A network-based trans-omics approach for predicting synergistic drug combinations.

BACKGROUND: Combination therapy can offer greater efficacy on medical treatments. However, the discovery of synergistic drug combinations is challenging. We propose a novel computational method, SyndrumNET, to predict synergistic drug combinations by network propagation with trans-omics analyses. METHODS: The prediction is based on the topological relationship, network-based proximity, and transcriptional correlation between diseases and drugs. SyndrumNET was applied to analyzing six diseases including asthma, diabetes, hypertension, colorectal cancer, acute myeloid leukemia (AML), and chronic myeloid leukemia (CML). RESULTS: Here we show that SyndrumNET outperforms the previous methods in terms of high accuracy. We perform in vitro cell survival assays to validate our prediction for CML. Of the top 17 predicted drug pairs, 14 drug pairs successfully exhibits synergistic anticancer effects. Our mode-of-action analysis also reveals that the drug synergy of the top predicted combination of capsaicin and mitoxantrone is due to the complementary regulation of 12 pathways, including the Rap1 signaling pathway. CONCLUSIONS: The proposed method is expected to be useful for discovering synergistic drug combinations for various complex diseases.

Adding drug treatments together can sometimes produce better results for patients. We introduced a new computer-based method called SyndrumNET, designed to identify effective drug combinations for treating diseases. The method uses data about how diseases and drugs interact at a molecular level to predict which drugs work well together. Tested on six different diseases, such as asthma and different types of cancer, SyndrumNET proved to be more accurate than previous approaches. For example, most of the drug combinations predicted by SyndrumNET to rank highly have shown better combination effects on leukemia cells. This method also helped understand why certain drug combinations work better by analyzing their effects on cellular pathways. The findings suggest that SyndrumNET could be a valuable tool in developing more effective treatment for various complex diseases.

Intratracheal instillation of polyacrylic acid induced pulmonary fibrosis with elevated transforming growth factor-ß1 and connective tissue growth factor.

We investigated the intratracheal instillation of Polyacrylic acid (PAA) in rats to determine if it would cause pulmonary disorders, and to see what factors would be associated with the pathological changes. Male F344 rats were intratracheally instilled with low (0.2 mg/rat) and high (1.0 mg/rat) doses of PAA. They were sacrificed at 3 days, 1 week, 1 month, 3 months, and 6 months after PAA exposure to examine inflammatory and fibrotic changes in the lungs. There was a persistent increase in the neutrophil count, lactate dehydrogenase (LDH) levels, cytokine-induced neutrophil chemoattractant (CINC) values in bronchoalveolar lavage fluid (BALF), and heme oxygenase-1 (HO-1) in lung tissue. Transforming growth factor-beta 1 (TGF-ß1), a fibrotic factor, showed a sustained increase in the BALF until 6 months after intratracheal instillation, and connective tissue growth factor (CTGF) in lung tissue was elevated at 3 days after exposure. Histopathological findings in the lung tissue showed persistent (more than one month) inflammation, fibrotic changes, and epithelial-mesenchymal transition (EMT) changes. There was also a strong correlation between TGF-ß1 in the BALF and, especially, in the fibrosis score of histopathological specimens. Intratracheal instillation of PAA induced persistent neutrophilic inflammation, fibrosis, and EMT in the rats' lungs, and TGF-ß1 and CTGF appeared to be associated with the persistent fibrosis.

The Effects of Endoplasmic Reticulum Stress via Intratracheal Instillation of Water-Soluble Acrylic Acid Polymer on the Lungs of Rats.

Polyacrylic acid (PAA), an organic chemical, has been used as an intermediate in the manufacture of pharmaceuticals and cosmetics. It has been suggested recently that PAA has a high pulmonary inflammatory and fibrotic potential. Although endoplasmic reticulum stress is induced by various external and intracellular stimuli, there have been no reports examining the relationship between PAA-induced lung injury and endoplasmic reticulum stress. F344 rats were intratracheally instilled with dispersed PAA (molecular weight: 269,000) at low (0.5 mg/mL) and high (2.5 mg/mL) doses, and they were sacrificed at 3 days, 1 week, 1 month, 3 months and 6 months after exposure. PAA caused extensive inflammation and fibrotic changes in the lungs' histopathology over a month following instillation. Compared to the control group, the mRNA levels of endoplasmic reticulum stress markers Bip and Chop in BALF were significantly increased in the exposure group. In fluorescent immunostaining, both Bip and Chop exhibited co-localization with macrophages. Intratracheal instillation of PAA induced neutrophil inflammation and fibrosis in the rat lung, suggesting that PAA with molecular weight 269,000 may lead to pulmonary disorder. Furthermore, the presence of endoplasmic reticulum stress in macrophages was suggested to be involved in PAA-induced lung injury.

Utility of human cytochrome P450 inhibition data in the assessment of drug-induced liver injury.

