Cross-platform Comparisons Research Articles

BIOM-22. SPATIAL, SINGLE-CELL, AND BULK RNA SEQUENCING IDENTIFY MOLECULAR PROGRAMS UNDERLYING MENINGIOMA BRAIN INVASION

Abstract Brain invasion is a negative prognostic factor for meningiomas, but the molecular programs underlying meningioma brain invasion are poorly understood. To address this, we performed transcriptomic analyses of 3 independent datasets: Bulk RNA sequencing from 199 meningiomas (n=33 with brain invasion), single-cell RNA sequencing of 2 regionally distinct samples from the brain tumor interface (BTI) versus tumor core (TC) (n=22,118 single-cell transcriptomes), and spatial RNA sequencing from 6 samples with (n=4) versus without (n=2) brain invasion (n=18,471 spatial transcriptomes). Single-cell and spatial datasets were integrated with Harmony, cell interactions were defined using CellChat, and cross-platform comparisons were performed with the Seurat data integration pipeline. Bulk RNA sequencing revealed enrichment of 1835 genes in meningiomas with brain invasion compared to those without brain invasion, including glial markers (GFAP, NCAN) and markers of extracellular matrix remodeling (PDGFRA, COL9A1). Single-cell RNA sequencing comparison of BTI versus TC meningioma cells identified 2793 genes that were enriched in BTI cells, 268 of which were conserved across bulk and single-cell transcriptomes from brain-invasive meningiomas. Gene ontology enrichment analysis showed molecular programs underlying cell migration and regulation of neurogenesis at the BTI, while glycolysis and antigen presentation programs were enriched in the TC. Cholesterol, CSPG4, and LIF signaling were active in the TC, while SLIT signaling was enriched at the BTI. Spatial RNA sequencing showed enrichment of 439 genes at the BTI, and a conserved set of 12 genes were enriched in BTI meningioma cells across bulk, single-cell, and spatial datasets (TGM2, APOC1, IGFBP6, PLEKHO1, GFPT2, ZYX, IQGAP3, LUM, S100A11, ARPC1B, CDK1, CYCS). Comparison of tumor microenvironment monocytes at the BTI versus TC demonstrated enrichment of 1571 genes that were associated with macrophage migration and activation. These data elucidate molecular programs underlying meningioma brain invasion and provide insights into meningioma intratumor heterogeneity.

Enhanced repetition codes for the cross-platform comparison of progress towards fault-tolerance

Achieving fault-tolerance will require a strong relationship between the hardware and the protocols used. Different approaches will therefore naturally have tailored proof-of-principle experiments to benchmark progress. Nevertheless, repetition codes have become a commonly used basis of experiments that allow cross-platform comparisons. Here we propose methods by which repetition code experiments can be expanded and improved, while retaining cross-platform compatibility. We also consider novel methods of analyzing the results, which offer more detailed insights than simple calculation of the logical error rate.

MicroBundlePillarTrack: A Python package for automated segmentation, tracking, and analysis of pillar deflection in cardiac microbundles.

Movies of human induced pluripotent stem cell (hiPSC)-derived engineered cardiac tissue (microbundles) contain abundant information about structural and functional maturity. However, extracting these data in a reproducible and high-throughput manner remains a major challenge. Furthermore, it is not straightforward to make direct quantitative comparisons across the multiple in vitro experimental platforms employed to fabricate these tissues. Here, we present "MicroBundlePillarTrack," an open-source optical flow-based package developed in Python to track the deflection of pillars in cardiac microbundles grown on experimental platforms with two different pillar designs ("Type 1" and "Type 2" design). Our software is able to automatically segment the pillars, track their displacements, and output time-dependent metrics for contractility analysis, including beating amplitude and rate, contractile force, and tissue stress. Because this software is fully automated, it will allow for both faster and more reproducible analyses of larger datasets and it will enable more reliable cross-platform comparisons as compared to existing approaches that require manual steps and are tailored to a specific experimental platform. To complement this open-source software, we share a dataset of 1,540 brightfield example movies on which we have tested our software. Through sharing this data and software, our goal is to directly enable quantitative comparisons across labs, and facilitate future collective progress via the biomedical engineering open-source data and software ecosystem.

