Extracellular vesicles for precision medicine in prostate cancer - Is it ready for clinical translation?

Biofluid-based biomarker tests hold great promise for precision medicine in prostate cancer (PCa) clinical practice. Extracellular vesicles (EV) are established as intercellular messengers in cancer development with EV cargos, including protein and nucleic acids, having the potential to serve as biofluid-based biomarkers. Recent clinical studies have begun to evaluate EV-based biomarkers for PCa diagnosis, prognosis, and disease/therapy resistance monitoring. Promising results have led to PCa EV biomarker validation studies which are currently underway with the next challenge being translation to robust clinical assays. However, EV research studies generally use low throughput EV isolation methods and costly molecular profiling technologies that are not suitable for clinical assays. Here, we consider the technical hurdles in translating EV biomarker research findings into precise and cost-effective clinical biomarker assays. Novel microfluidic devices coupling EV extraction with sensitive antibody-based biomarker detection are already being explored for point-of-care applications for rapid provision in personalised medicine approaches.

Defining the relationship between cellular and extracellular vesicle (EV) content in breast cancer via an integrative multi-omic analysis.

Much recent research has been dedicated to exploring the utility of extracellular vesicles (EVs) as circulating disease biomarkers. Underpinning this work is the assumption that the molecular cargo of EVs directly reflects the originating cell. Few attempts have been made, however, to empirically validate this on the -omic level. To this end, we have performed an integrative multi-omic analysis of a panel of breast cancer cell lines and corresponding EVs. Whole transcriptome analysis validated that the cellular transcriptome remained stable when cultured cells are transitioned to low serum or serum-free medium for EV collection. Transcriptomic profiling of the isolated EVs indicated a positive correlation between transcript levels in cells and EVs, including disease-associated transcripts. Analysis of the EV proteome verified that HER2 protein is present in EVs, however neither the estrogen (ER) nor progesterone (PR) receptor proteins are detected regardless of cellular expression. Using multivariate analysis, we derived an EV protein signature to infer cellular patterns of ER and HER2 expression, though the ER protein could not be directly detected. Integrative analyses affirmed that the EV proteome and transcriptome captured key phenotypic hallmarks of the originating cells, supporting the potential of EVs for non-invasive monitoring of breast cancers.

LipidSuite: interactive web server for lipidomics differential and enrichment analysis.

Advances in mass spectrometry enabled high throughput profiling of lipids but differential analysis and biological interpretation of lipidomics datasets remains challenging. To overcome this barrier, we present LipidSuite, an end-to-end differential lipidomics data analysis server. LipidSuite offers a step-by-step workflow for preprocessing, exploration, differential analysis and enrichment analysis of untargeted and targeted lipidomics. Three lipidomics data formats are accepted for upload: mwTab file from Metabolomics Workbench, Skyline CSV Export, and a numerical matrix. Experimental variables to be used in analysis are uploaded in a separate file. Conventional lipid names are automatically parsed to enable lipid class and chain length analyses. Users can interactively explore data, choose subsets based on sample types or lipid classes or characteristics, and conduct univariate, multivariate and unsupervised analyses. For complex experimental designs and clinical cohorts, LipidSuite offers confounding variables adjustment. Finally, data tables and plots can be both interactively viewed or downloaded for publication or reports. Overall, we anticipate this free, user-friendly webserver to facilitate differential lipidomics data analysis and re-analysis, and fully harness biological interpretation from lipidomics datasets. LipidSuite is freely available at http://suite.lipidr.org.

Increased lipid metabolism impairs NK cell function and mediates adaptation to the lymphoma environment.

Natural killer (NK) cells play critical roles in protection against hematological malignancies but can acquire a dysfunctional state, which limits antitumor immunity. However, the underlying reasons for this impaired NK cell function remain to be uncovered. We found that NK cells in aggressive B-cell lymphoma underwent substantial transcriptional reprogramming associated with increased lipid metabolism, including elevated expression of the transcriptional regulator peroxisome activator receptor-γ (PPAR-γ). Exposure to fatty acids in the lymphoma environment potently suppressed NK cell effector response and cellular metabolism. NK cells from both diffuse large B-cell lymphoma patients and Eµ-myc B-cell lymphoma-bearing mice displayed reduced interferon-γ (IFN-γ) production. Activation of PPAR-γ partially restored mitochondrial membrane potential and IFN-γ production. Overall, our data indicate that increased lipid metabolism, while impairing their function, is a functional adaptation of NK cells to the fatty-acid rich lymphoma environment.

