Next generation pan-cancer blood proteome profiling using proximity extension assay
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens (human)
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PROVIDER: S-BSST935 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Understanding the dynamics of the human proteome is crucial for developing biomarkers to be used as measurable indicators for disease severity and progression, patient stratification, and drug development. The Proximity Extension Assay (PEA) is a technology that translates protein information into actionable knowledge by linking protein-specific antibodies to DNA-encoded tags. In this report we demonstrate how we have combined the unique PEA technology with an innovative and automated sample preparation and high-throughput sequencing readout enabling parallel measurement of nearly 1500 proteins in 96 samples generating close to 150,000 data points per run. This advancement will have a major impact on the discovery of new biomarkers for disease prediction and prognosis and contribute to the development of the rapidly evolving fields of wellness monitoring and precision medicine.
| S-EPMC8633680 | biostudies-literature
Project description:The need for precision medicine approaches to monitor health and disease makes it important to develop sensitive and accurate assays for proteome profiles in blood. Here, we describe an approach for plasma profiling based on proximity extension assay combined with next generation sequencing. First, we analyze the variability of plasma profiles between and within healthy individuals in a longitudinal wellness study, including the influence of genetic variations on plasma levels. Second, we follow patients newly diagnosed with type 2 diabetes before and during therapeutic intervention using plasma proteome profiling. The studies show that healthy individuals have a unique and stable proteome profile and indicate that a panel of proteins could potentially be used for early diagnosis of diabetes, including stratification of patients with regards to response to metformin treatment. Although validation in larger cohorts is needed, the analysis demonstrates the usefulness of comprehensive plasma profiling for precision medicine efforts.
| S-EPMC8093230 | biostudies-literature
Project description:Exosomes have been implicated in numerous biological processes, and they may serve as important disease markers. Surface proteins on exosomes carry information about their tissues of origin. Because of the heterogeneity of exosomes it is desirable to investigate them individually, but this has so far remained impractical. Here, we demonstrate a proximity-dependent barcoding assay to profile surface proteins of individual exosomes using antibody-DNA conjugates and next-generation sequencing. We first validate the method using artificial streptavidin-oligonucleotide complexes, followed by analysis of the variable composition of surface proteins on individual exosomes, derived from human body fluids or cell culture media. Exosomes from different sources are characterized by the presence of specific combinations of surface proteins and their abundance, allowing exosomes to be separately quantified in mixed samples to serve as markers for tissue-specific engagement in disease.
| S-EPMC6710248 | biostudies-literature
Project description: Not available
| S-BSST719 | biostudies-other
Project description:Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates.
| S-EPMC6442356 | biostudies-literature
Project description:BackgroundCOVID-19 has caused millions of deaths globally, yet the cellular mechanisms underlying the various effects of the disease remain poorly understood. Recently, a new analytical platform for comprehensive analysis of plasma protein profiles using proximity extension assays combined with next generation sequencing has been developed, which allows for multiple proteins to be analyzed simultaneously without sacrifice on accuracy or sensitivity.MethodsWe analyzed the plasma protein profiles of COVID-19 patients (n = 50) with mild and moderate symptoms by comparing the protein levels in newly diagnosed patients with the protein levels in the same individuals after 14 days.FindingsThe study has identified more than 200 proteins that are significantly elevated during infection and many of these are related to cytokine response and other immune-related functions. In addition, several other proteins are shown to be elevated, including SCARB2, a host cell receptor protein involved in virus entry. A comparison with the plasma protein response in patients with severe symptoms shows a highly similar pattern, but with some interesting differences.InterpretationThe study presented here demonstrates the usefulness of "next generation plasma protein profiling" to identify molecular signatures of importance for disease progression and to allow monitoring of disease during recovery from the infection. The results will facilitate further studies to understand the molecular mechanism of the immune-related response of the SARS-CoV-2 virus.FundingThis work was financially supported by Knut and Alice Wallenberg Foundation.
| S-EPMC8626206 | biostudies-literature
Project description:Targeted proteomics utilizing antibody-based proximity extension assays provides sensitive and highly specific quantifications of plasma protein levels. Multivariate analysis of this data is hampered by frequent missing values (random or left censored), calling for imputation approaches. While appropriate missing-value imputation methods exist, benchmarks of their performance in targeted proteomics data are lacking. Here, we assessed the performance of two methods for imputation of values missing completely at random, the previously top-benchmarked 'missForest' and the recently published 'GSimp' method. Evaluation was accomplished by comparing imputed with remeasured relative concentrations of 91 inflammation related circulating proteins in 86 samples from a cohort of 645 patients with venous thromboembolism. The median Pearson correlation between imputed and remeasured protein expression values was 69.0% for missForest and 71.6% for GSimp (p = 5.8e-4). Imputation with missForest resulted in stronger reduction of variance compared to GSimp (median relative variance of 25.3% vs. 68.6%, p = 2.4e-16) and undesired larger bias in downstream analyses. Irrespective of the imputation method used, the 91 imputed proteins revealed large variations in imputation accuracy, driven by differences in signal to noise ratio and information overlap between proteins. In summary, GSimp outperformed missForest, while both methods show good overall imputation accuracy with large variations between proteins.
