Robust Workflow Research Articles

P17.03.B Modelling migration of glioblastoma patient-derived cells using human iPSC-derived neural spheroid and high content analysis

Abstract Background Glioblastoma multiforme (GBM) is the most common and aggressive brain tumour in adults. Despite current advances, the existing standard of treatment is ineffective, and the survival prognosis remains just over a year from diagnosis. Migrating tumour cells have been implicated in the therapeutic resistance of GBM. They spread by interacting with structures such as white matter tracts and inevitably cause recurrence of the tumour. Valuable cell models able to capture the invasiveness of GBM are critically needed to develop innovative therapies targeting migrating GBM cells. Material and Methods We established an in vitro model mimicking the GBM microenvironment by co-culturing patient-derived GBM cells and human induced pluripotent stem cell-derived cortical neural spheroids with radiating axons. Using high content imaging, we developed a robust workflow to quantify the GBM cells infiltration of the neural spheroid in endpoint assays. Images were acquired on the Operetta CLS high content device (Perkin Elmer) and analysed using the built-in Harmony Imaging and Analysis Software. We also performed live imaging assays using the Livecyte quantitative phase imager (Phasefocus), in which we studied the directionality, displacement and speed of the GBM cells engaged on axons. Results Our data indicate that GBM cells change morphology when cultured on axons and that they migrated towards the neural spheroid once engaged on axons. We showed that cell lines from different patients vary in migratory properties as well as in levels of infiltration capability. Finally, we used this model to test several antagonists to pathways involved in migration of GBM cells. Conclusion The main deliverable of this project is the setup of a novel model able to mimic the GBM migration on axons and able to screen for compounds affecting cell migration. This could potentially offer innovative precision-medicine therapies.

PNGase H + variant from Rudaea cellulosilytica with improved deglycosylation efficiency for rapid analysis of eukaryotic N-glycans and hydrogen deuterium exchange mass spectrometry analysis of glycoproteins.

The analysis of glycoproteins and the comparison of protein N‐glycosylation from different eukaryotic origins require unbiased and robust analytical workflows. The structural and functional analysis of vertebrate protein N‐glycosylation currently depends extensively on bacterial peptide‐N4‐(N‐acetyl‐β‐glucosaminyl) asparagine amidases (PNGases), which are indispensable enzymatic tools in releasing asparagine‐linked oligosaccharides (N‐glycans) from glycoproteins. So far, only limited PNGase candidates are available for N‐glycans analysis, and particularly the analysis of plant and invertebrate N‐glycans is hampered by the lack of suitable PNGases. Furthermore, liquid chromatography–mass spectrometry (LC–MS) workflows, such as hydrogen deuterium exchange mass spectrometry (HDX‐MS), require a highly efficient enzymatic release of N‐glycans at low pH values to facilitate the comprehensive structural analysis of glycoproteins. Herein, we describe a previously unstudied superacidic bacterial N‐glycanase (PNGase H+) originating from the soil bacterium Rudaea cellulosilytica (Rc), which has significantly improved enzymatic properties compared to previously described PNGase H+ variants. Active and soluble recombinant PNGase Rc was expressed at a higher protein level (3.8‐fold) and with higher specific activity (~56% increase) compared to the currently used PNGase H+ variant from Dyella japonicum (Dj). Recombinant PNGase Rc was able to deglycosylate the glycoproteins horseradish peroxidase and bovine lactoferrin significantly faster than PNGase Dj (10 min vs. 6 h). The versatility of PNGase Rc was demonstrated by releasing N‐glycans from a diverse array of samples such as peach fruit, king trumpet mushroom, mouse serum, and the soil nematode Caenorhabditis elegans . The presence of only two disulfide bonds shown in the AlphaFold protein model (so far all other superacidic PNGases possess more disulfide bonds) could be corroborated by intact mass‐ and peptide mapping analysis and provides a possible explanation for the improved recombinant expression yield of PNGase Rc.

