7,757 research outputs found
Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM
Epigenetic changes, such as aberrant DNA methylation, contribute to cancer clonal expansion and disease progression. However, identifying subpopulation-level changes in a heterogeneous sample remains challenging. Thus, we have developed a computational approach, DXM, to deconvolve the methylation profiles of major allelic subpopulations from the bisulfite sequencing data of a heterogeneous sample. DXM does not require prior knowledge of the number of subpopulations or types of cells to expect. We benchmark DXM\u27s performance and demonstrate improvement over existing methods. We further experimentally validate DXM predicted allelic subpopulation-methylation profiles in four Diffuse Large B-Cell Lymphomas (DLBCLs). Lastly, as proof-of-concept, we apply DXM to a cohort of 31 DLBCLs and relate allelic subpopulation methylation profiles to relapse. We thus demonstrate that DXM can robustly find allelic subpopulation methylation profiles that may contribute to disease progression using bisulfite sequencing data of any heterogeneous sample
Multivariate biophysical markers predictive of mesenchymal stromal cell multipotency
The capacity to produce therapeutically relevant quantities of multipotent mesenchymal stromal cells (MSCs) via in vitro culture is a common prerequisite for stem cell-based therapies. Although culture expanded MSCs are widely studied and considered for therapeutic applications, it has remained challenging to identify a unique set of characteristics that enables robust identification and isolation of the multipotent stem cells. New means to describe and separate this rare cell type and its downstream progenitor cells within heterogeneous cell populations will contribute significantly to basic biological understanding and can potentially improve efficacy of stem and progenitor cell-based therapies. Here, we use multivariate biophysical analysis of culture-expanded, bone marrow-derived MSCs, correlating these quantitative measures with biomolecular markers and in vitro and in vivo functionality. We find that, although no single biophysical property robustly predicts stem cell multipotency, there exists a unique and minimal set of three biophysical markers that together are predictive of multipotent subpopulations, in vitro and in vivo. Subpopulations of culture-expanded stromal cells from both adult and fetal bone marrow that exhibit sufficiently small cell diameter, low cell stiffness, and high nuclear membrane fluctuations are highly clonogenic and also exhibit gene, protein, and functional signatures of multipotency. Further, we show that high-throughput inertial microfluidics enables efficient sorting of committed osteoprogenitor cells, as distinct from these mesenchymal stem cells, in adult bone marrow. Together, these results demonstrate novel methods and markers of stemness that facilitate physical isolation, study, and therapeutic use of culture-expanded, stromal cell subpopulations.National University of Singapore (Graduate School for Integrative Sciences and Engineering Program)Singapore-MIT Alliance (Singapore-MIT Alliance-3 graduate fellowship program)Singapore. National Research FoundationSingapore-MIT Alliance for Research and Technology (BioSystems and Micromechanics Interdisciplinary Research Group)Singapore. National Medical Research Council (NMRC/Clinician Scientist Award/012/2009
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The Impact of Radiation on Glioblastoma Evolution
Glioblastoma (GB) is the most common and malignant primary adult brain cancer with a median survival of 15 months despite treatment with surgical resection followed by chemo-radiotherapy. The clonal diversity and evolutionary dynamics inherent to GBs is considered a major obstacle to effective treatment response. While studies have focused on temozolomide, a role for radiotherapy as an independent driver of GB evolution has not been investigated. We addressed the impact of radiation on glioblastoma evolution and potential treatment implications by examining the influence of intratumoral heterogeneity (ITH) on intrinsic radiosensitivity, by determining the effects of radiation on glioma stem-like cell (GSC) initiated orthotopic xenografts, and by assessing radioresistance with a reirradiation protocol.