Addressing Delicate and Variable Cancer Morphology in Spectral Histopathology Using Canine Visceral Hemangiosarcoma.

Spectral histopathology has shown promise for the classification and diagnosis of tumors with defined morphology, but application in tumors with variable or diffuse morphologies is yet to be investigated. To address this gap, we evaluated the application of Fourier transform infrared (FTIR) imaging as an accessory diagnostic tool for canine hemangiosarcoma (HSA), a vascular endothelial cell cancer that is difficult to diagnose. To preserve the delicate vascular tumor tissue structure, and potential classification of single endothelial cells, paraffin removal was not performed, and a partial least square discrimination analysis (PLSDA) and Random Forest (RF) models to classify different tissue types at individual pixel level were established using a calibration set (24 FTIR images from 13 spleen specimens). Next, the prediction capability of the PLSDA model was tested with an independent test set (n = 11), resulting in 74% correct classification of different tissue types at an individual pixel level. Finally, the performance of the FTIR spectropathology and chemometric algorithm for diagnosis of HSA was established in a blinded set of tissue samples (n = 24), with sensitivity and specificity of 80 and 81%, respectively. Taken together, these results show that FTIR imaging without paraffin removal can be applied to tumors with diffuse morphology, and this technique is a promising tool to assist in canine splenic HSA differential diagnosis.

Rapid Classification of COVID-19 Severity by ATR-FTIR Spectroscopy of Plasma Samples.

The coronavirus disease 2019 (COVID-19) pandemic continues to ravage the world, with many hospitals overwhelmed by the large number of patients presenting during major outbreaks. A rapid triage for COVID-19 patient requiring hospitalization and intensive care is urgently needed. Age and comorbidities have been associated with a higher risk of severe COVID-19 but are not sufficient to triage patients. Here, we investigated the potential of attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy as a rapid blood test for classification of COVID-19 disease severity using a cohort of 160 COVID-19 patients. A simple plasma processing and ATR-FTIR data acquisition procedure was established using 75% ethanol for viral inactivation. Next, partial least-squares-discriminant analysis (PLS-DA) models were developed and tested using data from 130 and 30 patients, respectively. Addition of the ATR-FTIR spectra to the clinical parameters (age, sex, diabetes mellitus, and hypertension) increased the area under the ROC curve (C-statistics) for both the training and test data sets, from 69.3% (95% CI 59.8-78.9%) to 85.7% (78.6-92.8%) and 77.8% (61.3-94.4%) to 85.1% (71.3-98.8%), respectively. The independent test set achieved 69.2% specificity (42.4-87.3%) and 94.1% sensitivity (73.0-99.0%). Diabetes mellitus was the strongest predictor in the model, followed by FTIR regions 1020-1090 and 1588-1592 cm-1. In summary, this study demonstrates the potential of ATR-FTIR spectroscopy as a rapid, low-cost COVID-19 severity triage tool to facilitate COVID-19 patient management during an outbreak.

Correction: Detecting antimicrobial resistance in Escherichia coli using benchtop attenuated total reflectance-Fourier transform infrared spectroscopy and machine learning.

Correction for 'Detecting antimicrobial resistance in Escherichia coli using benchtop attenuated total reflectance-Fourier transform infrared spectroscopy and machine learning' by Hewa G. S. Wijesinghe et al., Analyst, 2021, DOI: 10.1039/d1an00546d.

Detecting antimicrobial resistance in Escherichia coli using benchtop attenuated total reflectance-Fourier transform infrared spectroscopy and machine learning.

