Antibody-mediated delivery of therapeutic compounds to tumor cells for the treatment of cancer is a rapidly growing multibillion-euro market. One class of tumor markers, the glycosphingolipids (GSLs), are only rarely addressed in this context, due to the difficulty of obtaining antibodies against them. In this proof-of-concept program, we will develop a novel class of products — lectibodies — for the delivery of therapeutic compounds to tumor-specific GSLs. Our lectibodies are based on a naturally occurring GSL-binding protein with intrinsic tumor targeting capacity. We will rely on a proprietary phage library technology to isolate lectibodies against GSLs (or cocktails thereof). In this PoC program we will optimize and apply our technology to specifically target O-acetyl GD2, a GSL highly expressed in neuroblastoma tissues. This will enable us to generate lectibody-based therapeutics against neuroblastoma in children, a devastating disease for which the drug market is predicted to reach 118€ million in 2022. We will explore two options for further business development: a) building off of our current partnership with OGD2 Pharma (a biotech based n Nantes, France) and b)creation of a spin-off company which will license deals to several pharmaceutical partners based on pathology. We will capitalize on the expertise in launching start-ups of our principle investigator and on close links with clinicians and industry partners. Our technology has truly groundbreaking potential as, in principle, chimeric lectibodies can be developed against virtually any tumor-specific cocktail of GSLs thus opening the door for the development of novel therapies for several cancers. Thus, following the development of neuroblastoma-specific lectibodies, we foresee a wider range of future applications for our technology.

Socioeconomic inequalities in children’s neurodevelopment and mental health are observed from early onwards and widen over time. Moreover, children whose parents are immigrant, particularly if they belong to ethnic minority groups, may be especially vulnerable. Yet there are important inter-individual differences in development, implying the possibility of resilience. My project will examine the consequences of multiple forms of socioeconomic adversity in children’s family and broader social environment with regard to their neurodevelopment and mental health, testing the role of social supports as sources of resilience. Specifically, I will rely upon longitudinal data collected from the ELFE child cohort study, a nationally representative sample of 18 321 children born in France in 2011 and followed-up to age 10.5 years, which will be linked with longitudinal administrative and geographical information characterizing neighbourhoods of children’s school and residence, as well as healthcare use data. Potential resilience factors will include familial (e.g. relations between the child and his/her mother and father, grandparents’ involvement) and contextual social supports (e.g. childcare prior to school entry, neighborhood social capital). Lifecourse patterns of adversity and resilience at each level of analysis will be identified using statistical methods developed for high-dimensional data and their influence on children’s development will be ascertained applying methods that strengthen causal inference (e.g. propensity scores). The results will help clarify 1) the ways in which lifecourse patterns of exposure to adversity in the family and children’s broader social environment can influence neurodevelopment and mental health, particularly among children of immigrants; 2) familial and collective factors that can help children overcome the odds and should be promoted.

Early diagnostics based on multiple biomarkers is key in numerous diseases, yet current technologies for multiplexed detection are complicated and expensive. Living cells detect and process various environmental signals in parallel and can self-replicate, presenting an attractive platform for scalable and affordable autonomous diagnostic devices. In this project, I will apply my expertise in synthetic biology, the rational engineering of biological systems, to build cell-based biosensors for multiplexed diagnosis using the non-pathogenic bacterium Bacillus subtilis. In a first research line, I will conceive a scalable detection machinery by engineering chimeric receptors detecting extracellular biomarkers via sensing domains derived from antibodies. In a second research line, I will implement bio-molecular computing systems operating within and across bacterial cells to perform multiplexed biomarkers analysis. I will deploy in B. subtilis biomolecular logic gates and will engineer specific cell-cell communication systems to perform distributed multicellular computation in a bacterial consortia. My project is highly interdisciplinary and is at the cross-roads of genetic engineering, structural biology, biophysics, modeling, and clinics. On foundational point of view, I will make several breakthrough contributions to synthetic biology: (i) Advancing engineering frameworks for the Gram-positive model, B. subtilis. (ii) Pushing the limits of custom-ligand detection by engineered cells (iii) Exploring the frontiers of man-made biological computers. On an applied point of view, I plan to deliver a first prototype for the urinary diagnostic of diabetic nephropathy, a major complication of diabetes. Because of the modular design principles applied, my sensing platform will be reusable to diagnose other pathologies as well as for applications requiring custom-detection and bio-molecular computation like targeted therapy, drug delivery, or environmental monitoring.