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

Hollow SnO2/CdS QDs/CdCO3 heterostructured nanocubes coupled with hollow PtPd/MnCo-CeO2 nanozyme-mediated synergistic amplification for ultrasensitive PEC immunoanalysis of lung cancer biomarker

Nowadays, lung cancer is one of the most dangerous cancers threatening human life all over the world. As a crucial biomarker, cytokeratin 19 fragment 21-1 (CYFRA 21-1) is extraordinary important for diagnosis of non-small cell lung cancer (NSCLC). In this work, we synthesized hollow SnO₂/CdS QDs/CdCO₃ heterostructured nanocubes with high and stable photocurrents, which applied to construction of a sandwich-typed photoelectrochemical (PEC) immunosensor for detection of CYFRA 21-1, integrated by in-situ catalytic precipitation strategy with home-built PtPd alloy anchored MnCo-CeO₂ (PtPd/MnCo-CeO₂) nanozyme for synergistic amplification. The interfacial electron transfer mechanism upon visible-light irradiation was investigated in details. Further, the PEC responses were seriously quenched by the specific immunoreaction and precipitation catalyzed by the PtPd/MnCo-CeO₂ nanozyme. The established biosensor showed a wider linear range of 0.001-200 ng mL^-1 and a lower limit of detection (LOD = 0.2 pg mL^-1, S/N = 3), coupled by exploring such analysis even in diluted human serum sample. This work opens a constructive avenue to develop ultrasensitive PEC sensing platforms for detecting diverse cancer biomarkers in clinic.

Assessment of a Large-Scale Unbiased Malignant Pleural Effusion Proteomics Study of a Real-Life Cohort

Simple Summary

Pleural effusion (PE) occurs as a consequence of various pathologies. Malignant effusion due to lung cancer is one of the most frequent causes. A method for accurate differentiation of malignant from benign PE is an unmet clinical need. Proteomics profiling of PE has shown promising results. However, mass spectrometry (MS) analysis typically involves the tedious elimination of abundant proteins before analysis, and clinical annotation of proteomics profiled cohorts is limited. This study compares the proteomes of malignant PE and nonmalignant PE, identifies lung cancer malignant markers in agreement with other studies, and identifies markers strongly associated with patient survival.

Abstract

Background: Pleural effusion (PE) is common in advanced-stage lung cancer patients and is related to poor prognosis. Identification of cancer cells is the standard method for the diagnosis of a malignant PE (MPE). However, it only has moderate sensitivity. Thus, more sensitive diagnostic tools are urgently needed. Methods: The present study aimed to discover potential protein targets to distinguish malignant pleural effusion (MPE) from other non-malignant pathologies. We have collected PE from 97 patients to explore PE proteomes by applying state-of-the-art liquid chromatography-mass spectrometry (LC-MS) to identify potential biomarkers that correlate with immunohistochemistry assessment of tumor biopsy or with survival data. Functional analyses were performed to elucidate functional differences in PE proteins in malignant and benign samples. Results were integrated into a clinical risk prediction model to identify likely malignant cases. Sensitivity, specificity, and negative predictive value were calculated. Results: In total, 1689 individual proteins were identified by MS-based proteomics analysis of the 97 PE samples, of which 35 were diagnosed as malignant. A comparison between MPE and benign PE (BPE) identified 58 differential regulated proteins after correction of the p-values for multiple testing. Furthermore, functional analysis revealed an up-regulation of matrix intermediate filaments and cellular movement-related proteins. Additionally, gene ontology analysis identified the involvement of metabolic pathways such as glycolysis/gluconeogenesis, pyruvate metabolism and cysteine and methionine metabolism. Conclusion: This study demonstrated a partial least squares regression model with an area under the curve of 98 and an accuracy of 0.92 when evaluated on the holdout test data set. Furthermore, highly significant survival markers were identified (e.g., PSME1 with a log-rank of 1.68 × 10⁻⁶).

Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.

Methods

The gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A nomogram was used to predict the survival probability of LUAD based on a risk model.

Results

We constructed a prognostic signature comprising 13 EM-related genes (AGER, AHSG, ALDH2, CIDEC, CYP17A1, FBP1, GNB3, GZMB, IGFBP1, SORD, SOX2, TRH and TYMS). The Kaplan–Meier curves validated the good predictive ability of the prognostic signature in TCGA AND two GEO datasets (p<0.0001, p=0.00021, and p=0.0034, respectively). The area under the curve (AUC) of the ROC curves also validated the predictive accuracy of the risk model. We built a nomogram to predict the survival probability of LUAD, and the calibration curves showed good predictive ability. Finally, a functional analysis also unveiled the different immune statuses between the two different risk groups.

Conclusion

Our study constructed and verified a novel EM-related prognostic gene signature that could improve the individualized prediction of survival probability in LUAD.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Novel serum peptide model revealed by MALDI-TOF-MS and its diagnostic value in early bladder cancer

BACKGROUND

Bladder cancer is the ninth most common cancer worldwide and has high morbidity and mortality. We aimed to search for potential serum peptide biomarkers and establish a diagnostic model for early bladder cancer.

METHODS

A total of 67 bladder cancer patients and 64 healthy volunteers were randomly divided into a training set and testing set 1. There were 30 hematuria patients used as testing set 2. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on weak cation exchange magnetic beads was used to obtain and analyze the serum peptide profiles between bladder cancer patients and healthy volunteers in the training set. Serum peptide diagnostic model through a k-nearest neighbor algorithm, was established and validated, and significantly differentially expressed protein biomarkers were ultimately identified.

