Comprehensive genomic profiling on metastatic Melanoma: results from a network screening from 7 Italian Cancer Centres.

BACKGROUND: The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma. METHODS: 82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting. RESULTS: The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan-Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints. CONCLUSIONS: The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research.

Factor VIII promotes angiogenesis and vessel stability regulating extracellular matrix proteins.

Not available.

The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancer.

The high-grade serous ovarian cancer (HG-SOC) tumor microenvironment (TME) is constellated by cellular elements and a network of soluble constituents that contribute to tumor progression. In the multitude of the secreted molecules, the endothelin-1 (ET-1) has emerged to be implicated in the tumor/TME interplay; however, the molecular mechanisms induced by the ET-1-driven feed-forward loops (FFL) and associated with the HG-SOC metastatic potential need to be further investigated. The tracking of the patient-derived (PD) HG-SOC cell transcriptome by RNA-seq identified the vascular endothelial growth factor (VEGF) gene and its associated signature among those mostly up-regulated by ET-1 and down-modulated by the dual ET-1R antagonist macitentan. Within the ligand-receptor pairs concurrently expressed in PD-HG-SOC cells, endothelial cells and activated fibroblasts, we discovered two intertwined FFL, the ET-1/ET-1R and VEGF/VEGF receptors, concurrently activated by ET-1 and shutting-down by macitentan, or by the anti-VEGF antibody bevacizumab. In parallel, we observed that ET-1 fine-tuned the tumoral and stromal secretome toward a pro-invasive pattern. Into the fray of the HG-SOC/TME double and triple co-cultures, the secretion of ET-1 and VEGF, that share a common co-regulation, was inhibited upon the administration of macitentan. Functionally, macitentan, mimicking the effect of bevacizumab, interfered with the HG-SOC/TME FFL-driven communication that fuels the HG-SOC invasive behavior. The identification of ET-1 and VEGF FFL as tumor and TME actionable vulnerabilities, reveals how ET-1R blockade, targeting the HG-SOC cells and the TME simultaneously, may represent an effective therapeutic option for HG-SOC patients.

The acetyltransferase p300 is recruited in trans to multiple enhancer sites by lncSmad7.

The histone acetyltransferase p300 (also known as KAT3B) is a general transcriptional coactivator that introduces the H3K27ac mark on enhancers triggering their activation and gene transcription. Genome-wide screenings demonstrated that a large fraction of long non-coding RNAs (lncRNAs) plays a role in cellular processes and organ development although the underlying molecular mechanisms remain largely unclear (1,2). We found 122 lncRNAs that interacts directly with p300. In depth analysis of one of these, lncSmad7, is required to maintain ESC self-renewal and it interacts to the C-terminal domain of p300. lncSmad7 also contains predicted RNA-DNA Hoogsteen forming base pairing. Combined Chromatin Isolation by RNA precipitation followed by sequencing (ChIRP-seq) together with CRISPR/Cas9 mutagenesis of the target sites demonstrate that lncSmad7 binds and recruits p300 to enhancers in trans, to trigger enhancer acetylation and transcriptional activation of its target genes. Thus, these results unveil a new mechanism by which p300 is recruited to the genome.

The Emerging Roles of Long Non-Coding RNAs in Intellectual Disability and Related Neurodevelopmental Disorders.

In the human brain, long non-coding RNAs (lncRNAs) are widely expressed in an exquisitely temporally and spatially regulated manner, thus suggesting their contribution to normal brain development and their probable involvement in the molecular pathology of neurodevelopmental disorders (NDD). Bypassing the classic protein-centric conception of disease mechanisms, some studies have been conducted to identify and characterize the putative roles of non-coding sequences in the genetic pathogenesis and diagnosis of complex diseases. However, their involvement in NDD, and more specifically in intellectual disability (ID), is still poorly documented and only a few genomic alterations affecting the lncRNAs function and/or expression have been causally linked to the disease endophenotype. Considering that a significant fraction of patients still lacks a genetic or molecular explanation, we expect that a deeper investigation of the non-coding genome will unravel novel pathogenic mechanisms, opening new translational opportunities. Here, we present evidence of the possible involvement of many lncRNAs in the etiology of different forms of ID and NDD, grouping the candidate disease-genes in the most frequently affected cellular processes in which ID-risk genes were previously collected. We also illustrate new approaches for the identification and prioritization of NDD-risk lncRNAs, together with the current strategies to exploit them in diagnosis.