Understanding Powder Behavior in an Additive Manufacturing Process Using DEM

The handling of bulk solids in the form of powders is a fundamental process in a wide range of manufacturing industries, such as the automotive, aerospace, food, and healthcare sectors. All these sectors employ additive manufacturing (AM), as it enables the production of complex parts in a short amount of time. Thus, it is considered an established method for developing an agile manufacturing environment that can drastically reduce the lead time from conception to the production stage. At the same time, powder is a unique material sensitive to environmental and machine conditions; hence, establishing an optimal configuration is not straight-forward. This work presents a discrete element method (DEM) simulation of an experimental dosing system used in AM. We introduce a robust workflow that correlates suitable experimental data with simulation results, establishing models of real powders with different flowability. The results showed an excellent agreement between the experimental data and the simulation results and provided a better understanding of the material behavior. Furthermore, we employed a coarse-grained approach to extract continuum fields from the discrete data. The results showed that the cohesion level in the system was enough to create agglomerates that hindered the transport of the material and produced nonuniform distribution.

Endothelial Responses to Curvature-Induced Flow Patterns in Engineered Cerebral Aneurysms.

Hemodynamic factors have long been associated with clinical outcomes in the treatment of cerebral aneurysms. Computational studies of cerebral aneurysm hemodynamics have provided valuable estimates of the mechanical environment experienced by the endothelium in both the parent vessel and aneurysmal dome walls and have correlated them with disease state. These computational-clinical studies have recently been correlated with the response of endothelial cells (EC) using either idealized or patient-specific models. Here, we present a robust workflow for generating anatomic-scale aneurysm models, establishing luminal cultures of ECs at physiological relevant flow profiles, and comparing EC responses to curvature mediated flow. We show that flow patterns induced by parent vessel curvature produce changes in wall shear stress (WSS) and wall shear stress gradients (WSSG) that are correlated with differences in cell morphology and cellular protein localization. Cells in higher WSS regions align better with the flow and display strong Notch1-extracellular domain (ECD) polarization, while, under low WSS, differences in WSSG due to curvature change were associated with less alignment and attenuation of Notch1-ECD polarization in ECs of the corresponding regions. These proof-of-concept results highlight the use of engineered cellularized aneurysm models for connecting computational fluid dynamics to the underlying endothelial biology that mediates disease.

Reaching new sensitivity levels for the detection of fentanyl analogs and highly potent novel synthetic opioids in blood

The aim of this presentation is to demonstrate a sensitive quantitative workflow for the analysis of 32 of potent substances in poly-drug, discarded postmortem case samples at low (pg/mL) levels. The presentation will demonstrate that the unparalleled quantification performance of the method enabled accurate detection of potent substances in poly-drug, discarded postmortem case samples at trace levels that were not previously achievable, providing toxicologists a valuable insight into the causation of accidental overdoses. A total of 32 NSO including 17 fentanyl analogs and 15 newly emerging non-fentanyl opioids were selected for this panel. NSO were extracted from the 200 μL of spiked whole blood mixtures using a liquid-liquid extraction (LLE) procedure. Analytes were chromatographically separated using a Phenomenex Kinetex C18 column (50 × 3.0 mm, 2.6 μm, 00B-4462-Y0). Mobile phase A (MPA) and mobile phase B (MPB) were ammonium formate with formic acid and formic acid in methanol and acetonitrile, respectively. The injection volume was 10 μL and the total LC runtime was 15.5 minutes. A single acquisition method consisting of 68 MRM transitions (64 for the NSO and 4 for the internal standards) was created using the Scheduled MRM Algorithm. Control human whole blood samples spiked with the 32 target analytes were prepared at concentrations ranging from 1 pg/mL to 100 ng/mL. Excellent linearity was observed across the concentration ranges analyzed with R2 values greater than 0.99 for all of the NPS in the panel. Reported LLOQ values ranged between 10 to 50 pg/mL for the 32 analytes in the panel. The accuracy and precision of measurements ranged from 80.50–116.64% and from 0.42–17.80%, respectively. The excellent accuracy and precision were observed over the entire concentration range, including at the LLOQ. Overall, the developed method showed excellent reproducibility and linearity, proving the robustness of the developed method and quantitative performance of the SCIEX 7500 System even at low concentration levels for each of the targeted NSO in this study. The applicability of the method to analyze discarded postmortem case samples from subjects suspected of NPS ingestion resulting in accidental overdoses was investigated. For example, the results from the analysis of one of these case samples showed the successful detection of one NSO and its metabolite: isotonitazene and 5-aminoisotonitazene, as well as fentanyl and four of its analogs/metabolites: beta-hydroxy-fentanyl, norfentanyl, 4-ANPP and acetyl fentanyl at concentrations of 1434.33, 7.93, 599.10, 9756.67, 147.69 and 1465.00 pg/mL, respectively. The results demonstrate that the developed method enabled accurate detection of potent substances in poly-drug, authentic case samples at trace levels that were not previously achievable. A robust and sensitive drug screening workflow for the analysis of 32 potent NSO was successfully developed using the SCIEX 7500 System. Overall, the remarkable quantification performance of the SCIEX 7500 System enabled accurate detection of potent NSO at concentrations that were not previously achievable, providing a means to monitor ultra-potent NSO in overdose scenarios. The sensitivity levels afforded by the SCIEX 7500 system provided the ability to detect low levels of NSO in postmortem case samples that would normally go undetected, providing a clearer picture for help in determining the cause of death.

