Aging is an overly complex biological process, involving multiple mechanisms at different levels, from molecular to tissue scale. With the increase of life expectancy, the challenge is to predict the physiological age to reach healthy aging, namely the one’s ability to adapt and efficiently respond to stressors. The recent use of machine learning (ML) strategies may accurately model the physiological age to prevent age-related disruption. However, black boxes properties of most ML algorithms do not support the understanding of their internal decision-making mechanisms (i.e., the explainability), crucial to highlight the critical variables on the prediction.

Ageing and age-associated co-morbidities are major risk factors for non-healing chronic wounds. Chronic wound represent a debilitating condition that disproportionately affects millions of elderly patients with enormous societal and economic cost.

Body fat distribution is a strong determinant of health and exhibits, as a specific feature of human beings, a marked sexual dimorphism. Women have more subcutaneous adipose tissue (SAT), while men have fat predominantly distributed to the central body visceral adipose tissue (VAT). The central accumulation of fat is associated with metabolic complications that trigger a low-grade chronic inflammation. Conversely, the SAT is rather associated with very little inflammation even in obesity.

Every organ is a combination of a functional compartment, the parenchyma, and a stromal compartment, the stroma, supporting the parenchymal cells of the organ. Characterizing its involvement and defining whether and how stroma evolution can be a marker of frailty and/or can be therapeutically targeted is worthy particularly in the context of aging.

Adipose Tissue (AT) is a dynamic organ, made up of a heterogeneous stroma that is poorly understood. The stroma of AT is the richest bodily reservoir of a peculiar cell type the Adipose Stromal Cells (ASCs) that exhibit high regenerative potential. AT dysfunction is thought to be a predictor of frailty and declining health span. Here, we want to investigate the age-dependent heterogeneity of the AT stroma as a predictive marker of frailty. To address this issue methods using antibody labelling are very useful but also time consuming.

Moreover, spectral overlap inherently limits the number of simultaneous labels. Based on our preliminary data, we hypothesized that microscopic images of AT where only nuclei are stained allow the characterization of stroma’s heterogeneity using deep neural networks.

On the deep learning side, this raises many interesting problems such as the handling of pseudo-3D data, the scarcity of the data, and the prediction’s explainability that can take advantage of the strong geometric properties of the nuclei.

The position of nuclear chromatin domains in human cells impacts genome stability and gene regulation. The nuclear envelope (NE), which defines nuclear volume boundaries, is a keyplayer in organizing nuclear architecture as nuclear lamina protein scaffold, at its inner side, associates with large chromatin domains. During postmitotic nuclear assembly, physical connections occur between the NE and about 40 to 50% of telomeres, the chromosome ends. While suggesting a novel role for telomeres in nuclear organization, the functional significanceof this anchoring remains to be unraveled.

This proposal first intends to reveal the interplay between chromosome and telomere organization during postmitotic nuclear assembly. Interactions between telomeres and NE also likely regulate heterochromatin formation/maintenance. In telomerase-negative cancer cells that undergo recombinationmediated alternative lengthening of telomeres (ALT), telomeric heterochromatin is dysregulated.

Here, we will test the hypothesis that telomere-NE interaction may be disrupted in ALT cells to facilitate unwanted recombination events between telomeric repeats. To do this, a large panel of telomerase-expressing or ALT cancer cell lines will be used to characterize telomere-NE attachment and its impact on telomere maintenance.

Live cell imaging will be employed to investigate the kinetics of events. Artificial tethering and/or depletion of proteins involved in telomere tethering will be instrumental to characterize the functional significance of this interaction.

Extracellular Vesicles (EVs) are nanoparticles released by cells, key players in intercellular communication and in the maintenance of tissue homeostasis and in pathogenesis¹. EVs contribute to cancer initiation and progression: they modulate cancer-associated processes (immunosuppression, angiogenesis, invasion, and metastasis). Hence, EVs and their biomolecular cargo can be detected in body fluids and exploited as biomarkers in cancer.

Our group within the Institut de Recherche en Informatique de Toulouse (IRIT) has developed a simulation platform that provides all the tools necessary to simulate multicellular cell microtissues growth under different environmental or treatment conditions (1). Such platform is key to easily develop models of complex biological systems by proposing various interaction paradigms such as visual programming, real-time simulation generation, simulation analysis in 2D/3D and virtual reality among others. For this PhD program, we want to model oncolytic virus infection and killing of cancer cells, to identify an optimal dose of treatment with a given schedule in silico for best therapeutic efficacy. Briefly, oncolytic virus (OV) are novel therapeutics that specifically infect, kill, replicate and propagate in cancer cells and tumors, to induce cancer cell death via multiple pathways and to recruit an immune response against tumors. Our partner team, led by Dr P. Cordelier within the cancer research center of Toulouse (CRCT), recently demonstrated that OV derived from myxoma virus (MYXV) are effective in killing primary cells derived from pancreatic cancer (PDAC), a disease with no cure (2), and are promising therapies for patients with this disease (3). However, the method and timing of administration of a given total dose of virus in a treatment cycle in complex 3D tumoroïds is still to be identified, to foster clinical valorization of this research program.