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Institution

Vanderbilt University

EducationNashville, Tennessee, United States
About: Vanderbilt University is a education organization based out in Nashville, Tennessee, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 45066 authors who have published 106528 publications receiving 5435039 citations. The organization is also known as: Vandy.


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Journal ArticleDOI
Theo Vos1, Ryan M Barber1, Brad Bell1, Amelia Bertozzi-Villa1  +686 moreInstitutions (287)
TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as mentioned in this paper, the authors estimated the quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013.

4,510 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
27 Nov 2014-Nature
TL;DR: Evaluated data suggest that MPDL3280A is most effective in patients in which pre-existing immunity is suppressed by PD-L1, and is re-invigorated on antibody treatment, as well as across multiple cancer types.
Abstract: The development of human cancer is a multistep process characterized by the accumulation of genetic and epigenetic alterations that drive or reflect tumour progression. These changes distinguish cancer cells from their normal counterparts, allowing tumours to be recognized as foreign by the immune system. However, tumours are rarely rejected spontaneously, reflecting their ability to maintain an immunosuppressive microenvironment. Programmed death-ligand 1 (PD-L1; also called B7-H1 or CD274), which is expressed on many cancer and immune cells, plays an important part in blocking the 'cancer immunity cycle' by binding programmed death-1 (PD-1) and B7.1 (CD80), both of which are negative regulators of T-lymphocyte activation. Binding of PD-L1 to its receptors suppresses T-cell migration, proliferation and secretion of cytotoxic mediators, and restricts tumour cell killing. The PD-L1-PD-1 axis protects the host from overactive T-effector cells not only in cancer but also during microbial infections. Blocking PD-L1 should therefore enhance anticancer immunity, but little is known about predictive factors of efficacy. This study was designed to evaluate the safety, activity and biomarkers of PD-L1 inhibition using the engineered humanized antibody MPDL3280A. Here we show that across multiple cancer types, responses (as evaluated by Response Evaluation Criteria in Solid Tumours, version 1.1) were observed in patients with tumours expressing high levels of PD-L1, especially when PD-L1 was expressed by tumour-infiltrating immune cells. Furthermore, responses were associated with T-helper type 1 (TH1) gene expression, CTLA4 expression and the absence of fractalkine (CX3CL1) in baseline tumour specimens. Together, these data suggest that MPDL3280A is most effective in patients in which pre-existing immunity is suppressed by PD-L1, and is re-invigorated on antibody treatment.

4,227 citations

Journal ArticleDOI
TL;DR: Gen expression profiles from 21 breast cancer data sets and identified 587 TNBC cases may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
Abstract: Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem–like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted “driver” signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.

4,215 citations

BookDOI
01 Jan 2006
TL;DR: Regression models are frequently used to develop diagnostic, prognostic, and health resource utilization models in clinical, health services, outcomes, pharmacoeconomic, and epidemiologic research, and in a multitude of non-health-related areas.
Abstract: Regression models are frequently used to develop diagnostic, prognostic, and health resource utilization models in clinical, health services, outcomes, pharmacoeconomic, and epidemiologic research, and in a multitude of non-health-related areas. Regression models are also used to adjust for patient heterogeneity in randomized clinical trials, to obtain tests that are more powerful and valid than unadjusted treatment comparisons.

4,211 citations


Authors

Showing all 45403 results

NameH-indexPapersCitations
Walter C. Willett3342399413322
Meir J. Stampfer2771414283776
John Q. Trojanowski2261467213948
Robert M. Califf1961561167961
Matthew Meyerson194553243726
Scott M. Grundy187841231821
Tony Hunter175593124726
David R. Jacobs1651262113892
Donald E. Ingber164610100682
L. Joseph Melton16153197861
Ralph A. DeFronzo160759132993
David W. Bates1591239116698
Charles N. Serhan15872884810
David Cella1561258106402
Jay Hauser1552145132683
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023141
2022541
20215,134
20205,232
20194,883
20184,649