Laniakea@ReCaS: exploring the potential of customisable Galaxy on-demand instances as a cloud-based service.

BACKGROUND: Improving the availability and usability of data and analytical tools is a critical precondition for further advancing modern biological and biomedical research. For instance, one of the many ramifications of the COVID-19 global pandemic has been to make even more evident the importance of having bioinformatics tools and data readily actionable by researchers through convenient access points and supported by adequate IT infrastructures. One of the most successful efforts in improving the availability and usability of bioinformatics tools and data is represented by the Galaxy workflow manager and its thriving community. In 2020 we introduced Laniakea, a software platform conceived to streamline the configuration and deployment of "on-demand" Galaxy instances over the cloud. By facilitating the set-up and configuration of Galaxy web servers, Laniakea provides researchers with a powerful and highly customisable platform for executing complex bioinformatics analyses. The system can be accessed through a dedicated and user-friendly web interface that allows the Galaxy web server's initial configuration and deployment. RESULTS: "Laniakea@ReCaS", the first instance of a Laniakea-based service, is managed by ELIXIR-IT and was officially launched in February 2020, after about one year of development and testing that involved several users. Researchers can request access to Laniakea@ReCaS through an open-ended call for use-cases. Ten project proposals have been accepted since then, totalling 18 Galaxy on-demand virtual servers that employ ~ 100 CPUs, ~ 250 GB of RAM and ~ 5 TB of storage and serve several different communities and purposes. Herein, we present eight use cases demonstrating the versatility of the platform. CONCLUSIONS: During this first year of activity, the Laniakea-based service emerged as a flexible platform that facilitated the rapid development of bioinformatics tools, the efficient delivery of training activities, and the provision of public bioinformatics services in different settings, including food safety and clinical research. Laniakea@ReCaS provides a proof of concept of how enabling access to appropriate, reliable IT resources and ready-to-use bioinformatics tools can considerably streamline researchers' work.

Evolutionary Rewiring of Human Regulatory Networks by Waves of Genome Expansion.

Genome expansion is believed to be an important driver of the evolution of gene regulation. To investigate the role of a newly arising sequence in rewiring regulatory networks, we estimated the age of each region of the human genome by applying maximum parsimony to genome-wide alignments with 100 vertebrates. We then studied the age distribution of several types of functional regions, with a focus on regulatory elements. The age distribution of regulatory elements reveals the extensive use of newly formed genomic sequence in the evolution of regulatory interactions. Many transcription factors have expanded their repertoire of targets through waves of genomic expansions that can be traced to specific evolutionary times. Repeated elements contributed a major part of such expansion: many classes of such elements are enriched in binding sites of one or a few specific transcription factors, whose binding sites are localized in specific portions of the element and characterized by distinctive motif words. These features suggest that the binding sites were available as soon as the new sequence entered the genome, rather than being created later by accumulation of point mutations. By comparing the age of regulatory regions to the evolutionary shift in expression of nearby genes, we show that rewiring through genome expansion played an important role in shaping human regulatory networks.

B lymphocytes directly contribute to tissue fibrosis in patients with IgG4-related disease.

