Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries

Antibody array-based proteome approach reveals proteins involved in grape seed development

Grape (Vitis vinifera) is one of the most widely cultivated fruits globally, primarily used for processing and fresh consumption. Seedless grapes are favored by consumers for their convenience, making the study of seedlessness a subject of great interest to scientists. To identify regulators involved in this process in grape, a monoclonal antibody (mAb)-array-based proteomics approach, which contains 21,120 mAbs, was employed for screening proteins/antigens differentially accumulated in grape during development. Differences in antigen signals were detected between seeded and seedless grapes revealing the differential accumulation of 2,587 proteins. After immunoblotting validation, 71 antigens were further immunoprecipitated and identified by mass spectrometry (MS). An in planta protein-protein interaction (PPI) network of those differentially accumulated proteins was established using mAb antibody by immunoprecipitation (IP)-MS, which reveals the alteration of pathways related to carbon metabolism and glycolysis. To validate our result, a seedless-related protein, DUF642 domain-containing protein (VvDUF642), which is functionally uncharacterized in grapes, was ectopically overexpressed in tomato (Solanum lycopersicum "MicroTom") and led to a reduction in seed production. PPI network indicated that VvDUF642 interacts with pectin acetylesterase (VvPAE) in grapes, which was validated by BiFC and Co-IP. As anticipated, overexpression of VvPAE substantially reduced seed production in tomato. Moreover, S. lycopersicum colourless non-ripening expression was altered in VvDUF642- and VvPAE-overexpressing plants. Taken together, we provided a high-throughput method for the identification of proteins involved in the seed formation process. Among those, VvDUF642 and VvPAE are potential targets for breeding seedless grapes and other important fruits in the future.

Integrative Multianalytical Model Based on Novel Plasma Protein Biomarkers for Distinguishing Lung Adenocarcinoma and Benign Pulmonary Nodules

Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis (data are available via ProteomeXchange with identifier PXD046731), 12 differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of DEPs were validated in two independent validation cohorts. The results showed that the levels of three candidate proteins (PRDX2, PON1, and APOC3) were lower in the plasma of LUAD than in BPN. The three candidate proteins were combined with three promising computed tomography indicators (spiculation, vascular notch sign, and lobulation) and three traditional markers (CEA, CA125, and CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with an AUC of 0.904, a sensitivity of 81.44%, and a specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity, and accuracy of 0.868, 65.63%, 90.14%, and 82.52%, respectively. This model may be a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity.

Unveiling the potential of proteomic and genetic signatures for precision therapeutics in lung cancer management

Lung cancer's enduring global significance necessitates ongoing advancements in diagnostics and therapeutics. Recent spotlight on proteomic and genetic biomarker research offers a promising avenue for understanding lung cancer biology and guiding treatments. This review elucidates genetic and proteomic lung cancer biomarker progress and their treatment implications. Technological strides in mass spectrometry-based proteomics and next-generation sequencing enable pinpointing of genetic abnormalities and abnormal protein expressions, furnishing vital data for precise diagnosis, patient classification, and customized treatments. Biomarker-driven personalized medicine yields substantial treatment improvements, elevating survival rates and minimizing adverse effects. Integrating omics data (genomics, proteomics, etc.) enhances understanding of lung cancer's intricate biological milieu, identifying novel treatment targets and biomarkers, fostering precision medicine. Liquid biopsies, non-invasive tools for real-time treatment monitoring and early resistance detection, gain popularity, promising enhanced management and personalized therapy. Despite advancements, biomarker repeatability and validation challenges persist, necessitating interdisciplinary efforts and large-scale clinical trials. Integrating artificial intelligence and machine learning aids analyzing vast omics datasets and predicting treatment responses. Single-cell omics reveal cellular connections and intratumoral heterogeneity, valuable for combination treatments. Biomarkers enable accurate diagnosis, tailored medicines, and treatment response tracking, significantly impacting personalized lung cancer care. This approach spurs patient-centered trials, empowering active patient engagement. Lung cancer proteomic and genetic biomarkers illuminate disease biology and treatment prospects. Progressing towards individualized efficient therapies is imminent, alleviating lung cancer's burden through ongoing research, omics integration, and technological strides.

Large scale plasma proteome epitome profiling is an efficient tool for the discovery of cancer biomarkers

Current proteomic technologies focus on the quantification of protein levels, while little effort is dedicated to the development of systems approaches to simultaneously monitor proteome variability and abundance. Protein variants may display different immunogenic epitopes detectable by monoclonal antibodies. Epitope variability results from alternative splicing, posttranslational modifications, processing, degradation, and complex formation and possess dynamically changing availability of interacting surface structures frequently serve as reachable epitopes, and often carry different functions. Thus, it is highly likely, that the presence of some of the accessible epitopes correlate with function under physiological and pathological conditions. To enable the exploration of the impact of protein variation on the immunogenic epitome first; here, we present a robust and analytically validated protein epitome profiling (PEP) technology for characterizing immunogenic epitopes of the plasma. To this end we prepared mAb libraries directed against the normalized human plasma proteome as a complex natural immunogen. Resulting hybridoma supernatants were selected for mAb production and the corresponding hybridomas were cloned. Monoclonal antibodies react with single epitopes, thus profiling with the libraries is expected to profile many epitopes which we define by the mimotopes, as we present here. Screening blood plasma samples from control subjects (n = 558) and cancer patients (n = 598) for merely 69 native epitopes displayed by 20 abundant plasma proteins resulted in distinct cancer-specific epitope panels that showed high accuracy (AUC 0.826-0.966) and specificity for lung, breast, and colon cancer. Deeper profiling (≈290 epitopes of approximately 100 proteins) showed unexpected granularity of the epitope-level expression data and detected neutral and lung-cancer associated epitopes of individual proteins. Biomarker epitope panels selected from a pool of 21 epitopes of 12 proteins were validated in independent clinical cohorts. The results demonstrate the value of PEP as a rich and thus far unexplored source of protein biomarkers with diagnostic potential.

