Mots-Clés

Epigenomics Metabolism Glioma

Description

Deciphering the Metabolic and Epigenetic Interplay in IDH-mutant Glioma

The focus of this internship is to investigate how the epigenetic changes induced by IDH mutations in gliomas are impacting metabolic adaptation and vice versa, affecting tumor progression and response to therapies, in particular IDH mutant inhibitors.

Background and Context:

Metabolic reprogramming is a hallmark of cancer cells, occurring either adaptively to support cellular proliferation or directly due to mutations in genes encoding crucial metabolic enzymes. Notably, recurrent mutations in Isocitrate Dehydrogenase (IDH) genes, particularly in diffuse low-grade gliomas (LGGs; 80%), play a significant role. These mutations lead to the generation of the oncometabolite R-2-hydroxyglutarate (D-2HG), acting as a competitive inhibitor of α-KG-dependent dioxygenases, including histone, DNA, and RNA demethylases. This results in a widespread hypermethylation phenotype, influencing gene expression and tumor behavior in both cancer types. A key question in the field revolves around the poorly understood interplay between the epigenetic consequences and metabolic adaptations of IDH mutations in different tumor types.

Following the identification of IDH mutations, several specific IDH mutant inhibitors (IDHmi) have been developed. Recent results from a phase 3 clinical trial of the brain-penetrant dual inhibitor of mutant IDH1/2, vorasidenib – which has held authorization for clinical usage in Europe since September 2024 , demonstrated a noteworthy improvement in progression-free survival and time to the next intervention. The identification of biomarkers predicting response and resistance will be crucial to enhance the use of these new drugs, especially in designing the most effective combinations.

With this project, we aim to address these gaps of knowledge. In particular:

• A more detailed molecular characterization: Existing studies have provided insights into the general alterations in chromatin structure and gene expression in IDH-mutant gliomas, but a more detailedmolecular characterization is needed, in particular concerning metabolic rewiring. Specifically, understanding the exact chromatin changes at a finer scale and how these changes correlate with changes in gene expression related to metabolic pathways would allow to better define the crosstalk between epigenetic changes and metabolic adaptation in IDH-mutant driven cancers.
• A better mechanistic understanding: There is a need to understand the mechanisms through which these epigenetic and metabolic changes influence glioma pathogenesis and progression, which could revealnovel therapeutic targets for each cancer.
• Translational application: Translating these molecular findings into potential clinical applications, such as identifying biomarkers of response or resistance to IDH mutant inhibitors-based therapies.

Project Description:

The project involves a detailed analysis of ATAC-seq, ChIP-seq and methylome data upcycled from The Cancer Genome Atlas to explore the effects of IDH mutations on chromatin structure and gene regulation in gliomas and AML, focusing on the metabolic and epigenetic alterations.

Responsabilities:

• Analyze ATAC-seq, ChIP-seq and methylome data, referencing key studies in the field.
• Conduct a comprehensive literature review to contextualize findings within the broader field of IDH-mutant driven cancers.
• Utilize bioinformatics techniques for data preprocessing, peak calling, nucleosome positioning, digital foot-printing, differential analysis, and mullti-omic data integration (e.g. epigenomics and transcriptomics).
• Conduct pathway analysis and survival analysis using biostatistics and machine learning methods (e.g. classification and clustering algorithms).
• Collaborate with the research team to integrate findings and contribute to understanding IDH-mutation impact on glioma and AML tumorigenesis and response to specific inhibitors.

Qualifications:

• Enrollment in a Master’s program in Bioinformatics, Biostatistics, or related field.
• Experience in genomic data analysis and proficiency in R / Python / UNIX programming.
• Independent and collaborative research skills.
• Background knowledge in genomics and / or epigenetics.

Scientific environment:

The successful candidate will acquire skills in cancer genetics, bioinformatics, bio-statistics and machine learning, and will benefits from the expertise of her / his supervisors in glioma biology, epigenetics, metabolism, sequence bio-informatics, big data analysis and integration, R & UNIX programming and super-computing. She / he will be involved in the laboratory research program, aiming at characterizing the molecular mechanisms underpinning aging and oncogenesis, and will join a cohesive team with transversal dry and wet lab skills. The candidate will benefit from technical and scientific support in a stimulating environment ideal to develop her / his scientific mindset.

References:

1. Stalled Oligodendrocyte Differentiation in IDH-mutant Gliomas, Wei et al., 2023, Genome Medicine. 
2. Mutant-IDH1-dependent chromatin state reprogramming, reversibility, and persistence, Turcan et al., 2018, Nature Genetics.
3. Mapping Chromatin Accessibility and Active Regulatory Elements in Human Gliomas, Stępniak et al., 2021, Nature Communications.
4. Chromatin structure predicts survival in glioma patients, Garrett et al., 2022, Scientific Reports.
5. Mitochondrial metabolism supports resistance to IDH mutant inhibitors in acute myeloid leukemia, Stuani et al., 2021, Journal of Experimental Medicine.