Quantitative flow cytometry enables end-to-end optimization of cross-platform extracellular vesicle studies

Flow cytometry (FCM) is a common method for characterizing extracellular particles (EPs), including viruses and extracellular vesicles (EVs). Frameworks such as MIFlowCyt-EV exist to provide reporting guidelines for metadata, controls, and data reporting. However, tools to optimize FCM for EP analysis in a systematic and quantitative way are lacking. Here, we demonstrate a cohesive set of methods and software tools that optimize FCM settings and facilitate cross-platform comparisons for EP studies. We introduce an automated small-particle optimization (SPOT) pipeline to optimize FCM fluorescence and light scatter detector settings for EP analysis and leverage quantitative FCM (qFCM) as a tool to further enable FCM optimization of fluorophore panel selection, laser power, pulse statistics, and window extensions. Finally, we demonstrate the value of qFCM to facilitate standardized cross-platform comparisons, irrespective of instrument configuration, settings, and sensitivity, in a cross-platform standardization study utilizing a commercially available EV reference material.

A SOR Model Study on Millennial Parents in Quezon City: E-store Image, Shopping Value, and Purchase Intention

This study investigated the factors affecting the perceived shopping value and online purchase intentions of Filipino millennial parents in Quezon City, specifically in the context of e-stores selling baby and child-specific products. Using the Stimulus-Organism-Response model, the researcher used a causal research design to explore the relationships among e-store image attributes, perceived shopping value, and online purchasing intentions. The research utilized an adapted survey questionnaire administered to the respondents through a Google Form. The 400 participants, chosen through purposive sampling, were Filipino millennial parents with prior experience shopping at baby and child-specific specialty e-stores. Findings revealed that only security images significantly affected utility value, while design, order fulfillment, customer service, and security images significantly affected hedonic value. Also, a hedonic value significantly affected online purchase intention and mediated the relationship between e-store image and purchase intention. Four variables design, order fulfillment, customer service, and security had a direct positive relationship with online purchase intent. Thus, the study concluded that specific factors of e-store image significantly affect Filipino millennial parents’ shopping values and influence their online purchasing intentions. The study’s findings contribute to an underexplored area in the literature by emphasizing the unique context of Filipino millennial parents. It provides valuable insights for e-commerce targeting this demographic. It offers recommendations on practices and further research, such as a deeper exploration of hedonic value’s influence on purchase intention and cross-platform comparisons, which were also provided.

Whole-genome resequencing-based characterization of a durum wheat landrace showing similarity to 'Senatore Cappelli'.

Durum wheat (Triticum turgidum spp. durum) is a major cereal adopted since antiquity to feed humans. Due to its use, dating back several millennia, this species features a wide genetic diversity and landraces are considered important repositories of gene pools which constitute invaluable tools for breeders. The aim of this work is to provide a first characterization of a wheat landrace, referred to as 'TB2018', that was collected in the Apulia region (Southern Italy). 'TB2018' revealed, through visual inspection, characters reminiscent of the traditional variety 'Senatore Cappelli', while exhibiting a distinctive trait, i.e., reduced stature. Indeed, the comparison with a set of Italian durum wheat cultivars conducted in this study, in which 24 CPVO plant descriptors were adopted, placed the 'TB2018' landrace in proximity to the 'Senatore Cappelli' cultivar. In addition, the close similarity between the two genotypes was confirmed by the analysis of the seed protein pattern. A relative reduction was detected for 'TB2018' root elongation in the early stages of plant growth. The 'TB2018' genome sequence, obtained through low-coverage resequencing and comparison to the reference 'Svevo' cultivar is also reported in this study, followed by a genome-wide comparison against 259 durum wheat accessions that placed 'TB2018' close to the 'Cappelli' reference. Hundreds of genes putatively affected by variants that possess Gene Ontology descriptors were detected, among which some were shown to be putatively linked to the morphological traits that distinguish 'TB2018' from 'Senatore Cappelli', Overall, this study poses the basis for a possible exploitation of 'TB2018' per se in cultivation or as a source of alternative alleles in the breeding of traditional cultivars. This work also presents a genomic methodology that exploits the information contained in a low-depth, whole-genome sequence to derive genotypic data useful for cross-platform (chip data) comparisons.