The widespread dissemination of resistance to third-generation cephalosporins in the Enterobacterales through the production of extended-spectrum ß-lactamase (ESBL) is considered a critical global crisis requiring urgent attention of clinicians and scientists alike. Rapid diagnostic methods that can identify microbial resistance profiles closer to the point of care are crucial to minimize the overuse of antimicrobial agents and improve patient outcomes. Although Fourier transform infrared (FTIR) microscopy has shown promise in distinguishing between bacterial species, the high cost and technical requirements of the IR microscope may limit broad clinical use. To address the practical needs of a clinical microbiology laboratory, here, we examine the ability of a lower cost portable benchtop attenuated total reflectance (ATR)-FTIR spectrometer to achieve antimicrobial resistance detection, using a simple, clinically aligned sampling protocol. The technical reproducibility was confirmed through multi-day analysis of an Escherichia coli type strain, which serves as quality control. We generated a dataset of 100 E. coli clinical bloodstream isolates with 63 ceftriaxone resistant blaCTX-M ESBL gene variant strains and developed a classifier for blaCTX-M genotype detection. After assessing 35 machine learning methods using the training set (n = 71), four methods were further optimised, and the best performing method was evaluated using the held-out testing set (n = 29). A tuned support vector machine model with a polynomial kernel, using the 700-1500 cm-1 range achieved a sensitivity of 89.2%, and specificity of 66.7% for detecting blaCTX-M in independent testing, approaching the reported performance of FTIR microscopy. With further algorithm improvement, these data suggest the potential deployment of a portable FTIR spectrometer as a rapid antimicrobial susceptibility prediction platform to enable the efficient use of antimicrobials.

RaftProt V2: understanding membrane microdomain function through lipid raft proteomes.

Cellular membranes feature dynamic submicrometer-scale lateral domains termed lipid rafts, membrane rafts or glycosphingolipid-enriched microdomains (GEM). Numerous proteomics studies have been conducted on the lipid raft proteome, however, interpretation of individual studies is limited by potential undefined contaminant proteins. To enable integrated analyses, we previously developed RaftProt (http://lipid-raft-database.di.uq.edu.au/), a searchable database of mammalian lipid raft-associated proteins. Despite being a highly used resource, further developments in annotation and utilities were required. Here, we present RaftProt V2 (http://raftprot.org), an improved update of RaftProt. Besides the addition of new datasets and re-mapping of all entries to both UniProt and UniRef IDs, we have implemented a stringent annotation based on experimental evidence level to assist in identification of possible contaminant proteins. RaftProt V2 allows for simultaneous search of multiple proteins/experiments at the cell/tissue type and UniRef/Gene level, where correlations, interactions or overlaps can be investigated. The web-interface has been completely re-designed to enable interactive data and subset selection, correlation analysis and network visualization. Overall, RaftProt aims to advance our understanding of lipid raft function through integrative analysis of datasets collected from diverse tissue and conditions. Database URL: http://raftprot.org.

lipidr: A Software Tool for Data Mining and Analysis of Lipidomics Datasets.

The rapid evolution of mass spectrometry (MS)-based lipidomics has enabled the simultaneous measurement of numerous lipid classes. With lipidomics datasets becoming increasingly available, lipidomic-focused software tools are required to facilitate data analysis as well as mining of public datasets, integrating lipidomics-unique molecular information such as lipid class, chain length, and unsaturation. To address this need, we developed lipidr, an open-source R/Bioconductor package for data mining and analysis of lipidomics datasets. lipidr implements a comprehensive lipidomic-focused analysis workflow for targeted and untargeted lipidomics. lipidr imports numerical matrices, Skyline exports, and Metabolomics Workbench files directly into R, automatically inferring lipid class and chain information from lipid names. Through integration with the Metabolomics Workbench API, users can search, download, and reanalyze public lipidomics datasets seamlessly. lipidr allows thorough data inspection, normalization, and uni- and multivariate analyses, displaying results as interactive visualizations. To enable interpretation of lipid class, chain length, and total unsaturation data, we also developed and implemented a novel lipid set enrichment analysis. A companion online guide with two live example datasets is presented at https://www.lipidr.org/. We expect that the ease of use and innovative features of lipidr will allow the lipidomics research community to gain novel detailed insights from lipidomics data.

