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Todd R. Golub

Bio: Todd R. Golub is an academic researcher from Harvard University. The author has contributed to research in topics: Cancer & Gene expression profiling. The author has an hindex of 164, co-authored 422 publications receiving 201457 citations. Previous affiliations of Todd R. Golub include Rush University Medical Center & Boston Children's Hospital.


Papers
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Proceedings ArticleDOI
TL;DR: Members of the 19q miRNA family increased cell proliferation, migration and invasion in vitro and promoted tumor development in vivo suggesting their role as novel potential oncogenic drivers in HCC.
Abstract: Background: Hepatocellular carcinoma (HCC) is the most common form of liver cancer and the third cause of cancer-related death worldwide. Its incidence is increasing mainly due to hepatitis C virus (HCV) infection. A molecular classification of HCC is still lacking. microRNAs (miRNAs) are small non-coding RNA involved in HCC pathogenesis. Their expression profiling represents a powerful tool to classify cancers. Objectives: (1) To provide a miRNA-based molecular classification of HCC and, (2) To investigate the function of potential oncogenic miRNAs in HCC models. Methods: Expression of 358 miRNAs was analyzed in 89 HCV-related HCCs using a bead-based miRNA expression profiling method. Integrative analysis including miRNA profiling, gene expression (Affymetrix U133 2.0 ® ), DNA changes (Affymetrix STY Mapping Array ® ), IHC (p-Akt, p-IGF-IR, p-S6, p-EGFR, β-catenin) and mutation analysis (β-catenin) was performed. Expression of selected miRNA was validated in a validation set (n=167) by qRT-PCR. Methylation-specific PCR, FISH and SNP-array analyses were performed to identify mechanisms of miRNA deregulation. The function of miRNAs of interest was investigated in vitro by analyzing cell proliferation (thymidine incorporation), migration and invasion (trans-well migration and invasion assays, wound healing assay). Tumor development and growth following direct injection of luciferase-expressing cells stably transfected with specific miRNAs into the liver of nude mice were monitored to investigate their function in vivo. The bioluminescent signal emitted by luciferase-expressing cells was used as indicator of tumor growth. Results: Three classes of HCC patients were identified and defined by activation of different pathways: Wnt signalling (32/89, 36%), IFN-related genes (29/89, 33%) and proliferative cascades (IGF, Akt/mTOR) (28/89, 31%). A subgroup within the proliferative class (8/89, 9% overexpressed a cluster of miRNAs on 19q13.42 (median fold change: 8.8). Hypomethylation of CpG island upstream the miRNA cluster (2/8, 25%) and copy number gains (1/8, 12.5%) were detected. Their overexpression was confirmed in a validation set (17/167, 10.2%). Members of the cluster family significantly increased proliferation (p Conclusions: Overexpression of 19q miRNA family and activation of proliferative pathways defined a subclass of HCC. Members of 19q miRNA family increased cell proliferation, migration and invasion in vitro and promoted tumor development in vivo suggesting their role as novel potential oncogenic drivers in HCC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2996.

2 citations

Journal ArticleDOI
18 Nov 2011-Blood
TL;DR: A niche-based high throughput screen done in a murine system identified candidate small molecules potentially toxic to leukemic stem cells (LSCs) while sparing normal hematopoietic stem cells and bone marrow stroma, and one such compound demonstrated dose-dependent activity against leukemia in both a cell autonomous and non-autonomous manner, by modifying niche–based support.

1 citations

Book ChapterDOI
01 Jan 1998
TL;DR: The authors' data narrow down regions on chromosomes 6q, 9p, l lq and 12p containing putative tumor suppressor genes which may play an important role in leukemogenesis of childhood ALL.
Abstract: Chromosomal abnormalities on 6q, 9p, 11q and 12p have been reported frequently in acute lymphoblastic leukemia (ALL). In order to define regions that may contain tumor suppressor genes more precisely, the loss of heterozygosity (LOH) was analyzed on respective chromosome arms in childhood ALL. Using highly informative microsatellite markers, LOH was found in 17 of 112 (15%) ALL samples on 6q; in 29 of 54 (54%) on 9p; in 14 of 112 cases (13%) on 11q; in 33 of 100 (33%) on 12p. The commonly deleted region on 6q was flanked by the markers D6S468 and D6S283/D6S449 at 6q21. In 27 of the 29 cases with LOH on 9p the critical region was characterized by D9S1747 and D9S1748. Homozygous deletions of the CDKN2/INK4A/p16 gene residing in this region were found in 14 of the 27 patients. Two cases revealed LOH at the IFNA locus. Two distinct commonly deleted regions were identified on 11q and 12p, respectively. One region at 11g22 was flanked by D11S901 and D11S1391, and the other at 11q23 by D11S614 and D11S924. On chromosome 12p, one critical region was flanked by the markers D12S77 and D12S98 including the TEL gene, and the other was localized around the p27/kipl locus. Our data narrow down regions on chromosomes 6q, 9p, l lq and 12p containing putative tumor suppressor genes which may play an important role in leukemogenesis of childhood ALL.

1 citations

Patent
05 Apr 2011
TL;DR: In this article, the authors proposed a method for high throughput detection of analytes from samples, including but not limited to biological samples, such that the detection of nucleic acids, proteins, peptides, and small organic molecules is facilitated.
Abstract: The present invention improves the known compositions and methods for high throughput detection of analytes. Analytes may be derived from samples, including but not limited to biological samples, such that the detection of nucleic acids, proteins, peptides, and/or small organic molecules is facilitated. Different analytes may be attached to solid particles having identical spectral characteristics, wherein the analytes are identified by differential particle count (i.e., for example, subsets of identical particles are assayed in unequal proportions). The simultaneous detection and/or identification all analytes contained within a sample is facilitated by an algorithmic analysis of multimodal distribution patterns.

1 citations


Cited by
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Journal ArticleDOI
04 Mar 2011-Cell
TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.

51,099 citations

Journal ArticleDOI
TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

34,830 citations

Journal ArticleDOI
TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Abstract: Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

32,980 citations

Journal ArticleDOI
TL;DR: By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
Abstract: DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.

31,015 citations

Journal ArticleDOI
TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

22,147 citations