Stage de Master 2

SFBI; Arrondissement d'Évry; On-site; EUR 6,600 - 7,800; Full time

Job summary

Institut Gustave Roussy and IBISC invite a Master 2 student in bioinformatics to join the MORETON project. The intern will work on modelling neuroendocrine transdifferentiation to propose cell reprogramming strategies against therapeutic resistance, combining modelling, controllability analysis and experimental validation.

The role emphasizes Python-based development, data interpretation and collaboration with oncologists and biologists at Gustave Roussy and the IBISC lab in Évry.

Qualifications

• M2 student in bioinformatics with an interest in modelling biological systems.
• Good Python skills are expected; knowledge of Mathematica is a plus.

Skills

Python

Mathematica

Education

Master 2 in Bioinformatics

Tools

Mathematica

Job description

Internship topic

The MORETON project, a collaboration between Institut Gustave Roussy and the IBISC laboratory, builds a model of neuroendocrine transdifferentiation (NET) to propose cell reprogramming strategies against therapeutic resistance, combining modelling, controllability analysis and experimental validation.

NET is the process by which epithelial cells acquire neuroendocrine features under stress, notably anticancer treatments. Associated with aggressive phenotypes and increased therapeutic resistance, it remains poorly understood: experimental approaches identify the markers and signalling pathways involved, but neither capture its overall dynamics nor predict the conditions that favour it.

In metastatic castration-resistant prostate cancer (mCRPC), about 25% of patients are primarily resistant to androgen receptor pathway inhibitors (ARPi), and the others develop acquired resistance. In 15–20% of cases, luminal adenocarcinoma (ADK) then evolves into neuroendocrine prostate cancer (NEPC), one of the most lethal forms of the disease, progressing rapidly and leaving patients with almost no therapeutic options. The clinical challenge is to prevent or reverse this transition.

We built a 36-gene Boolean network modelling NET. A controllability analysis, which searches for the minimal interventions (freezing genes to 0 or 1) that drive the network towards a target phenotype, predicted therapeutic targets able to reprogram NEPC into ADK, in the Wnt/β-catenin, EGFR and NF-κB pathways.

Objectives

• Validate the model. Check that the network reproduces the effects of experimentally established perturbations and the expression profiles observed in patients. This step will allow the student to become familiar with the model, its biological foundations and the analysis tools.
• Characterise the vulnerability of the ADK state, that is, its propensity to switch to NEPC. Immanent to the network, it only manifests itself under extrinsic perturbations, such as therapeutic pressure. The internship will identify which perturbations trigger the switch, how many and in what order, and measure its components: the fragility of the ADK state (minimal number of perturbations that make it switch), its resilience (ability to return to it) and the irreversibility threshold, beyond which the switch can no longer be avoided. This threshold defines the window for therapeutic intervention; the states preceding it would provide early warning signatures, allowing therapy to be adapted before NEPC sets in. The goal is no longer to counter the switch, but to prevent it.

Profile

M2 student in bioinformatics with an interest in modelling biological systems. Good Python skills are expected; knowledge of Mathematica is a plus.

Supervision

The internship lies at the interface of computer science and oncology, where formal modelling leads to therapeutic hypotheses tested in the laboratory. Supervision at IBISC by specialists in bioinformatics and computational modelling, in close collaboration with oncologists and biologists at Gustave Roussy.

• Location: Institut Gustave Roussy (Villejuif) and IBISC laboratory (Évry)
• Stipend: statutory French rate
• Beltran H. et al. (2016). Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer. Nature Medicine, 22(3), 298–305. doi:10.1038/nm.4045
• Bluemn E. G. et al. (2017). Androgen Receptor Pathway-Independent Prostate Cancer Is Sustained through FGF Signaling. Cancer Cell, 32(4), 474–489. doi:10.1016/j.ccell.2017.09.003
• Zou M., Toivanen R. (2022). Plasticity and evolution in castration-resistant prostate cancer. Nature Reviews Urology, 19, 303–320. doi:10.1038/s41585-022-00597-6
• Zhu Y. et al. (2021). Emerging role of transcription factors in the plasticity of neuroendocrine prostate cancer. Frontiers in Oncology, 11, 658265. doi:10.3389/fonc.2021.658265
• Aggarwal R. et al. (2018). *Clinical and Genomic Characterization of Treatment-Emergent Small-Cell Neuroendocrine Prostate Cancer: A