Highly Multiplexed Proteomic Platform for Biomarker Discovery, Diagnostics, and Therapeutics

Serum protein risk stratification score for diagnostic evaluation of metabolic dysfunction-associated steatohepatitis

BACKGROUND

Reliable, noninvasive tools to diagnose at-risk metabolic dysfunction-associated steatohepatitis (MASH) are urgently needed to improve management. We developed a risk stratification score incorporating proteomics-derived serum markers with clinical variables to identify high-risk patients with MASH (NAFLD activity score >4 and fibrosis score >2).

METHODS

In this 3-phase proteomic study of biopsy-proven metabolic dysfunction-associated steatotic fatty liver disease, we first developed a multi-protein predictor for discriminating NAFLD activity score >4 based on SOMAscan proteomics quantifying 1305 serum proteins from 57 US patients. Four key predictor proteins were verified by ELISA in the expanded US cohort (N = 168) and enhanced by adding clinical variables to create the 9-feature MASH Dx score, which predicted MASH and also high-risk MASH (F2+). The MASH Dx score was validated in 2 independent, external cohorts from Germany (N = 139) and Brazil (N = 177).

RESULTS

The discovery phase identified a 6-protein classifier that achieved an AUC of 0.93 for identifying MASH. Significant elevation of 4 proteins (THBS2, GDF15, SELE, and IGFBP7) was verified by ELISA in the expanded discovery and independently in the 2 external cohorts. MASH Dx score incorporated these proteins with established MASH risk factors (age, body mass index, ALT, diabetes, and hypertension) to achieve good discrimination between MASH and metabolic dysfunction-associated steatotic fatty liver disease without MASH (AUC: 0.87-discovery; 0.83-pooled external validation cohorts), with similar performance when evaluating high-risk MASH F2-4 (vs. MASH F0-1 and metabolic dysfunction-associated steatotic fatty liver disease without MASH).

CONCLUSIONS

The MASH Dx score offers the first reliable noninvasive approach combining novel, biologically plausible ELISA-based fibrosis markers and clinical parameters to detect high-risk MASH in patient cohorts from the United States, Brazil, and Europe.

Crossing the Halfway Point: Aptamer-Based, Highly Multiplexed Assay for the Assessment of the Proteome

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

SomaLogic proteomics reveals new biomarkers and provides mechanistic, clinical insights into Acetyl coA Carboxylase (ACC) inhibition in Non-alcoholic Steatohepatitis (NASH)

Non-alcoholic Fatty Liver Disease (NAFLD) and Non-alcoholic Steatohepatitis (NASH) are major metabolic diseases with increasing global prevalence and no approved therapies. There is a mounting need to develop biomarkers of diagnosis, prognosis and treatment response that can effectively replace current requirements for liver biopsies, which are invasive, error-prone and expensive. We performed SomaLogic serum proteome profiling with baseline (n = 231) and on-treatment (n = 72, Weeks 12 and 16, Placebo and 25 mg PF-05221304) samples from a Phase 2a trial (NCT03248882) with Clesacostat (PF-05221304), an acetyl coA carboxylase inhibitor (ACCi) in patients with NAFLD/NASH. SomaSignal NASH probability scores and expression data for 7000+ analytes were analyzed to identify potential biomarkers associated with baseline clinical measures of NAFLD/NASH [Magnetic Resonance Imaging-Proton Density Fat Fraction (MRI-PDFF), alanine aminotransferase (ALT) and aspartate aminotransferase (AST)] as well as biomarkers of treatment response to ACCi. SomaSignal NASH probability scores identified biopsy-proven/clinically defined NIT-based (Presumed) NASH classification of the cohort with > 70% agreement. Clesacostat-induced reduction in steatosis probability scores aligned with observed clinical reduction in hepatic steatosis based on MRI-PDFF. We identify a set of 69 analytes that robustly correlate with clinical measures of hepatic inflammation and steatosis (MRI-PDFF, ALT and AST), 27 of which were significantly reversed with ACC inhibition. Clesacostat treatment dramatically upregulated Wnt5a protein and Apolipoproteins C3 and E, with drug-induced changes significantly correlating to changes on MRI-PDFF. Our data demonstrate the utility of SomaLogic- analyte panel for diagnosis and treatment response in NAFLD/NASH and provide potential new mechanistic insights into liver steatosis reduction, inflammation and serum triglyceride elevation with ACC inhibition. (Clinical Trial Identifier: NCT03248882).

Multimodal Analytical Tools to Enhance Mechanistic Understanding of Aortic Valve Calcification

This review focuses on technologies at the core of calcific aortic valve disease (CAVD) and drug target research advancement, including transcriptomics, proteomics, and molecular imaging. We examine how bulk RNA sequencing and single-cell RNA sequencing have engendered organismal genomes and transcriptomes, promoting the analysis of tissue gene expression profiles and cell subpopulations, respectively. We bring into focus how the field is also largely influenced by increasingly accessible proteome profiling techniques. In unison, global transcriptional and protein expression analyses allow for increased understanding of cellular behavior and pathogenic pathways under pathologic stimuli including stress, inflammation, low-density lipoprotein accumulation, increased calcium and phosphate levels, and vascular injury. We also look at how direct investigation of protein signatures paves the way for identification of targetable pathways for pharmacologic intervention. Here, we note that imaging techniques, once a clinical diagnostic tool for late-stage CAVD, have since been refined to address a clinical need to identify microcalcifications using positron emission tomography/computed tomography and even detect in vivo cellular events indicative of early stage CAVD and map the expression of identified proteins in animal models. Together, these techniques generate a holistic approach to CAVD investigation, with the potential to identify additional novel regulatory pathways.

Cancer biomarkers: Emerging trends and clinical implications for personalized treatment

The integration of cancer biomarkers into oncology has revolutionized cancer treatment, yielding remarkable advancements in cancer therapeutics and the prognosis of cancer patients. The development of personalized medicine represents a turning point and a new paradigm in cancer management, as biomarkers enable oncologists to tailor treatments based on the unique molecular profile of each patient's tumor. In this review, we discuss the scientific milestones of cancer biomarkers and explore future possibilities to improve the management of patients with solid tumors. This progress is primarily attributed to the biological characterization of cancers, advancements in testing methodologies, elucidation of the immune microenvironment, and the ability to profile circulating tumor fractions. Integrating these insights promises to continually advance the precision oncology field, fostering better patient outcomes.

