Research Use Only Research Articles

B-065 Comparative Analysis of 14-3-3η Autoantibody Assays on Luminex Platform for Diagnosing Axial Spondyloarthritis

Abstract Background The pathophysiological significance of extracellular 14-3-3η antigen and its autoantibodies (AAbs) is well-documented in autoimmune rheumatologic disorders. Use of 14-3-3η protein blood tests is common in diagnosing and managing rheumatoid arthritis (RA). Prior studies have established the diagnostic and prognostic value of 14-3-3η AAbs in RA and axial spondyloarthritis (AS), particularly in differentiating AS patients from healthy individuals and in relation to disease severity and progression. This study explores the performance of a novel assay platform in the context of AS diagnosis, especially in younger patients who are most responsive to early treatment interventions.This research aims to evaluate the discriminative accuracy of the 14-3-3η AAb assay on the Luminex® platform, a widely recognized clinical tool, in distinguishing AS patients from healthy subjects, and to compare its performance with that of the Meso Scale Discovery® (MSD) research-use only (RUO) platform. Methods Sera from 49 AS patients and 25 healthy controls (HC), previously assessed using the MSD platform, were reanalyzed using a new Luminex 14-3-3η AAb assay. These samples were sourced from the Follow Up Research Cohort in Axial Spondyloarthritis (FORCAST) Prognostic Cohort. Spearman correlations were employed for variable analysis, and the Mann-Whitney U-test was used to compare AAb levels between groups. Receiver Operating Characteristic (ROC) Area Under Curve (AUC) analyses were conducted for both assay platforms, with a specific focus on patients aged 45 and under. Results The AS patient group had a mean age (SD) of 44 (13) years, with 67% male representation. The median (IQR) disease duration was 19 (10-24) years, and median (IQR) C-reactive protein (CRP) levels were 9.6 (4.3 - 24.8) mg/L. Median (IQR) 14-3-3η AAb levels were significantly higher in AS patients at 136 U/μl (48 - 408) compared to HCs at 54 (28 - 161) U/μl, p=0.02. ROC AUC analysis for the MSD RUO platform showed an AUC of 0.67 (95% CI, 0.55 - 0.79), and for the Luminex platform, an AUC of 0.66 (95% CI, 0.53 - 0.80), indicating comparable performance across platforms. In the subgroup of AS patients aged ≤45 years, the Luminex assay demonstrated an AUC of 0.74 (95% CI, 0.61-0.88), p=0.003. Combination of 14-3-3η AAbs and CRP was able to identify 90% of AS patients. No correlation between the two markers was observed (r= -0.14, p=0.38). Conclusions The Luminex-based 14-3-3η AAb assay exhibits equivalent discriminative capability to the MSD RUO assay in differentiating AS patients from healthy individuals. The combined use of 14-3-3η AAbs and CRP, identifying 90% of AS patients, highlights the potential of these biomarkers as complementary diagnostic and prognostic tools in AS, meriting further research.

Comparison of Results from Two Commercially Available In-House Tissue-Based Comprehensive Genomic Profiling Solutions: Research Use Only AVENIO Tumor Tissue Comprehensive Genomic Profiling Kit and TruSight Oncology 500 Assay

Increased adoption of personalized medicine has brought comprehensive genomic profiling (CGP) to the forefront. However, differences in assay, bioinformatics, and reporting systems and lack of understanding of their complex interplay are a challenge for implementation and achieving uniformity in CGP testing. Two commercially available, tissue-based, in-house CGP assays were compared, in combination with a tertiary analysis solution in a research use only (RUO) context: the AVENIO Tumor Tissue CGP RUO Kit paired with navify Mutation Profiler (RUO) software and the TruSight Oncology 500 RUO assay paired with PierianDx Clinical Genomics Workspace software. Agreements and differences between the assays were assessed for short variants (SVs), copy number alterations (CNAs), rearrangements, tumor mutational burden (TMB), and microsatellite instability (MSI), including variant categorization and clinical trial-matching (CTM) recommendations. Results showed good overall agreement for SV, known gene fusion, and MSI detection. Important differences were obtained in TMB scoring, CNA detection, and CTM. Differences in variant and biomarker detection could be explained by bioinformatic approaches to variant calling, filtering, tiering, and normalization; differences in CTM, by underlying reported variants and conceptual differences in system parameters. Thus, distinctions between different approaches may lead to inconsistent results. Complexities in calling, filtering, and interpreting variants illustrate key considerations for implementation of any high-quality CGP in the laboratory and bringing uniformity to genomic insight results.

Breadth versus depth: whole transcriptome sequencing has reduced sensitivity for detection of clinically relevant fusions compared to RNA comprehensive genomic profiling.

While there is great potential for unbiased next-generation sequencing (NGS) approaches-eg, whole transcriptome sequencing (WTS)-for exploration, discovery, and clinical application in the realm of oncology, there are limitations that should be considered when relying on these methodologies for clinical decision making. When using WTS for the detection of clinically relevant gene fusions in tumor specimens, a key consideration is whether a limited coverage depth (approximately 30-50X) is sufficient for detecting these events, especially in samples with low tumor purity. We demonstrate the reduced sensitivity of both a commercial WTS assay for the detection of clinically relevant fusions in analytical validation control samples and of a research use only (RUO) WTS assay for the detection of clinically relevant fusions in real-world clinical samples compared to RNA comprehensive genomic profiling (CGP). Notably, the RUO WTS assay would not have reported 30% (6/20) of fusions detected using RNA CGP assays in fusion-positive tumor samples, highlighting a potential disadvantage of broader sequencing.