CfDNA methylome profiling for detection and subtyping of small cell lung cancers

Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients’ circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.

A robust workflow to study protein-correlated motion from ambient-temperature crystallography and total scattering

A robust workflow to study protein-correlated motion from ambient-temperature crystallography and total scattering

Three-Dimensional, Km-Scale Hyperspectral Data of Well-Exposed Zn–Pb Mineralization at Black Angel Mountain, Greenland

Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. As with any novel technology, robust processing workflows are required to ensure a wide use. We present an open-source hypercloud dataset capturing the complex but spectacularly well exposed geology from the Black Angel Mountain in Maarmorilik, West Greenland, alongside a detailed and interactive tutorial documenting relevant processing workflows. This contribution relies on very recent progress made on the correction, interpretation and integration of hyperspectral data in earth sciences. The possibility to fuse hyperspectral scans with 3D point cloud representations (hyperclouds) has opened up new possibilities for the mapping of complex natural targets. Spectroscopic and machine learning tools allow or the rapid and accurate characterization of geological structures in a 3D environment. Potential users can use this exemplary dataset and the associated tools to train themselves or test new algorithms. As the data and the tools have a wide range of application, we expect this contribution to benefit the scientific community at large.

Multi-Phenotypic Exosome Secretion Profiling Microfluidic Platform for Exploring Single-Cell Heterogeneity.

Cellular phenotypic and functional heterogeneities have advanced cancer evolution and treatment resistance. Although exosome-bound proteins reflect cellular functions, single-cell exosomes are rarely profiled owing to the lack of effective platforms. Herein, the authors developed an integrated microfluidic platform consisting of a single-cell trapping chip and a spatially coded antibody barcode chip for the multiplexed outline of exosome secretion by single cells. Using this platform, five phenotypic exosomes of over 1000 single cells are simultaneously profiled, in addition to inflammatory factor secretion from the same single cell. Also, a robust analysis workflow for single-cell secretion profiling is proposed to explore the intercellular heterogeneity, which integrated unsupervised clustering and linear clustering. When applied to the tumor cell lines of epithelial-origin and normal epithelial cell lines, the strategy identifies functionally heterogeneous subpopulations with unique secretion patterns. Notably, special functional cell subsets for unique phenotypic exosomes (HSP70+ , EPCAM+ ) are found within ovarian tumor cells. The strategy proposed offers a new analysis approach for cellular differential exosome secretion at single-cell resolution using inflammatory factors, ultimately reinforcing the understanding of cell-to-cell heterogeneity and tumor landscape, and providing a valuable universal platform for single-cell biomarker exploration in biological and clinical research.

Occurrence and Ecological Impact of Chemical Mixtures in a Semiclosed Sea by Suspect Screening Analysis.

Stress from mixtures of synthetic chemicals is among the key issues that have significant adverse impacts on the marine ecosystems. A robust screening workflow integrating toxicological-based ranking schemes is still deficient for comprehensive investigation on the main constituents in chemical mixtures that contribute to the ecological risks. In this study, the presence and compositions of a collection of priority pollutants were monitored by suspect screening analysis of seawater and estuarine water samples from the semiclosed Bohai Sea. In total, 108 organic pollutants in nine use categories were identified. Pesticides, intermediates, plastic additives, and per- and polyfluoroalkyl substances were the extensively detected chemical groups. Varied distribution patterns of the pollutants were illustrated intuitively in distinctive sampling areas by hierarchical cluster analysis, which were mainly influenced by run-off inputs, ocean currents, and chemical use history. Ecological risks of chemicals with quantified residue levels were first assessed by the toxicity-weighted concentration ranking scheme, and pentachlorophenol was found as the main contributor in the investigating areas. By optimization of multiple alternative variables (e.g., instrumental response and detection frequency), extended ranking of all the identified pollutants was plausible under the toxicological priority index framework. Similarity in toxicological endpoints of the prioritized pollutants could further been screened by ToxAlerts. Aromatic amine was highlighted as the most frequently detected structural alert (SA) for genotoxic carcinogenicity and mutagenicity. These findings fully demonstrate rationality of the ranking schemes integrated into the suspect screening analysis for profiling contamination characteristics, assessing ecological risk potentials, and prioritizing SAs.

