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Understanding the molecular basis of drug treatments is important for drug screening and drug efficiency testing to identify suitable interventions. However, heterogeneity among individual patients contributes to variation in responses to different treatments, making it difficult to predict treatment outcomes based on the disease or drug type alone. Therefore, developing effective approaches for evaluating drug responses in individual patients is important. Functional analyses using patient-derived cell lines, patient-derived xenografts (PDXs), or organoids are conventionally used for such purposes; however, these models can be time-consuming and difficult to establish. We applied Drug Ex vivo Test (DExT) to tumor tissues from two clear cell renal cell carcinoma (ccRCC) PDX models. Tissues were exposed ex vivo to the dual mTOR complex inhibitor TAK-228 for up to 120 minutes, and treatment-associated phosphorylation changes were measured by quantitative mass spectrometry-based phosphoproteomic analysis relative to time-matched untreated controls. Here we show that DExT captures acute drug-induced phosphorylation changes in ccRCC tumor tissues. TAK-228 reduces phosphorylation of EIF4EBP1-S65, consistent with inhibition of mTOR signaling. These findings demonstrate the initial feasibility of DExT for measuring drug-induced molecular responses directly in tumor-derived tissue material and provide a foundation for further evaluation with additional therapeutic agents and clinical specimens. People with the same type of cancer can respond differently to the same treatment. Current drug-response tests often require growing tumor cells or creating tumor models, which take time and may not always succeed. We developed Drug Ex vivo Test (DExT), which applies a drug directly to tumor tissue for a short period and then measures molecular changes caused by the treatment. We tested DExT using tumor tissues from two clear cell kidney cancer models and a drug that blocks a cancer-related signaling pathway. We detected changes consistent with the expected drug effect. These findings support further development of DExT through larger studies using patient tumor samples and a wider range of drugs.
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Lih et al. (2026) studied this question.
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