Implementation of a comprehensive genomic profiling (CGP) panel for precision oncology at a cancer center in Brazil.

e23520 Background: Assessing molecular alterations in solid tumors is essential for providing the best care in precision oncology. CGP tests utilize next-generation sequencing (NGS) to detect clinically relevant alterations and molecular signatures that are increasingly utilized in cancer careand can be performed in-house, which decreases test turnaround time (TAT) and costs. A paucity of studies have documented the experience of in-house testing at academic centers in Brazil. Methods: The TruSight Oncology (TSO) 500 assay/TSO 500 HRD are research use only (RUO) CGP assays that were validated for the detection of small variants (SVs), copy number variants (CNVs), microsatellite instability (MSI), tumor mutation burden (TMB) and genomic instability score (GIS) in DNA and gene fusions/splice variants in RNA in the NextSeq 500 system. Secondary analysis was performed with Illumina Connected Analytics. Tertiary analysis was performed with Illumina Connected Insights (ICI) and Sophia DDM. TMB ≥ 10mut/Mb was defined as TMB-High and GIS ≥ 42 was homologous recombination deficient (HRD). Results: We performed CGP on 40 FFPE samples (16 with HRD) with variable quality and block age most of which had known alterations detected by other genomics/molecular tests: 17 TNBC (16 paired DNA and RNA, 1 DNA only), 18 lung cancer (13 paired DNA and RNA, 5 DNA only), 1 endometrium cancer (DNA only, POLE mutated, 4 replicates), 1 colorectal cancer (DNA only, MSI unstable) and 11 sarcomas (RNA only). 84%, 84%, 90% and 89% of samples with DNA integrity number (DIN) > 2.5 were qualified for analysis of SVs/TMB, MSI, CNVs, and GIS, respectively, while for samples with DIN < 2.5 these values felt to 47%, 74%, 68% and 43%, respectively. RNA isolated from blocks dated up to 5 y.o. were qualified in 90% of cases while from older blocks only 6%. The 4 replicate (single sample) analysis showed 82% and 83% overall variant concordance in the ICI and Sophia DDM software, respectively. All previously known oncogenic alterations (SVs ≥5% VAF, fusions/splice, MSI, TMB) were detected (qualified samples) and with similar performance in ICI and Sophia, respectively: concordance 0.91/p < 0.0001 vs 0.94/p < 0.0001; sensitivity 100% vs 100%; specificity 98% vs 100%. TMB had 100% concordance with previous TMB results. Of note, 73% (8/11) TNBC samples analyzed for GIS were HRD and 75% (6/8) explained by BRCA1 germline mutation (25%) and BRCA1or RAD51C somatic promoter methylation (75%). Conclusions: This study demonstrates the utility of CGP and HRD testing in identifying multiple molecular alterations in FFPE tissue samples with high sensitivity and specificity. Pre-analytical variables directly impact data generation. BRCA1/RAD51C promoter methylation showed to be a potential biomarker for selecting metastatic TNBC patients for PARP inhibitor therapies. Offering CGP can potentially bring precision oncology to more patients with cancer in Brazil.

A molecular standard for circulating HBV RNA detection and quantification assays in patients with chronic hepatitis B

BackgroundCirculating HBV RNAs have been proposed as a biomarker that reflects the transcriptional activity of cccDNA and may help to evaluate HBV treatments activity. Different research assays have been proposed and, although 2 PCR-based research use only (RUO) investigational assays (IA) have been developed, the lack of standardized protocols represents an important limitation. Here we have designed and generated a stable clonal cell line producing an RNA-based standard for the calibration of PCR-based circulating HBV RNA assays. MethodsHBV RNA producing Huh7-derived stable cell lines were generated by transfecting pTriEX plasmids containing 1.1 length HBV DNA genomes carrying mutations in the catalytic site (YMAA mutation) and the TP-domain (Y63F) of the polymerase, and the ε-loop of the pgRNA (mutation A1G). ResultsThe clonal cell line (Huh7-3D29), carrying a double YMAA and Y63F mutation, displayed, and maintained over several passages in culture, a high RNA secretion phenotype with negligible residual secreted HBV DNA. Density gradient centrifugation showed that most of the secreted HBV RNA from Huh7-3D29 cells was detected in naked capsid and virions-like particles and only a minority in small extracellular vescicles (sEV). Nanopore sequencing of 5’RACE products shows that the majority of the Huh7-3D29 secreted HBV RNAs start at the 5' end of pgRNA and pgRNA derived spliced RNAs. Finally, Huh7-3D29 cells showed a high and up-scalable secreted RNA yield allowing 1,300 standard curves in 9 days from 1 flask. ConclusionWe generated a clonal cell line that produces high amounts of HBV RNAs with very low quantities of contaminating HBV DNAs, representing a stable source of RNA standard for HBV RNA assays calibration. Impact and ImplicationsSeveral investigational assays and 2 research use only (RUO) assays have been developed to detect and quantify circulating HBV RNAs, an emerging biomarker of cccDNA transcriptional activity and target engagement by new HBV treatments. The lack of a unique molecular standard for circulating HBV RNAs quantification represents an important limitation. Here we describe the generation of a stable clonal cell line producing and secreting an RNA-based standard containing all the HBV RNA species found in HBV patients’ sera (e.g., pgRNA, HBx transcripts). This new RNA standard will serve for the calibration of all PCR-based assays for circulating HBV RNA quantification to evaluate in a non-invasive manner the size of the transcriptionally active cccDNA pool and the activity of novel strategies aiming at curing HBV infection.

