Multiparametric Single-Vesicle Flow Cytometry Resolves Extracellular Vesicle Heterogeneity and Reveals Selective Regulation of Biogenesis and Cargo Distribution.

Mammalian cells release a heterogeneous array of extracellular vesicles (EVs) that contribute to intercellular communication by means of the cargo that they carry. To resolve EV heterogeneity and determine if cargo is partitioned into select EV populations, we developed a method named "EV Fingerprinting" that discerns distinct vesicle populations using dimensional reduction of multiparametric data collected by quantitative single-EV flow cytometry. EV populations were found to be discernible by a combination of membrane order and EV size, both of which were obtained through multiparametric analysis of fluorescent features from the lipophilic dye Di-8-ANEPPS incorporated into the lipid bilayer. Molecular perturbation of EV secretion and biogenesis through respective ablation of the small GTPase Rab27a and overexpression of the EV-associated tetraspanin CD63 revealed distinct and selective alterations in EV populations, as well as cargo distribution. While Rab27a disproportionately affects all small EV populations with high membrane order, the overexpression of CD63 selectively increased the production of one small EV population of intermediate membrane order. Multiplexing experiments subsequently revealed that EV cargos have a distinct, nonrandom distribution with CD63 and CD81 selectively partitioning into smaller vs larger EVs, respectively. These studies not only present a method to probe EV biogenesis but also reveal how the selective partitioning of cargo contributes to EV heterogeneity.

Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy.

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches.

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly.

HLA-DR cancer cells expression correlates with T cell infiltration and is enriched in lung adenocarcinoma with indolent behavior.

Lung adenocarcinoma (ADC) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate whether CyTOF identifies cellular and molecular predictors of tumor behavior. We developed and validated a CyTOF panel of 34 antibodies in four ADC cell lines and PBMC. We tested our panel in a set of 10 ADCs, classified into long- (LPS) (n = 4) and short-predicted survival (SPS) (n = 6) based on radiomics features. We identified cellular subpopulations of epithelial cancer cells (ECC) and their microenvironment and validated our results by multiplex immunofluorescence (mIF) applied to a tissue microarray (TMA) of LPS and SPS ADCs. The antibody panel captured the phenotypical differences in ADC cell lines and PBMC. LPS ADCs had a higher proportion of immune cells. ECC clusters (ECCc) were identified and uncovered two ADC groups. ECCc with high HLA-DR expression were correlated with CD4+ and CD8+ T cells, with LPS samples being enriched for those clusters. We confirmed a positive correlation between HLA-DR expression on ECC and T cell number by mIF staining on TMA slides. Spatial analysis demonstrated shorter distances from T cells to the nearest ECC in LPS. Our results demonstrate a distinctive cellular profile of ECC and their microenvironment in ADC. We showed that HLA-DR expression in ECC is correlated with T cell infiltration, and that a set of ADCs with high abundance of HLA-DR+ ECCc and T cells is enriched in LPS samples. This suggests new insights into the role of antigen presenting tumor cells in tumorigenesis.

Integrated Cells and Collagen Fibers Spatial Image Analysis.

Modern technologies designed for tissue structure visualization like brightfield microscopy, fluorescent microscopy, mass cytometry imaging (MCI) and mass spectrometry imaging (MSI) provide large amounts of quantitative and spatial information about cells and tissue structures like vessels, bronchioles etc. Many published reports have demonstrated that the structural features of cells and extracellular matrix (ECM) and their interactions strongly predict disease development and progression. Computational image analysis methods in combination with spatial analysis and machine learning can reveal novel structural patterns in normal and diseased tissue. Here, we have developed a Python package designed for integrated analysis of cells and ECM in a spatially dependent manner. The package performs segmentation, labeling and feature analysis of ECM fibers, combines this information with pre-generated single-cell based datasets and realizes cell-cell and cell-fiber spatial analysis. To demonstrate performance and compatibility of our computational tool, we integrated it with a pipeline designed for cell segmentation, classification, and feature analysis in the KNIME analytical platform. For validation, we used a set of mouse mammary gland tumors and human lung adenocarcinoma tissue samples stained for multiple cellular markers and collagen as the main ECM protein. The developed package provides sufficient performance and precision to be used as a novel method to investigate cell-ECM relationships in the tissue, as well as detect structural patterns correlated with specific disease outcomes.

