Genetic studies have linked PHACTR1 to a range of vascular diseases, underscoring its pivotal role in vascular biology. However, the full spectrum of PHACTR1-mediated signaling pathways remains largely unexplored. To bridge this gap, we employ a multi-omics pipeline combining pairwise differential expression analysis, multi-omics pathway integration, and feature-level correlation analyses across four distinct omics datasets to map the global signaling networks driven by PHACTR1. By integrating transcriptomic, proteomic, metabolic, and lipidomic profiles from human HT1080 cells with PHACTR1 overexpression or knockdown, and then validating key findings in primary human endothelial cells, here we show that PHACTR1 exerts broad control over fundamental cellular processes beyond cytoskeletal regulation. We demonstrate that PHACTR1 governs cell cycle progression, validating that increased expression alters key regulatory proteins. We also uncover a distinct function in iron metabolism, showing PHACTR1 regulates essential cellular iron-storage proteins and identify the PHACTR1 protein within the mitochondria where it directs morphology and bioenergetics through a signaling axis involving AKAP1 and Drp1. These mitochondrial changes align with observed shifts in lipid metabolism and correlations in human arterial tissue. These findings provide a systems-level blueprint of PHACTR1 function, revealing how this gene influences vascular health and offering potential targets for therapeutic intervention. Integrated multi-omics analysis uncovers the role of the vascular disease-associated gene PHACTR1 in regulating mitochondrial dynamics, iron metabolism, and cell cycle.

Coronary artery disease (CAD) is a major cause of global morbidity and mortality. Macrophages play a central role in orchestrating this disease process. In 2016, we initiated the STARNET primary blood macrophage study, followed by the multi-ethnic NGS-PREDICT primary blood macrophage study in 2018. We applied integrative systems genetics analysis to explore and validate the role of macrophage gene regulatory co-expression networks (GRNs) in clinically significant CAD. This study included 318 CAD cases and 134 CAD-free controls in STARNET, and 95 CAD cases and 35 CAD-free controls in NGS-PREDICT. Primary leukocytes were isolated from blood and differentiated into macrophages in vitro, followed by RNA extraction and deep sequencing (RNAseq). In STARNET, we analyzed differentially expressed genes, inferred macrophage GRNs, assessed the phenotypic associations and functions of these GRNs, and determined their key driver genes. Integrative analysis of STARNET expression quantitative traits (eQTLs) with genotype data from genome-wide association studies was performed to determine the content of CAD candidate genes in these GRNs, and their contributions to CAD heritability. Five independent RNAseq datasets were used to retrospectively validate CAD-associated macrophage GRNs, followed by prospective validation in the NGS-PREDICT study. Using the STARNET datasets, we identified 23 macrophage GRNs. Of these, GRNGREEN stood out as being causally associated with CAD severity (SYNTAX score) and comprised 729 genes and 90 key drivers, with the top key driver being NEIL1. GRNGREEN accounted for 3.73% of CAD heritability and contained 34 candidate genes previously identified by GWAS of CAD. Functional analysis of GRNGREEN revealed a large portion of genes involved in the biological process of SRP-dependent co-translational protein targeting to the membrane. GRNGREEN replicated retrospectively in five independent human arterial wall RNAseq datasets, and prospectively in the NGS-PREDICT study. To prevent clinically significant CAD, GRNGREEN and its top key driver NEIL1 may be suitable therapeutic targets to modify SRP-dependent co-translational targeting of proteins to the endoplasmic reticulum in macrophages.

Although c-Jun N-terminal Kinase (JNK) represents an attractive anti-cancer target, its pleiotropic functionality limits the use of direct JNK inhibitors. Here, we identify a distinct subcellular pattern of JNK activity as a therapeutic vulnerability in breast cancer, where cytoplasmic JNK activity predicts poor survival outcomes, is elevated in triple-negative breast cancers (TNBC) and is essential for metastatic outgrowth. Mechanistic analyses reveal cytoplasmic JNK acts through multiple mechanisms, with downstream targets involved in cellular metabolism and cytoskeletal regulation. On this basis, we leveraged actin-based phenotypic drug-screening and identified K12, an indirect but selective inhibitor of cytoplasmic JNK that blocks TNBC metastatic outgrowth in vivo . We reveal that K12 inhibits glutaminase-1 and the pyruvate dehydrogenase complex, and that this poly-pharmacology overcomes pyruvate anaplerosis, a known resistance mechanism of existing glutaminase inhibitors. These findings demonstrate the potential of selectively targeting the oncogenic function of JNK, offering new treatment options for early-stage metastatic TNBC. ### Competing Interest Statement The authors have declared no competing interest.

