Abstract
Chemicals have multiple effects in biological systems. Because their on-target effects dominate the output, their off-target effects are often overlooked and can sometimes cause dangerous adverse events. Recently, we developed a novel decomposition profile data analysis method, orthogonal linear separation analysis (OLSA), to analyse multiple effects. In this study, we tested whether OLSA identified the ability of drugs to induce endoplasmic reticulum (ER) stress as a previously unrecognized factor. After analysing the transcriptome profiles of MCF7 cells treated with different chemicals, we focused on a vector characterized by well-known ER stress inducers, such as ciclosporin A. We selected five drugs predicted to be unrecognized ER stress inducers, based on their inducing ability scores derived from OLSA. These drugs actually induced X-box binding protein 1 splicing, an indicator of ER stress, in MCF7 cells in a concentration-dependent manner. Two structurally different representatives of the five test compounds exhibited similar results in HepG2 and HuH7 cells, but not in PXB primary hepatocytes derived from human-liver chimeric mice. These results indicate that our decomposition strategy using OLSA uncovered the ER stress-inducing ability of drugs as an unrecognized effect, the manifestation of which depended on the background of the cells.
Highlights
Chemicals have multiple effects in biological systems
The genes constituting each vector were sorted by their absolute values and the top 1% genes were subjected to gene ontology (GO) analysis
We focused on vector P14V because the top 1% of vector genes was significantly enriched for GO terms relevant to endoplasmic reticulum (ER) stress induction, such as 0034976, 0035966, and 0006986 (Fig. 1b, Supplementary Data)
Summary
Chemicals have multiple effects in biological systems. Because their on-target effects dominate the output, their off-target effects are often overlooked and can sometimes cause dangerous adverse events. Two structurally different representatives of the five test compounds exhibited similar results in HepG2 and HuH7 cells, but not in PXB primary hepatocytes derived from human-liver chimeric mice. These results indicate that our decomposition strategy using OLSA uncovered the ER stress-inducing ability of drugs as an unrecognized effect, the manifestation of which depended on the background of the cells. These “big data” have been utilized to search for compounds that induce similar or even counteracting effects on gene e xpression[5] Such gene expression changes comprise a profile and have, for example, been employed to identify that ribavirin could induce reprogramming of docetaxel-resistant prostate cancer to be docetaxel s ensitive[6]
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