Biology subjects

Vincent-Salomon, A.

Publications and source records attributed to Vincent-Salomon, A..

13 recordsLinked to original sources

bioRxiv2025

Analysis of intratumoral immune heterogeneity reveals spatial organisation of immunosuppression in breast cancer

Recent advances in single-cell transcriptomics have illuminated intratumoral heterogeneity (ITH) in breast cancer, yet the spatial organization and functional states of immune populations within luminal tumors remain poorly understood. Here, we generated a spatially and clonally resolved single-cell immune atlas of early-stage luminal breast cancer by integrating paired single-cell RNA/TCR sequencing with multiplex immunohistochemistry across three spatially distinct tumor regions: central (core-proximal), intermediate and peripheral (invasive margin-proximal), in five patients. Peripheral regions are enriched in naive CD4 T cells, monocytes, dendritic cells, and memory CD8 T cells with bystander properties, alongside TCF1+ exhausted progenitors (Tpex), and displayed elevated antigen presentation and tertiary lymphoid structures (TLS) signatures. In contrast, central regions harbor macrophages, clonally expanded regulatory T cells (Tregs), and two subsets of terminally exhausted CD8 T cells (Tex), one tissue-resident and one circulating, both expressing tumor-reactive features. Clonal overlap was observed between peripheral Tpex and central, tissue-resident Tex cells, revealing a spatially confined differentiation trajectory toward exhaustion within the tumor microenvironment. Central T cells also upregulate TGF-{beta} signaling and metabolic pathways including fatty acid oxidation and oxidative phosphorylation, consistent with adaptation to an immunosuppressive microenvironment. Together, these findings reveal a spatially structured immune landscape in luminal breast cancer, marked by progressive immunosuppression from the tumor margin to the core, providing a framework for future region-specific immunotherapeutic strategies.

immunology↗

bioRxiv2025

Tumor-on-Chip as a Personalised Platform for Rapid Drug-Testing in Breast Cancer

Breast cancer (BC) remains one of the most common malignancies worldwide and continues to pose major therapeutic challenges, emphasizing the need for functional models that can inform fast treatment selection. Currently, patient-derived xenografts (PDXs) and organoids (PDOs) are valuable biological models for functional precision oncology; however, variable success rates of establishment and prolonged timelines limit their clinical application for real-time drug testing. To overcome this, we developed a Tumor-on-Chip (ToC) platform that enables functional drug sensitivity profiling within a clinically actionable 4-day timeframe. We compared ToC models with PDX results, and demonstrated high reproducibility and strong concordance with in vivo PDX responses. Drug sensitivity was correctly identified ex vivo in 88% of PDX-responsive cases, while resistance was detected in 91%, with no false positives at clinically relevant drug concentrations. To facilitate clinical translation, we engineered a custom microfluidic chip optimized for minimal breast cancer biopsy material, yielding results similar to those obtained from resection samples. We ultimately demonstrated the proof-of-concept for applying this platform to patient samples as a further tool for guiding clinical decision-making and discriminated between resistance and sensitive profiles among patients. These findings demonstrate the feasibility and translational potential of ToC models for personalized drug profiling in breast cancer, laying the groundwork for their integration into real-time clinical decision-making workflows.

bioengineering↗

bioRxiv2025

A recurrent pathogenic BRCA2 truncating variant reveals a role for BRCA2-PCAF complex in modulating NF-κB-driven transcription

Germline monoallelic truncating mutations in BRCA2, a critical mediator of homologous recombination (HR), predispose individuals to breast and ovarian cancer. While tumorigenesis is usually attributed to biallelic inactivation, emerging evidence suggests that haploinsufficiency may suffice in certain contexts. To investigate this, we recreated two BRCA2 pathogenic truncating variants in heterozygosis in non-tumorigenic breast epithelial cells. Cells carrying a truncating mutation that was not produced prompted sensitivity to PARP inhibitors (PARPi) and reduced the HR capacity indicating haploinsufficiency. Surprisingly, the other variant was expressed as a truncated product and prompted a transcriptional rewiring. Mechanistically, the truncated BRCA2 product formed abnormal oligomers with full-length BRCA2 and bound to the PCAF acetyltransferase, sequestering it. This led to reduced global histone H4 acetylation and decreased NF-{kappa}B transcriptional activity, ultimately impairing epithelial cell migration--a process also altered in tumors. Our findings uncover a previously unrecognized BRCA2-PCAF axis that modulates NF-{kappa}B-driven transcriptional program, a process that is co-opted by a recurrent BRCA2 pathogenic variant.

cancer biology↗

bioRxiv2025

SPARC is a new driver of early breast tumor progression via TGF-β -dependent mechanism.

Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor of invasive ductal carcinoma (IDC). The challenge lies in discriminating between DCIS progressors and DCIS non-progressors, often resulting in over- or under-treatment in many cases. Membrane type 1 (MT1)-matrix metalloproteinase (MMP) has been previously identified as an essential gene involved in DCIS progression. Here, RNA-sequencing analysis of MT1-MMPhigh subpopulation derived from invasive breast tumors in the intraductal xenograft model was compared against a dataset of human high-grade DCIS, and Secreted Protein Acidic and Cysteine Rich (SPARC) has emerged as a master candidate involved in early breast tumor progression. We report that SPARC is up-regulated in DCIS as compared to normal breast epithelial tissues, and further increased in IDC relative to synchronous DCIS foci. We found a positive correlation between SPARC and MT1-MMP expression in DCIS lesions. At the mechanistic level, depletion of SPARC reduced MT1-MMP expression, the degradative capacity of the cells and the activation of the TGF-{beta} signalling canonical pathway. Pharmacological inhibition of the TGF-{beta} signalling pathway decreased SPARC and MT1-MMP at the mRNA and protein level, and concomitantly the cell degradative capacity and 3D cell migration. Strikingly, inhibition of the TGF-{beta} signalling pathway limits the invasive transition of breast tumors in a new triple-negative mouse intraductal syngeneic xenograft model. Moreover, high SPARC expression was positively correlated with both, TGF-{beta} and its receptor, TGFBRI, in a basal type of breast cancer collection supporting our findings. This study identifies SPARC as a new driver of early breast tumor progression via a TGF-{beta}-dependent mechanism, suggesting TGF-{beta} signaling pathway as a potential target for patients with high SPARC expression.

cancer biology↗

bioRxiv2023

Democratizing computational pathology: optimized Whole Slide Image representations for The Cancer Genome Atlas

Automatic analysis of hematoxylin and eosin (H&E) stained Whole Slide Images (WSI) bears great promise for computer assisted diagnosis and biomarker discovery. However, scarcity of annotated datasets leads to underperforming models. Furthermore, the size and complexity of the image data limit their integration into bioinformatic workflows and thus their adoption by the bioinformatics community. Here, we present Giga-SSL, a self-supervised method for learning WSI representations without any annotation. We show that applying a simple linear classifier on the Giga-SSL representations improves classification performance over the fully supervised alternative on five benchmarked tasks and across different datasets. Moreover, we observe a substantial performance increase for small datasets (average gain of 7 AUC point) and a doubling of the number of mutations predictable from WSIs in a pan-cancer setting (from 45 to 93). We make the WSI representations available, compressing the TCGA-FFPE images from 12TB to 23MB and enabling fast analysis on a laptop CPU. We hope this resource will facilitate multimodal data integration in order to analyze WSI in their genomic and transcriptomic context.

bioinformatics↗

bioRxiv2023

Centrosome amplification primes for apoptosis and favors the response to chemotherapy in ovarian cancer beyond multipolar divisions

Centrosome amplification is a feature of cancer cells associated with chromosome instability and invasiveness. Enhancing chromosome instability and subsequent cancer cell death via centrosome unclustering and multipolar divisions is an aimed-for therapeutic approach. Here we show that centrosome amplification favors responses to conventional chemotherapy independently of multipolar divisions and chromosome instability. We perform single-cell live imaging of chemotherapy responses in epithelial ovarian cancer cell lines and observe increased cell death when centrosome amplification is induced. By correlating cell fate with mitotic behaviors, we show that enhanced cell death occurs independently of chromosome instability. We identify that cells with centrosome amplification are primed for apoptosis. We show they are dependent on the apoptotic inhibitor BCL-XL, and that this is not a consequence of mitotic stresses associated with centrosome amplification. Given the multiple mechanisms that promote chemotherapy responses in cells with centrosome amplification, we assess such a relationship in an epithelial ovarian cancer patient cohort. We show that high centrosome numbers associate with improved chemotherapy responses and longer overall survival. Our work identifies apoptotic priming as a clinically relevant consequence of centrosome amplification, expanding our understanding of this pleiotropic cancer cell feature.

cell biology↗

bioRxiv2023

EZH2 mutations in follicular lymphoma distort H3K27me3 profiles and alter transcriptional responses to PRC2 inhibition