Differential peripheral immune signatures elicited by vegan versus ketogenic diets in humans

Nutrition has broad impacts on all physiological processes. However, how nutrition affects human immunity remains largely unknown. Here we explored the impact of a dietary intervention on both immunity and the microbiota by performing a post hoc analysis of a clinical trial in which each of the 20 participants sequentially consumed vegan or ketogenic diets for 2 weeks ( NCT03878108 ). Using a multiomics approach including multidimensional flow cytometry, transcriptomic, proteomic, metabolomic and metagenomic datasets, we assessed the impact of each diet, and dietary switch, on host immunity and the microbiota. Our data revealed that overall, a ketogenic diet was associated with a significant upregulation of pathways and enrichment in cells associated with the adaptive immune system. In contrast, a vegan diet had a significant impact on the innate immune system, including upregulation of pathways associated with antiviral immunity. Both diets significantly and differentially impacted the microbiome and host-associated amino acid metabolism, with a strong downregulation of most microbial pathways following ketogenic diet compared with baseline and vegan diet. Despite the diversity of participants, we also observed a tightly connected network between datasets driven by compounds associated with amino acids, lipids and the immune system. Collectively, this work demonstrates that in diverse participants 2 weeks of controlled dietary intervention is sufficient to significantly and divergently impact host immunity, which could have implications for precision nutritional interventions. ClinicalTrials.gov registration: NCT03878108 .

Are EPB41 and alpha-synuclein diagnostic biomarkers of sport-related concussion? Findings from the NCAA and Department of Defense CARE Consortium

BACKGROUND

Current protein biomarkers are only moderately predictive at identifying individuals with mild traumatic brain injury or concussion. Therefore, more accurate diagnostic markers are needed for sport-related concussion.

METHODS

This was a multicenter, prospective, case-control study of athletes who provided blood samples and were diagnosed with a concussion or were a matched non-concussed control within the National Collegiate Athletic Association-Department of Defense Concussion Assessment, Research, and Education Consortium conducted between 2015 and 2019. The blood was collected within 48 h of injury to identify protein abnormalities at the acute and subacute timepoints. Athletes with concussion were divided into 6 h post-injury (0-6 h post-injury) and after 6 h post-injury (7-48 h post-injury) groups. We applied a highly multiplexed proteomic technique that used a DNA aptamers assay to target 1305 proteins in plasma samples from athletes with and without sport-related concussion.

RESULTS

A total of 140 athletes with concussion (79.3% males; aged 18.71 ± 1.10 years, mean ± SD) and 21 non-concussed athletes (76.2% males; 19.14 ± 1.10 years) were included in this study. We identified 338 plasma proteins that significantly differed in abundance (319 upregulated and 19 downregulated) in concussed athletes compared to non-concussed athletes. The top 20 most differentially abundant proteins discriminated concussed athletes from non-concussed athletes with an area under the curve (AUC) of 0.954 (95% confidence interval: 0.922‒0.986). Specifically, after 6 h of injury, the individual AUC of plasma erythrocyte membrane protein band 4.1 (EPB41) and alpha-synuclein (SNCA) were 0.956 and 0.875, respectively. The combination of EPB41 and SNCA provided the best AUC (1.000), which suggests this combination of candidate plasma biomarkers is the best for diagnosing concussion in athletes after 6 h of injury.

CONCLUSION

Our data suggest that proteomic profiling may provide novel diagnostic protein markers and that a combination of EPB41 and SNCA is the most predictive biomarker of concussion after 6 h of injury.

Perinatal mood and anxiety disorders: biomarker discovery using plasma proteomics

BACKGROUND

Perinatal mood and anxiety disorders encompass a range of mental health disorders that occur during pregnancy and up to 1 year postpartum, affecting approximately 20% of women. Traditional risk factors, such as a history of depression and pregnancy complications including preeclampsia, are known. Their predictive utility, however, is not specific or sensitive enough to inform clinical decision-making or prevention strategies for perinatal mood and anxiety disorders. Better diagnostic and prognostic models are needed for early identification and referral to treatment.

OBJECTIVE

This study aimed to determine if a panel of novel third-trimester plasma protein biomarkers in pregnant women can be used to identify those who have a high predisposed risk for perinatal mood and anxiety disorders within 3 months postpartum.

STUDY DESIGN

We studied 52 women (n=34 with a risk for perinatal mood and anxiety disorders and n=18 controls) among whom mental health screening was conducted at 2 time points, namely in the third trimester and again at 3 months postdelivery. An elevated perinatal mood and anxiety disorder risk was identified by screening individuals with above-validated cutoffs for depression (Edinburgh Postnatal Depression Scale ≥12), anxiety (Overall Anxiety Severity and Impairment Scale ≥7), and/or posttraumatic stress disorder (Impact of Events Scale >26) at both time points. Plasma samples collected in the third trimester were screened using the aptamer-based SomaLogic SomaScan proteomic assay technology to evaluate perinatal mood and anxiety disorder-associated changes in the expression of 1305 protein analytes. Ingenuity Pathway Analysis was conducted to highlight pathophysiological relationships between perinatal mood and anxiety disorder-specific proteins found to be significantly up- or down-regulated in all subjects with perinatal mood and anxiety disorder and in those with perinatal mood and anxiety disorders and no preeclampsia.

RESULTS

From a panel of 53 significant perinatal mood and anxiety disorder-associated proteins, a unique 20-protein signature differentiated perinatal mood and anxiety disorder cases from controls in a principal component analysis (P<.05). This protein signature included NCAM1, NRCAM, and NTRK3 that converge around neuronal signaling pathways regulating axonal guidance, astrocyte differentiation, and maintenance of GABAergic neurons. Interestingly, when we restricted the analysis to subjects without preeclampsia, a 30-protein signature differentiated perinatal mood and anxiety disorder cases from all controls without overlap on the principal component analysis (P<.001). In the nonpreeclamptic perinatal mood and anxiety disorder group, we observed increased expression of proteins, such as CXCL11, CXCL6, MIC-B, and B2MG, which regulate leucocyte migration, inflammation, and immune function.

CONCLUSION

Participants with perinatal mood and anxiety disorders had a unique and distinct plasma protein signature that regulated a variety of neuronal signaling and proinflammatory pathways. Additional validation studies with larger sample sizes are needed to determine whether some of these molecules can be used in conjunction with traditional risk factors for the early detection of perinatal mood and anxiety disorders.

Proteomic Profiling of Plasma Biomarkers Associated With Return to Sport Following Concussion: Findings From the NCAA and Department of Defense CARE Consortium

Objective

To investigate the plasma proteomic profiling in identifying biomarkers related to return to sport (RTS) following a sport-related concussion (SRC).

Methods

This multicenter, prospective, case-control study was part of a larger cohort study conducted by the NCAA-DoD Concussion Assessment, Research, and Education (CARE) Consortium, athletes (n = 140) with blood collected within 48 h of injury and reported day to asymptomatic were included in this study, divided into two groups: (1) recovery <14-days (n = 99) and (2) recovery ≥14-days (n = 41). We applied a highly multiplexed proteomic technique that uses DNA aptamers assay to target 1,305 proteins in plasma samples from concussed athletes with <14-days and ≥14-days.

Results

We identified 87 plasma proteins significantly dysregulated (32 upregulated and 55 downregulated) in concussed athletes with recovery ≥14-days relative to recovery <14-days groups. The significantly dysregulated proteins were uploaded to Ingenuity Pathway Analysis (IPA) software for analysis. Pathway analysis showed that significantly dysregulated proteins were associated with STAT3 pathway, regulation of the epithelial mesenchymal transition by growth factors pathway, and acute phase response signaling.

