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1.
Genome Res ; 22(10): 1833-44, 2012 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-22628462

RESUMEN

Abnormal replication timing has been observed in cancer but no study has comprehensively evaluated this misregulation. We generated genome-wide replication-timing profiles for pediatric leukemias from 17 patients and three cell lines, as well as normal B and T cells. Nonleukemic EBV-transformed lymphoblastoid cell lines displayed highly stable replication-timing profiles that were more similar to normal T cells than to leukemias. Leukemias were more similar to each other than to B and T cells but were considerably more heterogeneous than nonleukemic controls. Some differences were patient specific, while others were found in all leukemic samples, potentially representing early epigenetic events. Differences encompassed large segments of chromosomes and included genes implicated in other types of cancer. Remarkably, differences that distinguished leukemias aligned in register to the boundaries of developmentally regulated replication-timing domains that distinguish normal cell types. Most changes did not coincide with copy-number variation or translocations. However, many of the changes that were associated with translocations in some leukemias were also shared between all leukemic samples independent of the genetic lesion, suggesting that they precede and possibly predispose chromosomes to the translocation. Altogether, our results identify sites of abnormal developmental control of DNA replication in cancer that reveal the significance of replication-timing boundaries to chromosome structure and function and support the replication domain model of replication-timing regulation. They also open new avenues of investigation into the chromosomal basis of cancer and provide a potential novel source of epigenetic cancer biomarkers.


Asunto(s)
Momento de Replicación del ADN , Leucemia-Linfoma Linfoblástico de Células Precursoras/genética , Cariotipo Anormal , Línea Celular , Niño , Variaciones en el Número de Copia de ADN , Epigénesis Genética , Perfilación de la Expresión Génica , Heterogeneidad Genética , Humanos , Leucemia/genética , Linfocitos/metabolismo , Translocación Genética
2.
Bioinformatics ; 27(7): 933-8, 2011 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-21310746

RESUMEN

MOTIVATION: Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus. Analyzing the data from FISH images is a tedious process that invokes an element of subjectivity. Automated FISH image analysis offers savings in time as well as gaining the benefit of objective data analysis. While several FISH image analysis software tools have been developed, they often use a threshold-based segmentation algorithm for nucleus segmentation. As fluorescence signal intensities can vary significantly from experiment to experiment, from cell to cell, and within a cell, threshold-based segmentation is inflexible and often insufficient for automatic image analysis, leading to additional manual segmentation and potential subjective bias. To overcome these problems, we developed a graphical software tool called FISH Finder to automatically analyze FISH images that vary significantly. By posing the nucleus segmentation as a classification problem, compound Bayesian classifier is employed so that contextual information is utilized, resulting in reliable classification and boundary extraction. This makes it possible to analyze FISH images efficiently and objectively without adjustment of input parameters. Additionally, FISH Finder was designed to analyze the distances between differentially stained FISH probes. AVAILABILITY: FISH Finder is a standalone MATLAB application and platform independent software. The program is freely available from: http://code.google.com/p/fishfinder/downloads/list.


Asunto(s)
Procesamiento de Imagen Asistido por Computador/métodos , Hibridación Fluorescente in Situ/métodos , Programas Informáticos , Animales , Teorema de Bayes , Núcleo Celular/química , Gráficos por Computador , Humanos , Ratones , Microscopía Fluorescente
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