Mutations in chromatin regulators or their histone substrates are widespread in cancer and often play decisive roles in tumorigenesis. These include Polycomb Repressive Complex 2 (PRC2), a histone H3 lysine 27 methyltransferase that shows distinct alterations in each of a range of tumor types. Mechanistically, this tumor-type specificity is poorly understood. Here, we model several of these alterations in a single isogenic system in order to reveal their comparative impacts on chromatin and transcription. Focusing then on gain-of-function substitutions in catalytic subunit EZH2, which occur in [~]25% of follicular lymphomas, we show that Ezh2Y641F induces aberrant H3K27 methylation patterns even without wild-type Ezh2, and that these are alleviated by partial PRC2 inhibition. Ezh2Y641F also causes gains in existing H3K27 acetylation peaks and extensive gene expression changes. Remarkably, Ezh2Y641F transforms the transcriptomic response to PRC2 inhibition, leading notably to the induction of antigen presentation genes in mutant cells. Using a unique longitudinal cohort of FL patient samples we further strengthen the link between EZH2 mutation status and abnormal H3K27 methylation. This analysis also uncovered unexpected variability in the mutational landscape of successive biopsies from the same patient that points to the frequent co-existence of different clones. On a clinical level, this urges caution when stratifying patients based on single tumor sampling. Altogether, our results provide a mechanistic foundation for understanding how oncogenic PRC2 mutations disrupt chromatin and transcription, and the therapeutic vulnerabilities this creates.

cancer biology↗

bioRxiv2022

Optical Genome Mapping for detecting Homologous Recombination Deficiency (HRD) in human breast cancers

Homologous recombination deficiency (HRD) leads to genomic instability that marks HRD tumor genome with a specific genomic scar. Present in many cancers, HRD is important to be detected as it is associated with a hyper-sensitivity to some classes of drugs, in particular the PARP inhibitors. Here, we investigated the use of structural variants (SVs) detected by the Optical Genome Mapping (OGM) technology as biomarkers to identify HRD tumors. We analyzed SVs data obtained by OGM from 37 samples of triple-negative breast cancer or high grade ovarian cancer with the known HRD status. We found that HRD cases were enriched with duplications and reciprocal translocations, while nonHRD cases were enriched with inversions. The number of translocations, defined as inter-chromosomal or intra-chromosomal rearrangements of more 5Mb were similar in HRD and nonHRD cases. We defined isolated translocations as the subset of translocations having no other translocation within 2 megabase zone around both junctions, and demonstrated that the number of isolated translocations perfectly discriminated HRD and nonHRD cases in the training series. Validation series consisting from 26 cases showed 20% false positive and zero false negative error rate, which proved isolated translocations to be 100% sensitive and 80% specific SV marker of HRD. Our results demonstrate that the OGM technology is an affordable way of getting an insight of the structural variants present in solid tumors, even with low tumoral cellularity. It represents a promising technology for HRD diagnosis, where a single marker already gives 80% correct recognition.

cancer biology↗

bioRxiv2022

Neural network for the prediction of treatment response in triple negative breast cancer

AO_SCPLOWBSTRACTC_SCPLOWThe automatic analysis of stained histological sections is becoming increasingly popular. Deep Learning is today the method of choice for the computational analysis of such data, and has shown spectacular results for large datasets for a large variety of cancer types and prediction tasks. On the other hand, many scientific questions relate to small, highly specific cohorts. Such cohorts pose serious challenges for Deep Learning, typically trained on large datasets. In this article, we propose a modification of the standard nested cross-validation procedure for hyper-parameter tuning and model selection, dedicated to the analysis of small cohorts. We also propose a new architecture for the particularly challenging question of treatment prediction, and apply this workflow to the prediction of response to neoadjuvant chemotherapy for Triple Negative Breast Cancer.

bioinformatics↗

bioRxiv2021

Cancer/Testis genes are predictive of breast tumor subtypes

Breast cancer is the most prevalent type of cancer in women worldwide. Within breast tumors, the basal-like subtype has the worst prognosis and no dedicated therapy, therefore new tools to understand, detect, and treat these tumors are needed. Certain germline genes are re-expressed in tumors, and constitute the Cancer/Testis genes; their misexpression has diagnostic and therapeutic applications. Here, we designed a new approach to examine Cancer/ Testis gene misexpression in breast tumors. We identify several new markers in Luminal and HER-2 positive tumors, some of which predict response to chemotherapy. We then use machine learning to identify the 2 Cancer/Testis genes most associated with basal-like breast tumors: HORMAD1 and CT83. We show that these genes are expressed by tumor cells but not the microenvironment, and that they are not expressed by normal breast progenitors, in other words their activation occurs de novo. We find these genes are epigenetically repressed by DNA methylation, and that their activation upon DNA demethylation is irreversible, providing a memory of past epigenetic disturbances. Basal-like tumors expressing both genes have a poorer outcome than tumors expressing either gene alone or neither gene. Therefore, these findings suggest a potential synergistic effect between Cancer/Testis genes in basal breast tumors; these findings have consequences for the understanding, diagnosis, and therapy of the breast tumors with the worse outcomes.

cancer biology↗

bioRxiv2021

Tissue-resident FOLR2+ macrophages associate with tumor-infiltrating CD8+ T cells and with increased survival of breast cancer patients.

