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Find video protocols related to scientific articles indexed in Pubmed.
Expression profiling of formalin-fixed paraffin-embedded primary breast tumors using cancer-specific and whole genome gene panels on the DASL® platform.
BMC Med Genomics
PUBLISHED: 02-25-2010
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The cDNA-mediated Annealing, extension, Selection and Ligation (DASL) assay has become a suitable gene expression profiling system for degraded RNA from paraffin-embedded tissue. We examined assay characteristics and the performance of the DASL 502-gene Cancer Panel v1 (1.5K) and 24,526-gene panel (24K) platforms at differentiating nine human epidermal growth factor receptor 2- positive (HER2+) and 11 HER2-negative (HER2-) paraffin-embedded breast tumors.
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Whole-genome gene expression profiling of formalin-fixed, paraffin-embedded tissue samples.
PLoS ONE
PUBLISHED: 07-30-2009
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We have developed a gene expression assay (Whole-Genome DASL), capable of generating whole-genome gene expression profiles from degraded samples such as formalin-fixed, paraffin-embedded (FFPE) specimens.
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A comprehensive microarray-based DNA methylation study of 367 hematological neoplasms.
PLoS ONE
PUBLISHED: 07-23-2009
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Alterations in the DNA methylation pattern are a hallmark of leukemias and lymphomas. However, most epigenetic studies in hematologic neoplasms (HNs) have focused either on the analysis of few candidate genes or many genes and few HN entities, and comprehensive studies are required.
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Array-based DNA methylation profiling of primary lymphomas of the central nervous system.
BMC Cancer
PUBLISHED: 07-16-2009
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Although primary lymphomas of the central nervous system (PCNSL) and extracerebral diffuse large B-cell lymphoma (DLBCL) cannot be distinguished histologically, it is still a matter of debate whether PCNSL differ from systemic DLBCL with respect to their molecular features and pathogenesis. Analysis of the DNA methylation pattern might provide further data distinguishing these entities at a molecular level.
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New insights into the biology and origin of mature aggressive B-cell lymphomas by combined epigenomic, genomic, and transcriptional profiling.
Blood
PUBLISHED: 04-14-2009
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Lymphomas are assumed to originate at different stages of lymphocyte development through chromosomal aberrations. Thus, different lymphomas resemble lymphocytes at distinct differentiation stages and show characteristic morphologic, genetic, and transcriptional features. Here, we have performed a microarray-based DNA methylation profiling of 83 mature aggressive B-cell non-Hodgkin lymphomas (maB-NHLs) characterized for their morphologic, genetic, and transcriptional features, including molecular Burkitt lymphomas and diffuse large B-cell lymphomas. Hierarchic clustering indicated that methylation patterns in maB-NHLs were not strictly associated with morphologic, genetic, or transcriptional features. By supervised analyses, we identified 56 genes de novo methylated in all lymphoma subtypes studied and 22 methylated in a lymphoma subtype-specific manner. Remarkably, the group of genes de novo methylated in all lymphoma subtypes was significantly enriched for polycomb targets in embryonic stem cells. De novo methylated genes in all maB-NHLs studied were expressed at low levels in lymphomas and normal hematopoietic tissues but not in nonhematopoietic tissues. These findings, especially the enrichment for polycomb targets in stem cells, indicate that maB-NHLs with different morphologic, genetic, and transcriptional background share a similar stem cell-like epigenetic pattern. This suggests that maB-NHLs originate from cells with stem cell features or that stemness was acquired during lymphomagenesis by epigenetic remodeling.
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Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancer.
PLoS ONE
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Ovarian cancer is the fifth leading cause of cancer death for women in the U.S. and the seventh most fatal worldwide. Although ovarian cancer is notable for its initial sensitivity to platinum-based therapies, the vast majority of patients eventually develop recurrent cancer and succumb to increasingly platinum-resistant disease. Modern, targeted cancer drugs intervene in cell signaling, and identifying key disease mechanisms and pathways would greatly advance our treatment abilities. In order to shed light on the molecular diversity of ovarian cancer, we performed comprehensive transcriptional profiling on 129 advanced stage, high grade serous ovarian cancers. We implemented a, re-sampling based version of the ISIS class discovery algorithm (rISIS: robust ISIS) and applied it to the entire set of ovarian cancer transcriptional profiles. rISIS identified a previously undescribed patient stratification, further supported by micro-RNA expression profiles, and gene set enrichment analysis found strong biological support for the stratification by extracellular matrix, cell adhesion, and angiogenesis genes. The corresponding "angiogenesis signature" was validated in ten published independent ovarian cancer gene expression datasets and is significantly associated with overall survival. The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.