The two major molecular subtypes of pancreatic adenocarcinoma reportedly have differential response to FOLFIRINOX-based therapy. To promote rapid assignment of basal versus classical subtypes, an array-based single-sample classifier assay was developed and applied to 74 formalin-fixed, paraffin-embedded biopsy or resection specimens of known subtype based on transcriptomics. The Purity Independent Subtyping of Tumors algorithm assigns subtype based on relative expression of 16 RNAs counted by RNA sequencing (RNAseq) versus more practical array-based NanoString nCounter Elements XT technology. Subtype calls were largely concordant between RNAseq and array methods (72/74, 97% agreement). Compared with the lengthy RNAseq protocol, the array-based assay takes just 3 working days to analyze, permitting rapid reporting of tumor subtype. In conclusion, the Purity Independent Subtyping of Tumors pancreatic cancer classifier has robust performance to classify pancreatic adenocarcinoma into basal versus classical subtypes. Clinical validation studies are underway to evaluate outcome in patients whose standard-of-care chemotherapy regimen is selected on the basis of rapid subtype assignment (NCT04683315).

CM310 is a recombinant humanized monoclonal antibody targeting Interleukin (IL)-4 receptor alpha (IL-4Rα). IL-4Rα blockade prevents IL-4 and IL-13 from binding to their receptor, thereby inhibiting downstream signaling pathways that drive Type 2 helper T-cell (Th2) inflammation. CM310 holds potential for treating Th2-related inflammatory diseases, such as asthma, atopic dermatitis and chronic sinusitis with nasal polyposis. In this study, a direct enzyme-linked immunosorbent assay (ELISA) was developed to measure the concentrations of CM310 in rat serum. Seven calibration standards (ranging from 25 to 1600 ng/mL) and three quality controls (70, 500 and 1250 ng/mL) were defined. The limit of detection (LOD), lower limit of quantification (LLOQ) and upper limit of quantification (ULOQ) were 13, 25 and 1600 ng/mL, respectively. The method exhibited excellent precision and accuracy and successfully applied to in vitro serum stability and pharmacokinetic (PK) studies. In conclusion, we have developed and validated a highly sensitive and selective method for measuring CM310 in Sprague-Dawley rats. The development and validation ELISA method met the acceptable criteria, which suggested that these can be applied to quantify CM310, as well as in PK studies.

Sarcoptic mange, caused by epidermal infection with Sarcoptes scabiei, negatively impacts the health, welfare, and local abundance of bare-nosed wombats (Vombatus ursinus) in Australia. Improved understanding of the host immune response to disease and its contribution to pathophysiology could be used to inform management actions for this species in and ex situ. To evaluate the immune response of bare-nosed wombats to sarcoptic mange, we validated three assays (haptoglobin, agarose gel electrophoresis, and micro-erythrocyte sedimentation rate) measuring non-specific markers of inflammation using serum samples from free-living wombats from Tasmania (n = 33). We then analysed correlations between the assay results for each non-specific marker of inflammation and wombat\'s sarcoptic mange scores, and performed histopathological examinations to investigate association of the acute phase response with systemic amyloidosis. We present evidence that haptoglobin and erythrocyte sedimentation rate increased, and albumin decreased, in association with sarcoptic mange scores. This research demonstrates links between the acute phase response and sarcoptic mange severity in bare-nosed wombats, highlighting the utility of non-specific markers of inflammation for aiding assessment of the systemic effects of mange. Showing the value of agarose gel electrophoresis, we also identified specific acute phase proteins warranting future evaluation and found evidence of an immunoglobulin response in mange-affected wombats, revealed by increasing γ-globulins in association with apparent disease severity. Meanwhile, owing to its relatively low resource requirements and rapidity, the erythrocyte sedimentation rate assay may be useful as a point-of-care test to support therapeutic decisions in the field. Our methods and findings are likely to be applicable to a range of other clinical and population health scenarios in captive and free-living wombats, and species impacted by sarcoptic mange globally.

