Computational pathology: an evolving concept

The initial enthusiasm about computational pathology (CP) and artificial intelligence (AI) was that they will replace pathologists entirely on the way to fully automated diagnostics. It is becoming clear that currently this is not the immediate model to pursue. On top of the legal and regulatory complexities surrounding its implementation, the majority of tested machine learning (ML)-based predictive algorithms do not display the exquisite performance needed to render them unequivocal, standalone decision makers for matters with direct implications to human health. We are thus moving into a different model of "computer-assisted diagnostics", where AI is there to provide support, rather than replacing, the pathologist. Herein we focus on the practical aspects of CP, from a pathologist perspective. There is a wide range of potential applications where CP can enhance precision of pathology diagnosis, tailor prognostic and predictive information, as well as save time. There are, however, a number of potential limitations for CP that currently hinder their wider adoption in the clinical setting. We address the key necessary steps towards clinical implementation of computational pathology, discuss the significant obstacles that hinders its adoption in the clinical context and summarize some proposed solutions. We conclude that the advancement of CP in the clinic is a promising resource-intensive endeavour that requires broad and inclusive collaborations between academia, industry, and regulatory bodies.

The relationship between serum astroglial and neuronal markers and AQP4 and MOG autoantibodies

BACKGROUND

Certain demyelinating disorders, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) exhibit serum autoantibodies against aquaporin-4 (αAQP4) and myelin oligodendrocyte glycoprotein (αMOG). The variability of the autoantibody presentation warrants further research into subtyping each case.

METHODS

To elucidate the relationship between astroglial and neuronal protein concentrations in the peripheral circulation with occurrence of these autoantibodies, 86 serum samples were analyzed using immunoassays. The protein concentration of glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL) and tau protein was measured in 3 groups of subcategories of suspected NMOSD: αAQP4 positive (n = 20), αMOG positive (n = 32) and αMOG/αAQP4 seronegative (n = 34). Kruskal-Wallis analysis, univariate predictor analysis, and multivariate logistic regression with ROC curves were performed.

RESULTS

GFAP and NFL concentrations were significantly elevated in the αAQP4 positive group (p = 0.003; p = 0.042, respectively), and tau was elevated in the αMOG/αAQP4 seronegative group (p < 0.001). A logistic regression model to classify serostatus was able to separate αAQP4 seropositivity using GFAP + tau, and αMOG seropositivity using tau. The areas under the ROC curves (AUCs) were 0.77 and 0.72, respectively. Finally, a combined seropositivity versus negative status logistic regression model was generated, with AUC = 0.80.

CONCLUSION

The 3 markers can univariately and multivariately classify with moderate accuracy the samples with seropositivity and seronegativity for αAQP4 and αMOG.

Transforming diagnostics: The implementation of digital pathology in clinical laboratories

Digital pathology (DP) has emerged as a cutting-edge technology that promises to revolutionise diagnostics in clinical laboratories. This perspective article explores the implementation planning and considerations of DP in a single multicentre institution in Canada, the University Health Network, discussing benefits, challenges, potential implications and considerations for future adopters. We examine the transition from traditional microscopy to digital slide scanning and its impact on pathology practice, patient care and medical research. Furthermore, we address the regulatory, infrastructure and change management considerations for successful integration into clinical laboratories. By highlighting the advantages and addressing concerns, we aim to shed light on the transformative potential of DP and its role in shaping the future of diagnostics.

Multiplex proteomics in the identification of potential biomarkers of very severe sinusoidal obstruction syndrome/veno-occlusive disease (SOS/VOD) in allogeneic hematopoietic cell transplant patients treated with defibrotide

Introduction Despite well-established clinical criteria for diagnosis of SOS/VOD following allogeneic HCT, there is a lack of established diagnostic protein biomarkers. Methods Prospective samples were collected from patients with very severe SOS/VOD at diagnosis and days +3, +7, +14, and +30 post-initiation of defibrotide. Samples from age-matched controls with no VOD were collected at day +14, +30, +60, +90 and +180 following allogeneic HCT. Serum samples were analyzed for 2925 protein levels by antibody-based proximity extension assay (PEA). Mean differences in the log-transformed abundance values were compared using t-tests in a volcano plot. Results Five patients with very severe SOS/VOD and five control patients were compared. Ten proteins were identified that showed a statistically significant and log-transformed 3-fold increase in concentration. They were CALCA, CCL20, GPR37, IGFBP4, IL1RL1, SLC39A14, SPINK4, FABP3, MYL3, and CHCHD10. Four different proteins, namely CD83, LAIR2, CD7, and HEM6 showed a significant decrease with defibrotide treatment. SOS/VOD resolved in 80% (n=4) of patients, while one patient deceased due to SOS/VOD. Conclusion PEA technology identified 10 proteins that were significantly elevated in patients with very severe SOS/VOD. Prospective studies in a larger cohort using this technology may be able to conclusively identify diagnostic protein biomarkers for SOS/VOD.

Diagnostic and progression biomarkers in cerebrospinal fluid of Alzheimer's disease patients

In this commentary, we address a paper published by Johnson et al. by assessing the robustness of their method to discover diagnostic biomarkers in Alzheimer's disease (AD). In addition, we examine how these newly discovered and previously discovered biomarkers, can play a role in assisting patients with AD and those at risk for developing AD, with an emphasis on the translational hurdles that accompany such discoveries.

The relationship between serum astroglial and neuronal markers and AQP4 and MOG autoantibodies

Background

Certain demyelinating disorders, such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) exhibit serum autoantibodies against aquaporin-4 (αAQP4) and myelin oligodendrocyte glycoprotein (αMOG). The variability of the autoantibody presentation warrants further research into subtyping each case.

Methods

To elucidate the relationship between astroglial and neuronal protein concentrations in the peripheral circulation with occurrence of these autoantibodies, 86 serum samples were analyzed using immunoassays. The protein concentration of glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL) and tau protein was measured in 3 groups of subcategories of suspected NMOSD: αAQP4 positive (n = 20), αMOG positive (n = 32) and αMOG/αAQP4 seronegative (n = 34). Kruskal-Wallis analysis, univariate predictor analysis, and multivariate logistic regression with ROC curves were performed.

Results

GFAP and NFL concentrations were significantly elevated in the αAQP4 positive group (p = 0.003; p = 0.042, respectively), and tau was elevated in the αMOG/αAQP4 seronegative group (p < 0.001). A logistic regression model to classify serostatus was able to separate αAQP4 seropositivity using GFAP + tau, and αMOG seropositivity using tau. The areas under the ROC curves (AUCs) were 0.77 and 0.72, respectively. Finally, a combined seropositivity versus negative status logistic regression model was generated, with AUC = 0.80.

Conclusion

The 3 markers can univariately and multivariately classify with moderate accuracy the samples with seropositivity and seronegativity for αAQP4 and αMOG.

Beyond the amyloid hypothesis: how current research implicates autoimmunity in Alzheimer's disease pathogenesis

The amyloid hypothesis has so far been at the forefront of explaining the pathogenesis of Alzheimer's Disease (AD), a progressive neurodegenerative disorder that leads to cognitive decline and eventual death. Recent evidence, however, points to additional factors that contribute to the pathogenesis of this disease. These include the neurovascular hypothesis, the mitochondrial cascade hypothesis, the inflammatory hypothesis, the prion hypothesis, the mutational accumulation hypothesis, and the autoimmunity hypothesis. The purpose of this review was to briefly discuss the factors that are associated with autoimmunity in humans, including sex, the gut and lung microbiomes, age, genetics, and environmental factors. Subsequently, it was to examine the rise of autoimmune phenomena in AD, which can be instigated by a blood-brain barrier breakdown, pathogen infections, and dysfunction of the glymphatic system. Lastly, it was to discuss the various ways by which immune system dysregulation leads to AD, immunomodulating therapies, and future directions in the field of autoimmunity and neurodegeneration. A comprehensive account of the recent research done in the field was extracted from PubMed on 31 January 2022, with the keywords "Alzheimer's disease" and "autoantibodies" for the first search input, and "Alzheimer's disease" with "IgG" for the second. From the first search, 19 papers were selected, because they contained recent research on the autoantibodies found in the biofluids of patients with AD. From the second search, four papers were selected. The analysis of the literature has led to support the autoimmune hypothesis in AD. Autoantibodies were found in biofluids (serum/plasma, cerebrospinal fluid) of patients with AD with multiple methods, including ELISA, Mass Spectrometry, and microarray analysis. Through continuous research, the understanding of the synergistic effects of the various components that lead to AD will pave the way for better therapeutic methods and a deeper understanding of the disease.

