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1.
Biochim Biophys Acta Rev Cancer ; 1878(5): 188942, 2023 09.
Article in English | MEDLINE | ID: mdl-37343729

ABSTRACT

Renal cell carcinoma (RCC) and its principal subtype, clear cell RCC, are the most diagnosed kidney cancer. Despite substantial improvement over the last decades, current pharmacological intervention still fails to achieve long-term therapeutic success. RCC is characterized by a high intra- and inter-tumoral heterogeneity and is heavily influenced by the crosstalk of the cells composing the tumor microenvironment, such as cancer-associated fibroblasts, endothelial cells and immune cells. Moreover, multiple physicochemical properties such as pH, interstitial pressure or oxygenation may also play an important role. These elements are often poorly recapitulated in in vitro models used for drug development. This inadequate recapitulation of the tumor is partially responsible for the current lack of an effective and curative treatment. Therefore, there are needs for more complex in vitro or ex vivo drug screening models. In this review, we discuss the current state-of-the-art of RCC models and suggest strategies for their further development.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Humans , Carcinoma, Renal Cell/drug therapy , Endothelial Cells/pathology , Kidney Neoplasms/drug therapy , Tumor Microenvironment
2.
Mol Oncol ; 14(11): 2894-2919, 2020 11.
Article in English | MEDLINE | ID: mdl-33021054

ABSTRACT

The current standard of care for colorectal cancer (CRC) is a combination of chemotherapeutics, often supplemented with targeted biological drugs. An urgent need exists for improved drug efficacy and minimized side effects, especially at late-stage disease. We employed the phenotypically driven therapeutically guided multidrug optimization (TGMO) technology to identify optimized drug combinations (ODCs) in CRC. We identified low-dose synergistic and selective ODCs for a panel of six human CRC cell lines also active in heterotypic 3D co-culture models. Transcriptome sequencing and phosphoproteome analyses showed that the mechanisms of action of these ODCs converged toward MAP kinase signaling and cell cycle inhibition. Two cell-specific ODCs were translated to in vivo mouse models. The ODCs reduced tumor growth by ~80%, outperforming standard chemotherapy (FOLFOX). No toxicity was observed for the ODCs, while significant side effects were induced in the group treated with FOLFOX therapy. Identified ODCs demonstrated significantly enhanced bioavailability of the individual components. Finally, ODCs were also active in primary cells from CRC patient tumor tissues. Taken together, we show that the TGMO technology efficiently identifies selective and potent low-dose drug combinations, optimized regardless of tumor mutation status, outperforming conventional chemotherapy.


Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Colorectal Neoplasms/drug therapy , Animals , Antineoplastic Combined Chemotherapy Protocols/administration & dosage , Antineoplastic Combined Chemotherapy Protocols/pharmacology , Cell Cycle/drug effects , Cell Line, Tumor , Colorectal Neoplasms/genetics , Dose-Response Relationship, Drug , Female , HCT116 Cells , Humans , Male , Mice , Transcriptome/drug effects , Treatment Outcome
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