Conclusion

Our data showed the feasibility of large-scale plasma proteomic profiling in concussed athletes with a <14-days and ≥ 14-days recovery. These findings provide a possible understanding of the pathophysiological mechanism in neurobiological recovery. Further study is required to determine whether these proteins can aid clinicians in RTS decisions.

Proteomics and Population Biology in the Cardiovascular Health Study (CHS): design of a study with mentored access and active data sharing

BACKGROUND

In the last decade, genomic studies have identified and replicated thousands of genetic associations with measures of health and disease and contributed to the understanding of the etiology of a variety of health conditions. Proteins are key biomarkers in clinical medicine and often drug-therapy targets. Like genomics, proteomics can advance our understanding of biology.

METHODS AND RESULTS

In the setting of the Cardiovascular Health Study (CHS), a cohort study of older adults, an aptamer-based method that has high sensitivity for low-abundance proteins was used to assay 4979 proteins in frozen, stored plasma from 3188 participants (61% women, mean age 74 years). CHS provides active support, including central analysis, for seven phenotype-specific working groups (WGs). Each CHS WG is led by one or two senior investigators and includes 10 to 20 early or mid-career scientists. In this setting of mentored access, the proteomic data and analytic methods are widely shared with the WGs and investigators so that they may evaluate associations between baseline levels of circulating proteins and the incidence of a variety of health outcomes in prospective cohort analyses. We describe the design of CHS, the CHS Proteomics Study, characteristics of participants, quality control measures, and structural characteristics of the data provided to CHS WGs. We additionally highlight plans for validation and replication of novel proteomic associations.

CONCLUSION

The CHS Proteomics Study offers an opportunity for collaborative data sharing to improve our understanding of the etiology of a variety of health conditions in older adults.

Metformin for treatment of cytopenias in children and young adults with Fanconi anemia

Fanconi anemia (FA), a genetic DNA repair disorder characterized by marrow failure and cancer susceptibility. In FA mice, metformin improves blood counts and delays tumor development. We conducted a single institution study of metformin in nondiabetic patients with FA to determine feasibility and tolerability of metformin treatment and to assess for improvement in blood counts. Fourteen of 15 patients with at least 1 cytopenia (hemoglobin < 10 g/dL; platelet count < 100 000 cells/µL; or an absolute neutrophil count < 1000 cells/µL) were eligible to receive metformin for 6 months. Median patient age was 9.4 years (range 6.0-26.5 ). Thirteen of 14 subjects (93%) tolerated maximal dosing for age; 1 subject had dose reduction for grade 2 gastrointestinal symptoms. No subjects developed hypoglycemia or metabolic acidosis. No subjects had dose interruptions caused by toxicity, and no grade 3 or higher adverse events attributed to metformin were observed. Hematologic response based on modified Myelodysplastic Syndrome International Working Group criteria was observed in 4 of 13 evaluable patients (30.8%; 90% confidence interval, 11.3-57.3). Median time to response was 84.5 days (range 71-128 days). Responses were noted in neutrophils (n = 3), platelets (n = 1), and red blood cells (n = 1). No subjects met criteria for disease progression or relapse during treatment. Correlative studies explored potential mechanisms of metformin activity in FA. Plasma proteomics showed reduction in inflammatory pathways with metformin. Metformin is safe and tolerable in nondiabetic patients with FA and may provide therapeutic benefit. This trial was registered at as #NCT03398824.

Uncovering the Depths of the Human Proteome: Antibody-based Technologies for Ultrasensitive Multiplexed Protein Detection and Quantification

Probing the human proteome in tissues and biofluids such as plasma is attractive for biomarker and drug target discovery. Recent breakthroughs in multiplex, antibody-based, proteomics technologies now enable the simultaneous quantification of thousands of proteins at as low as sub fg/ml concentrations with remarkable dynamic ranges of up to 10-log. We herein provide a comprehensive guide to the methodologies, performance, technical comparisons, advantages, and disadvantages of established and emerging technologies for the multiplexed ultrasensitive measurement of proteins. Gaining holistic knowledge on these innovations is crucial for choosing the right multiplexed proteomics tool for applications at hand to critically complement traditional proteomics methods. This can bring researchers closer than ever before to elucidating the intricate inner workings and cross talk that spans multitude of proteins in disease mechanisms.

Current knowledge about biomarkers of acute kidney injury in liver cirrhosis

Acute kidney injury (AKI) is common in advanced cirrhosis. Prerenal azotemia, hepatorenal syndrome, and acute tubular necrosis are the main causes of AKI in patients with cirrhosis. Evaluation of renal function and differentiation between functional and structural kidney injury are important issues in the management of cirrhosis. However, AKI in cirrhosis exists as a complex clinical spectrum rather than concrete clinical entity. Based on current evidence, changes in serum creatinine (Cr) levels remain the most appropriate standard for defining AKI in cirrhosis. However, serum Cr has a limited role in assessing renal function in this population. This review examines previous studies that investigated the ability of recent biomarkers for AKI in cirrhosis from the perspective of earlier and accurate diagnosis, classification of AKI phenotype, and prediction of clinical outcomes. Serum cystatin C and urine neutrophil gelatinase-associated lipocalin have been extensively studied in cirrhosis, and have facilitated improved diagnosis and prognosis prediction in patients with AKI. In addition, urine N-acetyl-β-D-glucosaminidase, interleukin 18, and kidney injury molecule 1 are other promising biomarkers for advanced cirrhosis. However, the clinical significance of these markers remains unclear because there are no cut-off values defining the normal range and differentiating phenotypes of AKI. In addition, AKI has been defined in terms of serum Cr, and renal biopsy-the gold standard-has not been carried out in most studies. Further discovery of innovate biomarkers and incorporation of various markers could improve the diagnosis and prognosis prediction of AKI, and will translate into meaningful improvements in patient outcomes.

The Molecular Basis of Predicting Atherosclerotic Cardiovascular Disease Risk

Atherosclerotic cardiovascular disease (ASCVD) proceeds through a series of stages: initiation, progression (or regression), and complications. By integrating known biology regarding molecular signatures of each stage with recent advances in high-dimensional molecular data acquisition platforms (to assay the genome, epigenome, transcriptome, proteome, metabolome, and gut microbiome), snapshots of each phase of atherosclerotic cardiovascular disease development can be captured. In this review, we will summarize emerging approaches for assessment of atherosclerotic cardiovascular disease risk in humans using peripheral blood molecular signatures and molecular imaging approaches. We will then discuss the potential (and challenges) for these snapshots to be integrated into a personalized movie providing dynamic readouts of an individual's atherosclerotic cardiovascular disease risk status throughout the life course.

Integrated plasma proteomics and lung transcriptomics reveal novel biomarkers in idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease with a significant unmet medical need. Development of transformational therapies for IPF is challenging in part to due to lack of robust predictive biomarkers of prognosis and treatment response. Importantly, circulating biomarkers of IPF are limited and none are in clinical use.

