Quality Control Metrics Research Articles

Global sources of cryoprecipitate demonstrate variability in coagulant factor levels and functional hemostasis.

Cryoprecipitate (cryo) is a plasma-derived blood product utilized during trauma resuscitation, surgery, and other major bleeding. Although local quality control metrics exist, inherent donor variability, and processing may confer differences in hemostatic effect between sources. The purposes of this study were to quantify procoagulant content in three global sources of cryo and evaluate their functional hemostatic effect. In this Institutional Review Board exempt study, 24 units of group A cryo from three different sources, American Red Cross single donor and pooled donor, Australian Red Cross single donor, Southwestern United States single donor, and Southwest pooled donor, were evaluated. Procoagulant factors were quantified from each source using ELISA and automated clot-based assays. Functional hemostasis was evaluated using rotational Thromboelastometry (ROTEM). Microparticles isolated from cryo units were enumerated and evaluated for cellular origin by flow cytometry, as well as their capacity to support thrombin generation. Southwestern United States single donor units demonstrated highest levels of fibrinogen, fibronectin, factor VIII, and von Willebrand factor in the selected units. In the coagulopathy model, successive doses from all cryo units were significantly correlated to decreasing coagulation time (P = 0.0100), and increasing maximum clot firmness (P = 0.0002) and alpha angle (P = 0.0009). Southwest pooled donor demonstrated significantly shorter coagulation time at all three doses (P = 0.02) than other sources. Microparticles support prothrombinase activity and thrombin generation. In this study of global cryo sources, procoagulant activity and in-vitro clot formation varied by source. This could be explained by variance in production and storage protocols. Further study is warranted to assess functional variance in cryo to optimize and standardize the use of cryo products.

ATACdb: a comprehensive human chromatin accessibility database.

Accessible chromatin is a highly informative structural feature for identifying regulatory elements, which provides a large amount of information about transcriptional activity and gene regulatory mechanisms. Human ATAC-seq datasets are accumulating rapidly, prompting an urgent need to comprehensively collect and effectively process these data. We developed a comprehensive human chromatin accessibility database (ATACdb, http://www.licpathway.net/ATACdb), with the aim of providing a large amount of publicly available resources on human chromatin accessibility data, and to annotate and illustrate potential roles in a tissue/cell type-specific manner. The current version of ATACdb documented a total of 52 078 883 regions from over 1400 ATAC-seq samples. These samples have been manually curated from over 2200 chromatin accessibility samples from NCBI GEO/SRA. To make these datasets more accessible to the research community, ATACdb provides a quality assurance process including four quality control (QC) metrics. ATACdb provides detailed (epi)genetic annotations in chromatin accessibility regions, including super-enhancers, typical enhancers, transcription factors (TFs), common single-nucleotide polymorphisms (SNPs), risk SNPs, eQTLs, LD SNPs, methylations, chromatin interactions and TADs. Especially, ATACdb provides accurate inference of TF footprints within chromatin accessibility regions. ATACdb is a powerful platform that provides the most comprehensive accessible chromatin data, QC, TF footprint and various other annotations.

Modeling performance of sample collection sites using whole exome sequencing metrics.

Although next-generation sequencing assays are routinely carried out using samples from cancer trials, the sequencing data are not always of the required quality. There is a need to evaluate the performance of tissue collection sites and provide feedback about the quality of next-generation sequencing data. This study used a modeling approach based on whole exome sequencing quality control (QC) metrics to evaluate the relative performance of sites participating in the Bristol Myers Squibb Immuno-Oncology clinical trials sample collection. We identified several events for the sample swap. Overall, most sites performed well and few showed poor performance. These findings can increase awareness of sample failure and improve the quality of samples.

Evolutionary Analysis of Pre- and Post-treatment Molecular Diversity in Rectal Cancer Patients Receiving Neoadjuvant Chemoradiation (CRT) and a KRAS Mutation-targeted Radiosensitizer