Depletion of Embryonic Macrophages Leads to a Reduction in Angiogenesis in the Ex Ovo Chick Chorioallantoic Membrane Assay.

Macrophages play an important but poorly understood role in angiogenesis. To investigate their role in vessel formation, relevant in vivo models are crucial. Although the chick chorioallantoic membrane (CAM) model has been frequently used as an angiogenesis assay, limited data are available on the involvement of chicken macrophages in this process. Here, we describe a method to deplete macrophages in the ex ovo chick CAM assay by injection of clodronate liposomes and show that this depletion directly affects vascularisation of collagen onplants. Chicken embryos were injected intravenously with either clodronate or phosphate-buffered saline (PBS) liposomes, followed by placement of collagen type I plugs on the CAM to quantify angiogenic ingrowth. Clodronate liposome injection led to a significant 3.4-fold reduction of macrophages compared with control embryos as measured by immunohistochemistry and flow cytometry. Furthermore, analysis of vessel ingrowth into the collagen plugs revealed a significantly lower angiogenic response in macrophage-depleted embryos compared with control embryos, indicating that chicken embryonic macrophages play an essential function in the development of blood vessels. These results demonstrate that the chick CAM assay provides a promising model to investigate the role of macrophages in angiogenesis.

Comprehensive palmitoyl-proteomic analysis identifies distinct protein signatures for large and small cancer-derived extracellular vesicles.

Extracellular vesicles (EVs) are membrane-enclosed particles that play an important role in cancer progression and have emerged as a promising source of circulating biomarkers. Protein S-acylation, frequently called palmitoylation, has been proposed as a post-translational mechanism that modulates the dynamics of EV biogenesis and protein cargo sorting. However, technical challenges have limited large-scale profiling of the whole palmitoyl-proteins of EVs. We successfully employed a novel approach that combines low-background acyl-biotinyl exchange (LB-ABE) with label-free proteomics to analyse the palmitoyl-proteome of large EVs (L-EVs) and small EVs (S-EVs) from prostate cancer cells. Here we report the first palmitoyl-protein signature of EVs, and demonstrate that L- and S-EVs harbour proteins associated with distinct biological processes and subcellular origin. We identified STEAP1, STEAP2, and ABCC4 as prostate cancer-specific palmitoyl-proteins abundant in both EV populations. Importantly, localization of the above proteins in EVs was reduced upon inhibition of palmitoylation in the producing cells. Our results suggest that this post-translational modification may play a role in the sorting of the EV-bound secretome and possibly enable selective detection of disease biomarkers.

Integration of the ImageJ Ecosystem in the KNIME Analytics Platform.

Open-source software tools are often used for analysis of scientific image data due to their flexibility and transparency in dealing with rapidly evolving imaging technologies. The complex nature of image analysis problems frequently requires many tools to be used in conjunction, including image processing and analysis, data processing, machine learning and deep learning, statistical analysis of the results, visualization, correlation to heterogeneous but related data, and more. However, the development, and therefore application, of these computational tools is impeded by a lack of integration across platforms. Integration of tools goes beyond convenience, as it is impractical for one tool to anticipate and accommodate the current and future needs of every user. This problem is emphasized in the field of bioimage analysis, where various rapidly emerging methods are quickly being adopted by researchers. ImageJ is a popular open-source image analysis platform, with contributions from a global community resulting in hundreds of specialized routines for a wide array of scientific tasks. ImageJ's strength lies in its accessibility and extensibility, allowing researchers to easily improve the software to solve their image analysis tasks. However, ImageJ is not designed for development of complex end-to-end image analysis workflows. Scientists are often forced to create highly specialized and hard-to-reproduce scripts to orchestrate individual software fragments and cover the entire life-cycle of an analysis of an image dataset. KNIME Analytics Platform, a user-friendly data integration, analysis, and exploration workflow system, was designed to handle huge amounts of heterogeneous data in a platform-agnostic, computing environment and has been successful in meeting complex end-to-end demands in several communities, such as cheminformatics and mass spectrometry. Similar needs within the bioimage analysis community led to the creation of the KNIME Image Processing extension which integrates ImageJ into KNIME Analytics Platform, enabling researchers to develop reproducible and scalable workflows, integrating a diverse range of analysis tools. Here we present how users and developers alike can leverage the ImageJ ecosystem via the KNIME Image Processing extension to provide robust and extensible image analysis within KNIME workflows. We illustrate the benefits of this integration with examples, as well as representative scientific use cases.

