The Flow Cytometry Shared Resource provides cell analysis and cell sorting services for cancer research in the Stanford community. The mission of the Flow Cytometry Shared Resource is to (1) promote cancer research and training for cell-based assays at the highest level of quality and rigor, (2) bring new developments in instrumentation, technique and analysis for preclinical use in the Stanford research community, and (3) support early clinical trial analysis in patient management. The Flow Cytometry Shared Resource enhances the productivity and effectiveness of research by promoting high-content data acquisition, assuring the highest data quality and consistency, carrying out efficient cell sorting, providing reliable data management, educating and training researchers and consulting in experiment design and evaluation. A large majority (88%) of current use in this Shared Resource is by Cancer Center members. In fiscal year 2005, the Flow Cytometry Shared Resource provided approximately 12,500 hours of cell analysis and cell sorting service to 490 individual researchers in the laboratories of 97 Stanford investigators. An oversight committee provides recommendations on Shared Resource policies and activities, ensuring that this Shared Resource is aligned with the Cancer Center's strategic goals. This Shared Resource has been at the cutting edge in the development of stem cell analysis and intracellular signaling analysis in leukemia and other cancers. It will greatly facilitate new understanding of stem cells in cancer, development of bioinformatics tools for analysis of complex flow cytometric datasets, patient cell analysis, and early development of biomarkers for patient stratification.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA124435-03
Application #
7826903
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2009-06-01
Budget End
2010-05-31
Support Year
3
Fiscal Year
2009
Total Cost
$58,210
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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

Showing the most recent 10 out of 322 publications