Abstract 3644: Uncover spatial signatures of tumor microenvironment and oncogenic pathways using 6,000-plex single-cell spatial molecular imaging on FFPE skin squamous cell carcinoma

Abstract Background: Tumor progression and therapeutic response are regulated by the tumor microenvironment. Understanding the spatial association and architecture of molecular characteristics and composition of tumor immune microenvironment at single-cell and subcellular resolution encourages improvements in clinical prognosis and immunotherapy benefits. Single-cell Spatial profiling technologies permit the study of transcriptional activity at the spatial, single-cell level and provide abundant, high-resolution information required for the identification of clinical-related features in immuno-oncology. Methods: We performed an ultra-high-plex RNA assay to detect 6,000 targets simultaneously in situ on FFPE human skin squamous cell carcinoma using the CosMx™ Spatial Molecular Imager (SMI). For the selection of regions of interest, four protein markers and DAPI were co-detected on the same tissue slide. Tertiary analysis algorithms were developed for cell typing, co-localization of genes and ligands, cell-cell interaction, and pathway analysis. Results: Thousands of transcripts were simultaneously detected with high sensitivity and specificity on the FFPE skin squamous cell carcinoma tissue section at single-cell subcellular resolution. We investigated the tumor microenvironment including cell types, their spatial distribution and proportion of diversified immune cells in the tumor compartment. The cell typing results revealed many cancerous subpopulations, which resolved spatially from cells that lacked any defining marker genes. We also assessed distances between immune cells and their nearest functional-related neighbors. Moreover, we revealed the ligands co-localization, as well as spatial patterns of direct cell-cell interactions and signaling pathways. We found that some genes have elevated expression in macrophages which are near cancer compared to those are far from cancer cells, empowering the molecular investigation of novel signaling between immune and cancer cells in tumor immune microenvironment. Conclusions: Single-cell spatial measurements of 6,000 RNA and four proteins on the same tissue section, along with a large viewing area on archival FFPE tissue, provide a novel tool to reveal the spatial signature of tumor microenvironment and oncogenic pathways, facilitating the next level of cancer and therapeutic research. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Michael Patrick, Shanshan He, Saskia Ilcisin, David Kroeppler, Patrick Danaher, Jason Reeves, Mark Gregory, Haiyan Zhai, Michael Rhodes, Joseph Beechem. Uncover spatial signatures of tumor microenvironment and oncogenic pathways using 6,000-plex single-cell spatial molecular imaging on FFPE skin squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3644.

Abstract 3649: A novel spatial multi-omic approach for biological discoveries in colonic diseased tissues using a comprehensive Immuno-Oncology Proteome Atlas and Whole Transcriptome Atlas

Abstract The advancement of spatially resolved, multiplex proteomic and transcriptomic technologies has revolutionized and redefined the approaches to complex biological questions pertaining to tissue heterogeneity, tumor microenvironments, cellular interactions, cellular diversity, and therapeutic response. While spatial transcriptomics has traditionally led the way in plex, multiple studies have demonstrated a poor correlation between RNA expression and protein abundance, owing to transcriptional and translational regulation, target turnover, and most critically, post-translational protein modifications. Therefore, a more holistic, ultra-high-plex, and high-throughput proteomic atlas approach becomes critical for the next phase of discovery biology. Here, we present a barrier-breaking, spatial proteomics panel that was designed to accelerate scientific discoveries. A Digital Spatial Profiler platform is uniquely suited to support high-plex proteomics, allowing for the simultaneous analyses of proteins from discrete regions of interest (ROIs) in FFPE tissue sections while preserving spatial context. The assay relies upon abcam antibodies coupled to photocleavable DNA barcodes readout with NGS sequencing, allowing for theoretically unlimited plex. Here we introduce the Human Immuno-Oncology Proteome Atlas (IPA), a 570+ antibody-based proteomic discovery panel, compatible with immunohistochemistry on FFPE tissues with NGS readout. IPA is the highest-plex, most comprehensive, antibody-based multi-omic panel to date focusing on key areas of immuno-oncology, oncology, immunology, epigenetics, metabolism, cell death, and signaling pathway regulation. Here we demonstrate the performance of IPA on various cell lines and tissue. Additionally, we show the power of IPA, using the spatial multi-omic assay along with the GeoMx® Whole Transcriptome Atlas (> 18,000 transcripts), a 40-plex custom antibody panel and microbiome-curated RNA custom spike-in (~220 transcripts) to evaluate 70 different colon disease samples across 5 pathologies including adenocarcinoma, hyperplasia, and chronic inflammation. This is the highest-plex multi-omic (~610-plex proteins and >18,220 genes) study ever implemented for spatial biology. When we compared the diseased tissue to normal tissue, we observed an upregulation of specific pathways associated with tumorigenesis and inflammation. Furthermore, we observed distinct differences in proteomic and transcriptomic landscape between pathologies. The cutting-edge, data-driven, expert-curated IPA panel is at the forefront of spatial proteomics, empowering the researcher for the acceleration of biological discoveries. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Alyssa Rosenbloom, Shilah Bonnett, Mark Conner, Christine Kang, Erin Piazza, Brian Filanoski, Rhonda Meredith, Hye Son Yi, Lori Hamanishi, Eduardo Ignacio, Nadine Nelson, Michael Prater, Vik Devgan, Rudy Van Eijsden, Melanie Moon, Lesley Isgur, Terence Theisen, Margaret Hoang, Gary Geiss, Joseph M. Beechem. A novel spatial multi-omic approach for biological discoveries in colonic diseased tissues using a comprehensive Immuno-Oncology Proteome Atlas and Whole Transcriptome Atlas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3649.