Advances in the application of proteomics in lung cancer

Although the incidence and mortality of lung cancer have decreased significantly in the past decade, it is still one of the leading causes of death, which greatly impairs people’s life and health. Proteomics is an emerging technology that involves the application of techniques for identifying and quantifying the overall proteins in cells, tissues and organisms, and can be combined with genomics, transcriptomics to form a multi-omics research model. By comparing the content of proteins between normal and tumor tissues, proteomics can be applied to different clinical aspects like diagnosis, treatment, and prognosis, especially the exploration of disease biomarkers and therapeutic targets. The applications of proteomics have promoted the research on lung cancer. To figure out potential applications of proteomics associated with lung cancer, we summarized the role of proteomics in studies about tumorigenesis, diagnosis, prognosis, treatment and resistance of lung cancer in this review, which will provide guidance for more rational application of proteomics and potential therapeutic strategies of lung cancer.

Application of an antibody microarray for serum protein profiling of coronary artery stenosis

Protein expression profiling in the serum is used to identify novel biomarkers and investigate the signaling pathways in various diseases. The aim of the present study was to evaluate serum biomarkers associated with coronary artery stenosis resulting from atherosclerosis. The study included 4 groups of subjects: group A and B with and without coronary lesions, respectively, were selected from a previously reported cohort study on coronary atherosclerosis, control group C comprised of asymptomatic subjects and group D was used for independent validation of the microarray data by ELISA. Labeled serum proteins were profiled by an Explorer antibody array, which included 656 specific antibodies in two replicates (FullMoon Biosystems, USA). Cadherin-P, interleukin-5, glutathione S-transferase Mu, and neuronal nitric oxide synthase were sex-independently increased in Group A compared with those in group B. The microarray data on cadherin-P were externally validated in an independent group D using ELISA. Fibroblast growth factor-1, FGF-2, collagen II, granulocyte-macrophage colony-stimulating factor, IL-1 alpha, angiopoietin-2, granulocyte colony-stimulating factor, lymphocyte cell-specific protein tyrosine kinase, and IkappaB kinase b were increase in men in group A compared with group B. Cyclin-dependent kinase 1, DNA fragmentation factor subunit alpha DFF45/ICAD, adenovirus type 2 E1A, calponin, ADP-ribosylation factor-6, muscle-specific actin, thyroid hormone receptor alpha, and alpha-methylacyl-CoA racemase were specifically increased in women in Group A compared with group B. Alterations in the levels of specific proteins may point to the signaling pathways contributing to coronary atherosclerosis, and these proteins will be useful biomarkers for the progression of cardiovascular diseases.

The 2022 Winners of the Lifetime Achievement and Emerging Leader in Chromatography Awards

Barry L. Karger and James P. Grinias are the winners of the 15th annual LCGC Lifetime Achievement and Emerging Leader in Chromatography Awards, respectively. Here, we review their achievements.

LRG1: an emerging player in disease pathogenesis

The secreted glycoprotein leucine-rich α-2 glycoprotein 1 (LRG1) was first described as a key player in pathogenic ocular neovascularization almost a decade ago. Since then, an increasing number of publications have reported the involvement of LRG1 in multiple human conditions including cancer, diabetes, cardiovascular disease, neurological disease, and inflammatory disorders. The purpose of this review is to provide, for the first time, a comprehensive overview of the LRG1 literature considering its role in health and disease. Although LRG1 is constitutively expressed by hepatocytes and neutrophils, Lrg1-/- mice show no overt phenotypic abnormality suggesting that LRG1 is essentially redundant in development and homeostasis. However, emerging data are challenging this view by suggesting a novel role for LRG1 in innate immunity and preservation of tissue integrity. While our understanding of beneficial LRG1 functions in physiology remains limited, a consistent body of evidence shows that, in response to various inflammatory stimuli, LRG1 expression is induced and directly contributes to disease pathogenesis. Its potential role as a biomarker for the diagnosis, prognosis and monitoring of multiple conditions is widely discussed while dissecting the mechanisms underlying LRG1 pathogenic functions. Emphasis is given to the role that LRG1 plays as a vasculopathic factor where it disrupts the cellular interactions normally required for the formation and maintenance of mature vessels, thereby indirectly contributing to the establishment of a highly hypoxic and immunosuppressive microenvironment. In addition, LRG1 has also been reported to affect other cell types (including epithelial, immune, mesenchymal and cancer cells) mostly by modulating the TGFβ signalling pathway in a context-dependent manner. Crucially, animal studies have shown that LRG1 inhibition, through gene deletion or a function-blocking antibody, is sufficient to attenuate disease progression. In view of this, and taking into consideration its role as an upstream modifier of TGFβ signalling, LRG1 is suggested as a potentially important therapeutic target. While further investigations are needed to fill gaps in our current understanding of LRG1 function, the studies reviewed here confirm LRG1 as a pleiotropic and pathogenic signalling molecule providing a strong rationale for its use in the clinic as a biomarker and therapeutic target.

Detection of leucine-rich alpha-2-glycoprotein 1-containing immunocomplexes in the plasma of lung cancer patients with epitope-specific mAbs

BACKGROUND

Lung cancer is the leading cause of cancer-related deaths worldwide. With the expectation of improved survival, tremendous efforts and resources have been invested in the discovery of specific biomarkers for early detection of the disease. Several investigators have reported the presence of cancer-associated autoantibodies in the plasma or serum of lung cancer patients. Previously, we used a monoclonal-antibody proteomics technology platform for the discovery of novel lung cancer-associated proteins.

OBJECTIVE

The identification of specific protein epitopes associated with various cancers is a promising method in biomarker discovery. Here, in a preliminary study, we aimed to detect autoantibody-leucine-rich alpha-2-glycoprotein 1 (LRG1) immunocomplexes using epitope-specific monoclonal antibodies (mAbs).

METHODS

We performed sandwich ELISA assays using the LRG1 epitope-specific capture mAbs, Bsi0352 and Bsi0392, and an IgG-specific polyclonal antibody coupled to a reporter system as the detection reagent. We tested the plasma of lung-cancer patients and apparently healthy controls.