Neoadjuvant CRT for locally advanced rectal cancer results in variable pathologic complete response (pCR) rates that may be in part genomically determined. Prior preclinical and clinical data established KRAS/TP53 mutations (mut) as biomarkers of radiation resistance. Lab data suggested that KRAS mut tumors may be preferentially radiosensitized by midostaurin, an oral multi-target tyrosine kinase inhibitor that is FDA-approved for FLT3-mutated leukemia. Using pre- and post-treatment samples from a phase Ib trial of midostaurin + neoadjuvant CRT (mCRT), we assessed the evolution of somatic mutations over the course of treatment and identified molecular determinants of responsiveness. Patients with locally advanced (T3/T4 or N+, M0) rectal adenocarcinoma were enrolled on an IRB-approved protocol (clinicaltrials.gov registered). Neoadjuvant fluoropyrimidine-based mCRT (50.4 Gy) was administered with midostaurin dosed according to a 3+3 dose escalation study design. The MTD for midostaurin was previously reported as 75 mg BID. Total mesorectal excision (TME) was performed at 6-9 weeks post-treatment. DNA was extracted from FFPE samples and whole exome sequencing was performed on pre/post-treatment tumor and matched germline DNA. Data were analyzed by standard mutation analysis pipelines to determine tumor purity and identify somatic mutations, insertion/deletions, and copy number variations. From 10/2011 to 11/2016, 19 patients were enrolled (median age 53 years, 84.2% female, 73.6% stage III), all of whom completed mCRT + TME. Eight patients were classified as non-responders (NR) while 11 patients were partial (n = 8) or complete responders (n = 3) (R). FFPE samples from 17 patients were successfully sequenced and passed quality control metrics (7 NR, 10 R). Mean somatic tumor mutational burden pre- and post-mCRT was 6.7 (range, 3.3-24.3) and 4.8 (range, 0.8-15.4) mutations/MB, respectively. Exploratory comparison of mutational profiles pre- and post-treatment supported varied models of evolutionary pressure and subclonal selection in response to mCRT. Unexpectedly, of 4 KRAS mut tumors (2 with concurrent TP53 mut), 3 were in the R group, and the only NR had no KRAS mut identified in the post-treatment sample, suggesting selection against KRAS mut subclones during treatment. Further molecular analyses supported broad trends in the evolution of putative molecular subclones over the course of treatment with respect to major colorectal cancer driver pathways, including RTK/RAS, PI3K/AKT, WNT/APC, TGFb/EMT. Data suggest successful clinical translation of a KRAS-targeted treatment approach. Future personalized treatment approaches may be informed by a better understanding of tumor evolution in response to treatment.

Genome-wide study of the effect of blood collection tubes on the cell-free DNA methylome

ABSTRACT The methylation pattern of cfDNA, isolated from liquid biopsies, is gaining substantial interest for diagnosis and monitoring of diseases. We have evaluated the impact of type of blood collection tube and time delay between blood draw and plasma preparation on bisulphite-based cfDNA methylation profiling. Fifteen tubes of blood were drawn from three healthy volunteer subjects (BD Vacutainer K2E EDTA spray tubes, Streck Cell-Free DNA BCT tubes, PAXgene Blood ccfDNA tubes, Roche Cell-Free DNA Collection tubes and Biomatrica LBgard blood tubes in triplicate). Samples were either immediately processed or stored at room temperature for 24 or 72 hours before plasma preparation. DNA fragment size was evaluated by capillary electrophoresis. Reduced representation bisulphite sequencing was performed on the cell-free DNA isolated from these plasma samples. We evaluated the impact of blood tube and time delay on several quality control metrics. All preservation tubes performed similar on the quality metrics that were evaluated. Furthermore, a considerable increase in cfDNA concentration and the fraction of it derived from NK cells was observed after a 72-hour time delay in EDTA tubes. The methylation pattern of cfDNA is robust and reproducible in between the different preservation tubes. EDTA tubes processed as soon as possible, preferably within 24 hours, are the most cost effective. If immediate processing is not possible, preservation tubes are valid alternatives.

Clinical Validation of Somatic Mutation Detection by the OncoScan CNV Plus Assay

The OncoScan CNV Plus Assay (OS+) is a single-nucleotide polymorphism microarray platform that can detect 74 hotspot somatic mutations (SMs) in nine genes via molecular inversion probes. We report validation of the SM component of OS+using a cohort of pediatric high-grade brain tumor specimens. SM calls were generated from 46 brain tumor cases, most tested orthogonally via bidirectional Sanger sequencing. The initial calling algorithm result showed that 31 tumors were positive and 15 were negative for SM, with a total of 71 OS+SM calls [28 high-confidence (HC) and 43 low-confidence (LC)]. Sanger sequencing was performed for 54 of the 71 calls (27 HC and 27 LC), as well as for 21 randomly selected hotspots across the 15 OS+negative cases. HC calls (except EGFR) Sanger sequencing confirmed positive, negative calls confirmed negative, but none of the LC calls were Sanger-confirmed positive. An update of the OS+algorithm resolved the LC calls, but of the 11 HC SM EGFR calls, Sanger sequencing confirmed only one. Two PTEN SM calls by OS+ in two separate cases were also negative per Sanger sequencing. We conclude that a majority of HC OS+SM calls were accurate, except calls identified in EGFR and PTEN. Clinically, we report SMs identified by OS+only after Sanger sequencing verification.

