Multiplexed LC–ESI–MRM‐MS‐based Assay for Identification of Coronary Artery Disease Biomarkers in Human Plasma

Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

Quantitative Proteomics of Maternal Blood Plasma in Isolated Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) remains a significant concern in modern obstetrics, linked to high neonatal health problems and even death, as well as childhood disability, affecting adult quality of life. The role of maternal and fetus adaptation during adverse pregnancy is still not completely understood. This study aimed to investigate the disturbance in biological processes associated with isolated IUGR via blood plasma proteomics. The levels of 125 maternal plasma proteins were quantified by liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with corresponding stable isotope-labeled peptide standards (SIS). Thirteen potential markers of IUGR (Gelsolin, Alpha-2-macroglobulin, Apolipoprotein A-IV, Apolipoprotein B-100, Apolipoprotein(a), Adiponectin, Complement C5, Apolipoprotein D, Alpha-1B-glycoprotein, Serum albumin, Fibronectin, Glutathione peroxidase 3, Lipopolysaccharide-binding protein) were found to be inter-connected in a protein-protein network. These proteins are involved in plasma lipoprotein assembly, remodeling, and clearance; lipid metabolism, especially cholesterol and phospholipids; hemostasis, including platelet degranulation; and immune system regulation. Additionally, 18 proteins were specific to a particular type of IUGR (early or late). Distinct patterns in the coagulation and fibrinolysis systems were observed between isolated early- and late-onset IUGR. Our findings highlight the complex interplay of immune and coagulation factors in IUGR and the differences between early- and late-onset IUGR and other placenta-related conditions like PE. Understanding these mechanisms is crucial for developing targeted interventions and improving outcomes for pregnancies affected by IUGR.

Development of Extracellular Vesicle Therapeutics: Challenges, Considerations, and Opportunities

Extracellular vesicles (EVs) hold great promise as therapeutic modalities due to their endogenous characteristics, however, further bioengineering refinement is required to address clinical and commercial limitations. Clinical applications of EV-based therapeutics are being trialed in immunomodulation, tissue regeneration and recovery, and as delivery vectors for combination therapies. Native/biological EVs possess diverse endogenous properties that offer stability and facilitate crossing of biological barriers for delivery of molecular cargo to cells, acting as a form of intercellular communication to regulate function and phenotype. Moreover, EVs are important components of paracrine signaling in stem/progenitor cell-based therapies, are employed as standalone therapies, and can be used as a drug delivery system. Despite remarkable utility of native/biological EVs, they can be improved using bio/engineering approaches to further therapeutic potential. EVs can be engineered to harbor specific pharmaceutical content, enhance their stability, and modify surface epitopes for improved tropism and targeting to cells and tissues in vivo. Limitations currently challenging the full realization of their therapeutic utility include scalability and standardization of generation, molecular characterization for design and regulation, therapeutic potency assessment, and targeted delivery. The fields' utilization of advanced technologies (imaging, quantitative analyses, multi-omics, labeling/live-cell reporters), and utility of biocompatible natural sources for producing EVs (plants, bacteria, milk) will play an important role in overcoming these limitations. Advancements in EV engineering methodologies and design will facilitate the development of EV-based therapeutics, revolutionizing the current pharmaceutical landscape.