Cerebrospinal fluid camk2a levels at baseline predict long-term progression in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) remains a highly unpredictable disease. Many hope that fluid biomarkers may contribute to better stratification of disease, aiding the personalisation of treatment decisions, ultimately improving patient outcomes.

OBJECTIVE

The objective of this study was to evaluate the predictive value of CSF brain-specific proteins from early in the disease course of MS on long term clinical outcomes.

METHODS

In this study, 34 MS patients had their CSF collected and stored within 5 years of disease onset and were then followed clinically for at least 15 years. CSF concentrations of 64 brain-specific proteins were analyzed in the 34 patient CSF, as well as 19 age and sex-matched controls, using a targeted liquid-chromatography tandem mass spectrometry approach.

RESULTS

We identified six CSF brain-specific proteins that significantly differentiated MS from controls (p < 0.05) and nine proteins that could predict disease course over the next decade. CAMK2A emerged as a biomarker candidate that could discriminate between MS and controls and could predict long-term disease progression.

CONCLUSION

Targeted approaches to identify and quantify biomarkers associated with MS in the CSF may inform on long term MS outcomes. CAMK2A may be one of several candidates, warranting further exploration.

Tachykinins and the potential causal factors for post-COVID-19 condition

The most prevalent symptoms of post-COVID-19 condition are pulmonary dysfunction, fatigue and muscle weakness, anxiety, anosmia, dysgeusia, headaches, difficulty in concentrating, sexual dysfunction, and digestive disturbances. Hence, neurological dysfunction and autonomic impairments predominate in post-COVID-19 condition. Tachykinins including the most studied substance P are neuropeptides expressed throughout the nervous and immune systems, and contribute to many physiopathological processes in the nervous, immune, gastrointestinal, respiratory, urogenital, and dermal systems and participate in inflammation, nociception, and cell proliferation. Substance P is a key molecule in neuroimmune crosstalk; immune cells near the peripheral nerve endings can send signals to the brain with cytokines, which highlights the important role of tachykinins in neuroimmune communication. We reviewed the evidence that relates the symptoms of post-COVID-19 condition to the functions of tachykinins and propose a putative pathogenic mechanism. The antagonism of tachykinins receptors can be a potential treatment target.

Quantitation of neurofilament light chain protein in serum and cerebrospinal fluid from patients with multiple sclerosis using the MSD R-PLEX NfL assay

OBJECTIVES

Neurofilament light (NfL) chain is a marker of neuroaxonal damage in various neurological diseases. Here we quantitated NfL levels in the cerebrospinal fluid (CSF) and serum from patients with multiple sclerosis (MS) and controls, using the R-PLEX NfL assay, which employs advanced Meso Scale Discovery® (MSD) electrochemiluminescence (ECL)-based detection technology.

METHODS

NfL was quantitated in samples from 116 individuals from two sites (Ottawa Hospital Research Institute and Mayo Clinic), consisting of patients with MS (n=71) and age- and sex-matched inflammatory neurological controls (n=13) and non-inflammatory controls (n=32). Correlation of NfL levels between CSF and serum was assessed in paired samples in a subset of MS patients and controls (n=61). Additionally, we assessed the correlation between NfL levels obtained with MSD's R-PLEX® and Quanterix's single molecule array (Simoa®) assays in CSF and serum (n=32).

RESULTS

Using the R-PLEX, NfL was quantitated in 99% of the samples tested, and showed a broad range in the CSF (82-500,000 ng/L) and serum (8.84-2,014 ng/L). Nf-L levels in both biofluids correlated strongly (r=0.81, p<0.0001). Lastly, Nf-L measured by MSD's R-PLEX and Quanterix's Simoa assays were highly correlated for both biofluids (CSF: r=0.94, p<0.0001; serum: r=0.95, p<0.0001).

CONCLUSIONS

We show that MSD's R-PLEX NfL assay can reliably quantitate levels of NfL in the CSF and serum from patients with MS and controls, where levels correlate strongly with Simoa.

B cell profiles, antibody repertoire and reactivity reveal dysregulated responses with autoimmune features in melanoma

B cells are known to contribute to the anti-tumor immune response, especially in immunogenic tumors such as melanoma, yet humoral immunity has not been characterized in these cancers to detail. Here we show comprehensive phenotyping in samples of circulating and tumor-resident B cells as well as serum antibodies in melanoma patients. Memory B cells are enriched in tumors compared to blood in paired samples and feature distinct antibody repertoires, linked to specific isotypes. Tumor-associated B cells undergo clonal expansion, class switch recombination, somatic hypermutation and receptor revision. Compared with blood, tumor-associated B cells produce antibodies with proportionally higher levels of unproductive sequences and distinct complementarity determining region 3 properties. The observed features are signs of affinity maturation and polyreactivity and suggest an active and aberrant autoimmune-like reaction in the tumor microenvironment. Consistent with this, tumor-derived antibodies are polyreactive and characterized by autoantigen recognition. Serum antibodies show reactivity to antigens attributed to autoimmune diseases and cancer, and their levels are higher in patients with active disease compared to post-resection state. Our findings thus reveal B cell lineage dysregulation with distinct antibody repertoire and specificity, alongside clonally-expanded tumor-infiltrating B cells with autoimmune-like features, shaping the humoral immune response in melanoma.

Discovery of novel glioma serum biomarkers by proximity extension assay

BACKGROUND

Gliomas are among the most malignant tumors, with a very poor prognosis. Early diagnosis is highly desirable since it can help implement more effective treatments for smaller tumors, which have not yet extensively metastasized. Improving early diagnosis may facilitate access of patients to clinical trials and prepare them for the future availability of new disease-modifying treatments.

METHODS

We analyzed retrospective samples collected at diagnosis (before therapy initiation), with PEA (Olink Proteomics), quantifying about 3000 proteins. We utilized 30 plasmas from gliomas (20 glioblastomas, 5 anaplastic astrocytomas, 5 anaplastic oligodendrogliomas) and 20 meningiomas (as controls). We then analyzed the data to identify proteins which either alone, or in combination, could discriminate gliomas from meningiomas, or correlate with clinical and molecular alterations.

RESULTS

We identified 8 plasma proteins which were increased in gliomas vs. meningiomas (GFAP, NEFL, EDDM3B, PROK1, MMP3, CTRL, GP2, SPINT3) and 4 proteins which were decreased in gliomas vs. meningiomas (FABP4, ALDH3A1, IL-12B and OXT). Partition algorithms and logistic regression algorithms with two biomarkers (GFAP and FABP4) achieved sensitivity of 83% and 93% at 100% and 90% specificity, respectively. The strongest single marker was GFAP with an area under the ROC curve (AUC) of 0.86. The AUC for the GFAP-FABP4 combination was 0.98.

CONCLUSION

PEA is a powerful new proteomic technology for biomarker discovery. GFAP and a handful of other plasma biomarkers may be useful for early glioma detection and probably, prognosis.

STATEMENT

Detecting gliomas as early as possible is highly desirable since it can significantly improve the chances of effective treatments. Reliable glioma biomarkers can timely inform glioma patients about the efficacy of their prescribed treatment. Our results reveal some novel putative glioma markers that may prove valuable, when used alone or in combination, towards improved clinical care of gliomas. In order to better appreciate the potential usefulness of these markers, their performance needs to be further validated in a larger cohort of samples.

Quantitation of cardiac troponin I in cancer patients treated with immune checkpoint inhibitors: a case-control study

OBJECTIVES

Immune checkpoint inhibitors (ICIs) cause a variety of toxicities, including immune-related adverse events (irAEs), but there are no biomarkers to predict their development. Guidelines recommend measuring circulating cardiac troponin I (cTnI) during ICI therapy to detect related cardiotoxicities. Moreover, elevated cTnI has also been associated with worse outcomes in non-cardiac patients, including cancer. Thus here, we investigated whether cTnI levels were higher in patients with irAEs.