Macrophage infiltration is a hallmark of solid cancers and overall macrophage infiltration is correlated with lower patient survival and resistance to therapy. However, tumor-associated macrophages are phenotypically and functionally heterogeneous. Specific tumor-associated macrophage subsets might be endowed with antagonistic role on cancer progression and on the development of anti-tumor immunity. For instance, monocyte-derived TREM2+ tumor-associated macrophages have pro-tumorigenic and immunosuppressive functions. Here, we identify a discrete population of FOLR2+ tumor-associated macrophages positively correlating with patient survival in breast cancer. FOLR2+ macrophages are evolutionarily conserved across species and populate human and murine healthy mammary gland. Moreover, FOLR2+ macrophages co-localize with lymphoid aggregates containing CD8+ T cells in breast cancer and across ten other types of cancers. This study highlights antagonistic roles for tumor-associated macrophage subsets and paves the way for subset-specific therapeutic interventions in macrophages-based cancer therapies.

immunology↗

bioRxiv2019

Centrosome amplification favours survival and impairs ovarian cancer progression

Centrosome amplification, the presence of more than two centrosomes in a cell is a common feature of most human cancer cell lines. However, little is known about centrosome numbers of human cancers and whether amplification or other numerical aberrations are frequently present. To address this question, we have analyzed a large cohort of human epithelial ovarian cancers (EOCs) from 100 patients. Using state-of-the-art microscopy, we have determined the Centrosome-Nucleus Index (CNI) of each tumor. We found that EOCs show infrequent centrosome amplifications. Strikingly, the large majority of these tumors presented low CNIs. We show that low CNI tumors are enriched in the mesenchymal subgroup and correlate with poor patient survival. Our findings highlight a novel paradigm linking low centrosome number with highly aggressive behavior in ovarian cancers and show that the CNI signature may be used to stratify ovarian cancers.

cancer biology↗

bioRxiv2019

A single droplet digital PCR for ESR1 activating mutations detection in plasma

BackgroundActivating mutations in the estrogen receptor 1 (ESR1) gene are recurrent mechanisms of acquired resistance to aromatase inhibitors (AI), and may be the target of other selective estrogen receptor down-regulators. To assess the clinical utility of monitoring ESR1 resistant mutations, a droplet digital PCR (ddPCR)-based assay compatible with body fluids is ideal due to its cost-effectiveness and quick turnaround.\n\nMethodsWe designed a multiplex ddPCR, which combines a drop-off assay, targeting the clustered hotspot mutations found in exon 8, with another pair of probes interrogating the E380Q mutation in exon 5. We assessed its sensitivity in vitro using synthetic oligonucleotides, harboring E380Q, L536R, Y537C, Y537N, Y537S or D538G mutations. Validation of the assay was performed on plasma samples from a prospective study and compared to next generation sequencing (NGS) data.\n\nResultsThe multiplex ESR1-ddPCR showed a high sensitivity with a limit of detection ranging from 0.07 to 0.19% in mutant allele frequency depending on the mutation tested. The screening of plasma samples from patients with AI-resistant metastatic breast cancer identified ESR1 mutations in 29% of them with perfect concordance (and higher sensitivity) to NGS data obtained in parallel. Additionally, this test identifies patients harboring polyclonal alterations. Furthermore, the monitoring of ctDNA using this technique during treatment follow-up predicts the radiological response to palbociclib-fulvestrant.\n\nConclusionThe multiplex ESR1-ddPCR detects, in a single reaction, the most frequent ESR1 activating mutations and is compatible with plasma samples. This method is thus suitable for real-time ESR1 mutation monitoring in large cohorts of patients.\n\nStatement of translational relevanceExons 5 and 8 mutations in ESR1 are recurrent mechanisms of resistance to aromatase inhibitors (AI) in estrogen receptor (ER)-positive metastatic breast cancer and may be targeted by selective ER down-regulators. We implemented a novel droplet digital PCR, which allows for the detection of the most frequent ESR1 mutations in circulating cell-free DNA. In prospectively collected plasma samples, ESR1 mutations were found in 29% of AI-resistant patients, with excellent concordance and higher sensitivity to next generation sequencing. Moreover, circulating ESR1 mutations appear to be reliable markers for ctDNA monitoring in order to predict treatment response. Ultimately, the short turnaround time, high sensitivity and limited cost of the ESR1-ddPCR are compatible with repeated samplings to detect the onset of resistance to AI before the radiological progression. This opens a window of opportunity to develop new clinical strategies for breast cancer hormone therapy, as tested in an ongoing phase 3 trial.\n\nList of abbreviations\n\nHuman genesESR1: Estrogen Receptor 1\nHER2: Human Epidermal Growth Factor Receptor 2\nEGFR: Epithelial Growth Factor Receptor\nKRAS: KRAS proto-oncogene, GTPase\nBRAF: B-Raf Proto-Oncogene, Serine/Threonine kinase

cancer biology↗