The Quest for Anti-α-Synuclein Antibody Specificity-Lessons Learnt From Flow Cytometry Analysis.

The accumulation of alpha-synuclein (aSyn) is the hallmark of a group of neurodegenerative conditions termed synucleopathies. Physiological functions of aSyn, including those outside of the CNS, remain elusive. However, a reliable and reproducible evaluation of aSyn protein expression in different cell types and especially in low-expressing cells is impeded by the existence of a huge variety of poorly characterized anti-aSyn antibodies and a lack of a routinely used sensitive detection methods. Here, we developed a robust flow cytometry-based workflow for aSyn detection and antibody validation. We test our workflow using three commercially available antibodies (MJFR1, LB509, and 2A7) in a variety of human cell types, including induced pluripotent stem cells, T lymphocytes, and fibroblasts, and provide a cell- and antibody-specific map for aSyn expression. Strikingly, we demonstrate a previously unobserved unspecificity of the LB509 antibody, while the MJFR1 clone revealed specific aSyn binding however with low sensitivity. On the other hand, we identified an aSyn-specific antibody clone 2A7 with an optimal sensitivity for detecting aSyn in a range of cell types, including those with low aSyn expression. We further utilize our workflow to demonstrate the ability of the 2A7 antibody to distinguish between physiological differences in aSyn expression in neuronal and non-neuronal cells from the cortical organoids, and in neural progenitors and midbrain dopaminergic neurons from healthy controls and in patients with Parkinson's disease who have aSyn gene locus duplication. Our results provide a proof of principle for the use of high-throughput flow cytometry-based analysis of aSyn and highlight the necessity of rigorous aSyn antibody validation to facilitate the research of aSyn physiology and pathology.

A Combination of MALDI-TOF MS Proteomics and Species-Unique Biomarkers' Discovery for Rapid Screening of Brucellosis.

Brucellosis is considered to be a zoonotic infection with a predominant incidence in most parts of Iran that may even simply involve diagnostic laboratory personnel. In the present study, we apply matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for rapid and reliable discrimination of Brucella abortus and Brucella melitensis, based on proteomic mass patterns from chemically treated whole-cell analyses. Biomarkers of the low molecular weight proteome in the MALDI-TOF MS spectra were assigned to conserved ribosomal and structural protein families that were found in genome assemblies of B. abortus and B. melitensis in the NCBI database. Significant protein mass signals successfully mapped to ribosomal proteins and structural proteins, such as integration host factor subunit alpha, cold-shock proteins, HU family DNA-binding protein, ATP synthase subunit C, and GNAT family N-acetyltransferase, with specific biomarker peaks that have been identified for each virulent and vaccine strain. Web-accessible bioinformatics algorithms, with a robust data analysis workflow, followed by ribosomal and structural protein mapping, significantly enhanced the reliable assignment of key proteins and accurate identification of Brucella species. Furthermore, clinical samples were analyzed to confirm the most dominant protein biomarker candidates and their relevance for the identifications of B. melitensis and B. abortus. With proper optimization, we envision that the presented MALDI-TOF MS proteomics analyses, coupled with special usage of bioinformatics, could be used as a cost-efficient strategy for the diagnostics of brucellosis and introduce a reliable identification protocol for species of dangerous bacteria.

