Systematic proximal mapping of the classical RAD51 paralogs unravel functionally and clinically relevant interactors for genome stability.

Homologous recombination (HR) plays an essential role in the maintenance of genome stability by promoting the repair of cytotoxic DNA double strand breaks (DSBs). More recently, the HR pathway has emerged as a core component of the response to replication stress, in part by protecting stalled replication forks from nucleolytic degradation. In that regard, the mammalian RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) have been involved in both HR-mediated DNA repair and collapsed replication fork resolution. Still, it remains largely obscure how they participate in both processes, thereby maintaining genome stability and preventing cancer development. To gain better insight into their contribution in cellulo, we mapped the proximal interactome of the classical RAD51 paralogs using the BioID approach. Aside from identifying the well-established BCDX2 and CX3 sub-complexes, the spliceosome machinery emerged as an integral component of our proximal mapping, suggesting a crosstalk between this pathway and the RAD51 paralogs. Furthermore, we noticed that factors involved RNA metabolic pathways are significantly modulated within the BioID of the classical RAD51 paralogs upon exposure to hydroxyurea (HU), pointing towards a direct contribution of RNA processing during replication stress. Importantly, several members of these pathways have prognostic potential in breast cancer (BC), where their RNA expression correlates with poorer patient outcome. Collectively, this study uncovers novel functionally relevant partners of the different RAD51 paralogs in the maintenance of genome stability that could be used as biomarkers for the prognosis of BC.

Multi-omics data integration analysis identifies the spliceosome as a key regulator of DNA double-strand break repair.

DNA repair by homologous recombination (HR) is critical for the maintenance of genome stability. Germline and somatic mutations in HR genes have been associated with an increased risk of developing breast (BC) and ovarian cancers (OvC). However, the extent of factors and pathways that are functionally linked to HR with clinical relevance for BC and OvC remains unclear. To gain a broader understanding of this pathway, we used multi-omics datasets coupled with machine learning to identify genes that are associated with HR and to predict their sub-function. Specifically, we integrated our phylogenetic-based co-evolution approach (CladePP) with 23 distinct genetic and proteomic screens that monitored, directly or indirectly, DNA repair by HR. This omics data integration analysis yielded a new database (HRbase) that contains a list of 464 predictions, including 76 gold standard HR genes. Interestingly, the spliceosome machinery emerged as one major pathway with significant cross-platform interactions with the HR pathway. We functionally validated 6 spliceosome factors, including the RNA helicase SNRNP200 and its co-factor SNW1. Importantly, their RNA expression correlated with BC/OvC patient outcome. Altogether, we identified novel clinically relevant DNA repair factors and delineated their specific sub-function by machine learning. Our results, supported by evolutionary and multi-omics analyses, suggest that the spliceosome machinery plays an important role during the repair of DNA double-strand breaks (DSBs).

Reversal of diet-induced hepatic steatosis by peripheral CB1 receptor blockade in mice is p53/miRNA-22/SIRT1/PPARα dependent.

OBJECTIVE: The endocannabinoid (eCB) system is increasingly recognized as being crucially important in obesity-related hepatic steatosis. By activating the hepatic cannabinoid-1 receptor (CB1R), eCBs modulate lipogenesis and fatty acid oxidation. However, the underlying molecular mechanisms are largely unknown. METHODS: We combined unbiased bioinformatics techniques, mouse genetic manipulations, multiple pharmacological, molecular, and cellular biology approaches, and genomic sequencing to systematically decipher the role of the hepatic CB1R in modulating fat utilization in the liver and explored the downstream molecular mechanisms. RESULTS: Using an unbiased normalized phylogenetic profiling analysis, we found that the CB1R evolutionarily coevolves with peroxisome proliferator-activated receptor-alpha (PPARα), a key regulator of hepatic lipid metabolism. In diet-induced obese (DIO) mice, peripheral CB1R blockade (using AM6545) induced the reversal of hepatic steatosis and improved liver injury in WT, but not in PPARα-/- mice. The antisteatotic effect mediated by AM6545 in WT DIO mice was accompanied by increased hepatic expression and activity of PPARα as well as elevated hepatic levels of the PPARα-activating eCB-like molecules oleoylethanolamide and palmitoylethanolamide. Moreover, AM6545 was unable to rescue hepatic steatosis in DIO mice lacking liver sirtuin 1 (SIRT1), an upstream regulator of PPARα. Both of these signaling molecules were modulated by the CB1R as measured in hepatocytes exposed to lipotoxic conditions or treated with CB1R agonists in the absence/presence of AM6545. Furthermore, using microRNA transcriptomic profiling, we found that the CB1R regulated the hepatic expression, acetylation, and transcriptional activity of p53, resulting in the enhanced expression of miR-22, which was found to specifically target SIRT1 and PPARα. CONCLUSIONS: We provide strong evidence for a functional role of the p53/miR-22/SIRT1/PPARα signaling pathway in potentially mediating the antisteatotic effect of peripherally restricted CB1R blockade.