METHODS

The study consisted of three groups; 21 cancer patients undergoing ICI immunotherapies who presented with irAEs, four patients without irAEs, and 20 healthy controls. Patient samples were assessed at baseline (n=25), during ICI treatment (n=25, median=6 weeks of treatment) and at toxicity (n=6, median=13 weeks of treatment). In addition to blood high sensitivity cardiac troponin I (hs-cTnI), anti-thyroglobulin (TG) and anti-thyroid peroxidase (TPO) antibodies were also quantitated to detect thyroid dysfunction, constituting the second leading toxicity (23.8%) after pneumonitis (28.6%).

RESULTS

Four patients with irAEs (n=4/21; 19%) and one without irAEs (n=1/4; 25%) showed higher hs-cTnI levels at any time-point; the remaining had physiological levels. None of these patients developed cardiotoxicity. Concurrent elevated levels of anti-thyroid antibodies and hs-cTnI were detected in one patient with thyroid dysfunction (n=1/5, 20%). However, these antibodies were also elevated in three patients (n=3/16, 19%) with non-thyroid irAEs and in up to 40% of healthy controls.

CONCLUSIONS

hs-cTnI was not elevated in patients with irAEs, but larger studies are needed to confirm these observations.

Multiplex proteomics using proximity extension assay for the identification of protein biomarkers predictive of acute graft-vs.-host disease in allogeneic hematopoietic cell transplantation

OBJECTIVES

Allogeneic hematopoietic cell transplantation (HCT) is associated with acute graft-vs.-host disease (aGVHD). The presented study applied a novel multiplex antibody-based proximity extension assay (PEA) proteomic platform that can detect thousands of serum proteins simultaneously for the identification of potential biomarkers of aGVHD.

METHODS

Serum samples from 28 patients who underwent allogeneic HCT for acute myeloid leukemia (AML) were analyzed; 17 were diagnosed with grade II-IV aGVHD while 11 patients were not. Samples collected on day -6, day 0, +14, +30, +60 and +90 post-HCT were analyzed for the relative concentrations of 552 proteins. The concentration of each protein from baseline to the closest time point before onset of aGVHD, or to the latest time point in control patients, was documented.

RESULTS

Individualized analysis identified 26 proteins demonstrating ≥3-fold increase at aGVHD onset compared to baseline, eliminating proteins with a similar increase in controls. Another approach used paired t-testing and logistic regression that identified a four-marker panel, including SLAMF7, IL-1ra, BTN3A2 and DAB2, where individual log-likelihood ratios ranged from 3.99 to 8.15 (logistic regression, p=0.004-0.046). When combined, the four-marker panel demonstrated an area under the curve (AUC) of 0.90 (95% CI: 0.78-1.00; p=0.0006) with high negative predictive value of 81.8% and positive predictive value of 86.7%. All four markers play a physiological role in immune regulation. Among these, three were also present in the individualized analysis (SLAMF7, IL-1ra and BTN3A2).

CONCLUSIONS

We conclude that serum proteins identified using multiplex proteomics, particularly SLAMF7, IL-1ra, BTN3A2 and DAB2, may potentially predict aGVHD.

The therapeutic relevance of the Kallikrein-Kinin axis in SARS-cov-2-induced vascular pathology

While coronavirus disease 2019 (COVID-19) begins as a respiratory infection, it progresses as a systemic disease involving multiorgan microthromboses that underly the pathology. SARS-CoV-2 enters host cells via attachment to the angiotensin-converting enzyme 2 (ACE2) receptor. ACE2 is widely expressed in a multitude of tissues, including the lung (alveolar cells), heart, intestine, kidney, testis, gallbladder, vasculature (endothelial cells), and immune cells. Interference in ACE2 signaling could drive the aforementioned systemic pathologies, such as endothelial dysfunction, microthromboses, and systemic inflammation, that are typically seen in patients with severe COVID-19. ACE2 is a component of the renin-angiotensin system (RAS) and is intimately associated with the plasma kallikrein-kinin system (KKS). As many papers are published on the role of ACE and ACE2 in COVID-19, we will review the role of bradykinin, and more broadly the KSS, in SARS-CoV-2-induced vascular dysfunction. Furthermore, we will discuss the possible therapeutic interventions that are approved and in development for the following targets: coagulation factor XII (FXII), tissue kallikrein (KLK1), plasma kallikrein (KLKB1), bradykinin (BK), plasminogen activator inhibitor (PAI-1), bradykinin B1 receptor (BKB1R), bradykinin B2 receptor (BKB2R), ACE, furin, and the NLRP3 inflammasome. Understanding these targets may prove of value in the treatment of COVID-19 as well as in other virus-induced coagulopathies in the future.

Sensitive Serology Measurements in the Saliva of Individuals with COVID-19 Symptoms Using a Multiplexed Immunoassay

Background

There are numerous benefits to performing salivary serology measurements for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen for coronavirus disease 2019 (COVID-19). Here, we used a sensitive multiplex serology assay to quantitate salivary IgG against 4 SARS-CoV-2 antigens: nucleocapsid, receptor-binding domain, spike, and N-terminal domain.

Methods

We used single samples from 90 individuals with COVID-19 diagnosis collected at 0 to 42 days postsymptom onset (PSO) and from 15 uninfected control subjects. The infected individuals were segmented in 4 groups (0–7 days, 8–14 days, 15–21 days, and >21 days) based on days PSO, and values were compared to controls.

Results

Compared to controls, infected individuals showed higher levels of antibodies against all antigens starting from 8 days PSO. When applying cut-offs with at least 93.3% specificity at every time interval segment, nucleocapsid protein serology had the best sensitivity at 0 to 7 days PSO (60% sensitivity [35.75% to 80.18%], ROC area under the curve [AUC] = 0.73, P = 0.034). Receptor-binding domain serology had the best sensitivity at 8 to 14 days PSO (83.33% sensitivity [66.44%–92.66%], ROC AUC = 0.90, P < 0.0001), and all assays except for N-terminal domain had 92% sensitivity (75.03%–98.58%) at >14 days PSO.

Conclusions

This study shows that our multiplexed immunoassay can distinguish infected from uninfected individuals and reliably (93.3% specificity) detect seroconversion (in 60% of infected individuals) as early as the first week PSO, using easy-to-collect saliva samples.

Electronic field effect detection of SARS-CoV-2 N-protein before the onset of symptoms

As part of the efforts to contain the pandemic, researchers around the world have raced to develop testing platforms to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the Coronavirus disease 2019 (COVID-19). Within the different detection platforms studied, the field effect transistor (FET) is a promising device due to its high sensitivity and fast detection capabilities. In this work, a graphene-based FET which uses a boron and nitrogen co-doped graphene oxide gel (BN-GO gel) transducer functionalized with nucleoprotein antibodies, has been investigated for the detection of SARS-CoV-2 nucleocapsid (N)-protein in buffer. This biosensor was able to detect the viral protein in less than 4 min, with a limit of detection (LOD) as low as 10 ag/mL and a wide linear detection range stretching over 11 orders of magnitude from 10 ag/mL-1 μg/mL. This represents the lowest LOD and widest detection range of any COVID-19 sensor and thus can potentially enable the detection of infected individuals before they become contagious. In addition to its potential use in the COVID-19 pandemic, our device serves as a proof-of-concept of the ability of functionalized BN-GO gel FETs to be used for ultrasensitive yet robust biosensors.

Patients with severe COVID-19 do not have elevated autoantibodies against common diagnostic autoantigens

OBJECTIVES

Infection by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative pathogen of coronavirus disease 2019 (COVID-19) presents occasionally with an aberrant autoinflammatory response, including the presence of elevated circulating autoantibodies in some individuals. Whether the development of autoantibodies against self-antigens affects COVID-19 outcomes remains unclear. To better understand the prognostic role of autoantibodies in COVID-19, we quantified autoantibodies against 23 markers that are used for diagnosis of autoimmune disease. To this end, we used serum samples from patients with severe [intensive care unit (ICU)] and moderate (ward) COVID-19, across two to six consecutive time points, and compared autoantibody levels to uninfected healthy and ICU controls.

