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.

Accurate, non-destructive, and high-throughput age estimation for Golden perch (Macquaria ambigua spp.) using DNA methylation.

Age structure information of animal populations is fundamental to their conservation and management. In fisheries, age is routinely obtained by counting daily or annual increments in calcified structures (e.g., otoliths) which requires lethal sampling. Recently, DNA methylation has been shown to estimate age using DNA extracted from fin tissue without the need to kill the fish. In this study we used conserved known age-associated sites from the zebrafish (Danio rerio) genome to predict the age of golden perch (Macquaria ambigua), a large-bodied native fish from eastern Australia. Individuals aged using validated otolith techniques from across the species' distribution were used to calibrate three epigenetic clocks. One clock was calibrated using daily (daily clock) and another with annual (annual clock) otolith increment counts, respectively. A third used both daily and annual increments (universal clock). We found a high correlation between the otolith and epigenetic age (Pearson correlation > 0.94) across all clocks. The median absolute error was 2.4 days in the daily clock, 184.6 days in the annual clock, and 74.5 days in the universal clock. Our study demonstrates the emerging utility of epigenetic clocks as non-lethal and high-throughput tools for obtaining age estimates to support the management of fish populations and fisheries.

Genetic Variants Associated with Long-Terminal Repeats Can Diagnostically Classify Cannabis Varieties.

Cannabis sativa (Cannabis) has recently been legalized in multiple countries globally for either its recreational or medicinal use. This, in turn, has led to a marked increase in the number of Cannabis varieties available for use in either market. However, little information currently exists on the genetic distinction between adopted varieties. Such fundamental knowledge is of considerable value and underpins the accelerated development of both a nascent pharmaceutical industry and the commercial recreational market. Therefore, in this study, we sought to assess genetic diversity across 10 Cannabis varieties by undertaking a reduced representation shotgun sequencing approach on 83 individual plants to identify variations which could be used to resolve the genetic structure of the assessed population. Such an approach also allowed for the identification of the genetic features putatively associated with the production of secondary metabolites in Cannabis. Initial analysis identified 3608 variants across the assessed population with phylogenetic analysis of this data subsequently enabling the confident grouping of each variety into distinct subpopulations. Within our dataset, the most diagnostically informative single nucleotide polymorphisms (SNPs) were determined to be associated with the long-terminal repeat (LTRs) class of retroelements, with 172 such SNPs used to fully resolve the genetic structure of the assessed population. These 172 SNPs could be used to design a targeted resequencing panel, which we propose could be used to rapidly screen different Cannabis plants to determine genetic relationships, as well as to provide a more robust, scientific classification of Cannabis varieties as the field moves into the pharmaceutical sphere.

Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality.

BACKGROUND: Prostate cancer is a clinically heterogeneous disease with a subset of patients rapidly progressing to lethal-metastatic prostate cancer. Current clinicopathological measures are imperfect predictors of disease progression. Epigenetic changes are amongst the earliest molecular changes in tumourigenesis. To find new prognostic biomarkers to enable earlier intervention and improved outcomes, we performed methylome sequencing of DNA from patients with localised prostate cancer and long-term clinical follow-up. METHODS: We used whole-genome bisulphite sequencing (WGBS) to comprehensively map and compare DNA methylation of radical prostatectomy tissue between patients with lethal disease (n = 7) and non-lethal (n = 8) disease (median follow-up 19.5 years). Validation of differentially methylated regions (DMRs) was performed in an independent cohort (n = 185, median follow-up 15 years) using targeted multiplex bisulphite sequencing of candidate regions. Survival was assessed via univariable and multivariable analyses including clinicopathological measures (log-rank and Cox regression models). RESULTS: WGBS data analysis identified cancer-specific methylation patterns including CpG island hypermethylation, and hypomethylation of repetitive elements, with increasing disease risk. We identified 1420 DMRs associated with prostate cancer-specific mortality (PCSM), which showed enrichment for gene sets downregulated in prostate cancer and de novo methylated in cancer. Through comparison with public prostate cancer datasets, we refined the DMRs to develop an 18-gene prognostic panel. Applying this panel to an independent cohort, we found significant associations between PCSM and hypermethylation at EPHB3, PARP6, TBX1, MARCH6 and a regulatory element within CACNA2D4. Strikingly in a multivariable model, inclusion of CACNA2D4 methylation was a better predictor of PCSM versus grade alone (Harrell's C-index: 0.779 vs. 0.684). CONCLUSIONS: Our study provides detailed methylome maps of non-lethal and lethal prostate cancer and identifies novel genic regions that distinguish these patient groups. Inclusion of our DNA methylation biomarkers with existing clinicopathological measures improves prognostic models of prostate cancer mortality, and holds promise for clinical application.