A live cell reporter of exosome secretion and uptake reveals pathfinding behavior of migrating cells.

Small extracellular vesicles called exosomes affect multiple autocrine and paracrine cellular phenotypes. Understanding the function of exosomes requires a variety of tools, including live imaging. Our previous live-cell reporter, pHluorin-CD63, allows dynamic subcellular monitoring of exosome secretion in migrating and spreading cells. However, dim fluorescence and the inability to make stably-expressing cell lines limit its use. We incorporated a stabilizing mutation in the pHluorin moiety, M153R, which now exhibits higher, stable expression in cells and superior monitoring of exosome secretion. Using this improved construct, we visualize secreted exosomes in 3D culture and in vivo and identify a role for exosomes in promoting leader-follower behavior in 2D and 3D migration. Incorporating an additional non-pH-sensitive red fluorescent tag allows visualization of the exosome lifecycle, including multivesicular body (MVB) trafficking, MVB fusion, exosome uptake and endosome acidification. This reporter will be a useful tool for understanding both autocrine and paracrine roles of exosomes.

Myeloid Cell-Derived TGFß Signaling Regulates ECM Deposition in Mammary Carcinoma via Adenosine-Dependent Mechanisms.

TGFß plays a crucial role in the tumor microenvironment by regulating cell-cell and cell-stroma interactions. We previously demonstrated that TGFß signaling on myeloid cells regulates expression of CD73, a key enzyme for production of adenosine, a protumorigenic metabolite implicated in regulation of tumor cell behaviors, immune response, and angiogenesis. Here, using an MMTV-PyMT mouse mammary tumor model, we discovered that deletion of TGFß signaling on myeloid cells (PyMT/TGFßRIILysM) affects extracellular matrix (ECM) formation in tumor tissue, specifically increasing collagen and decreasing fibronectin deposition. These changes were associated with mitigated tumor growth and reduced metastases. Reduced TGFß signaling on fibroblasts was associated with their proximity to CD73+ myeloid cells in tumor tissue. Consistent with these findings, adenosine significantly downregulated TGFß signaling on fibroblasts, an effect regulated by A2A and A2B adenosine receptors. METABRIC dataset analysis revealed that patients with triple-negative breast cancer and basal type harbored a similar signature of adenosine and ECM profiles; high expression of A2B adenosine receptors correlated with decreased expression of Col1 and was associated with poor outcome. Taken together, our studies reveal a new role for TGFß signaling on myeloid cells in tumorigenesis. This discovered cross-talk between TGFß/CD73 on myeloid cells and TGFß signaling on fibroblasts can contribute to ECM remodeling and protumorigenic actions of cancer-associated fibroblasts. SIGNIFICANCE: TGFß signaling on fibroblasts is decreased in breast cancer, correlates with poor prognosis, and appears to be driven by adenosine that accelerates tumor progression and metastasis via ECM remodeling.

Hyperoxia Injury in the Developing Lung Is Mediated by Mesenchymal Expression of Wnt5A.

Rationale: Bronchopulmonary dysplasia (BPD) is a leading complication of preterm birth that affects infants born in the saccular stage of lung development at <32 weeks of gestation. Although the mechanisms driving BPD remain uncertain, exposure to hyperoxia is thought to contribute to disease pathogenesis.Objectives: To determine the effects of hyperoxia on epithelial-mesenchymal interactions and to define the mediators of activated Wnt/ß-catenin signaling after hyperoxia injury.Methods: Three hyperoxia models were used: A three-dimensional organotypic coculture using primary human lung cells, precision-cut lung slices (PCLS), and a murine in vivo hyperoxia model. Comparisons of normoxia- and hyperoxia-exposed samples were made by real-time quantitative PCR, RNA in situ hybridization, quantitative confocal microscopy, and lung morphometry.Measurements and Main Results: Examination of an array of Wnt ligands in the three-dimensional organotypic coculture revealed increased mesenchymal expression of WNT5A. Inhibition of Wnt5A abrogated the BPD transcriptomic phenotype induced by hyperoxia. In the PCLS model, Wnt5A inhibition improved alveolarization following hyperoxia exposure, and treatment with recombinant Wnt5a reproduced features of the BPD phenotype in PCLS cultured in normoxic conditions. Chemical inhibition of NF-κB with BAY11-7082 reduced Wnt5a expression in the PCLS hyperoxia model and in vivo mouse hyperoxia model, with improved alveolarization in the PCLS model.Conclusions: Increased mesenchymal Wnt5A during saccular-stage hyperoxia injury contributes to the impaired alveolarization and septal thickening observed in BPD. Precise targeting of Wnt5A may represent a potential therapeutic strategy for the treatment of BPD.

