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Abstract Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number of possible drug-dose combinations vastly exceeds what could be tested in patient cells. Here, we describe a machine learning approach, scTherapy, which leverages single-cell transcriptomic profiles to prioritize multi-targeting treatment options for individual patients with hematological cancers or solid tumors. Patient-specific treatments reveal a wide spectrum of co-inhibitors of multiple biological pathways predicted for primary cells from heterogenous cohorts of patients with acute myeloid leukemia and high-grade serous ovarian carcinoma, each with unique resistance patterns and synergy mechanisms. Experimental validations confirm that 96% of the multi-targeting treatments exhibit selective efficacy or synergy, and 83% demonstrate low toxicity to normal cells, highlighting their potential for therapeutic efficacy and safety. In a pan-cancer analysis across five cancer types, 25% of the predicted treatments are shared among the patients of the same tumor type, while 19% of the treatments are patient-specific. Our approach provides a widely-applicable strategy to identify personalized treatment regimens that selectively co-inhibit malignant cells and avoid inhibition of non-cancerous cells, thereby increasing their likelihood for clinical success.

Summary: Patient-derived organoids (PDOs) are ideal ex vivo model systems to study cancer progression and drug resistance mechanisms. Here, we present a protocol for measuring drug efficacy in three-dimensional (3D) high-grade serous ovarian cancer PDO cultures through quantification of cytotoxicity using propidium iodide incorporation in dead cells. We also provide detailed steps to analyze proliferation of PDOs using the Ki67 biomarker. We describe steps for sample processing, immunofluorescent staining, high-throughput confocal imaging, and image-based quantification for 3D cultures.For complete details on the use and execution of this protocol, please refer to Lahtinen et al. (2023).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Quiescent cancer cells in malignant tumors can withstand cell-cycle active treatment and cause cancer spread and recurrence. Three-dimensional (3D) cancer cell models have led to the identification of oxidative phosphorylation (OXPHOS) as a context-dependent vulnerability. The limited treatment options for advanced hepatocellular carcinoma (HCC) and colorectal carcinoma (CRC) metastatic to the liver include the multikinase inhibitors sorafenib and regorafenib. Off-target effects of sorafenib and regorafenib are related to OXPHOS inhibition; however the importance of this feature to the effect on tumor cells has not been investigated in 3D models. We began by assessing global transcriptional responses in monolayer cell cultures, then moved on to multicellular tumor spheroids (MCTS) and tumoroids generated from a CRC patient. Cells were treated with chemotherapeutics, kinase inhibitors, and the OXPHOS inhibitors. Cells grown in 3D cultures were sensitive to the OXPHOS inhibitor nitazoxanide, sorafenib, and regorafenib and resistant to other multikinase inhibitors and chemotherapeutic drugs. Furthermore, nitazoxanide and sorafenib reduced viability, regrowth potential and inhibited mitochondrial membrane potential in an additive manner at clinically relevant concentrations. This study demonstrates that the OXPHOS inhibition caused by sorafenib and regorafenib parallels 3D activity and can be further investigated for new combination strategies.

Summary: Spheroid cultures of primary human hepatocytes (PHH) are used in studies of hepatic drug metabolism and toxicity. The cultures are maintained under different conditions, with possible confounding results. We performed an in-depth analysis of the influence of various culture conditions to find the optimal conditions for the maintenance of an in vivo like phenotype. The formation, protein expression, and function of PHH spheroids were followed for three weeks in a high-throughput 384-well format. Medium composition affected spheroid histology, global proteome profile, drug metabolism and drug-induced toxicity. No epithelial-mesenchymal transition was observed. Media with fasting glucose and insulin levels gave spheroids with phenotypes closest to normal PHH. The most expensive medium resulted in PHH features most divergent from that of native PHH. Our results provide a protocol for culture of healthy PHH with maintained function - a prerequisite for studies of hepatocyte homeostasis and more reproducible hepatocyte research.