METHODS

Acute and post-acute serum (from 1 to 26 ICU days) was collected from 18 ICU COVID-19-positive patients at three to six time points; 18 ICU COVID-19-negative patients (sampled on ICU day 1 and 3); 21 ward COVID-19-positive patients (sampled on hospital day 1 and 3); and from 59 healthy uninfected controls deriving from two cohorts. Levels of IgG autoantibodies against 23 autoantigens, commonly used for autoimmune disease diagnosis, were measured in serum samples using MSD^® U-PLEX electrochemiluminescence technology (MSD division Meso Scale Discovery^®), and results were compared between groups.

RESULTS

There were no significant elevations of autoantibodies for any of the markers tested in patients with severe COVID-19.

CONCLUSIONS

Sample collections at longer time points should be considered in future studies, for assessing the possible development of autoantibody responses following infection with SARS-CoV-2.

Ultrasensitive assay for saliva-based SARS-CoV-2 antigen detection

OBJECTIVES

Widespread SARS-CoV-2 testing is invaluable for identifying asymptomatic/pre-symptomatic individuals. There remains a technological gap for highly reliable, easy, and quick SARS-CoV-2 diagnostic tests suitable for frequent mass testing. Compared to nasopharyngeal (NP) swab-based tests, saliva-based methods are attractive due to easier and safer sampling. Current saliva-based SARS-CoV-2 rapid antigen tests (RATs) are hindered by limited analytical sensitivity. Here, we report one of the first ultrasensitive, saliva-based SARS-CoV-2 antigen assays with an analytical sensitivity of <0.32 pg/mL, corresponding to four viral RNA copies/µL, which is comparable to that of PCR-based tests.

METHODS

Using the novel electrochemiluminescence (ECL)-based immunoassay, we measured the SARS-CoV-2 nucleocapsid (N) antigen concentration in 105 salivas, obtained from non-COVID-19 and COVID-19 patients. We then verified the results with a second, independent cohort of 689 patients (3.8% SARS-CoV-2 positivity rate). We also compared our method with a widely used point-of-care rapid test.

RESULTS

In the first cohort, at 100% specificity, the sensitivity was 92%. Our assay correctly identified samples with viral loads up to 35 CT cycles by saliva-based PCR. Paired NP swab-based PCR results were obtained for 86 cases. Our assay showed high concordance with saliva-based and NP swab-based PCR in samples with negative (<0.32 pg/mL) and strongly positive (>2 pg/mL) N antigen concentrations. In the second cohort, at 100% specificity, sensitivity was also 92%. Our assay is about 700-fold more sensitive than the Abbott Panbio Rapid Test.

CONCLUSIONS

We demonstrated the ultrasensitivity and specificity assay and its concordance with PCR. This novel assay is especially valuable when compliance to frequent swabbing may be problematic.

Putative Concussion Biomarkers Identified in Adolescent Male Athletes Using Targeted Plasma Proteomics

Sport concussions can be difficult to diagnose and if missed, they can expose athletes to greater injury risk and long-lasting neurological disabilities. Discovery of objective biomarkers to aid concussion diagnosis is critical to protecting athlete brain health. To this end, we performed targeted proteomics on plasma obtained from adolescent athletes suffering a sports concussion. A total of 11 concussed male athletes were enrolled at our academic Sport Medicine Concussion Clinic, as well as 24 sex-, age- and activity-matched healthy control subjects. Clinical evaluation was performed and blood was drawn within 72 h of injury. Proximity extension assays were performed for 1,472 plasma proteins; a total of six proteins were considered significantly different between cohorts (P < 0.01; five proteins decreased and one protein increased). Receiver operating characteristic curves on the six individual protein biomarkers identified had areas-under-the-curves (AUCs) for concussion diagnosis ≥0.78; antioxidant 1 copper chaperone (ATOX1; AUC 0.81, P = 0.003), secreted protein acidic and rich in cysteine (SPARC; AUC 0.81, P = 0.004), cluster of differentiation 34 (CD34; AUC 0.79, P = 0.006), polyglutamine binding protein 1 (PQBP1; AUC 0.78, P = 0.008), insulin-like growth factor-binding protein-like 1 (IGFBPL1; AUC 0.78, P = 0.008) and cytosolic 5'-nucleotidase 3A (NT5C3A; AUC 0.78, P = 0.009). Combining three of the protein biomarkers (ATOX1, SPARC and NT5C3A), produced an AUC of 0.98 for concussion diagnoses (P < 0.001; 95% CI: 0.95, 1.00). Despite a paucity of studies on these three identified proteins, the available evidence points to their roles in modulating tissue inflammation and regulating integrity of the cerebral microvasculature. Taken together, our exploratory data suggest that three or less novel proteins, which are amenable to a point-of-care immunoassay, may be future candidate biomarkers for screening adolescent sport concussion. Validation with protein assays is required in larger cohorts.

An overview of mental health during the COVID-19 pandemic

Since its initial outbreak in late 2019, the COVID-19 pandemic has profoundly affected the global community. In addition to the negative health consequences of contracting COVID-19, the implementation of strict quarantine and lockdown measures has also disrupted social networks and devastated the global economy. As a result, there is rising concern that the pandemic has taken a toll on the mental health of the general population. To better understand its impact, an increasing number of studies examined the effects of the pandemic on mental health and psychosocial implications of enforced quarantine and lockdown. In this article, we aim to review and summarize the findings from a variety of studies that have explored the psychosociological effects of the pandemic and its impact on the mental well-being of the general population. We will also examine how various demographic groups, such as the elderly and youth, can be more susceptible or resilient to the pandemic's mental health effects. We hope to provide a broader understanding of the underlying causes of mental health issues triggered by the pandemic and provide recommendations that may be employed to address mental health issues in the population over the long-term.

Comparison of two multiplexed technologies for profiling >1,000 serum proteins that may associate with tumor burden

Background: In this pilot study, we perform a preliminary comparison of two targeted multiplex proteomics technologies for discerning serum protein concentration changes that may correlate to tumor burden in ovarian cancer (OC) patients. Methods: Using the proximity extension assay (PEA) and Quantibody® Kiloplex Array (QKA), we measured >1,000 proteins in the pre-surgical and post-surgical serum from nine OC patients (N=18 samples). We expect that proteins that have decreased significantly in the post-surgical serum concentration may correlate to tumor burden in each patient. Duplicate sera from two healthy individuals were used as controls (N=4 samples). We employed in-house ELISAs to measure five proteins with large serum concentration changes in pre- and post-surgical sera, from four of the original nine patients and the two original controls. Results: Both platforms showed a weak correlation with clinical cancer antigen 125 (CA125) data. The two multiplexed platforms showed a significant correlation with each other for >400 overlapping proteins. PEA uncovered 15 proteins, while QKA revealed 11 proteins, with more than a two-fold post-surgical decrease in at least six of the nine patients. Validation using single enzyme-linked immunosorbent assays (ELISAs) showed at least a two-fold post-surgical decrease in serum concentration of the same patients, as indicated by the two multiplex assays. Conclusion: Both methods identified proteins that had significantly decreased in post-surgical serum concentration, as well as recognizing proteins that had been implicated in OC patients. Our findings from a limited sample size suggest that novel targeted proteomics platforms are promising tools for identifying candidate serological tumor-related proteins.  However further studies are essential for the improvement of accuracy and avoidance of false results.

Novel severe traumatic brain injury blood outcome biomarkers identified with proximity extension assay

OBJECTIVES

Severe traumatic brain injury (sTBI) patients suffer high mortality. Accurate prognostic biomarkers have not been identified. In this exploratory study, we performed targeted proteomics on plasma obtained from sTBI patients to identify potential outcome biomarkers.

METHODS

Blood sample was collected from patients admitted to the ICU suffering a sTBI, using standardized clinical and computerized tomography (CT) imaging criteria. Age- and sex-matched healthy control subjects and sTBI patients were enrolled. Targeted proteomics was performed on plasma with proximity extension assays (1,161 proteins).

