Biology subjects

Labrie, M.

Publications and source records attributed to Labrie, M..

6 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

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↗

bioRxiv2024

A Comprehensive Proteogenomic and Spatial Analysis of Innate and Acquired Resistance of Metastatic Melanoma to Immune Checkpoint Blockade Therapies

While a subset of patients with metastatic melanoma achieves durable responses to immune checkpoint blockade (ICB) therapies, the majority ultimately exhibit either innate or acquired resistance to these treatments. However, the molecular mechanisms underlying resistance to ICB therapies remain elusive and are warranted to elucidate. Here, we comprehensively investigated the tumor and tumor immune microenvironment (TIME) of paired pre- and post-treatment tumor specimens from metastatic melanoma patients who were primary or secondary resistance to anti-CTLA-4 and/or anti-PD-1/PD-L1 therapies. Differentially expressed gene (DEG) analysis and single-sample gene set enrichment analysis (ssGSEA) with transcriptomic data identified cell cycle and c-MYC signaling as pathway-based resistance signatures. And weighted gene co-expression network analysis (WGCNA) revealed the activation of a cross-resistance meta-program involving key signaling pathways related to tumor progression in ICB resistant melanoma. Moreover, spatially-resolved, image-based immune monitoring analysis by using NanoStrings digital spatial profiling (DSP) and Cyclic Immunofluorescence (CyCIF) showed infiltration of suppressive immune cells in the tumor microenvironment of melanoma with resistance to ICB therapies. Our study reveals the molecular mechanisms underlying resistance to ICB therapies in patients with metastatic melanoma by conducting such integrated analyses of multi-dimensional data, and provides rationale for salvage therapies that will potentially overcome resistance to ICB therapies. Statement of translational relevanceThis study paves the way for the creation of innovative therapeutic strategies, aimed at subverting resistance to immune checkpoint blockade (ICB) therapies in metastatic melanoma patients. By unraveling the specific molecular mechanisms underlying resistance, scientists can design effective alternative treatments that target pathways such as pathways associated with cell cycle dysregulation and c-MYC signaling. Furthermore, through the application of advanced immune monitoring techniques such as NanoString Digital Spatial Profiling (DSP) and Cyclic Immunofluorescence (CyCIF), this study has significantly enriched our understanding of the tumor microenvironment. This enhanced characterization facilitates the discovery of potential biomarkers that may forecast a patients response to ICB treatment. Ultimately, these advancements could potentially refine patient outcomes and foster the development of more personalized cancer treatments in the future.

genetics↗

bioRxiv2021

ME-VAE: Multi-Encoder Variational AutoEncoder for Controlling Multiple Transformational Features in Single Cell Image Analysis

Image-based cell phenotyping relies on quantitative measurements as encoded representations of cells; however, defining suitable representations that capture complex imaging features is challenged by the lack of robust methods to segment cells, identify subcellular compartments, and extract relevant features. Variational autoencoder (VAE) approaches produce encouraging results by mapping an image to a representative descriptor, and outperform classical hand-crafted features for morphology, intensity, and texture at differentiating data. Although VAEs show promising results for capturing morphological and organizational features in tissue, single cell image analyses based on VAEs often fail to identify biologically informative features due to uninformative technical variation. Herein, we propose a multi-encoder VAE (ME-VAE) in single cell image analysis using transformed images as a self-supervised signal to extract transform-invariant biologically meaningful features, including emergent features not obvious from prior knowledge. We show that the proposed architecture improves analysis by making distinct cell populations more separable compared to traditional VAEs and intensity measurements by enhancing phenotypic differences between cells and by improving correlations to other analytic modalities.

bioinformatics↗

bioRxiv2020

An Integrated Clinical, Omic, and Image Atlas of an Evolving Metastatic Breast Cancer

Mechanisms of therapeutic resistance manifest in metastatic cancers as tumor cell intrinsic alterations and extrinsic microenvironmental influences that can change during treatment. To support the development of methods for the identification of these mechanisms in individual patients, we present here an Omic and Multidimensional Spatial (OMS) Atlas generated from four serial biopsies of a metastatic breast cancer patient during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata including treatment times and doses, anatomic imaging, and blood-based response measurements to exploratory analytics including comprehensive DNA, RNA, and protein profiles, images of multiplexed immunostaining, and 2- and 3-dimensional scanning electron micrographs. These data reveal aspects of therapy-associated heterogeneity and evolution of the cancers genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples showing how integrative analyses of these data provide insights into potential mechanisms of response and resistance, and suggest novel therapeutic vulnerabilities.

cancer biology↗

bioRxiv2018

PARPi triggers STING-dependent immune response and enhances therapeutic efficacy of immune checkpoint blockade independent of BRCAness

Poly-(ADP-ribose) polymerase (PARP) inhibitors (PARPis) have shown remarkable therapeutic efficacy against BRCA1/2 mutant cancers through a synthetic lethal interaction. PARPis are believed to exert their therapeutic effects mainly through the blockade of single-strand DNA damage repair, which leads to the accumulation of toxic DNA double strand breaks, specifically in cancer cells with DNA repair deficiency (BCRAness), including those harboring BRCA1/2 mutations. Here, we show that PARPis modulate immune reposes, which contribute to their therapeutic effects independent of BRCA1/2 mutations. The mechanism underlying this PARPi-induced reprogramming of anti-tumor microenvironment involves a promoted accumulation of cytosolic DNA fragments due to unresolved DNA lesions. This in turn activates the DNA sensing cGAS-STING pathway and stimulates production of type I interferons. Ultimately, these events promote PARPi-induced antitumor immunity independent of BRCAness, which can be further enhanced by immune checkpoint blockade. Our results may provide a mechanistic rationale for using PARPis as immunomodulatory agents to harness therapeutic efficacy of immune checkpoint blockade.

cancer biology↗