METHODS

We previously reported dysregulated pathways and new disease biomarkers in advanced IPF through RNA sequencing of lung tissues from a cohort of transplant-stage IPF patients (n = 36) in comparison to normal healthy donors (n = 19) and patients with acute lung injury (n = 11). Here we performed proteomic profiling of matching plasma samples from these cohorts through the Somascan-1300 SomaLogics platform.

RESULTS

Comparative analyses of lung transcriptomic and plasma proteomic signatures identified a set of 34 differentially expressed analytes (fold change (FC) ≥  ± 1.5, false discovery ratio (FDR) ≤ 0.1) in IPF samples compared to healthy controls. IPF samples showed strong enrichment of chemotaxis, tumor infiltration and mast cell migration pathways and downregulated extracellular matrix (ECM) degradation. Mucosal (CCL25 and CCL28) and Th2 (CCL17 and CCL22) chemokines were markedly upregulated in IPF and highly correlated within the subjects. The mast cell maturation chemokine, CXCL12, was also upregulated in IPF plasma (fold change 1.92, FDR 0.006) and significantly correlated (Pearson r = - 0.38, p = 0.022) to lung function (%predicted FVC), with a concomitant increase in the mast cell Tryptase, TPSB2. Markers of collagen III and VI degradation (C3M and C6M) were significantly downregulated (C3M p < 0.001 and C6M p < 0.0001 IPF vs control) and correlated, Pearson r = 0.77) in advanced IPF consistent with altered ECM homeostasis.

CONCLUSIONS

Our study identifies a panel of tissue and circulating biomarkers with clinical utility in IPF that can be validated in future studies across larger cohorts.

Therapeutic Aptamers: Evolving to Find their Clinical Niche

BACKGROUND

The discovery that short oligonucleotides, termed aptamers, can fold into three-dimensional structures that allow them to selectively bind and inhibit the activity of pathogenic proteins is now over 25 years old. The invention of the SELEX methodology heralded in an era in which such nucleic acid-based ligands could be generated against a wide variety of therapeutic targets.

RESULTS

A large number of aptamers have now been identified by combinatorial chemistry methods in the laboratory and moreover, an increasing number have been discovered in nature. The affinities and activities of such aptamers have often been compared to that of antibodies, yet only a few of these agents have made it into clinical studies compared to a large and increasing number of therapeutic antibodies. One therapeutic aptamer targeting VEGF has made it to market, while 3 others have advanced as far as phase III clinical trials.

CONCLUSION

In this manuscript, we hope the reader appreciates that the success of aptamers becoming a class of drugs is less about nucleic acid biochemistry and more about target validation and overall drug chemistry.

Placenta accreta spectrum: biomarker discovery using plasma proteomics

BACKGROUND

Many cases of placenta accreta spectrum are not diagnosed antenatally, despite identified risk factors and improved imaging methods. Identification of plasma protein biomarkers could further improve the antenatal diagnosis of placenta accreta spectrum .

OBJECTIVE

The purpose of this study was to determine if women with placenta accreta spectrum have a distinct plasma protein profile compared with control subjects.

STUDY DESIGN

We obtained plasma samples before delivery from 16 participants with placenta accreta spectrum and 10 control subjects with similar gestational ages (35.1 vs 35.5 weeks gestation, respectively). We analyzed plasma samples with an aptamer-based proteomics platform for alterations in 1305 unique proteins. Heat maps of the most differentially expressed proteins (T test, P<.01) were generated with matrix visualization and analysis software. Principal component analysis was performed with the use of all 1305 proteins and the top 21 dysregulated proteins. We then confirmed dysregulated proteins using enzyme-linked immunosorbent assay and report significant differences between placenta accreta spectrum and control cases (Wilcoxon-rank sum test, P<.05).

RESULTS

Many of the top 50 proteins that significantly dysregulated in participants with placenta accreta spectrum were inflammatory cytokines, factors that regulate vascular remodeling, and extracellular matrix proteins that regulate invasion. Placenta accreta spectrum, with the use of the top 21 proteins, distinctly separated the placenta accreta spectrum cases from control cases (P<.01). Using enzyme-linked immunosorbent assay, we confirmed 4 proteins that were dysregulated in placenta accreta spectrum compared with control cases: median antithrombin III concentrations (240.4 vs 150.3 mg/mL; P=.002), median plasminogen activator inhibitor 1 concentrations (4.1 vs 7.1 ng/mL; P<.001), soluble Tie2 (13.5 vs 10.4 ng/mL; P=.02), soluble vascular endothelial growth factor receptor 2 (9.0 vs 5.9 ng/mL; P=.003).

CONCLUSION

Participants with placenta accreta spectrum had a unique and distinct plasma protein signature.

Advances in Oligonucleotide Aptamers for NSCLC Targeting

Non-small-cell lung cancer (NSCLC) is the most common type of lung cancer worldwide, with the highest incidence in developed countries. NSCLC patients often face resistance to currently available therapies, accounting for frequent relapses and poor prognosis. Indeed, despite great recent advancements in the field of NSCLC diagnosis and multimodal therapy, most patients are diagnosed at advanced metastatic stage, with a very low overall survival. Thus, the identification of new effective diagnostic and therapeutic options for NSCLC patients is a crucial challenge in oncology. A promising class of targeting molecules is represented by nucleic-acid aptamers, short single-stranded oligonucleotides that upon folding in particular three dimensional (3D) structures, serve as high affinity ligands towards disease-associated proteins. They are produced in vitro by SELEX (systematic evolution of ligands by exponential enrichment), a combinatorial chemistry procedure, representing an important tool for novel targetable biomarker discovery of both diagnostic and therapeutic interest. Aptamer-based approaches are promising options for NSCLC early diagnosis and targeted therapy and may overcome the key obstacles of currently used therapeutic modalities, such as the high toxicity and patients’ resistance. In this review, we highlight the most important applications of SELEX technology and aptamers for NSCLC handling.

Evaluation of a novel blood microsampling device for clinical trial sample collection and protein biomarker analysis

Aim: Evaluation of a novel microsampling device for its use in clinical sample collection and biomarker analysis. Methodology: Matching samples were collected from 16 healthy donors (ten females, six males; age 42 ± 20) via K2EDTA touch activated phlebotomy (TAP) device and phlebotomy. The protein profile differences between sampling groups was evaluated using aptamer-based proteomic assay SomaScan and selected ELISA. Conclusion: Somascan signal concordance between phlebotomy- and TAP-generated samples was studied and comparability of protein abundances between these blood sample collection methods was demonstrated. Statistically significant correlation in selected ELISA assays also confirmed the TAP device applicability to the quantitative analysis of protein biomarkers in clinical trials.