RESULTS

Cohorts were well-balanced for age and sex. The majority of sTBI patients were injured in motor vehicle collisions and the most frequent head CT finding was subarachnoid hemorrhage. Mortality rate for sTBI patients was 40%. Feature selection identified the top performing 15 proteins for identifying sTBI patients from healthy control subjects with a classification accuracy of 100%. The sTBI proteome was dominated by markers of vascular pathology, immunity/inflammation, cell survival and macrophage/microglia activation. Receiver operating characteristic (ROC) curve analyses demonstrated areas-under-the-curves (AUC) for identifying sTBI that ranged from 0.870-1.000 (p≤0.005). When mortality was used as outcome, ROC curve analyses identified the top 3 proteins as Willebrand factor (vWF), Wnt inhibitory factor-1 (WIF-1), and colony stimulating factor-1 (CSF-1). Combining vWF with either WIF-1 or CSF-1 resulted in excellent mortality prediction with AUC of 1.000 for both combinations (p=0.011).

CONCLUSIONS

Targeted proteomics with feature classification and selection distinguished sTBI patients from matched healthy control subjects. Two protein combinations were identified that accurately predicted sTBI patient mortality. Our exploratory findings require confirmation in larger sTBI patient populations.

Immunotherapy using IgE or CAR T cells for cancers expressing the tumor antigen SLC3A2

Background

Cancer immunotherapy with monoclonal antibodies and chimeric antigen receptor (CAR) T cell therapies can benefit from selection of new targets with high levels of tumor specificity and from early assessments of efficacy and safety to derisk potential therapies.

Methods

Employing mass spectrometry, bioinformatics, immuno-mass spectrometry and CRISPR/Cas9 we identified the target of the tumor-specific SF-25 antibody. We engineered IgE and CAR T cell immunotherapies derived from the SF-25 clone and evaluated potential for cancer therapy.

Results

We identified the target of the SF-25 clone as the tumor-associated antigen SLC3A2, a cell surface protein with key roles in cancer metabolism. We generated IgE monoclonal antibody, and CAR T cell immunotherapies each recognizing SLC3A2. In concordance with preclinical and, more recently, clinical findings with the first-in-class IgE antibody MOv18 (recognizing the tumor-associated antigen Folate Receptor alpha), SF-25 IgE potentiated Fc-mediated effector functions against cancer cells in vitro and restricted human tumor xenograft growth in mice engrafted with human effector cells. The antibody did not trigger basophil activation in cancer patient blood ex vivo, suggesting failure to induce type I hypersensitivity, and supporting safe therapeutic administration. SLC3A2-specific CAR T cells demonstrated cytotoxicity against tumor cells, stimulated interferon-γ and interleukin-2 production in vitro. In vivo SLC3A2-specific CAR T cells significantly increased overall survival and reduced growth of subcutaneous PC3-LN3-luciferase xenografts. No weight loss, manifestations of cytokine release syndrome or graft-versus-host disease, were detected.

Conclusions

These findings identify efficacious and potentially safe tumor-targeting of SLC3A2 with novel immune-activating antibody and genetically modified cell therapies.

Plasma Protein Profiling by Proximity Extension Assay Technology Reveals Novel Biomarkers of Traumatic Brain Injury-A Pilot Study

BACKGROUND

Traumatic brain injury (TBI) is a significant public health issue affecting nearly 69 million patients worldwide per year. Reliable diagnostic biomarkers are urgently needed to aid in disease diagnosis and prognosis and to guide patient aftercare. Blood biomarkers represent an attractive modality to quickly, cheaply, and objectively evaluate clinical status. We hypothesize that deep and quantitative plasma proteomic profiling with a novel technology, proximity extension assay, may lead to the discovery of diagnostic and/or prognostic biomarkers of TBI.

METHODS

We used high-throughput proximity extension assays (PEA) to quantify the relative abundance of over 1000 unique proteins in plasma. PEA is a highly sensitive multiplex immunoassay capable of detecting very low-abundance proteins (down to fg/mL) in complex biological matrices. Our patient cohort consisted of severe TBI (sTBI) patients, matched healthy controls, and another non-TBI group that was included in the analysis to validate the specificity of the candidates during the selection process. The obtained protein quantification data was then filtered to identify candidate biomarkers through statistical analysis, literature searches, and comparison to our reference control groups.

RESULTS

Overall, we identified 6 novel candidate TBI biomarkers. Candidates exhibit a significant increase in plasma protein abundance in sTBI when comparing between healthy controls and sTBI patients. Candidates generally had low expression in our reference groups compared with the sTBI group.

CONCLUSIONS

Our preliminary findings represent a starting point for future validation. These biomarkers, either alone or in combination, may have significant clinical utility in aiding in TBI diagnosis, prognosis, and/or management.

COVID-19: from an acute to chronic disease? Potential long-term health consequences

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite pulmonary impairments being the most prevalent, extra-pulmonary manifestations of COVID-19 are abundant. Confirmed COVID-19 cases have now surpassed 57.8 million worldwide as of 22 November 2020. With estimated case fatality rates (number of deaths from COVID-19 divided by number of confirmed COVID-19 cases) varying between 1 and 7%, there will be a large population of recovered COVID-19 patients that may acquire a multitude of long-term health consequences. While the multi-organ manifestations of COVID-19 are now well-documented, the potential long-term implications of these manifestations remain to be uncovered. In this review, we turn to previous similar coronaviruses (i.e. SARS-CoV-1 and Middle East respiratory syndrome coronavirus [MERS-CoV]) in combination with known health implications of SARS-CoV-2 infection to predict potential long-term effects of COVID-19, including pulmonary, cardiovascular, hematologic, renal, central nervous system, gastrointestinal, and psychosocial manifestations, in addition to the well-known post-intensive care syndrome. It is necessary to monitor COVID-19 patients after discharge to understand the breadth and severity of long-term effects. This can be accomplished by repurposing or initiating large cohort studies to not only focus on the long-term consequences of SARS-CoV-2 infection, but also on acquired immune function as well as ethno-racial group and household income disparities in COVID-19 cases and hospitalizations. The future for COVID-19 survivors remains uncertain, and if this virus circulates among us for years to come, long-term effects may accumulate exponentially.

Alzheimer Disease Pathogenesis: The Role of Autoimmunity

BACKGROUND

In addition to deposits of amyloid β (Aβ) plaques and neurofibrillary tangles, growing evidence demonstrates that complex and multifaceted biological processes can arise during Alzheimer disease (AD) pathogenesis. The recent failures of clinical trials based on the amyloid hypothesis and the presence of Aβ plaques in cognitively healthy elderly persons without AD point toward a need to explore novel pathobiological mechanisms of AD.

CONTENT

In the search for alternative AD mechanisms, numerous genome-wide association studies and mechanistic discoveries suggest a potential immunologic component of the disease. However, new experimental tools are needed to uncover these immunogenic components. The current methods, such as ELISAs or protein microarrays, have limitations of low throughput and/or sensitivity and specificity. In this article, we briefly discuss evidence of potential autoimmune contributions to AD pathobiology, describe the current methods for identifying autoantibodies in patient fluids, and outline our own efforts to develop new techniques for novel autoantibody biomarker discovery.

SUMMARY

Uncovering the putative autoimmune components of AD may be crucial in paving the way to new concepts for pathogenesis, diagnosis, and therapy.

IMPACT STATEMENT

In addition to deposits of amyloid β plaques and neurofibrillary tangles, growing evidence demonstrates that complex and multifaceted biological processes can arise during Alzheimer disease (AD) pathogenesis. Numerous research directions, including genome-wide association, clinical correlation, and mechanistic studies, have pointed to a potential autoimmunologic contribution to AD pathology. We present research suggesting the association between autoimmunity and AD and demonstrate the need for new laboratory techniques to further characterize potential brain antigen-specific autoantibodies. Uncovering the putative autoimmune components of AD may be crucial in paving the way to new concepts for pathogenesis, diagnosis, and therapy.

Kallikrein 13 serves as a priming protease during infection by the human coronavirus HKU1

Unlike SARS-CoV-2, the human coronavirus HKU1 normally causes relatively mild respiratory tract infections; however, it shares with SARS-CoV-2 the mechanism of using its surface spike (S) protein to enter target cells. Because the host receptor for HCoV-HKU1 is unknown, efforts to study the virus in cell culture systems have proved difficult. Milewska et al. found that knockout of the protease kallikrein 13 (KLK13) in human airway epithelial cells blocked their infection by HCoV-HKU1, that overexpression of KLK13 in nonpermissive cells enabled their infection by the virus, and that KLK13 cleaved the viral S protein. Together, these findings suggest that KLK13 is a priming enzyme for viral entry and may help to establish cell lines that can facilitate further investigation of the mechanism of viral pathogenesis.

