Molecular diagnosis of human cancer type by gene expression profiles and independent component analysis.
The precise diagnosis of cancer type based on microarray data is of particular importance and is also a challenging task. We have devised a novel pattern recognition procedure based on independent component analysis (ICA). Different from the conventional cancer classification methods, which are limited in their clinical applicability of cancer diagnosis, our method extracts explicitly, by ICA algorithm, a set of specific diagnostic patterns of normal and tumor tissues corresponding to a set of biomarkers for clinical use. We validated our procedure with the colon and prostate cancer data sets and achieved good diagnosis (>90%) on the data sets studied here. This technique is also suitable for the identification of diagnostic expression patterns for other human cancers and demonstrates the feasibility of simple and accurate molecular cancer diagnostics for clinical implementation.
Zhang
Xue Wu
XW
College of Light Industry and Food Sciences, South China University of Technology, Guangzhou, China. snow_dance@sina.com
Yap
Yee Leng
YL
Wei
Dong
D
Chen
Feng
F
Danchin
Antoine
A
D000465:Algorithms; D003110:Colonic Neoplasms / Q000175:diagnosis* / Q000235:genetics; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D020411:Oligonucleotide Array Sequence Analysis; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000235:genetics