Coronary artery disease (CAD) is a major cause of global morbidity and mortality. Macrophages play a central role in orchestrating this disease process. In 2016, we initiated the STARNET primary blood macrophage study, followed by the multi-ethnic NGS-PREDICT primary blood macrophage study in 2018. We applied integrative systems genetics analysis to explore and validate the role of macrophage gene regulatory co-expression networks (GRNs) in clinically significant CAD. This study included 318 CAD cases and 134 CAD-free controls in STARNET, and 95 CAD cases and 35 CAD-free controls in NGS-PREDICT. Primary leukocytes were isolated from blood and differentiated into macrophages in vitro, followed by RNA extraction and deep sequencing (RNAseq). In STARNET, we analyzed differentially expressed genes, inferred macrophage GRNs, assessed the phenotypic associations and functions of these GRNs, and determined their key driver genes. Integrative analysis of STARNET expression quantitative traits (eQTLs) with genotype data from genome-wide association studies was performed to determine the content of CAD candidate genes in these GRNs, and their contributions to CAD heritability. Five independent RNAseq datasets were used to retrospectively validate CAD-associated macrophage GRNs, followed by prospective validation in the NGS-PREDICT study. Using the STARNET datasets, we identified 23 macrophage GRNs. Of these, GRNGREEN stood out as being causally associated with CAD severity (SYNTAX score) and comprised 729 genes and 90 key drivers, with the top key driver being NEIL1. GRNGREEN accounted for 3.73

Phenotypic plasticity, defined as the ability of individual cells with stable genotypes to exert different phenotypes upon exposure to specific environmental cues, represent the quintessential hallmark of the cancer cell en route from the primary lesion to distant organ sites where metastatic colonization will occur. Phenotypic plasticity is driven by a broad spectrum of epigenetic mechanisms that allow for the reversibility of epithelial-to-mesenchymal and mesenchymal-to-epithelial transitions (EMT/MET). By taking advantage of the co-existence of epithelial and quasi-mesenchymal cells within immortalized cancer cell lines, we have analyzed the role of EMT-related gene isoforms in the regulation of epithelial mesenchymal plasticity (EMP) in high grade serous ovarian cancer. When compared with colon cancer, a distinct spectrum of downstream targets characterizes quasi-mesenchymal ovarian cancer cells, likely to reflect the different modalities of metastasis formation between these two types of malignancy, i.e. hematogenous in colon and transcoelomic in ovarian cancer. Moreover, upstream RNA-binding proteins differentially expressed between epithelial and quasi-mesenchymal subpopulations of ovarian cancer cells were identified that underlie differential regulation of EMT-related isoforms. In particular, the up- and down-regulation of RBM24 and ESRP1, respectively, represent a main regulator of EMT in ovarian cancer cells. To validate the functional and clinical relevance of our approach, we selected and functionally analyzed the Tropomyosin 1 gene (TPM1), encoding for a protein that specifies the functional characteristics of individual actin filaments in contractile cells, among the ovarian-specific downstream AS targets. The low-molecular weight Tpm1.8/9 isoforms are specifically expressed in patient-derived ascites and promote invasion through activation of EMT and Wnt signaling, together with a broad spectrum of inflammation-related pathways. Moreover, Tpm1.8/9 expression confers resistance to taxane- and platinum-based chemotherapy. Small molecule inhibitors that target the Tpm1 isoforms support targeting Tpm1.8/9 as therapeutic targets for the development of future tailor-made clinical interventions.