GREPore-seq: A Robust Workflow to Detect Changes After Gene Editing Through Long-range PCR and Nanopore Sequencing

To achieve the enormous potential of gene-editing technology in clinical therapies, one needs to evaluate both the on-target efficiency and unintended editing consequences comprehensively. However, there is a lack of a pipelined, large-scale, and economical workflow for detecting genome editing outcomes, in particular insertion or deletion of a large fragment. Here, we describe an approach for efficient and accurate detection of multiple genetic changes after CRISPR/Cas9 editing by pooled nanopore sequencing of barcoded long-range PCR products. Recognizing the high error rates of Oxford nanopore sequencing, we developed a novel pipeline to capture the barcoded sequences by grepping reads of nanopore amplicon sequencing (GREPore-seq). GREPore-seq can assess nonhomologous end-joining (NHEJ)-mediated double-stranded oligodeoxynucleotide (dsODN) insertions with comparable accuracy to Illumina next-generation sequencing (NGS). GREPore-seq also reveals a full spectrum of homology-directed repair (HDR)-mediated large gene knock-in, correlating well with the fluorescence-activated cell sorting (FACS) analysis results. Of note, we discovered low-level fragmented and full-length plasmid backbone insertion at the CRISPR cutting site. Therefore, we have established a practical workflow to evaluate various genetic changes, including quantifying insertions of short dsODNs, knock-ins of long pieces, plasmid insertions, and large fragment deletions after CRISPR/Cas9-mediated editing. GREPore-seq is freely available at GitHub (https://github.com/lisiang/GREPore-seq) and the National Genomics Data Center (NGDC) BioCode (https://ngdc.cncb.ac.cn/biocode/tools/BT007293).

Pathogen profiling of Australian rabbits by metatranscriptomic sequencing.

Australia is known for its long history of using biocontrol agents, such as myxoma virus (MYXV) and rabbit haemorrhagic disease virus (RHDV), to manage wild European rabbit populations. Interestingly, while undertaking RHDV surveillance of rabbits that were found dead, we observed that approximately 40% of samples were negative for RHDV. To investigate whether other infectious agents are responsible for killing rabbits in Australia, we subjected a subset of these RHDV-negative liver samples to metatranscriptomic sequencing. In addition, we investigated whether the host transcriptome data could provide additional differentiation between likely infectious versus non-infectious causes of death. We identified transcripts from several Clostridia species, Pasteurella multocida, Pseudomonas spp., and Eimeria stiedae, in liver samples of several rabbits that had died suddenly, all of which are known to infect rabbits and are capable of causing disease and mortality. In addition, we identified Hepatitis E virus and Cyniclomyces yeast in some samples, both of which are not usually associated with severe disease. In one-third of the sequenced total liver RNAs, no infectious agent could be identified. While metatranscriptomic sequencing cannot provide definitive evidence of causation, additional host transcriptome analysis provided further insights to distinguish between pathogenic microbes and commensals or environmental contaminants. Interestingly, three samples where no pathogen could be identified showed evidence of up-regulated host immune responses, while immune response pathways were not up-regulated when E. stiedae, Pseudomonas, or yeast were detected. In summary, although no new putative rabbit pathogens were identified, this study provides a robust workflow for future investigations into rabbit mortality events.

Establishing workflow for locoregionally advanced nasopharyngeal carcinoma (NPC) patients undergoing induction chemotherapy (IC) prior to radiation therapy (RT)

