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Séminaire
Tracing back primed resistance in cancer
Treatment resistance is a major challenge in cancer care. Beyond genetic changes, non-genetic changes affecting gene expression can drive intrinsic resistance, which are harder to study due to the responsive nature of the transcriptome. To tackle this, we developed ReSisTrace, a methodology that uses shared transcriptomic features of sister cells to predict cell states priming treatment resistance.
Initially, ReSisTrace was applied to a high-grade serous ovarian cancer cell line to reveal pre-existing resistant states to chemotherapy, targeted therapy, or innate immunity (Dai J. et al, Nature Communications, 2024). In ReSisTrace, cancer cells are labelled uniquely with genetic barcodes and allowed to divide once so that each sister cell pair can be identified based on a shared barcode. Then single cell transcriptomes are analysed from half of the cells before the treatment, while treating the other half. Finally, analysis of the surviving cells enables the identification of the resistant lineages and tracing back their pre-resistant states via the sister cells analysed prior to the treatment.
Using this approach, we predicted small molecules that could reverse the pre-resistant states, and shift cells to states resembling transcriptomes of pre-sensitive cells. These drugs significantly sensitized cells to carboplatin, PARP inhibitor, or NK killing when used as pre-treatment Now, we have expanded the method to a patient derived ovarian cancer organoid model. Even in this more heterogeneous and challenging context, we were able to identify a pre-existing chemoresistant state, and successfully target it with a pre-sensitising therapy, thus suggesting broad applicability of the method. In summary, ReSisTrace reveals features of cells that will become resistant to treatments by coupling cell state and fate in sister cell resolution. It is widely applicable to identify and target pre-existing resistant cell states across cancer types and treatment modalities, including immunotherapies. Our final aim is to develop sequential cancer therapies to block resistance before it emerges.
Orateur(s)
Single-cell Transcriptomics of Cancer Laboratory
University of Helsinki
Organisateur(s)
Scientific Project Manager
Dynamique de l'information génétique : bases fondamentales et cancer (DIG-Cancer) (UMR3244)
Institut Curie
Invité(e)(s) par
Research Director
Dynamique de l'information génétique : bases fondamentales et cancer (DIG-Cancer) (UMR3244)
Institut Curie