RESULTS

Depending on the epitope specificity of the capture monoclonal mAb, we were either unable to distinguish the control from LC-groups or showed a higher level of LRG1 and IgG autoantibody containing immunocomplexes in the plasma of non-small cell lung cancer and small cell lung cancer subgroups of lung cancer patients than in the plasma of control subjects.

CONCLUSIONS

Our findings underline the importance of protein epitope-specific antibody targeted approaches in biomarker research, as this may increase the accuracy of previously described tests, which will need further validation in large clinical cohorts.

Proteomics of Non-human Primate Plasma after Partial-body Radiation with Minimal Bone Marrow Sparing

High-dose radiation exposure results in organ-specific sequelae that occurs in a time- and dose-dependent manner. The partial body irradiation with minimal bone marrow sparing model was developed to mimic intentional or accidental radiation exposures in humans where bone marrow sparing is likely and permits the concurrent analysis of coincident short- and long-term damage to organ systems. To help inform on the natural history of the radiation-induced injury of the partial body irradiation model, we quantitatively profiled the plasma proteome of non-human primates following 12 Gy partial body irradiation with 2.5% bone marrow sparing with 6 MV LINAC-derived photons at 0.80 Gy min over a time period of 3 wk. The plasma proteome was analyzed by liquid chromatography-tandem mass spectrometry. A number of trends were identified in the proteomic data including pronounced protein changes as well as protein changes that were consistently upregulated or downregulated at all time points and dose levels interrogated. Pathway and gene ontology analysis were performed; bioinformatic analysis revealed significant pathway and biological process perturbations post high-dose irradiation and shed light on underlying mechanisms of radiation damage. Additionally, proteins were identified that had the greatest potential to serve as biomarkers for radiation exposure.

Application of an antibody chip for screening differentially expressed proteins during peach ripening and identification of a metabolon in the SAM cycle to generate a peach ethylene biosynthesis model

Peach (Prunus persica) is a typical climacteric fruit that produces ethylene rapidly during ripening, and its fruit softens quickly. Stony hard peach cultivars, however, do not produce large amounts of ethylene, and the fruit remains firm until fully ripe, thus differing from melting flesh peach cultivars. To identify the key proteins involved in peach fruit ripening, an antibody-based proteomic analysis was conducted. A mega-monoclonal antibody (mAb) library was generated and arrayed on a chip (mAbArray) at a high density, covering ~4950 different proteins of peach. Through the screening of peach fruit proteins with the mAbArray chip, differentially expressed proteins recognized by 1587 mAbs were identified, and 33 corresponding antigens were ultimately identified by immunoprecipitation and mass spectrometry. These proteins included not only important enzymes involved in ethylene biosynthesis, such as ACO1, SAHH, SAMS, and MetE, but also novel factors such as NUDT2. Furthermore, protein-protein interaction analysis identified a metabolon containing SAHH and MetE. By combining the antibody-based proteomic data with the transcriptomic and metabolic data, a mathematical model of ethylene biosynthesis in peach was constructed. Simulation results showed that MetE is an important regulator during peach ripening, partially through interaction with SAHH.

Blood test shows high accuracy in detecting stage I non-small cell lung cancer

Background

In a previous study (Goebel et. al, Cancer Genomics Proteomics 16:229-244, 2019), we identified 33 biomarkers for an early stage (I-II) Non-Small Cell Lung Cancer (NSCLC) test with 90% accuracy, 80.3% sensitivity, and 95.4% specificity. For the current study, we used a narrowed ensemble of 21 biomarkers while retaining similar accuracy in detecting early stage lung cancer.

Methods

A multiplex platform, 486 human plasma samples, and 21 biomarkers were used to develop and validate our algorithm which detects early stage NSCLC. The training set consisted of 258 human plasma with 79 Stage I-II NSCLC samples. The 21 biomarkers with the statistical model (Lung Cancer Detector Test 1, LCDT1) was then validated using 228 novel samples which included 55 Stage I NSCLC.

Results

The LCDT1 exhibited 95.6% accuracy, 89.1% sensitivity, and 97.7% specificity in detecting Stage I NSCLC on the blind set. When only NSCLC cancers were analyzed, the specificity increased to 99.1%.

Conclusions

Compared to current approved clinical methods for diagnosing NSCLC, the LCDT1 greatly improves accuracy while being non-invasive; a simple, cost-effective, early diagnostic blood test should result in expanding access and increase survival rate.

Identification of protein changes in the blood plasma of lung cancer patients subjected to chemotherapy using a 2D-DIGE approach

A comparative analysis of blood samples (depleted of albumin and IgG) obtained from lung cancer patients before chemotherapy versus after a second cycle of chemotherapy was performed using two-dimensional difference gel electrophoresis (2D-DIGE). The control group consisted of eight patients with non-cancerous lung diseases, and the experimental group consisted of four adenocarcinoma (ADC) and four squamous cell carcinoma (SCC) patients. Analyses of gels revealed significant changes in proteins and/or their proteoforms between control patients and lung cancer patients, both before and after a second cycle of chemotherapy. Most of these proteins were related to inflammation, including acute phase proteins (APPs) such as forms of haptoglobin and transferrin, complement component C3, and clusterin. The variable expression of APPs can potentially be used for profiling lung cancer. The greatest changes observed after chemotherapy were in transferrin and serotransferrin, which likely reflect disturbances in iron turnover after chemotherapy-induced anaemia. Significant changes in plasma proteins between ADC and SCC patients were also revealed, suggesting use of plasma vitronectin as a potential marker of SCC.