Morroniside attenuates apoptosis and pyroptosis of chondrocytes and ameliorates osteoarthritic development by inhibiting NF-κB signaling

Ethnopharmacological relevanceCorni Fructus (CF), the red fruit of Cornus officinalis Siebold & Zucc, has been used both as food and medicinal herb in traditional Chinese medicine (TCM). Our previous studies showed that Yougui pills and Bushenhuoxue formula, both TCM prescriptions containing Corni Fructus (CF), have protective effects on osteoarthritis (OA). However, the underlying detailed components in both TCM prescriptions that play therapeutic roles have not been fully defined. Morroniside is a major iridoid glycoside and one of the quality control metrics of CF, but the effects of morroniside on OA remain largely elusive. Aim of the studyThe study aims to assess the therapeutic effects of morroniside on cartilage degeneration using a mouse model of OA. Material and methods8-week-old male C57BL/6J mice were randomly divided into 4 groups: Sham, destabilization of the medial meniscus (DMM)-treated with vehicle, DMM-treated with low dose morroniside and DMM-treated with high dose morroniside. Histological staining, immunostaining, and TUNEL staining were conducted to detect changes in tissue morphology, expression of key molecules in chondrocytes, and chondrocyte apoptosis, respectively. Osteophyte formation, meniscus calcification, and subchondral sclerosis were quantitated using micro-CT. The expression of chondrocyte markers was also analyzed by Western blot in primary chondrocytes derived from mice treated with morroniside. ResultsMorroniside attenuated the progression of OA in mice, resulting in substantially reduced osteophyte formation and subchondral sclerosis and lower OARSI scores. Specifically, morroniside significantly promoted cartilage matrix synthesis by increasing collagen type II expression and suppressing chondrocyte pyroptosis. Morroniside administration led to inhibition of matrix metalloproteinase-13 (MMP13), Caspase-1 and nod-like receptor protein-3 (NLRP3) expression in DMM mice and IL-1β-stimulated chondrocytes. In addition, morroniside attenuated the progression of OA by enhancing chondrocyte proliferation and inhibiting chondrocyte apoptosis. Morroniside also attenuated the progression of OA by inhibiting nuclear factor-κB (NF-κB) signaling. ConclusionMorroniside was protective against cartilage matrix degradation and reduced DMM-induced chondrocyte pyroptosis and apoptosis by the inhibition of NF-κB signaling.

CRISP-view: a database of functional genetic screens spanning multiple phenotypes.

High-throughput genetic screening based on CRISPR/Cas9 or RNA-interference (RNAi) enables the exploration of genes associated with the phenotype of interest on a large scale. The rapid accumulation of public available genetic screening data provides a wealth of knowledge about genotype-to-phenotype relationships and a valuable resource for the systematic analysis of gene functions. Here we present CRISP-view, a comprehensive database of CRISPR/Cas9 and RNAi screening datasets that span multiple phenotypes, including in vitro and in vivo cell proliferation and viability, response to cancer immunotherapy, virus response, protein expression, etc. By 22 September 2020, CRISP-view has collected 10 321 human samples and 825 mouse samples from 167 papers. All the datasets have been curated, annotated, and processed by a standard MAGeCK-VISPR analysis pipeline with quality control (QC) metrics. We also developed a user-friendly webserver to visualize, explore, and search these datasets. The webserver is freely available at http://crispview.weililab.org.