Antibody-Free Targeted Proteomics Assay for Absolute Measurement of α-Tubulin Acetylation.

Acetylation of α-tubulin at conserved lysine 40 (K40) amino acid residue regulates microtubule dynamics and controls a wide range of cellular activities. Dysregulated microtubule dynamics characterized by differential α-tubulin acetylation is a hallmark of cancer, neurodegeneration, and other complex disorders. Hence, accurate quantitation of α-tubulin acetylation is required in human disease and animal model studies. We developed a novel antibody-free proteomics assay to measure α-tubulin acetylation targeting protease AspN-generated peptides harboring K40 site. Using the synthetic unmodified and acetylated stable isotope labeled peptides DKTIGGG and DKTIGGGD, we demonstrate assay linearity across 4 log magnitude and reproducibility of <10% coefficient of variation. The assay accuracy was validated by titration of 10-80% mixture of acetylated/nonacetylated α-tubulin peptides in the background of human olfactory neurosphere-derived stem (ONS) cell matrix. Furthermore, in agreement with antibody-based high content microscopy analysis, the targeted proteomics assay reported an induction of α-tubulin K40 acetylation upon Trichostatin A stimulation of ONS cells. Independently, we found 35.99% and 16.11% α-tubulin acetylation for mouse spinal cord and brain homogenate tissue, respectively, as measured by our assay. In conclusion, this simple, antibody-free proteomics assay enables quantitation of α-tubulin acetylation, and is applicable across various fields of biology and medicine.

Antibody-Free Multiplex Measurement of 23 Human Cytokines in Primary Cell Culture Secretome Using Targeted Mass Spectrometry.

Cytokines are commonly measured by immunoassays; however, these have limited multiplexing capacity, are costly, and can exhibit cross-reactivity. Multiple reaction monitoring (MRM) mass spectrometry is a robust method to quantify analytes with high specificity and multiplexing ability, hence we aimed to investigate its suitability as an alternative cost-effective method for cytokine measurement. Human keratinocyte conditioned media spiked with recombinant cytokines was used as an experimental system to evaluate sensitivity, linearity, and reproducibility of an MRM assay targeting 79 peptides representing 23 human cytokines. Our MRM method was able to identify 21 cytokines by two or more unique peptides and two cytokines by a single unique peptide. In a serum-free matrix, the median LOD and LOQ for cytokine peptides was 130 and 433 pg/mL, respectively. The presence of serum increased median LOD and LOQ by about 2.3-fold. The assay shows excellent replicate consistency with 8% intra- and 12% interday coefficient of variations. We found high pH reversed-phase fractionation a useful tool to increase assay sensitivity with the drawback of increasing its variability by approximately 10%. Overall, our results suggest utility of a multiplex cytokine MRM for routine measurement of secreted cytokines in cellular experiments under low serum conditions. Additional enrichment steps will be required in high complexity matrices such as serum.

Evaluation of Serum Glycoprotein Biomarker Candidates for Detection of Esophageal Adenocarcinoma and Surveillance of Barrett's Esophagus.

Esophageal adenocarcinoma (EAC) is thought to develop from asymptomatic Barrett's esophagus (BE) with a low annual rate of conversion. Current endoscopy surveillance of BE patients is probably not cost-effective. Previously, we discovered serum glycoprotein biomarker candidates which could discriminate BE patients from EAC. Here, we aimed to validate candidate serum glycoprotein biomarkers in independent cohorts, and to develop a biomarker candidate panel for BE surveillance. Serum glycoprotein biomarker candidates were measured in 301 serum samples collected from Australia (4 states) and the United States (1 clinic) using previously established lectin magnetic bead array (LeMBA) coupled multiple reaction monitoring mass spectrometry (MRM-MS) tier 3 assay. The area under receiver operating characteristic curve (AUROC) was calculated as a measure of discrimination, and multivariate recursive partitioning was used to formulate a multi-marker panel for BE surveillance. Complement C9 (C9), gelsolin (GSN), serum paraoxonase/arylesterase 1 (PON1) and serum paraoxonase/lactonase 3 (PON3) were validated as diagnostic glycoprotein biomarkers in lectin pull-down samples for EAC across both cohorts. A panel of 10 serum glycoprotein biomarker candidates discriminated BE patients not requiring intervention (BE± low grade dysplasia) from those requiring intervention (BE with high grade dysplasia (BE-HGD) or EAC) with an AUROC value of 0.93. Tissue expression of C9 was found to be induced in BE, dysplastic BE and EAC. In longitudinal samples from subjects that have progressed toward EAC, levels of serum C9 were significantly (p < 0.05) increased with disease progression in EPHA (erythroagglutinin from Phaseolus vulgaris) and NPL (Narcissus pseudonarcissus lectin) pull-down samples. The results confirm alteration of complement pathway glycoproteins during BE-EAC pathogenesis. Further prospective clinical validation of the confirmed biomarker candidates in a large cohort is warranted, prior to development of a first-line BE surveillance blood test.