Human coronavirus HKU1 (HCoV-HKU1) is associated with respiratory disease and is prevalent worldwide, but an in vitro model for viral replication is lacking. An interaction between the coronaviral spike (S) protein and its receptor is the primary determinant of tissue and host specificity; however, viral entry is a complex process requiring the concerted action of multiple cellular elements. Here, we found that the protease kallikrein 13 (KLK13) was required for the infection of human respiratory epithelial cells and was sufficient to mediate the entry of HCoV-HKU1 into nonpermissive RD cells. We also demonstrated the cleavage of the HCoV-HKU1 S protein by KLK13 in the S1/S2 region, suggesting that KLK13 is the priming enzyme for this virus. Together, these data suggest that protease distribution and specificity determine the tissue and cell specificity of the virus and may also regulate interspecies transmission.

Proteomic Profiling of the Human Tissue and Biological Fluid Proteome

In-depth analysis of the human genome sequence has led to the annotation of approximately 20,000 human protein-coding genes. Although mass spectrometry (MS)-based workflows have made a great headway in achieving near genome-wide coverage, an equivalent complete map of the human proteome remains elusive. Delineating the spatial distribution of all human proteins at the organ, tissue, and cellular level can offer insight into health and disease and represents an excellent reference for the discovery of biomarkers and therapeutic targets. Here, we performed label-free liquid chromatography coupled to tandem MS (LC-MS/MS) to profile the normal human proteome. In total, we analyzed 117 samples from 46 normal tissues and organs at autopsy. Our high-resolution MS approach allowed for the quantification of 10,438 unique proteins. In order to expand our coverage of the human proteome, we combined our previously published biological fluid proteomic data from healthy individuals. We considered data from seven biological fluids, including urine, cerebrospinal fluid, synovial fluid, seminal plasma, sweat, cervical vaginal fluid, and nipple aspirate fluid. Overall, we generated tandem mass spectra corresponding to 13,028 unique human protein-coding genes. Although our analysis did not accomplish complete proteome coverage, it should be an important complementary resource for future biomarker discovery.

Liquid biopsy of cerebrospinal fluid identifies neuronal pentraxin receptor (NPTXR) as a biomarker of progression of Alzheimer's disease

Background Alzheimer's disease (AD) is the most prevalent form of dementia. Currently, the most studied biomarkers of AD are cerebrospinal fluid (CSF) amyloid β 1-42, total tau and phosphorylated tau. However, misdiagnosis can exceed 20%. Recently, we found that CSF amyloid β precursor-like protein-1 (APLP1) and neuronal pentraxin receptor (NPTXR) are promising biomarkers of AD. The aim of the present study is to validate CSF APLP1 and NPTXR as biomarkers of AD severity. Methods APLP1 and NPTXR concentrations were measured in the CSF of patients with mild cognitive impairment (MCI) (n = 14), mild AD (n = 21), moderate AD (n = 43) and severe AD (n = 30) using enzyme-linked immunosorbent assays (ELISAs). Results CSF APLP1 and NPTXR were not associated with age or sex. CSF APLP1 was not different between any of the AD severity groups (p = 0.31). CSF NPTXR was significantly different between MCI and mild AD (p = 0.006), mild and moderate AD (p = 0.016), but not between moderate and severe AD (p = 0.36). NPTXR concentration progressively declined from MCI to mild, to moderate and to severe AD patients (p < 0.0001, Kruskal-Wallis test). CSF NPTXR positively correlated with the Mini-Mental Status Examination (MMSE) score (p < 0.001). Conclusions NPTXR concentration in CSF is a promising biomarker of AD severity and could inform treatment success and disease progression in clinical settings.

Screening of chemical libraries in pursuit of kallikrein-5 specific inhibitors for the treatment of inflammatory dermatoses

Background Aberrant kallikrein activity is observed in a number of inflammatory dermatoses. Up-regulation of kallikrein-5 (KLK5) activity leads to uncontrolled skin desquamation and cleavage of proteinase-activated receptor-2 (PAR2), causing the release of pro-inflammatory cytokines and disruption of epidermal barrier function. This study aimed to identify KLK5-specific small molecule inhibitors which can serve as the foundation of a novel therapeutic for inflammatory skin disorders. Methods Five chemical libraries (13,569 compounds total) were screened against recombinant KLK5 using a fluorogenic enzymatic assay. Secondary validation was performed on the top 22 primary hits. All hits were docked in the KLK5 crystal structure to rationalize their potential interactions with the protein. Results A naturally occurring compound derived from the wood of Caesalpinia sappan (Brazilin) was identified as a novel KLK5 inhibitor (IC50: 20 μM, Ki: 6.4 μM). Docking suggests that the phenolic moiety of Brazilin binds in the S1-pocket of KLK5 and forms a H-bond with S195 side chain. KLK14 was also found to be susceptible to inhibition by Brazilin with a calculated IC50 value of 14.6 μM. Conclusions Natural KLK5 small molecule inhibitors such as Brazilin, are ideal for topical skin disease drug design and remain a promising therapeutic for severe cases of inflammatory skin disorders. Optimized KLK inhibitors may have increased efficacy as therapeutics and warrant further investigation.

Abstract 5144: Exploring the potential of a novel multiplex proteomics technology to identify personalized biomarkers of tumor burden in ovarian cancer patients

Objective: Owing to tumor heterogeneity, we hypothesize that each tumor secretes a unique mixture of tumor-related proteins into the bloodstream, which when quantified can serve as personalized markers of tumor load. We previously introduced the concept of "personalized tumor markers", which are highly sensitive for monitoring tumor load in a small subpopulation (5-30%) of patients. Screening against a robust panel of such personalized markers could identify the most effective markers of relapse in each patient. With the advent of multiplex proteomics technologies, for the first time we can screen serum for tumor-related proteins in individual patients. In this pilot study, we explored the potential of one of the leading new multiplex proteomics technologies for identifying personalized markers of tumor burden in the most common and deadliest type of ovarian cancer - high grade serous carcinoma (HGSC). Serum CA125 is the only widely used marker for HGSC but it is not informative of relapse in 30-60% of cases. With up-and-coming immunotherapies and precision medicines, there is a timely need for personalized markers to monitor for relapse and find the optimal timing for 2nd-line treatment in each patient.

Methods: We leveraged the multiplex immuno-PCR assay, Proseek Panels (Olink, Sweden), to concurrently measure 1,196 proteins in sera obtained pre- and post-surgically from 10 HGSC patients. Sera from two healthy individuals, with blinded technical duplicates, were used as controls. To validate the multiplexed results, we used independent, clinical grade ELISA immunoassays to measure three candidate proteins in sera collected pre- and post-surgically from five of the same 10 HGSC patients.

Results: Scatterplot analysis of 1,196 protein measurements in the technical duplicates showed high correlation and excellent assay precision. For candidate selection, we eliminated proteins that showed greater than two-fold change in the controls. We identified a panel of eight proteins that dropped more than 10-fold post-surgery in at least two patients. The panel as a whole was informative of tumor burden for 80% (8/10) of the patients tested. Using independent ELISAs, we observed high concordance in the post-surgical fold decrease between the Proseek panels and ELISA results, confirming the reliability of the novel platform. Further literature search demonstrated the relevance to tumorigenesis and ovarian cancer for the eight candidate personalized tumor markers.

Significance: With future validation in larger, longitudinal studies, our goal is to develop a panel of personalized HGSC biomarkers of relapse to aid in individualizing patient monitoring and ameliorating survival outcome. Our study also showed the utility of an innovative high throughput biotechnology that is promising for measuring tumor-derived proteins, which can be adapted for a myriad of biomarker studies, particularly in prevalent cancers with no reliable serum biomarkers such as lung cancer.

Citation Format: Annie Ren, Ioannis Prassas, Antoninus Soosaipillai, Marcus Bernardini, Vathany Kulasingam, Eleftherios Diamandis. Exploring the potential of a novel multiplex proteomics technology to identify personalized biomarkers of tumor burden in ovarian cancer patients [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5144.