Cross-platform comparisons for targeted bisulfite sequencing of MGISEQ-2000 and NovaSeq6000

BackgroundAn accurate and reproducible next-generation sequencing platform is essential to identify malignancy-related abnormal DNA methylation changes and translate them into clinical applications including cancer detection, prognosis, and surveillance. However, high-quality DNA methylation sequencing has been challenging because poor sequence diversity of the bisulfite-converted libraries severely impairs sequencing quality and yield. In this study, we tested MGISEQ-2000 Sequencer’s capability of DNA methylation sequencing with a published non-invasive pancreatic cancer detection assay, using NovaSeq6000 as the benchmark.ResultsWe sequenced a series of synthetic cell-free DNA (cfDNA) samples with different tumor fractions and found MGISEQ-2000 yielded data with similar quality as NovaSeq6000. The methylation levels measured by MGISEQ-2000 demonstrated high consistency with NovaSeq6000. Moreover, MGISEQ-2000 showed a comparable analytic sensitivity with NovaSeq6000, suggesting its potential for clinical detection. As to evaluate the clinical performance of MGISEQ-2000, we sequenced 24 clinical samples and predicted the pathology of the samples with a clinical diagnosis model, PDACatch classifier. The clinical model performance of MGISEQ-2000’s data was highly consistent with that of NovaSeq6000’s data, with the area under the curve of 1. We also tested the model’s robustness with MGISEQ-2000’s data when reducing the sequencing depth. The results showed that MGISEQ-2000’s data showed matching robustness of the PDACatch classifier with NovaSeq6000’s data.ConclusionsTaken together, MGISEQ-2000 demonstrated similar data quality, consistency of the methylation levels, comparable analytic sensitivity, and matching clinical performance, supporting its application in future non-invasive early cancer detection investigations by detecting distinct methylation patterns of cfDNAs.

A Holistic 4D Approach to Optimize Intrinsic and Extrinsic Factors Contributing to Variability in Microarray Biosensing in Glycomics

Protein–carbohydrate interactions happen to be a crucial facet of biology, discharging a myriad of functions. Microarrays have become a premier choice to discern the selectivity, sensitivity and breadth of these interactions in a high-throughput manner. The precise recognition of target glycan ligands among the plethora of others is central for any glycan-targeting probe being tested by microarray analyses. Ever since the introduction of the microarray as an elemental tool for high-throughput glycoprofiling, numerous distinct array platforms possessing different customizations and assemblies have been developed. Accompanying these customizations are various factors ushering variances across array platforms. In this primer, we investigate the influence of various extrinsic factors, namely printing parameters, incubation procedures, analyses and array storage conditions on the protein–carbohydrate interactions and evaluate these factors for the optimal performance of microarray glycomics analysis. We hereby propose a 4D approach (Design–Dispense–Detect–Deduce) to minimize the effect of these extrinsic factors on glycomics microarray analyses and thereby streamline cross-platform analyses and comparisons. This work will aid in optimizing microarray analyses for glycomics, minimize cross-platform disparities and bolster the further development of this technology.

Cross-platform comparison of immune signatures in immunotherapy-treated patients with advanced melanoma using a rank-based scoring approach

