Translational Cancer Genomics
The team is supported by ARC foundation grant: "Emerging Leaders in Oncology".
This team belongs to the UMR 981:"Molecular predictors and new targets in oncology".
Advancing Cancer Genomics: Decoding Resistance and Mutagenesis
Our translational cancer genomics team is dedicated to unraveling the genetic underpinnings of cancer, with a dual focus on damage-induced mutagenesis and the genetic mechanisms of resistance to anti-neoplastic treatments. We believe that by understanding how normal cells transform into cancer and how cancer cells evolve under therapy, we can pave the way for more effective treatments and improved patient outcomes.
Our Research Interests & Projects:
Understanding Damage-Induced Mutagenesis
We investigate how various forms of damage lead to the accumulation of mutations in cancer. Our models include:
- UV-light exposed skin cancer: Examining the impact of UV radiation on mutational profiles.
- Xeroderma Pigmentosum (XP) disease: Studying this genetic disorder characterized by an inability to repair DNA lesions, in close collaboration with the "L'association Enfants de la lune" XP society.
- Advanced cancers treated with genotoxic therapies: Analyzing how anti-cancer treatments that damage DNA contribute to subsequent mutations.
Our goal is to characterize the cellular responses to damage, identify factors influencing mutational processes, and understand why cancer risk varies between individuals and cancer types. This research aims to predict treatment efficacy and the likelihood of resistance development.
Dissecting Resistance to Anti-Neoplastic Treatments
We dissect the later stages of cancer evolution by comparing the genetic, epigenetic, and transcriptional landscapes of advanced, refractory tumors with primary, untreated tumors of the same types. This approach helps us understand how cancers become resistant to therapy.
Our projects in this area include:
- META-PRISM Cohort Analysis: Through the PRISM study at Gustave Roussy, we analyze large genetic cohorts with Whole Exome Sequencing (WES) and RNA sequencing (RNA-seq) data across different progression stages. For breast cancer patients with advanced refractory disease, we've identified genetic markers that enhance 6-month survival prediction and optimize patient selection for Phase I clinical trials.
- Sanofi Collaboration on Lung Cancer Resistance: We are actively characterizing mechanisms of tolerance and resistance to receptor tyrosine kinase inhibitors (TKIs) in lung cancers. This prospective cohort study collects samples at baseline, best response, and resistance stages. We utilize bulk WES and RNA-seq, as well as single-cell approaches including scRNA-seq, ATAC-seq, and scDNA-seq with Tapestri. A unique aspect is our focus on characterizing cancer at its persistent stage, aiming to optimize treatment regimens by understanding features of persister cells that lead to resistance.
- MyProbe Consortium Projects on Breast Cancer: As part of the MyProbe consortium, two projects aim to predict markers of resistance to hormonal therapy in HR+/Her2- breast cancer. These works leverage large, homogenous cohorts of baseline and resistant tumors, employing novel approaches such as ATAC-seq to dissect unique epigenetic features of refractory cancers and single-cell DNA sequencing to uncover the impact of subclonality on disease aggressiveness.
Future Directions & Technical Capabilities
Looking ahead, we aim to identify comprehensive sets of genetic and epigenetic markers that capture the full complexity of cancer. The application of single-cell approaches, integrating data on genetics, epigenetics, and transcriptomics, is key to achieving a comprehensive cancer profile.
Our laboratory employs a strong bioinformatics component that guides our wet lab experimentation. Our dedicated bioinformaticians develop robust pipelines common to multiple projects, such as our Next-Generation Sequencing (NGS) pipeline for cancer genome analysis. This pipeline assesses somatic and germline variations, processing whole genome, exome, or panel sequencing data in tumor-only or tumor/normal modes. It identifies point mutations, somatic copy number alterations, and retrieves critical tumor information like purity, microsatellite instability score, and tumor mutational burden. Our RNA NGS pipeline performs gene fusion calling and deconvolutes the tumor microenvironment from transcript counts. Genetic variants are automatically annotated using OncoKB and CiViC databases.
New pipelines, including those for ATAC-seq and single-cell RNA-seq data processing, are continually being developed. Our lab fosters a collaborative environment where each scientist or PhD student leads a primary project while contributing to others. For damage-induced mutagenesis research, we actively validate peculiar mutational profiles, especially those linked to DNA repair pathway aberrations or genotoxins, in experimental settings. Our focus includes Nucleotide Excision Repair deficiencies and UV-light induced mutagenesis.
