Decomposition profile data analysis of multiple drug effects identifies endoplasmic reticulum stress-inducing ability as an unrecognized factor

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. Small compounds have the capacity to interact with multiple cellular proteins, thereby mediating multiple effects depending on their exposure to interacting proteins. It is quite difficult to identify the full range of effects of a new chemical, even for its developers, and some factors may be unrecognized. Even approved drugs show off-target effects that are often unrecognized during drug development, and which can lead to adverse reactions including lethal effects. For instance, astemizole has been withdrawn from the market in most countries because it causes a fatal side effect, cardiac arrhythmia 1,2 , by blocking the human Ether-ago go Related Gene potassium channel, thereby causing QT interval prolongation and torsade de pointes. However, we should not be too negative about unrecognized effects of small compounds, because identification of these can lead to drug repurposing. For example, memantine was synthesized in 1968 as a derivative of amantadine, an anti-influenza agent. Recently, it was revealed that this anti-influenza agent is also an antagonist for the N-methyl-D-aspartate receptor, and the drug has become a medication for dementia 3. Thus, the important question is how such unrecognized effects of chemicals can be identified. Profile data analysis is quite useful in addressing this issue. Although the terminology sometimes varies between contexts, the method is a type of multivariate analysis that describes data using multiple variables and investigates the relationship between data with high robustness and detection power by sharing information about the structure of the data 4. Data from "omics" analysis, which converts biological information of a specim...

An in vivo drug repurposing screen and transcriptional analyses reveals the serotonin pathway and GSK3 as major therapeutic targets for NGLY1 deficiency

“…Alternatively, trimipramine, and possibly other compounds like lithium, may rescue lethality and larval size defects through a separate mechanism. Trimipramine induces the expression of ER stress markers, including spliced XBP1, GRP78, CHOP, and phosphorylated IRE1a in multiple cell lines [ 47 ]. Similarly, lithium treatment upregulated expression of GRP78 and the antiapoptotic protein Bcl-2 [ 48 ].…”

Decomposition Profile Data Analysis for Deep Understanding of Multiple Effects of Natural Products

“…Compared with the straightforward approach shown in Figure S1a (Supporting Information), the proposed approach reduces the costs for evaluation by restricting the candidate effects to be evaluated and systematically analyzing all possible effects by using their unsupervised and comprehensive characteristics (Figure , Figure S1b). Previously, we confirmed that decomposition profile data analysis actually identified unrecognized toxic aspects of FDA-approved drugs, while natural products were not analyzed . Thus, we analyzed transcriptome data for MCF7 cells treated with 293 compounds including natural products as derived from the CMap database with OLSA.…”

“…When a natural product is newly discovered and purified, its effects are investigated by observing the responses of culture cells treated with the compound. While the easily observable effects such as cytotoxicity and morphological changes are often observable and easily understood, the other effects are difficult to recognize and often missed . A straightforward scheme for investigating the effects of chemicals has the following flow: hypothesis formulation, construction of an assay system for testing the hypothesis, and conducting experiments with the assay system.…”

“…OLSA decomposes the profile data set of chemicals, representing their multiple effects, into factors, reflecting decomposed effects. As an example, we revealed latent endoplasmic reticulum stress inducibility of some of U.S. Food and Drug Agency (FDA)-approved drugs as an unrecognized aspect by analyzing a decomposed effect derived from OLSA . In this regard, we call this kind of approach decomposition profile data analysis.…”

An in vivo drug repurposing screen and transcriptional analyses reveals the serotonin pathway and GSK3 as major therapeutic targets for NGLY1 deficiency

“…Alternatively, trimipramine, and possibly other compounds like lithium, may rescue lethality and larval size defects through a separate mechanism. Trimipramine induces the expression of ER stress markers, including spliced XBP1, GRP78, CHOP, and phosphorylated IRE1a in multiple cell lines (Morita et al, 2020). Similarly, lithium treatment upregulated expression of GRP78 and the antiapoptotic protein Bcl-2 (Hiroi et al, 2005).…”