BackgroundGene expression profiling is increasingly being utilised as a diagnostic, prognostic and predictive tool for managing cancer patients. Single-sample scoring approach has been developed to alleviate instability of signature scores due to variations from sample composition. However, it is a challenge to achieve comparable signature scores across different expressional platforms.MethodsThe pre-treatment biopsies from a total of 158 patients, who have received single-agent anti-PD-1 (n = 84) or anti-PD-1 + anti-CTLA-4 therapy (n = 74), were performed using NanoString PanCancer IO360 Panel. Multiple immune-related signature scores were measured from a single-sample rank-based scoring approach, singscore. We assessed the reproducibility and the performance in reporting immune profile of singscore based on NanoString assay in advance melanoma. To conduct cross-platform analyses, singscores between the immune profiles of NanoString assay and the previous orthogonal whole transcriptome sequencing (WTS) data were compared through linear regression and cross-platform prediction.Resultssingscore-derived signature scores reported significantly high scores in responders in multiple PD-1, MHC-1-, CD8 T-cell-, antigen presentation-, cytokine- and chemokine-related signatures. We found that singscore provided stable and reproducible signature scores among the repeats in different batches and cross-sample normalisations. The cross-platform comparisons confirmed that singscores derived via NanoString and WTS were comparable. When singscore of WTS generated by the overlapping genes to the NanoString gene set, the signatures generated highly correlated cross-platform scores (Spearman correlation interquartile range (IQR) [0.88, 0.92] and r2 IQR [0.77, 0.81]) and better prediction on cross-platform response (AUC = 86.3%). The model suggested that Tumour Inflammation Signature (TIS) and Personalised Immunotherapy Platform (PIP) PD-1 are informative signatures for predicting immunotherapy-response outcomes in advanced melanoma patients treated with anti-PD-1-based therapies.ConclusionsOverall, the outcome of this study confirms that singscore based on NanoString data is a feasible approach to produce reliable signature scores for determining patients’ immune profiles and the potential clinical utility in biomarker implementation, as well as to conduct cross-platform comparisons, such as WTS.

Cell type matching in single-cell RNA-sequencing data using FR-Match

Reference cell atlases powered by single cell and spatial transcriptomics technologies are becoming available to study healthy and diseased tissue at single cell resolution. One important use of these data resources is to compare cell types from new dataset with cell types in the reference atlases to evaluate their phenotypic similarities and differences, for example, for identifying novel cell types under disease conditions. For this purpose, rigorously-validated computational algorithms are needed to perform these cell type matching tasks that can compare datasets from different experiment platforms and sample types. Here, we present significant enhancements to FR-Match (v2.0)—a multivariate nonparametric statistical testing approach for matching cell types in query datasets to reference atlases. FR-Match v2.0 includes a normalization procedure to facilitate cross-platform cluster-level comparisons (e.g., plate-based SMART-seq and droplet-based 10X Chromium single cell and single nucleus RNA-seq and spatial transcriptomics) and extends the pipeline to also allow cell-level matching. In the use cases evaluated, FR-Match showed robust and accurate performance for identifying common and novel cell types across tissue regions, for discovering sub-optimally clustered cell types, and for cross-platform and cross-sample cell type matching.

Abstract 6201: Cross-platform comparisons for DNA methylation sequencing

Abstract Introduction: Accurate, reproducible, and cost-effective NGS platform is essential to identify malignancy-related abnormal DNA methylation changes and translate them into clinical applications including cancer detection, prognosis, and surveillance. In this study we evaluated the performances by the MGISEQ-2000 sequencer in DNA methylation sequencing, using Illumina’s NovaSeq6000 as a benchmark. Materials and Methods: We performed both genome-wide methylation profiling and targeted methylation sequencing on reference DNA and clinical DNA samples. To minimize non-platform discrepancies, we prepared 2 libraries, one for NovaSeq600 and the other for MGISEQ-2000, from each DNA sample using the same experimental protocol except the last step, when we used indexed primers whose sequences and chemical modification are compatible with either NovaSeq600 or MGISEQ-2000 to amplify the corresponding library. We conducted standardized analyses on MGISEQ-2000’s reads quality, sequence bias, genome alignment and coverage, regional depth, limits of detection (LOD), etc. We compared methylation levels at CpG sites, and measurements of methylation haplotypes to assess the consistency in mapping and quantifying genome-wide and regional methylation by MGISEQ-2000 and between the 2 platforms. Furthermore, we analyzed inter-platform variations in classifying normal and malignant plasma DNA samples using targeted methylation sequencing data from either platform exclusively. Results: We prepared and sequenced libraries from over 100 DNA samples of normal or malignant tissue or blood samples for comparison, in addition to reference DNA. Overall, MGISEQ-2000 displayed high level of consistency, and little-to-no sequence bias in methylation sequencing. At genome-wide, regional, and individual-CpG levels, MGISEQ-2000 demonstrated high degree of concordance with NovaSeq6000 in quantifying DNA methylation, as the inter-platform Pearson correlation coefficients were consistently above 0.90 or higher for both targeted sequencing and whole-genome bisulfite sequencing, regardless of whether average methylation level (AMF) or methylation haplotype-specific metrics such as Methylation Haplotype Load (MHL) were used to quantify methylation. Additionally, MGISEQ-2000 is as sensitive as NovaSeq6000 at detecting spik-in methylation controls, as both reached an LOD of 0.1%. Lastly, MGISEQ-2000 produced similar results in classifying normal and malignant samples as NovaSeq6000, suggesting it had minimal distortion on the NovaSeq6000-based classifier. Conclusions: MGISEQ-2000 demonstrated comparable data quality, methylation-calling accuracy, and consistency as NovaSeq6000 in DNA methylation sequencing, supporting its application in future investigation on DNA methylation as cancer biomarkers. Citation Format: Mingyang Su, Jin Sun, Jianhua Ma, Jun Xia, Chengcheng Ma, Wei Li, Zhixi Su, Qiye He, Rui Liu. Cross-platform comparisons for DNA methylation sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6201.