G9a drives hypoxia-mediated gene repression for breast cancer cell survival and tumorigenesis.

G9a is an epigenetic regulator that methylates H3K9, generally causing repression of gene expression, and participates in diverse cellular functions. G9a is genetically deregulated in a variety of tumor types and can silence tumor suppressor genes and, therefore, is important for carcinogenesis. Although hypoxia is recognized to be an adverse factor in tumor growth and metastasis, the role of G9a in regulating gene expression in hypoxia has not been described extensively. Here, we show that G9a protein stability is increased in hypoxia via reduced proline hydroxylation and, hence, inefficient degradation by the proteasome. This inefficiency leads to an increase in H3K9me2 at its target promoters. Blocking the methyltransferase activity of G9a inhibited cellular proliferation and migration in vitro and tumor growth in vivo. Furthermore, an increased level of G9a is a crucial factor in mediating the hypoxic response by down-regulating the expression of specific genes, including ARNTL, CEACAM7, GATA2, HHEX, KLRG1, and OGN This down-regulation can be rescued by a small molecule inhibitor of G9a. Based on the hypothesis that the changes in gene expression would influence patient outcomes, we have developed a prognostic G9a-suppressed gene signature that can stratify breast cancer patients. Together, our findings provide an insight into the role G9a plays as an epigenetic mediator of hypoxic response, which can be used as a diagnostic marker, and proposes G9a as a therapeutic target for solid cancers.

Optimizing Size Exclusion Chromatography for Extracellular Vesicle Enrichment and Proteomic Analysis from Clinically Relevant Samples.

The field of extracellular vesicle (EV) research has rapidly expanded in recent years, with particular interest in their potential as circulating biomarkers. Proteomic analysis of EVs from clinical samples is complicated by the low abundance of EV proteins relative to highly abundant circulating proteins such as albumin and apolipoproteins. To overcome this, size exclusion chromatography (SEC) has been proposed as a method to enrich EVs whilst depleting protein contaminants; however, the optimal SEC parameters for EV proteomics have not been thoroughly investigated. Here, quantitative evaluation and optimization of SEC are reported for separating EVs from contaminating proteins. Using a synthetic model system followed by cell line-derived EVs, it is found that a 10 mL Sepharose 4B column in PBS produces optimal resolution of EVs from background protein. By spiking-in cancer cell-derived EVs to healthy plasma, it is shown that some cancer EV-associated proteins are detectable by nano-LC-MS/MS when as little as 1% of the total plasma EV number are derived from a cancer cell line. These results suggest that an optimized SEC and nanoLC-MS/MS workflow may be sufficiently sensitive for disease EV protein biomarker discovery from patient-derived clinical samples.

Discovery and Qualification of Serum Protein Biomarker Candidates for Cholangiocarcinoma Diagnosis.