Purpose: Treatment management for locoregionally advanced nasopharyngeal carcinoma (NPC) patients involves concurrent radiation therapy (RT) and chemotherapy. Phase III clinical trial by Sun Yat-sen University Cancer Center, introduced Gemcitabine (Gem) and Cisplatin (Cis) as induction chemotherapy (IC) regime prior to concurrent chemo-radiotherapy (CCRT). This study reported 3-year recurrence-free survival of 85.3% in IC followed by CCRT, which corresponded to 4.3% higher overall survival at 3 years among IC group compared to standard therapy group. In July 2019, IC GemCis followed by CCRT was adopted as standard of care for locoregionally advanced NPC patients in National Cancer Centre Singapore (NCCS), Department of Radiation Oncology (DRO). To enable prompt referral of patients back to DRO for CCRT, new workflow was established.Methods: Since July 2019, >120 NPC patients were included in the pathway of IC and CCRT. Their journey through IC cycles were tracked as part of the newly established workflow and DRO bookings were made between second and third cycles of IC regime. Besides, their original shells were kept to replicate the original position and head tilt of pre- and post- IC.Results: IC NPC patients experienced a prompt referral back to DRO due to precise tracking of patients’ IC journey. The established workflow was found to be robust and beneficial in preventing prolonged delay to facilitate the timely commencement of CCRT. The original shell that helped to replicate the original position allows optimized delineation of gross tumor volume (GTV) post-IC, reduce workload for re-making shell and saves money plus resources.Conclusion: With the success of this robust workflow, valuable database could be obtained to enable future studies. Moving forward, analysis of Epstein-Barr virus (EBV) load, pre- and post-IC GTV, along with evaluation of dosimetric impact on surrounding organs at risk (OARs) will be investigated. Purpose: Treatment management for locoregionally advanced nasopharyngeal carcinoma (NPC) patients involves concurrent radiation therapy (RT) and chemotherapy. Phase III clinical trial by Sun Yat-sen University Cancer Center, introduced Gemcitabine (Gem) and Cisplatin (Cis) as induction chemotherapy (IC) regime prior to concurrent chemo-radiotherapy (CCRT). This study reported 3-year recurrence-free survival of 85.3% in IC followed by CCRT, which corresponded to 4.3% higher overall survival at 3 years among IC group compared to standard therapy group. In July 2019, IC GemCis followed by CCRT was adopted as standard of care for locoregionally advanced NPC patients in National Cancer Centre Singapore (NCCS), Department of Radiation Oncology (DRO). To enable prompt referral of patients back to DRO for CCRT, new workflow was established. Methods: Since July 2019, >120 NPC patients were included in the pathway of IC and CCRT. Their journey through IC cycles were tracked as part of the newly established workflow and DRO bookings were made between second and third cycles of IC regime. Besides, their original shells were kept to replicate the original position and head tilt of pre- and post- IC. Results: IC NPC patients experienced a prompt referral back to DRO due to precise tracking of patients’ IC journey. The established workflow was found to be robust and beneficial in preventing prolonged delay to facilitate the timely commencement of CCRT. The original shell that helped to replicate the original position allows optimized delineation of gross tumor volume (GTV) post-IC, reduce workload for re-making shell and saves money plus resources. Conclusion: With the success of this robust workflow, valuable database could be obtained to enable future studies. Moving forward, analysis of Epstein-Barr virus (EBV) load, pre- and post-IC GTV, along with evaluation of dosimetric impact on surrounding organs at risk (OARs) will be investigated.

Histidine phosphorylation in human cells; a needle or phantom in the haystack?

It has been suggested that in mammalian cells histidine residues in proteins may become as frequently phosphorylated as serine, threonine and tyrosine, and may play a key role in mammalian signaling. Here we applied a robust workflow that earlier allowed us to detect histidine phosphorylation in bacteria unambiguously, to probe for histidine phosphorylation in four human cell lines. Initially, seemingly hundreds of protein histidine phosphorylations were picked up in all studied human cell lines. However, careful examination of the data, and several control experiments, led us to the conclusion that >99% of these initially assigned pHis sites were not genuine, and should be site localized to neighboring Ser/Thr residues. Nevertheless, our methods are selective enough to detect just a handful of genuine pHis sites in mammalian cells, representing well-known enzymatic intermediates. Consequently, we do not find any evidence in our data supporting that protein histidine phosphorylation plays a role in mammalian signaling.

Abstract 3084: Label-free, real-time live cell assays for 3D organoids embedded in Matrigel®