Cross-platform transcriptomic profiling of the response to recombinant human erythropoietin

RNA-seq has matured and become an important tool for studying RNA biology. Here we compared two RNA-seq (MGI DNBSEQ and Illumina NextSeq 500) and two microarray platforms (GeneChip Human Transcriptome Array 2.0 and Illumina Expression BeadChip) in healthy individuals administered recombinant human erythropoietin for transcriptome-wide quantification of differential gene expression. The results show that total RNA DNB-seq generated a multitude of target genes compared to other platforms. Pathway enrichment analyses revealed genes correlate to not only erythropoiesis and oxygen transport but also a wide range of other functions, such as tissue protection and immune regulation. This study provides a knowledge base of genes relevant to EPO biology through cross-platform comparisons and validation.

Single-Cell Transcriptome Analysis of Embryonic Erythro-Myeloid Progenitor Cells Reveals Lineage Heterogeneity

The paradigm that multipotential hematopoietic stem cells (HSC) differentiate through a hierarchical series of increasingly specified progenitors has recently been challenged by single cell transcriptome analyses, which suggest greater heterogeneity in progenitor populations and hierarchy than previously thought. These studies are complicated by the wide variety of hematopoietic progenitors at different stages of maturation concurrently present in the adult bone marrow. In the early mammalian embryo, unique hematopoietic progenitors arise prior to, and independently of, HSC. These include erythro-myeloid progenitors (EMP) that arise from hemogenic endothelium in the yolk sac and migrate to the fetal liver to jump-start definitive hematopoiesis before HSC emerge. In vitro, EMP can generate definitive erythroid, megakaryocyte and myeloid cells, although not B-cells, and include at least some single cells with both erythroid and myeloid potential (McGrath et al. 2015 Cell Rep. 11:1892). We have previously shown that day 9.5 (E9.5) murine EMP have a unique and uniform (kit+CD41+CD16/32+) immunophenotype in the yolk sac and circulation, which is maintained as they colonize the E10.5 liver. We performed single-cell transcriptome analysis of this apparently poised, embryonic-specific multi-potential hematopoietic progenitor population, asking whether it contains an underlying heterogeneity or intrinsic lineage hierarchy. High quality data, as assessed by transcriptomic complexity, read depth, and alignment distributions, were generated for 133 single-cell EMP (scEMP) derived from E9.5 mouse embryos. Use both of supervised and of semi-supervised analytical approaches uncovered transcriptome heterogeneity that allowed clustering of scEMP by expression patterns. Based on expression of known lineage-directing transcription factors and cell type enrichment analysis, clusters of cells were identified that could be annotated as multipotential hematopoietic, megakaryocyte/erythroid, myeloid, and a more specific macrophage lineage potential. A novel binary reduction data integration and transformation methods was developed and utilized to further refine and characterize single-cell classifications by facilitating cross platform comparisons with single cell RNA-seq data obtained from EMP progeny in E11.5 liver and with published gene expression datasets derived from adult hematopoietic progenitors and fetal macrophage populations. Predictions of lineage potential based on our analytical approaches were tested by sorting cells based on immunophenotypic markers differentially expressed in specific clusters and analyzing their potential using single cell colony-forming assays. These functional studies support the concept that immunophenotypically homogeneous EMP contain subpopulations of multipotential progenitors differentiating into erythro-megakaryocyte, myeloid, and macrophage-specific lineage fates. DisclosuresNo relevant conflicts of interest to declare.

