? TOPS The overarching goal of the Translational Oncology Program at Stanford (TOPS) is to foster collaboration across scientific and clinical disciplines in order to gain deeper insights into the underlying causes of cancer and to develop more effective diagnostic, prognostic and therapeutic approaches to cancer. The TOPS Program was newly created in 2013 to meet the translational goals of the SCI. The program brings together translational and clinical researchers, chemists, biologists and biostatisticians who have a focus on projects that will have substantial clinical impact on solid tumors. The program is based on the activities of a number of working groups including the solid tumor Clinical Research Groups (CRGs) and the Developmental Therapeutics (Phase I) Working Group. Program members meet monthly to discuss topics of broad general interest to translational researchers. The new Jill and John Freidenrich Center for Translational Research (FCTR) provides a venue that brings together interdisciplinary teams of investigators and research staff whose interests are centered around specific cancer types. The building provides collaborative meeting spaces and serves as a single convenient location for the disease-specific interdisciplinary research teams. All TOPS meetings and working groups encourage the participation of graduate students and fellows to form new interdisciplinary interactions. Co-led by Mark Pegram, MD and George Sledge, MD, the 42 members of the TOPS Program represent 16 departments and three schools within the University, of whom 13 have been recruited to the Stanford faculty since the last review. The research activities of the 42 investigators are supported by 27 peer- reviewed, investigator-initiated grants and include a NCI U10 grant. Peer-reviewed funding consists of $8.1M in total annual costs of which $4.2M is from the NCI. Other NIH support amounts to $3.0M, and other peer-reviewed support to $0.9 million. Since 2009, program members have published over 570 manuscripts of which 12% are intra- and 34% are inter-programmatic. The SCI will continue to be invaluable to the program by fostering innovative projects and assisting with the translation of research findings into the clinic for the benefit of cancer patients.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA124435-10
Application #
9359344
Study Section
Special Emphasis Panel (ZCA1-RTRB-0)
Program Officer
Marino, Michael A
Project Start
Project End
Budget Start
2017-06-01
Budget End
2018-05-31
Support Year
10
Fiscal Year
2017
Total Cost
$32,997
Indirect Cost
$12,114
Name
Stanford University
Department
Type
Domestic Higher Education
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Malta, Tathiane M; Sokolov, Artem; Gentles, Andrew J et al. (2018) Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation. Cell 173:338-354.e15
Banerjee, Imon; Gensheimer, Michael Francis; Wood, Douglas J et al. (2018) Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives. Sci Rep 8:10037
Thorsson, Vésteinn; Gibbs, David L; Brown, Scott D et al. (2018) The Immune Landscape of Cancer. Immunity 48:812-830.e14
Rogers, Zoë N; McFarland, Christopher D; Winters, Ian P et al. (2018) Mapping the in vivo fitness landscape of lung adenocarcinoma tumor suppression in mice. Nat Genet 50:483-486
Nair, Viswam S; Sundaram, Vandana; Desai, Manisha et al. (2018) Accuracy of Models to Identify Lung Nodule Cancer Risk in the National Lung Screening Trial. Am J Respir Crit Care Med 197:1220-1223
She, Richard; Jarosz, Daniel F (2018) Mapping Causal Variants with Single-Nucleotide Resolution Reveals Biochemical Drivers of Phenotypic Change. Cell 172:478-490.e15
Champion, Magali; Brennan, Kevin; Croonenborghs, Tom et al. (2018) Module Analysis Captures Pancancer Genetically and Epigenetically Deregulated Cancer Driver Genes for Smoking and Antiviral Response. EBioMedicine 27:156-166
Zhou, Mu; Leung, Ann; Echegaray, Sebastian et al. (2018) Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications. Radiology 286:307-315
Pollom, Erqi L; Fujimoto, Dylann K; Han, Summer S et al. (2018) Newly diagnosed glioblastoma: adverse socioeconomic factors correlate with delay in radiotherapy initiation and worse overall survival. J Radiat Res 59:i11-i18
Nørgaard, Caroline Holm; Jakobsen, Lasse Hjort; Gentles, Andrew J et al. (2018) Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow - A proof of concept study. PLoS One 13:e0193249

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