EPHB2 carried on small extracellular vesicles induces tumor angiogenesis via activation of ephrin reverse signaling.

Angiogenesis is a key process that allows nutrient uptake and cellular trafficking and is coopted in cancer to enable tumor growth and metastasis. Recently, extracellular vesicles (EVs) have been shown to promote angiogenesis; however, it is unclear what unique features EVs contribute to the process. Here, we studied the role of EVs derived from head and neck squamous cell carcinoma (HNSCC) in driving tumor angiogenesis. Small EVs (SEVs), in the size range of exosomes (50-150 nm), induced angiogenesis both in vitro and in vivo. Proteomic analysis of HNSCC SEVs revealed the cell-to-cell signaling receptor ephrin type B receptor 2 (EPHB2) as a promising candidate cargo to promote angiogenesis. Analysis of patient data further identified EPHB2 overexpression in HNSCC tumors to be associated with poor patient prognosis and tumor angiogenesis, especially in the context of overexpression of the exosome secretion regulator cortactin. Functional experiments revealed that EPHB2 expression in SEVs regulated angiogenesis both in vitro and in vivo and that EPHB2 carried by SEVs stimulates ephrin-B reverse signaling, inducing STAT3 phosphorylation. A STAT3 inhibitor greatly reduced SEV-induced angiogenesis. These data suggest a model in which EVs uniquely promote angiogenesis by transporting Eph transmembrane receptors to nonadjacent endothelial cells to induce ephrin reverse signaling.

Urinary Metabolomics Validates Metabolic Differentiation Between Renal Cell Carcinoma Stages and Reveals a Unique Metabolic Profile for Oncocytomas.

Renal cell carcinoma (RCC) is a heterogeneous malignancy which often develops and progresses asymptomatically. Benign oncocytomas are morphologically similar to malignant chromophobe RCC and distinguishing between these two forms on cross-sectional imaging remains a challenge. Therefore, RCC-specific biomarkers are urgently required for accurate and non-invasive, pre-surgical diagnosis of benign lesions. We have previously shown that dysregulation in glycolytic and tricarboxylic acid cycle intermediates can distinguish benign lesions from RCC in a stage-specific manner. In this study, preoperative fasting urine samples from patients with renal masses were assessed by ¹H nuclear magnetic resonance (NMR). Significant alterations in levels of tricarboxylic acid cycle intermediates, carnitines and its derivatives were detected in RCC relative to benign masses and in oncocytomas vs. chromophobe RCC. Orthogonal Partial Least Square Discriminant Analysis plots confirmed stage discrimination between benign vs. pT1 (R2 = 0.42, Q2 = 0.27) and benign vs. pT3 (R2 = 0.48, Q2 = 0.32) and showed separation for oncocytomas vs. chromophobe RCC (R2 = 0.81, Q2 = 0.57) and oncocytomas vs. clear cell RCC (R2 = 0.32, Q2 = 0.20). This study validates our previously described metabolic profile distinguishing benign tumors from RCC and presents a novel metabolic signature for oncocytomas which may be exploited for diagnosis before cross-sectional imaging.

The importance of developing therapies targeting the biological spectrum of metastatic disease.