Detections of Whale Vocalizations by Simultaneously Deployed Bottom-Moored and Deep-Water Mobile Autonomous Hydrophones

Advances in mobile autonomous platforms for oceanographic sensing, including gliders and deep-water profiling floats, have provided new opportunities for passive acoustic monitoring (PAM) of cetaceans. However, there are few direct comparisons of these mobile autonomous systems to more traditional methods, such as stationary bottom-moored recorders. Cross-platform comparisons are necessary to enable interpretation of results across historical and contemporary surveys that use different recorder types, and to identify potential biases introduced by the platform. Understanding tradeoffs across recording platforms informs best practices for future cetacean monitoring efforts. This study directly compares the PAM capabilities of a glider (Seaglider) and a deep-water profiling float (QUEphone) to a stationary seafloor system (High-frequency Acoustic Recording Package, or HARP) deployed simultaneously over a two week period in the Catalina Basin, California, USA. Two HARPs were deployed 4 km apart while a glider and deep-water drifter surveyed within 20 km of the HARPs. Acoustic recordings were analyzed for the presence of multiple cetacean species, including beaked whales, delphinids, and minke whales. Variation in acoustic occurrence at one-minute (beaked whales only), hourly, and daily scales were examined. The number of minutes, hours, and days with beaked whale echolocation clicks were variable across recorders, likely due to differences in the noise floor of each recording system, the spatial distribution of the recorders, and the short detection radius of such a high-frequency, directional signal type. Delphinid whistles and clicks were prevalent across all recorders, and at levels that may have masked beaked whale vocalizations. The number and timing of hours and days with minke whale boing sounds were nearly identical across recorder types, as was expected given the relatively long propagation distance of boings. This comparison provides evidence that gliders and deep-water drifters record cetaceans at similar detection rates to traditional stationary recorders at a single point. The spatiotemporal scale over which these single hydrophone systems record sounds is highly dependent on acoustic features of the sound source. Additionally, these mobile platforms provide improved spatial coverage which may be critical for species that produce calls that propagate only over short distances such as beaked whales.

Systematic review: Soluble immunological biomarkers in advanced non-small-cell lung cancer (NSCLC).

In the highly dynamic field of advanced malignancies, biomarkers from liquid samples are urgently needed to improve treatment tailoring. However, the heterogenic data lack direct comparison of assays, vectors and relevant validations are rarely found. Therefore, we classified the available studies based on three categories: Measured vectors, applied technique and detected biomarker. High blood tumor mutational burden and low baseline levels of soluble programmed cell death 1 ligand 1 (PD-L1) appear to predict treatment responses to immunotherapy. A high PD-1+ CD4+ T-cell count was associated with poor overall survival, PD-1+CD8+ T-cells connect to a favorable outcome. Circulating tumor cells expressing PD-L1 were mainly associated with poor overall survival and treatment failure. CONCLUSION: Measurement of immunological factors as liquid biomarkers is feasible and has shown promising results. The use of coherent nomenclatures, cross-platform assay comparisons and validations through appropriate powered clinical trials are urgently required to push this auspicious field.