BACKGROUND: IgG4-related disease (IgG4-RD) is a fibroinflammatory condition marked by rapid clinical improvement after selective depletion of B lymphocytes with rituximab. This feature suggests that B cells might participate in fibrogenesis and wound healing. OBJECTIVE: In the present work we aimed to demonstrate that B lymphocytes contribute directly to tissue fibrosis in patients with IgG4-RD. METHODS: Total circulating CD19+ B lymphocytes, naive B cells, memory B cells, or plasmablasts from patients with IgG4-RD were cultivated with human fibroblasts. Profibrotic soluble factors and collagen production in cocultures were assessed by using ELISAs and Luminex assays. RNA sequencing and quantitative RT-PCR were used to assess fibroblast activation in the presence of B cells, as well as induction of profibrotic pathways in B-cell subsets. Relevant profibrotic and inflammatory molecules were confirmed in vitro by using functional experiments and on IgG4-RD tissue sections by using multicolor immunofluorescence studies. RESULTS: B cells from patients with IgG4-RD (1) produced the profibrotic molecule platelet-derived growth factor B and stimulated collagen production by fibroblasts; (2) expressed enzymes implicated in extracellular matrix remodeling, such as lysyl oxidase homolog 2; (3) produced the chemotactic factors CCL4, CCL5, and CCL11; and (4) induced production of these same chemokines by activated fibroblasts. Plasmablasts expressed sets of genes implicated in fibroblast activation and proliferation and therefore represent cells with intrinsic profibrotic properties. CONCLUSION: We have demonstrated that B cells contribute directly to tissue fibrosis in patients with IgG4-RD. These unanticipated profibrotic properties of B lymphocytes, particularly plasmablasts, might be relevant for fibrogenesis in patients with other fibroinflammatory disorders and for wound-healing processes in physiologic conditions.

Expanding the spectrum of genes responsible for hereditary motor neuropathies.

BACKGROUND: Inherited peripheral neuropathies (IPNs) represent a broad group of genetically and clinically heterogeneous disorders, including axonal Charcot-Marie-Tooth type 2 (CMT2) and hereditary motor neuropathy (HMN). Approximately 60%-70% of cases with HMN/CMT2 still remain without a genetic diagnosis. Interestingly, mutations in HMN/CMT2 genes may also be responsible for motor neuron disorders or other neuromuscular diseases, suggesting a broad phenotypic spectrum of clinically and genetically related conditions. Thus, it is of paramount importance to identify novel causative variants in HMN/CMT2 patients to better predict clinical outcome and progression. METHODS: We designed a collaborative study for the identification of variants responsible for HMN/CMT2. We collected 15 HMN/CMT2 families with evidence for autosomal recessive inheritance, who had tested negative for mutations in 94 known IPN genes, who underwent whole-exome sequencing (WES) analyses. Candidate genes identified by WES were sequenced in an additional cohort of 167 familial or sporadic HMN/CMT2 patients using next-generation sequencing (NGS) panel analysis. RESULTS: Bioinformatic analyses led to the identification of novel or very rare variants in genes, which have not been previously associated with HMN/CMT2 (ARHGEF28, KBTBD13, AGRN and GNE); in genes previously associated with HMN/CMT2 but in combination with different clinical phenotypes (VRK1 and PNKP), and in the SIGMAR1 gene, which has been linked to HMN/CMT2 in only a few cases. These findings were further validated by Sanger sequencing, segregation analyses and functional studies. CONCLUSIONS: These results demonstrate the broad spectrum of clinical phenotypes that can be associated with a specific disease gene, as well as the complexity of the pathogenesis of neuromuscular disorders.

In silico prediction of lncRNA function using tissue specific and evolutionary conserved expression.

