Chi-De Chen

Candidate Serological Biomarkers for Cancer Identified from the Secretomes of 23 Cancer Cell Lines and the Human Protein Atlas

Although cancer cell secretome profiling is a promising strategy used to identify potential body fluid-accessible cancer biomarkers, questions remain regarding the depth to which the cancer cell secretome can be mined and the efficiency with which researchers can select useful candidates from the growing list of identified proteins. Therefore, we analyzed the secretomes of 23 human cancer cell lines derived from 11 cancer types using one-dimensional SDS-PAGE and nano-LC-MS/MS performed on an LTQ-Orbitrap mass spectrometer to generate a more comprehensive cancer cell secretome. A total of 31,180 proteins was detected, accounting for 4,584 non-redundant proteins, with an average of 1,300 proteins identified per cell line. Using protein secretion-predictive algorithms, 55.8% of the proteins appeared to be released or shed from cells. The identified proteins were selected as potential marker candidates according to three strategies: (i) proteins apparently secreted by one cancer type but not by others (cancer type-specific marker candidates), (ii) proteins released by most cancer cell lines (pan-cancer marker candidates), and (iii) proteins putatively linked to cancer-relevant pathways. We then examined protein expression profiles in the Human Protein Atlas to identify biomarker candidates that were simultaneously detected in the secretomes and highly expressed in cancer tissues. This analysis yielded 6–137 marker candidates selective for each tumor type and 94 potential pan-cancer markers. Among these, we selectively validated monocyte differentiation antigen CD14 (for liver cancer), stromal cell-derived factor 1 (for lung cancer), and cathepsin L1 and interferon-induced 17-kDa protein (for nasopharyngeal carcinoma) as potential serological cancer markers. In summary, the proteins identified from the secretomes of 23 cancer cell lines and the Human Protein Atlas represent a focused reservoir of potential cancer biomarkers.

Comparative and Targeted Proteomic Analyses of Urinary Microparticles from Bladder Cancer and Hernia Patients

Bladder cancer is a common urologic cancer whose incidence continues to rise annually. Urinary microparticles are an attractive material for noninvasive bladder cancer biomarker discovery. In this study, we applied isotopic dimethylation labeling coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to discover bladder cancer biomarkers in urinary microparticles isolated from hernia (control) and bladder cancer patients. This approach identified 2964 proteins based on more than two distinct peptides, of which 2058 had not previously been reported as constituents of human urine exosomes/microparticles. A total of 107 differentially expressed proteins were identified as candidate biomarkers. Differences in the concentrations of 29 proteins (41 signature peptides) were precisely quantified by LC-MRM/MS in 48 urine samples of bladder cancer, hernia, and urinary tract infection/hematuria. Concentrations of 24 proteins changed significantly (p<0.05) between bladder cancer (n=28) and hernia (n=12), with area-under-the-curve values ranging from 0.702 to 0.896. Finally, we quantified tumor-associated calcium-signal transducer 2 (TACSTD2) in raw urine specimens (n=221) using a commercial ELISA and confirmed its potential value for diagnosis of bladder cancer. Our study reveals a strong association of TACSTD2 with bladder cancer and highlights the potential of human urinary microparticles in the noninvasive diagnosis of bladder cancer.

Discovery of novel bladder cancer biomarkers by comparative urine proteomics using iTRAQ technology.

A urine sample preparation workflow for the iTRAQ (isobaric tag for relative and absolute quantitation) technique was established. The reproducibility of this platform was evaluated and applied to discover proteins with differential levels between pooled urine samples from nontumor controls and three bladder cancer patient subgroups with different grades/stages (a total of 14 controls and 23 cancer cases in two multiplex iTRAQ runs). Combining the results of two independent clinical sample sets, a total of 638 urine proteins were identified. Among them, 55 proteins consistently showed >2-fold differences in both sample sets. Western blot analyses of individual urine samples confirmed that the levels of apolipoprotein A-I (APOA1), apolipoprotein A-II, heparin cofactor 2 precursor and peroxiredoxin-2 were significantly elevated in bladder cancer urine specimens (n = 25-74). Finally, we quantified APOA1 in a number of urine samples using a commercial ELISA and confirmed again its potential value for diagnosis (n = 126, 94.6% sensitivity and 92.0% specificity at a cutoff value of 11.16 ng/mL) and early detection (n = 71, 83.8% sensitivity and 94.0% specificity). Collectively, our results provide the first iTRAQ-based quantitative profile of bladder cancer urine proteins and represent a valuable resource for the discovery of bladder cancer markers.