Transcriptional comparison of testicular adrenal rest tumors with fetal and adult tissues.

Background: Testicular adrenal rest tumors (TART) are a common complication of unknown cellular origin in patients with congenital adrenal hyperplasia (CAH). These benign tumors have both adrenal and testicular characteristics and are hypothesized to either derive from cells of adrenal origin from the fetal adrenogonadal primordium or by atypical differentiation of adult Leydig-progenitor cells. Objective: This study aims to unravel the identity and etiology of TART. Methods: Co-expression of adrenal-specific CYP11B1 and Leydig cell-specific HSD17B3 in TART was studied using immunohistochemistry. We studied the possibility of TART being derived from atypical differentiation of adult Leydig-progenitor cells by the quantification of adrenal-specific enzyme expression upon adrenocorticotrophic hormone (ACTH)-like stimulation of ex vivo cultured platelet-derived growth factor receptor alpha-positive cells. By comparing the transcriptome of TART (n = 16) with the transcriptome of fetal adrenal (n = 13), fetal testis (n = 5), adult adrenal (n = 11), and adult testis (n = 10) tissues, we explored the identity of TART. Results: We demonstrate co-expression of adrenal-specific CYP11B1 and testis-specific HSD17B3 in TART cells, indicating the existence of a distinct TART cell exhibiting both adrenal and testicular characteristics. Ex vivo cultured adult Leydig-progenitor cells did not express the ACTH-receptor MC2R but did express CYP11B1 upon stimulation. Unsupervised clustering of transcriptome data showed that TART was most similar to adult adrenal tissue, followed by adult testis tissue, and least similar to either fetal tissue. Conclusion: Our data suggest that TART is induced - most likely via activation of a cAMP/protein kinase A-dependent receptor - from a progenitor cell into a unique mature adrenal-like cell type, sometimes exhibiting both adrenal and testicular features.

Modelling clinical DNA fragmentation in the development of universal PCR-based assays for bisulfite-converted, formalin-fixed and cell-free DNA sample analysis.

In fragmented DNA, PCR-based methods quantify the number of intact regions at a specific amplicon length. However, the relationship between the population of DNA fragments within a sample and the likelihood they will amplify has not been fully described. To address this, we have derived a mathematical equation that relates the distribution profile of a stochastically fragmented DNA sample to the probability that a DNA fragment within that sample can be amplified by any PCR assay of arbitrary length. Two panels of multiplex PCR assays for quantifying fragmented DNA were then developed: a four-plex panel that can be applied to any human DNA sample and used to estimate the percentage of regions that are intact at any length; and a two-plex panel optimized for quantifying circulating cell-free DNA (cfDNA). For these assays, regions of the human genome least affected by copy number aberration were identified and selected; within these copy-neutral regions, each PCR assay was designed to amplify both genomic and bisulfite-converted DNA; and all assays were validated for use in both conventional qPCR and droplet-digital PCR. Finally, using the cfDNA-optimized assays we find evidence of universally conserved nucleosome positioning among individuals.

Age prediction of green turtles with an epigenetic clock.

Age is a fundamental life history attribute that is used to understand the dynamics of wild animal populations. Unfortunately, most animals do not have a practical or nonlethal method to determine age. This makes it difficult for wildlife managers to carry out population assessments, particularly for elusive and long-lived fauna such as marine turtles. In this study, we present an epigenetic clock that predicts the age of marine turtles from skin biopsies. The model was developed and validated using DNA from known-age green turtles (Chelonia mydas) from two captive populations, and mark-recapture wild turtles with known time intervals between captures. Our method, based on DNA methylation levels at 18 CpG sites, was highly accurate with a median absolute error of 2.1 years (4.7% of maximum age in data set). This is the first epigenetic clock developed for a reptile and illustrates their broad applicability across a broad variety of vertebrate species. It has the potential to transform marine turtle management through a nonlethal and inexpensive method to provide key life history information.