| S-EPMC7735586 | biostudies-literature
Project description:BACKGROUND:Cystic fibrosis is a life-threatening genetic disorder that has been associated with mutations in the CFTR [cystic fibrosis transmembrane conductance regulator (ATP-binding cassette sub-family C, member 7)] gene. Hundreds of CFTR mutations have been detected to date. Current CFTR genotyping assays target a subset of these mutations, particularly a mutation panel recommended by the American College of Medical Genetics for carrier screening of the general population. Fast sequencing of the entire coding sequence in a scalable manner could expand the detection of CFTR mutations and facilitate management of costs and turnaround times in the clinical laboratory. METHODS:We describe a proof-of-concept CFTR assay that uses PCR target enrichment and next-generation sequencing on the Ion Torrent Personal Genome Machine™ (PGM™) platform. RESULTS:The scalability of the assay was demonstrated, with an average mean depth of coverage ranging from 500× to 3500×, depending on the number of multiplexed patient samples and the Ion Torrent chip used. In a blinded study of 79 previously genotyped patient DNA samples and cell lines, our assay detected most of the mutations, including single-nucleotide variants, small insertions and deletions, and large copy-number variants. The reproducibility was 100% for detecting mutations in independent runs. Our assay demonstrated high specificity, with only 2 false-positive calls (at 2184delA) found in 2 samples caused by a sequencing error in a homopolymer stretch of sequence. The detection rate for variants of unknown significance was very low in the targeted region. CONCLUSIONS:With continued optimization and system refinements, PGM sequencing promises to be a powerful, rapid, and scalable means of clinical diagnostic sequencing.
| S-EPMC4570467 | biostudies-literature
Project description:Saliva is an easy-to access body fluid with high diagnostic potential. The utilization of saliva for oral cancer diagnosis can be an attractive possibility. Besides the oral cancer, it is important to better understand the precancerous lesions such as oral lichen planus (OLP) and leukoplakia (OLK). In order to examine the changes of salivary proteins in controls, patients with oral cancer, and patients with precancerous conditions, proximity extension assay was utilized. Some proteins and functions were characteristic to the examined groups and can serve as a starting point for further biomarker studies. The different nature of OLK and OLP was demonstrated, showing the malignant transformation and the inflammation as the prominent biological processes in the OLK and OLP, respectively. The salivary level of IL6 was verified using quantitative ELISA and the mRNA level was also studied. Elevated IL6 levels could be detected in precancerous groups compared to controls.
| S-EPMC7764999 | biostudies-literature
Project description:OBJECTIVE:The high degree of clinical overlap between atypical parkinsonian syndromes (APS) and Parkinson's disease (PD) makes diagnosis challenging. We aimed to identify novel diagnostic protein biomarkers of APS using multiplex proximity extension assay (PEA) testing. METHODS:Cerebrospinal fluid (CSF) samples from two independent cohorts, each consisting of APS and PD cases, and controls, were analysed for neurofilament light chain (NF-L) and Olink Neurology and Inflammation PEA biomarker panels. Whole-cohort comparisons of biomarker concentrations were made between APS (n=114), PD (n=37) and control (n=34) groups using logistic regression analyses that included gender, age and disease duration as covariates. RESULTS:APS versus controls analyses revealed 11 CSF markers with significantly different levels in cases and controls (p<0.002). Four of these markers also reached significance (p<0.05) in APS versus PD analyses. Disease-specific analyses revealed lower group levels of FGF-5, FGF-19 and SPOCK1 in multiple system atrophy compared with progressive supranuclear palsy and corticobasal syndrome. Receiver operating characteristic curve analyses suggested that the diagnostic accuracy of NF-L was superior to the significant PEA biomarkers in distinguishing APS, PD and controls. The biological processes regulated by the significant proteins include cell differentiation and immune cell migration. Delta and notch-like epidermal growth factor-related receptor (DNER) had the strongest effect size in APS versus controls and APS versus PD analyses. DNER is highly expressed in substantia nigra and is an activator of the NOTCH1 pathway which has been implicated in the aetiology of other neurodegenerative disorders including Alzheimer's disease. CONCLUSIONS:PEA testing has identified potential novel diagnostic biomarkers of APS.
| S-EPMC6585258 | biostudies-literature