Cross-platform comparison of highly sensitive immunoassay technologies for cytokine markers: Platform performance in post-traumatic stress disorder and Parkinson’s disease

There is mounting evidence of systemic inflammation in post-traumatic stress disorder (PTSD) and Parkinson’s disease (PD), yet inconsistency and a lack of replicability in findings of putative biological markers have delayed progress in this space. Variability in performance between platforms may contribute to the lack of consensus in the biomarker literature, as has been seen for a number of psychiatric disorders, including PTSD. Thus, there is a need for high-performance, scalable, and validated platforms for the discovery and development of biomarkers of inflammation for use in drug development and as clinical diagnostics. To identify the best platform for use in future biomarker discovery efforts, we conducted a comprehensive cross-platform and cross-assay evaluation across five leading platform technologies. This initial assessment focused on four cytokines that have been implicated PTSD – interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, and interferon (IFN)-γ. To assess platform performance and understand likely measurements in individuals with brain disorders, serum and plasma samples were obtained from individuals with PTSD (n = 13) or Parkinson’s Disease (n = 14) as well as healthy controls (n = 5). We compared platform performance across a number of common analytic parameters, including assay precision, sensitivity, frequency of endogenous analyte detection (FEAD), correlation between platforms, and parallelism in measurement of cytokines using a serial dilution series. The single molecule array (Simoa™) ultra-sensitive platform (Quanterix), MESO V-Plex (Mesoscale Discovery), and Luminex xMAP® (Myriad) were conducted by their respective vendors, while Luminex® and Quantikine® high-sensitivity ELISA assays were evaluated by R&D System’s Biomarker Testing Services. The assay with the highest sensitivity in detecting endogenous analytes across all analytes and clinical populations (i.e. the highest FEAD), was the Simoa™ platform. In contrast, more variable performance was observed for MESO V-plex, R&D Luminex® and Quantikine®, while Myriad’s Luminex xMAP® exhibited low FEAD across all analytes and samples. Simoa™ also demonstrated high precision in detecting endogenous cytokines, as reflected in < 20 percent coefficient of variance (%CV) across replicate runs for samples from the healthy controls, PTSD patients, and PD patients. In contrast, MESO V-Plex, R&D Luminex® and Quantikine® had variable performance in terms of precision across cytokines. Myriad Luminex xMAP® could not be included in precision estimates because the vendor did not run samples in duplicate. For cross-platform performance comparisons, the highest cross-platform correlations were observed for IL-6 such that all platforms – except for Myriad’s Luminex xMAP® – had strong correlations with one another in measurements of IL-6 (r range = 0.59 – 0.86). For the other cytokines, there was low to no correlation across platforms, such that reported measurements of IL-1β, TNF-α, and IFN-γ varied across assays. Taken together, these findings provide novel evidence that the choice of immunoassay could greatly impact reported cytokine findings. The current study provides crucial information on the variability in performance between platforms and across immunoassays that may help inform the selection of assay in future research studies. Further, the results emphasize the need for performing comparative evaluations of immunoassays as new technologies emerge over time, particularly given the lack of reference standards for the quantitative assessments of cytokines.

The ‘bad women drivers’ myth: the overrepresentation of female drivers and gender bias in China’s media

ABSTRACTThe body of literature on underrepresentation and gender inequality is vast. However, despite its potential to perpetuate gender stereotypes, the overrepresentation of women in media has received inadequate attention. This study explores how traditional news media and social media overrepresent females as drivers when discussing traffic accidents, and whether social media could be the ‘new equalizer’ for gender. Focusing on China, we collected 97,120 posts from Weibo, China’s largest microblogging site, and 11,290 newspaper articles dated between January 2010 and November 2018. We analyzed the data through a mixed-methods design and found that female drivers are overrepresented in discussions of traffic accidents, in both newspapers and on Weibo. While the gender bias against female drivers is more prevalent on Weibo than in newspapers, Weibo has provided a platform for gender-aware discussion. Our study closes by offering suggestions for cross-platform and cross-cultural comparisons of gender representation in the digital age.

