Discovery of Lung Cancer Biomarkers by Profiling the Plasma Proteome with Monoclonal Antibody Libraries

Article · September 2011with46 Reads
DOI: 10.1074/mcp.M111.010298 · Source: PubMed
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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    • The overwhelming majority of clinical reports have shown that serum or plasma LRG1 levels are elevated during the development of various diseases. For example, LRG1 was upregulated in the serum or plasma of patients with hepatocellular carcinoma [20] , pancreatic cancer [21], ovarian cancer [7], lung cancer [8], and colorectal cancer [22]. Increased LRG1 expression was also found in patients undergoing neurodegenerative diseases [23], acute appendicitis [9], hydrocephalus [24], heart failure [25], autoimmune diseases [12], and ageing [26].
    [Show abstract] [Hide abstract] ABSTRACT: 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.
    Full-text · Article · Jul 2016
    • Several blood components have been analyzed in the search for such biomarkers, including circulating tumor cells, circulating tumor DNA, micro RNA, autoantibodies and specific serum or plasma proteins [8][9][10] . Of those, particularly promising are multicomponent panels of serum proteins, which were found to discriminate between healthy controls and patients with lung cancer in early and advanced stages with 80–90% sensitivity and specificity [11][12][13][14][15]. A promising potential of multicomponent signatures based on features of blood proteome in the detection of early stage lung cancer was demonstrated in several studies [16][17][18][19][20][21].
    [Show abstract] [Hide abstract] ABSTRACT: 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 (1000–14,000 Da) 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.
    Full-text · Article · Jun 2016
    • Based on the experiments described here, Fig. 1shows a workflow for the generation of useful information on antibody quality in the absence of epitope specificity and purified cognate protein. The technology is proposed for application during the proximal phase of the monoclonal antibody proteomics profiling process we described earlier [17,18].
    [Show abstract] [Hide abstract] 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.
    Full-text · Article · Aug 2014
    • However, one limitation of this approach was that the area under the curve (AUC) for LRG1 and the AUC of the combined markers (LRG1 + CA125) were not statistically different from the AUC of CA125 alone. Recently, LRG1 was found to be enriched in the urine of patients with appendicitis [39], as well as the serum of individuals with lung cancer [40], and heart failure [41]. It has also been suggested as a biomarker of ulcerative colitis [42].
    [Show abstract] [Hide abstract] ABSTRACT: 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.
    Full-text · Article · Jun 2014
    • Some of these are as follows: 34 miRNA signatures [6], expression profiles of 11 miRNAs (miR-106a, miR-15b, miR-27b, miR-142-3p, miR-26b, miR-182, miR-126, let7g, let-7i and miR-30e- 5p) from serum [7], 7 miRNA signatures [8] , overexpression of six snoRNAs [9], and expression of 3 miRs (miR-205, miR-210 and miR-708) in sputum [10] . Additional signatures and markers have also been reported from the plasma proteome [11,12] , the salivary pro- teome [13], the serum epigenome [14], sputum-based genomics [15], and blood-based gene expression studies [16] . However, none of these have progressed sufficiently to provide the necessary specificity and sensitivity required for clinical implementation.
    [Show abstract] [Hide abstract] 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.
    Full-text · Article · Oct 2013
  • [Show abstract] [Hide abstract] ABSTRACT: Complement (C) activation-related hypersensitivity reactions (HSRs) represent an unsolved adverse immune effect of many i.v. administered “nanomedicines”, such as liposomal doxorubicin (Doxil/Caelyx). Because these pseudoallergic reactions can be severe or even lethal, it is an important clinical objective to find biomarkers for proneness for C activation by reactogenic nanoparticles that will allow the prediction of in vivo reactions by in vitro assays. With this goal in mind we identified a normal human blood donor who consistently showed high sensitivity to Caelyx-induced C activation in vitro, whose plasma (Caelyx sensitive plasma, CSP) was subjected to proteome profiling with a library of human plasma proteome specific mAbs. The chip (PlasmaScan-380TM) contained 380 non redundant (with respect to epitopes) mAbs. The analysis revealed 8 proteins that were differentially represented in CSP in comparison with Caelyx-insensitive control plasma. These proteins were identified by mass spectrometry and Western blot analyses to represent factor H (decreased in CSP), factor H related protein, serum amyloid P component, fibronectin, complement component C4, Apo B100, prothrombin and alpha-2-HS glycoprotein (all increased in CSP). Some of these protein changes are consistent with proneness for increased C activation, suggesting the potential use of this method in the search for biomarkers for liposome-induced or other types of nanomedicine-induced HSRs.
    Full-text · Article · Jan 2013
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