It might sound a paradox saying that cells are deeply impacted by diseases. It is not if considering the resolution available up to now to study the mechanisms underlining the development and progression of the pathological condition. A complex network of interconnected biochemical pathways are often involved in the onset of a disease, thus it may result difficult to isolate and target its exact cause with the pharmacological treatment. This difficulty is further exacerbated by the low resolution used to study multifactorial disease mechanisms and the therapeutic effects of the administered drugs, as diagnostic methods usually gives a picture at the level of the impacted organs or tissues. A mean signal is thus obtained, representing an average value measured taking into consideration the total of cells.

The ambitious goal to obtain a high resolution picture of the disease at the single cell level is the main objective of the LifeTime initiative, which has just launched its ten years roadmap research programme aimed to integrate single-cell multi-omics, imaging, AI-based technologies and personalised medicine models (e.g.organoids) to analyse large molecular and clinical datasets in order to identify new molecular mechanisms, predictive models of disease progression and new therapeutical targets.

The LifeTime initiative is one of the six preparatory actions selected in 2018 by the European Commission to address major technological and societal challenges in the areas of ICT (information and communication technology), health and energy. The Commission will also integrate the concepts described in the roadmap to plan contents of the new Horizon Europe research programme. The LifeTime Consortium includes more than hundred members, among which  leading European laboratories, institutions in the field of computational technologies and infrastructure, bioethicists and important clinical scientists, plus 80 private companies, patient organisations and European scientific societies. The network is coordinated by Nikolaus Rajewsky (Max Delbrück Center, Germany) and Geneviève Almouzni (Institut Curie, France).

The new research field of cell-based interceptive medicine

The identification, pharmacological targeting and monitoring of single cells involved in a specific disease may represent a future breakthrough innovation impacting on how new therapeutic options will be developed by the industry and administered to patients. These last shall be approached under an ethical and patient-centered vision requiring the fine-tune coordination of interactions across academia, hospitals, patient-associations, health data management systems and industry. 

The Strategic Agenda of the LifeTime initiative has been presented in a paper published in Nature, available on the initiative’s website. Key areas of research will initially include cancer, neurological, infectious, chronic inflammatory and cardiovascular diseases. The interception of the molecular determinants of the disease at the single cell level is the final goal, giving rise to a completely new branch of medicine known as “cell-based interceptive medicine”.

The new approach is expected to better address the mechanisms responsible, for example, for the low response to certain treatments, or the development of resistance against the drug substance. A better prediction of the cells’ behaviour should favour the development of more effective and less invasive or aggressive treatments, especially for chronic conditions. “Timely detection and successful treatment of disease will depend crucially on our ability to understand and identify when, why, and how cells deviate from their normal trajectory”, write the authors of the Nature paper.

A better knowledge of the disease heterogeneity in tissues is the looking forward that will inspire the research run within the LifeTime initiative. This target has been already vertically addressed under the activities of the Human Cell Atlas Consortium, but it now requires to be further studied under a longitudinal perspective to span the entire life of a patient. The data arising from large cohorts of patients should be then integrated, a very complex challenge considering the extremely high number of different phenotypes possible. 

The main technologies under the lens

Identification of early biomarkers indicative of the possible entrance of cells into a disease trajectory, together with a better understanding of the molecular aetiology of the same disease may support the easier selection of the better treatment available for a certain patient. The identification of new diagnostic and therapeutic molecular targets shall be supported by the extensive use of transcriptomics to create reference atlas of normal and pathological tissues. Data will then be integrated with additional information about chromatin accessibility, DNA methylation, histone modification, 3D structural organisation of the genomic materials and presence of mutations. Information about proteomes, lipidomes and metabolomes shall also contribute to better characterise the profile of the specific patient. Spatial mapping of the different cell types may benefit of advanced imaging techniques, while cell lineage tracing may help the monitoring of the information along time life. 

This heterogeneous pool of data requires the availability of advanced IT infrastructures to be stored, analysed using machine learning and elaborated, while also ensuring the interoperability of different data types (including those contained in electronic clinical records). This challenge will require the LifeTime initiative to collaborate with European and national legislators to include molecular data into the electronic health records, using interoperable standards and formats. “Machine learning and advanced modelling approaches will be used to integrate and analyse the different layers of cellular activity, and can generate multi-scale and potentially even causal models that will allow us to infer regulatory networks and predict present and future disease phenotypes at the cellular level”, states the Nature’s paper.

A Launchpad to identify priorities

The five areas forming the initial set to be addressed by the LifeTime initiative have been selected using the Launchpad tool, a mechanism developed to systemically identify medical challenges which may benefit from the integrated approach of studying the underlying mechanisms of the disease. 

The first ten years targets have been selected by working groups formed by experts in the different therapeutics areas on the basis of established selection criteria. These include the impact on society, evidence for cellular heterogeneity, availability of samples from biobanks, relevant preclinical models, existence of patient cohorts (also enabling longitudinal studies), clinical feasibility and ethical considerations, and alignment with national and EU funding priorities.

In cancer, the project will tackle early metastatic dissemination and therapy resistance, while early events in the onset of the disease will be the main focus in the neurological area. Infection mechanisms and development of the host response will characterise activities in the area of infectious diseases, in order to develop new precision immune-based therapeutics. Understanding the impact of cellular heterogeneity in the development and progression of chronic inflammatory diseases is expected to support a better prediction of the outcomes for available treatments. Understanding of abnormal cardiac cell structures and functions should support early diagnosis and therapy of cardiovascular diseases. 

Three distinct phases will characterise the activities, starting with addressing the identified challenges with the already available technologies and methods. The further development of new technologies will represent the second phase, to finish with their application for the longitudinal analysis of patient samples and the development of patient-derived models combined with machine learning to generate predictive models of the disease.

Patients may in future be stratified on the basis of a risk analysis using specific predictors and biomarkers. The activation of an experimental design working group is also planned in order to guarantee for the availability of systematic procedures to be used in all cases for the acquisition of samples and the definition of  clinical cohorts of patients. 

Thematic clusters to optimise the effort

The complexity of the activities planned in the roadmap will be addressed through the creation of a multidisciplinary network of LifeTime Centres across Europe, each one aggregating complementary thematic clusters and working in close coordination with hospitals. Data collection and usage will benefit of the expansion of the European Open Science Cloud (EOSC) and the EuroHPC providing high-performance computing capacity. The network of the European Life Sciences Research Infrastructures will also be involved, in order to avoid duplication of efforts. A joint Data Coordination Centre will be responsible for the transparent control of the access to data, their compatibility and standardisation. 

The ethical impact of the innovation resulting from the LifeTime initiative shall be assess in real time by mean of a parallel ELSI (ethical, legal and societal issues) programme, with the final goal to improve citizens’ trust. The introduction of the new methods in the clinical practice will also need to train health professionals through an extensive Education and Training Programme, as well as updating the infrastructures. “Bench to bedside and back” will be the paradigm of the new approach to education, with researchers and clinicians to exchange and communicate each other their respective perspectives and needs.