OBJECTIVE: To optimize and evaluate methods for the detection of the inflammatory biomarkers myeloperoxidase (MPO) and calprotectin (CP) in equine feces by ELISA.
METHODS: Healthy horses (n = 28) and horses with intestinal inflammation (n = 10).
METHODS: Feces were suspended in buffer to create fecal supernatant. Serum and fecal supernatant were analyzed using ELISA kits validated for the detection of MPO and CP in equine serum. Assay validation steps included intra- and interassay variability (coefficient of variation [CV]), dilution linearity, spike recovery, and sample type correlation. Variations in sample handling protocols (centrifugation speed, extraction buffer, and filtration) were evaluated.
RESULTS: 17 paired fecal and serum samples were used for initial analysis (10 healthy horses, 7 colitis). Previously reported sample handling protocols resulted in detectable MPO and CP but poor CV, linearity, and spike recovery. There was a linear correlation between serum and fecal samples for CP but not MPO. There was a significant difference between the concentration and CV of alternative sample handling protocols for CP and MPO, with improved CV for CP (2.1% to 18.6%) but not MPO (14.4% to 53.4%). Processing fresh feces with a fecal extraction buffer and filtration of supernatant resulted in the best CV (0.5% to 3.8%) and recovery (45% to 64%) for CP. Detection of MPO was inconsistent regardless of method.
CONCLUSIONS: There are few reliable diagnostic modalities for inflammation of the equine large colon. Findings support quantification of CP in equine feces using the described ELISA kit and protocol. With additional study to establish reference interval and clinical utility, the fecal inflammatory biomarker CP may allow for noninvasive quantification of intestinal inflammation in horses.

While two Plasmodium falciparum circumsporozoite protein-based pre-erythrocytic vaccines (PEV), RTS,S and R21, have been approved by the WHO, no blood-stage vaccine (BSV) or transmission-blocking vaccine (TBV) has reached a phase 3 trial. One of the major obstacles that slows down malaria vaccine development is the shortage (or lack) of in vitro assays or animal models by which investigators can reasonably select the best vaccine formulation (e.g., antigen, adjuvant, or platform) and/or immunization strategy (e.g., interval of inoculation or route of immunization) before a human phase 2 trial. In the case of PEV, RTS,S and R21 have set a benchmark, and a new vaccine can be compared with (one of) the approved PEV directly in preclinical or early clinical studies. However, such an approach cannot be utilized for BSV or TBV development at this moment. The focus of this review is in vitro assays or in vivo models that can be used for P. falciparum BSV or TBV development, and I discuss important considerations during assay selection, standardization, qualification, validation, and interpretation of the assay results. Establishment of a robust assay/model with proper interpretation of the results is the one of key elements to accelerate future vaccine development.

T cell receptor (TCR) T cell therapies target tumor antigens in a human leukocyte antigen (HLA)-restricted manner. Biomarker-defined therapies require validation of assays suitable for determination of patient eligibility. For clinical trials evaluating TCR T cell therapies targeting melanoma-associated antigen A4 (MAGE-A4), screening in studies NCT02636855 and NCT04044768 assesses patient eligibility based on: (1) high-resolution HLA typing and (2) tumor MAGE-A4 testing via an immunohistochemical assay in HLA-eligible patients. The HLA/MAGE-A4 assays validation, biomarker data, and their relationship to covariates (demographics, cancer type, histopathology, tissue location) are reported here. HLA-A∗02 eligibility was 44.8% (2,959/6,606) in patients from 43 sites across North America and Europe. While HLA-A∗02:01 was the most frequent HLA-A∗02 allele, others (A∗02:02, A∗02:03, A∗02:06) considerably increased HLA eligibility in Hispanic, Black, and Asian populations. Overall, MAGE-A4 prevalence based on clinical trial enrollment was 26% (447/1,750) across 10 solid tumor types, and was highest in synovial sarcoma (70%) and lowest in gastric cancer (9%). The covariates were generally not associated with MAGE-A4 expression, except for patient age in ovarian cancer and histology in non-small cell lung cancer. This report shows the eligibility rate from biomarker screening for TCR T cell therapies and provides epidemiological data for future clinical development of MAGE-A4-targeted therapies.

Cerebrospinal fluid (CSF) is a critical body fluid to examine in attempts to discover potential biomarkers for neuroinflammatory and other disorders of the central nervous system (CNS). Serum and/or plasma cytokine levels have been associated with a variety of inflammatory conditions, and some have been shown to be actionable therapeutic targets. Less is known, however, about cytokine levels in CSF. Serum and plasma cytokine testing is widely available in clinical and research laboratories, but cytokine testing in CSF is extremely limited and if performed, accompanied by a disclaimer that it is an unvalidated specimen type. In this study, we validate CSF as a suitable specimen type and determine normal reference intervals for multiple cytokines as well as a soluble cytokine receptor. CSF was validated as a specimen type for testing using a laboratory developed multiplexed cytokine assay previously validated to measure 13 cytokines/markers in serum and plasma. Performance parameters including specimen dilution, specimen interference, linearity and precision were examined. Reference intervals were established using 197 normal and control CSF specimens by non-parametric quantile-based methods. CSF cytokine analysis demonstrated within and between run precision of <10% and < 20% CV, respectively and linearity of ±15% for all analytes throughout the analytical measurement range of the assay. Reference intervals for the 13 cytokines/markers were established from 197 normal and control CSF specimens (78 Male; mean 44.8 y ± 21.7 SD, 119 Female; mean 42.8 y ± 20.3 SD). Cytokine concentrations in CSF from normal donors and controls were less than the lower limit of quantitation of our assay for 6 of the 13 measured cytokines/markers. The chemokine IL8 demonstrated the highest concentration of all analytes measured. CSF demonstrated acceptable performance as a specimen type in our multiplexed cytokine assay. By validating CSF as a specimen type and establishing normal reference intervals for cytokine concentrations in CSF, their potential as biomarkers for infectious, autoimmune and other inflammatory CNS disorders can be more appropriately investigated.