RESULTS

We constructed a diagnostic model containing five peptides (m/z 1954.9, m/z 2081.0, m/z 3938.3, m/z 3946.5, and m/z 4268.8). In the training set, the area under the curve (AUC) value of the five-peptide model was 0.923, and the sensitivity and specificity was 93.75% and 96.77%, respectively. In testing set 1, the sensitivity and specificity was 91.43% and 90.91%, respectively, and the specificity of testing set 2 was 73.33%. For early-stage bladder cancer, the sensitivity and specificity was 92.31% and 93.75%, respectively; the sensitivity of early low-grade bladder cancer was 90.00%; and the AUC value was 0.944.

CONCLUSION

The five-peptide diagnostic model established in this study had high sensitivity and specificity, especially in the diagnosis of early bladder cancer, and could differentiate between healthy volunteers and hematuria patients.

Integrative Omics Analysis Reveals Soluble Cadherin-3 as a Survival Predictor and an Early Monitoring Marker of EGFR Tyrosine Kinase Inhibitor Therapy in Lung Cancer

PURPOSE

EGFR tyrosine kinase inhibitors (EGFR-TKI) benefit patients with advanced lung adenocarcinoma (ADC) harboring activating EGFR mutations. We aimed to identify biomarkers to monitor and predict the progression of patients receiving EGFR-TKIs via a comprehensive omic analysis.

EXPERIMENTAL DESIGN

We applied quantitative proteomics to generate the TKI resistance-associated pleural effusion (PE) proteome from patients with ADC with or without EGFR-TKI resistance. Candidates were selected from integrated genomic and proteomic datasets. The PE (n = 33) and serum (n = 329) levels of potential biomarkers were validated with ELISAs. Western blotting was applied to detect protein expression in tissues, PEs, and a cell line. Gene knockdown, TKI treatment, and proliferation assays were used to determine EGFR-TKI sensitivity. Progression-free survival (PFS) and overall survival (OS) were assessed to evaluate the prognostic values of the potential biomarkers.

RESULTS

Fifteen proteins were identified as potential biomarkers of EGFR-TKI resistance. Cadherin-3 (CDH3) was overexpressed in ADC tissues compared with normal tissues. CDH3 knockdown enhanced EGFR-TKI sensitivity in ADC cells. The PE level of soluble CDH3 (sCDH3) was increased in patients with resistance. The altered sCDH3 serum level reflected the efficacy of EGFR-TKI after 1 month of treatment (n = 43). Baseline sCDH3 was significantly associated with PFS and OS in patients with ADC after EGFR-TKI therapy (n = 76). Moreover, sCDH3 was positively associated with tumor stage in non-small cell lung cancer (n = 272).

CONCLUSIONS

We provide useful marker candidates for drug resistance studies. sCDH3 is a survival predictor and real-time indicator of treatment efficacy in patients with ADC treated with EGFR-TKIs.

IGFBP2: integrative hub of developmental and oncogenic signaling network

Insulin-like growth factor (IGF) binding protein 2 (IGFBP2) was discovered and identified as an IGF system regulator, controlling the distribution, function, and activity of IGFs in the pericellular space. IGFBP2 is a developmentally regulated gene that is highly expressed in embryonic and fetal tissues and markedly decreases after birth. Studies over the last decades have shown that in solid tumors, IGFBP2 is upregulated and promotes several key oncogenic processes, such as epithelial-to-mesenchymal transition, cellular migration, invasion, angiogenesis, stemness, transcriptional activation, and epigenetic programming via signaling that is often independent of IGFs. Growing evidence indicates that aberrant expression of IGFBP2 in cancer acts as a hub of an oncogenic network, integrating multiple cancer signaling pathways and serving as a potential therapeutic target for cancer treatment.

Label-Free Quantitative Proteomics Identifies Novel Biomarkers for Distinguishing Tuberculosis Pleural Effusion from Malignant Pleural Effusion

PURPOSE

To identify potential protein biomarkers for distinguishing tuberculosis plural effusion (TBPE) from malignant plural effusion (MPE).

EXPERIMENTAL DESIGN

Five independent samples from each group (TBPE and MPE) are enrolled for label-free quantitative proteomics analyses. The differentially expressed proteins are validated by western blot and ELISA. Logistic regression analysis is used to obtain the optimal diagnostic model.

RESULTS

In total, 14 proteins with significant difference are identified between TBPE and MPE. Seven differentially expressed proteins are validated using western blot, and the expression patterns of these seven proteins are similar with those in proteomics analysis. Statistically significant differences in four proteins (AGP1, ORM2, C9, and SERPING1) are noted between TBPE and MPE in the training set (n = 230). Logistic regression analysis shows the combination of AGP1-ORM2-C9 presents a sensitivity of 73.0% (92/126) and specificity of 89.4% (93/104) in discriminating TBPE from MPE. Additional validation is performed to evaluate the diagnostic model in an independent blind testing set (n = 80), and yielded a sensitivity of 74.4% (32/43) and specificity of 91.9% (34/37) in discriminating TBPE from MPE.

CONCLUSION

The study uncovers the proteomic profiles of TBPE and MPE, and provides new potential diagnostic biomarkers for distinguishing TBPE from MPE.

