Biology subjects

Popova, T.

Publications and source records attributed to Popova, T..

5 recordsLinked to original sources

bioRxiv2023

Polθ is phosphorylated by Polo-like kinase 1 (PLK1) to enable repair of DNA double strand breaks in mitosis

DNA double strand breaks (DSBs) are deleterious lesions that challenge genome integrity. To mitigate this threat, human cells rely on the activity of multiple DNA repair machineries that are tightly regulated throughout the cell cycle1. In interphase, DSBs are mainly repaired by non-homologous end joining (NHEJ) and homologous recombination (HR)2. However, these pathways are completely inhibited in mitosis3-5, leaving the fate of mitotic DSBs unknown. Here we show that DNA polymerase theta (Pol{theta})6 repairs mitotic DSBs and thereby maintains genome integrity. In contrast to other DSB repair factors, Pol{theta} function is activated in mitosis upon phosphorylation by the Polo-like kinase 1 (PLK1). Phosphorylated Pol{theta} is recruited to mitotic DSBs, where it mediates joining of broken DNA ends, while halting mitotic progression. The lack of Pol{theta} leads to a shortening of mitotic duration and defective repair of mitotic DSBs, resulting in a loss of genome integrity. In addition, we identify mitotic Pol{theta} repair as the underlying cause of the synthetic lethality between Pol{theta} and HR. Our findings reveal the critical importance of mitotic DSB repair for maintaining genome stability.

cell 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↗

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↗