Abstract Organoid technologies are increasingly being used as in-vitro models of human development and disease as they exhibit structural, morphogenetic, and functional properties that recapitulate in vivo pathophysiology. To successfully use these models across a variety of research disciplines and applications, approaches that reduce variability and technology pipelines to image & quantify these complex cell models are required. Here, we demonstrate simple, robust workflows for monitoring and automatically quantifying features, such as morphology, growth and death of organoids using real time live cell analysis. To quantitatively optimize and characterize organoid cultures in-vitro, mouse hepatic, intestinal and pancreatic organoids were embedded in Matrigel® domes (50% or 100%) in 24-well plates and imaged over time in an Incucyte® Live Cell System. Organoid growth, differentiation, and maturation was measured using Incucyte’ s automated Organoid Software Analysis Module, which tracks changes in size and morphology. Integrated metrics enabled objective determination of cell-type specific growth conditions and passaging regimes. To illustrate the utility of the Incucyte® Organoid Analysis Software Module to track organoid growth and death in 96-well plates, intestinal and hepatic organoid fragments were embedded in Matrigel® (50%) for 3 days prior to treatment with protein kinase inhibitor staurosporine (1 µM, STP). Vehicle treated organoids increased in size (10-fold; intestinal or 3-fold; hepatic) over time while marked reduction was observed in the presence of STP. Using label-free size and morphology metrics we could distinguish between cytotoxic and cytostatic mechanisms of action (MoA) of known chemotherapeutic compounds. STP, cisplatin (CIS, DNA synthesis inhibitor) or fluorouracil (5-FU, thymidylate synthetase inhibitor) exhibited concentration dependent inhibition of hepatic organoid growth, yielding IC50 values of 3 nM for STP, 9.7 µM for CIS and 0.78 µM for 5-FU. Whilst attenuation of size was observed across all compounds, increases in eccentricity and darkness indictive of 3D structure disruption and cell death respectively were only observed in CIS and STP-treated organoids (cytotoxic MoA). Differences between the size and morphology readouts illustrated the cytostatic mechanism of 5-FU. Use of this approach was extended to visualize and quantify CFTR function. Following forskolin stimulation, a concentration-dependent increase in intestinal organoid size was observed. In the presence of CFTR inhibitor CFTRinh-172 the maximal response was reduced by >50% (~150% at 10 µM) illustrating that swelling was CFTR-dependent. These data demonstrate the capability to kinetically visualize and quantify distinct organoid morphologies, assess drug-induced cellular changes label-free and illustrates the amenability of this approach across a range of disease areas. Citation Format: Tim R. Jackson, Miniver Oliver, Daniel Appledorn, Tim Dale, Kalpana Barnes. Label-free, real-time live cell assays for 3D organoids embedded in Matrigel® [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 3084.

Abstract 6238: Profiling of the circulating cell-free DNA methylome for detection and subtyping of small cell lung cancers

Abstract Introduction: Small-cell lung cancer (SCLC) is a high-grade neuroendocrine carcinoma characterised by high proliferation rate and early, rapid metastatic spread. Although SCLC is treated as a homogenous disease, recent studies revealed morphologic and transcriptomic heterogeneity with several molecular subtypes described based on predominant transcription factor expression (ASCL1, NEUROD1, ATOH1, POU2F3, YAP1) (Rudin et al., 2019; Simpson et al., 2020) which in preclinical studies exhibit differing vulnerabilities raising the potential of stratified therapy. DNA methylation is also thought be an important regulator of SCLC biology (Gazdar et al., 2017) and epigenetically distinct subtypes derived from SCLC primary tumour samples reported (Poirier et al., 2015). Here, we developed a robust workflow for genome-wide DNA methylation profiling to examine the potential use of cfDNA methylation profiling for detection and subtyping of SCLC. Results: To evaluate SCLC genome-wide DNA methylation patterns we employed a bisulfite-free enrichment-based approach (T7-MBD-seq). We tested this approach on tissue samples from preclinical models and from normal lung (n=110) and on cfDNA samples from both patients with SCLC and from non-cancer controls (n=157). Methylation profiles from preclinical models (patient-derived xenografts (PDX) and CTC derived explant (CDX) models) were comparable to previously described methylation patterns from SCLC primary tumours and were recapitulated in patients’ cfDNA samples. A tumour/normal classifier, based on 4,061 genomic regions detected as being hypermethylated in SCLC preclinical models, correctly assigned 93% and 100% cfDNA samples from patients with limited and extensive stage SCLC respectively, with a statistically significant correlation of prediction scores with disease stage (P=0.0076). Finally, to determine whether cfDNA methylation profiling could subtype SCLC patients, we built a subtype classifier, based on methylation signatures derived from 59 established SCLC cell lines. We applied the classifier to cfDNA samples from 56 patients and 10/11 with known subtypes (identified from a donor matched CDX model) were correctly classified. Overall, 73% of cfDNA samples were classified as ASCL1, 13% were classified as NEUROD1 and 14% were classified as being double negative with the distribution of the subtypes correlating closely to previously published IHC data from SCLC tissue samples (Baine et al., 2020). Conclusions: Our data reveal two potential clinical utilities of cfDNA methylation profiling; a universally applicable liquid biopsy approach for more sensitive detection and monitoring of SCLC and molecular subtyping to ease the path to future clinical trials of subtype stratified treatments for patients with SCLC. Citation Format: Dominic G. Rothwell, Francesca Chemi, Simon Pearce, Alex Clipson, Steven Hill, Alicia Marie Conway, Sophie Richardson, Katarzyna Murat, Rebecca Caeser, Jacklynn Egger, John T. Poirier, Alastair Kerr, Fiona Blackhall, Charles M. Rudin, Caroline Dive. Profiling of the circulating cell-free DNA methylome for detection and subtyping of small cell lung cancers [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 6238.