EFFECTS OF SPERM AGE ON EMBRYO PLOIDY IN PGT-A

PGT-A is routinely offered to patients undergoing IVF. Advanced maternal age (AMA), defined as ≥35 years, has a known significant effect on embryo ploidy status. The effects of advanced paternal age (APA), defined as ≥40 years, on ploidy have been studied less. This study assesses euploid and mosaic rates of embryos created with donor sperm (DS), non-APA sperm, and APA sperm, stratified by use of donor egg (DE), non-AMA eggs, and AMA eggs. Retrospective analysis. All samples received 5/2018 - 5/2020 were included, except for those sent for PGT-SR or with suspected rearrangements. Samples created with known donor gametes were categorized with their respective age groups. Whole-genome amplification, next generation sequencing, and data analysis was performed using the Ion ReproSeqTM PGS Kit and Ion ReporterTM software (Thermo Fisher Scientific). Results were reported as 1) no abnormal cells detected, 2) abnormal cells detected (with percentages if mosaicism was identified), or 3) did not pass quality control (QC) metrics, leading to embryo categories euploid, aneuploid, mosaic, and QC failure. Results were tallied and chi square analyses were performed to compare euploid and mosaic rates between DS samples and non-APA and APA sperm samples. A total of 23,239 samples from 4,691 cycles were included. Table 1 displays ploidy rates for each group and corresponding chi square p-values. Our data shows that sperm age can have an effect on embryos’ ploidy status, as shown by a significantly higher euploid rate in embryos created with DE and DS compared to those created using DE and either non-APA or APA sperm; this effect was noted even with a small sample size. Amongst embryos created with AMA eggs, DS has less of an effect, demonstrating that egg age is still the primary factor affecting embryo ploidy. Clinicians can use this information when counseling patients on the effects of AMA and APA on embryo ploidy.Tabled 1Table 1. Euploid & Mosaic Rates by GroupEmbryo Categories% Euploidχ2 p-value (Euploid)% Mosaicχ2 p-value (Mosaic)Average Egg Age (years)Average Sperm Age (years)DE + DS97/146-19/146-25.228.266.44%13.01%DE + S<401770/3146p = 0.015581/3146NS25.834.656.26%18.47%DE + S≥401478/2593p = 0.025456/2593NS264657.00%17.59%E<35 + DS265/494-99/494-31.626.353.64%20.04%E<35 + S<402662/4808NS757/4808p = 0.01331.833.755.37%15.74%E<35 + S≥40455/829NS129/829p = 0.03732.146.254.89%15.56%E≥35 + DS396/1145-129/1145-39.427.434.59%11.27%E≥35 + S<402122/5251p = 0.0003646/5251NS37.736.340.41%12.30%E≥35 + S≥401559/4827NS458/4827NS39.445.132.30%9.49%DE: donor egg; DS: donor sperm; S<40: non-APA sperm; S≥40: APA sperm; E<35: non-AMA egg; E≥35: AMA egg; NS: not significant Open table in a new tab

Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control.

Quality control (QC) is a critical step in single-cell RNA-seq (scRNA-seq) data analysis. Low-quality cells are removed from the analysis during the QC process to avoid misinterpretation of the data. An important QC metric is the mitochondrial proportion (mtDNA%), which is used as a threshold to filter out low-quality cells. Early publications in the field established a threshold of 5% and since then, it has been used as a default in several software packages for scRNA-seq data analysis, and adopted as a standard in many scRNA-seq studies. However, the validity of using a uniform threshold across different species, single-cell technologies, tissues and cell types has not been adequately assessed. We systematically analyzed 5530106 cells reported in 1349 annotated datasets available in the PanglaoDB database and found that the average mtDNA% in scRNA-seq data across human tissues is significantly higher than in mouse tissues. This difference is not confounded by the platform used to generate the data. Based on this finding, we propose new reference values of the mtDNA% for 121 tissues of mouse and 44 tissues of humans. In general, for mouse tissues, the 5% threshold performs well to distinguish between healthy and low-quality cells. However, for human tissues, the 5% threshold should be reconsidered as it fails to accurately discriminate between healthy and low-quality cells in 29.5% (13 of 44) tissues analyzed. We conclude that omitting the mtDNA% QC filter or adopting a suboptimal mtDNA% threshold may lead to erroneous biological interpretations of scRNA-seq data. The code used to download datasets, perform the analyzes and produce the figures is available at https://github.com/dosorio/mtProportion. Supplementary data are available at Bioinformatics online.