Abstract 1138: A single-cell spatially resolved atlas of immune-mediated control of lung adenocarcinoma using 1,000-plex single-cell spatial molecular imaging in a transgenic mouse model

Abstract Background: Lung adenocarcinoma is one of the leading causes of cancer-related mortality. One of the most frequently occurring mutations in lung cancer is KRAS mutations. Recent development of chemical inhibitors that specifically target oncogenic variants of Ras, particularly the commonly mutated KRAS-G12D isoform, represents a significant breakthrough in targeted therapeutics. The tissue-level mechanisms underlying the cell-autonomous and non-cell-autonomous effects of KRas-G12D inhibitors are poorly understood. Additionally, the effectiveness of KRas-G12D inhibitors in lung cancer models remains unknown. To address these gaps in knowledge, we analyzed the spatial interactions between cancer cells and the surrounding tissue microenvironment during the process of tumor eradication mediated through KRas-G12D inhibitors. Methods: We utilized a genetic mouse model of non-small cell lung cancer (NSCLC), driven by the activation of KRas-G12D in combination with the loss of p53. We investigated the immune-mediated tumor recognition following the targeting of KRas-G12D in an immunocompetent setting. Lung samples were collected from control mice and treated. Spatial transcriptomic analysis (CosMxTM SMI 1,000-plex Mouse Universal Cell Characterization Panel) were employed to obtain a high-plex, single-cell, temporal and spatially resolved molecular atlas of lung tumor regression. Results: Prior to Kras inhibitor treatment, mice displayed both LuAD and lung adenomas. Lesion size and histological grade progressively decrease during pharmacological treatment with Kras inhibitor. 906 unique genes were detected above background on intact FFPE tissue slides, along with 4 protein markers for optimal single-cell segmentation results. Concordance between CosMx SMI and scRNAseq was assessed and demonstrated high assay sensitivity and specificity of the CosMx assay. LUAD cell subtypes were identified and showed distinct spatial features. Molecular states, and receptor-ligand interactions, within niche-specific signaling networks were investigated to underline molecular mechanism of immune attack and eventual eradication of tumors. Conclusion: This study provides novel insights into the temporal and spatial dynamics of KRas-G12D inhibitor-mediated tumor regression in lung cancer, shedding light on the previously unknown cell-cell interactions occurring during this process. By investigating these spatiotemporal aspects, we aim to enhance our understanding of lung cancer biology and potentially identify new immunotherapeutic biomarkers. Moreover, the research tools used in this study have implications for the design of future preclinical studies exploring the potential of immuno-oncology combination therapies. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Tito Panciera, Francesca Zanconato, Michelangelo Cordenonsi, Mattia Forcato, Giada Vanni, Silvio Bicciato, Julian Preciado, Saskia Ilcisin, Katrina V. Raay, Margaret Hoang, Michael Patrick, Shanshan He, Joseph Beechem, Stefano Piccolo. A single-cell spatially resolved atlas of immune-mediated control of lung adenocarcinoma using 1,000-plex single-cell spatial molecular imaging in a transgenic mouse model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1138.

Abstract B007: Early detection and risk stratification of pancreatic cancer using apolipoprotein A2-isoforms as a blood biomarker

Abstract To reduce the mortality rate of pancreatic cancer, there is an urgent need to develop a biomarker that can efficiently screen for pancreatic cancer in blood tests. We had identified the unique processing of C-terminal amino acids of apolipoprotein A2 homodimers, we named it apolipoprotein A2-isoforms (apoA2-i). ApoA2-i consists of three isoforms with different C-terminal amino acids. Especially, we had reported that apoA2-ATQ/AT, known as the intermediate isoform, was significantly reduced in the bloodstream of pancreatic adenocarcinoma (PDAC) patients compared to healthy controls. However, previous reports were investigated using a research use only (RUO) reagent, which could not be used in clinical settings. We generated a novel ELISA for measuring apoA2-i under the Japanese medical device Quality Management System requirements, and measured the concentration of apoA2-i in 2,732 of plasma samples. The clinical equivariance and significance of apoA2i were evaluated by pre-specified endpoints. The point estimate of the area under the curve to distinguish between PDAC and healthy controls was higher for apoA2-ATQ/AT [0.879, 95% confidence interval (CI): 0.832–0.925] than for CA19-9 (0.849, 95%CI: 0.793–0.905) and achieved the primary endpoint. The cut-off apoA2-ATQ/AT of 59.5 μg/mL was defined based on 95% specificity in 2,000 healthy samples. The sensitivity of apoA2-ATQ/AT for detecting both stage I (47.4%) and I/II (50%) of PDAC was higher than that of CA19-9 (36.8% and 46.7%, respectively). The combination of apoA2-ATQ/AT (cut-off, 59.5 μg/mL) and CA19-9 (37 U/mL) increased the sensitivity for pancreatic cancer to 87.7% compared with 69.8% for CA19-9 alone. ApoA2-ATQ/AT has equivalent or better clinical performance to CA19-9 as a blood biomarker. Citation Format: Kazufumi Honda, Ayumi H. Kashiro, Michimoto Kobayashi, Keiko Takeuchi, Yuya Shizume, Takanori Oh, Chigusa Morizane, Susumu Hijioka, Satoshi Nara. Early detection and risk stratification of pancreatic cancer using apolipoprotein A2-isoforms as a blood biomarker [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B007.

Validation of an Ultra-Sensitive Method for Quantitation of Phospho-Tau 217 (pTau217) in Human Plasma, Serum, and CSF using the ALZpath pTau217 Assay on the Quanterix HD-X Platform.

