Publication Date:
2004-11-13
Description:
We present a method for high-throughput cytological profiling by microscopy. Our system provides quantitative multidimensional measures of individual cell states over wide ranges of perturbations. We profile dose-dependent phenotypic effects of drugs in human cell culture with a titration-invariant similarity score (TISS). This method successfully categorized blinded drugs and suggested targets for drugs of uncertain mechanism. Multivariate single-cell analysis is a starting point for identifying relationships among drug effects at a systems level and a step toward phenotypic profiling at the single-cell level. Our methods will be useful for discovering the mechanism and predicting the toxicity of new drugs.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Perlman, Zachary E -- Slack, Michael D -- Feng, Yan -- Mitchison, Timothy J -- Wu, Lani F -- Altschuler, Steven J -- P01 CA078048/CA/NCI NIH HHS/ -- New York, N.Y. -- Science. 2004 Nov 12;306(5699):1194-8.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Institute of Chemistry and Cell Biology, Harvard Medical School, Boston, MA 02115, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/15539606" target="_blank"〉PubMed〈/a〉
Keywords:
Automation
;
Cell Cycle/drug effects
;
Cluster Analysis
;
DNA/analysis
;
Dose-Response Relationship, Drug
;
Drug Evaluation, Preclinical/*methods
;
Fluorescent Dyes
;
HeLa Cells
;
Humans
;
Image Processing, Computer-Assisted
;
*Microscopy, Fluorescence
;
Pharmacology/*methods
;
Phenotype
;
Statistics as Topic
;
Toxicity Tests/*methods
Print ISSN:
0036-8075
Electronic ISSN:
1095-9203
Topics:
Biology
,
Chemistry and Pharmacology
,
Computer Science
,
Medicine
,
Natural Sciences in General
,
Physics