Clinical Significance of SERPINA1 Gene and Its Encoded Alpha1-antitrypsin Protein in NSCLC

High expression of SERPINA1 gene encoding acute phase protein, alpha1-antitrypsin (AAT), is associated with various tumors. We sought to examine the significance of SERPINA1 and AAT protein in non-small-cell lung cancer (NSCLC) patients and NSCLC cell lines. Tumor and adjacent non-tumor lung tissues and serum samples from 351 NSCLC patients were analyzed for SERPINA1 expression and AAT protein levels. We also studied the impact of SERPINA1 expression and AAT protein on H1975 and H661 cell behavior, in vitro. Lower SERPINA1 expression in tumor but higher in adjacent non-tumor lung tissues (n = 351, p = 0.016) as well as higher serum levels of AAT protein (n = 170, p = 0.033) were associated with worse survival rates. Specifically, in NSCLC stage III patients, higher blood AAT levels (>2.66 mg/mL) correlated with a poor survival (p = 0.002). Intriguingly, levels of serum AAT do not correlate with levels of C-reactive protein, neutrophils-to-leukocyte ratio, and do not correlate with SERPINA1 expression or AAT staining in the tumor tissue. Additional experiments in vitro revealed that external AAT and/or overexpressed SERPINA1 gene significantly improve cancer cell migration, colony formation and resistance to apoptosis. SERPINA1 gene and AAT protein play an active role in the pathogenesis of lung cancer and not just reflect inflammatory reaction related to cancer development.

Idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbon in human blood serum are new biomarkers of lung cancer

Evaluation of epidemiologic risk factor in relation to lung cancer invoked by polycyclic aromatic hydrocarbons has been inconsistent. To address this issue, we conducted a prospective evaluation of new biomarkers for lung cancer classified according levels of idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbons in human blood serum. The blood serums of 557 lung cancer patients and 227 healthy donors were analysis of these antibodies by ELISA. Collected data were regrouped and analyzed by gender, smoking, and age as predictors of risk lung cancer factors. Also, the data of lung cancer patients were additionally analyzed by stages and types of lung cancer, surgery, and chemotherapy. It was suggested to use ratio of idiotypic and anti-idiotypic antibodies rather than distinguish level each of them separately. The ratio of levels in healthy people was 3.32 times higher than in lung cancer patients. This approach gave more precisely results and great prognostic value. The logistic regression model (AUC = 0.9) and neural networks (AUC = 0.95) were built to compare lung cancer patients and healthy donors by predictors. The ELISA data of 49 people random sampled from the originally ELISA data and ELISA data of 52 coal miners as a group of lung cancer risk were confirmed logistic regression model. So, suggested idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbons were not only shown difference between healthy donors and lung cancer patients also elicited group of lung cancer risk among healthy people.

Evaluation of a biomarker for the diagnosis of pancreas cancer using an animal model

Many approaches have been taken to identify new biomarkers of pancreatic ductal carcinoma (PDC). Since animal models can be sampled under controlled conditions, better standardization is possible compared with heterogeneous human studies. Transgenic rats with conditional activation of oncogenic RAS in pancreatic tissue develop PDC that closely resembles the biological and histopathological features of human PDC. Using this model, we evaluated the usefulness of leucine-rich α2-glycoprotein-1 (LRG-1) as a serum marker. In this study, we found that LRG-1 was overexpressed in rat PDC compared with normal pancreas tissue of the control rats. Serum levels of LRG-1 were also significantly higher in rats bearing PDC than in controls. Importantly, chronic pancreatitis in male Wistar Bonn/Kobori rats, which is a widely accepted as a model of chronic pancreatitis, did not cause serum levels of LRG-1 to become elevated. These results strongly support serum LRG-1 as a candidate biomarker for noninvasive diagnosis of PDC. Our models of pancreas cancer provide a useful strategy for evaluation of candidate markers applicable to human cancer.

Systematic Development of Sandwich Immunoassays for the Plasma Secretome

The plasma proteome offers a clinically useful window into human health. Recent advances from highly multiplexed assays now call for appropriate pipelines to validate individual candidates. Here, a workflow is developed to build dual binder sandwich immunoassays (SIA) and for proteins predicted to be secreted into plasma. Utilizing suspension bead arrays, ≈1800 unique antibody pairs are first screened against 209 proteins with recombinant proteins as well as EDTA plasma. Employing 624 unique antibodies, dilution-dependent curves in plasma and concentration-dependent curves of full-length proteins for 102 (49%) of the targets are obtained. For 22 protein assays, the longitudinal, interindividual, and technical performance is determined in a set of plasma samples collected from 18 healthy subjects every third month over 1 year. Finally, 14 of these assays are compared with with SIAs composed of other binders, proximity extension assays, and affinity-free targeted mass spectrometry. The workflow provides a multiplexed approach to screen for SIA pairs that suggests using at least three antibodies per target. This design is applicable for a wider range of targets of the plasma proteome, and the assays can be applied for discovery but also to validate emerging candidates derived from other platforms.

Compensated Interferometry Measures of CYFRA 21-1 Improve Diagnosis of Lung Cancer

Diagnosis of lung cancer patients with indeterminate pulmonary nodules (IPNs) presents a significant clinical challenge, with morbidity and management costs of $28 billion/year. We show that a quantitative free-solution assay (FSA), coupled with a compensated interferometric reader (CIR), improves the diagnostic performance of CYFRA 21-1 as a lung cancer biomarker. FSA-CIR is a rapid, mix-and-read, isothermal, label- and enzyme-free, matrix-insensitive, and target and probe-agnostic assay. Operating FSA-CIR at ∼40, 0.75 μL samples/day delivered a serum CYFRA 21-1 limit of quantification (LOQ) of 81 pg/mL with intra-assay and interassay CVs of 4.9% and 9.6% for four-day replicate determinations. Blinded analysis of a 225 patient cohort, consisting of 75 nonmalignant nodules, 45 adenocarcinomas, 44 squamous cell carcinomas, and 61 small cell lung cancers, gave a clear separation of cases and controls, not observed in the Cobas ECL analysis. The area under the curve (AUC) for the Mayo model increased from 0.595 to 0.923 when combined with the FSA-CIR CYFRA 21-1 measurements. In a population with nodules between 6 and 30 mm, the AUC increased from 0.567 to 0.943. In this subgroup, the positive predictive value (PPV) for all tumors by the CYFRA 21-1 assay was 98.7%. Our results demonstrate increased performance of the CYFRA 21-1 assay using FSA-CIR and represents a proof of concept for redefining the performance characteristics of this important candidate biomarker.