Both blood (plasma and serum) and CSF tau phosphorylated at Threonine 217 (pTau217) have been shown to be able to discriminate early to mild Alzheimer's disease (AD) from non-AD neurodegenerative disorders and healthy controls with high sensitivity and specificity. We report the full validation of the ALZpath ultra-sensitive pTau217 research-use only (RUO) assays for human EDTA plasma, serum, and CSF using the Quanterix Simoa HD-X platform, in support of clinical trials and early diagnosis of Alzheimer's disease. The ALZpath pTau217 Simoa Advantage v2 kit from ALZpath/Quanterix was used for method development and validation of pTau217 in human plasma, serum, and CSF. All three method validations have followed the 2018 FDA BMV and 2022 ICH M10 guidelines. Validation of pTau217 quantitation in human plasma, serum, and CSF demonstrated that the validated pTau217 assay has an analytical LLOQ of 0.00977 pg/mL. It is one of the most sensitive assays with a minimal required sample volume of 33.3 µl for plasma and serum, and 5 µl for CSF, and is relatively cost-effective, compared to the currently published data. The minimum required dilution (MRD) for plasma, serum, and CSF were determined. The analyte passed short-term stability tests. It was also tolerant of moderate hemolytic, and lipemic interferences in plasma and serum. pTau217 was detected in 100% of tested healthy control plasma, 90.0% of healthy control serum, 92.3% of healthy control CSF samples, and 100% of AD plasma and CSF samples. The validated assay was successfully applied in the analysis of AD samples, with data showing dramatic differences in the pTau217 levels between healthy control subjects and AD patients in both plasma and CSF. Validation of the ALZpath pTau217 Simoa assay in human plasma, serum, and CSF demonstrates ultra sensitivity, high accuracy, and assay robustness. Together with other established and sensitive assays for pTau181, GFAP, and NfL, these assays have immediate utility for application in clinical trials and can play a role in the early diagnosis of neurodegenerative diseases.

A complete pipeline for high‐plex spatial proteomic profiling and analysis of neural cell phenotypes on the CosMx™ Spatial Molecular Imager and AtoMx™ Spatial Informatics Platform

AbstractBackgroundThe brain is complex and heterogeneous where cell function and cell‐to‐cell communication are critical for rapid and accurate performance. The ability to explore protein‐driven activities at high resolution within spatial context of their immediate environment is critical to gain comprehensive pictures of brain development, activity, aging, disease or dysfunction, and inflammatory responses. Many existing approaches for high‐plex single cell spatial proteomics face issues around simplicity, speed, scalability, and big data analysis.MethodHere, we present an integrated workflow from sample through analysis that addresses key concerns around high plex proteomics. The CosMx™ Spatial Molecular Imager and AtoMx™ Spatial Informatics Platform comprises an end‐to‐end workflow that efficiently handles highly multiplex protein analysis at plex sizes exceeding 68 targets. The CosMx protein assays uses oligonucleotide conjugated antibodies, detected using universal, multi‐analyte CosMx readout reagents. The CosMx Mouse Neural Cell Typing and Alzheimer’s Pathology panel is optimized to comprehensively profile neural cell lineages across the brain as well as the progression of Alzheimer’s disease (AD), including specific antibodies for humanized mouse AD models. The AtoMx spatial informatics platform provides full analysis support, including whole‐slide image viewer, and methods for performing built‐in or fully customizable analyses for cell typing, ligand‐receptor analysis, neighborhood analysis and spatial differential expression.ResultThe CosMx protein assay reagents were validated on FFPE adult mouse brain, mouse embryo, and Alzheimer’s positive human brain. We used the CosMx Mouse Neural Cell Typing and Alzheimer’s Pathology panel with the CosMx Spatial Molecular Imager to identify multiple neuronal subtypes, different reactive states of astrocytes and microglial, cell degeneration and proliferation. Single cell exploration of mitochondria showed distinct patterning of key immune targets based on their immediate microenvironment.ConclusionCosMx SMI is a high‐plex spatial multi‐omics platform that enables detection of > 68 proteins at subcellular resolution. In combination with the high‐plex CosMx Mouse Neural Cell Typing and Alzheimer’s Pathology panel, we present a flexible and scalable informatics platform, a robust solution for comprehensive neural and disease phenotyping that captures the complexity of neuronal and glial cellular activity with full spatial context.FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.

Deep Learning for Circulating Multiple Myeloma Cell (CMMC) Enumeration with the Cellsearch System

Background Circulating Multiple Myeloma Cell (CMMC) enumeration in blood samples with the CELLSEARCH® system is a minimally invasive assay used to quantify plasma cells in patients with Multiple Myeloma (MM) and in precursor stages MGUS and SMM 1 particularly during disease stages when a bone marrow aspirate is not desirable (Foulk et al. 2017). Currently, CMMC identification is performed by human reviewers through visual assessment, which is a time-consuming procedure that could be affected by subjective interpretations. Modern Deep Learning (DL) methods can provide a solution by automating the process of CMMC identification, thus eliminating subjectivity and producing faster and more reproducible results. The purpose of this study was to train and test an automated algorithm (for research use only) based on DL models for CMMC identification in CELLSEARCH® fluorescent images. Methods The DL algorithm was designed to analyze images using a segmentation and a classification network as presented in recent studies (Zeune et al. Nature MI 2020; Coumans et al. ACTC 2021). The DL classification model was trained on 5139 CMMC and 16235 non-CMMC images (training set) of fully anonymized blood samples from the CoMMpass study (NCT01454297 sponsored by the Multiple Myeloma Research Foundation) scanned by CELLTRACKS ANALYZER II® (CTAII). The test set was composed of 75 samples from the CoMMpass study with 1000 images per sample reviewed by an operator (with training and experience of reviewing CTAII images) and processed by the algorithm, for a total of 75000 images. The algorithm was compared with the human reviewer in terms of overall agreement and Cohen's Kappa of the image classification results and of correlation for the CMMC enumeration results per sample. Results In the test dataset, out of 75000 images in total the reviewer identified 32403 CMMCs and the algorithm 32842 CMMCs. The DL algorithm and the reviewer provided the same classification for 71711 images, thus showing very high agreement = 95.6% (Cohen's Kappa = 0.91). CMMC counts per sample and linear regression are shown in the figure: slope = 0.95 (95% CI = 0.02), intercept = 26.99 (95% CI = 11.56) and coefficient of determination R 2 = 0.99. Conclusion These preliminary results show the potential of applying automated algorithms to CMMC identification with the CELLSEARCH® system in order to remove human subjectivity from the review process, thus maximizing standardization among different research centers. 1) The CMMC assay is run in a CLIA/CAP certified laboratory in the US and is also New York State CLEP approved. In the EU, the CMMC assay is research use only (RUO).