Great progress has been made in cancer therapeutics. However, metastasis remains the predominant cause of death from cancer. Importantly, metastasis can manifest many years after initial treatment of the primary cancer. This is because cancer cells can remain dormant before forming symptomatic metastasis. An important question is whether metastasis research should focus on the early treatment of metastases, before they are clinically evident ("overt"), or on developing treatments to stop overt metastasis (stage IV cancer). In this commentary we want to clarify why it is important that all avenues of treatment for stage IV patients are developed. Indeed, future treatments are expected to go beyond the mere shrinkage of overt metastases and will include strategies that prevent disseminated tumor cells from emerging from dormancy.

Modulation of cell adhesion and migration through regulation of the immunoglobulin superfamily member ALCAM/CD166.

In epithelial-derived cancers, altered regulation of cell-cell adhesion facilitates the disruption of tissue cohesion that is central to the progression to malignant disease. Although numerous intercellular adhesion molecules participate in epithelial adhesion, the immunoglobulin superfamily (IgSF) member activated leukocyte cell adhesion molecule (ALCAM), has emerged from multiple independent studies as a central contributor to tumor progression. ALCAM is an archetypal member of the IgSF with conventional organization of five Ig-like domains involved in homo- and heterotypic adhesions. Like many IgSF members, ALCAM is broadly expressed and involved in cellular adhesion across many cellular processes. While the redundancy of intercellular adhesion molecules (CAMs) could diminish the impact of any single CAM, consistent correlation between ALCAM expression and patient outcome for multiple cancers underscores its role in tumor progression. Unlike most oncogenes and tumor suppressors, ALCAM is neither mutated nor amplified or deleted. Experimental disruption of ALCAM-mediated adhesions implies that this IgSF member contributes to tumor progression through dynamic turnover of the protein at the cell surface. Since ALCAM is not frequently altered at the gene level, it appears to promote malignant behavior through regulation of its availability rather than its specific activity. These observations help explain its heterogeneous expression within malignant disease and the drastic changes in protein levels across tumor progression. To reveal how ALCAM contributes to tumor progression, we review regulation of its gene expression, alternative splicing, targeted proteolysis, binding partners, and surface shedding within the context of cancer. Studying ALCAM regulation has led to a novel understanding of the fine-tuning of cell adhesive state through the utilization of otherwise normal regulatory processes, which thereby enable tumor cell invasion and metastasis.

Beyond the H&E: Advanced Technologies for in situ Tissue Biomarker Imaging.

For decades, histopathology with routine hematoxylin and eosin staining has been and remains the gold standard for reaching a morphologic diagnosis in tissue samples from humans and veterinary species. However, within the past decade, there has been exponential growth in advanced techniques for in situ tissue biomarker imaging that bridge the divide between anatomic and molecular pathology. It is now possible to simultaneously observe localization and expression magnitude of multiple protein, nucleic acid, and molecular targets in tissue sections and apply machine learning to synthesize vast, image-derived datasets. As these technologies become more sophisticated and widely available, a team-science approach involving subspecialists with medical, engineering, and physics backgrounds is critical to upholding quality and validity in studies generating these data. The purpose of this manuscript is to detail the scientific premise, tools and training, quality control, and data collection and analysis considerations needed for the most prominent advanced imaging technologies currently applied in tissue sections: immunofluorescence, in situ hybridization, laser capture microdissection, matrix-assisted laser desorption ionization imaging mass spectrometry, and spectroscopic/optical methods. We conclude with a brief overview of future directions for ex vivo and in vivo imaging techniques.

AXL Mediates Esophageal Adenocarcinoma Cell Invasion through Regulation of Extracellular Acidification and Lysosome Trafficking.

Esophageal adenocarcinoma (EAC) is a highly aggressive malignancy that is characterized by resistance to chemotherapy and a poor clinical outcome. The overexpression of the receptor tyrosine kinase AXL is frequently associated with unfavorable prognosis in EAC. Although it is well documented that AXL mediates cancer cell invasion as a downstream effector of epithelial-to-mesenchymal transition, the precise molecular mechanism underlying this process is not completely understood. Herein, we demonstrate for the first time that AXL mediates cell invasion through the regulation of lysosomes peripheral distribution and cathepsin B secretion in EAC cell lines. Furthermore, we show that AXL-dependent peripheral distribution of lysosomes and cell invasion are mediated by extracellular acidification, which is potentiated by AXL-induced secretion of lactate through AKT-NF-κB-dependent MCT-1 regulation. Our novel mechanistic findings support future clinical studies to evaluate the therapeutic potential of the AXL inhibitor R428 (BGB324) in highly invasive EAC.