Cellular Interactions in the Tumor Microenvironment: The Role of Secretome

Over the past years, it has become evident that cancer initiation and progression depends on several components of the tumor microenvironment, including inflammatory and immune cells, fibroblasts, endothelial cells, adipocytes, and extracellular matrix. These components of the tumor microenvironment and the neoplastic cells interact with each other providing pro and antitumor signals. The tumor-stroma communication occurs directly between cells or via a variety of molecules secreted, such as growth factors, cytokines, chemokines and microRNAs. This secretome, which derives not only from tumor cells but also from cancer-associated stromal cells, is an important source of key regulators of the tumorigenic process. Their screening and characterization could provide useful biomarkers to improve cancer diagnosis, prognosis, and monitoring of treatment responses.

Potential biomarkers for antidiastole of tuberculous and malignant pleural effusion by proteome analysis

AIM

To investigate novel potential biomarkers for antidiastole of tuberculous pleural effusion (TPE) from malignant pleural effusion (MPE).

MATERIALS & METHODS

iTRAQTM-coupled LC-MS/MS were applied to analyze the proteome of TPE and MPE samples. The candidate proteins were verified by enzyme-linked immunosorbent assay.

RESULTS

A total of 432 differential proteins were identified. Enzyme-linked immunosorbent assay revealed significantly higher levels of fibronectin (FN) and cathepsin G (CTSG) in MPE than in TPE, but lower levels of leukotriene-A4 hydrolase (LTA4H). The receiver operator characteristic values were 0.285 for FN, 0.64 for LTA4H, 0.337 for CTSG and 0.793 for a combination of these candidate markers.

CONCLUSION

FN, LTA4H and CTSG were identified as potential biomarkers to differentiate TPE from MPE and their combination exhibited higher diagnostic capacity.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Impact of Fetuin-A (AHSG) on Tumor Progression and Type 2 Diabetes

Fetuin-A is the protein product of the AHSG gene in humans. It is mainly synthesized by the liver in adult humans and is secreted into the blood where its concentration can vary from a low of ~0.2 mg/mL to a high of ~0.8 mg/mL. Presently, it is considered to be a multifunctional protein that plays important roles in diabetes, kidney disease, and cancer, as well as in inhibition of ectopic calcification. In this review we have focused on work that has been done regarding its potential role(s) in tumor progression and sequelae of diabetes. Recently a number of laboratories have demonstrated that a subset of tumor cells such as pancreatic, prostate and glioblastoma multiform synthesize ectopic fetuin-A, which drives their progression. Fetuin-A that is synthesized, modified, and secreted by tumor cells may be more relevant in understanding the pathophysiological role of this enigmatic protein in tumors, as opposed to the relatively high serum concentrations of the liver derived protein. Lastly, auto-antibodies to fetuin-A frequently appear in the sera of tumor patients that could be useful as biomarkers for early diagnosis. In diabetes, solid experimental evidence shows that fetuin-A binds the β-subunit of the insulin receptor to attenuate insulin signaling, thereby contributing to insulin resistance in type 2 diabetes mellitus (T2DM). Fetuin-A also may, together with free fatty acids, induce apoptotic signals in the beta islets cells of the pancreas, reducing the secretion of insulin and further exacerbating T2DM.

Performance of clinical prediction rules for diagnosis of pleural tuberculosis in a high-incidence setting

OBJECTIVES

Diagnosis of pleural tuberculosis (PT) is still a challenge, particularly in resource-constrained settings. Alternative diagnostic tools are needed. We aimed at evaluating the utility of Clinical Prediction Rules (CPRs) for diagnosis of pleural tuberculosis in Peru.

METHODS

We identified CPRs for diagnosis of PT through a structured literature search. CPRs using high-complexity tests, as defined by the FDA, were excluded. We applied the identified CPRs to patients with pleural exudates attending two third-level hospitals in Lima, Peru, a setting with high incidence of tuberculosis. Besides pleural fluid analysis, patients underwent closed pleural biopsy for reaching a final diagnosis through combining microbiological and histopathological criteria. We evaluated the performance of the CPRs against this composite reference standard using classic indicators of diagnostic test validity.

RESULTS

We found 15 eligible CPRs, of which 12 could be validated. Most included ADA, age, lymphocyte proportion and protein in pleural fluid as predictive findings. A total of 259 patients were included for their validation, of which 176 (67%) had PT and 50 (19%) malignant pleural effusion. The overall accuracy of the CPRs varied from 41% to 86%. Two had a positive likelihood ratio (LR) above 10, but none a negative LR below 0.1. ADA alone at a cut-off of ≥40 IU attained 87% diagnostic accuracy and had a positive LR of 6.6 and a negative LR of 0.2.

CONCLUSION

Many CPRs for PT are available. In addition to ADA alone, none of them contributes significantly to diagnosis of PT.

Proteome profiling reveals novel biomarkers to identify complicated parapneumonic effusions

Patients with pneumonia and parapneumonic effusion (PPE) have elevated mortality and a poor prognosis. The aim of this study was to discover novel biomarkers to help distinguish between uncomplicated PPE (UPPE) and complicated PPE (CPPE). Using an iTRAQ-based quantitative proteomics, we identified 766 proteins in pleural effusions from PPE patients. In total, 45 of these proteins were quantified as upregulated proteins in CPPE. Four novel upregulated candidates (BPI, NGAL, AZU1, and calprotectin) were selected and further verified using enzyme-linked immunosorbent assays (ELISAs) on 220 patients with pleural effusions due to different causes. The pleural fluid levels of BPI, NGAL, AZU1, and calprotectin were significantly elevated in patients with CPPE. Among these four biomarkers, BPI had the best diagnostic value for CPPE, with an AUC value of 0.966, a sensitivity of 97%, and a specificity of 91.4%. A logistic regression analysis demonstrated a strong association between BPI levels > 10 ng/ml and CPPE (odds ratio = 341.3). Furthermore, the combination of pleural fluid BPI levels with LDH levels improved the sensitivity and specificity to 100% and 91.4%, respectively. Thus, our findings provided a comprehensive effusion proteome data set for PPE biomarker discovery and revealed novel biomarkers for the diagnosis of CPPE.