Analytical Performance and Concordance with Next-Generation Sequencing of a Rapid, Multiplexed dPCR Panel for the Detection of DNA and RNA Biomarkers in Non-Small-Cell Lung Cancer

FDA approval of targeted therapies for lung cancer has significantly improved patient survival rates. Despite these improvements, barriers to timely access to biomarker information, such as nucleic acid input, still exist. Here, we report the analytical performance and concordance with next-generation sequencing (NGS) of a highly multiplexed research-use-only (RUO) panel using digital PCR (dPCR). The panel’s analytical sensitivity and reactivity were determined using contrived DNA and RNA mixes. The limit of blank was established by testing FFPE curls classified as negative by pathology. Concordance was established on 77 FFPE samples previously characterized using the Oncomine Precision Assay®, and any discordant results were resolved with Archer Fusionplex® and Variantplex® panels. The analytical sensitivity, reported as the estimated mutant allele fraction (MAF), for DNA targets ranged from 0.1 to 0.9%. For RNA targets (ALK, RET, ROS, NTRK 1/2/3 Fusions, and MET Exon 14 skipping alteration), the analytical sensitivity ranged from 23 to 101 detected counts with 5 ng of total RNA input. The population prevalence-based coverage ranged from 89.2% to 100.0% across targets and exceeded 99.0% in aggregate. The assay demonstrated >97% concordance with respect to the comparator method.

Nucleic acid testing for monkeypox in United States blood donor specimens.

The 2022 multi-country outbreak of monkeypox (mpox) resulted in blood collection and public health agencies closely monitoring for changes in transmission dynamics that could pose a threat to the blood supply. While mpox virus (MPXV) is not known to be transfusion transmissible, there have been several studies demonstrating the detection of MPXV in blood. We evaluated the performance characteristics of a research use only (RUO) nucleic acid amplification test for MPXV. The assay was developed to detect MPXV DNA in plasma and serum specimens from human blood donors. The sensitivity of the RUO MPXV Assay was determined using a synthetic DNA sequence, purified full-length genomic DNA, and a chemically inactivated virus. Specificity was determined using fresh plasma samples collected from blood donors during the outbreak. Plasma samples collected from donors considered at increased risk for exposure to mpox were also tested. For sensitivity, the 95% limit of detection (LOD) ranged from 0.26 copies/mL (inactivated virus) to 31.65 copies/mL (synthetic DNA) to 166.61 copies/mL (for full-length DNA). All donor samples tested with the RUO MPXV Assay were nonreactive, resulting in a specificity of 100% (95% CI, 99.93%-100.00%). The RUO MPXV Assay was developed as a potential blood donation screening assay in response to the outbreak. While not directly comparable, the 95% LOD fiducial limits obtained from partial- and full-length DNA analysis were similar to other manufacturers' MPXV assays. Additionally, this assay demonstrated high specificity for screening blood donors.

Research use only and cell population data items obtained from the Beckman Coulter DxH800 automated hematology analyzer are useful in discriminating MDS patients from those with cytopenia without MDS.

We investigated the performance of research use only/cell population data (RUO/CPD) items obtained from the Beckman Coulter DxH800 automated hematologic analyzer in discriminating MDS patients from cytopenic patients without MDS.Total of 14 routine CBC, 18 research use only (RUO) items, and 70 CPD items were obtained retrospectively at diagnosis. The results were then compared between 94 MDS patients and 100 cytopenic patients without MDS. In items with statistically significant differences, receiver operating characteristic (ROC) analysis was performed and the results were compared.Four CBC/RUO items [red cell distribution width-standard deviation (RDW-SD), immature reticulocyte fraction (IRF), mean sphered cell volume (MSCV), high light scatter reticulocytes (HLR)], and two CPD items [mean volume of neutrophils (NE-V-Mean) and mean volume of early granulated cells (EGC-V-Mean)] showed area-under the curve (AUC) scores > 0.750. Notably, four RUO/CPD items (MSCV > 81.4/HLR > 0.15%/NE-V-Mean > 145/EGC-V-Mean > 156) showed high sensitivity (91.9%/93.6%/88.1%/90.2%, respectively) in discriminating MDS patients from cytopenic patients without MDS. With these six items, scores ≥ 4 (defined as ≥ 4 items exceeding cutoff values out of six items) showed AUC scores/sensitivity/specificity/accuracy (0.891/87.3%/79.0%/83.0%, respectively).Six CBC/RUO/CPD items showed satisfactory AUC scores of > 0.750, and four RUO/CPD items showed high sensitivity in discriminating MDS patients from cytopenic patients without MDS. Scoring system with six items showed high sensitivity, specificity, and accuracy with decision criteria of ≥ 4 scores. Therefore, DxH800 RUO/CPD items would be useful in discriminating MDS patients from cytopenic patients without MDS.