Comparative proteomic analysis in serum of former uranium miners with and without radon induced squamous lung cancer

Summary

Former uranium miners of the Wismut Company, East Germany, have been exposed to ionizing radiation from radon decay products and therefore were at high risk for lung cancer. Since histological types of cancer in the so called Wismut cohort revealed an association of high radon exposure with a higher relative frequency of squamous cell carcinoma (SqCC), we used comparative proteomic analysis to identify differentially expressed proteins in serum exposed uranium miners with SqCC.

Methode

Pooled sera of exposed former uranium miners without lung disease and pooled sera of former uranium miners with SqCC were analysed by 2-D gel electrophoresis. MALDI-TOF-MS was performed from reproducable, significantly, at least 5-fold up-regulated protein spots. Proteins were identified by MASCOT peptide mass fingerprint search. Additionally a receiver operating characteristic curve for CYFRA 21-1 was created.

Results

The protein spots were identified as Keratin 10 (K10), Keratin 1 (K1), complement factor H (CFH) and a haptoglobin (Hpt) fragment. The sensitivity for CYFRA 21-1 reveals 60% at a specifity of 95 and 80% at a specifity of 80%. Plotting the sensitivity against specifity reveals an AUC of 0.88.

Conclusion

In SqCC Keratin 10 and 1 were strongly induced. This was associated with CYFRA 21-1, confirming the cytokeratin fragment as a tumormarker.

Metabolome-based biomarkers: their potential role in the early detection of lung cancer

Lung cancer is the leading cause of cancer-related death worldwide, and a major problem affecting its mortality is the late diagnosis of the majority of cases, where treatment options are limited and overall prognosis is very bad. Currently, a low-dose computed tomography (LD-CT) screening in the high-risk group is the only available diagnostic strategy that could reduce mortality due to this malignancy. However, the LD-CT screening test suffers from a high false positive rate. Hence, complementation of LD-CT examination with blood-based biomarkers is a rational approach to increase efficacy and reduce the cost of early lung cancer screening programs. Several molecular signatures that discriminate between patients with early lung cancer and healthy individuals have been proposed in recent years, which are based on components of serum/plasma metabolome. However, none of these signatures has been validated by independent studies based on material collected during real lung cancer screening. Therefore, the validation of the real diagnostic value of these otherwise promising candidates remains a critical step in this challenging field of cancer diagnostics.

Identification of blood biomarkers in glioblastoma by SWATH mass spectrometry and quantitative targeted absolute proteomics

Molecular biomarkers in blood are needed to aid the early diagnosis and clinical assessment of glioblastoma (GBM). Here, in order to identify biomarker candidates in plasma of GBM patients, we performed quantitative comparisons of the plasma proteomes of GBM patients (n = 14) and healthy controls (n = 15) using SWATH mass spectrometry analysis. The results were validated by means of quantitative targeted absolute proteomics analysis. As a result, we identified eight biomarker candidates for GBM (leucine-rich alpha-2-glycoprotein (LRG1), complement component C9 (C9), C-reactive protein (CRP), alpha-1-antichymotrypsin (SERPINA3), apolipoprotein B-100 (APOB), gelsolin (GSN), Ig alpha-1 chain C region (IGHA1), and apolipoprotein A-IV (APOA4)). Among them, LRG1, C9, CRP, GSN, IGHA1, and APOA4 gave values of the area under the receiver operating characteristics curve of greater than 0.80. To investigate the relationships between the biomarker candidates and GBM biology, we examined correlations between plasma concentrations of biomarker candidates and clinical presentation (tumor size, progression-free survival time, or overall survival time) in GBM patients. The plasma concentrations of LRG1, CRP, and C9 showed significant positive correlations with tumor size (R² = 0.534, 0.495, and 0.452, respectively).

Direct labeling of serum proteins by fluorescent dye for antibody microarray

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum.

Sequential Validation of Blood-Based Protein Biomarker Candidates for Early-Stage Pancreatic Cancer

Background

CA19-9, which is currently in clinical use as a pancreatic ductal adenocarcinoma (PDAC) biomarker, has limited performance in detecting early-stage disease. We and others have identified protein biomarker candidates that have the potential to complement CA19-9. We have carried out sequential validations starting with 17 protein biomarker candidates to determine which markers and marker combination would improve detection of early-stage disease compared with CA19-9 alone.

Methods

Candidate biomarkers were subjected to enzyme-linked immunosorbent assay based sequential validation using independent multiple sample cohorts consisting of PDAC cases (n = 187), benign pancreatic disease (n = 93), and healthy controls (n = 169). A biomarker panel for early-stage PDAC was developed based on a logistic regression model. All statistical tests for the results presented below were one-sided.

Results

Six out of the 17 biomarker candidates and CA19-9 were validated in a sample set consisting of 75 PDAC patients, 27 healthy subjects, and 19 chronic pancreatitis patients. A second independent set of 73 early-stage PDAC patients, 60 healthy subjects, and 74 benign pancreatic disease patients (combined validation set) yielded a model that consisted of TIMP1, LRG1, and CA19-9. Additional blinded testing of the model was done using an independent set of plasma samples from 39 resectable PDAC patients and 82 matched healthy subjects (test set). The model yielded areas under the curve (AUCs) of 0.949 (95% confidence interval [CI] = 0.917 to 0.981) and 0.887 (95% CI = 0.817 to 0.957) with sensitivities of 0.849 and 0.667 at 95% specificity in discriminating early-stage PDAC vs healthy subjects in the combined validation and test sets, respectively. The performance of the biomarker panel was statistically significantly improved compared with CA19-9 alone (P < .001, combined validation set; P = .008, test set).

Conclusion

The addition of TIMP1 and LRG1 immunoassays to CA19-9 statistically significantly improves the detection of early-stage PDAC.

