We are seeking a highly motivated and scientifically driven computational biologist/bioinformatician. The candidate will bring his/her expertise to contribute to the team objective in identifying key immune surveillance pathways operating in tumors using a unique strategy, based on the team advanced expertise on DC subsets, combining single-cell transcriptomic and spatial analyses of innate immune cells at preneoplastic stages in breast and colon environment. Using both human tissue samples and spontaneous sporadic mouse tumor models, the team has generated datasets along 2 axes: 1) Deep single-cell RNA-sequencing of innate immune (DC, Macrophages, neutrophils, NK) and epithelial/stromal cell compartments comparing normal, preneoplastic lesions and established tumors in order to define cell trajectories during tumor progression and identify specific pathways activated at preneoplastic stage and contributing to prevention of tumor development. 2) Tissue localization of each innate immune cell population and identification of its neighbors by deep in situ multi-IF spatial analysis with the aim to define the spatio-temporal crosstalk between innate and epithelial/stromal cells.
The successful candidate will take the lead to integrate these 2 approaches through deep machine-learning techniques representing a breakthrough strategy to pinpoint key cell/cell interactions and immune surveillance pathways activated at early stage and interrupted in advanced tumors.
Contract: 3 years private-law contract with salary based on experience. The team is ready to support the candidate to apply to an INSERM/CNRS researcher position, with possibility to develop new research lines.
Recent publications from the lab related to the field:
– Di Roio et al (2023), MDR1-expressing CD4+ T cells with Th1.17 features resist to neoadjuvant chemotherapy and are associated with breast cancer clinical response. Journal of ImmunoTherapy of Cancer, in press
– Voissiere et al (2023), The CSF-1R inhibitor Pexidartinib impacts dendritic cell differentiation through inhibition of FLT3 signaling and may antagonize the effect of durvalumab in patients with advanced cancer – results from a phase 1 study. Science Translational Medicine, in press
– Hubert et al. (2020), IFN-III Is Selectively Produced by cDC1 and Predicts Good Clinical Outcome in Breast Cancer. Science Immunology 5(46).
– Small M et al. (2018), Genetic alterations and tumor immune attack in Yo paraneoplastic cerebellar degeneration. Acta Neuropathol. 135(4):569-579.Détails du téléchargement