Abstract 615: Spatially resolved expression of T cell receptors elucidates spatial relationships between T cells, immune infiltration, and cancer-associated pathways

Abstract Spatial distribution of T cells is key in understanding the escape of tumors from immune surveillance via the adaptive immune response, including interactions between immune cells and the surrounding tumor microenvironment. T cells are critical to the adaptive immune response to pathogens and cancers, mediating an antigen-specific response through both specificity and diversity of T cell receptor (TCR) clonotypes. Many methods exist to determine specific clonotypes and overall TCR diversity present from bulk tissues or sorted cell populations; however, nearly all fail to capture spatial orientation and arrangement of T cells engaging with their microenvironment, and most require large amounts of starting material from precious samples. Here, we present a TCR expression profiling panel for the GeoMx® Digital Spatial Profiler that can be combined with the GeoMx Cancer Transcriptome Atlas (CTA) or Human Whole Transcriptome Atlas (WTA) on archival formalin-fixed paraffin embedded (FFPE) tissue specimens. This represents the first commercial spatial expression profiling assay for the simultaneous quantification of TCR constant, variable, and joining segments in situ. We show reliable sensitivity and specificity (>90%) with respect to orthogonal sequencing and robust detection of TCR chains with evidence of clonal expansion and CD8 infiltration across tumor regions in colorectal cancer tissue. These events also corresponded to increased signatures of exhaustion from the T cells and suggest that the T cells resident in or near the tumor are tumor-specific and poised for activation via checkpoint blockade. Signaling pathways and tumor-specific signatures were also evaluated to look for mechanisms through which tumor cells respond to T cell infiltration. We further validated the performance of the TCR probe pool in cell pellet arrays with orthogonal TCR sequencing, tonsil and colorectal cancer tissues. Together, the combination of our TCR add-on panel with the CTA or WTA illuminates T cell phenotypes, signaling pathways, population dynamics, and transcriptomic changes, yielding an unparalleled view of the T cell response in any context. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Katrina van Raay, Michelle Kriner, Jason Reeves, Erin Piazza, Hargita Kaplan, John Vivian, Francis Fernandez, Margaret Hoang, Joseph Beechem. Spatially resolved expression of T cell receptors elucidates spatial relationships between T cells, immune infiltration, and cancer-associated pathways [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 615.

Abstract 6765: Spatial insights into tumor immune evasion illuminated with 1000-plex RNA profiling with CosMx Spatial Molecular Imager

Abstract Patient response to immunotherapy has been revolutionary but remains limited due to the inability to convert excluded or cold tumors into ones which would be permissive to therapeutic intervention. To treat patients that evade immune therapy, comprehensive understanding of their tumor microenvironment (TME) is needed. To date, most profiling efforts have lacked the ability to capture high-plex ‘omics data while retaining the spatial architecture of the TME. We developed the CosMx™ Spatial Molecular Imager (SMI) for analyzing formalin-fixed paraffin-embedded (FFPE) or fresh-frozen (FF) tissue and capturing the expression of over 1000 RNA targets simultaneously with subcellular resolution from a single histopathology slide. We profiled a cohort of 16 slides with CosMx using the Human Universal Cell Characterization (UCC) Panel across a range of solid tumors. This cohort represents a diverse array of patients which include both infiltrated and excluded tumors. We included technical replicates for 5 of the samples to better understand reproducibility of the assay. We were able to characterize over 4.5 million cells and detected on average over 80% of the panel per patient and assigning more than 95% of the transcripts profiled to unique cells across these samples. We were able to robustly identify more than 20 cell types by integrating our data with previous single-cell sequencing projects from the human cell atlas. We demonstrate robust delineation of critical immune cell populations from across lymphoid and myeloid lineages, as well as stromal cell populations inclusive of cell types frequently missed using dissociated cell sequencing, such as vascular endothelium associated with immune cell migration into the tumor bed. We leveraged 450+ genes from our panel dedicated to cell lineage, cell-cell interaction, and ligand-receptor signaling to identify unique interactions occurring at different scales between the tumor and the TME. We find that diverse mechanisms of immune evasion can be captured, and a clear role for cell types such as SPP1+ Macrophages emerges in multiple cancer types. Utilizing the CosMx platform to profile tissues allows for robust resolution of critical immunogenic signaling cascades and cellular interactions that are necessary to truly understand the tumor architecture. By maintaining the tissue structure, we can directly measure cellular interactions and capture cells commonly missed during dissociative studies. With this new platform, we are better poised than ever to truly understand the molecular mechanisms that drive tumor response to intervention. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures Citation Format: Claire Williams, Jason W. Reeves, Patrick Danaher, Shanshan He, Sean Kim, Michael Patrick, Julian Preciado, Mark Gregory, Zach Reitz, Justin Jenkins, Rachel Liu, Sarah Murphy, Christine Kang, Byron Hartman, Vikram Devgan, Michael Rhodes, Joseph Beechem. Spatial insights into tumor immune evasion illuminated with 1000-plex RNA profiling with CosMx Spatial Molecular Imager [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6765.