BACKGROUND: In recent years long non coding RNAs (lncRNAs) have been the subject of increasing interest. Thanks to many recent functional studies, the existence of a large class of lncRNAs with potential regulatory functions is now widely accepted. Although an increasing number of lncRNAs is being characterized and shown to be involved in many biological processes, the functions of the vast majority lncRNA genes is still unknown. Therefore computational methods able to take advantage of the increasing amount of publicly available data to predict lncRNA functions could be very useful. RESULTS: Since coding genes are much better annotated than lncRNAs, we attempted to project known functional information regarding proteins onto non coding genes using the guilt by association principle: if a gene shows an expression profile that correlates with those of a set of coding genes involved in a given function, that gene is probably involved in the same function. We computed gene coexpression for 30 human tissues and 9 vertebrates and mined the resulting networks with a methodology inspired by the rank product algorithm used to identify differentially expressed genes. Using different types of reference data we can predict putative new annotations for thousands of lncRNAs and proteins, ranging from cellular localization to relevance for disease and cancer. CONCLUSIONS: New function of coding genes and lncRNA can be profitably predicted using tissue specific coexpression, as well as expression of orthologous genes in different species. The data are available for download and through a user-friendly web interface at www.funcpred.com .

A functional strategy to characterize expression Quantitative Trait Loci.

The study of genetic variation has been revolutionized by the advent of high-throughput technologies able to determine the complete genomic sequence of thousands of individuals. Understanding the functional relevance of variants is, however, still a difficult task, especially when focusing on non-coding variants. Most of the variants associated with disease by Genome-Wide Association Studies (GWAS) are indeed non-coding, and presumably exert their effects by altering gene regulation. Expression Quantitative Trait Loci (eQTL) studies represent an important step in understanding the functional relevance of regulatory variants. We propose a new strategy to detect and characterize eQTLs, based on the effect of variants on the Total Binding Affinity (TBA) profiles of regulatory regions. Using a large dataset of coupled genome and expression data, we show that TBA-based inference allows the identification of eQTLs not revealed by traditional methods and helps in their interpretation in terms of altered transcription factor binding.

Genome-wide identification and characterization of fixed human-specific regulatory regions.

Changes in gene regulatory networks are believed to have played an important role in the development of human-specific anatomy and behavior. We identified the human genome regions that show the typical chromatin marks of regulatory regions but cannot be aligned to other mammalian genomes. Most of these regions have become fixed in the human genome. Their regulatory targets are enriched in genes involved in neural processes, CNS development, and diseases such as autism, depression, and schizophrenia. Specific transposable elements contributing to the rewiring of the human regulatory network can be identified by the creation of human-specific regulatory regions. Our results confirm the relevance of regulatory evolution in the emergence of human traits and cognitive abilities and the importance of newly acquired genomic elements for such evolution.

Roar: detecting alternative polyadenylation with standard mRNA sequencing libraries.

BACKGROUND: Post-transcriptional regulation is a complex mechanism that plays a central role in defining multiple cellular identities starting from a common genome. Modifications in the length of 3'UTRs have been found to play an important role in this context, since alternative 3' UTRs could lead to differences for example in regulation by microRNAs and cellular localization of the transcripts thus altering their fate. RESULTS: We propose a strategy to identify the genes undergoing regulation of 3' UTR length using RNA sequencing data obtained from standard libraries, thus widely applicable to data originally obtained to perform classical differential expression analyses. We decided to exploit previously annotated APA sites from public databases, in contrast with other approaches recently proposed in which the location of the APA site is inferred from the data together with the relative abundance of the isoforms. We demonstrate the reliability of our method by comparing it to the results of other microarray based or specific RNA-seq libraries methods and show that using APA sites databases results in higher sensitivity compared to de novo site prediction approach. CONCLUSIONS: We implemented the algorithm in a Bioconductor package to facilitate its broad usage in the scientific community. The ability of this approach to detect shortening from libraries with a number of reads comparable to that needed for differential expression analyses makes it useful for investigating if alternative polyadenylation is relevant in a certain biological process without requiring specific experimental assays.

Disease-gene discovery by integration of 3D gene expression and transcription factor binding affinities.