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis

OBJECTIVE

We performed a comprehensive review and meta-analysis to evaluate the diagnostic values of serum single and multiplex tumor-associated autoantibodies (TAAbs) in patients with lung cancer (LC).

METHODS

We searched the MEDLINE and EMBASE databases for relevant studies investigating serum TAAbs for the diagnosis of LC. The primary outcomes included sensitivity, specificity and accuracy of the test.

RESULTS

The systematic review and meta-analysis included 31 articles with single autoantibody and 39 with multiplex autoantibodies. Enzyme-linked immunosorbent assay (ELISA) was the most common detection method. For the diagnosis of patients with all stages and early-stage LC, different single or combinations of TAAbs demonstrated different diagnostic values. Although individual TAAbs showed low diagnostic sensitivity, the combination of multiplex autoantibodies offered relatively high sensitivity. For the meta-analysis of a same panel of autoantibodies in patients at all stages of LC, the pooled results of the panel of 6 TAAbs (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2) were: sensitivity 38% (95% CI 0.35-0.40), specificity 89% (95% CI 0.86-0.91), diagnostic accuracy 65.9% (range 62.5-81.8%), AUC 0.52 (0.48-0.57), while the summary estimates of 7 TAAbs (p53, CAGE, NY-ESO-1, GBU4-5, SOX2, MAGE A4 and Hu-D) were: sensitivity 47% (95% CI 0.34-0.60), specificity 90% (95% CI 0.89-0.92), diagnostic accuracy 78.4% (range 67.5-88.8%), AUC 0.90 (0.87-0.93). For the meta-analysis of the same panel of autoantibodies in patients at early-stage of LC, the sensitivities of both panels of 7 TAAbs and 6 TAAbs were 40% and 29.7%, while their specificities were 91% and 87%, respectively.

CONCLUSIONS

Serum single or combinations of multiplex autoantibodies can be used as a tool for the diagnosis of LC patients at all stages or early-stage, but the combination of multiplex autoantibodies shows a higher detection capacity; the diagnostic value of the panel of 7 TAAbs is higher than the panel of 6 TAAbs, which may be used as potential biomarkers for the early detection of LC.

Specific detection and quantitation of bovine IgG in bioreactor derived mouse mAb preparations

Monoclonal antibody and recombinant protein production benefits greatly from bovine serum as an additive. The caveat is that bovine serum IgG, co-purifies with mAbs and IgG Fc-containing fusion proteins and it presents a contaminant in the end products. In order to analytically validate the products, species specific reagents are needed that react with bovine IgG exclusively. Our attempts to find such commercially available reagents failed. Here, we report the production of species specific mAbs which recognize bovine IgG even in the presence of excess amount of mouse IgG. We present five mAbs: Bsi4028, Bsi4032, Bsi4033, Bsi4034 and Bsi4035 suitable to determine the presence of bovine IgG contamination via ELISA or immunoblotting in bioreactor derived mouse mAb preparations. To quantitate bovine IgG content we developed sensitive sandwich ELISAs capable to detect bovine IgG contaminant in the ng/ml (~10^-11M/l) range. Finally, we show that bovine IgG is efficiently removed from bioreactor produced mouse mAb preparation via affinity depletion columns prepared with Bsi4028, Bsi4032, Bsi4033, Bsi4034, Bsi4035 mAbs.

LRG1 downregulation in allergic airway disorders and its expression in peripheral blood and tissue cells

Background

Increased leucine-rich α2-glycoprotein-1 (LRG1) has been observed in plasma of individuals with various diseases. However, the role of LRG1 in allergic airway disease has not been investigated.

Objective

To explore the involvement of LRG1 in allergy and its cell origins.

Methods

The expression levels of LRG1 and its receptor transforming growth factor-beta receptor II (TGFBR2) in patients with allergic rhinitis (AR) and asthma (AS) were examined by flow cytometry, and enzyme-linked immunosorbent assay (ELISA).

Results

LRG1 and soluble TGFBR2 expression in plasma of patients with AR and AS were markedly lower than that of healthy control (HC) subjects. Large proportions of CD123 + HLA-DR−, CD16+, CD4+, CD8+, CD14+, and CD19+ cells expressed LRG1, although the percentages of LRG1+ cells in these cell populations were lower in AR and AS patients. Up to 89.8 and 15.5 % of dispersed mast cells expressed LRG1 and TGFBR2. Moreover, allergen extract exposure significantly reduced LRG1 and TGFBR2 expression in the plasma and leukocytes of patients with AR and AS.

Conclusions

Reduced LRG1 and TGFBR2 levels in patients with allergic airway disorders are likely caused by inhibitory actions of allergens in LRG1 producing cells. Thus, LRG1 may be a key regulatory factor of allergic responses.

Serum mass profile signature as a biomarker of early lung cancer

OBJECTIVES

Circulating molecular biomarkers of lung cancer may allow the pre-selection of candidates for computed tomography screening or increase its efficacy. We aimed to identify features of serum mass profile distinguishing individuals with early lung cancer from healthy participants of the lung cancer screening program.

METHODS

Blood samples were collected during a low-dose computed tomography (LD-CT) screening program performed by one institution (Medical University of Gdansk, Poland). MALDI-ToF mass spectrometry was used to characterize the low-molecular-weight (1000-14,000Da) serum fraction. The analysis comprised 95 patients with early stage lung cancer (including 30 screen-detected cases) and a matched group of 285 healthy controls. The cases were split into two independent cohorts (discovery and validation), analyzed separately 6 months apart.

RESULTS

Several molecular components of serum (putatively components of endogenous peptidome) discriminating patients with early lung cancer from controls were identified in a discovery cohort. This allowed building an effective cancer classifier as a model tuned to maximize negative predictive value, with an area under the curve (AUC) of 0.88, a negative predictive value of 100%, and a positive predictive value of 48%. However, the classifier performed worse in a validation cohort including independent sample sets (AUC 0.73, NPV 88% and PPV 30%).