Cholangiocarcinoma (CCA) is a major health problem in northeastern Thailand. The majority of CCA cases are clinically silent and difficult to detect at an early stage. Although abdominal ultrasonography (US) can detect premalignant periductal fibrosis (PDF), this method is not suitable for screening populations in remote areas. With the goal of developing a blood test for detecting CCA in the at-risk population, we carried out serum protein biomarker discovery and qualification. Label-free shotgun proteomics was performed on depleted serum samples from 30 participants (n = 10 for US-normal, US-PDF, and CCA groups). Of 40 protein candidates selected using multiple reaction monitoring on 90 additional serum samples (n = 30 per group), 11 discriminatory proteins were obtained using supervised multivariate statistical analysis. We further evaluated 3 candidates using ELISA and immunohistochemistry (IHC). S100A9, thioredoxin (TRX), and cadherin-related family member 2 (CDHR2) were significantly different between CCA and normal, and CCA and PDF groups when measured in an additional 247 serum samples (P < 0.0001). By IHC, TRX and CDHR2 were detected in the cytoplasm and nucleus of CCA and inflammatory cells. S100A9 was detected in the infiltrating tumor stroma immune cells. Proteomics discovery and qualification in depleted sera revealed promising biomarker candidates for CCA diagnosis.

Acute high intensity interval exercise reduces colon cancer cell growth.

KEY POINTS: Physical activity is associated with reduced mortality rates for survivors of colorectal cancer. Acute high intensity interval exercise (HIIE) reduced colon cancer cell number in vitro and promoted increases in inflammatory cytokines immediately following exercise. This acute suppression of colon cancer cell number was transient and not observed at 120 minutes post-acute HIIE. The acute effects of exercise may constitute an important mechanism by which exercise can influence colorectal cancer outcomes. ABSTRACT: Physical activity is associated with significant reductions in colorectal cancer mortality. However, the mechanisms by which exercise mediates this anti-oncogenic effect are not clear. In the present study, colorectal cancer survivors completed acute (n = 10) or chronic (n = 10) exercise regimes. An acute high intensity interval exercise session (HIIE; 4 × 4 min at 85-95% peak heart rate) was completed with serum samples collected at baseline, as well as 0 and 120 min post-exercise. For the 'chronic' intervention, resting serum was sampled before and after 4 weeks (12 sessions) of HIIE. The effect of serum on colon cancer cell growth was evaluated by incubating cells (CaCo-2 and LoVo) for up to 72 h and assessing cell number. Serum obtained immediately following HIIE, but not 120 min post-HIIE, significantly reduced colon cancer cell number. Significant increases in serum interleukin-6 (P = 0.023), interleukin-8 (P = 0.036) and tumour necrosis factor-α (P = 0.003) were found immediately following acute HIIE. At rest, short-term HIIE training did not promote any changes in cellular growth or cytokine concentrations. The acute effects of HIIE and the cytokine flux may be important mediators of reducing colon cancer cell progression. Repetitive exposure to these acute effects may contribute to the relationship between exercise and improved colorectal cancer survival.

Advances and challenges in understanding the role of the lipid raft proteome in human health.

INTRODUCTION: Phase separation as a biophysical principle drives the formation of liquid-ordered 'lipid raft' membrane microdomains in cellular membranes, including organelles. Given the critical role of cellular membranes in both compartmentalization and signaling, clarifying the roles of membrane microdomains and their mutual regulation of/by membrane proteins is important in understanding the fundamentals of biology, and has implications for health. Areas covered: This article will consider the evidence for lateral membrane phase separation in model membranes and organellar membranes, critically evaluate the current methods for lipid raft proteomics and discuss the biomedical implications of lipid rafts. Expert commentary: Lipid raft homeostasis is perturbed in numerous chronic conditions; hence, understanding the precise roles and regulation of the lipid raft proteome is important for health and medicine. The current technical challenges in performing lipid raft proteomics can be overcome through well-controlled experimental design and careful interpretation. Together with technical developments in mass spectrometry and microscopy, our understanding of lipid raft biology and function will improve through recognition of the similarity between organelle and plasma membrane lipid rafts and considered integration of published lipid raft proteomics data.

Endocytic crosstalk: cavins, caveolins, and caveolae regulate clathrin-independent endocytosis.

