Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries.
ABSTRACT A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC.
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ABSTRACT: 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.Clinical Proteomics 01/2014; 11(1):23.
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ABSTRACT: Monoclonal antibody proteomics uses nascent libraries or cloned (Plasmascan™, QuantiPlasma™) libraries of mAbs that react with individual epitopes of proteins in the human plasma. At the initial phase of library creation, cognate protein antigen and the epitope interacting with the antibodies are not known. Scouting for monoclonal antibodies (mAbs) with the best binding characteristics is of high importance for mAb based biomarker assay development. However, in the absence of the identity of the cognate antigen the task represents a challenge. We combined phage display, and surface plasmon resonance (Biacore) experiments to test whether specific phages and the respective mimotope peptides obtained from large scale studies are applicable to determine key features of antibodies for scouting. We show here that mAb captured phage-mimotope heterogeneity that is the diversity of the selected peptide sequences, is inversely correlated with an important binding descriptor; the off-rate of the antibodies and that represents clues for driving the selection of useful mAbs for biomarker assay development. Carefully chosen synthetic mimotope peptides are suitable for specificity testing in competitive assays using the target proteome, in our case the human plasma.Immunology letters 08/2014; · 2.91 Impact Factor
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ABSTRACT: 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.BMC Genomics 10/2013; · 4.04 Impact Factor