The Exploration of Peptide Biomarkers in Malignant Pleural Effusion of Lung Cancer Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Background. Diagnoses of malignant pleural effusion (MPE) are a crucial problem in clinics. In our study, we compared the peptide profiles of MPE and tuberculosis pleural effusion (TPE) to investigate the value of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in diagnosis of MPE. Material and Methods. The 46 MPE and 32 TPE were randomly assigned to training set and validation set. Peptides were isolated by weak cation exchange magnetic beads and peaks in the m/z range of 800–10000 Da were analyzed. Comparing the peptide profile between 30 MPE and 22 TPE samples in training set by ClinProTools software, we screened the specific biomarkers and established a MALDI-TOF-MS classification of MPE. Finally, the other 16 MPE and 10 TPE were included to verify the model. We additionally determined carcinoembryonic antigen (CEA) in MPE and TPE samples using electrochemiluminescent immunoassay method. Results. Five peptide peaks (917.37 Da, 4469.39 Da, 1466.5 Da, 4585.21 Da, and 3216.87 Da) were selected to separate MPE and TPE by MALDI-TOF-MS. The sensitivity, specificity, and accuracy of the classification were 93.75%, 100%, and 96.15%, respectively, after blinded test. The sensitivity of CEA was significantly lower than MALDI-TOF-MS classification (P = 0.035). Conclusions. The results indicate MALDI-TOF-MS is a potential method for diagnosing MPE.

A Multiplexed Cytokeratin Analysis Using Targeted Mass Spectrometry Reveals Specific Profiles in Cancer-Related Pleural Effusions

Pleural effusion (PE), excess fluid in the pleural space, is often observed in lung cancer patients and also forms due to many benign ailments. Classifying it quickly is critical, but this remains an analytical challenge often lengthening the diagnosis process or exposing patients to unnecessary risky invasive procedures. We tested the analysis of PE using a multiplexed cytokeratin (CK) panel with targeted mass spectrometry–based quantitation for its rapid classification. CK markers are often assessed in pathological examinations for cancer diagnosis and guiding treatment course. We developed methods to simultaneously quantify 33 CKs in PE using peptide standards for increased analytical specificity and a simple CK enrichment method to detect their low amounts. Analyzing 121 PEs associated with a variety of lung cancers and noncancerous causes, we show that abundance levels of 10 CKs can be related to PE etiology. CK-6, CK-7, CK-8, CK-18, and CK-19 were found at significantly higher levels in cancer-related PEs. Additionally, elevated levels of vimentin and actin differentiated PEs associated with bacterial infections. A classifier algorithm effectively grouped PEs into cancer-related or benign PEs with 81% sensitivity and 79% specificity. A set of undiagnosed PEs showed that our method has potential to shorten PE diagnosis time. For the first time, we show that a cancer-relevant panel of simple-epithelial CK markers currently used in clinical assessment can also be quantitated in PEs. Additionally, while requiring less invasive sampling, our methodology demonstrated a significant ability to identify cancer-related PEs in clinical samples and thus could improve patient care in the future.

Pre-analytical issues in effusion cytology

Effusions or body cavity fluids are amongst the most commonly submitted samples to the cytology laboratory. Knowledge of proper collection, storage, preservation and processing techniques is essential to ensure proper handling and successful analysis of the sample. This article describes how the effusions should be collected and proper conditions for submission. The different processing techniques to extract the cellular material and prepare slides satisfactory for microscopic evaluation are described such as direct smears, cytospins, liquid based preparations and cell blocks. The article further elaborates on handling the specimens for additional ancillary testing such as immunostaining and molecular tests, including predictive ones, as well as future research approaches.

Proteomic study of benign and malignant pleural effusion

BACKGROUND

Lung adenocarcinoma can easily cause malignant pleural effusion which was difficult to discriminate from benign pleural effusion. Now there was no biomarker with high sensitivity and specificity for the malignant pleural effusion.

PURPOSE

This study used proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model.

METHODS

We chose the weak cationic-exchanger magnetic bead (WCX-MB) to purify peptides in the pleural effusion, used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to obtain peptide expression profiles from the benign and malignant pleural effusion samples, established and validated the diagnostic model through a genetic algorithm (GA) and finally identified the most promising protein biomarker.

RESULTS

A GA diagnostic model was established with spectra of 3930.9 and 2942.8 m/z in the training set including 25 malignant pleural effusion and 26 benign pleural effusion samples, yielding both 100 % sensitivity and 100 % specificity. The accuracy of diagnostic prediction was validated in the independent testing set with 58 malignant pleural effusion and 34 benign pleural effusion samples. Blind evaluation was as follows: the sensitivity was 89.6 %, specificity 88.2 %, PPV 92.8 %, NPV 83.3 % and accuracy 89.1 % in the independent testing set. The most promising peptide biomarker was identified successfully: Isoform 1 of caspase recruitment domain-containing protein 9 (CARD9), with 3930.9 m/z, was decreased in the malignant pleural effusion.

