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Jean, D.

Publications and source records attributed to Jean, D..

5 recordsLinked to original sources

Novel Replication Stress-Associated High-Grade Serous Ovarian Cancer Models Recapitulate Diverse Tumour Ecosystems and Enable Preclinical Studies

Abstract Background: High-grade serous ovarian cancer (HGSC) is characterized by extensive genomic heterogeneity and frequent alterations that promote replication stress (RS). Although RS has emerged as a promising therapeutic vulnerability, it remains unclear whether distinct RS-associated genomic alterations generate similar tumour states or drive unique biological programs and therapeutic dependencies. Methods: We developed and characterized a panel of syngeneic HGSC models representing recurrent RS-associated alterations, including overexpression of Ccne1, Brd4, Myc, Ndrg1, Pik3ca, and Brca1 heterozygosity, alongside previously established Pten/Nf1-deficient and Myc overexpressing models. Tumour fitness, transcriptomic programs, histopathology, extracellular matrix composition, immune organization, and therapeutic vulnerabilities were assessed using subcutaneous (s.c.) and intraperitoneal (i.p.) allografts, RNA sequencing (RNAseq), mass spectrometry (MS), cyclic-immunofluorescence (Cyc-IF), and preclinical therapeutic studies. Results: RS-associated genotypes exhibited marked differences in tumour fitness and generated distinct tumour ecosystem states despite sharing a common genetic background. Tumours harbouring BRCA1 heterozygosity displayed reduced tumour fitness, mesenchymal features, extracellular matrix remodelling, stromal expansion, and immune-excluded phenotypes. In contrast, tumours co-expressing Ccne1 and Brd4 exhibited the highest RS level together with strong activation of DNA damage response pathways and limited immune infiltration. Immune characterization identified immune-desert, immune-suppressed, and immune-excluded states across models, demonstrating substantial genotype-dependent immune heterogeneity. Elevated CD47 expression emerged as a defining feature of the Ccne1/Brd4 tumour state and was confirmed in human HGSC specimens with high CCNE1 and BRD4 protein expression. Therapeutic targeting of ATR and CD47 in intraperitoneal Ccne1/Brd4 allografts reduced tumour burden and induced histopathological responses compared with either monotherapy alone, supporting the translational relevance of this RS-high tumour state. Conclusions: Distinct RS-associated alterations do not converge on a common HGSC phenotype but instead generate diverse tumour ecosystem states with unique effects on tumour fitness, stromal remodelling, immune organization, and therapeutic vulnerabilities. These findings highlight the importance of considering the genetic origin of RS when developing therapeutic strategies and establish a framework for investigating genotype-specific vulnerabilities in HGSC.

cancer biology↗

SCORPy: Lowering the computational barrier to reproducible multiplexed imaging spatial single cell proteomics analysis

Spatially resolved single-cell proteomic imaging technologies, including cyclic immunofluorescence (CycIF), generate high-dimensional data, critical for tissue-scale biological analysis. However, single-cell analysis remains computationally demanding, lacks standardization across platforms and is often inaccessible to experimental biologists without programming expertise. Here we present SCORPy (Single-Cell proteOmics Research Platform), a standalone, cross-platform desktop application that provides an end-to-end, code-free workflow for the analysis of single-cell proteomic data extracted from imaging experiments. SCORPy introduces methodological advances for preprocessing multiplexed imaging data: an exposure-aware, cycle-matched background correction strategy, and a normalization framework that harmonizes signal distributions across markers while enabling batch correction across experiments. These approaches are integrated with quality control, interactive thresholding and cell phenotyping using a hierarchical cell reference library, and downstream compositional and spatial analyses within a unified interface. Sample-level metadata can be incorporated throughout the workflow to support integrative analyses and facilitate generation of publication-ready visualizations. By combining robust preprocessing methods with an accessible implementation, SCORPy reduces computational barriers and promotes broader adoption of spatial single-cell proteomics analysis.