Big Data in occupational medicine: the convergence of -omics sciences, participatory research and e-health

BACKGROUND

New occupational hazards and risks are emerging in our progressively globalized society, in which ageing, migration, wild urbanization and rapid economic growth have led to unprecedented biological, chemical and physical exposures, linked to  novel technologies, products and duty cycles. A focus shift from worker health to worker/citizen and community health is crucial. One of the major revolutions of the last decades is the computerization and digitization of the work process, the so-called "work 4.0", and of the workplace.

OBJECTIVES

To explore the roles and implications of Big Data in the new occupational medicine settings.

METHODS

Comprehensive literature search.

RESULTS

Big Data are characterized by volume, variety, veracity, velocity, and value. They come both from wet-lab techniques ("molecular Big Data") and computational infrastructures, including databases, sensors and smart devices ("computational Big Data" and "digital Big Data").

CONCLUSIONS

In the light of novel hazards and thanks to new analytical approaches, molecular and digital underpinnings become extremely important in occupational medicine. Computational and digital tools can enable us to uncover new relationships between exposures and work-related diseases; to monitor the public reaction to novel risk factors associated to occupational diseases; to identify exposure-related changes in disease natural history; and to evaluate preventive workplace practices and legislative measures adopted for workplace health and safety.

Cancer protein biomarker discovery based on nucleic acid aptamers

Identification of biomarkers is essential for diagnosis, targeted therapy and prognosis evaluation of diseases, especially cancers. Currently, the number of ideal clinical biomarkers is still limited partially because of lacking efficient methods in biomarker discovery. Nucleic acid aptamers are artificial single-stranded DNA or RNA sequences that can selectively bind to various targets with high specificity and affinity. Moreover, aptamers possess desirable advantages, including easy synthesis, convenient modification, relative chemical stability and low immunogenicity. Recently, different aptamer-based strategies have been developed to facilitate the discovery of biomarkers. Based on cell-SELEX technology, the selected aptamers can be used to identify cell-surface protein biomarkers of different cancer cells. SOMAscan can analyze thousands of proteins of different biological samples, which becomes a multiplexed protein biomarker discovery platform. Additionally, secreted protein biomarkers can be discovered by aptamers screened through secretome SELEX. In order to facilitate the identification of target proteins, several covalent cross-linking strategies have been developed, such as aptamer-based affinity labeling (ABAL), DNA-templated aptamer and protein-aptamer template (PAT). In this review, we mainly highlight the emerging nucleic acid aptamer-based biomarker discovery strategies and demonstrate their unique technological advantages in discovering cancer biomarkers. The challenges and perspectives of aptamer-based methods are also discussed.

Plasma proteomics identifies a 'chemokine storm' in idiopathic multicentric Castleman disease

Human Herpesvirus-8 (HHV-8)-negative/idiopathic multicentric Castleman disease (iMCD) is a poorly understood disease involving polyclonal lymphoproliferation with dysmorphic germinal centers, constitutional symptoms, and multi-organ failure. Patients can experience thrombocytopenia, anasarca, reticulin fibrosis, renal dysfunction, organomegaly, and normal immunoglobulin levels, - iMCD-TAFRO. Others experience thrombocytosis, milder effusions, and hypergammaglobulinemia, -iMCD-Not Otherwise Specified (iMCD-NOS). Though the etiology is unknown in both subtypes, iMCD symptoms and disease progression are believed to be driven by a cytokine storm, often including interleukin-6 (IL-6). However, approximately two-thirds of patients do not respond to anti-IL-6 therapy; alternative drivers and signaling pathways are not known for anti-IL-6 nonresponders. To identify potential mediators of iMCD pathogenesis, we quantified 1129 proteins in 13 plasma samples from six iMCD patients during flare and remission. The acute phase reactant NPS-PLA2 was the only significantly increased protein (P = .017); chemokines and complement were significantly enriched pathways. Chemokines represented the greatest proportion of upregulated cytokines, suggesting that iMCD involves a chemokine storm. The chemokine CXCL13, which is essential in homing B cells to germinal centers, was the most upregulated cytokine across all patients (log2 fold-change = 3.22). Expression of CXCL13 was also significantly increased in iMCD lymph node germinal centers compared to controls in a stromal meshwork pattern. We observed distinct proteomic profiles between the two iMCD-TAFRO patients, who both failed anti-IL-6-therapy, and the four iMCD-NOS patients, in whom all three treated with anti-IL-6-therapy responded, suggesting that differing mechanisms may exist. This study reveals proteomic differences between flare and remission and the potential to molecularly define iMCD subgroups.

Human biomarker interpretation: the importance of intra-class correlation coefficients (ICC) and their calculations based on mixed models, ANOVA, and variance estimates

Human biomonitoring is the foundation of environmental toxicology, community public health evaluation, preclinical health effects assessments, pharmacological drug development and testing, and medical diagnostics. Within this framework, the intra-class correlation coefficient (ICC) serves as an important tool for gaining insight into human variability and responses and for developing risk-based assessments in the face of sparse or highly complex measurement data. The analytical procedures that provide data for clinical and public health efforts are continually evolving to expand our knowledge base of the many thousands of environmental and biomarker chemicals that define human systems biology. These chemicals range from the smallest molecules from energy metabolism (i.e., the metabolome), through larger molecules including enzymes, proteins, RNA, DNA, and adducts. In additiona, the human body contains exogenous environmental chemicals and contributions from the microbiome from gastrointestinal, pulmonary, urogenital, naso-pharyngeal, and skin sources. This complex mixture of biomarker chemicals from environmental, human, and microbiotic sources comprise the human exposome and generally accessed through sampling of blood, breath, and urine. One of the most difficult problems in biomarker assessment is assigning probative value to any given set of measurements as there are generally insufficient data to distinguish among sources of chemicals such as environmental, microbiotic, or human metabolism and also deciding which measurements are remarkable from those that are within normal human variability. The implementation of longitudinal (repeat) measurement strategies has provided new statistical approaches for interpreting such complexities, and use of descriptive statistics based upon intra-class correlation coefficients (ICC) has become a powerful tool in these efforts. This review has two parts; the first focuses on the history of repeat measures of human biomarkers starting with occupational toxicology of the early 1950s through modern applications in interpretation of the human exposome and metabolic adverse outcome pathways (AOPs). The second part reviews different methods for calculating the ICC and explores the strategies and applications in light of different data structures.

Divergent roles for Clusterin in Lung Injury and Repair

Lung fibrosis is an unabated wound healing response characterized by the loss and aberrant function of lung epithelial cells. Herein, we report that extracellular Clusterin promoted epithelial cell apoptosis whereas intracellular Clusterin maintained epithelium viability during lung repair. Unlike normal and COPD lungs, IPF lungs were characterized by significantly increased extracellular Clusterin whereas the inverse was evident for intracellular Clusterin. In vitro and in vivo studies demonstrated that extracellular Clusterin promoted epithelial cell apoptosis while intercellular Clusterin modulated the expression of the DNA repair proteins, MSH2, MSH6, OGG1 and BRCA1. The fibrotic response in Clusterin deficient (CLU-/-) mice persisted after bleomycin and it was associated with increased DNA damage, reduced DNA repair responses, and elevated cellular senescence. Remarkably, this pattern mirrored that observed in IPF lung tissues. Together, our results show that cellular localization of Clusterin leads to divergent effects on epithelial cell regeneration and lung repair during fibrosis.