Titanium Tackles the Endoplasmic Reticulum: A First Genomic Study on a Titanium Anticancer Metallodrug.

PhenolaTi is an advanced non-toxic anticancer chemotherapy; this inert bis(phenolato)bis(alkoxo) Ti(IV) complex demonstrates the intriguing combination of high and wide efficacy with no detected toxicity in animals. Here we unravel the cellular pathways involved in its mechanism of action by a first genome study on Ti(IV)-treated cells, using an attuned RNA sequencing-based available technology. First, phenolaTi induced apoptosis and cell-cycle arrest at the G2/M phase in MCF7 cells. Second, the transcriptome of the treated cells was analyzed, identifying alterations in pathways relating to protein translation, DNA damage, and mitochondrial eruption. Unlike for common metallodrugs, electrophoresis assay showed no inhibition of DNA polymerase activity. Reduced in vitro cytotoxicity with added endoplasmic reticulum (ER) stress inhibitor supported the ER as a putative cellular target. Altogether, this paper reveals a distinct ER-related mechanism by the Ti(IV) anticancer coordination complex, paving the way for wider applicability of related techniques in mechanistic analyses of metallodrugs.

Author Correction: Clinical Implications of Sub-grouping HER2 Positive Tumors by Amplicon Structure and Co-amplified Genes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Clinical Implications of Sub-grouping HER2 Positive Tumors by Amplicon Structure and Co-amplified Genes.

ERBB2 amplification is a prognostic marker for aggressive tumors and a predictive marker for prolonged survival following treatment with HER2 inhibitors. We attempt to sub-group HER2+ tumors based on amplicon structures and co-amplified genes. We examined five HER2+ cell lines, three HER2+ xenographs and 57 HER2+ tumor tissues. ERBB2 amplification was analyzed using digital droplet PCR and low coverage whole genome sequencing. In some HER2+ tumors PPM1D, that encodes WIP1, is co-amplified. Cell lines were treated with HER2 and WIP1 inhibitors. We find that inverted duplication is the amplicon structure in the majority of HER2+ tumors. In patients suffering from an early stage disease the ERBB2 amplicon is composed of a single segment while in patients suffering from advanced cancer the amplicon is composed of several different segments. We find robust WIP1 inhibition in some HER2+ PPM1D amplified cell lines. Sub-grouping HER2+ tumors using low coverage whole genome sequencing identifies inverted duplications as the main amplicon structure and based on the number of segments, differentiates between local and advanced tumors. In addition, we found that we could determine if a tumor is a recurrent tumor or second primary tumor and identify co-amplified oncogenes that may serve as targets for therapy.

Mapping global and local coevolution across 600 species to identify novel homologous recombination repair genes.

The homologous recombination repair (HRR) pathway repairs DNA double-strand breaks in an error-free manner. Mutations in HRR genes can result in increased mutation rate and genomic rearrangements, and are associated with numerous genetic disorders and cancer. Despite intensive research, the HRR pathway is not yet fully mapped. Phylogenetic profiling analysis, which detects functional linkage between genes using coevolution, is a powerful approach to identify factors in many pathways. Nevertheless, phylogenetic profiling has limited predictive power when analyzing pathways with complex evolutionary dynamics such as the HRR. To map novel HRR genes systematically, we developed clade phylogenetic profiling (CladePP). CladePP detects local coevolution across hundreds of genomes and points to the evolutionary scale (e.g., mammals, vertebrates, animals, plants) at which coevolution occurred. We found that multiscale coevolution analysis is significantly more biologically relevant and sensitive to detect gene function. By using CladePP, we identified dozens of unrecognized genes that coevolved with the HRR pathway, either globally across all eukaryotes or locally in different clades. We validated eight genes in functional biological assays to have a role in DNA repair at both the cellular and organismal levels. These genes are expected to play a role in the HRR pathway and might lead to a better understanding of missing heredity in HRR-associated cancers (e.g., heredity breast and ovarian cancer). Our platform presents an innovative approach to predict gene function, identify novel factors related to different diseases and pathways, and characterize gene evolution.