CONCLUSIONS

This model is suitable to discriminate benign and malignant pleural effusion and CARD9 can be used as a new peptide biomarker.

Diagnostic marker signature for esophageal cancer from transcriptome analysis

Esophageal cancer is often diagnosed at an advanced stage. Diagnostic markers are needed for achieving a cure in esophageal cancer detecting and treating tumor cells earlier. In patients with locally advanced squamous cell carcinoma of the esophagus (ESCC), we profiled the gene expression of ESCC compared to corresponding normal biopsies for diagnostic markers by genome microarrays. Profiling of gene expression identified 4844 genes differentially expressed, 2122 upregulated and 2722 downregulated in ESCC. Twenty-three overexpressed candidates with best scores from significance analysis have been selected for further analysis by TaqMan low-density array-technique using a validation cohort of 40 patients. The verification rate was 100 % for ESCC. Twenty-two markers were additionally overexpressed in adenocarcinoma of the esophagus (EAC). The markers significantly overexpressed already in earlier tumor stages (pT1-2) of both histological subtypes (n = 19) have been clustered in a "diagnostic signature": PLA2G7, PRAME, MMP1, MMP3, MMP12, LIlRB2, TREM2, CHST2, IGFBP2, IGFBP7, KCNJ8, EMILIN2, CTHRC1, EMR2, WDR72, LPCAT1, COL4A2, CCL4, and SNX10. The marker signature will be translated to clinical practice to prove its diagnostic impact. This diagnostic signature may contribute to the earlier detection of tumor cells, with the aim to complement clinical techniques resulting in the development of better detection of concepts of esophageal cancer for earlier therapy and more favorite prognosis.

Proteoglycan 4 is a diagnostic biomarker for COPD

Introduction

The measurement of C-reactive protein (CRP) to confirm the stability of COPD has been reported. However, CRP is a systemic inflammatory biomarker that is related to many other diseases.

Objective

The objective of this study is to discover a diagnostic biomarker for COPD.

Methods

Sixty-one subjects with COPD and 15 healthy controls (10 healthy non-smokers and 5 smokers) were recruited for a 1-year follow-up study. Data regarding the 1-year acute exacerbation frequency and changes in lung function were collected. CRP and the identified biomarkers were assessed in the validation COPD cohort patients and healthy subjects. Receiver operating characteristic values of CRP and the identified biomarkers were determined. A validation COPD cohort was used to reexamine the identified biomarker. Correlation of the biomarker with 1-year lung function decline was determined.

Results

Proteoglycan 4 (PRG4) was identified as a biomarker in COPD. The serum concentrations of PRG4 in COPD Global initiative for chronic Obstructive Lung Disease (GOLD) stages 1+2 and 3+4 were 10.29 ng/mL and 13.20 ng/mL, respectively; 4.99 ng/mL for healthy controls (P<0.05); and 4.49 ng/mL for healthy smokers (P<0.05). PRG4 was more sensitive and specific than CRP for confirming COPD severity and acute exacerbation frequency. There was no correlation between CRP and PRG4 levels, and PRG4 was negatively correlated with the 1-year change in predicted forced vital capacity percent (R²=0.91, P=0.013).

Conclusion

PRG4 may be a biomarker for identification of severity in COPD. It was related to the 1-year forced vital capacity decline in COPD patients.

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.

A functional proteomics approach to the comprehension of sarcoidosis

Pulmonary sarcoidosis (Sar) is an idiopathic disease histologically typified by non-caseating epitheliod cell sarcoid granulomas. A cohort of 37 Sar patients with chronic persistent pulmonary disease was described in this study. BAL protein profiles from 9 of these Sar patients were compared with those from 8 smoker (SC) and 10 no-smoker controls (NSC) by proteomic approach. Principal Component Analysis was performed to clusterize the samples in the corresponding conditions highlighting a differential pattern profiles primarily in Sar than SC. Spot identification reveals thirty-four unique proteins involved in lipid, mineral, and vitamin Dmetabolism, and immuneregulation of macrophage function. Enrichment analysis has been elaborated by MetaCore, revealing 14-3-3ε, α1-antitrypsin, GSTP1, and ApoA1 as "central hubs". Process Network as well as Pathway Maps underline proteins involved in immune response and inflammation induced by complement system, innate inflammatory response and IL-6signalling. Disease Biomarker Network highlights Tuberculosis and COPD as pathologies that share biomarkers with sarcoidosis. In conclusion, Sar protein expression profile seems more similar to that of NSC than SC, conversely to other ILDs. Moreover, Disease Biomarker Network revealed several common features between Sar and TB, exhorting to orientate the future proteomics investigations also in comparative BALF analysis of Sar and TB.

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons.