PHOTOMATCH: AN OPEN-SOURCE MULTI-VIEW AND MULTI-MODAL FEATURE MATCHING TOOL FOR PHOTOGRAMMETRIC APPLICATIONS

Abstract. Automatic feature matching is a crucial step in Structure-from-Motion (SfM) applications for 3D reconstruction purposes. From an historical perspective we can say now that SIFT was the enabling technology that made SfM a successful and fully automated pipeline. SIFT was the ancestor of a wealth of detector/descriptor methods that are now available. Various research activities have tried to benchmark detector/descriptors operators, but a clear outcome is difficult to be drawn. This paper presents an ISPRS Scientific Initiative aimed at providing the community with an educational open-source tool (called PhotoMatch) for tie point extractions and image matching. Several enhancement and decolorization methods can be initially applied to an image dataset in order to improve the successive feature extraction steps. Then different detector/descriptor combinations are possible, coupled with different matching strategies and quality control metrics. Examples and results show the implemented functionality of PhotoMatch which has also a tutorial for shortly explaining the implemented methods.

ScCancer: a package for automated processing of single-cell RNA-seq data in cancer.

Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis and treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer cell heterogeneities and microenvironments at single-cell transcriptomic level. Here, we develop an R package named scCancer, which focuses on processing and analyzing scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features. Firstly, the package introduced comprehensive quality control metrics. Secondly, it used a data-driven machine learning algorithm to accurately identify major cancer microenvironment cell populations. Thirdly, it estimated a malignancy score to classify malignant (cancerous) and non-malignant cells. Then, it analyzed intra-tumor heterogeneities by key cellular phenotypes (such as cell cycle and stemness), gene signatures and cell-cell interactions. Besides, it provided multi-sample data integration analysis with different batch-effect correction strategies. Finally, user-friendly graphic reports were generated for all the analyses. By testing on 56 samples with 433405 cells in total, we demonstrated its good performance. The package is available at: http://lifeome.net/software/sccancer/.

Single-Cell Distribution Analysis of AR Levels by High-Throughput Microscopy in Cell Models: Application for Testing Endocrine-Disrupting Chemicals.

Cell-to-cell variation of protein expression in genetically homogeneous populations is a common biological trait often neglected during analysis of high-throughput (HT) screens and is rarely used as a metric to characterize chemicals. We have captured single-cell distributions of androgen receptor (AR) nuclear levels after perturbations as a means to evaluate assay reproducibility and characterize a small subset of chemicals. AR, a member of the nuclear receptor family of transcription factors, is the central regulator of male reproduction and is involved in many pathophysiological processes. AR protein levels and nuclear localization often increase following ligand binding, with dihydrotestosterone (DHT) being the natural agonist. HT AR immunofluorescence imaging was used in multiple cell lines to define single-cell nuclear values extracted from thousands of cells per condition treated with DHT or DMSO (control). Analysis of numerous biological replicates led to a quality control metric that takes into account the distribution of single-cell data, and how it changes upon treatments. Dose-response experiments across several cell lines showed a large range of sensitivity to DHT, prompting us to treat selected cell lines with 45 Environmental Protection Agency (EPA)-provided chemicals that include many endocrine-disrupting chemicals (EDCs); data from six of the compounds were then integrated with orthogonal assays. Our comprehensive results indicate that quantitative single-cell distribution analysis of AR protein levels is a valid method to detect the potential androgenic and antiandrogenic actions of environmentally relevant chemicals in a sensitive and reproducible manner.

Comprehensive fundamental somatic variant calling and quality management strategies for human cancer genomes.

Next-generation sequencing (NGS) technology has revolutionised human cancer research, particularly via detection of genomic variants with its ultra-high-throughput sequencing and increasing affordability. However, the inundation of rich cancer genomics data has resulted in significant challenges in its exploration and translation into biological insights. One of the difficulties in cancer genome sequencing is software selection. Currently, multiple tools are widely used to process NGS data in four stages: raw sequence data pre-processing and quality control (QC), sequence alignment, variant calling and annotation and visualisation. However, the differences between these NGS tools, including their installation, merits, drawbacks and application, have not been fully appreciated. Therefore, a systematic review of the functionality and performance of NGS tools is required to provide cancer researchers with guidance on software and strategy selection. Another challenge is the multidimensional QC of sequencing data because QC can not only report varied sequence data characteristics but also reveal deviations in diverse features and is essential for a meaningful and successful study. However, monitoring of QC metrics in specific steps including alignment and variant calling is neglected in certain pipelines such as the 'Best Practices Workflows' in GATK. In this review, we investigated the most widely used software for the fundamental analysis and QC of cancer genome sequencing data and provided instructions for selecting the most appropriate software and pipelines to ensure precise and efficient conclusions. We further discussed the prospects and new research directions for cancer genomics.

