68 research outputs found
Unlocking biomarker discovery: Large scale application of aptamer proteomic technology for early detection of lung cancer
Lung cancer is the leading cause of cancer deaths, because ~84% of cases are diagnosed at an advanced stage. Worldwide in 2008, ~1.5 million people were diagnosed and ~1.3 million died – a survival rate unchanged since 1960. However, patients diagnosed at an early stage and have surgery experience an 86% overall 5-year survival. New diagnostics are therefore needed to identify lung cancer at this stage. Here we present the first large scale clinical use of aptamers to discover blood protein biomarkers in disease with our breakthrough proteomic technology. This multi-center case-control study was conducted in archived samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. We measured >800 proteins in 15uL of serum, identified 44 candidate biomarkers, and developed a 12-protein panel that distinguished NSCLC from controls with 91% sensitivity and 84% specificity in a training set and 89% sensitivity and 83% specificity in a blinded, independent verification set. Performance was similar for early and late stage NSCLC. This is a significant advance in proteomics in an area of high clinical need
Aptamer-based multiplexed proteomic technology for biomarker discovery
Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine
The dopamine β-hydroxylase -1021C/T polymorphism is associated with the risk of Alzheimer's disease in the Epistasis Project
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88930.pdf (publisher's version ) (Open Access)BACKGROUND: The loss of noradrenergic neurones of the locus coeruleus is a major feature of Alzheimer's disease (AD). Dopamine beta-hydroxylase (DBH) catalyses the conversion of dopamine to noradrenaline. Interactions have been reported between the low-activity -1021T allele (rs1611115) of DBH and polymorphisms of the pro-inflammatory cytokine genes, IL1A and IL6, contributing to the risk of AD. We therefore examined the associations with AD of the DBH -1021T allele and of the above interactions in the Epistasis Project, with 1757 cases of AD and 6294 elderly controls. METHODS: We genotyped eight single nucleotide polymorphisms (SNPs) in the three genes, DBH, IL1A and IL6. We used logistic regression models and synergy factor analysis to examine potential interactions and associations with AD. RESULTS: We found that the presence of the -1021T allele was associated with AD: odds ratio = 1.2 (95% confidence interval: 1.06-1.4, p = 0.005). This association was nearly restricted to men < 75 years old: odds ratio = 2.2 (1.4-3.3, 0.0004). We also found an interaction between the presence of DBH -1021T and the -889TT genotype (rs1800587) of IL1A: synergy factor = 1.9 (1.2-3.1, 0.005). All these results were consistent between North Europe and North Spain. CONCLUSIONS: Extensive, previous evidence (reviewed here) indicates an important role for noradrenaline in the control of inflammation in the brain. Thus, the -1021T allele with presumed low activity may be associated with misregulation of inflammation, which could contribute to the onset of AD. We suggest that such misregulation is the predominant mechanism of the association we report here
Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease
We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development
31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two
Background
The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd.
Methods
We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background.
Results
First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001).
Conclusions
In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival
Early Detection of Malignant Pleural Mesothelioma in Asbestos-Exposed Individuals with a Noninvasive Proteomics-Based Surveillance Tool
SARS-CoV-2 infection, inflammation and birth outcomes in a prospective NYC pregnancy cohort
Associations between antenatal SARS-CoV-2 infection and pregnancy outcomes have been conflicting and the role of the immune system is currently unclear. This prospective cohort study investigated the interaction of antenatal SARS-CoV-2 infection, changes in cytokine and HS-CRP levels, birthweight and gestational age at birth. 2352 pregnant participants from New York City (2020–2022) were included. Plasma levels of interleukin (IL)-1β, IL-6, IL-17A and high-sensitivity C-reactive protein (HS-CRP) were quantified in blood specimens obtained across pregnancy. Quantile and linear regression models were conducted to 1) assess the impact of antenatal SARS-CoV-2 infection, overall and by timing of detection of SARS-CoV-2 positivity (< 20 weeks versus ≥ 20 weeks), on birthweight and gestational age at delivery; 2) examine the relationship between SARS-CoV-2 infection and maternal immune changes during pregnancy. All models were adjusted for maternal demographic and obstetric factors and pandemic timing. Birthweight models were additionally adjusted for gestational age at delivery and fetal sex. Immune marker models were also adjusted for gestational age at specimen collection and multiplex assay batch. 371 (15.8%) participants were infected with SARS-CoV-2 during pregnancy, of which 98 (26.4%) were infected at < 20 weeks gestation. Neither SARS-CoV-2 infection in general nor in early or late pregnancy was associated with lower birthweight nor earlier gestational age at delivery. Further, we did not observe cytokine or HS-CRP changes in response to SARS-CoV-2 infection and thus found no evidence to support a potential association between immune dysregulation and the diversity in pregnancy outcomes following infection.</p
Early Detection of Malignant Pleural Mesothelioma in Asbestos-Exposed Individuals with a Noninvasive Proteomics-Based Surveillance Tool
<div><h3>Background</h3><p>Malignant pleural mesothelioma (MM) is an aggressive, asbestos-related pulmonary cancer that is increasing in incidence. Because diagnosis is difficult and the disease is relatively rare, most patients present at a clinically advanced stage where possibility of cure is minimal. To improve surveillance and detection of MM in the high-risk population, we completed a series of clinical studies to develop a noninvasive test for early detection.</p> <h3>Methodology/Principal Findings</h3><p>We conducted multi-center case-control studies in serum from 117 MM cases and 142 asbestos-exposed control individuals. Biomarker discovery, verification, and validation were performed using SOMAmer proteomic technology, which simultaneously measures over 1000 proteins in unfractionated biologic samples. Using univariate and multivariate approaches we discovered 64 candidate protein biomarkers and derived a 13-marker random forest classifier with an AUC of 0.99±0.01 in training, 0.98±0.04 in independent blinded verification and 0.95±0.04 in blinded validation studies. Sensitivity and specificity at our pre-specified decision threshold were 97%/92% in training and 90%/95% in blinded verification. This classifier accuracy was maintained in a second blinded validation set with a sensitivity/specificity of 90%/89% and combined accuracy of 92%. Sensitivity correlated with pathologic stage; 77% of Stage I, 93% of Stage II, 96% of Stage III and 96% of Stage IV cases were detected. An alternative decision threshold in the validation study yielding 98% specificity would still detect 60% of MM cases. In a paired sample set the classifier AUC of 0.99 and 91%/94% sensitivity/specificity was superior to that of mesothelin with an AUC of 0.82 and 66%/88% sensitivity/specificity. The candidate biomarker panel consists of both inflammatory and proliferative proteins, processes strongly associated with asbestos-induced malignancy.</p> <h3>Significance</h3><p>The SOMAmer biomarker panel discovered and validated in these studies provides a solid foundation for surveillance and diagnosis of MM in those at highest risk for this disease.</p> </div
Classifier performance for training, verification and validation.
<p>Percentage values at the predefined decision threshold and 95% confidence intervals.</p
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