Large extracellular vesicles carry most of the tumour DNA circulating in prostate cancer patient plasma.

Cancer-derived extracellular vesicles (EVs) are membrane-enclosed structures of highly variable size. EVs contain a myriad of substances (proteins, lipid, RNA, DNA) that provide a reservoir of circulating molecules, thus offering a good source of biomarkers. We demonstrate here that large EVs (L-EV) (large oncosomes) isolated from prostate cancer (PCa) cells and patient plasma are an EV population that is enriched in chromosomal DNA, including large fragments up to 2 million base pair long. While L-EVs and small EVs (S-EV) (exosomes) isolated from the same cells contained similar amounts of protein, the DNA was more abundant in L-EV, despite S-EVs being more numerous. Consistent with in vitro observations, the abundance of DNA in L-EV obtained from PCa patient plasma was variable but frequently high. Conversely, negligible amounts of DNA were present in the S-EVs from the same patients. Controlled experimental conditions, with spike-ins of L-EVs and S-EVs from cancer cells in human plasma from healthy subjects, showed that circulating DNA is almost exclusively enclosed in L-EVs. Whole genome sequencing revealed that the DNA in L-EVs reflects genetic aberrations of the cell of origin, including copy number variations of genes frequently altered in metastatic PCa (i.e. MYC, AKT1, PTK2, KLF10 and PTEN). These results demonstrate that L-EV-derived DNA reflects the genomic make-up of the tumour of origin. They also support the conclusion that L-EVs are the fraction of plasma EVs with DNA content that should be interrogated for tumour-derived genomic alterations.

Emerin Deregulation Links Nuclear Shape Instability to Metastatic Potential.

Abnormalities in nuclear shape are a well-known feature of cancer, but their contribution to malignant progression remains poorly understood. Here, we show that depletion of the cytoskeletal regulator, Diaphanous-related formin 3 (DIAPH3), or the nuclear membrane-associated proteins, lamin A/C, in prostate and breast cancer cells, induces nuclear shape instability, with a corresponding gain in malignant properties, including secretion of extracellular vesicles that contain genomic material. This transformation is characterized by a reduction and/or mislocalization of the inner nuclear membrane protein, emerin. Consistent with this, depletion of emerin evokes nuclear shape instability and promotes metastasis. By visualizing emerin localization, evidence for nuclear shape instability was observed in cultured tumor cells, in experimental models of prostate cancer, in human prostate cancer tissues, and in circulating tumor cells from patients with metastatic disease. Quantitation of emerin mislocalization discriminated cancer from benign tissue and correlated with disease progression in a prostate cancer cohort. Taken together, these results identify emerin as a mediator of nuclear shape stability in cancer and show that destabilization of emerin can promote metastasis.Significance: This study identifies a novel mechanism integrating the control of nuclear structure with the metastatic phenotype, and our inclusion of two types of human specimens (cancer tissues and circulating tumor cells) demonstrates direct relevance to human cancer.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/21/6086/F1.large.jpg Cancer Res; 78(21); 6086-97. ©2018 AACR.

Epithelial-Mesenchymal Transition Induces Podocalyxin to Promote Extravasation via Ezrin Signaling.

The epithelial-mesenchymal transition (EMT) endows carcinoma cells with traits needed to complete many of the steps leading to metastasis formation, but its contributions specifically to the late step of extravasation remain understudied. We find that breast cancer cells that have undergone an EMT extravasate more efficiently from blood vessels both in vitro and in vivo. Analysis of gene expression changes associated with the EMT program led to the identification of an EMT-induced cell-surface protein, podocalyxin (PODXL), as a key mediator of extravasation in mesenchymal breast and pancreatic carcinoma cells. PODXL promotes extravasation through direct interaction of its intracellular domain with the cytoskeletal linker protein ezrin. Ezrin proceeds to establish dorsal cortical polarity, enabling the transition of cancer cells from a non-polarized, rounded cell morphology to an invasive extravasation-competent shape. Hence, the EMT program can directly enhance the efficiency of extravasation and subsequent metastasis formation through a PODXL-ezrin signaling axis.