Investigating a novel multiplex proteomics technology for detection of changes in serum protein concentrations that may correlate to tumor burden

Background: To account for cancer heterogeneity, we previously introduced the concept of "personalized" tumor markers, which are biomarkers that are informative in subsets of patients or even a single patient. Recent developments in various multiplex protein technologies create excitement for the discovery of markers of tumor burden in individual patients, but the reliability of the technologies remains to be tested for this purpose. Here, we sought to explore the potential of a novel proteomics platform, which utilizes a multiplexed antibody microarray, to detect changes in serum protein concentration that may correlate to tumor burden in pancreatic cancer. Methods: We applied the Quantibody® Human Kiloplex Array to simultaneously measure 1,000 proteins in sera obtained pre- and post-surgically from five pancreatic cancer patients. We expected that proteins which decreased post-surgery may correlate to tumor burden. Sera from two healthy individuals, split into two aliquots each, were used as controls. To validate the multiplexed results, we used single-target ELISA assays to measure the proteins with the largest serum concentration changes after surgery in sera collected pre- and post-surgically from the previous five patients and 10 additional patients. Results: The multiplexed array revealed nine proteins with more than two-fold post-surgical decrease in at least two of five patients. However, validation using single ELISAs showed that only two proteins tested displayed more than two-fold post-surgical decrease in one of the five original patients. In the independent cohort, six of the proteins tested showed at least a two-fold decrease post-surgery in at least one patient. Conclusions: Our study found that the Quantibody® Human Kiloplex Array results could not be reliably replicated with individual ELISA assays and most hits would likely represent false positives if applied to biomarker discovery. These findings suggest that data from novel, high-throughput proteomic platforms need stringent validation to avoid false discoveries.

Investigating a novel multiplex proteomics technology for detection of changes in serum protein concentrations that may correlate to tumor burden

Background: To account for cancer heterogeneity, we previously introduced the concept of "personalized" tumor markers, which are biomarkers that are informative in subsets of patients or even a single patient. Recent developments in various multiplex protein technologies create excitement for the discovery of markers of tumor burden in individual patients, but the reliability of the technologies remains to be tested for this purpose. Here, we sought to explore the potential of a novel proteomics platform, which utilizes a multiplexed antibody microarray, to detect changes in serum protein concentration that may correlate to tumor burden in pancreatic cancer. Methods: We applied the Quantibody® Human Kiloplex Array to simultaneously measure 1,000 proteins in sera obtained pre- and post-surgically from five pancreatic cancer patients. We expected that proteins which decreased post-surgery may correlate to tumor burden. Sera from two healthy individuals, split into two aliquots each, were used as controls. To validate the multiplexed results, we used single-target ELISA assays to measure the proteins with the largest serum concentration changes after surgery in sera collected pre- and post-surgically from the previous five patients and 10 additional patients. Results: The multiplexed array revealed nine proteins with more than two-fold post-surgical decrease in at least two of five patients. However, validation using single ELISAs showed that only two proteins tested displayed more than two-fold post-surgical decrease in one of the five original patients. In the independent cohort, six of the proteins tested showed at least a two-fold decrease post-surgery in at least one patient. Conclusions: Our study found that the Quantibody® Human Kiloplex Array results could not be reliably replicated with individual ELISA assays and most hits would likely represent false positives if applied to biomarker discovery. These findings suggest that data from novel, high-throughput proteomic platforms need stringent validation to avoid false discoveries.

The role of kallikreins in inflammatory skin disorders and their potential as therapeutic targets

The skin is a vital organ of the human body, serving numerous protective and functional roles that are essential for survival. Residing in the epidermis are various epidermal proteases responsible for the establishment and regulation of barrier function. The human tissue kallikrein-related peptidase family conserves homeostasis of the skin barrier through their roles in desquamation, antimicrobial defense, innate immune response, and barrier maintenance. The activity of kallikreins is tightly regulated and dysregulation of kallikrein activity is seen to contribute to the formation of several inflammatory skin disorders. This review highlights the roles of kallikreins in skin homeostasis and pathologies. Due to their part in these skin disorders, inhibitors of the skin kallikreins have become attractive therapeutics. Over the past few years, both natural and synthetic inhibitors of several kallikreins have been identified and are undergoing further development as treatments to restore compromised barrier function. This review summarizes the kallikrein inhibitors under development for this purpose. These inhibitors remain promising therapeutics in cases of severe skin inflammation not well managed by current therapies.

Predicting response and toxicity to PD-1 inhibition using serum autoantibodies identified from immuno-mass spectrometry

Background: Validated biomarkers are needed to identify patients at increased risk of immune-related adverse events (irAEs) to immune checkpoint blockade (ICB). Antibodies directed against endogenous antigens can change after exposure to ICB. Methods: Patients with different solid tumors stratified into cohorts received pembrolizumab every 3 weeks in a Phase II trial (INSPIRE study). Blood samples were collected prior to first pembrolizumab exposure (baseline) and approximately 7 weeks (pre-cycle 3) into treatment. In a discovery analysis, autoantibody target immuno-mass spectrometry was performed in baseline and pre-cycle 3 pooled sera of 24 INSPIRE patients based on clinical benefit (CBR) and irAEs. Results: Thyroglobulin (Tg) and thyroid peroxidase (TPO) were identified as the candidate autoantibody targets. In the overall cohort of 78 patients, the frequency of CBR and irAEs from pembrolizumab was 31% and 24%, respectively. Patients with an anti-Tg titer increase ≥1.5x from baseline to pre-cycle 3 were more likely to have irAEs relative to patients without this increase in unadjusted, cohort adjusted, and multivariable models (OR=17.4, 95% CI 1.8-173.8, p=0.015). Similarly, patients with an anti-TPO titer ≥ 1.5x from baseline to pre-cycle 3 were more likely to have irAEs relative to patients without the increase in unadjusted and cohort adjusted (OR=6.1, 95% CI 1.1-32.7, p=0.035) models. Further, the cohort adjusted analysis showed patients with anti-Tg titer greater than median (10.0 IU/mL) at pre-cycle 3 were more likely to have irAEs (OR=4.7, 95% CI 1.2-17.8, p=0.024). Patients with pre-cycle 3 anti-TPO titers greater than median (10.0 IU/mL) had a significant difference in overall survival (23.8 vs 11.5 months; HR=1.8, 95% CI 1.0-3.2, p=0.05). Conclusions: Patient increase ≥1.5x of anti-Tg and anti-TPO titers from baseline to pre-cycle 3 were associated with irAEs from pembrolizumab, and patients with elevated pre-cycle 3 anti-TPO titers had an improvement in overall survival.

Abstract PR03: Immuno-mass spectrometric identification of serum biomarkers of response and toxicity to pembrolizumab

Immune checkpoint blockade (ICB) is a breakthrough form of cancer immunotherapy that employs antibody targeting of specific inhibitory receptors and ligands, such as cytotoxic T-lymphocyte associated antigen 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed cell death ligand 1 (PD-L1). The major limitations of ICB are high cost, limited success rate (10-40%), and potential severe toxicity due to immune-related adverse effects (IRAEs), which resemble autoimmune disease. Predictive biomarkers of ICB are not currently widespread in clinical use, despite the growing need for a personalized approach to cancer treatment. Effective immunotherapy causes tumor cell death, which releases tumor-associated antigens (TAAs) into circulation. This results in abnormal presentation of these antigens to immune cells, which leads to B-cell autoantibody production against them. Autoantibodies are effective biomarkers of some autoimmune diseases and may be present before disease onset. We hypothesized that patients who develop immune-related toxicity from immunotherapy will produce specific autoantibodies that are indicative of an autoimmune-like response. Furthermore, we hypothesized that responders to pembrolizumab will develop high titers of serum autoantibodies against TAAs, indicative of a strong humoral immune response to TAAs released during immunotherapy. Likewise, nonresponders will have low levels of these autoantibodies, due to a weaker or nonexistent antitumor and humoral immune response. We used a novel immuno-mass spectrometry method to screen for autoantibodies in the sera of patients with various tumors treated with PD-1 inhibition in the clinical trial called INSPIRE (INvestigator-initiated Phase II Study of Pembrolizumab Immunological Response Evaluation; NCT02644369) at Princess Margaret Cancer Centre. Our methodology involves immunoprecipitation of proteome-wide target antigens of autoantibodies in patient sera with the use of protein G magnetic beads, followed by shotgun mass spectrometry analysis. We analyzed autoantibody responses in the sera before and after immunotherapy initiation in a total of 24 patients, subdivided into 4 patient groups based on their objective response and toxicity status. Candidate autoantibody target antigens, including thyroglobulin, thyroid peroxidase, and ficolin-2, were identified by our pilot study. Validation with additional datasets is planned. Furthermore, we identified PD-1 as an antibody target exclusively in the post-immunotherapy patient sera of all 4 patient groups. This finding confirms the efficacy of our method since pembrolizumab is a humanized antibody targeting PD-1. Predictive biomarkers of cancer immunotherapy will save significant resources, ensure proper patient selection for cancer treatment, and spare certain patients from the toxic effects of immunotherapy.