cell biology↗

A Proximity MAP of RAB GTPases

RAB GTPases are the most abundant family of small GTPases and regulate multiple aspects of membrane trafficking events, from cargo sorting to vesicle budding, transport, docking, and fusion. To regulate these processes, RABs are tightly regulated by guanine exchange factors (GEFs) and GTPase-activating proteins (GAPs). Activated RABs recruit effector proteins that regulate trafficking. Identifying RAB-associated proteins has proven to be difficult because their association with interacting proteins is often transient. Recent advances in proximity labeling approaches that allow for the covalent labeling of neighbors of proteins of interest now permit the cataloging of proteins in the vicinity of RAB GTPases. Here, we report APEX2 proximity labeling of 23 human RABs and their neighboring proteomes. We have used bioinformatic analyses to map specific proximal proteins for an extensive array of RAB GTPases, and RAB localization can be inferred from their adjacent proteins. Focusing on specific examples, we identified a physical interaction between RAB25 and DENND6A, which affects cell migration. We also show functional relationships between RAB14 and the EARP complex, or between RAB14 and SHIP164 and its close ortholog UHRF1BP1. Our dataset provides an extensive resource to the community and helps define novel functional connections between RAB GTPases and their neighboring proteins.

cell biology↗

Preclinical evaluation of CDK4 phosphorylation predicts high sensitivity of malignant pleural mesotheliomas to CDK4/6 inhibition

Malignant pleural mesothelioma (MPM) is an aggressive cancer with limited therapeutic options. In this study, we evaluated the impact of CDK4/6 inhibition by palbociclib in a panel of 28 MPM cell lines, including 19 patient-derived cell lines, using a variety of approaches including RNA-sequencing. Palbociclib used alone sufficed to strongly and durably inhibit the proliferation of 23 MPM cell lines, indicating a unique sensitivity of MPM to CDK4/6 inhibition. Importantly, insensitivity to palbociclib was mostly explained by the lack of active T172-phosphorylated CDK4. This was associated with the high p16INK4A (CDKN2A) levels that accompany RB1 defects or inactivation, and also (unexpectedly) cyclin E1 over-expression in the presence of wild-type RB1. Prolonged treatment with palbociclib irreversibly inhibited proliferation despite re-induction of cell cycle genes upon drug washout. A senescence-associated secretory phenotype including various potentially immunogenic components was also irreversibly induced. Phosphorylated CDK4 was detected in 80% of 47 MPM tumors indicating their intrinsic sensitivity to CDK4/6 inhibitors. The absence of this phosphorylation in some highly proliferative MPM tumors was linked to partial deletions of RB1, leading to very high p16 (CDKN2A) expression. Our study strongly supports the clinical evaluation of CDK4/6 inhibitory drugs for MPM treatment, in monotherapy or combination therapy.

cancer biology↗

Disentangling heterogeneity of Malignant Pleural Mesothelioma through deep integrative omics analyses

Malignant Pleural Mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Using the largest series of whole-genome sequencing data integrated with transcriptomic and epigenomic data using multi-omic factor analysis, we demonstrate that MPM heterogeneity arises from four sources of variation: tumor cell morphology, ploidy, adaptive immune response, and CpG island methylator phenotype. Previous genomic studies focused on describing only the tumor cell morphology factor, although we robustly find the three other sources in all publicly available cohorts. We prove how these sources of variation explain the biological functions performed by the cancer cells, and how genomic events shape MPM molecular profiles. We show how these new sources of variation help understand the heterogeneity of the clinical behavior of MPM and drug responses measured in cell lines. These findings unearth the interplay between MPM functional biology and its genomic history, and ultimately, inform classification, prognostication and treatment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461908v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@b6c43corg.highwire.dtl.DTLVardef@10d45a9org.highwire.dtl.DTLVardef@58746eorg.highwire.dtl.DTLVardef@143f880_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