Importin subunit alpha-2 is identified as a potential biomarker for non-small cell lung cancer by integration of the cancer cell secretome and tissue transcriptome

The cancer cell secretome may contain potentially useful biomarkers. In this study, we integrated the profiles of secreted proteins in lung cancer cell lines with mRNA expression levels from pulmonary adenocarcinoma tissue, with a view to identify effective biomarkers for non‐small cell lung cancer (NSCLC). Among the novel candidates isolated, importin subunit alpha‐2 (also known as karyopherin subunit alpha [KPNA]‐2), was selected for further validation. Immunohistochemical staining revealed overexpression of KPNA2 in the nuclei of tumor cells, compared with adjacent normal cells. A sandwich ELISA assay developed to detect KPNA2 levels in serum samples showed significantly higher serum KPNA2 in NSCLC patients than in healthy controls. A combination of serum KPNA2 and carcinoembryonic antigen displayed higher diagnostic capacity than either marker alone. Importantly, protein levels of KPNA2 in pleural effusion from NSCLC patients were also significantly higher than those from non‐lung cancer. Moreover, knockdown of KPNA2 inhibited the migration ability and viability of lung cancer cells. Our results collectively suggest that integration of the cancer cell secretome and transcriptome datasets provides an efficient means of identifying novel biomarkers for NSCLC, such as KPNA2.

Discovery of Retinoblastoma-Associated Binding Protein 46 as a Novel Prognostic Marker for Distant Metastasis in Nonsmall Cell Lung Cancer by Combined Analysis of Cancer Cell Secretome and Pleural Effusion Proteome

Nonsmall cell lung cancer (NSCLC) is the most common type of lung cancer, which is one of the most prominent causes of cancer-related mortality worldwide. Discovery of serum tumor markers could facilitate early NSCLC detection and metastatic prognosis. Here, we simultaneously analyzed the NSCLC cell secretome and proteomic profiles of pleural effusion from lung adenocarcinoma patients for NSCLC biomarker discovery. Retinoblastoma-associated binding protein 46 (RbAp46), one of the proteins detected both in NSCLC cell secretome and pleural effusion proteome, was chosen for further evaluation. Both of RbAp46 mRNA and protein levels were upregulated significantly in NSCLC cancer tissues. Serum levels of RbAp46 were markedly higher in NSCLC patients than in healthy controls, and a combination of RbAp46 and CEA could outperform CEA alone in discriminating NSCLC patients from healthy persons. Importantly, elevated serum RbAp46 level was highly correlated with NSCLC distant metastasis. Moreover, knockdown of RbAp46 inhibited the migration ability of lung cancer cells. Our data collectively suggest that RbAp46 serves as a novel biomarker and prognosticator for NSCLC, and is involved in lung cancer cell migration.

Comprehensive proteomic analysis of mineral nanoparticles derived from human body fluids and analyzed by liquid chromatography–tandem mass spectrometry

Mineralo-protein nanoparticles (NPs) formed spontaneously in the body have been associated with ectopic calcifications seen in atherosclerosis, chronic degenerative diseases, and kidney stone formation. Synthetic NPs are also known to become coated with proteins when they come in contact with body fluids. Identifying the proteins found in NPs should help unravel how NPs are formed in the body and how NPs in general, be they synthetic or naturally formed, interact within the body. Here, we developed a proteomic approach based on liquid chromatography (LC) and tandem mass spectrometry (MS/MS) to determine the protein composition of carbonate-apatite NPs derived from human body fluids (serum, urine, cerebrospinal fluid, ascites, pleural effusion, and synovial fluid). LC-MS/MS provided not only an efficient and comprehensive determination of the protein constituents, but also a semiquantitative ranking of the identified proteins. Notably, the identified NP proteins mirrored the protein composition of the contacting body fluids, with albumin, fetuin-A, complement C3, α-1-antitrypsin, prothrombin, and apolipoproteins A1 and B-100 being consistently associated with the particles. Since several coagulation factors, calcification inhibitors, complement proteins, immune regulators, protease inhibitors, and lipid/molecule carriers can all become NP constituents, our results suggest that mineralo-protein complexes may interface with distinct biochemical pathways in the body depending on their protein composition. We propose that LC-MS/MS be used to characterize proteins found in both synthetic and natural NPs.

Comprehensive Proteome Analysis of Malignant Pleural Effusion for Lung Cancer Biomarker Discovery by Using Multidimensional Protein Identification Technology

Malignant pleural effusion (MPE) obtained from lung adenocarcinoma may contain potentially useful biomarkers for detection of lung cancer. In this study, we used a removal system for high-abundance proteins followed by one-dimensional SDS-PAGE combined with nano-LC-MS/MS to generate a comprehensive MPE proteome data set with 482 nonredundant proteins. Next, we integrated the MPE proteome and secretome data sets from three adenocarcinoma cell lines, with a view to identifying potential PE biomarkers originating from malignant cells. Four potential candidates, alpha-2-HS-glycoprotein (AHSG), angiogenin, cystatin-C, and insulin-like growth factor-binding protein 2, (IGFBP2), were isolated for preclinical validation using ELISA. Both AHSG and IGFBP2 levels were increased in lung patients with MPE (n = 68), compared to those with nonmalignant pleural effusion (n = 119). Notably, the IGFBP2 level was higher in MPE, compared with that in benign diseases (bacteria pneumonia and tuberculosis pleuritis), and significantly associated with malignancy, regardless of the cancer type. Our data additionally support an extracellular function of IGFBP2 in migration in lung cancer cells. These findings collectively suggest that the adenocarcinoma MPE proteome provides a useful data set for malignancy biomarker research.

