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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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Journal ArticleDOI
TL;DR: A framework of patient-partnered research allows patients with angiosarcoma to share their samples and clinical records securely to accelerate molecular characterization of tumors and identification of therapeutic approaches, demonstrating that empowering patients to directly participate in research can overcome barriers in rare diseases and can enable discoveries.
Abstract: Despite rare cancers accounting for 25% of adult tumors1, they are difficult to study due to the low disease incidence and geographically dispersed patient populations, which has resulted in significant unmet clinical needs for patients with rare cancers. We assessed whether a patient-partnered research approach using online engagement can overcome these challenges, focusing on angiosarcoma, a sarcoma with an annual incidence of 300 cases in the United States. Here we describe the development of the Angiosarcoma Project (ASCproject), an initiative enabling US and Canadian patients to remotely share their clinical information and biospecimens for research. The project generates and publicly releases clinically annotated genomic data on tumor and germline specimens on an ongoing basis. Over 18 months, 338 patients registered for the ASCproject, which comprises a large proportion of all patients with angiosarcoma. Whole-exome sequencing (WES) of 47 tumors revealed recurrently mutated genes that included KDR, TP53, and PIK3CA. PIK3CA-activating mutations were observed predominantly in primary breast angiosarcoma, which suggested a therapeutic rationale. Angiosarcoma of the head, neck, face and scalp (HNFS) was associated with a high tumor mutation burden (TMB) and a dominant ultraviolet damage mutational signature, which suggested that for the subset of patients with angiosarcoma of HNFS, ultraviolet damage may be a causative factor and that immune checkpoint inhibition may be beneficial. Medical record review revealed that two patients with HNFS angiosarcoma had received off-label therapeutic use of antibody to the programmed death-1 protein (anti-PD-1) and had experienced exceptional responses, which highlights immune checkpoint inhibition as a therapeutic avenue for HNFS angiosarcoma. This patient-partnered approach has catalyzed an opportunity to discover the etiology and potential therapies for patients with angiosarcoma. Collectively, this proof-of-concept study demonstrates that empowering patients to directly participate in research can overcome barriers in rare diseases and can enable discoveries. A framework of patient-partnered research allows patients with angiosarcoma to share their samples and clinical records securely to accelerate molecular characterization of tumors and identification of therapeutic approaches.

131 citations

Journal ArticleDOI
15 Oct 2005-Blood
TL;DR: Gefitinib induced differentiation based on morphologic assessment, nitro-blue tetrazolium reduction, cell-surface markers, genome-wide patterns of gene expression, and inhibition of proliferation at clinically achievable doses, indicating that gefit inib functions through a previously unrecognized EGFR-independent mechanism.

131 citations

Journal ArticleDOI
14 Sep 2007-Science
TL;DR: Although the biological methodology in Sjöblom et al. is sound, more samples are needed to achieve sufficient power, and few genes with significantly elevated mutation rates remain.
Abstract: Sjoblom et al (Research Article, 13 October 2006, p 268) reported nearly 200 novel cancer genes said to have a 90% probability of being involved in colon or breast cancer However, their analysis raises two statistical concerns When these concerns are addressed, few genes with significantly elevated mutation rates remain Although the biological methodology in Sjoblom et al is sound, more samples are needed to achieve sufficient power

129 citations

Journal ArticleDOI
30 Mar 2017-Nature
TL;DR: It is shown, using in vitro and in vivo studies in mice and humans, that the mitochondrial protein LACTB potently inhibits the proliferation of breast cancer cells and demonstrates a connection between mitochondrial lipid metabolism and the differentiation program of Breast cancer cells, thereby revealing a previously undescribed mechanism of tumour suppression.
Abstract: Post-mitotic, differentiated cells exhibit a variety of characteristics that contrast with those of actively growing neoplastic cells, such as the expression of cell-cycle inhibitors and differentiation factors. We hypothesized that the gene expression profiles of these differentiated cells could reveal the identities of genes that may function as tumour suppressors. Here we show, using in vitro and in vivo studies in mice and humans, that the mitochondrial protein LACTB potently inhibits the proliferation of breast cancer cells. Its mechanism of action involves alteration of mitochondrial lipid metabolism and differentiation of breast cancer cells. This is achieved, at least in part, through reduction of the levels of mitochondrial phosphatidylserine decarboxylase, which is involved in the synthesis of mitochondrial phosphatidylethanolamine. These observations uncover a novel mitochondrial tumour suppressor and demonstrate a connection between mitochondrial lipid metabolism and the differentiation program of breast cancer cells, thereby revealing a previously undescribed mechanism of tumour suppression.

127 citations

Journal ArticleDOI
TL;DR: UBE1L is proposed as a direct pharmacological target that overcomes oncogenic effects of PML/RARα by triggering its degradation and signaling apoptosis in APL cells.
Abstract: All-trans-retinoic acid (RA) treatment induces remissions in acute promyelocytic leukemia (APL) cases expressing the t(15;17) product, promyelocytic leukemia (PML)/RA receptor α (RARα). Microarray analyses previously revealed induction of UBE1L (ubiquitin-activating enzyme E1-like) after RA treatment of NB4 APL cells. We report here that this occurs within 3 h in RA-sensitive but not RA-resistant APL cells, implicating UBE1L as a direct retinoid target. A 1.3-kb fragment of the UBE1L promoter was capable of mediating transcriptional response to RA in a retinoid receptor-selective manner. PML/RARα, a repressor of RA target genes, abolished this UBE1L promoter activity. A hallmark of retinoid response in APL is the proteasome-dependent PML/RARα degradation. UBE1L transfection triggered PML/RARα degradation, but transfection of a truncated UBE1L or E1 did not cause this degradation. A tight link was shown between UBE1L induction and PML/RARα degradation. Notably, retroviral expression of UBE1L rapidly induced apoptosis in NB4 APL cells, but not in cells lacking PML/RARα expression. UBE1L has been implicated directly in retinoid effects in APL and may be targeted for repression by PML/RARα. UBE1L is proposed as a direct pharmacological target that overcomes oncogenic effects of PML/RARα by triggering its degradation and signaling apoptosis in APL cells.

126 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