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Institution

Memorial Sloan Kettering Cancer Center

HealthcareNew York, New York, United States
About: Memorial Sloan Kettering Cancer Center is a healthcare organization based out in New York, New York, United States. It is known for research contribution in the topics: Cancer & Population. The organization has 30293 authors who have published 65381 publications receiving 4462534 citations. The organization is also known as: MSKCC & New York Cancer Hospital.


Papers
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Journal ArticleDOI
16 Apr 2019-Immunity
TL;DR: An overview of the complex biology of the TGF-β family and its context-dependent nature is presented and how this knowledge is being leveraged to unleash the immune system against the tumor is discussed.

1,131 citations

Journal ArticleDOI
TL;DR: Nine major recommendations that should be taken to improve the outcome for women with ovarian cancer are outlined in this Opinion article.
Abstract: There have been major advances in our understanding of the cellular and molecular biology of the human malignancies that are collectively referred to as ovarian cancer. At a recent Helene Harris Memorial Trust meeting, an international group of researchers considered actions that should be taken to improve the outcome for women with ovarian cancer. Nine major recommendations are outlined in this Opinion article.

1,130 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

1,129 citations

Journal ArticleDOI
TL;DR: Despite the potential for residual axillary disease after SLND, SLND without ALND can offer excellent regional control and may be reasonable management for selected patients with early-stage breast cancer treated with breast-conserving therapy and adjuvant systemic therapy.
Abstract: Background and Objective:Sentinel lymph node dissection (SLND) has eliminated the need for axillary dissection (ALND) in patients whose sentinel node (SN) is tumor-free. However, completion ALND for patients with tumor-involved SNs remains the standard to achieve locoregional control. Few studies ha

1,128 citations

Journal ArticleDOI
13 Nov 2019-Nature
TL;DR: A reductionist approach is taken to define and separate the key determinants of drug resistance, which include tumour burden and growth kinetics; tumour heterogeneity; physical barriers; the immune system and the microenvironment; undruggable cancer drivers; and the many consequences of applying therapeutic pressures.
Abstract: The problem of resistance to therapy in cancer is multifaceted. Here we take a reductionist approach to define and separate the key determinants of drug resistance, which include tumour burden and growth kinetics; tumour heterogeneity; physical barriers; the immune system and the microenvironment; undruggable cancer drivers; and the many consequences of applying therapeutic pressures. We propose four general solutions to drug resistance that are based on earlier detection of tumours permitting cancer interception; adaptive monitoring during therapy; the addition of novel drugs and improved pharmacological principles that result in deeper responses; and the identification of cancer cell dependencies by high-throughput synthetic lethality screens, integration of clinico-genomic data and computational modelling. These different approaches could eventually be synthesized for each tumour at any decision point and used to inform the choice of therapy. A review of drug resistance in cancer analyses each biological determinant of resistance separately and discusses existing and new therapeutic strategies to combat the problem as a whole.

1,127 citations


Authors

Showing all 30708 results

NameH-indexPapersCitations
Gordon H. Guyatt2311620228631
Edward Giovannucci2061671179875
Irving L. Weissman2011141172504
Craig B. Thompson195557173172
Joan Massagué189408149951
Gad Getz189520247560
Chris Sander178713233287
Richard B. Lipton1762110140776
Richard K. Wilson173463260000
George P. Chrousos1691612120752
Stephen J. Elledge162406112878
Murray F. Brennan16192597087
Lewis L. Lanier15955486677
David W. Bates1591239116698
Dan R. Littman157426107164
Network Information
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023163
2022413
20214,330
20204,389
20194,156
20183,686