A low-density cDNA microarray with a unique reference RNA: pattern recognition analysis for IFN efficacy prediction to HCV as a model.

Akito Daiba; Niro Inaba; Satoshi Ando; Naoki Kajiyama; Hiroshi Yatsuhashi; Hiroshi Terasaki; Atsushi Ito; Masanori Ogasawara; Aki Abe; Junichi Yoshioka; Kazuhiro Hayashida; Shuichi Kaneko; Michinori Kohara; Satoru Ito

doi:10.1016/j.bbrc.2004.01.160

PubMed · 14985125

A low-density cDNA microarray with a unique reference RNA: pattern recognition analysis for IFN efficacy prediction to HCV as a model.

Akito Daiba·Niro Inaba·Satoshi Ando·Naoki Kajiyama·Hiroshi Yatsuhashi·Hiroshi Terasaki·Atsushi Ito·Masanori Ogasawara·Aki Abe·Junichi Yoshioka·Kazuhiro Hayashida·Shuichi Kaneko·Michinori Kohara·Satoru Ito

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Abstract

We have designed and established a low-density (295 genes) cDNA microarray for the prediction of IFN efficacy in hepatitis C patients. To obtain a precise and consistent microarray data, we collected a data set from three spots for each gene (mRNA) and using three different scanning conditions. We also established an artificial reference RNA representing pseudo-inflammatory conditions from established hepatocyte cell lines supplemented with synthetic RNAs to 48 inflammatory genes. We also developed a novel algorithm that replaces the standard hierarchical-clustering method and allows handling of the large data set with ease. This algorithm utilizes a standard space database (SSDB) as a key scale to calculate the Mahalanobis distance (MD) from the center of gravity in the SSDB. We further utilized sMD (divided by parameter k: MD/k) to reduce MD number as a predictive value. The efficacy prediction of conventional IFN mono-therapy was 100% for non-responder (NR) vs. transient responder (TR)/sustained responder (SR) (P < 0.0005). Finally, we show that this method is acceptable for clinical application.

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Algorithms Antiviral Agents Cell Line, Tumor Cluster Analysis Gene Expression Profiling Gene Expression Regulation, Viral Hepacivirus Hepatitis C Humans Interferons Models, Genetic Models, Statistical Oligonucleotide Array Sequence Analysis Pattern Recognition, Automated RNA Reference Values Sensitivity and Specificity Journal Article

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Akito Daiba, Niro Inaba, Satoshi Ando, Naoki Kajiyama, Hiroshi Yatsuhashi, Hiroshi Terasaki, Atsushi Ito, Masanori Ogasawara, Aki Abe, Junichi Yoshioka, Kazuhiro Hayashida, Shuichi Kaneko, Michinori Kohara, Satoru Ito. 2004-03-19. A low-density cDNA microarray with a unique reference RNA: pattern recognition analysis for IFN efficacy prediction to HCV as a model.. https://doi.org/10.1016/j.bbrc.2004.01.160

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