Systems-level effects of ectopic galectin-7 reconstitution in cervical cancer and its microenvironment

Background

Galectin-7 (Gal-7) is negatively regulated in cervical cancer, and appears to be a link between the apoptotic response triggered by cancer and the anti-tumoral activity of the immune system. Our understanding of how cervical cancer cells and their molecular networks adapt in response to the expression of Gal-7 remains limited.

Methods

Meta-analysis of Gal-7 expression was conducted in three cervical cancer cohort studies and TCGA. In silico prediction and bisulfite sequencing were performed to inquire epigenetic alterations. To study the effect of Gal-7 on cervical cancer, we ectopically re-expressed it in the HeLa and SiHa cervical cancer cell lines, and analyzed their transcriptome and SILAC-based proteome. We also examined the tumor and microenvironment host cell transcriptomes after xenotransplantation into immunocompromised mice. Differences between samples were assessed with the Kruskall-Wallis, Dunn’s Multiple Comparison and T tests. Kaplan–Meier and log-rank tests were used to determine overall survival.

Results

Gal-7 was constantly downregulated in our meta-analysis (p < 0.0001). Tumors with combined high Gal-7 and low galectin-1 expression (p = 0.0001) presented significantly better prognoses (p = 0.005). In silico and bisulfite sequencing assays showed de novo methylation in the Gal-7 promoter and first intron. Cells re-expressing Gal-7 showed a high apoptosis ratio (p < 0.05) and their xenografts displayed strong growth retardation (p < 0.001). Multiple gene modules and transcriptional regulators were modulated in response to Gal-7 reconstitution, both in cervical cancer cells and their microenvironments (FDR < 0.05 %). Most of these genes and modules were associated with tissue morphogenesis, metabolism, transport, chemokine activity, and immune response. These functional modules could exert the same effects in vitro and in vivo, even despite different compositions between HeLa and SiHa samples.

Conclusions

Gal-7 re-expression affects the regulation of molecular networks in cervical cancer that are involved in diverse cancer hallmarks, such as metabolism, growth control, invasion and evasion of apoptosis. The effect of Gal-7 extends to the microenvironment, where networks involved in its configuration and in immune surveillance are particularly affected.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2700-8) contains supplementary material, which is available to authorized users.

From the RNA world to the clinic

The study of RNA has continually emphasized the structural and functional versatility of RNA molecules. This versatility has inspired translational and clinical researchers to explore the utility of RNA-based therapeutic agents for a wide variety of medical applications. Several RNA therapeutics, with diverse modes of action, are being evaluated in large late-stage clinical trials, and many more are in early clinical development. Hundreds of patients are enrolled in large trials testing messenger RNAs to combat cancer, small interfering RNAs to treat renal and hepatic disorders, and aptamers to combat ocular and cardiovascular disease. Results from these studies are generating considerable interest among the biomedical community and the public and will be important for the future development of this emerging class of therapeutic agents.

Identification of ssDNA aptamers specific to clinical isolates of Streptococcus mutans strains with different cariogenicity

Streptococcus mutans, a Gram-positive facultative anaerobic bacterium, is considered to be a major etiological factor for dental caries. In this study, plaques from dental enamel surfaces of caries-active and caries-free individuals were obtained and cultivated for S. mutans isolation. Morphology examination, biochemical characterization, and polymerase chain reaction were performed to identify S. mutans The cariogenicity of S. mutans strains isolated from clinical specimens was evaluated by testing the acidogenicity, aciduricity, extracellular polysaccharide production, and adhesion ability of the bacteria. Finally, subtractive SELEX (systematic evolution of ligands by exponential enrichment) technology targeting whole intact cells was used to screen for ssDNA aptamers specific to the strains with high cariogenicity. After nine rounds of subtractive SELEX, sufficient pool enrichment was achieved as shown by radioactive isotope analysis. The enriched pool was cloned and sequenced randomly, followed by MEME online and RNA structure software analysis of the sequences. Results from the flow cytometry indicated that aptamers H1, H16, H4, L1, L10, and H19 could discriminate highly cariogenic S. mutans strains from poorly cariogenic strains. Among these, Aptamer H19 had the strongest binding capacity with cariogenic S. mutans strains with a dissociation constant of 69.45 ± 38.53 nM. In conclusion, ssDNA aptamers specific to highly cariogenic clinical S. mutans strains were successfully obtained. These ssDNA aptamers might be used for the early diagnosis and treatment of dental caries.

The relationship of circulating proteins in early pregnancy with preterm birth

BACKGROUND

Preterm birth (PTB) (< 37 completed weeks' gestation) is a pathological outcome of pregnancy and a major global health problem. Babies born preterm have an elevated risk for long-term adverse medical and neurodevelopmental sequelae. Substantial evidence implicates intrauterine infection and/or inflammation in PTB. However, these are often relatively late findings in the process, when PTB is inevitable. Identification of earlier markers of PTB may make successful intervention possible. Although select proteins, notably those related to the inflammatory pathways, have been associated with PTB, there has been a lack of research into the role of other protein pathways in the development of PTB. The purpose of this study was to investigate, using a previously described biomarker discovery approach, a subset of circulating proteins and their association with PTB focusing on samples from early pregnancy.

OBJECTIVES

The objectives of the study were as follows: (1) to perform a large-scale biomarker discovery, utilizing an innovative platform to identify proteins associated with preterm birth in plasma taken between 10 and 15 weeks' gestation and, (2) to determine which protein pathways are most strongly associated with preterm birth. To address these aims, we measured 1129 proteins in a plasma sample from early pregnancy using a multiplexed aptamer-based proteomic technology developed in Colorado by SomaLogic.

STUDY DESIGN

Using a nested case-control approach, we measured proteins at a single time point in early pregnancy in 41 women who subsequently delivered preterm and 88 women who had term uncomplicated deliveries. We measured 1129 proteins using a multiplexed aptamer-based proteomic technology developed by SomaLogic. Logistic regressions and random forests were used to compare protein levels.

RESULTS

The complement factors B and H and the coagulation factors IX and IX ab were the highest-ranking proteins distinguishing cases of preterm birth from term controls. The top 3 pathways associated with preterm birth were the complement cascade, the immune system, and the clotting cascade.

CONCLUSION

Using a discovery approach, these data provide further confirmation that there is an association of immune- and coagulation-related events in early pregnancy with preterm birth. Thus, plasma protein profiles at 10-15 weeks of gestation are related to the development of preterm birth later in pregnancy.