The actin cytoskeleton is composed of both branched and unbranched actin filaments. In mammals, the unbranched actin filaments are primarily copolymers of actin and tropomyosin. Biochemical and imaging studies indicate that different tropomyosin isoforms are segregated to different actin filament populations in cells and tissues, providing isoform-specific functionality to the actin filament. Intrinsic to this model is the prediction that single-molecule imaging of tropomyosin isoforms would confirm homopolymer formation along the length of single actin filaments, a knowledge gap that remains unaddressed in the cellular environment. We combined chemical labeling of genetically engineered tropomyosin isoforms with electron tomography to locate individual tropomyosin molecules in fibroblasts. We find that the organization of two non-muscle tropomyosins, Tpm3.1 with Tpm4.2, can be distinguished from each other using light and electron microscopy. Visualization of single tropomyosin molecules associated with actin filaments supports the hypothesis that tropomyosins form continuous homopolymers, instead of heteropolymers, in the presence of all physiologically native actin-binding proteins. This is true for both isoforms tested. Furthermore, the data suggest that the tropomyosin molecules on one side of an actin filament may not be in register with those on the opposite side, indicating that each tropomyosin polymer may assembly independently.

The combinations of anti-Tpm3.1 compounds and VCR synergistically arrest HeLa cells in mitosis.

The measurement of spindle length and cell vertical length.

The synergistic anti-cancer efficiency of the drug combinations is well correlated with the combinational impact on mitosis.

Representative images of spindle phenotypes.

The impact of single drugs and the synergy of their combinations on the viability of HeLa cells.

Aurora-A inhibitor MLN8237 (MLN) shows no or low synergy with VCR or ATM.

The combinations of anti-Tpm3.1 drugs and VCR show strong synergy in inducing apoptosis.

Tpm3.1 localizes at cell cortex during mitosis.

Background: Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association study data sets. Methods: We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). Results: We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks. Conclusions: We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.

Genome wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with the risk of common disorders. However, since the large majority of these risk SNPs reside outside gene-coding regions, GWAS generally provide no information about causal mechanisms regarding the specific gene(s) that are affected or the tissue(s) in which these candidate gene(s) exert their effect. The ‘gold standard’ method for understanding causal genes and their mechanisms of action are laborious basic science studies often involving sophisticated knockin or knockout mouse lines, however, these types of studies are impractical as a high-throughput means to understand the many risk variants that cause complex diseases like coronary artery disease (CAD). As a solution, we developed a streamlined, data-driven informatics pipeline to gain mechanistic insights on complex genetic loci. The pipeline begins by understanding the SNPs in a given locus in terms of their relative location and linkage disequilibrium relationships, and then identifies nearby expression quantitative trait loci (eQTLs) to determine their relative independence and the likely tissues that mediate their disease-causal effects. The pipeline then seeks to understand associations with other disease-relevant genes, disease sub-phenotypes, potential causality (Mendelian randomization), and the regulatory and functional involvement of these genes in gene regulatory co-expression networks (GRNs). Here, we applied this pipeline to understand a cluster of SNPs associated with CAD within and immediately adjacent to the gene encoding HDAC9 . Our pipeline demonstrated, and validated, that this locus is causal for CAD by modulation of TWIST1 expression levels in the arterial wall, and by also governing a GRN related to metabolic function in skeletal muscle. Our results reconciled numerous prior studies, and also provided clear evidence that this locus does not govern HDAC9 expression, structure or function. This pipeline should be considered as a powerful and efficient way to understand GWAS risk loci in a manner that better reflects the highly complex nature of genetic risk associated with common disorders.

Background Anti-microtubule agents are widely used to treat ovarian cancers, but the efficacy is often compromised by drug resistance. We investigated co-targeting the actin/tropomyosin cytoskeleton and microtubules to increase treatment efficacy in ovarian cancers and potentially overcome resistance. Methods The presence of tropomyosin-3.1 (Tpm3.1) was examined in clinical specimens from ovarian cancer patients using immunohistochemistry. Combinatorial effects of an anti-Tpm3.1 compound, ATM-3507, with vinorelbine and paclitaxel were evaluated in ovarian cancer cells via MTS and apoptosis assays. The mechanisms of action were established using live- and fixed-cell imaging and protein analysis. Results Tpm3.1 is overexpressed in 97% of tumour tissues (558 of 577) representing all histotypes of epithelial ovarian cancer. ATM-3507 displayed synergy with both anti-microtubule agents to reduce cell viability. Only vinorelbine synergised with ATM-3507 in causing apoptosis. ATM-3507 significantly prolonged vinorelbine-induced mitotic arrest with elevated activity of the spindle assembly checkpoint and mitotic cell death; however, ATM-3507 showed minor impact on paclitaxel-induced mitotic defects. Both combinations substantially increased post-mitotic G1 arrest with cyclin D1 and E1 downregulation and an increase of p21(Cip) and p27(Kip). Conclusion Combined targeting of Tpm3.1/actin and microtubules is a promising treatment strategy for ovarian cancer that should be further tested in clinical settings.

