Mots-Clés

cancer-associated fibroblasts spatial transcriptomics multiplexed imaging TME NGS machine learning R Python

Description

Description 

In close collaboration with wet-lab researchers , the internship project involves exploration and analysis of spatial transcriptomics and multiplex imaging data (including Visium and Xenium 10x genomics technologies) using machine learning algorithms to characterize the tumor microenvironment (TME). The project will focus on the association between immune-stroma-tumor cellular interactions and its variability between patients and medical records. Such study will offer valuable knowledge of tumor-driven stromal and immune changes, providing a powerful tool for the rational design of therapies aimed at modulating these cell compartments in humans. 

Main objectives of the study 

Using spatial transcriptomics and multiplexed imaging data, the student will:  

• Characterize the main cell populations in the TME 

• Extract relevant spatial information such as differential localization, spatially varying genes, spatial interactions of cell types, cellular neighborhoods, etc. 

• Correlate spatial patterns with relevant clinical information 

Context 

The internship will take place at Institut Curie, in Inserm U932 – STROMA AND IMMUNITY team, a junior group headed by Dr Hélène Salmon.  Institut Curie is composed of a cancer hospital and a research center, which allows for a unique continuum between fundamental research and innovations for patients and provides direct access to tissue samples from cancer patients. The Salmon Lab, which is composed of 2 PhD students, 2 senior bioinformaticians, 1 postdoc, 3 engineers, is part of the “Immunity and Cancer” Department (U932), gathering experts in cell biology, immunology, clinical immunotherapy, as well as a large working group of bioinformaticians. The team combines experimental and computational approaches to understand the contribution of stromal cells, especially cancer-associated fibroblasts, to shaping immune responses against cancer. The M2 student will also join the bioinfo-HUB, which is a structure attached in the Institut Curie Bioinformatics Core Facility (led by Dr. Nicolas Servant, Dr. Philippe Hupé and Dr Emmanuel Barillot) promoting exchanges and interactions between bioinformaticians. Finally, the student will be under the joint supervision of Dr. Mamy Andrianteranagna and Dr. Abbas Abdenour, senior bioinformaticians in the team. 

Pre-requisites 

• Familiarity with command line tools for bioinformatics analyses 

• Familiarity with R programming language (Python is a plus) 

• Basic knowledge in statistics and machine learning 

• Great interest in oncology and/or immunology 

• Previous experience with singe-cell/ imaging data analyses is a plus 

• Ability to communicate scientific results in a clear and precise way 

• Ability to understand complex biological questions and to identify relevant tools to address them