Biology subjects

Prompsy, P.

Publications and source records attributed to Prompsy, P..

4 recordsLinked to original sources

bioRxiv2025

Identification of a shared persistence program in triple-negative breast cancer across treatments and patients

Acquisition of resistance to anti-cancer therapies is a multistep process, which initiates with the survival of drug persister cells. Understanding the mechanisms driving the emergence of persister cells remains challenging, primarily because of their limited accessibility in patients. Here, using mouse models to isolate persister cells from patient tumors, we determine the identity features of persister cells from eight patients with triple-negative breast cancer (TNBC). Combining over 80 transcriptome studies, we reveal hallmarks of the persister state across patient models and treatment modalities: high expression of basal keratins together with activation of a stress response and inflammation pathways. Patient-derived persister cells are transcriptionally plastic and return to a common treatment-naive like state upon relapse, regardless of the treatment they have been exposed to. Leveraging gene regulatory networks, we identify AP-1, NFKB and IRF/STAT as the key drivers of this hallmark persister state. As a proof of concept, we show that FOSL1 - an AP-1 member - is sufficient to drive cells to the persister state by binding enhancers and reprogramming the transcriptome of cancer cells. On the contrary, cancer cells without FOSL1 have a decreased ability to reach the persister state. By defining hallmarks of drug persistence to multiple therapies of the standard of care, our study provides a resource to design novel combination therapeutic strategies to limit resistance.

cancer biology↗

bioRxiv2022

Luminal progenitors undergo partial epithelial-to-mesenchymal transition at the onset of basal-like breast tumorigenesis

Defects in double-strand repair mechanisms - both through germline or somatic inactivation of repair genes - is a hallmark of basal-like breast cancers. In this genetically-unstable context, a recurrent shift in cell identity occurs within the mammary epithelium. Basal-like tumors have indeed been proposed to originate from luminal progenitor (LP) cells yet tumor-initiating events remain poorly understood. Here, we map state transitions at the onset of basal-like tumorigenesis, using a Brca-1 deficient mouse model launching tumorigenesis in multiple LP cells. Combining single-cell transcriptomics to spatial multiplex imaging, we identify a population of cycling p16-expressing cells, emerging from the luminal progenitor compartment, undergoing partial epithelial-to-mesenchymal transition and losing luminal identity. Pseudo-temporal analyses position these cells as a transitory pre-tumoral state between aberrant Brca1-deficient luminal progenitors and growing tumor cells. In patients, the p16 pre-tumoral signature is found in early stage basal-like tumors, that rarely recur. Concomitant to p16 activation, we show that LP cells undergo an epigenomic crisis attested by the general re-organization of their heterochromatin. They accumulate multiple H3K27me3 micro-foci - reminiscent of the formation of senescence-associated heterochromatin foci (SAHFs) - and lose their inactive X (Xi). Both p16 activation and heterochromatin reorganization are hallmarks of human basal-like breast tumors; we propose that these events occur during initial LP transformation and are scars of an initial transitory senescent-like state.

cancer biology↗

bioRxiv2021

H3K27me3 is a determinant of chemotolerance in triple-negative breast cancer

Triple-negative breast cancer is associated with the worst prognosis and the highest risk of recurrence among all breast cancer subtypes1. Residual disease, formed by cancer cells persistent to chemotherapy, remains one of the major clinical challenges towards full cure2,3. There is now consensus that non-genetic processes contribute to chemoresistance in various tumor types, notably through the initial emergence of a reversible chemotolerant state4-6. Understanding non-genetic tumor evolution stands now as a prerequisite for the design of relevant combinatorial approaches to delay recurrence. Here we show that the repressive histone mark H3K27me3 is a determinant of cell fate under chemotherapy exposure, monitoring epigenomes, transcriptomes and lineage with single-cell resolution. We identify a reservoir of persister basal cells with EMT markers and activated TGF-{beta} pathway leading to multiple chemoresistance phenotypes. We demonstrate that, in unchallenged cells, H3K27 methylation is a lock to the expression program of persister cells. Promoters are primed with both H3K4me3 and H3K27me3, and removing H3K27me3 is sufficient for their transcriptional activation. Leveraging lineage barcoding, we show that depleting H3K27me3 alters tumor cell fate under chemotherapy insult - a wider variety of tumor cells tolerate chemotherapy. Our results highlight how chromatin landscapes shape the potential of unchallenged cancer cells to respond to therapeutic stress.

cancer biology↗

bioRxiv2019

ChromSCape : an R/Shiny application for interactive analysis of single-cell chromatin profiles

Assessing chromatin profiles at single-cell resolution is now feasible thanks to recently published experimental methods such as single cell chromatin immunoprecipitation followed by sequencing (scChIP-seq) (Grosselin et al., 2019; Rotem et al., 2015) and single-cell assay for transposase-accessibility chromatin (scATAC-seq) (Buenrostro et al., 2015; Chen et al., 2018; Cusanovich et al., 2015; Lareau et al., 2019). With these methods, we can detect the heterogeneity of epigenomic profiles within complex biological samples. Yet, existing tools used to analyze bulk epigenomic experiments are not fit for the low coverage and sparsity of single-cell epigenomic datasets. Here, we present ChromSCape: a user-friendly Shiny/R application that processes single-cell epigenomic data to help the biological interpretation of epigenomic landscapes within cell populations. The user can identify different sub-populations within heterogeneous samples, find differentially enriched regions between subpopulations and identify associated genes and pathways. ChromSCape accepts multiple samples to allow comparisons of cell populations between and within samples. ChromSCape source code is written in Shiny/R, works as a stand-alone application and is freely downloadable at https://github.com/vallotlab/ChromSCape. Here, using ChromSCape on multiple H3K27me3 scChIP-seq datasets, we deconvolve chromatin landscapes within the tumor microenvironment, identifying distinct H3K27me3 landscapes associated to cell identity and tumor subtype.\n\nContactpacome.prompsy@curie.fr; celine.vallot@curie.fr

bioinformatics↗