To determine the impact of ITH on intrinsic radiosensitivity, we performed whole-exome sequencing (WES) of multiple tumour fragments and corresponding patient-derived cell lines that underwent γH2AX foci analysis and limiting dilution assay analysis. Cell lines from the same tumour seem to display similar levels of intrinsic radiosensitivity despite genomic differences, suggesting that radiotherapy regimens may be effective for the whole of the tumour. To test the ability of radiation to drive GB evolution, we utilised GSC-initiated orthotopic xenograft models treated with or without fractionated radiation (3x5Gy) to examine differences in survival, morphology/histology, Viral integration site analysis (VISA), and WES. Irradiated mice experienced a survival advantage and harboured less invasive tumours compared to control mice. VISA revealed that control tumours harbour fewer clones than in vitro lines and that irradiated tumours harbour the fewest clones of all suggesting that radiation, particularly in the context of the brain microenvironment, drives GBM evolution. WES results demonstrated that variants from irradiated tumours mapped to different COSMIC mutational signatures and displayed a considerable amount of subpopulation shifting compared to control tumours, consistent with radiation-induced evolution and subpopulation selection. By adding a reirradiation protocol to this GSC-initiated orthotopic xenograft model, we sought to better understand the functional impact of radiotherapy on recurrent GB evolution and to establish an in vivo model for studying reirradiation. After initial treatment, mice were rerandomised into control (3x5Gy-Control) and radiation therapy groups (3x5Gy-3x5Gy) and retreated once the average BLI ratio began to increase. A further survival advantage was found for mice undergoing reirradiation compared to mice receiving only one course of radiation. This survival advantage was supported by clonogenic survival and reimplantation studies of cell lines derived from control and irradiated NSC11 tumours that did not demonstrate a difference in survival after radiation regardless of the previous tumour’s treatment regimen. Whereas radiation-induced evolution may not influence radioresponse, it may lead to the identification of novel targets for sensitisation which may ultimately yield more effective treatment strategies.
Our results demonstrate that radiation, a treatment component for almost all glioblastoma patients, can have wide-ranging effects on the evolution of this dynamic tumour. In particular, the pressures imposed by radiation treatment seem to lead to the selection of a reduced number of clones. This selection may have future implications for tumour evolution and the treatment of recurrent GB. In addition, we have demonstrated for the first time the utility of a GSC-initiated orthotopic xenograft model for studying retreatment protocols and recurrent GB biology. This reirradiation model may provide the opportunity to design and test more effective recurrent GB treatment strategies centered around recurrent biology.Financial support for Chapter 4-6 was provided by Division of Basic Sciences, Intramural Program, National Cancer Institute (Z1ABC011372, Z1ABC011373) to P.J. Tofilon. The project has also been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this thesis does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organisations imply endorsement by the U.S. Government.
Tissue was accessed through the Human Research Tissue Bank supported by the NIHR Cambridge Biomedical Research Centre and Addenbrooke's Hospital
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Identifying and quantifying heterogeneity in high content analysis: Application of heterogeneity indices to drug discovery
One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology. © 2014 Gough et al
High Chromosome Number in hematological cancer cell lines is a Negative Predictor of Response to the inhibition of Aurora B and C by GSK1070916
<p>Abstract</p> <p>Background</p> <p>Aurora kinases play critical roles in mitosis and are being evaluated as therapeutic targets in cancer. GSK1070916 is a potent, selective, ATP competitive inhibitor of Aurora kinase B and C. Translation of predictive biomarkers to the clinic can benefit patients by identifying the tumors that are more likely to respond to therapies, especially novel inhibitors such as GSK1070916.</p> <p>Methods</p> <p>59 Hematological cancer-derived cell lines were used as models for response where <it>in vitro </it>sensitivity to GSK1070916 was based on both time and degree of cell death. The response data was analyzed along with karyotype, transcriptomics and somatic mutation profiles to determine predictors of response.</p> <p>Results</p> <p>20 cell lines were sensitive and 39 were resistant to treatment with GSK1070916. High chromosome number was more prevalent in resistant cell lines (p-value = 0.0098, Fisher Exact Test). Greater resistance was also found in cell lines harboring polyploid subpopulations (p-value = 0.00014, Unpaired t-test). A review of NOTCH1 mutations in T-ALL cell lines showed an association between NOTCH1 mutation status and chromosome number (p-value = 0.0066, Fisher Exact Test).</p> <p>Conclusions</p> <p>High chromosome number associated with resistance to the inhibition of Aurora B and C suggests cells with a mechanism to bypass the high ploidy checkpoint are resistant to GSK1070916. High chromosome number, a hallmark trait of many late stage hematological malignancies, varies in prevalence among hematological malignancy subtypes. The high frequency and relative ease of measurement make high chromosome number a viable negative predictive marker for GSK1070916.</p
The development of intratumoral heterogeneity in ovarian tumors: role of cancer stem cells in disease progression