Next-Generation Molecular Discovery: From Bottom-Up In Vivo and In Vitro Approaches to In Silico Top-Down Approaches for Therapeutics Neogenesis.

Protein and drug engineering comprises a major part of the medical and research industries, and yet approaches to discovering and understanding therapeutic molecular interactions in biological systems rely on trial and error. The general approach to molecular discovery involves screening large libraries of compounds, proteins, or antibodies, or in vivo antibody generation, which could be considered "bottom-up" approaches to therapeutic discovery. In these bottom-up approaches, a minimal amount is known about the therapeutics at the start of the process, but through meticulous and exhaustive laboratory work, the molecule is characterised in detail. In contrast, the advent of "big data" and access to extensive online databases and machine learning technologies offers promising new avenues to understanding molecular interactions. Artificial intelligence (AI) now has the potential to predict protein structure at an unprecedented accuracy using only the genetic sequence. This predictive approach to characterising molecular structure-when accompanied by high-quality experimental data for model training-has the capacity to invert the process of molecular discovery and characterisation. The process has potential to be transformed into a top-down approach, where new molecules can be designed directly based on the structure of a target and the desired function, rather than performing screening of large libraries of molecular variants. This paper will provide a brief evaluation of bottom-up approaches to discovering and characterising biological molecules and will discuss recent advances towards developing top-down approaches and the prospects of this.

Opportunities for Early Cancer Detection: The Rise of ctDNA Methylation-Based Pan-Cancer Screening Technologies.

The efficiency of conventional screening programs to identify early-stage malignancies can be limited by the low number of cancers recommended for screening as well as the high cumulative false-positive rate, and associated iatrogenic burden, resulting from repeated multimodal testing. The opportunity to use minimally invasive liquid biopsy testing to screen asymptomatic individuals at-risk for multiple cancers simultaneously could benefit from the aggregated diseases prevalence and a fixed specificity. Increasing both latter parameters is paramount to mediate high positive predictive value-a useful metric to evaluate a screening test accuracy and its potential harm-benefit. Thus, the use of a single test for multi-cancer early detection (stMCED) has emerged as an appealing strategy for increasing early cancer detection rate efficiency and benefit population health. A recent flurry of these stMCED technologies have been reported for clinical potential; however, their development is facing unique challenges to effectively improve clinical cost-benefit. One promising avenue is the analysis of circulating tumour DNA (ctDNA) for detecting DNA methylation biomarker fingerprints of malignancies-a hallmark of disease aetiology and progression holding the potential to be tissue- and cancer-type specific. Utilizing panels of epigenetic biomarkers could potentially help to detect earlier stages of malignancies as well as identify a tumour of origin from blood testing, useful information for follow-up clinical decision making and subsequent patient care improvement. Overall, this review collates the latest and most promising stMCED methodologies, summarizes their clinical performances, and discusses the specific requirements multi-cancer tests should meet to be successfully implemented into screening guidelines.

Multiplex PCR Design for Scalable Resequencing.

While conventional PCR applications typically focus on a single PCR assay per reaction, multiplex PCR applications are a convenient and scalable solution becoming more routine. Multiplex methods can be applied to virtually any DNA template source (e.g., plant or human DNA, FFPE DNA isolated from clinical samples, bisulfite-converted DNA for DNA methylation analysis), and offers a cheap, convenient, and scalable solution for experiments that require characterization and analysis of multiple genomic regions.This method will detail the procedures to successfully design, screen, and prepare multiplex amplicon libraries; as well as supporting instructions on how to prepare these libraries for sequencing on Illumina, Ion Torrent, and Oxford Nanopore platforms. The flexibility of assay design allows means that custom multiplex panels can range in size from two assays up to a few hundred amplicons or more. Notably, the method described here is also amenable to whatever PCR buffer system the user prefers to use, making the system globally adaptable to the needs and preferences of the end user.

Dynamic Monitoring of EMT in CTCs as an Indicator of Cancer Metastasis.