MOTIVATION: The computational evaluation of candidate genes for hereditary disorders is a non-trivial task. Several excellent methods for disease-gene prediction have been developed in the past 2 decades, exploiting widely differing data sources to infer disease-relevant functional relationships between candidate genes and disorders. We have shown recently that spatially mapped, i.e. 3D, gene expression data from the mouse brain can be successfully used to prioritize candidate genes for human Mendelian disorders of the central nervous system. RESULTS: We improved our previous work 2-fold: (i) we demonstrate that condition-independent transcription factor binding affinities of the candidate genes' promoters are relevant for disease-gene prediction and can be integrated with our previous approach to significantly enhance its predictive power; and (ii) we define a novel similarity measure-termed Relative Intensity Overlap-for both 3D gene expression patterns and binding affinity profiles that better exploits their disease-relevant information content. Finally, we present novel disease-gene predictions for eight loci associated with different syndromes of unknown molecular basis that are characterized by mental retardation.

The roles of multiparametric magnetic resonance imaging, PCA3 and prostate health index-which is the best predictor of prostate cancer after a negative biopsy?

PURPOSE: In patients with a negative prostate biopsy and persistent suspicion of prostate cancer, additional analyses such as the PCA3 score, PHI and multiparametric magnetic resonance imaging have been proposed to reduce the number of unnecessary repeat biopsies. In this study we evaluate the diagnostic accuracy of PCA3, PHI, multiparametric magnetic resonance imaging and various combinations of these tests in the repeat biopsy setting. MATERIALS AND METHODS: A total of 170 patients with an initial negative prostate biopsy and persistent suspicion of prostate cancer were enrolled in this prospective study. The patients underwent measurements of the total prostate specific antigen and free prostate specific antigen rate, along with PHI, PCA3 tests and multiparametric magnetic resonance imaging before standard repeat biopsy that was performed by urologists blinded to the multiparametric magnetic resonance imaging results. Multivariate logistic regression models with various combinations of PCA3, PHI and multiparametric magnetic resonance imaging were used to identify the predictors of prostate cancer with repeat biopsy, and the performance of these models was compared using ROC curves, AUC analysis and decision curve analysis. RESULTS: In the ROC analysis the most significant contribution was provided by multiparametric magnetic resonance imaging (AUC 0.936), which was greater than the contribution of the PHI+PCA3 model (p <0.001). In the multivariate logistic regression analysis only multiparametric magnetic resonance imaging was a significant independent predictor of prostate cancer diagnosis with repeat biopsy (p <0.001). The results of the decision curve analysis confirmed that the most significant improvement in the net benefit was provided by multiparametric magnetic resonance imaging. CONCLUSIONS: Multiparametric magnetic resonance imaging provides high diagnostic accuracy in identifying patients with prostate cancer in the repeat biopsy setting compared with PCA3 and PHI.

Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs).

BACKGROUND: The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of 'ad hoc' gene expression data-sets. RESULTS: By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. CONCLUSIONS: Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation.

Identification of functional cis-regulatory polymorphisms in the human genome.

Polymorphisms in regulatory DNA regions are believed to play an important role in determining phenotype, including disease, and in providing raw material for evolution. We devised a new pipeline for the systematic identification of functional variation in human regulatory sequences. The algorithm is based on the identification of SNPs leading to significant changes in both the affinity of a regulatory region for transcription factors (TFs) and the expression in vivo of the regulated gene. We tested the algorithm by identifying SNPs leading to altered regulation by STAT3 in human promoters and introns, and experimentally validated the top-scoring ones, showing that most of the SNPs identified by the algorithm indeed correspond to differential binding of STAT3 and differential induction of the target gene upon stimulation with IL6. Using the same computational approach, we compiled a database of thousands of predicted functional regulatory SNPs for hundreds of human TFs, which we provide as online Supporting Information. We discuss possible applications to the interpretation of noncoding SNPs associated with human diseases. The method we propose and the database of predicted functional cis-regulatory polymorphisms will be useful in future studies of regulatory variation and in particular to interpret the results of past and future genome-wide association studies.

The RacGAP ArhGAP15 is a master negative regulator of neutrophil functions.