The actin cytoskeleton is the primary driver of cellular adhesion and mechanosensing due to its ability to generate force and sense the stiffness of the environment. At the cell’s leading edge, severing of the protruding Arp2/3 actin network generates a specific actin/tropomyosin (Tpm) filament population that controls lamellipodial persistence. The interaction between these filaments and adhesion to the environment is unknown. Using cellular cryo-electron tomography we resolve the ultrastructure of the Tpm/actin copolymers and show that they specifically anchor to nascent adhesions and are essential for focal adhesion assembly. Re-expression of Tpm1.8/1.9 in transformed and cancer cells is sufficient to restore cell–substrate adhesions. We demonstrate that knock-out of Tpm1.8/1.9 disrupts the formation of dorsal actin bundles, hindering the recruitment of α-actinin and non-muscle myosin IIa, critical mechanosensors. This loss causes a force-generation and proliferation defect that is notably reversed when cells are grown on soft surfaces. We conclude that Tpm1.8/1.9 suppress the metastatic phenotype, which may explain why transformed cells naturally downregulate this Tpm subset during malignant transformation.

Abstract Anti-microtubule agents are widely used to treat ovarian cancers in the first line and recurrent setting either in combination with platinum or as single agents. However, the majority of patients will experience a recurrence, and most will die with drug resistant disease. We investigated co-targeting the actin cytoskeleton in combination with anti-microtubule agents to increase efficacy of treatment in epithelial ovarian cancers and potentially overcome resistance mechanisms. We examined the presence of actin/tropomyosin 3.1 (Tpm3.1) filaments in a large cohort of clinical specimens from patients with epithelial ovarian cancer of all histotypes using immunohistochemistry. Combinatorial effects of an anti-Tpm3.1 compound (ATM) with both vinorelbine and paclitaxel were evaluated in three ovarian cancer cell lines using cell viability and apoptosis assays. The mechanisms of synergy of both combinations were established using live-cell imaging, fluorescent microscopy, and pathway analysis. We found that Tpm3.1 is abundant and overexpressed in 97% of ovarian cancers examined (558 of 577) representing all histotypes of epithelial ovarian cancer. High levels of Tpm3.1 were also present in all sites sampled and similar at primary diagnosis and at recurrence. ATM displayed both single agent activity as well as synergy with both anti-microtubule drugs to reduce cell viability in all ovarian cancer cell lines tested, including one with platinum resistance. Only vinorelbine, however, synergised with ATM in the induction of apoptosis. Vinorelbine-induced mitotic arrest was significantly prolonged by ATM with elevated activity of the spindle assembly checkpoint, leading to almost one third of total cells dying in mitosis. In contrast, ATM showed minor impact on paclitaxel-induced mitotic defects. Both combinations resulted in a substantial increase in cells arrested in the subsequent G1 phase with a large decrease of both cyclin D1 and E1 as compared to single agents. Upregulation of p21Cip and p27Kip were associated with both combinations. In summary, targeting Tpm3.1-associated actin filaments in combination with anti-microtubule drugs is a promising treatment strategy that should be tested in clinical trials and is potentially applicable to all histotypes of ovarian cancer. Citation Format: Xing Xu, Yao Wang, Nicole Bryce, Katrina Tang, Nicola S. Meagher, Eun Young Kang, Linda E. Kelemen, Martin Köbel, Susan J. Ramus, Michael Friedlander, Caroline E. Ford, Edna C. Hardeman, Peter W. Gunning. Combined targeting of actin/tropomyosin and microtubules underlies a potential treatment strategy of epithelial ovarian cancer with cell-cycle dependent synergy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1045.