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.
Project description:Clonal and subclonal evolution is involved in the progression of chronic lymphocytic leukemia (CLL). Evolution can work to select not only genetic mutations, but also epigenetic states. Here we performed a long-term longitudinal DNA methylation profiling study of CLL patients to look for associations of epigenetic evolution to different disease courses. In line with the genetic data, large-scale methylation evolution was not present in any of the evaluated long-term untreated (n = 3) and relapsed (n = 2) patients displaying clonal changes of linear type while 3 of the 5 examined refractory patients featured profound changes in DNA methylation.
Project description:Identify and track clonal evolution of clones in consecutive human chronic lymphocytic leukemia samples identified by whole exome sequencing.
Project description:Identify and track clonal evolution of clones in consecutive human chronic lymphocytic leukemia samples identified by whole exome sequencing.
Project description:<p>Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enables the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome.</p>
Project description:THis is a simple ordinary differential equation model describing chemoimmunotherapy of chronic lymphocytic leukemia, including descriptions of the combinatorial effects of chemotherapy and adoptive cellular immunotherapy.
Project description: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