Drug-induced liver injury (DILI) is a major cause of drug development discontinuation and drug withdrawal from the market, but there are no golden standard methods for DILI risk evaluation. Since we had found the association between DILI and CYP1A1 or CYP1B1 inhibition, we further evaluated the utility of cytochrome P450 (P450) inhibition assay data for DILI risk evaluation using decision tree analysis.The inhibitory activity of drugs with DILI concern (DILI drugs) and no DILI concern (no-DILI drugs) against 10 human P450s was assessed using recombinant enzymes and luminescent substrates. The drugs were also subjected to cytotoxicity assays and high-content analysis using HepG2 cells. Molecular descriptors were calculated by alvaDesc.Decision tree analysis was performed with the data obtained as variables with or without P450-inhibitory activity to discriminate between DILI drugs and no-DILI drugs. The accuracy was significantly higher when P450-inhibitory activity was included. After the decision tree discrimination, the drugs were further discriminated with the P450-inhibitory activity. The results demonstrated that many false-positive and false-negative drugs were correctly discriminated by using the P450 inhibition data.These results suggest that P450 inhibition assay data are useful for DILI risk evaluation.

DIRECTEUR: transcriptome-based prediction of small molecules that replace transcription factors for direct cell conversion.

MOTIVATION: Direct reprogramming (DR) is a process that directly converts somatic cells to target cells. Although DR via small molecules is safer than using transcription factors (TFs) in terms of avoidance of tumorigenic risk, the determination of DR-inducing small molecules is challenging. RESULTS: Here we present a novel in silico method, DIRECTEUR, to predict small molecules that replace TFs for DR. We extracted DR-characteristic genes using transcriptome profiles of cells in which DR was induced by TFs, and performed a variant of simulated annealing to explore small molecule combinations with similar gene expression patterns with DR-inducing TFs. We applied DIRECTEUR to predicting combinations of small molecules that convert fibroblasts into neurons or cardiomyocytes, and were able to reproduce experimentally verified and functionally related molecules inducing the corresponding conversions. The proposed method is expected to be useful for practical applications in regenerative medicine. AVAILABILITY AND IMPLEMENTATION: The code and data are available at the following link: https://github.com/HamanoLaboratory/DIRECTEUR.git.

Small compound-based direct cell conversion with combinatorial optimization of pathway regulations.

MOTIVATION: Direct cell conversion, direct reprogramming (DR), is an innovative technology that directly converts source cells to target cells without bypassing induced pluripotent stem cells. The use of small compounds (e.g. drugs) for DR can help avoid carcinogenic risk induced by gene transfection; however, experimentally identifying small compounds remains challenging because of combinatorial explosion. RESULTS: In this article, we present a new computational method, COMPRENDRE (combinatorial optimization of pathway regulations for direct reprograming), to elucidate the mechanism of small compound-based DR and predict new combinations of small compounds for DR. We estimated the potential target proteins of DR-inducing small compounds and identified a set of target pathways involving DR. We identified multiple DR-related pathways that have not previously been reported to induce neurons or cardiomyocytes from fibroblasts. To overcome the problem of combinatorial explosion, we developed a variant of a simulated annealing algorithm to identify the best set of compounds that can regulate DR-related pathways. Consequently, the proposed method enabled to predict new DR-inducing candidate combinations with fewer compounds and to successfully reproduce experimentally verified compounds inducing the direct conversion from fibroblasts to neurons or cardiomyocytes. The proposed method is expected to be useful for practical applications in regenerative medicine. AVAILABILITY AND IMPLEMENTATION: The code supporting the current study is available at the http://labo.bio.kyutech.ac.jp/~yamani/comprendre. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Association of CYP1A1 and CYP1B1 inhibition in in vitro assays with drug-induced liver injury.

Drug-induced liver injury (DILI) is one of the major causes for the discontinuation of drug development and withdrawal of drugs from the market. Since it is known that reactive metabolite formation and being substrates or inhibitors of cytochrome P450s (P450s) are associated with DILI, we systematically investigated the association between human P450 inhibition and DILI. The inhibitory activity of 266 DILI-positive drugs (DILI drugs) and 92 DILI-negative drugs (no-DILI drugs), which were selected from Liver Toxicity Knowledge Base (US Food and Drug Administration), against 8 human P450 forms was assessed using recombinant enzymes and luminescent substrates, and the threshold values showing the highest balanced accuracy for DILI discrimination were determined for each P450 enzyme using receiver operating characteristic analyses. The results showed that among the P450s tested, CYP1A1 and CYP1B1 were inhibited by DILI drugs more than no-DILI drugs with a statistical significance. We found that 91% of drugs that showed inhibitory activity greater than the threshold values against CYP1A1 or CYP1B1 were DILI drugs. The results of internal 5-fold cross-validation confirmed the usefulness of CYP1A1 and CYP1B1 inhibition data for the threshold-based discrimination of DILI drugs. Although the contribution of these P450s to drug metabolism in the liver is considered minimal, our present findings suggest that the assessment of CYP1A1 and CYP1B1 inhibition is useful for screening DILI risk of drug candidates at the early stage of drug development.