Cancer biomarker discovery using DNA aptamers

Biomarkers are signature molecules able to indicate specific physiological states of cells. Identification of reliable biomarkers is essential for early diagnosis and adaptive treatment of diseases, especially cancer. Aptamers are single-stranded oligonucleotides generated by an in vitro screening method called Systematic Evolution of Ligands by Exponential Enrichment (SELEX). They can recognize their cognate targets with selectivity and affinity comparable to protein antibodies. In addition, aptamers have superiorities including easy synthesis, high chemical stability, convenient modification and flexible design. As such, these DNA molecules show great promise as powerful molecular probes for biomarker discovery and biomarker-based clinical applications. Using complex samples as targets, a panel of aptamers can be systematically generated for comprehensive recognition of disease-specific proteins, which can potentially serve as biomarkers. This review describes the current methods for biomarker discovery using aptamers.

Use of aptamers in immunoassays

Aptamers, short single-chain DNA or RNA oligonucleotides, react specifically with small molecules, as well as with proteins. Unlike antibodies, they may be obtained relatively easily. Aptamers are now widely employed in immunological studies and could replace antibodies in immunoassays. In this short review, methods for immobilizing aptamers on various insoluble materials (so-called apta-sorbents) are described. Recent findings on their use in the detection and isolation of immunoglobulins and their application in various immunoassays are also discussed.

Synthetic genetic polymers: advances and applications

Advances and applications of synthetic genetic polymers (xeno-nucleic acids) are reviewed in this article. The types of synthetic genetic polymers are summarized. The basic properties of them are elaborated and their technical applications are presented. Challenges and prospects of synthetic genetic polymers are discussed.

Non-helical DNA Triplex Forms a Unique Aptamer Scaffold for High Affinity Recognition of Nerve Growth Factor

Discerning the structural building blocks of macromolecules is essential for understanding their folding and function. For a new generation of modified nucleic acid ligands (called slow off-rate modified aptamers or SOMAmers), we previously observed essential functions of hydrophobic aromatic side chains in the context of well-known nucleic acid motifs. Here we report a 2.45-Å resolution crystal structure of a SOMAmer complexed with nerve growth factor that lacks any known nucleic acid motifs, instead adopting a configuration akin to a triangular prism. The SOMAmer utilizes extensive hydrophobic stacking interactions, non-canonical base pairing and irregular purine glycosidic bond angles to adopt a completely non-helical, compact S-shaped structure. Aromatic side chains contribute to folding by creating an unprecedented intercalating zipper-like motif and a prominent hydrophobic core. The structure provides compelling rationale for potent inhibitory activity of the SOMAmer and adds entirely novel motifs to the repertoire of structural elements uniquely available to SOMAmers.

Proteomics in pharmaceutical research and development

In the 20 years since its inception, the evolution of proteomics in pharmaceutical industry has mirrored the developments within academia and indeed other industries. From initial enthusiasm and subsequent disappointment in global protein expression profiling, pharma research saw the biggest impact when relating to more focused approaches, such as those exploring the interaction between proteins and drugs. Nowadays, proteomics technologies have been integrated in many areas of pharmaceutical R&D, ranging from the analysis of therapeutic proteins to the monitoring of clinical trials. Here, we review the development of proteomics in the drug discovery process, placing it in a historical context as well as reviewing the current status in light of the contributions to this special issue, which reflect some of the diverse demands of the drug and biomarker pipelines.

Pathway and network approaches for identification of cancer signature markers from omics data

The advancement of high throughput omic technologies during the past few years has made it possible to perform many complex assays in a much shorter time than the traditional approaches. The rapid accumulation and wide availability of omic data generated by these technologies offer great opportunities to unravel disease mechanisms, but also presents significant challenges to extract knowledge from such massive data and to evaluate the findings. To address these challenges, a number of pathway and network based approaches have been introduced. This review article evaluates these methods and discusses their application in cancer biomarker discovery using hepatocellular carcinoma (HCC) as an example.

Antibody-based proteomics and biomarker research - current status and limitations

Antibody-based proteomics play a very important role in biomarker discovery and validation, facilitating the high-throughput evaluation of candidate markers. Most proteomics-driven discovery is nowadays based on the use of MS. MS has many advantages, including its suitability for hypothesis-free biomarker discovery, since information on protein content of a sample is not required prior to analysis. However, MS presents one main caveat which is the limited sensitivity in complex samples, especially for body fluids, where protein expression covers a huge dynamic range. Antibody-based technologies remain the main solution to address this challenge since they reach higher sensitivity. In this article, we review the benefits and limitations of antibody-based proteomics in preclinical and clinical biomarker research for discovery and validation in body fluids and tissue. The combination of antibodies and MS, utilizing the best of both worlds, opens new avenues in biomarker research.

Nucleic Acid Ligands With Protein-like Side Chains: Modified Aptamers and Their Use as Diagnostic and Therapeutic Agents

Limited chemical diversity of nucleic acid libraries has long been suspected to be a major constraining factor in the overall success of SELEX (Systematic Evolution of Ligands by EXponential enrichment). Despite this constraint, SELEX has enjoyed considerable success over the past quarter of a century as a result of the enormous size of starting libraries and conformational richness of nucleic acids. With judicious introduction of functional groups absent in natural nucleic acids, the “diversity gap” between nucleic acid–based ligands and protein-based ligands can be substantially bridged, to generate a new class of ligands that represent the best of both worlds. We have explored the effect of various functional groups at the 5-position of uracil and found that hydrophobic aromatic side chains have the most profound influence on the success rate of SELEX and allow the identification of ligands with very low dissociation rate constants (named Slow Off-rate Modified Aptamers or SOMAmers). Such modified nucleotides create unique intramolecular motifs and make direct contacts with proteins. Importantly, SOMAmers engage their protein targets with surfaces that have significantly more hydrophobic character compared with conventional aptamers, thereby increasing the range of epitopes that are available for binding. These improvements have enabled us to build a collection of SOMAmers to over 3,000 human proteins encompassing major families such as growth factors, cytokines, enzymes, hormones, and receptors, with additional SOMAmers aimed at pathogen and rodent proteins. Such a large and growing collection of exquisite affinity reagents expands the scope of possible applications in diagnostics and therapeutics.

Validation of a blood protein signature for non-small cell lung cancer

Background

CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.

Results

Blood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n = 363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n = 138 in the first validation and n = 135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation.

Conclusions

Selecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules.

The Use of Antibodies in Small-Molecule Drug Discovery

Antibodies are powerful research tools that can be used in many areas of biology to probe, measure, and perturb various biological structures. Successful drug discovery is dependent on the correct identification of a target implicated in disease, coupled with the successful selection, optimization, and development of a candidate drug. Because of their specific binding characteristics, with regard to specificity, affinity, and avidity, coupled with their amenability to protein engineering, antibodies have become a key tool in drug discovery, enabling the quantification, localization, and modulation of proteins of interest. This review summarizes the application of antibodies and other protein affinity reagents as specific research tools within the drug discovery process.