Epithelial to mesenchymal transition (EMT) results in the genesis of circulating tumor cells (CTCs) from tumor sites and promotes the metastatic capability of CTCs in circulation. In this study, we develop a multiplex surface-enhanced Raman scattering nanotechnology for comprehensive characterization of EMT-associated phenotypes in CTCs, to monitor cancer metastasis. We observe the downregulation of the CTC marker (EpCAM) and the epithelial marker (E-cadherin), as well as the upregulation of a mesenchymal marker (N-cadherin) and a stem cell marker (ABCB5) during the transforming growth factor-ß-induced EMT process in breast cancer cell line models. Additionally, we also find changes in the heterogeneity levels of these selected markers in cells. With this method, we successfully detect the presence of disease in samples from breast cancer patients and characterize EMT-associated phenotypes in their CTCs. Overall, this approach and findings provide a new means for monitoring the EMT process in cancer, insights into the detailed mechanistic progress of the diseases, and have potential for detecting the early occurrence of cancer metastasis.

Nonlethal age estimation of three threatened fish species using DNA methylation: Australian lungfish, Murray cod and Mary River cod.

Age-based demography is fundamental to management of wild fish populations. Age estimates for individuals can determine rates of change in key life-history parameters such as length, maturity, mortality and fecundity. These age-based characteristics are critical for population viability analysis in endangered species and for developing sustainable harvest strategies. For teleost fish, age has traditionally been determined by counting increments formed in calcified structures such as otoliths. However, the collection of otoliths is lethal and therefore undesirable for threatened species. At a molecular level, age can be predicted by measuring DNA methylation. Here, we use previously identified age-associated sites of DNA methylation in zebrafish (Danio rerio) to develop two epigenetic clocks for three threatened freshwater fish species. One epigenetic clock was developed for the Australian lungfish (Neoceratodus forsteri) and the second for the Murray cod (Maccullochella peelii) and Mary River cod (Maccullochella mariensis). Age estimation models were calibrated using either known-age individuals, ages derived from otoliths or bomb radiocarbon dating of scales. We demonstrate a high Pearson's correlation between the chronological and predicted age in both the Lungfish clock (cor = .98) and Maccullochella clock (cor = .92). The median absolute error rate for both epigenetic clocks was also low (Lungfish = 0.86 years; Maccullochella = 0.34 years). This study demonstrates the transferability of DNA methylation sites for age prediction between highly phylogenetically divergent fish species. Given the method is nonlethal and suited to automation, age prediction by DNA methylation has the potential to improve fisheries and other wildlife management settings.

Network mapping of primary CD34+ cells by Ampliseq based whole transcriptome targeted resequencing identifies unexplored differentiation regulatory relationships.

With the exception of a few master transcription factors, regulators of neutrophil maturation are poorly annotated in the intermediate phenotypes between the granulocyte-macrophage progenitor (GMP) and the mature neutrophil phenotype. Additional challenges in identifying gene expression regulators in differentiation pathways relate to challenges wherein starting cell populations are heterogeneous in lineage potential and development, are spread across various states of quiescence, as well as sample quality and input limitations. These factors contribute to data variability make it difficult to draw simple regulatory inferences. In response we have applied a multi-omics approach using primary blood progenitor cells primed for homogeneous proliferation and granulocyte differentiation states which combines whole transcriptome resequencing (Ampliseq RNA) supported by droplet digital PCR (ddPCR) validation and mass spectrometry-based proteomics in a hypothesis-generation study of neutrophil differentiation pathways. Primary CD34+ cells isolated from human cord blood were first precultured in non-lineage driving medium to achieve an active, proliferating phenotype from which a neutrophil primed progenitor was isolated and cultured in neutrophil lineage supportive medium. Samples were then taken at 24-hour intervals over 9 days and analysed by Ampliseq RNA and mass spectrometry. The Ampliseq dataset depth, breadth and quality allowed for several unexplored transcriptional regulators and ncRNAs to be identified using a combinatorial approach of hierarchical clustering, enriched transcription factor binding motifs, and network mapping. Network mapping in particular increased comprehension of neutrophil differentiation regulatory relationships by implicating ARNT, NHLH1, PLAG1, and 6 non-coding RNAs associated with PU.1 regulation as cell-engineering targets with the potential to increase total neutrophil culture output. Overall, this study develops and demonstrates an effective new hypothesis generation methodology for transcriptome profiling during differentiation, thereby enabling identification of novel gene targets for editing interventions.