Inter-alpha-trypsin inhibitor heavy chain 4: a novel biomarker for environmental exposure to particulate air pollution in patients with chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease that is correlated with environmental stress. Particulate matter ≤10 μm (PM₁₀) is considered to be a risk factor for COPD development; however, the effects of PM₁₀ on the protein levels in COPD remain unclear. Fifty subjects with COPD and 15 healthy controls were recruited. Gene ontology analysis of differentially expressed proteins identified immune system process and binding as the most important biological process and molecular function, respectively, in the responses of PM₁₀-exposed patients with COPD. Biomarkers for PM₁₀ in COPD were identified and compared with the same in healthy controls and included proteoglycan 4 (PRG4), inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4), and apolipoprotein F (APOF). PRG4 and ITIH4 were associated with a past 3-year PM₁₀ exposure level. The receiver operating characteristic curve analysis showed that ITIH4 is a sensitive and specific biomarker for PM₁₀ exposure (area under the curve [AUC] =0.690, P=0.015) compared with PRG4 (AUC =0.636, P=0.083), APOF (AUC =0.523, P=0.766), 8-isoprostane (AUC =0.563, P=0.405), and C-reactive protein (CRP; AUC =0.634, P=0.086). ITIH4 levels were correlated with CRP (r=0.353, P=0.005), suggesting that ITIH4 may be involved in an inflammatory mechanism. In summary, serum ITIH4 may be a PM₁₀-specific biomarker in COPD and may be related to inflammation.

Microemulsion-based synergistic dual-drug codelivery system for enhanced apoptosis of tumor cells

A microemulsion-based synergistic dual-drug codelivery system was developed for enhanced cell apoptosis by transporting coix seed oil and etoposide into A549 (human lung carcinoma) cells simultaneously. Results obtained by dynamic light scattering showed that an etoposide (VP16)-loaded coix seed oil microemulsion (EC-ME) delivery system had a small size around 35 nm, a narrow polydispersity index, and a slightly negative surface charge. The encapsulating efficiency and total drug loading rate were 97.01% and 45.48%, respectively, by high-performance liquid chromatography. The release profiles at various pH values showed an obvious pH-responsive difference, with the accumulated amount of VP16 released at pH 4.5 (and pH 5.5) being 2.7-fold higher relative to that at pH 7.4. Morphologic alteration (particle swelling) associated with a mildly acidic pH environment was found on transmission electron microscopy. In the cell study, the EC-ME system showed a significantly greater antiproliferative effect toward A549 cells in comparison with free VP16 and the mixture of VP16 and coix seed oil. The half-maximal inhibitory concentration of the EC-ME system was 3.9-fold and 10.4-fold lower relative to that of free VP16 and a mixture of VP16 and coix seed oil, respectively. Moreover, fluorescein isothiocyanate and VP16 (the green fluorescent probe and entrapped drug, respectively) were efficiently internalized into the cells by means of coix seed oil microemulsion through intuitive observation and quantitative measurement. Importantly, an EC-ME system containing 20 μg/mL of VP16 showed a 3.3-fold and 3.5-fold improvement in induction of cell apoptosis compared with the VP-16-loaded microemulsion and free VP16, respectively. The EC-ME combination strategy holds promise as an efficient drug delivery system for induction of apoptosis and treatment of lung cancer.

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.

IGF-Binding Protein 2 - Oncogene or Tumor Suppressor?

The role of insulin-like growth factor binding protein 2 (IGFBP2) in cancer is unclear. In general, IGFBP2 is considered to be oncogenic and its expression is often observed to be elevated in cancer. However, there are a number of conflicting reports in vitro and in vivo where IGFBP2 acts in a tumor suppressor manner. In this mini-review, we discuss the factors influencing the variation in IGFBP2 expression in cancer and our interpretation of these findings.

Liquid biopsies in lung cancer: the new ambrosia of researchers

In the last decades the approach to cancer patient management has been deeply revolutionized. We are moving from a "one-fits-all" strategy to the "personalized medicine" based on the molecular characterization of the tumor. In this new era it is becoming more and more clear that the monitoring of the disease is fundamental for the success of the treatment, thus there is the need of new biomarker discovery. More precisely in the last years the scientific community has started to use the term "liquid biopsy". A liquid biopsy is a liquid biomarker that can be easily isolated from many body fluids (blood, saliva, urine, ascites, pleural effusion, etc.) and, as well as a tissue biopsy, a representative of the tissue from which it is spread. In this review we will focus our attention on circulating tumor cells, circulating tumor DNA, exosomes and secretomes with the aim to underlie their usefulness and potential application in a clinical setting for lung cancer patient management.

Extracellular vesicles shed from gefitinib-resistant nonsmall cell lung cancer regulate the tumor microenvironment

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs), including gefitinib, are the first-line treatment of choice for nonsmall cell lung cancer patients who harbor activating EGFR mutations, however, acquired resistance to EGFR-TKIs is inevitable. The main objective of this study was to identify informative protein signatures of extracellular vesicles (EV) derived from gefitinib-resistant nonsmall cell lung cancer cells using proteomics analysis. Nano-LC-MS/MS analysis identified with high confidence (false discovery rate < 0.05, fold change ≥2) 664 EV proteins enriched in PC9R cells, which are resistant to gefitinib due to EGFR T790M mutation. Computational analyses suggested components of several signal transduction mechanisms including the AKT (also PKB, protein kinase B)/mTOR (mechanistic target of rapamycin) pathway are overrepresented in EV from PC9R cells. Treatment of recipient cells with EV harvested from PC9R cells increased phosphorylation of signaling molecules, and enhanced proliferation, invasion, and drug resistance to gefitinib-induced apoptosis. Dose- and time-dependent pharmaceutical inhibition of AKT/mTOR pathway overcame drug resistance of PC9R cells and those of H1975 exhibiting EGFR T790M mutation. Our findings provide new insight into an oncogenic EV protein signature regulating tumor microenvironment, and will aid in the development of novel diagnostic strategies for prediction and assessment of gefitinib resistance.