This abstract is also being presented as Poster B05.

Citation Format: Milena Music, Marco Iafolla, Antoninus Soosaipillai, Ihor Batruch, Ioannis Prassas, Lillian L. Siu, Eleftherios P. Diamandis. Immuno-mass spectrometric identification of serum biomarkers of response and toxicity to pembrolizumab [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr PR03.

Kallikrein-related peptidases protein expression in lymphoid tissues suggests potential implications in immune response

OBJECTIVES

Kallikrein-related peptidases (KLKs) are a subgroup of 15 secreted chymotrypsin- and trypsin-like serine proteases that have been reported to possess novel functions in innate immunity and inflammation. Since the potential role of KLKs in immunity has not been studied in detail at the protein level, we examined the expression pattern of 12 members of the KLK family in immune-related tissues.

DESIGN & METHODS

Protein expression in tissue extracts was evaluated using immunoassays (ELISA). Immunohistochemistry (IHC) was performed on representative sections of tonsil and lymph nodes to determine the cellular localization of the KLK family members.

RESULTS

ELISA profiling of KLK3-KLK15 (except KLK12) revealed higher protein levels in the tonsil, compared to the lymph nodes and spleen. Relatively high protein levels in the tonsil were observed for KLK7, KLK9, KLK10 and KLK13. Expression of these KLKs was significantly lower in lymph nodes and spleen. IHC analysis in tonsil unveiled that KLK9 and KLK10 were differentially expressed in lymphoid cells. KLK9 was strongly expressed in the germinal center of lymphoid follicles where activated B-cells reside, whereas KLK10 was expressed in the follicular dendritic cells (FDCs) that are vital for maintaining the cycle of B cell maturation.

CONCLUSION

Overall, our study revealed the possible implications of KLK expression and regulation in the immune cells of lymphoid tissues.

Putative autoantibodies in the cerebrospinal fluid of Alzheimer's disease patients

Background: Recent efforts have described an immunogenic component to the pathobiology of Alzheimer's disease (AD) and Parkinson's disease (PD). However, current methods of studying fluid autoantibodies, such as enzyme-linked immunosorbent assays and immunohistochemistry, are hypothesis-driven and not optimal for discovering new autoantibody biomarkers by proteome-wide screening. Recently, we developed a general mass spectrometry-based approach to identify tissue-specific autoantibodies in serum, at a proteome-wide level. In this study, we adapted the method to explore novel autoantibody biomarkers in the cerebrospinal fluid (CSF) of AD and PD patients. Methods: CSF samples were obtained from 10 headache control individuals, 10 AD patients and 10 PD patients. Antibodies present in the CSF were isolated by immobilization to protein-G magnetic beads. These antibodies were incubated with a brain tissue extract, prepared from frontal cortex, pons, cerebellum and brain stem. Protein antigens captured by the protein-G magnetic bead-bound antibodies were digested with trypsin and analyzed using mass spectrometry. Autoantibody candidates were selected by 1) detection in one or less individuals of the control group and 2) identification in at least half of the patient groups. Results: There were 16 putative autoantibody biomarkers selected from the AD group. Glia-derived nexin autoantibody was detected in eight of ten AD patients and was absent in the control group. Other AD pathology-related targets were also identified, such as actin-interaction protein, quinone oxidoreductase, sushi repeat-containing protein, metalloproteinase inhibitor 2, IP3 receptor 1 and sarcoplasmic/endoplasmic reticulum calcium ATPase 2. An additional eleven autoantibody targets were also identified in the present experiment, although their link to AD is not clear. No autoantibodies in the PD group satisfied our selection criteria. Conclusion: Our unbiased mass spectrometry method was able to detect new putative CSF autoantibody biomarkers of AD. Further investigation into the involvement of humoral autoimmunity in AD and PD pathobiology may be warranted.

A proteome-wide immuno-mass spectrometric identification of serum autoantibodies

Background

Autoantibodies are produced when tolerance to self-antigens is broken and they can be mediators of tissue injury and systemic inflammation. They are excellent biomarkers because they are minimally invasive to screen and are highly abundant in serum due to limited proteolysis and slow clearance. Conventionally used methods of identifying autoantibodies in patient sera include indirect immunofluorescence, enzyme-linked immunoabsorbent assays (ELISAs) and protein microarrays. Here we present a novel proteome-wide immuno-mass spectrometric method to identify serum autoantibody targets.

Methods

Serum samples from patients with inflammatory bowel disease (IBD) were analyzed by ELISA for the presence of autoantibodies to CUB and zona pellucida-like domain-containing protein 1 (CUZD1). Protein was extracted from the human pancreas as well as 16 other human tissues to make a complex tissue lysate protein mixture. Antibodies in patient sera were immobilized and purified on protein G magnetic beads and subsequently incubated with pancreatic lysate containing CUZD1 or the aforementioned complex tissue lysate. After extensive washing, antibody-bound protein antigens were trypsin-digested and identified using shotgun mass spectrometry.

Results

The protocol was optimized for the immunoaffinity purification of autoantibody targets from tissue lysate, using CUZD1 from pancreatic lysate and anti-CUZD1 autoantibodies present in IBD patient serum as a proof-of-concept. Pancreatic secretory granule membrane major glycoprotein 2, whose autoantibodies are a known biomarker of Crohn’s disease, was also immunoprecipitated from IBD patient serum, as an additional internal positive control.

Conclusions

This study demonstrates the effectiveness of a proteomic approach to identify serum autoantibody targets, using immunoaffinity purification followed by tandem mass spectrometry. Our methodology is applicable for proteome-wide analysis of autoantibody targets in a wide variety of clinical settings.

Electronic supplementary material

The online version of this article (10.1186/s12014-019-9246-0) contains supplementary material, which is available to authorized users.

Proteome-wide onco-proteogenomic somatic variant identification in ER-positive breast cancer

BACKGROUND

Recent advances in mass spectrometric instrumentation and bioinformatics have critically contributed to the field of proteogenomics. Nonetheless, whether that integrative approach has reached the point of maturity to effectively reveal the flow of genetic variants from DNA to proteins still remains elusive. The objective of this study was to detect somatically acquired protein variants in breast cancer specimens for which full genome and transcriptome data was already available (BASIS cohort).

METHODS

LC-MS/MS shotgun proteomic results of 21 breast cancer tissues were coupled to DNA sequencing data to identify variants at the protein level and finally were used to associate protein expression with gene expression levels.

RESULTS

Here we report the observation of three sequencing-predicted single amino acid somatic variants. The sensitivity of single amino acid variant (SAAV) detection based on DNA sequencing-predicted single nucleotide variants was 0.4%. This sensitivity was increased to 0.6% when all the predicted variants were filtered for MS "compatibility" and was further increased to 2.9% when only proteins with at least one wild type peptide detected were taken into account. A correlation of mRNA abundance and variant peptide detection revealed that transcripts for which variant proteins were detected ranked among the top 6.3% most abundant transcripts. The variants were detected in highly abundant proteins as well, thus establishing transcript and protein abundance and MS "compatibility" as the main factors affecting variant onco-proteogenomic identification.

CONCLUSIONS

While proteomics fails to identify the vast majority of exome DNA variants in the resulting proteome, its ability to detect a small subset of SAAVs could prove valuable for precision medicine applications.