Aim & Research Approach - Computational Cancer Genomics
AIM
The Rare Cancers Genomics initiative is an international multidisciplinary open-science effort to shed light on the molecular characteristics of cancers, to understand their etiology and carcinogenesis processes, and to ultimately improve their clinical management and consequently, patient’s prognosis.
RESEARCH APPROACH
To achieve our aims we follow different approaches:
1
Perform integrative multi-omics multi-region bulk and single-cell sequencing analyses as well as spatial profiling of large bio-repositories with good quality of samples and detailed pathological, clinical and epidemiological annotations.
(led by Drs Lynnette Fernandez-Cuesta and Matthieu Foll)
2
Review and identify new morphological characteristics using image-based AI and integrate them with the molecular data.
(led by Drs Matthieu Foll and Lynnette Fernandez-Cuesta – read more)
3
Study cancer ecology and evolution to identify and understand carcinogenic processes.
(led by Dr Nicolas Alcala – read more)
4
Use state-of-the-art in vitro organoid models to study the cancer initiation and progression.
(led by Dr Talya Dayton – read more)
OPEN SCIENCE EFFORT
This initiative includes a strong commitment to open science, reproducibility, and capacity building: best-practices pipelines have been set-up to analyze WGS, RNAseq, and methylation data, as well as supervised and unsupervised methods to perform multi-omic data integration. All the necessary resources to reproduce the initiative’s analyses are available, and the bioinformatics pipelines are continuously updated and improved, with detailed documentation to ensure that they are reproducible and effectively reusable by others. Similar single-cell RNA- seq, ATAC-seq, and spatial RNA-seq data processing workflows following best practices (Andrews, 2021) are currently being developed.