Q-1802 is a humanized bispecific antibody targeting programmed death-ligand 1 (PD-L1) and Claudin 18.2 (CLDN18.2). It can bind to CLDN18.2 and mediate antibody-dependent cell-mediated cytotoxicity against tumor cells. The Fc segment of the antibody recognizing PD-L1 blocks PD-1 signaling and activates innate immunity and adaptive immunity. In this study, we report the development, validation, and application of sensitive and high-throughput enzyme-linked immunosorbent assays (ELISA) to measure the concentrations of Q-1802 in ICR mouse serum. The assay is sensitive, with a lower limit of quantification of 50 ng/mL, has a broad dynamic range of 50-3200 ng/mL, and exhibits excellent precision and accuracy. These assays were successfully applied to in vitro serum stability and pharmacokinetic (PK) studies. In conclusion, we have developed and validated a highly sensitive and selective method for measuring Q-1802 in ICR mouse serum. The development and validation steps of assays met the required criteria for validation, which suggested that these can be applied to quantify Q-1802, as well as in PK studies.

Neutralizing antibody responses from COVID-19 vaccines are pivotal in conferring protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Effective COVID-19 vaccines and assays measuring neutralizing antibodies against emerging variants (i.e., XBB.1.5, XBB.1.16, and XBB.2.3) are needed. The use of biosafety level (BSL)-3 laboratories for live virus assays results in higher costs and a longer turnaround time; therefore, a BSL-2-based pseudovirus neutralization assay (PNT) was developed. The pseudoviruses were produced by cotransfecting cells with plasmids encoding a lentiviral backbone-expressing luciferase reporter; non-surface proteins for lentiviral production; and ancestral or Omicron (BA.1 and BA.5) SARS-CoV-2 spike (S) proteins. The PNT was developed and optimized in dose and kinetics experiments. The representative serum samples (COVID-19-convalescent or NVX-CoV2373-vaccinated participants enrolled in the 2019nCoV-101 trial) demonstrated a wide dynamic range. The neutralization data showed robust correlation with validated anti-recombinant spike IgG levels and angiotensin-converting enzyme 2 inhibition titers (ancestral). This assay is suitable for measurement of the neutralization ability in clinical samples from individuals infected with SARS-CoV-2 or immunized with a COVID-19 vaccine. The results suggest that this PNT provides a lower cost, high-throughput, rapid turnaround alternative to BSL-3-based microneutralization assays and enables the discovery and development of effective vaccines against emerging variants.

Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human error, and require considerable infrastructure. AIgarMIC streamlines and standardizes MIC measurement and is especially valuable for large-scale surveillance activities. MICs were measured using agar dilution for n = 10 antibiotics against clinical Enterobacterales isolates (n = 1,086) obtained from a large tertiary hospital microbiology laboratory. Escherichia coli (n = 827, 76%) was the most common organism. Photographs of agar plates were divided into smaller images covering one inoculation site. A labeled data set of colony images was created and used to train a convolutional neural network to classify images based on whether a bacterial colony was present (first-step model). If growth was present, a second-step model determined whether colony morphology suggested antimicrobial growth inhibition. The ability of the AI to determine MIC was then compared with standard visual determination. The first-step model classified bacterial growth as present/absent with 94.3% accuracy. The second-step model classified colonies as \"inhibited\" or \"good growth\" with 88.6% accuracy. For the determination of MIC, the rate of essential agreement was 98.9% (644/651), with a bias of -7.8%, compared with manual annotation. AIgarMIC uses artificial intelligence to automate endpoint assessments for agar dilution and potentially increases throughput without bespoke equipment. AIgarMIC reduces laboratory barriers to generating high-quality MIC data that can be used for large-scale surveillance programs.
OBJECTIVE: This research uses modern artificial intelligence and machine-learning approaches to standardize and automate the interpretation of agar dilution minimum inhibitory concentration testing. Artificial intelligence is currently of significant topical interest to researchers and clinicians. In our manuscript, we demonstrate a use-case in the microbiology laboratory and present validation data for the model\'s performance against manual interpretation.