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Van Andel Institute

NonprofitGrand Rapids, Michigan, United States
About: Van Andel Institute is a nonprofit organization based out in Grand Rapids, Michigan, United States. It is known for research contribution in the topics: Cancer & DNA methylation. The organization has 1137 authors who have published 2046 publications receiving 141286 citations.


Papers
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Journal ArticleDOI
John T. Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando U. Garcia1, Nancy Young2, Barbara A. Foster3, Mike Moser3, Ellen Karasik3, Bryan Gillard3, Kimberley Ramsey3, Susan L. Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura A. Siminoff4, Heather M. Traino4, Maghboeba Mosavel4, Laura Barker4, Scott D. Jewell5, Daniel C. Rohrer5, Dan Maxim5, Dana Filkins5, Philip Harbach5, Eddie Cortadillo5, Bree Berghuis5, Lisa Turner5, Eric Hudson5, Kristin Feenstra5, Leslie H. Sobin6, James A. Robb6, Phillip Branton, Greg E. Korzeniewski6, Charles Shive6, David Tabor6, Liqun Qi6, Kevin Groch6, Sreenath Nampally6, Steve Buia6, Angela Zimmerman6, Anna M. Smith6, Robin Burges6, Karna Robinson6, Kim Valentino6, Deborah Bradbury6, Mark Cosentino6, Norma Diaz-Mayoral6, Mary Kennedy6, Theresa Engel6, Penelope Williams6, Kenyon Erickson, Kristin G. Ardlie7, Wendy Winckler7, Gad Getz8, Gad Getz7, David S. DeLuca7, MacArthur Daniel MacArthur8, MacArthur Daniel MacArthur7, Manolis Kellis7, Alexander Thomson7, Taylor Young7, Ellen Gelfand7, Molly Donovan7, Yan Meng7, George B. Grant7, Deborah C. Mash9, Yvonne Marcus9, Margaret J. Basile9, Jun Liu8, Jun Zhu10, Zhidong Tu10, Nancy J. Cox11, Dan L. Nicolae11, Eric R. Gamazon11, Hae Kyung Im11, Anuar Konkashbaev11, Jonathan K. Pritchard12, Jonathan K. Pritchard11, Matthew Stevens11, Timothée Flutre11, Xiaoquan Wen11, Emmanouil T. Dermitzakis13, Tuuli Lappalainen13, Roderic Guigó, Jean Monlong, Michael Sammeth, Daphne Koller14, Alexis Battle14, Sara Mostafavi14, Mark I. McCarthy15, Manual Rivas15, Julian Maller15, Ivan Rusyn16, Andrew B. Nobel16, Fred A. Wright16, Andrey A. Shabalin16, Mike Feolo17, Nataliya Sharopova17, Anne Sturcke17, Justin Paschal17, James M. Anderson17, Elizabeth L. Wilder17, Leslie Derr17, Eric D. Green17, Jeffery P. Struewing17, Gary F. Temple17, Simona Volpi17, Joy T. Boyer17, Elizabeth J. Thomson17, Mark S. Guyer17, Cathy Ng17, Assya Abdallah17, Deborah Colantuoni17, Thomas R. Insel17, Susan E. Koester17, Roger Little17, Patrick Bender17, Thomas Lehner17, Yin Yao17, Carolyn C. Compton17, Jimmie B. Vaught17, Sherilyn Sawyer17, Nicole C. Lockhart17, Joanne P. Demchok17, Helen F. Moore17 
TL;DR: The Genotype-Tissue Expression (GTEx) project is described, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
Abstract: Genome-wide association studies have identified thousands of loci for common diseases, but, for the majority of these, the mechanisms underlying disease susceptibility remain unknown. Most associated variants are not correlated with protein-coding changes, suggesting that polymorphisms in regulatory regions probably contribute to many disease phenotypes. Here we describe the Genotype-Tissue Expression (GTEx) project, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.

6,545 citations

Journal ArticleDOI
Daniel J. Klionsky1, Kotb Abdelmohsen2, Akihisa Abe3, Joynal Abedin4  +2519 moreInstitutions (695)
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

5,187 citations

Journal ArticleDOI
TL;DR: These guidelines are presented for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.

4,316 citations

Journal ArticleDOI
17 Apr 2018-Immunity
TL;DR: An extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA identifies six immune subtypes that encompass multiple cancer types and are hypothesized to define immune response patterns impacting prognosis.

3,246 citations

Journal ArticleDOI
08 Mar 2007-Nature
TL;DR: More than 1,000 somatic mutations found in 274 megabases of DNA corresponding to the coding exons of 518 protein kinase genes in 210 diverse human cancers reveal the evolutionary diversity of cancers and implicates a larger repertoire of cancer genes than previously anticipated.
Abstract: Cancers arise owing to mutations in a subset of genes that confer growth advantage. The availability of the human genome sequence led us to propose that systematic resequencing of cancer genomes for mutations would lead to the discovery of many additional cancer genes. Here we report more than 1,000 somatic mutations found in 274 megabases (Mb) of DNA corresponding to the coding exons of 518 protein kinase genes in 210 diverse human cancers. There was substantial variation in the number and pattern of mutations in individual cancers reflecting different exposures, DNA repair defects and cellular origins. Most somatic mutations are likely to be 'passengers' that do not contribute to oncogenesis. However, there was evidence for 'driver' mutations contributing to the development of the cancers studied in approximately 120 genes. Systematic sequencing of cancer genomes therefore reveals the evolutionary diversity of cancers and implicates a larger repertoire of cancer genes than previously anticipated.

2,732 citations


Authors

Showing all 1151 results

NameH-indexPapersCitations
Stephen B. Baylin168548188934
David A. Jackson136109568352
Peter A. Jones13051381683
Peter W. Laird120292133318
Tomas Olsson10567739905
Jianfeng Xu9757944557
Jeffrey M. Trent9634248052
Jeffrey H. Kordower9434034270
Gerd P. Pfeifer9331529439
Bin Tean Teh9247133359
Timothy J. Triche8833282893
Yong Xu88139139268
Robert C. Baxter8738127390
Lee W. Jones8542526044
Patrik Brundin7723224428
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
202229
2021184
2020204
2019150
2018167