Several studies have suggested crosstalk between different clathrin-independent endocytic pathways. However, the molecular mechanisms and functional relevance of these interactions are unclear. Caveolins and cavins are crucial components of caveolae, specialized microdomains that also constitute an endocytic route. Here we show that specific caveolar proteins are independently acting negative regulators of clathrin-independent endocytosis. Cavin-1 and Cavin-3, but not Cavin-2 or Cavin-4, are potent inhibitors of the clathrin-independent carriers/GPI-AP enriched early endosomal compartment (CLIC/GEEC) endocytic pathway, in a process independent of caveola formation. Caveolin-1 (CAV1) and CAV3 also inhibit the CLIC/GEEC pathway upon over-expression. Expression of caveolar protein leads to reduction in formation of early CLIC/GEEC carriers, as detected by quantitative electron microscopy analysis. Furthermore, the CLIC/GEEC pathway is upregulated in cells lacking CAV1/Cavin-1 or with reduced expression of Cavin-1 and Cavin-3. Inhibition by caveolins can be mimicked by the isolated caveolin scaffolding domain and is associated with perturbed diffusion of lipid microdomain components, as revealed by fluorescence recovery after photobleaching (FRAP) studies. In the absence of cavins (and caveolae) CAV1 is itself endocytosed preferentially through the CLIC/GEEC pathway, but the pathway loses polarization and sorting attributes with consequences for membrane dynamics and endocytic polarization in migrating cells and adult muscle tissue. We also found that noncaveolar Cavin-1 can act as a modulator for the activity of the key regulator of the CLIC/GEEC pathway, Cdc42. This work provides new insights into the regulation of noncaveolar clathrin-independent endocytosis by specific caveolar proteins, illustrating multiple levels of crosstalk between these pathways. We show for the first time a role for specific cavins in regulating the CLIC/GEEC pathway, provide a new tool to study this pathway, identify caveola-independent functions of the cavins and propose a novel mechanism for inhibition of the CLIC/GEEC pathway by caveolin.

Serum Glycoprotein Biomarker Discovery and Qualification Pipeline Reveals Novel Diagnostic Biomarker Candidates for Esophageal Adenocarcinoma.

We report an integrated pipeline for efficient serum glycoprotein biomarker candidate discovery and qualification that may be used to facilitate cancer diagnosis and management. The discovery phase used semi-automated lectin magnetic bead array (LeMBA)-coupled tandem mass spectrometry with a dedicated data-housing and analysis pipeline; GlycoSelector (http://glycoselector.di.uq.edu.au). The qualification phase used lectin magnetic bead array-multiple reaction monitoring-mass spectrometry incorporating an interactive web-interface, Shiny mixOmics (http://mixomics-projects.di.uq.edu.au/Shiny), for univariate and multivariate statistical analysis. Relative quantitation was performed by referencing to a spiked-in glycoprotein, chicken ovalbumin. We applied this workflow to identify diagnostic biomarkers for esophageal adenocarcinoma (EAC), a life threatening malignancy with poor prognosis in the advanced setting. EAC develops from metaplastic condition Barrett's esophagus (BE). Currently diagnosis and monitoring of at-risk patients is through endoscopy and biopsy, which is expensive and requires hospital admission. Hence there is a clinical need for a noninvasive diagnostic biomarker of EAC. In total 89 patient samples from healthy controls, and patients with BE or EAC were screened in discovery and qualification stages. Of the 246 glycoforms measured in the qualification stage, 40 glycoforms (as measured by lectin affinity) qualified as candidate serum markers. The top candidate for distinguishing healthy from BE patients' group was Narcissus pseudonarcissus lectin (NPL)-reactive Apolipoprotein B-100 (p value = 0.0231; AUROC = 0.71); BE versus EAC, Aleuria aurantia lectin (AAL)-reactive complement component C9 (p value = 0.0001; AUROC = 0.85); healthy versus EAC, Erythroagglutinin Phaseolus vulgaris (EPHA)-reactive gelsolin (p value = 0.0014; AUROC = 0.80). A panel of 8 glycoforms showed an improved AUROC of 0.94 to discriminate EAC from BE. Two biomarker candidates were independently verified by lectin magnetic bead array-immunoblotting, confirming the validity of the relative quantitation approach. Thus, we have identified candidate biomarkers, which, following large-scale clinical evaluation, can be developed into diagnostic blood tests. A key feature of the pipeline is the potential for rapid translation of the candidate biomarkers to lectin-immunoassays.