CONCLUSIONS

We developed a serum mass profile-based signature identifying patients with early lung cancer. Although this marker has insufficient value as a stand-alone preselecting tool for LD-CT screening, its potential clinical usefulness in evaluation of indeterminate pulmonary nodules deserves further investigation.

Survivin Autoantibodies Are Not Elevated in Lung Cancer When Assayed Controlling for Specificity and Smoking Status

The high mortality rate in lung cancer is largely attributable to late diagnosis. Case-control studies suggest that autoantibodies to the survivin protein are potential biomarkers for early diagnosis. We tested the hypothesis that sandwich ELISA can detect autoantibodies to survivin before radiologic diagnosis in patients with early-stage non-small cell lung cancer (NSCLC). Because previous studies assayed survivin autoantibodies with the direct antigen-coating ELISA (DAC-ELISA), we first compared that assay with the sandwich ELISA. Based on the more robust results from the sandwich ELISA, we used it to measure survivin autoantibodies in the serum of 100 individuals from a well-controlled population study [the Dutch-Belgian Lung Cancer Screening Trial (NELSON) trial] composed of current and former smokers (50 patients with NSCLC, both before and after diagnosis, and 50 matched, smoking-habit control subjects), and another 50 healthy nonsmoking control subjects. We found no difference in specific autoantibodies to survivin in NSCLC patients, although nonspecific median optical densities were 24% higher (P < 0.001) in both NSCLC patients and smokers, than in healthy nonsmokers. Finally, we confirmed the ELISA results with Western blot analysis of recombinant and endogenous survivin (HEK-293), which showed no anti-survivin reactivity in patient sera. We conclude that specific anti-survivin autoantibody reactivity is most likely not present in sera before or after diagnosis. Autoantibody studies benefit from a comparison to a well-controlled population, stratified for smoking habit.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies.

Transition from identity to bioactivity-guided proteomics for biomarker discovery with focus on the PF2D platform

Proteomic strategies provide a valuable tool kit to identify proteins involved in diseases. With recent progress in MS technology, high throughput proteomics has accelerated protein identification for potential biomarkers. Numerous biomarker candidates have been identified in several diseases, and many are common among pathologies. An overall strategy that could complement and strengthen the search for biomarkers is combining protein identity with biological outcomes. This review describes an emerging framework of bridging bioactivity to protein identity, exploring the possibility that some biomarkers will have a mechanistic role in the disease process. A review of pulmonary, cardiovascular, and CNS biomarkers will be discussed to demonstrate the utility of combining bioactivity with identification as a means to not only find meaningful biomarkers, but also to uncover functional mediators of disease.

The role of TGFβ1 and LRG1 in cardiac remodelling and heart failure

Heart failure is a life-threatening condition that carries a considerable emotional and socio-economic burden. As a result of the global increase in the ageing population, sedentary life-style, increased prevalence of risk factors, and improved survival from cardiovascular events, the incidence of heart failure will continue to rise. Despite the advances in current cardiovascular therapies, many patients are not suitable for or may not benefit from conventional treatments. Thus, more effective therapies are required. Transforming growth factor (TGF) β family of cytokines is involved in heart development and dys-regulated TGFβ signalling is commonly associated with fibrosis, aberrant angiogenesis and accelerated progression into heart failure. Therefore, a potential therapeutic pathway is to modulate TGFβ signalling; however, broad blockage of TGFβ signalling may cause unwanted side effects due to its pivotal role in tissue homeostasis. We found that leucine-rich α-2 glycoprotein 1 (LRG1) promotes blood vessel formation via regulating the context-dependent endothelial TGFβ signalling. This review will focus on the interaction between LRG1 and TGFβ signalling, their involvement in the pathogenesis of heart failure, and the potential for LRG1 to function as a novel therapeutic target.

Lung Cancer Biomarkers

Lung cancer is the most frequently occurring cancer in the world and continually leads in mortality among cancers. The overall 5-year survival rate for lung cancer has risen only 4% (from 12% to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving lung cancer prognosis. Survival of patients undergoing lung resection is greater than 80%, suggesting that early detection and diagnosis of cancers before they become inoperable and lethal will greatly improve mortality. Lung cancer biomarkers can be used for screening, detection, diagnosis, prognosis, prediction, stratification, therapy response monitoring, and so on. This review focuses on noninvasive diagnostic and prognostic biomarkers. For that purpose, our discussion in this review will focus on biological fluid-based biomarkers. The body fluids include blood (serum or plasma), sputum, saliva, BAL, pleural effusion, and VOC. Since it is rich in different cellular and molecular elements and is one of the most convenient and routine clinical procedures, serum or plasma is the main source for the development and validation of many noninvasive biomarkers. In terms of molecular aspects, the most widely validated ones are proteins, some of which are used in the clinical sector, though in limited accessory purposes. We will also discuss the lung cancer (protein) biomarkers in clinical trials and currently in the validation phase with hundreds of samples. After proteins, we will discuss microRNAs, methylated DNA, and circulating tumor cells, which are being vigorously developed and validated as potential lung cancer biomarkers. The main aim of this review is to provide researchers and clinicians with an understanding of the potential noninvasive lung cancer biomarkers in biological fluids that have recently been discovered.

Delineating monoclonal antibody specificity by mass spectrometry

Generation of monoclonal antibody (mAb) libraries against antigens in complex matrices can prove a valuable analytical tool. However, delineating the specificity of newly generated antibodies is the limiting step of the procedure. Here, we propose a strategy for mAb production by injecting mice with complex biological fluid and mAb characterization by coupling immunoaffinity techniques with Mass spectrometry (immuno-MS). Mice were immunized against fractionated seminal plasma and mAbs were produced. Different immuno-MS protocols based on four types of solid support (i.e. polystyrene microtiter plates, NHS-activated agarose beads, tosyl-activated magnetic beads and MSIA™ pipette tips) were established. A well-characterized mouse monoclonal anti-KLK3 (PSA) Ab was used as a model to evaluate each protocol's robustness and reproducibility and to establish a set of criteria which would allow antigen characterization of newly developed Abs. Three of the newly generated Abs were analyzed using our optimized protocols. Analysis revealed that all assay configurations used were capable of antibody characterization. Furthermore, low-abundance antigens (e.g. ribonuclease T2) could be identified as efficiently as the high-abundance ones. Our data suggest that complex biological samples can be used for the production of mAbs, which will facilitate the analysis of their proteome, while the established immuno-MS protocols can offer efficient mAb characterization.