Abstract 4617: A complete pipeline for high-plex spatial proteomic profiling and analysis on the cosmxtm spatial molecular imager and atomtm spatial informatics platform

Abstract Detecting and analyzing large numbers of proteins using whole-slide imaging is critical for a comprehensive picture of immune response to cancer. Many existing approaches for high-plex proteomics face issues around simplicity, speed, scalability, and big data analysis. Here, we present an integrated workflow from sample preparation through downstream analysis that addresses many key concerns around high plex proteomics. The CosMx Spatial Molecular Imager (SMI) and AtoMx Spatial Informatics Platform (SIP) comprise of a turnkey, end-to-end workflow that efficiently handles highly multiplex protein analysis at plex sizes exceeding 110 targets. We demonstrate an extension of our commercially available 64-plex human immuno-oncology panel to higher numbers of targets and show how the cloud computing-enabled AtoMx SIP allows flexible construction of analytic pipelines for cell typing and spatial analyses. The CosMx protein assay uses antibodies conjugated with oligonucleotides, which are detected using universal, multi-analyte CosMx readout reagents. The CosMx Human Immuno-oncology panel was optimized to comprehensively profile lymphoid and stromal lineages within the tumor microenvironment as well as markers of cancer signaling and progression. Each CosMx SMI antibody was validated on multi-organ FFPE tissue microarrays covering prevalent solid tumor types with matched controls, and 52 human FFPE cell lines, including overexpression lines for key targets such as GITR, CD278, PD-L1, and PD-1. CosMx SMI uses a deep learning algorithm to segment whole cells and a semi-supervised algorithm to classify cell types. The AtoMx SIP provides full analysis support, including a whole-slide image viewer, and methods for performing built-in or fully customizable analyses for cell typing, ligand-receptor analysis, neighborhood analysis and spatial differential expression. Within the cancer sample profiled, we performed in-depth single-cell proteomic profiling across different cell populations. We detected TLS, characterized TLS maturation, and identified immune interactions with the tumor microenvironment. The CosMx SMI assay profiled the composition and spatial organization of infiltrating immune cells within and around the tumor microenvironment. We found that markers of T cell activation and exhaustion varied across the tumor landscape. CosMx SMI is a high-plex spatial multi-omics platform that enables detection of more than 110 proteins at subcellular resolution in real-world FFPE tissues. The extensibility of the CosMx protein assay to large numbers of protein targets and our flexible, scalable bioinformatic platform provides a straightforward and robust solution for comprehensive immune phenotyping with full spatial context. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Tien Phan-Everson, Zachary Lewis, Giang Ong, Yan Liang, Emily Brown, Liuliu Pan, Aster Wardhani, Mithra Korukonda, Carl Brown, Dwayne Dunaway, Edward Zhao, Dan McGuire, Sangsoon Woo, Alyssa Rosenbloom, Brian Filanoski, Rhonda Meredith, Kan Chantranuvatana, Brian Birditt, Hye Son Yi, Erin Piazza, Jason Reeves, John Lyssand, Vik Devgan, Michael Rhodes, Gary Geiss, Joseph Beechem. A complete pipeline for high-plex spatial proteomic profiling and analysis on the cosmxtm spatial molecular imager and atomtm spatial informatics platform. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4617.

Structure and content of the EU-IVDR

Regulation (EU) 2017/746 on in vitro diagnostic medical devices (IVDR) was passed by the European Parliament and the Council of the European Union on 5 April 2017 and came into force on 26 May 2017. Anew amending regulation, which introduces aphased implementation of the IVDR with new transitional provisions for certain in vitro diagnostic medical devices (IVDs) and alater date of application of some requirements for in-house devices for healthcare facilities, was adopted on 15 December 2021. The combined use of CE-certified IVDs (CE-IVDs), in-house IVDs (IH-IVDs), and research use only (RUO) devices are acornerstone of diagnostics in pathology departments and crucial for optimal patient care. The IVDR not only regulates the manufacture and placement on the market of industrially manufactured IVDs, but also imposes conditions on the manufacture and use of IH-IVDs for internal use by healthcare facilities. Our work provides an overview of the background and structure of the IVDR and identifies core areas that need to be interpreted and fleshed out in the context of the legal framework as well as expert knowledge. The gaps and ambiguities in the IVDR crucially require the expertise of professional societies, alliances, and individual stakeholders to successfully facilitate the implementation and use of the IVDR in pathology departments and to avoid aberrant developments.

Mpox infection investigation using multiplexed syndromic diagnostics: Evaluation of an AusDiagnostics multiplexed tandem PCR (MT-PCR) syndromic panel

BackgroundDetection of mpox virus during investigation of viral vesicular rash illness is required to identify mpox infection. ObjectivesThis study evaluated the performance of a research-use-only (RUO) AusDiagnostics MT-PCR syndromic assay containing an mpox virus target. MethodsThe analytical specificity and limit of detection (LoD) of the AusDiagnostics MT-PCR mpox assay was verified using control material. Clinical performance was evaluated using anonymised residual nucleic acids extracted from swab specimens previously tested for mpox virus using a laboratory developed test (LDT). Residual nucleic acids were derived from consecutive sample panels collected during two periods in the 2022 mpox outbreak. ResultsThe AusDiagnostics MT-PCR assay demonstrated an LoD of 35 input copies of mpox virus and correctly detected all relevant members of a specificity panel (n = 34). 175 residual nucleic acids were included in the study with a prevalence of mpox of 40.0% (95%CI 32.7–47.6). The AusDiagnostics MT-PCR mpox assay demonstrated an accuracy of 98.9% (95%CI 93.8–99.9), sensitivity of 94.2% (95%CI 85.2 – 98.1) and specificity of 100% (95%CI 95.6 -100), when compared to the LDT qPCR assay. The AusDiagnostics MT-PCR mpox assay detected additional vesicular rash pathogens in 26.8% samples. Co-detection with other vesicular rash pathogens was described in 12.8% of mpox virus detected samples ConclusionsPerformance of the RUO AusDiagnostics MT-PCR mpox assay was comparable to an LDT qPCR for the detection of mpox virus in nucleic acids extracted from swab specimens. The RUO AusDiagnostics MT-PCR mpox assay facilitated the simultaneous detection of additional infective etiologies of vesicular rash syndromes.