Biology subjects

Stern, M.-H.

Publications and source records attributed to Stern, M.-H..

8 recordsLinked to original sources

bioRxiv2026

Human PMS1-dependent non-canonical mismatch repair converges with MBD4 to repair 5-methylcytosine deamination

CpG dinucleotides are hotspots for mutagenesis by spontaneous deamination of 5-methylcytosine (5mC) into thymine, resulting in T:G mismatches that can lead to C>T transitions. These mutations are a hallmark of aging and cancer and a major force shaping the evolution of vertebrate genomes. We have previously uncovered MBD4 as the primary base excision repair (BER) glycosylase responsible for 5mC deamination repair. In this study, we employ a cytosine base-editing system, comprising an APOBEC1 deaminase fused to a catalytically dead Cas9, to induce targeted cytosine deamination in native chromatin and track its repair. This approach reveals that MBD4 cooperates with a non-canonical branch of mismatch repair (MMR) to elicit 5mC deamination repair. We demonstrate that MBD4 activity depends on MMR complexes MutS (MSH2-MSH6) and MutL{beta} (MLH1-PMS1), but not on post-replicative MMR elicited by the MutL (MLH1-PMS2) complex. We find that PMS1 loss phenocopies the genome-wide CpG>TpG hypermutated profile associated with MBD4 deficiency, uncovering that 5mC deamination repair may represent one of the primary functions of the MutL{beta} complex. The mutational landscape of MMR-deficient tumors aligns with our experimental results, showing that replication-independent CpG>TpG mutagenesis partly contributes to the mutational burden of tumors inactivated for MLH1, MSH2 and MSH6. Finally, using structural predictions alongside biochemical validation, we show that MBD4 physically interacts with MutL{beta} in an MLH1-dependent manner, illuminating the structural basis for the convergence of the BER and MMR pathways. Altogether, we uncover a novel function of non-canonical MMR that underscores its interplay with BER in safeguarding genomic integrity against damage to methylated DNA.

molecular 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↗

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

Multi-omics comparison of malignant and normal uveal melanocytes reveals novel molecular features of uveal melanoma.

Uveal Melanoma (UM) is a rare cancer resulting from transformation of melanocytes residing in the uveal tract. Integrative analysis has identified four molecular and clinical subsets in UM. To improve our molecular understanding of UM we performed extensive multi-omics characterization comparing two aggressive UM patient-derived xenograft models with normal choroidal melanocytes, including DNA optical mapping, specific histone modifications, and DNA topology analysis by Hi-C. Our gene expression and cytogenetic analyses suggest that genomic instability is a hallmark of UM. We also identified a recurrent deletion in the BAP1 promoter resulting in loss of expression and associated with high risk of metastases in UM patients. Hi-C revealed chromatin topology changes associated with up-regulation of PRAME, an independent prognostic biomarker in UM and potential therapeutic target. Our findings illustrate how multi-omics approaches can improve the understanding of tumorigenesis and reveals two novel mechanisms of gene expression dysregulation in UM.

genomics↗

bioRxiv2021

Deep Learning identifies new morphological patterns of Homologous Recombination Deficiency in luminal breast cancers from whole slide images.

Homologous Recombination DNA-repair deficiency (HRD) is a well-recognized marker of platinum-salt and PARP inhibitor chemotherapies in ovarian and breast cancers (BC). Causing high genomic instability, HRD is currently determined by BRCA1/2 sequencing or by genomic signatures, but its morphological manifestation is not well understood. Deep Learning (DL) is a powerful machine learning technique that has been recently shown to be capable of predicting genomic signatures from stained tissue slides. However, DL is known to be sensitive to dataset biases and lacks interpretability. Here, we present and evaluate a strategy to control for biases in retrospective cohorts. We train a deep-learning model to predict the HRD in a controlled cohort with unprecedented accuracy (AUC: 0.86) and we develop a new visualization technique that allows for automatic extraction of new morphological features related to HRD. We analyze in detail the extracted morphological patterns that open new hypotheses on the phenotypic impact of HRD.

cancer biology↗

bioRxiv2019

RAD51 promotes non-homologous genetic rearrangements that are prevented by 53BP1

Homologous recombination (HR), which requires long sequence homologies, is considered a high fidelity mechanism, preserving genome stability. In contrast, we show here that the central HR players RAD51 or BRCA2, promote genetic instability, fostering translocations and capture of ectopic chromosomal sequences when joining distant DNA breaks. Surprisingly, these events do not involve sequence homologies. Moreover, our data reveal that 53BP1 protects against RAD51-mediated non-homologous genetic rearrangements. Finally, analysis of a large panel of breast tumors revealed that BRCA2 proficiency is associated with increased frequency of capture of non-homologous sequences at junctions of structural variants (translocations, duplications, inversions, deletions). These data reveal that HR proteins (RAD51, BRCA2) possess the intrinsic capacity to generate genetic instability through sequence homology-independent processes, and that 53BP1 protects against it. We propose that BRCA2/RAD51-mediated genome instability occurs in the course of sequence homology search for HR.

molecular biology↗

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↗