A DNA methylation age predictor for zebrafish.

Changes in DNA methylation at specific CpG sites have been used to build predictive models to estimate animal age, predominantly in mammals. Little testing for this effect has been conducted in other vertebrate groups, such as bony fish, the largest vertebrate class. The development of most age-predictive models has relied on a genome-wide sequencing method to obtain a DNA methylation level, which makes it costly to deploy as an assay to estimate age in many samples. Here, we have generated a reduced representation bisulfite sequencing data set of caudal fin tissue from a model fish species, zebrafish (Danio rerio), aged from 11.9-60.1 weeks. We identified changes in methylation at specific CpG sites that correlated strongly with increasing age. Using an optimised unique set of 26 CpG sites we developed a multiplex PCR assay that predicts age with an average median absolute error rate of 3.2 weeks in zebrafish between 10.9-78.1 weeks of age. We also demonstrate the use of multiplex PCR as an efficient quantitative approach to measure DNA methylation for the use of age estimation. This study highlights the potential further use of DNA methylation as an age estimation method in non-mammalian vertebrate species.

Regulation of Canonical Oncogenic Signaling Pathways in Cancer via DNA Methylation.

Disruption of signaling pathways that plays a role in the normal development and cellular homeostasis may lead to the dysregulation of cellular signaling and bring about the onset of different diseases, including cancer. In addition to genetic aberrations, DNA methylation also acts as an epigenetic modifier to drive the onset and progression of cancer by mediating the reversible transcription of related genes. Although the role of DNA methylation as an alternative driver of carcinogenesis has been well-established, the global effects of DNA methylation on oncogenic signaling pathways and the presentation of cancer is only emerging. In this article, we introduced a differential methylation parsing pipeline (MethylMine) which mined for epigenetic biomarkers based on feature selection. This pipeline was used to mine for biomarkers, which presented a substantial difference in methylation between the tumor and the matching normal tissue samples. Combined with the Data Integration Analysis for Biomarker discovery (DIABLO) framework for machine learning and multi-omic analysis, we revisited the TCGA DNA methylation and RNA-Seq datasets for breast, colorectal, lung, and prostate cancer, and identified differentially methylated genes within the NRF2-KEAP1/PI3K oncogenic pathway, which regulates the expression of cytoprotective genes, that serve as potential therapeutic targets to treat different cancers.

Comprehensive evaluation of targeted multiplex bisulphite PCR sequencing for validation of DNA methylation biomarker panels.

BACKGROUND: DNA methylation is a well-studied epigenetic mark that is frequently altered in diseases such as cancer, where specific changes are known to reflect the type and severity of the disease. Therefore, there is a growing interest in assessing the clinical utility of DNA methylation as a biomarker for diagnosing disease and guiding treatment. The development of an accurate loci-specific methylation assay, suitable for use on low-input clinical material, is crucial for advancing DNA methylation biomarkers into a clinical setting. A targeted multiplex bisulphite PCR sequencing approach meets these needs by allowing multiple DNA methylated regions to be interrogated simultaneously in one experiment on limited clinical material. RESULTS: Here, we provide an updated protocol and recommendations for multiplex bisulphite PCR sequencing (MBPS) assays for target DNA methylation analysis. We describe additional steps to improve performance and reliability: (1) pre-sequencing PCR optimisation which includes assessing the optimal PCR cycling temperature and primer concentration and (2) post-sequencing PCR optimisation to achieve uniform coverage of each amplicon. We use a gradient of methylated controls to demonstrate how PCR bias can be assessed and corrected. Methylated controls also allow assessment of the sensitivity of methylation detection for each amplicon. Here, we show that the MBPS assay can amplify as little as 0.625 ng starting DNA and can detect methylation differences of 1% with a sequencing coverage of 1000 reads. Furthermore, the multiplex bisulphite PCR assay can comprehensively interrogate multiple regions on 1-5 ng of formalin-fixed paraffin-embedded DNA or circulating cell-free DNA. CONCLUSIONS: The MBPS assay is a valuable approach for assessing methylated DNA regions in clinical samples with limited material. The optimisation and additional quality control steps described here improve the performance and reliability of this method, advancing it towards potential clinical applications in biomarker studies.