Like with many cancers, a single ovarian tumor can display remarkable diversity in genetics, epigenetics, expression profiles, microenvironment and cell differentiation and plasticity. This so-called intratumoral heterogeneity (ITH) is thought to greatly increase mortality by enabling tumors to adapt quickly to therapy, metastasize, and recur, thus the study of ITH holds great clinical significance. Clonal evolution and cancer stem cell (CSC) theory are two models for the initiation and propagation of a tumor, which offer differing views on the way that ITH is developed and maintained. In the clonal evolution model, cancer arises from a single cell and, through genetic instability, proliferates into a diverse population of daughter cells, which develop additional mutations and undergo Darwinian selection under the influence of the tumor microenvironment. Each cell of the clonal evolution model may be capable of initiating a tumor independently. In CSC theory, cancer arises from the transformation of a stem cell that has the capacity to self-renew and differentiate into a diverse population of daughter cells. Each cell is NOT capable of tumorigenesis as most are terminally differentiated and do not harbor self-renewing capabilities. According to CSC theory, small, rare subpopulations of CSCs persist throughout chemotherapy and are responsible for repopulating the heterogeneous tumor post-treatment. The hypothesis that CSCs may play a role in ovarian cancer progression is the subject of this thesis. Many studies have detected the presence of stem cell markers and dysregulated stem cell signaling pathways in ovarian cancer, but doubts remain as to the existence of ovarian CSCs; critics have pointed out inherent flaws in experimental designs meant to identify and characterize CSCs. For example, the presence of cancer cells which express the stem cell marker CD133 has been correlated to both positive and negative impacts on prognosis. Further challenging the study of ovarian CSCs is the lack of consensus on the true cell of origin for ovarian cancer - whether it be from the fallopian tube epithelium or ovarian surface epithelium, or elsewhere in the peritoneal cavity - this will have important implications for the identification and characterization of tumorigenic ovarian CSCs. Advocates of clonal evolution theory have put forth incredible effort to reveal the extent of inter and intra-tumoral heterogeneity in ovarian cancer, and from these data there has arisen a general consensus that cancer cell populations do evolve in a step-wise fashion, accumulating additional mutations over time. The involvement of cancer stem cells in this progression and how exactly they fit in (as a cell of origin or arising from genetic mutations), as well as their significance for different cancer types, is a question worth answering. Despite the challenges facing the study of ovarian CSCs, the clinical impact of cells with stem-like properties has been repeatedly demonstrated, especially with regard to metastatic processes and chemoresistance. Moreover, new drugs which target stem cell pathways have proven effective in the treatment of ovarian cancer. The existence of a rare subset of cells that have enhanced tumor-initiating properties is apparent in ovarian cancer, and more work is needed to characterize the unique identifiers and behavior of these cells in vivo. Future experiments involving lineage tracing promise to deepen our understanding of the nature of ovarian CSCs and address whether normal stem cells might serve as the cell of origin
Eco-Evolutionary Implications of Environmental Change Across Heterogeneous Landscapes
Species use a variety of mechanisms to adapt to environmental change. These range from spatially tracking optimal environments, to phenotypically plastic responses and evolutionary adaptation. Due to increases in anthropogenic influence on environments, characteristics of change such as their duration and magnitude are undergoing fundamental shifts away from the natural disturbance regimes that shaped species’ evolution. This dissertation uses empirical data and simulation models to examine the ecological and evolutionary consequences of environmental change across real, heterogeneous landscapes for multiple species, with an emphasis on anthropogenic changes. I used landscape genetics to evaluate the effects of urbanization on two native amphibian species, spotted salamanders (Ambystoma maculatum) and wood frogs (Lithobates sylvaticus). Population isolation was positively associated with local urbanization and lessened genetic diversity for both species. Resistance surface modelling revealed connectivity was diminished by developed land cover, light roads, interstates, and topography for both species, plus secondary roads and rivers for wood frogs, highlighting the influence of anthropogenic landscape features relative to natural features. Further study of a subset of wood frog populations revealed adaptive evolution associated with urban environments. I identified a set of 37 loci with the capacity to correctly reassign individuals into rural or urban populations with 87.5 and 93.8% accuracy, respectively. I developed an agent-based model to examine how gene flow, rates of change, and strength of landscape spatial and temporal autocorrelation influence abundance outcomes for species experiencing an environmental shift. Analysis of 36 environmental scenarios suggests that environmental variation, which is an emergent property of landscape autocorrelation, is negatively associated with the magnitude and duration of abundance declines following environmental change. Higher levels of gene flow lessened this effect, particularly in abrupt change scenarios, although gradual changes also resulted in demographic costs. Lastly, I used an investigation of an emerging disease in American lobsters (Homarus americanus) to study within-generation responses to environmental pressures. Using whole transcriptome shotgun sequencing I identified eight differentially expressed unigenes associated with the disease and seven related to environmental differences. Collectively, my dissertation provides numerous examples of how anthropogenically induced environmental change can direct ecological and evolutionary processes
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