Periodic Reporting for period 2 - DocTIS (DECISION ON OPTIMAL COMBINATORIAL THERAPIES IN IMIDS USING SYSTEMS APPROACHES)
Reporting period: 2021-07-01 to 2022-12-31
Immune-Mediated Inflammatory Diseases (IMIDs) are a group of common autoimmune diseases that include clinically heterogeneous disorders such as rheumatoid arthritis, psoriasis, psoriatic arthritis, Crohn’s disease, ulcerative colitis and systemic lupus erythematosus. Despite their clinical heterogeneity, IMIDs share a significant number of features at the molecular and cellular levels. Recently developed therapies like anti-TNF agents, targeting common key molecules of the immune system, have collectively resulted in a significant improvement in the management of IMIDs. Despite this major medical achievement, there is a still a too high percentage of patients who will not respond at all to a given targeted therapy (40% on average). Also, none of the developed therapies are able to achieve complete remission for most patients or for a sustained amount of time. This lack of efficacy affects the quality of life of many patients and poses an enormous social and economic burden.
The DocTIS project is aimed at addressing the urgent need to discover effective therapeutic strategies for IMIDs in a personalised way. It proposes using novel systems level approaches to identify the best drug combinations based on translating the data from high-throughput technology analysis of biobank samples from patients, highly curated clinical data, and evidence from model organisms into actionable evidence to on which to base preclinical studies of combinatorial therapies.The main objective of the project is to provide a clinical proof of concept that a deep understanding of the pathophysiology of IMIDs can be used to find synergic treatments that will be much more beneficial than the current monotherapy approach.
The DocTIS project is aimed at addressing the urgent need to discover effective therapeutic strategies for IMIDs in a personalised way. It proposes using novel systems level approaches to identify the best drug combinations based on translating the data from high-throughput technology analysis of biobank samples from patients, highly curated clinical data, and evidence from model organisms into actionable evidence to on which to base preclinical studies of combinatorial therapies.The main objective of the project is to provide a clinical proof of concept that a deep understanding of the pathophysiology of IMIDs can be used to find synergic treatments that will be much more beneficial than the current monotherapy approach.
The following work has been performed:
Regarding WP2, High throughput data management, the clinical database was recoded into international standard annotations in order to fulfil the FAIR recommendations (i.e. SNOMED-CT and WHO terminologies). The DoCTIS data analysis environment -JupyterLab Notebook- was created in the IMIDomics EC2 cloud server, and is ready to undergo the computational analyses required for the processing and analysis of the molecular and clinical data associated with the project.
Regarding WP3, the selection from each of the 12 IMID x drug patient groups was initiated. The patient selection has been completed for RA (2 drugs), PsA (2 drugs), Ps (1 drug), the request to the IMID-Biobank for the corresponding biological samples approved, and the samples are being analyzed using the diverse platforms (WP4). The selection for the remaining drugxIMID combinations will be completed in the following months.
In WP5, Systems biology analysis, the DocTIS has developed the Learning Disease Models (LDMs) using single cell data from mouse models for IMIDs. LDMs are the central analytical approach followed in DoCTIS. It works by connecting differentially expressed genes in each cell type based on predicted molecular interactions. The resulting network model will be then used as a template for LDM construction on the patient data generated by the project. LIU is currently trying different network tools to prioritise cell types, pathways and interactions. Additionally, available bulk data from IMID patients is being compiled and processed to be later integrated with the data generated from the project.
Regarding WP6, Preclinical validation of combinatorial therapies, the work performed regarding the animal models can be summarized as follows:
- Rheumatoid arthritis: the different approaches taken to circumvent the limitation imposed by COVID-19 pandemic have been successful, and currently the mice are being bred to start the collagen-induced arthritis mice model.
- Crohn’s disease: the SAMP1/YitFc mouse strain develops ileitis spontaneously with a 100% penetrance by the 30th week of age making it a good model to study the Crohn’s disease combinatorial therapies.
- Ulcerative colitis: the implementation of the model in the IDIBAPS’s animal facility was successful, and the experiments with anti-TFNα therapy have started.
- Systematic Lupus Erythematous: a murine anti-CD20 antibody emulating Rituximab, has been produced.
Regarding WP9, Dissemination and exploitation, the website and the professional LinkedIn and Twitter accounts have been created. These sites are used to periodically post news from the project, the partners and relevant developments in IMIDs.
Regarding WP2, High throughput data management, the clinical database was recoded into international standard annotations in order to fulfil the FAIR recommendations (i.e. SNOMED-CT and WHO terminologies). The DoCTIS data analysis environment -JupyterLab Notebook- was created in the IMIDomics EC2 cloud server, and is ready to undergo the computational analyses required for the processing and analysis of the molecular and clinical data associated with the project.
Regarding WP3, the selection from each of the 12 IMID x drug patient groups was initiated. The patient selection has been completed for RA (2 drugs), PsA (2 drugs), Ps (1 drug), the request to the IMID-Biobank for the corresponding biological samples approved, and the samples are being analyzed using the diverse platforms (WP4). The selection for the remaining drugxIMID combinations will be completed in the following months.
In WP5, Systems biology analysis, the DocTIS has developed the Learning Disease Models (LDMs) using single cell data from mouse models for IMIDs. LDMs are the central analytical approach followed in DoCTIS. It works by connecting differentially expressed genes in each cell type based on predicted molecular interactions. The resulting network model will be then used as a template for LDM construction on the patient data generated by the project. LIU is currently trying different network tools to prioritise cell types, pathways and interactions. Additionally, available bulk data from IMID patients is being compiled and processed to be later integrated with the data generated from the project.