Key considerations for comprehensive validation of an RNA fusion NGS panel

ObjectivesValidation of RNA-based NGS assays for the detection of therapeutically targetable gene fusions is challenging. Here, we report systematic validation and quality control monitoring of our targeted fusion panel for the detection of 17 clinically relevant fusion transcripts across several tumor types. We implemented this RNA Fusion Panel as a reflex test for tumors lacking DNA driver mutations. DesignForty-four formalin-fixed, paraffin-embedded (FFPE) or fresh-frozen lung, brain, soft tissue and skin tumors were used to determine the accuracy of the assay. Additional fusion-positive specimens and a calibrated reference standard were used to establish the precision, reproducibility and sensitivity of the assay. All aspects of the validation, including quality control metrics, were performed according to New York State guidelines. ResultsFor the RNA fusion panel, accuracy, reproducibility and precision studies were above 99%. Reproducibility and sensitivity studies with the reference standard were helpful in identifying inconsistencies. The limit of detection for most RNA fusion transcripts was 50 copies. Application of the RNA fusion assay as a reflex test to 450 tumor samples lacking DNA driver mutations resulted in a 10% increase in diagnostic yield with minimal additional processing time. ConclusionsThe validated RNA fusion panel provides clinical utility in therapy selection for patients with solid tumors. By using a sequential testing approach, the RNA fusion assay complements the DNA hotspot assay in identifying clinically relevant variants across many tumor types with minimal additional increase in processing time.

Abstract B49: Substantial performance differences among RNA purification kits and blood collection tubes in the Extracellular RNA Quality Control study—important considerations for liquid biopsies

Abstract Cancer biomarker studies require procedures that provide accurate and precise test results with high analytical sensitivity. Consequently, the growing use of extracellular RNA from human biofluids as clinically relevant biomarker requires the implementation of benchmarked methods for sample collection, processing, and profiling. While several small-scale studies have pointed at the impact of individual preanalytical factors, no comprehensive study has addressed the many preanalytical variables affecting downstream sequencing of blood-derived exRNAs. In the Extracellular RNA Quality Control study, we have systematically evaluated the type of blood collection tube (n=10, including 5 so-called preservation tubes), the time between blood draw and plasma preparation (n=3), different plasma types (n=3, i.e., platelet-free, -poor, and -rich plasma), and RNA purification methods using the supplier-specified minimum and maximum plasma input volumes (n=15). The impact of these preanalytical factors is assessed by deep transcriptome profiling of all small and messenger RNAs from healthy donors’ plasma, using TruSeq Small RNA sequencing and TruSeq RNA Exome sequencing, respectively. All experiments are conducted in triplicate (for a total of 270 transcriptomes) using 191 synthetic RNA spike-in molecules as processing controls over a relevant dynamic range. When comparing blood collection tubes, serum mRNA seems very similar to EDTA plasma mRNA, but serum-derived small RNAs are markedly different in biotype composition compared to their plasma counterparts. Furthermore, several plasma tubes with preservation reagents do not stabilize RNA very well, as is reflected by increasing RNA concentrations and number of detected genes over time. Also, their reproducibility is generally compromised. In addition, we demonstrate large differences in RNA purification kit performance in terms of reproducibility, sensitivity, and observed transcriptome complexity. Among others, we note a 50-fold difference in mRNA yield and a 5-fold difference in the number of detected mRNAs. We summarized the results in 12 performance parameters that enable an informed selection of the most optimal sample processing workflow. In conclusion, using a systematic approach, we put forward robust quality control metrics for exRNA quantification methods with validated SOPs for sample collection, processing, and profiling. Our results are crucially important for all future RNA-based liquid biopsy-guided precision oncology applications. Authors in random order; abstract submitted on behalf of the exRNAQC Consortium. Citation Format: Anneleen Decock, Jasper Anckaert, Celine Everaert, Justine Nuytens, Scott Kuersten, An Hendrix, Jo Vandesompele, Pieter Mestdagh, Bert Dhondt, Ruben Van Paemel, Kimberly Verniers, Gary Schroth, Carolina Fierro, Nurten Yigit, Kathleen Schoofs, Annelien Morlion, Jill Deleu, Eva Hulstaert, Francisco Avila Cobos, Nele Nijs, Eveline Vanden Eynde, Hetty Hilde Helsmoortel, Olivier De Wever, Annouck Philippron. Substantial performance differences among RNA purification kits and blood collection tubes in the Extracellular RNA Quality Control study—important considerations for liquid biopsies [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr B49.