BIOLOGICAL SIGNIFICANCE

The inoculation of animals with complex biological samples is aiming at the discovery of novel disease biomarkers, present in the biological specimens, as well as the production of rare reagents that will facilitate the ultra-sensitive analysis of the biomolecules' native form. In the present study, we initially propose a general workflow concerning the handling of biological samples, as well as the monoclonal antibody production. Furthermore, we established protocols for the reliable and reproducible identification of antibody specificity using various immuno-affinity purification techniques coupled to mass spectrometry. Our data suggest that processed biological fluids can be used for the production of mAbs targeting proteins of varying abundance, and that various immuno-MS protocols can offer great capabilities for the mAb characterization procedure.

Co-overexpression of Hsp90-β and annexin A1 with a significantly positive correlation contributes to the diagnosis of lung cancer

AIM

Hsp90-β and annexin A1 have been demonstrated to be associated with tumorigenesis. However, the effect of Hsp90-β and annexin A1 in lung cancer remains poorly understood. In this research, the correlation of Hsp90-β and annexin A1 in lung cancer patients were analyzed.

METHODS

The expression levels of Hsp90-β and annexin A1 were examined by immunohistochemistry and ELISA.

RESULTS

Lung cancer tissues and serum exhibited higher co-expression of Hsp90-β and annexin A1 than control groups (p < 0.05). Hsp90-β and annexin A1 could discriminate lung cancer from the control groups (sensitivity of Hsp90-β was 80.2% in tissues and 96% in serum; specificity of Hsp90-β was 80% in tissues and 83.33% in serum; sensitivity of annexin A1 was 68.76% in tissues and 95.23% in serum; specificity of annexin A1 was 75% in tissues and 85.7% in serum) and multi-index combined detection had a better diagnostic value.

CONCLUSION

The expression levels of Hsp90-β and annexin A1 positively correlated and such co-overexpression of Hsp90-β and annexin A1 contributed to lung cancer diagnosis.

Deciphering the peptidome of urine from ovarian cancer patients and healthy controls

Background

Ovarian cancer (OvCa) is the most lethal gynecological malignancy. The emergence of high-throughput technologies, such as mass spectrometry, has allowed for a paradigm shift in the way we search for novel biomarkers. Urine-based peptidomic profiling is a novel approach that may result in the discovery of noninvasive biomarkers for diagnosing patients with OvCa. In this study, the peptidome of urine from 6 ovarian cancer patients and 6 healthy controls was deciphered.

Results

Urine samples underwent ultrafiltration and the filtrate was subjected to solid phase extraction, followed by fractionation using strong cation exchange chromatography. These fractions were analyzed using an Orbitrap mass spectrometer. Over 4600 unique endogenous urine peptides arising from 713 proteins were catalogued, representing the largest urine peptidome reported to date. Each specimen was processed in triplicate and reproducibility at the protein (69-76%) and peptide (58-63%) levels were noted. More importantly, over 3100 unique peptides were detected solely in OvCa specimens. One such promising biomarker was leucine-rich alpha-2-glycoprotein (LRG1), where multiple peptides were found in all urines from OvCa patients, but only one peptide was found in one healthy control urine sample.

Conclusions

Mining the urine peptidome may yield highly promising novel OvCa biomarkers.

A novel in silico reverse-transcriptomics-based identification and blood-based validation of a panel of sub-type specific biomarkers in lung cancer

Lung cancer accounts for the highest number of cancer-related deaths worldwide. Early diagnosis significantly increases the disease-free survival rate and a large amount of effort has been expended in screening trials and the development of early molecular diagnostics. However, a gold standard diagnostic strategy is not yet available. Here, based on miRNA expression profile in lung cancer and using a novel in silico reverse-transcriptomics approach, followed by analysis of the interactome; we have identified potential transcription factor (TF) markers that would facilitate diagnosis of subtype specific lung cancer. A subset of seven TF markers has been used in a microarray screen and was then validated by blood-based qPCR using stage-II and IV non-small cell lung carcinomas (NSCLC). Our results suggest that overexpression of HMGA1, E2F6, IRF1, and TFDP1 and downregulation or no expression of SUV39H1, RBL1, and HNRPD in blood is suitable for diagnosis of lung adenocarcinoma and squamous cell carcinoma sub-types of NSCLC. Here, E2F6 was, for the first time, found to be upregulated in NSCLC blood samples. The miRNA-TF-miRNA interaction based molecular mechanisms of these seven markers in NSCLC revealed that HMGA1 and TFDP1 play vital roles in lung cancer tumorigenesis. The strategy developed in this work is applicable to any other cancer or disease and can assist in the identification of potential biomarkers.

Neoglycoproteins as carbohydrate antigens: synthesis, analysis, and polyclonal antibody response

The analysis and polyclonal antibody response for newly synthesized maltose-BSA conjugate neoglycoproteins is described. In this first proof of concept study, a simple carbohydrate antigen, maltose, was linked to BSA by reductive amination. An aglycone spacer was utilized to conserve the intact annular maltose structure and to promote the accessibility of the carbohydrate immunogen hapten during immunization. The neoglycoproteins were investigated by CGE and the number of conjugated maltose residues was determined by MALDI-TOF MS. The neoglycoproteins were then evaluated by immunization of BALB/c mice and the polyclonal antibody response was tested by ELISA as evidence for the presence of sugar-containing epitope-specific antibodies. Selective antibody binding was demonstrated to the synthesized neoglycoproteins with different (low and high) glycosylation degrees suggesting the possible use of this approach to generate antibodies. Moreover, the polyclonal antibody response was not inhibited by maltose or other simple carbohydrates to confirm presence of the neoglycoprotein-specific antibodies.