Regarding WP6, Preclinical validation of combinatorial therapies, the work performed regarding the animal models can be summarized as follows:
- Rheumatoid arthritis: the different approaches taken to circumvent the limitation imposed by COVID-19 pandemic have been successful, and currently the mice are being bred to start the collagen-induced arthritis mice model.
- Crohn’s disease: the SAMP1/YitFc mouse strain develops ileitis spontaneously with a 100% penetrance by the 30th week of age making it a good model to study the Crohn’s disease combinatorial therapies.
- Ulcerative colitis: the implementation of the model in the IDIBAPS’s animal facility was successful, and the experiments with anti-TFNα therapy have started.
- Systematic Lupus Erythematous: a murine anti-CD20 antibody emulating Rituximab, has been produced.
Regarding WP9, Dissemination and exploitation, the website and the professional LinkedIn and Twitter accounts have been created. These sites are used to periodically post news from the project, the partners and relevant developments in IMIDs.
The DocTIS will suppose an advance regarding the state of the art in the following areas:
- Personalised medicine in IMIDs: currently, the decision on the therapy that must be administered to a given IMID patient is a subjective process, subject to trial and error. The discriminatory capacity that molecular phenotypes or endophenotypes can provide to personalize the management of IMIDs have been barely exploited. The DoCTIS aims to achieve a complete control of the autoimmune pathophysiology of IMIDs by identifying combinations of therapies that will act synergistically, and the patients where this treatment combination will be most efficacious.
- High throughput data management: The project has built a computing framework that provides the necessary IT capacity to store the large amount of data generated in the project, as well as the computing power to perform the systems biology analyses.
- Molecular data generation: previous studies analyzing drug response in IMIDs have mostly been based on bulk data analysis approaches. However, this approach misses critical biological information, like the complex cell population heterogeneity and specific functional states of the immune system. To provide the information at the cell level, DoCTIS will apply single cell RNA-Seq technology to the samples of IMID patients. Profiling complex samples using scRNA-Seq will provide an invaluable complement to the bulk technologies that will be also used in the project. This multi-omic approach will generate a deep characterization of the biological processes associated with the response to targeted therapies in IMIDs.
- Systems biology analysis: DocTIS aims to show that the LDMs are a powerful framework to continuously integrate and learn from vast and increasing sources of genome-wide data, and use them for personalised combinatorial treatment. DocTIS also aims to show that LDMs are an excellent tool for data sharing and collaborations, contributing to accelerate the clinical translation of research.
- Personalised therapy biomarker development: at present, there is no companion diagnostic for any of the targeted therapies used in IMID patients. DocTIS aims to provide the European health systems with the first biomarker test that provides treatment personalization in IMIDs. With the companion diagnostic method developed at DocTIS, the clinical specialist will have an objective and reliable tool to identify the patients that will benefit most from the combinatorial drug therapy and, ultimately, increase the percentage of IMID patients in Europe that are under stable remission.
- Pre-clinical validation: DocTIS will test, both individually and in combination, the therapeutic efficacy and toxicological effects of the targeted therapies that are currently being used to treat IMID in a series of animal models of chronic autoimmune inflammation. This approach will enable head-to-head comparisons of these different compounds and their combinations in individual pathologies as well as across pathologies.
- Personalised medicine in IMIDs: currently, the decision on the therapy that must be administered to a given IMID patient is a subjective process, subject to trial and error. The discriminatory capacity that molecular phenotypes or endophenotypes can provide to personalize the management of IMIDs have been barely exploited. The DoCTIS aims to achieve a complete control of the autoimmune pathophysiology of IMIDs by identifying combinations of therapies that will act synergistically, and the patients where this treatment combination will be most efficacious.
- High throughput data management: The project has built a computing framework that provides the necessary IT capacity to store the large amount of data generated in the project, as well as the computing power to perform the systems biology analyses.
- Molecular data generation: previous studies analyzing drug response in IMIDs have mostly been based on bulk data analysis approaches. However, this approach misses critical biological information, like the complex cell population heterogeneity and specific functional states of the immune system. To provide the information at the cell level, DoCTIS will apply single cell RNA-Seq technology to the samples of IMID patients. Profiling complex samples using scRNA-Seq will provide an invaluable complement to the bulk technologies that will be also used in the project. This multi-omic approach will generate a deep characterization of the biological processes associated with the response to targeted therapies in IMIDs.
- Systems biology analysis: DocTIS aims to show that the LDMs are a powerful framework to continuously integrate and learn from vast and increasing sources of genome-wide data, and use them for personalised combinatorial treatment. DocTIS also aims to show that LDMs are an excellent tool for data sharing and collaborations, contributing to accelerate the clinical translation of research.
- Personalised therapy biomarker development: at present, there is no companion diagnostic for any of the targeted therapies used in IMID patients. DocTIS aims to provide the European health systems with the first biomarker test that provides treatment personalization in IMIDs. With the companion diagnostic method developed at DocTIS, the clinical specialist will have an objective and reliable tool to identify the patients that will benefit most from the combinatorial drug therapy and, ultimately, increase the percentage of IMID patients in Europe that are under stable remission.
- Pre-clinical validation: DocTIS will test, both individually and in combination, the therapeutic efficacy and toxicological effects of the targeted therapies that are currently being used to treat IMID in a series of animal models of chronic autoimmune inflammation. This approach will enable head-to-head comparisons of these different compounds and their combinations in individual pathologies as well as across pathologies.