description:This SuperSeries is composed of the following subset Series: GSE38611: Relevance of Chromosome 2p Gain in Early Binet Stage A Chronic Lymphocytic Leukemia (expression) GSE38613: Relevance of Chromosome 2p Gain in Early Binet Stage A Chronic Lymphocytic Leukemia (SNP) Refer to individual Series

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