Genome sequencing identifies multiple deleterious variants in autism patients with more severe phenotypes

PurposeTo maximize the discovery of potentially pathogenic variants to better understand the diagnostic utility of genome sequencing (GS) and to assess how the presence of multiple risk events might affect the phenotypic severity in autism spectrum disorders (ASD). MethodsGS was applied to 180 simplex and multiplex ASD families (578 individuals, 213 patients) with exome sequencing and array comparative genomic hybridization further applied to a subset for validation and cross-platform comparisons. ResultsWe found that 40.8% of patients carried variants with evidence of disease risk, including a de novo frameshift variant in NR4A2 and two de novo missense variants in SYNCRIP, while 21.1% carried clinically relevant pathogenic or likely pathogenic variants. Patients with more than one risk variant (9.9%) were more severely affected with respect to cognitive ability compared with patients with a single or no-risk variant. We observed no instance among the 27 multiplex families where a pathogenic or likely pathogenic variant was transmitted to all affected members in the family. ConclusionThe study demonstrates the diagnostic utility of GS, especially for multiple risk variants that contribute to the phenotypic severity, shows the genetic heterogeneity in multiplex families, and provides evidence for new genes for follow up.

Quantitative Proteomic Analysis Identifies AHNAK (Neuroblast Differentiation-associated Protein AHNAK) as a Novel Candidate Biomarker for Bladder Urothelial Carcinoma Diagnosis by Liquid-based Cytology

Cytological examination of urine is the most widely used noninvasive pathologic screen for bladder urothelial carcinoma (BLCA); however, inadequate diagnostic accuracy remains a major challenge. We performed mass spectrometry-based proteomic analysis of urine samples of ten patients with BLCA and ten paired patients with benign urothelial lesion (BUL) to identify ancillary proteomic markers for use in liquid-based cytology (LBC). A total of 4,839 proteins were identified and 112 proteins were confirmed as expressed at significantly different levels between the two groups. We also performed an independent proteomic profiling of tumor tissue samples where we identified 7,916 proteins of which 758 were differentially expressed. Cross-platform comparisons of these data with comparative mRNA expression profiles from The Cancer Genome Atlas identified four putative candidate proteins, AHNAK, EPPK1, MYH14 and OLFM4. To determine their immunocytochemical expression levels in LBC, we examined protein expression data from The Human Protein Atlas and in-house FFPE samples. We further investigated the expression of the four candidate proteins in urine cytology samples from two independent validation cohorts. These analyses revealed AHNAK as a unique intracellular protein differing in immunohistochemical expression and subcellular localization between tumor and non-tumor cells. In conclusion, this study identified a new biomarker, AHNAK, applicable to discrimination between BLCA and BUL by LBC. To our knowledge, the present study provides the first identification of a clinical biomarker for LBC based on in-depth proteomics.

Evaluation of cross-platform and interlaboratory concordance via consensus modelling of genomic measurements.

MotivationA synoptic view of the human genome benefits chiefly from the application of nucleic acid sequencing and microarray technologies. These platforms allow interrogation of patterns such as gene expression and DNA methylation at the vast majority of canonical loci, allowing granular insights and opportunities for validation of original findings. However, problems arise when validating against a “gold standard” measurement, since this immediately biases all subsequent measurements towards that particular technology or protocol. Since all genomic measurements are estimates, in the absence of a ”gold standard” we instead empirically assess the measurement precision and sensitivity of a large suite of genomic technologies via a consensus modelling method called the row-linear model. This method is an application of the American Society for Testing and Materials Standard E691 for assessing interlaboratory precision and sources of variability across multiple testing sites. Both cross-platform and cross-locus comparisons can be made across all common loci, allowing identification of technology- and locus-specific tendencies.ResultsWe assess technologies including the Infinium MethylationEPIC BeadChip, whole genome bisulfite sequencing (WGBS), two different RNA-Seq protocols (PolyA+ and Ribo-Zero) and five different gene expression array platforms. Each technology thus is characterised herein, relative to the consensus. We showcase a number of applications of the row-linear model, including correlation with known interfering traits. We demonstrate a clear effect of cross-hybridisation on the sensitivity of Infinium methylation arrays. Additionally, we perform a true interlaboratory test on a set of samples interrogated on the same platform across twenty-one separate testing laboratories.Availability and implementationA full implementation of the row-linear model, plus extra functions for visualisation, are found in the R package consensus at https://github.com/timpeters82/consensus.Supplementary information Supplementary data are available at Bioinformatics online.