Proteomic landscape of human coronary artery atherosclerosis

In order to investigate novel biomarkers for the detection of coronary artery disease for effective therapeutic targets, a comprehensive understanding of the protein networks and protein expression abundance in coronary artery samples is required. This was established by means of liquid chromatography (LC)-mass spectrometry (MS)/MS analysis in the present study. A total of 20 human coronary artery specimens from 2 autopsied adults were employed in the present study. The natural history and histological classification of the atherosclerotic lesions of the coronary artery samples were analyzed by hematoxylin and eosin (H&E) staining, and the human coronary arterial proteome and proteomics features were characterized by MS analysis. The present study identified 2,135 proteins in the 20 coronary artery segments samples from the 2 cases. Combined with the results of H&E staining of the coronary artery samples, a total of 174 proteins, including 4 upregulated proteins and 164 downregulated proteins (excluding 6 proteins with inconsistent expression tendencies), were shown to be associated with coronary artery disease. In addition, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment of the differentially expressed proteins revealed that the mitochondrial energy metabolism may be responsible for the occurrence and development of coronary artery atherosclerosis. The human coronary arterial proteome can be considered as a complex network whose architectural characteristics vary considerably as a function of the presence or absence, and histological classification of coronary artery atherosclerosis. These data thus suggest that the prevention of mitochondrial dysfunction via the retrieval of the mitochondrial associated proteins expression may be a promising target in coronary artery disease.

Value-based healthcare delivery through metabolomics-based personalized health platform

Type 2 diabetes is routinely identified in clinical practice by tests that rely on a hyperglycemic index. However, people at risk for developing type 2 diabetes may not present with hyperglycemia. We identified several underlying risks for type 2 diabetes, insulin resistance, and associated co-morbidities, using a liquid chromatography mass spectrometry-based analysis of blood metabolites, in participants with normoglycemia and no clinical symptoms. Personalized lifestyle recommendations, including diet, exercise, and nutritional supplement recommendations, were conveyed to these participants by a web-based platform, and after 100 days of following their recommendations, these participants reported reductions in the health risks associated with type 2 diabetes and associated diseases. Our comprehensive metabolite-based assay can be used for type 2 diabetes risk stratification, and our personalized lifestyle recommendation system could be deployed as a preventative treatment option to improve health outcomes, reduce the incidence of chronic disease, and live healthier lives in an evidence-based way.

Identification of Putative Early Atherosclerosis Biomarkers by Unsupervised Deconvolution of Heterogeneous Vascular Proteomes

Coronary artery disease remains a leading cause of death in industrialized nations, and early detection of disease is a critical intervention target to effectively treat patients and manage risk. Proteomic analysis of mixed tissue homogenates may obscure subtle protein changes that occur uniquely in underlying tissue subtypes. The unsupervised 'convex analysis of mixtures' (CAM) tool has previously been shown to effectively segregate cellular subtypes from mixed expression data. In this study, we hypothesized that CAM would identify proteomic information specifically informative to early atherosclerosis lesion involvement that could lead to potential markers of early disease detection. We quantified the proteome of 99 paired abdominal aorta (AA) and left anterior descending coronary artery (LAD) specimens (N = 198 specimens total) acquired during autopsy of young adults free of diagnosed cardiac disease. The CAM tool was then used to segregate protein subsets uniquely associated with different underlying tissue types, yielding markers of normal and fibrous plaque (FP) tissues in LAD and AA (N = 62 lesions markers). CAM-derived FP marker expression was validated against pathologist estimated luminal surface involvement of FP, as well as in an orthogonal cohort of "pure" fibrous plaque, fatty streak, and normal vascular specimens. A targeted mass spectrometry (MS) assay quantified 39 of 62 CAM-FP markers in plasma from women with angiographically verified coronary artery disease (CAD, N = 46) or free from apparent CAD (control, N = 40). Elastic net variable selection with logistic regression reduced this list to 10 proteins capable of classifying CAD status in this cohort with <6% misclassification error, and a mean area under the receiver operating characteristic curve of 0.992 (confidence interval 0.968-0.998) after cross validation. The proteomics-CAM workflow identified lesion-specific molecular biomarker candidates by distilling the most representative molecules from heterogeneous tissue types.

Assessment of Serological Early Biomarker Candidates for Lung Adenocarcinoma by using Multiple Reaction Monitoring-Mass Spectrometry

PURPOSE

Plasma markers that enable diagnosis in the early stage of lung cancer is not discovered. A liquid chromatography multiple reaction monitoring-mass spectrometry (LC-MRM-MS) assay for identifying potential early marker proteins for lung adenocarcinoma is developed.