Retooling phage display with electrohydrodynamic nanomixing and nanopore sequencing.

Phage display methodologies offer a versatile platform for the isolation of single-chain Fv (scFv) molecules which may be rebuilt into monoclonal antibodies. Herein, we report on a complete workflow termed PhageXpress, for rapid selection of single-chain Fv sequences by leveraging electrohydrodynamic-manipulation of a solution containing phage library particles to enhance target binding whilst minimizing non-specific interactions. Our PhageXpress technique is combined with Oxford Nanopore Technologies' MinION sequencer and custom bioinformatics to achieve high-throughput screening of phage libraries. We performed 4 rounds of biopanning against Dengue virus (DENV) non-structural protein 1 (NS1) using traditional methods (4 week turnaround), which resulted in the isolation of 19 unique scFv clones. We validated the feasibility and efficiency of the PhageXpress method utilizing the same phage library and antigen target. Notably, we successfully mapped 14 of the 19 anti-NS1 scFv sequences (∼74%) with our new method, despite using ∼30-fold less particles during screening and conducting only a single round of biopanning. We believe this approach supersedes traditional methods for the discovery of bio-recognition molecules such as antibodies by speeding up the process for the development of therapeutic and diagnostic biologics.

PrimerROC: accurate condition-independent dimer prediction using ROC analysis.

To-date systematic testing and comparison of the accuracy of available primer-dimer prediction software has never been conducted, due in part to a lack of tools able to measure the efficacy of Gibbs free energy (ΔG) calculations at predicting dimer formation in PCR. To address this we have developed a novel online tool called PrimerROC ( www.primer-dimer.com/roc/ ), which uses epidemiologically-based Receiver Operating Characteristic (ROC) curves to assess dimer prediction accuracy. Moreover, by integrating PrimerROC with our PrimerDimer prediction software we can determine a ΔG-based dimer-free threshold above which dimer formation is predicted unlikely to occur. Notably, PrimerROC determines this cut-off without any additional information such as salt concentration or annealing temperature, meaning that our PrimerROC method is an assay and condition independent prediction tool. To demonstrate the broad utility of PrimerROC we assessed the performance of seven publically available primer design and dimer analysis tools using a dataset of over 300 primer pairs. We found that our PrimerROC/PrimerDimer software consistently outperforms these other tools and can achieve predictive accuracies greater than 92%. To illustrate its predictive power this method was used in multiplex PCR design to successfully generate four resequencing assays containing up to 126 primers with no observable primer-primer amplification artefacts.

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.

A SERS microfluidic platform for targeting multiple soluble immune checkpoints.

Immune checkpoint blockade therapies are promising next generation immunotherapeutic treatments for cancer. Whilst sequential solid biopsies are an invaluable source of prognostic information, they are not feasible for monitoring therapeutic outcomes over time. Monitoring soluble immune checkpoint markers expression in body fluids could potentially be a better alternative. Current methods (e.g. ELISA) for detecting immune-checkpoint proteins mostly rely on the use of monoclonal antibodies which are expensive and time-consuming to manufacture and isolate. Herein, we report an integrated surface enhanced Raman scattering (SERS)-microfluidics device for the detection of immune checkpoint proteins which involves the use of i) nano yeast single chain variable fragment (scFv) as a promising alternative to monoclonal antibodies providing high stability at relative low-cost and simplicity for production, ii) graphene oxide functionalised surface to reduces the bio functionalization steps, thus avoiding the general paradigm of biotin-streptavidin chemistry and iii) a microfluidic platform enabling alternating current electrohydrodynamics (ac-EHD) induced nanomixing to enhance the target scFv binding and minimize the non-specific interactions. Specific and multiplex detection of immune checkpoint biomarkers is achieved by SERS based spectral encoding. Using this platform, we successfully demonstrated the detection of clinically relevant soluble immune checkpoints PD-1, PD-L1 and LAG-3 from as low as 100 fg/mL of analytes spiked in human serum.