Is insulin-like growth factor binding protein 2 associated with metastasis in lung cancer?

Insulin-like growth factor binding protein 2 (IGFBP2) is involved in the progression of many epithelial cancers. However, its role in non-small cell lung cancer (NSCLC), another type of epithelial cancer, remains unclear. We detected IGFBP2 expression using immunohistochemistry in surgically resected tumors from 110 NSCLC patients, 37 of which had metastases. The positive rate of IGFBP2 expression was compared between the metastatic and the non-metastatic group, and correlations of IGFBP2 expression with metastasis and overall survival were analyzed. We also investigated the expression of IGFBP2 in microvesicles (MVs) collected from primary lung cancer cell cultures, and in different locations of newly resected NSCLC tumors, using immunoblotting. The overall positive rate of IGFBP2 expression in lung cancer was 51.8 % and it was significantly higher in the metastatic group than in the non-metastatic group (70.3 and 42.5 % respectively, p < 0.01). And the higher the lymph node stage, the higher the positive rate. Cytoplasmic expression was predominant in the majority of the tumors. Based on multivariate regression analysis, IGFBP2 was correlated with metastasis and poor overall survival (Hazard ratio: 3.56 and 3.23 respectively). IGFBP2 was detectable in the MVs collected from IGFBP2 positive cell lines, and its expression was most abundant in the marginal region of the newly resected tumors. IGFBP2 is associated with metastasis and poor survival of lung cancer. Its presence in MVs and high abundance in the marginal region of tumors suggest that its association with metastasis may be related to tumor microenviroment remodeling in NSCLC.

Identification and characterization of proteins isolated from microvesicles derived from human lung cancer pleural effusions

Microvesicles (MVs, also known as exosomes, ectosomes, microparticles) are released by various cancer cells, including lung, colorectal, and prostate carcinoma cells. MVs released from tumor cells and other sources accumulate in the circulation and in pleural effusion. Although recent studies have shown that MVs play multiple roles in tumor progression, the potential pathological roles of MV in pleural effusion, and their protein composition, are still unknown. In this study, we report the first global proteomic analysis of highly purified MVs derived from human nonsmall cell lung cancer (NSCLC) pleural effusion. Using nano-LC-MS/MS following 1D SDS-PAGE separation, we identified a total of 912 MV proteins with high confidence. Three independent experiments on three patients showed that MV proteins from PE were distinct from MV obtained from other malignancies. Bioinformatics analyses of the MS data identified pathologically relevant proteins and potential diagnostic makers for NSCLC, including lung-enriched surface antigens and proteins related to epidermal growth factor receptor signaling. These findings provide new insight into the diverse functions of MVs in cancer progression and will aid in the development of novel diagnostic tools for NSCLC.

Glycoproteomics using fluid-based specimens in the discovery of lung cancer protein biomarkers: promise and challenge

Lung cancer is the leading cancer in the United States and worldwide. In spite of the rapid progression in personalized treatments, the overall survival rate of lung cancer patients is still suboptimal. Over the past decade, tremendous efforts have been focused on the discovery of protein biomarkers to facilitate the early detection and monitoring of lung cancer progression during treatment. In addition to tumor tissues and cancer cell lines, a variety of biological material has been studied. Particularly in recent years, studies using fluid-based specimen or so-called "fluid-biopsy" specimens have progressed rapidly. Fluid specimens are relatively easier to collect than tumor tissue, and they can be repeatedly sampled during the disease progression. Glycoproteins are the major content of fluid specimens and have long been recognized to play fundamental roles in many physiological and pathological processes. In this review, we focus the discussion on recent advances of glycoproteomics, particularly in the identification of potential glyco protein biomarkers using fluid-based specimens in lung cancer. The purpose of this review is to summarize current strategies, achievements, and perspectives in the field. This insight will highlight the discovery of tumor-associated glycoprotein biomarkers in lung cancer and their potential clinical applications.

Proteomic analysis of osteoarthritic chondrocyte reveals the hyaluronic acid-regulated proteins involved in chondroprotective effect under oxidative stress

Osteoarthritis (OA), the most common type of arthritis, is a degenerative joint disease. Oxidative stress is well known to play important roles in cartilage degradation and pathogenesis of OA. The intra-articular injection of hyaluronic acid (IAHA) is accepted as an effective clinical therapy for OA, but we do not yet fully understand the mechanisms underlying the effects of HA on OA chondrocytes under oxidative stress. Here, we show for the first time that IAHA significantly reduces the synovial fluid levels of hydrogen peroxide (H2O2) and superoxide (O2(-)) in patients with knee OA. We also demonstrate that HA suppresses H2O2-induced cell death in human OA chondrocytes. Proteomic approaches (2-DE combined with mass spectrometry) allowed us to identify 13 protein spots corresponding to 12 non-redundant proteins as HA-regulated proteins in OA chondrocytes under oxidative stress. The expression levels of three putative HA-regulated proteins (TALDO, ANXA1 and EF2) in control, H2O2-, HA- and HA/H2O2-treated OA chondrocytes were verified by Western blotting and the results indeed support the notion that HA acts in anti-oxidation, anti-apoptosis, and the promotion of cell survival. Our results collectively demonstrate the utility of proteomic approaches and provide new insights into the chondroprotective effects of HA on OA.

