Mots-Clés

spatial transcriptomics tumor micro-environment cancer-associated fibroblasts statistics machine learning AI/Deep learning R Python

Description

Master 2 Bioinformatics Internship (6 months)

“Spatial transcriptomics data analysis to dissect the role of the tumor microenvironment in human bladder and lung cancer development.”

Data:

The M2 student will work on spatial transcriptomics data generated by recent technologies based on imaging (MERFISH and Xenium) and sequencing (Visium HD).

Objectives of the project

The internship project aims to explore and analyze spatial transcriptomics data from tumor samples of bladder and lung cancer patients to study the role of cancer-associated fibroblasts (CAFs), especially their interplay with cancer and immune cells.

The goals of the study are to:

 (1) implement appropriate statistical approaches for data filtering and normalization as well as machine learning/AI-deep learning tools for cell type annotation and cell-cell communications

(2) answer biological questions about how the spatial organization and cellular interactions between CAFs, immune cells, and tumor cells may explain the difference in tumor progression and response to treatments observed between patients.

Main tasks

• Image processing and cell segmentation
• Apply appropriate statistical methods for data filtering and normalization
• Spatially and molecularly characterize the main cell populations
• Spatially characterize immune cells, tumor cells and CAFs co-localization
• Study cell-cell communication, especially between CAFs and tumor cells
• Facilitate data visualization and exploration for biologists

Context

The internship will take place at Institut Curie, in Inserm U932 – STROMA AND IMMUNITY team headed by 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 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 CAFs, on shaping the immune responses against cancer. The M2 student will also join the bioinfo-HUB, a structure attached to the Institut Curie Bioinformatics Core Facility (led by N. Servant, P. Hupé and  E. Barillot) promoting exchanges and interactions between bioinformaticians and analysis good practices. The student will be under the joint supervision of Mamy Andrianteranagna and Hélène Salmon.

Pre-requisites

• Familiarity with bash, R and Python programming languages
• Good knowledge in statistics and machine learning (IA/Deep learning is a plus)
• Great interest in biology, oncology and/or immunology
• Previous experience with single cell RNA-seq and/or spatial transcriptomics data analyses is a plus
• Ability to communicate scientific results in a clear and didactic manner