OP0044 WHOLE KIDNEY TRANSCRIPTOMIC ANALYSIS OF FORMALIN-FIXED PARAFFIN-EMBEDDED LUPUS NEPHRITIS KIDNEY BIOPSY TISSUE USING THE NANOSTRING NCOUNTER PLATFORM

Background:There is an ongoing effort to elucidate the molecular pathways that are key to kidney injury in lupus nephritis (LN). One approach is to study the transcriptome utilising kidney tissue obtained during diagnostic renal biopsy [1]. In clinical practice the most common tissue that is surplus to diagnostic requirements is formalin-fixed paraffin-embedded (FFPE) tissue. However, due to RNA degradation, transcriptomic analysis has been sub-optimal and challenging using standard procedures. The NanoString technology platform has the advantage that reliable detection of transcripts can be achieved even with degraded RNA. In this study we explored the utility of NanoString technology in identifying transcripts in RNA isolated from archival FFPE kidney biopsy sections in a cohort of patients with LN.Objectives:To explore the utility of the NanoString platform in elucidating a renal transcriptomic signature in formalin-fixed paraffin-embedded Lupus Nephritis kidney biopsy tissue.Methods:We utilised well defined Class III (n=11); Class IV (n=22) and Class V (n=24) LN FFPE kidney biopsies from female patients attending the Imperial College Healthcare NHS Trust. We excluded biopsies with mixed lesions or chronic lesions (i.e. significant glomerular scarring). Kidney biopsies from patients with Thin Basement Membrane (TBM; n=14) disease were used as controls. Six 10 micron thick sections were obtained from each biopsy and RNA isolated using the Qiagen RNeasy FFPE Kit. 100 micrograms of RNA was used for the detection of transcripts. We used the NanoString PanCancer immune profiling panel (770 transcript probes) and an additional 30 custom designed probes, enabling us to detect 800 transcripts, including 40 reference genes. Transcript analysis was performed according to manufacturer’s instructions using the NanoString nSolver software. When analysing differential gene expression (DGE) we used Benjamini-Hochberg adjustment to account for multiple testing. The threshold for statistical significance was an adjusted P value of 0.05 (5% false discovery rate).Results:Transcriptomic data passing NanoString nSolver quality control metrics was obtained from all sections. Notably sections included biopsies up to 16 years old (range: 1-16 years). Our transcript panel contained several Type I interferon (IFN) responsive genes, including sialic acid-binding Ig-like lectin 1 (Siglec-1). We detected a type I IFN signature using 8 IFN-responsive transcripts in 39 (68.4%) of the LN biopsies but in none of the TBM biopsies. This signature was present in Class III (n=9, 81.8%), Class IV (n=16, 72.7%) and Class V (n=14, 58.3%) LN samples. When we performed DGE analysis using TBM as the baseline we detected significantly increased expression across the classes (Class III = 202; Class IV = 357 and Class V = 237 differentially expressed transcripts, Figure 1).Conclusion:We have successfully identified transcriptomic signatures in RNA samples derived from a relatively large cohort of FFPE LN samples. Consistent with published reports we could detect a type I IFN signature in the LN kidney tissue [1]. Consistent with a recent study [1], we detected increased expression of OPN (osteopontin) and FN1 (fibronectin-1) in proliferative (Class III and IV) but not Class V LN. We are now performing clinical correlations to determine if the differentially expressed transcripts are clinically informative.

Novel target discovery in pembrolizumab-resistant gastric cancer using a comprehensive RNA-seq analysis pipeline.