In-depth proteomic analysis of six types of exudative pleural effusions for nonsmall cell lung cancer biomarker discovery.

Pleural effusion (PE), a tumor-proximal body fluid, may be a promising source for biomarker discovery in human cancers. Because a variety of pathological conditions can lead to PE, characterization of the relative PE proteomic profiles from different types of PEs would accelerate discovery of potential PE biomarkers specifically used to diagnose pulmonary disorders. Using quantitative proteomic approaches, we identified 772 nonredundant proteins from six types of exudative PEs, including three malignant PEs (MPE, from lung, breast, and gastric cancers), one lung cancer paramalignant PE, and two benign diseases (tuberculosis and pneumonia). Spectral counting was utilized to semiquantify PE protein levels. Principal component analysis, hierarchical clustering, and Gene Ontology of cellular process analyses revealed differential levels and functional profiling of proteins in each type of PE. We identified 30 candidate proteins with twofold higher levels (q<0.05) in lung cancer MPEs than in the two benign PEs. Three potential markers, MET, DPP4, and PTPRF, were further verified by ELISA using 345 PE samples. The protein levels of these potential biomarkers were significantly higher in lung cancer MPE than in benign diseases or lung cancer paramalignant PE. The area under the receiver-operator characteristic curve for three combined biomarkers in discriminating lung cancer MPE from benign diseases was 0.903. We also observed that the PE protein levels were more clearly discriminated in effusions in which the cytological examination was positive and that they would be useful in rescuing the false negative of cytological examination in diagnosis of nonsmall cell lung cancer-MPE. Western blotting analysis further demonstrated that MET overexpression in lung cancer cells would contribute to the elevation of soluble MET in MPE. Our results collectively demonstrate the utility of label-free quantitative proteomic approaches in establishing differential PE proteomes and provide a new database of proteins that can be used to facilitate identification of pulmonary disorder-related biomarkers.

Targeted proteomics pipeline reveals potential biomarkers for the diagnosis of metastatic lung cancer in pleural effusion.

The ability to discriminate lung cancer malignant pleural effusion (LC-MPE) from benign pleural effusion has profound implications for the therapy and prognosis of lung cancer. Here, we established a pipeline to verify potential biomarkers for this purpose. In the discovery phase, label-free quantification was performed for the proteome profiling of exudative pleural effusion in order to select 34 candidate biomarkers with significantly elevated levels in LC-MPE. In the verification phase, signature peptides for 34 candidates were first confirmed by accurate inclusion mass screening (AIMS). To quantify the candidates in PEs, multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope-labeled standards (SIS) peptides was performed for the 34 candidate biomarkers using the QconCAT approach for the generation of the SIS peptides. The results of the MRM assay were used to prioritize candidates based on their discriminatory power in 82 exudative PE samples. The five potential biomarkers (ALCAM, CDH1, MUC1, SPINT1, and THBS4; AUC > 0.7) and one three-marker panel (SPINT1/SVEP1/THBS4; AUC = 0.95) were able to effectively differentiate LC-MPE from benign PE. Collectively, these results demonstrate that our pipeline is a feasible platform for verifying potential biomarkers for human diseases.

Quantitative plasma proteome analysis reveals aberrant level of blood coagulation-related proteins in nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC), one of the most common cancers in Southeast Asia, is not easily diagnosed until advanced stages. To discover potential biomarkers for improving NPC diagnosis, we herein identified the aberrant plasma proteins in NPC patients. We first removed the top-seven abundant proteins from plasma samples of healthy controls and NPC patients, and then labeled the samples with different fluorescent cyanine dyes. The labeled samples were then mixed equally and fractionated with ion-exchange chromatography followed by SDS-PAGE. Proteins showing altered levels in NPC patients were identified by in-gel tryptic digestion and LC-MS/MS. When the biological roles of the 45 identified proteins were assessed via MetaCore™ analysis, the blood coagulation pathway emerged as the most significantly altered pathway in NPC plasma. Plasma kallikrein (KLKB1) and thrombin-antithrombin III complex (TAT) were chosen for evaluation as the candidate NPC biomarkers because of their involvement in blood coagulation. ELISAs confirmed the elevation of their plasma levels in NPC patients versus healthy controls. Western blot and activity assays further showed that the KLKB1 active form was significantly increased in NPC plasma. Collectively, our results identified the significant alteration of blood coagulation pathway in NPC patients, and KLKB1 and TAT may represent the potential NPC biomarkers.