EXPERIMENTAL DESIGN

LC-MRM-MS assay is used for measuring the level of 35 candidate peptides in plasma from 102 lung adenocarcinoma patients (including n = 50, 16, 24, and 12 in stage I, II, III, and IV, respectively.) and 84 healthy controls. Stable isotope labeled standard peptides are synthesized to accurately measure the amount of these proteins.

RESULTS

Seven proteins are able to distinguish stage I patients from controls. These proteins are combined in to a protein marker panel which improve the sensitivity to discriminate stage I patients from controls with cross-validated area under the curve = 0.76. Besides, it is found that low expression of eukaryotic initiation factor 4A-I and high expression of lumican show significantly poor prognosis in overall survival (p = 0.012 and 0.0074, respectively), which may be used as prognostic biomarkers for lung cancer.

CONCLUSIONS AND CLINICAL RELEVANCE

Proteins highlighted here may be used for early detection of lung adenocarcinoma or therapeutics development after validation in a larger cohort.

An MRM-Based Multiplexed Quantification Assay for Human Adipokines and Apolipoproteins

Adipokines and apolipoproteins are key regulators and potential biomarkers in obesity and associated diseases and their quantitative assessment is crucial for functional analyses to understand disease mechanisms. Compared to routinely used ELISAs, multiple reaction monitoring (MRM)-based mass spectrometry allows multiplexing and detection of proteins for which antibodies are not available. Thus, we established an MRM method to quantify 9 adipokines and 10 apolipoproteins in human serum. We optimized sample preparation by depleting the two most abundant serum proteins for improved detectability of low abundant proteins. Intra-day and inter-day imprecision were below 16.5%, demonstrating a high accuracy. In 50 serum samples from participants with either normal weight or obesity, we quantified 8 adipokines and 10 apolipoproteins. Significantly different abundances were observed for five adipokines (adipsin, adiponectin, chemerin, leptin, vaspin) and four apolipoproteins (apo-B100/-C2/-C4/-D) between the body mass index (BMI) groups. Additionally, we applied our MRM assay to serum samples from normal weight children and human adipocyte cell culture supernatants to proof the feasibility for large cohort studies and distinct biological matrices. In summary, this multiplexed assay facilitated the investigation of relationships between adipokines or apolipoproteins and phenotypes or clinical parameters in large cohorts, which may contribute to disease prediction approaches in the future.

An external quality assurance trial to assess mass spectrometry protein testing facilities for identifying multiple human peptides

The application of proteomic liquid chromatography mass spectrometry (LC-MS) for identifying proteins and peptides associated with human disease is rapidly growing in clinical diagnostics. However, the ability to accurately and consistently detect disease-associated peptides remains clinically uncertain. Variability in diagnostic testing occurs in part due to the absence of appropriate reference testing materials and standardised clinical guidelines for proteomic testing. In addition, multiple proteomic testing pipelines have not been fully assessed through external quality assurance (EQA). This trial was therefore devised to evaluate the performance of a small number of mass spectrometry (MS) testing facilities to (i) evaluate the EQA material for potential usage in a proteomic quality assurance program, and to (ii) identify key problem areas associated with human peptide testing. Five laboratories were sent six peptide reference testing samples formulated to contain a total of 35 peptides in differing ratios of light (natural) to heavy (labelled) peptides. Proficiency assessment of laboratory data used a modified approach to similarity and dissimilarity testing that was based on Bray-Curtis and Sorensen indices. Proficiency EQA concordant consensus values could not be derived from the assessed data since none of the laboratories correctly identified all reference testing peptides in all samples. However, the produced data may be reflective of specific inter-laboratory differences for detecting multiple peptides since no two testing pipelines used were the same for any laboratory. In addition, laboratory feedback indicated that peptide filtering of the reference material was a common key problem area prior to analysis. These data highlight the importance of an EQA programme for identifying underlying testing issues so that improvements can be made and confidence for clinical diagnostic analysis can be attained.