Occupancy–detection models with museum specimen data: Promise and pitfalls

Abstract Historical museum records provide potentially useful data for identifying drivers of change in species occupancy. However, because museum records are typically obtained via many collection methods, methodological developments are needed to enable robust inferences. Occupancy–detection models, a relatively new and powerful suite of statistical methods, are a potentially promising avenue because they can account for changes in collection effort through space and time. We use simulated datasets to identify how and when patterns in data and/or modelling decisions can bias inference. We focus primarily on the consequences of contrasting methodological approaches for dealing with species' ranges and inferring species' non‐detections in both space and time. We find that not all datasets are suitable for occupancy–detection analysis but, under the right conditions (namely, datasets that are broken into more time periods for occupancy inference and that contain a high fraction of community‐wide collections, or collection events that focus on communities of organisms), models can accurately estimate trends. Finally, we present a case study on eastern North American odonates where we calculate long‐term trends of occupancy using our most robust workflow. These results indicate that occupancy–detection models are a suitable framework for some research cases and expand the suite of available tools for macroecological analysis available to researchers, especially where structured datasets are unavailable.

Immuno-multiple reaction monitoring (iMRM) for quantitation of PD-L1 and PD-1-signaling proteins in non-small cell lung carcinoma (NSCLC).

2627 Background: More accurate predictive biomarkers of response to checkpoint inhibitors (CPIs) still is a major unmet need in oncology. PD-L1 immunohistochemistry (IHC) limitations include its analytical variability and the post-translational modifications of PD-1 signaling-associated proteins like glycosylation. Moreover, PD-L1 IHC is an imperfect surrogate of the tumor immune microenvironment, and immunoscoring is important but difficult to assess in a clinical setting. Proteomic based technologies can overcome these challenges, but the low concentration of these proteins and the presence of high background noise in formalin-fixed paraffin embedded (FFPE) tumors were limiting obstacles. In this study, we evaluate the benefit of a new approach we used with anti-peptide antibodies to purify surrogate peptides, while liquid chromatography (LC) was coupled to multiple reaction monitoring mass spectrometry (iMRM) to improve specificity and precision of protein quantitation. Methods: To determine the concentration of PD-L1, PD-1, PD-L2, NT5E, LCK and ZAP70, we used unique and well detectable proteolytic peptides as surrogates. In a refined protocol, we optimized protein extraction and digestion, peptide immuno-enrichment, LC and MRM parameters to maximize recovery, increase target-specific signal and reduce noise. Plus, we assessed the glycosylation status of PD-L1, PD-L2, and PD-1. The entire workflow was fully validated using 31 NSCLC FFPE tumors. PD-L1 quantitation by iMRM was compared to PD-L1 IHC clone 22C3. Results: On average, 71±29 µg (n = 52) of protein could be extracted from each 1–3 mm3 NSCLC tumor FFPE core. The optimized iMRM method allowed the quantitation of PD-L1 and PD-1 down to 21 amol on-column. Inter- and intra-day repeatability were well below FDA guidelines (coefficients of variation [CV] < 20%) with average CVs of 5.2±4.0% (intra-day) and 4.5±2.6% (inter-day). Sample storage had no significant effect on peptide quantitation. The final multiplexed iMRM assay enables quantitation all targets and glycosylation states for > 40 samples in only 3 days (including external calibration and quality controls) and was used to quantify the PD-1/PD-L1 axis proteins successfully in all 31 NSCLC FFPE tumors. PD-L1 expression ranged from 2 amol/μg to 61 amol/μg of total protein. As expected, iMRM results correlated moderately (R = 0.56, ρ < 0.001) with PD-L1 IHC. PD-L1 glycosylation status ranged from 99.9±0.2%, and therefore did not explain the discrepancies between IHC and iMRM for these samples. Conclusions: Herein a robust iMRM workflow was developed for the quantitation of the PD-1/PD-L1 axis in FFPE. This proof-of-concept supports that MS-based assay can provide otherwise unavailable data (e.g., PD-L1 concentration, glycosylation status). CPI treated patient tumors are being currently processed to validate the predictive value of the assay.