Periodic Reporting for period 3 - OPTIM (Optimized drug combinations for effective cancer treatment: a personalised approach.)
Período documentado: 2019-05-01 hasta 2020-04-30
The current standard-of-care for colorectal carcinoma (CRC) is a combination of chemotherapeutics, often supplemented with targeted biological drugs. Despite recent improvements, an urgent need exists for improved efficacy, especially at late-stage disease, and minimized side effects.
In this project we employed our recently developed and validated mathematical approach of the phenotypically-driven therapeutically guided multidrug optimization (TGMO) technology, to identify individualized optimized drug combinations (ODCs) for CRC treatment. We identified low-dose synergistic and selective ODCs specific for a panel of six human colorectal carcinoma cells, that were highly active in 3-dimensional human heterotypic co-culture models. Transcriptome sequencing and phosphoproteome analyses showed that the mechanisms of action of these ODCs converge towards MAP kinase signaling and cell cycle inhibition present despite differential cell mutation status, transcript expression levels and protein kinase phosphorylation state. Cell-specific ODCs were successfully translated in two in vivo models. The ODCs reduced tumor growth by approximately 80% and significantly outperformed the standard chemotherapy (FOLFOX). Complete lack of toxicity was observed for the ODCs, while significant side effects were induced after FOLFOX therapy. Pharmacokinetics demonstrated that the drug combinations showed significantly enhanced bioavailability of individual components. Finally, the high-order ODCs were also active in freshly isolated cells from human CRC patient tumor tissues.
Taken together, we proved that the TGMO technology may efficiently identify selective and potent low-dose multidrug combinations that outperforme conventional chemotherapy and are optimized regardless of tumor mutation status.
In this project we employed our recently developed and validated mathematical approach of the phenotypically-driven therapeutically guided multidrug optimization (TGMO) technology, to identify individualized optimized drug combinations (ODCs) for CRC treatment. We identified low-dose synergistic and selective ODCs specific for a panel of six human colorectal carcinoma cells, that were highly active in 3-dimensional human heterotypic co-culture models. Transcriptome sequencing and phosphoproteome analyses showed that the mechanisms of action of these ODCs converge towards MAP kinase signaling and cell cycle inhibition present despite differential cell mutation status, transcript expression levels and protein kinase phosphorylation state. Cell-specific ODCs were successfully translated in two in vivo models. The ODCs reduced tumor growth by approximately 80% and significantly outperformed the standard chemotherapy (FOLFOX). Complete lack of toxicity was observed for the ODCs, while significant side effects were induced after FOLFOX therapy. Pharmacokinetics demonstrated that the drug combinations showed significantly enhanced bioavailability of individual components. Finally, the high-order ODCs were also active in freshly isolated cells from human CRC patient tumor tissues.
Taken together, we proved that the TGMO technology may efficiently identify selective and potent low-dose multidrug combinations that outperforme conventional chemotherapy and are optimized regardless of tumor mutation status.
This project aimed to improve the treatment of colorectal carcinoma (CRC). The key to improvement of cancer therapy resides in optimal combination of drugs. Optimally combining drugs is non-trivial due to the large number of possibilities, especially when more than two drugs are combined at various doses. In the current research program it was proposed to use a mathematics-based phenotypic approach to guide the way in finding optimal combination therapies in the least possible experimental effort.
During this reporting period we have: (1) developed mathematical methods to optimize multidrug combinations in both non-cancerous and cancerous cells, (2) modelled the drug-drug interactions, (3) characterised the activity and toxicity of optimized high-order drug combinations in 2D models, (3) explored their activity in 3D complex models role of shape-change of flagella due to its flexibility on the generation of hydrodynamic forces and flows, (4) developed new short-term 3D human co-culture spheroids to capture the drug-drug interactions in complex microenvironment, (5) have shown that this in vitro optimized drug combination are active in vivo, (6) characterised the pharmacokinetics of the opimized drug combinations, (7) provided an accurate theoretical prediction for the value of the bacterial motor torque, (8) developed novel theoretical models for the bundling and unbundling of bacterial flagella, (9) captured theoretically the role of the MAPK signaling pathway on activity of the optimized drug combinations, (10) started new experimental collaborations
We have already achieved numerous remarkable deliverables:
- 10 scientific peer-reviewed publications
- 1 patent (priority stage)
- 2 personal awards (2019 SVG award, and 2020 3R UNIGE award)
- 17 presentation at national and international conferences
- 20 press releases and radio interviews
During this reporting period we have: (1) developed mathematical methods to optimize multidrug combinations in both non-cancerous and cancerous cells, (2) modelled the drug-drug interactions, (3) characterised the activity and toxicity of optimized high-order drug combinations in 2D models, (3) explored their activity in 3D complex models role of shape-change of flagella due to its flexibility on the generation of hydrodynamic forces and flows, (4) developed new short-term 3D human co-culture spheroids to capture the drug-drug interactions in complex microenvironment, (5) have shown that this in vitro optimized drug combination are active in vivo, (6) characterised the pharmacokinetics of the opimized drug combinations, (7) provided an accurate theoretical prediction for the value of the bacterial motor torque, (8) developed novel theoretical models for the bundling and unbundling of bacterial flagella, (9) captured theoretically the role of the MAPK signaling pathway on activity of the optimized drug combinations, (10) started new experimental collaborations
We have already achieved numerous remarkable deliverables:
- 10 scientific peer-reviewed publications
- 1 patent (priority stage)
- 2 personal awards (2019 SVG award, and 2020 3R UNIGE award)
- 17 presentation at national and international conferences
- 20 press releases and radio interviews
Beyond the current state of the art, expected results until the end of the project include primarily the identification of the cell-type specific optimized multidrug combinations successfully translated to the in vivo conditions and outperforming existing chemotherapies
Our established research programme uniquely combines state-of-the-art experiments and computations with mathematical modelling, collectively aimed at providing the most complete understanding of drug-drug interactions. It is envisioned that such approach will enable the most precise understanding of the role of drug-drug interactions and their activity while improving, the stratification of patients and the design of personalised therapies.
Our established research programme uniquely combines state-of-the-art experiments and computations with mathematical modelling, collectively aimed at providing the most complete understanding of drug-drug interactions. It is envisioned that such approach will enable the most precise understanding of the role of drug-drug interactions and their activity while improving, the stratification of patients and the design of personalised therapies.