e16541 Background: Immune checkpoint inhibition (ICI) has made significant breakthroughs in several tumor types including gastric cancer (GC) in recent years. We recently showed that single agent pembrolizumab demonstrated remarkable and durable response in MSI and EBV GC. However, the response to ICI remains low in MSS and most patients progress after initial response. We explore novel targets in ICI-resistant GC patients by analyzing pre- and post-resistant expression. Methods: Of the 61 patients who were enrolled onto our previously reported phase II pembrolizumab trial (NCT#02589496), whole transcriptome RNA-seq analysis of 10 paired freshly collected tissue samples (all from primary gastric tumors) was performed using TruSeq. All biopsies were performed at progression following stable disease (SD) or partial response (PR) to pembrolizumab. All patients had a MSI status of MSS and EBV negative. Molecular features were extracted using the validated Ocean Genomics, Inc. gene expression analysis pipeline, which trims reads, computes transcript- and gene-level expression, predicts structural variants, assembles novel isoforms, and computes per-sample quality control metrics, among other analyses. Samples that passed quality control, with mapping rates &gt; 88%, were selected for analysis. Differentially expressed (DE) genes between resistant and pre-resistant samples were identified using a statistical test with a study design that accounted for the pairing of samples for each patient. Results: 16 genes (GENCODE v31) had absolute log2-fold expression changes (L2FC) &gt; 2, P-value &lt; 10−5 and FDR-adjusted P-value &lt; 0.05. Because sex was only partially controlled for, we excluded genes on the X and Y chromosomes. We also excluded non-protein encoding genes and pseudogenes. The 7 remaining genes are in the table. PDL-1 (CD274) was not identified as significantly DE (FDR-adjusted P-value &gt; 0.9999). Conclusions: This is the first study to identify novel targets in pembrolizumab-resistant GC using RNA-seq algorithms beyond PDL-1. [Table: see text]

OR31-06 Candidate Gene Variants in a Large Cohort of Women with Primary Ovarian Insufficiency

Primary ovarian insufficiency (POI) is highly heritable. The majority of cases have no known cause. We hypothesized that mutations in previously identified genes or genes from the same pathways are the cause of POI in a recessive or dominant manner. Subjects included 294 women diagnosed with POI (amenorrhea with an elevated FSH level). All had a 46XX karyotype, and normal FMR1 repeat number. Subjects were recruited in Boston (n=95), at the NIH and Washington University (n=98), and in Pittsburgh (n=98). Controls included subjects recruited for health in old age and disorders unrelated to reproduction or cancer, and subjects from the 1000 Genomes Project (total n=587). Variants were called using the Sentieon software package (https://www.sentieon.com). Case and control samples were stratified on ethnicity, relatedness and heterozygosity. Peddy and XPAT were used to calculate quality control metrics to detect outlier samples for removal from analysis to create a homogenous dataset. The number of cases (227) and controls (458) was adjusted for downstream analysis. XPAT imposed additional quality filters and removed variants. A second filter removed variants that did not pass a Gnomad filter of <0.001 allele frequency. VAAST was used to determine a composite likelihood ratio (CLR) as the test statistic to represent the aggregate burden of variants of affected individuals in each transcript relative to a set of 458 control genomes. The significance of each transcript’s VAAST CLR score was evaluated by 1 million permutations. We screened exomes for variants in previously identified genes causing POI in humans and those demonstrating infertility in a male or female mouse model. We also used the American College of Medical Genetics and Genomics standards for interpretation of pathogenicity of a variant, with priority on null variants in genes with probability of loss of function intolerance based on the observed vs. expected rate in gnomAD, in vivo or in vitro functional evidence of a damaging effect, significantly increased prevalence compared to controls, i.e. not found in any controls or in fewer than 10 in the gnomAD database if the subject had a matching race/ethnicity. Thirty-four subjects were removed for poor quality exomes and relatedness. Fifty-three subjects had at least one variant in a previously identified POI gene or one in which there was a previously identified functional model. Two subjects carried recessive variants and 30 carried at least one novel heterozygous candidate variant for follow up. Analysis of genetic causes of POI in this large cohort identified candidate causal gene variants in over half of the subjects. The data demonstrate that the genetic architecture is heterogeneous. Although recessive mutations have been identified in consanguineous families, the data suggest that a dominant or oligogenic pattern of inheritance may be important.

ScATAC-pro: a comprehensive workbench for single-cell chromatin accessibility sequencing data

Single-cell chromatin accessibility sequencing has become a powerful technology for understanding epigenetic heterogeneity of complex tissues. However, there is a lack of open-source software for comprehensive processing, analysis, and visualization of such data generated using all existing experimental protocols. Here, we present scATAC-pro for quality assessment, analysis, and visualization of single-cell chromatin accessibility sequencing data. scATAC-pro computes a range of quality control metrics for several key steps of experimental protocols, with a flexible choice of methods. It generates summary reports for both quality assessment and downstream analysis. scATAC-pro is available at https://github.com/tanlabcode/scATAC-pro.