In phagocytes, GTPases of the Rac family control crucial antimicrobial functions. The RacGAP ArhGAP15 negatively modulates Rac activity in leukocytes, but its in vivo role in innate immunity remains largely unknown. Here we show that neutrophils and macrophages derived from mice lacking ArhGAP15 presented higher Rac activity but distinct phenotypes. In macrophages, the loss of ArhGAP15 induced increased cellular elongation and membrane protrusions but did not modify chemotactic responses. Conversely, the lack of ArhGAP15 in neutrophils affected critical Rac-dependent antimicrobial functions, specifically causing enhanced chemotactic responses, straighter directional migration, amplified reactive oxygen species production, increased phagocytosis, and improved bacterial killing. In vivo, in a model of severe abdominal sepsis, these effects contributed to increase neutrophil recruitment to the site of infection, thereby limiting bacterial growth, controlling infection spread, reducing systemic inflammation, and ultimately improving survival in ArhGAP15-null mice. Altogether, these results demonstrate the relevance of ArhGAP15 in the selective regulation of multiple neutrophil functions, suggesting that ArhGAP15 targeting might be beneficial in specific pathologic settings like severe sepsis.

3plex enables deep computational investigation of triplex forming lncRNAs.

Long non-coding RNAs (lncRNAs) regulate gene expression through different molecular mechanisms, including DNA binding via the formation of RNA:DNA:DNA triple helices (TPXs). Despite the increasing amount of experimental evidence, TPXs investigation remains challenging. Here we present 3plex, a software able to predict TPX interactions in silico. Given an RNA sequence and a set of DNA sequences, 3plex integrates 1) Hoogsteen pairing rules that describe the biochemical interactions between RNA and DNA nucleotides, 2) RNA secondary structure prediction and 3) determination of the TPX thermal stability derived from a collection of TPX experimental evidences. We systematically collected and uniformly re-analysed published experimental lncRNA binding sites on human and mouse genomes. We used these data to evaluate 3plex performance and showed that its specific features allow a reliable identification of TPX interactions. We compared 3plex with the other available software and obtained comparable or even better accuracy at a fraction of the computation time. Interestingly, by inspecting collected data with 3plex we found that TPXs tend to be shorter and more degenerated than previously expected and that the majority of analysed lncRNAs can directly bind to the genome by TPX formation. Those results suggest that an important fraction of lncRNAs can exert its biological function through this mechanism. The software is available at https://github.com/molinerisLab/3plex.

Targeting tumor-stroma communication by blocking endothelin-1 receptors sensitizes high-grade serous ovarian cancer to PARP inhibition.

PARP inhibitors (PARPi) have changed the treatment paradigm of high-grade serous ovarian cancer (HG-SOC). However, the impact of this class of inhibitors in HG-SOC patients with a high rate of TP53 mutations is limited, highlighting the need to develop combinatorial therapeutic strategies to improve responses to PARPi. Here, we unveil how the endothelin-1/ET-1 receptor (ET-1/ET-1R) axis, which is overexpressed in human HG-SOC and associated with poor prognosis, instructs HG-SOC/tumor microenvironment (TME) communication via key pro-malignant factors and restricts the DNA damage response induced by the PARPi olaparib. Mechanistically, the ET-1 axis promotes the p53/YAP/hypoxia inducible factor-1α (HIF-1α) transcription hub connecting HG-SOC cells, endothelial cells and activated fibroblasts, hence fueling persistent DNA damage signal escape. The ET-1R antagonist macitentan, which dismantles the ET-1R-mediated p53/YAP/HIF-1α network, interferes with HG-SOC/stroma interactions that blunt PARPi efficacy. Pharmacological ET-1R inhibition by macitentan in orthotopic HG-SOC patient-derived xenografts synergizes with olaparib to suppress metastatic progression, enhancing PARPi survival benefit. These findings reveal ET-1R as a mechanistic determinant in the regulation of HG-SOC/TME crosstalk and DNA damage response, indicating the use of macitentan in combinatorial treatments with PARPi as a promising and emerging therapy.