Oncogenic protein interfaces: small molecules, big challenges

Historically, targeting protein-protein interactions with small molecules was not thought possible because the corresponding interfaces were considered mostly flat and featureless and therefore 'undruggable'. Instead, such interactions were targeted with larger molecules, such as peptides and antibodies. However, the past decade has seen encouraging breakthroughs through the refinement of existing techniques and the development of new ones, together with the identification and exploitation of unexpected aspects of protein-protein interaction surfaces. In this Review, we describe some of the latest techniques to discover modulators of protein-protein interactions and how current drug discovery approaches have been adapted to successfully target these interfaces.

In vitro selection using modified or unnatural nucleotides

Incorporation of modified nucleotides into in vitro RNA or DNA selections offers many potential advantages, such as the increased stability of selected nucleic acids against nuclease degradation, improved affinities, expanded chemical functionality, and increased library diversity. This unit provides useful information and protocols for in vitro selection using modified nucleotides. It includes a discussion of when to use modified nucleotides; protocols for evaluating and optimizing transcription reactions, as well as confirming the incorporation of the modified nucleotides; protocols for evaluating modified nucleotide transcripts as template in reverse transcription reactions; protocols for the evaluation of the fidelity of modified nucleotides in the replication and the regeneration of the pool; and a protocol to compare modified nucleotide pools and selection conditions.

Aptamer-based proteomic signature of intensive phase treatment response in pulmonary tuberculosis

BACKGROUND

New drug regimens of greater efficacy and shorter duration are needed for tuberculosis (TB) treatment. The identification of accurate, quantitative, non-culture based markers of treatment response would improve the efficiency of Phase 2 TB drug testing.

METHODS

In an unbiased biomarker discovery approach, we applied a highly multiplexed, aptamer-based, proteomic technology to analyze serum samples collected at baseline and after 8 weeks of treatment from 39 patients with pulmonary TB from Kampala, Uganda enrolled in a Centers for Disease Control and Prevention (CDC) TB Trials Consortium Phase 2B treatment trial.

RESULTS

We identified protein expression differences associated with 8-week culture status, including Coagulation Factor V, SAA, XPNPEP1, PSME1, IL-11 Rα, HSP70, Galectin-8, α2-Antiplasmin, ECM1, YES, IGFBP-1, CATZ, BGN, LYNB, and IL-7. Markers noted to have differential changes between responders and slow-responders included nectin-like protein 2, EphA1 (Ephrin type-A receptor 1), gp130, CNDP1, TGF-b RIII, MRC2, ADAM9, and CDON. A logistic regression model combining markers associated with 8-week culture status revealed an ROC curve with AUC = 0.96, sensitivity = 0.95 and specificity = 0.90. Additional markers showed differential changes between responders and slow-responders (nectin-like protein), or correlated with time-to-culture-conversion (KLRK1).

CONCLUSIONS

Serum proteins involved in the coagulation cascade, neutrophil activity, immunity, inflammation, and tissue remodeling were found to be associated with TB treatment response. A quantitative, non-culture based, five-marker signature predictive of 8-week culture status was identified in this pilot study.

Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013

To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

Generation of monoclonal antibody MS17-57 targeting secreted alkaline phosphatase ectopically expressed on the surface of gastrointestinal cancer cells

Background

Therapeutic antibody development is one of the fastest growing areas of the pharmaceutical industry. Generating high-quality monoclonal antibodies against a given therapeutic target is crucial for successful drug development. However, due to immune tolerance, making it difficult to generate antibodies using conventional approaches.

Methodology/Findings

Mixed four human gastric cancer (GC) cell lines were used as the immunogen in A/J mice; sixteen highly positive hybridoma colonies were selected via fluorescence-activated cell sorting-high throughput screening (FACS-HTS) using a total of 20,000 colonies in sixty-seven 96-well plates against live cells (mixed human GC cells versus human PBMC controls). MS17-57 and control commercial Alkaline Phosphatase (ALP) mAbs were used to confirm the target antigens (Ags), which were identified as ALPs expressed on the GC cell surface through a combination of western blot, immunoprecipitation and mass spectrometry (MS).

MS identified the Ags recognized by MS17-57 to be two variants of a secreted ALP, PALP and IALP (Placental and intestinal ALP). These proteins belong to a hydrolase enzyme family responsible for removing phosphate groups from many types of molecules. Immunofluorescence staining using MS17-57 demonstrated higher staining of gastrointestinal (GI) cancer tissues compared to normal GI tissues (P<0.03), and confirmed binding of MS17-57 to be restricted to a functional epitope expressed on the cancer cell surface. Proliferation assays using the PALP/IALP-expressing GC cell lines demonstrated that MS17-57 inhibited cell growth by 32±8%. Transwell cell migration assays documented that MS17-57 can inhibit PALP/IALP-expressing GI cancer cell migration by 25±5%. MS17-57 mAb inhibited tumor growth in nude mice.

Conclusions

Our findings indicate that PALP and IALP can be ectopically expressed on extracellular matrix of GI cancers, and that MS17-57 directed against PALP/IALP can inhibit GI cancer cells growth and migration invitro and invivo. This investigation provides an example of identification of cancer biomarkers representing promising therapeutic targets using mAb generated through a novel HTS technology.

Proteomic analysis of venous thromboembolism: an update

Venous thromboembolism is a complex, multifactorial disorder, the pathogenesis of which typically involves a variety of inherited or acquired factors. The multifactorial etiology of this disease and the partial correlation between genotype and prothrombotic phenotype limit greatly the value of genetic analysis in assessing thrombotic risk. The integration of several new 'omics' techniques enables a multifaceted and holistic approach to the study of venous thrombotic processes and pave the way to the search and identification of novel blood biomarkers and/or effectors of thrombus formation that can also be the possible future target of new anticoagulant and thrombolytic therapies for more personalized medicine. This review provides a comprehensive overview of the latest candidate proteomic biomarkers of venous thrombosis and of the proteomics studies relevant to its pathophysiology, some of which seem to confirm the existence of a common physiopathological basis for venous thromboembolism and atherothrombosis.

Aptamers: multifunctional molecules for biomedical research

Aptamers are single-stranded oligonucleotides that fold into well-defined three-dimensional shapes, allowing them to bind their targets with high affinity and specificity. They can be generated through an in vitro process called "Systemic Evolution of Ligands by Exponential Enrichment" and applied for specific detection, inhibition, and characterization of various targets like small organic and inorganic molecules, proteins, and whole cells. Aptamers have also been called chemical antibodies because of their synthetic origin and their similar modes of action to antibodies. They exhibit significant advantages over antibodies in terms of their small size, synthetic accessibility, and ability to be chemically modified and thus endowed with new properties. The first generation of aptamer drug "Macugen" was available for public use within 25 years of the discovery of aptamers. With others in the pipeline for clinical trials, this emerging field of medical biotechnology is raising significant interest. However, aptamers pose different problems for their development than for antibodies that need to be addressed to achieve practical applications. It is likely that current developments in aptamer engineering will be the basis for the evolution of improved future bioanalytical and biomedical applications. The present review discusses the development of aptamers for therapeutics, drug delivery, target validation and imaging, and reviews some of the challenges to fully realizing the promise of aptamers in biomedical applications.