BIOLOGICAL SIGNIFICANCE

In the present study, we show for the first time that IAHA reduces the levels of H2O2 and O2(-) in synovial fluids from OA patients. We used primary cultured human OA chondrocytes as a model, treated cells with H2O2 to partly mimic their physiological conditions under oxidative stress, and examined the protection effects of HA. The proteomic approach allowed us to identify candidate proteins regulated by H2O2 and/or HA in OA chondrocytes. We found that proteins functioning in stress responses, apoptosis and protein synthesis were consistently regulated by HA in chondrocytes under oxidative stress. These novel results contribute to our understanding of the molecular mechanisms underlying HA-mediated chondroprotection.

Comparative proteomics of inhaled silver nanoparticles in healthy and allergen provoked mice

Background

Silver nanoparticles (AgNPs) have been associated with the exacerbation of asthma; however, the immunological basis for the adjuvant effects of AgNPs is not well understood.

Objective

The aim of the study reported here was to investigate the allergic effects of AgNP inhalation using proteomic approaches.

Methods

Allergen provoked mice were exposed to 33 nm AgNPs at 3.3 mg/m³. Following this, bronchoalveolar lavage fluid (BALF) and plasma were collected to determine protein profiles.

Results

In total, 106 and 79 AgNP-unique proteins were identified in the BALF of control and allergic mice, respectively. Additionally, 40 and 26 AgNP-unique proteins were found in the plasma of control and allergic mice, respectively. The BALF and plasma protein profiles suggested that metabolic, cellular, and immune system processes were associated with pulmonary exposure to AgNPs. In addition, we observed 18 proteins associated with systemic lupus erythematosus that were commonly expressed in both control and allergic mice after AgNP exposure. Significant allergy responses were observed after AgNP exposure in control and allergic mice, as determined by ovalbumin-specific immunoglobulin E.

Conclusion

Inhaled AgNPs may regulate immune responses in the lungs of both control and allergic mice. Our results suggest that immunology is a vital response to AgNPs.

The role of vascular endothelial growth factor in the pathogenesis, diagnosis and treatment of malignant pleural effusion

Malignant pleural effusions (MPEs) are a significant source of cancer-related morbidity. Over 150,000 patients in the United States suffer from breathlessness and diminished quality of life due to MPE each year. Current management strategies are of mostly palliative value and focus on symptom control; they do not address the pathobiology of the effusion, nor do they improve survival. Further elucidation of the pathophysiological mechanisms, coupled with the development of novel treatments such as intrapleural chemotherapeutics targeting this process, has the potential to greatly improve the efficacy of our current management options. Vascular endothelial growth factor-A (VEGF-A) has been implicated as a critical cytokine in the formation of malignant pleural effusions. Elevated levels of VEGF produced by tumor cells, mesothelial cells, and infiltrating immune cells result in increased vascular permeability, cancer cell transmigration, and angiogenesis. Therefore antiangiogenic therapies such as Bevacizumab, a monoclonal antibody targeting VEGF-A, may have a potential role in the management of malignant pleural effusions. Herein we review the pathogenesis and potential treatment strategies of malignant pleural effusions, with a focus on angiogenesis and antiangiogenic therapeutics.

Sieving through the cancer secretome

Cancer is among the most prevalent and serious health problems worldwide. Therefore, there is an urgent need for novel cancer biomarkers with high sensitivity and specificity for early detection and management of the disease. The cancer secretome, encompassing all the proteins that are secreted by cancer cells, is a promising source of biomarkers as the secreted proteins are most likely to enter the blood circulation. Moreover, since secreted proteins are responsible for signaling and communication with the tumor microenvironment, studying the cancer secretome would further the understanding of cancer biology. Latest developments in proteomics technologies have significantly advanced the study of the cancer secretome. In this review, we will present an overview of the secretome sample preparation process and summarize the data from recent secretome studies of six common cancers with high mortality (breast, colorectal, gastric, liver, lung and prostate cancers). In particular, we will focus on the various platforms that were employed and discuss the clinical applicability of the key findings in these studies. This article is part of a Special Issue entitled: An Updated Secretome.

The cancer secretome, current status and opportunities in the lung, breast and colorectal cancer context

Despite major improvements on the knowledge and clinical management, cancer is still a deadly disease. Novel biomarkers for better cancer detection, diagnosis and treatment prediction are urgently needed. Proteins secreted, shed or leaking from the cancer cell, collectively termed the cancer secretome, are promising biomarkers since they might be detectable in blood or other biofluids. Furthermore, the cancer secretome in part represents the tumor microenvironment that plays a key role in tumor promoting processes such as angiogenesis and invasion. The cancer secretome, sampled as conditioned medium from cell lines, tumor/tissue interstitial fluid or tumor proximal body fluids, can be studied comprehensively by nanoLC-MS/MS-based approaches. Here, we outline the importance of current cancer secretome research and describe the mass spectrometry-based analysis of the secretome. Further, we provide an overview of cancer secretome research with a focus on the three most common cancer types: lung, breast and colorectal cancer. We conclude that the cancer secretome research field is a young, but rapidly evolving research field. Up to now, the focus has mainly been on the discovery of novel promising secreted cancer biomarker proteins. An interesting finding that merits attention is that in cancer unconventional secretion, e.g. via vesicles, seems increased. Refinement of current approaches and methods and progress in clinical validation of the current findings are vital in order to move towards applications in cancer management. This article is part of a Special Issue entitled: An Updated Secretome.

Secretome analysis using a hollow fiber culture system for cancer biomarker discovery

Secreted proteins, collectively referred to as the secretome, were suggested as valuable biomarkers in disease diagnosis and prognosis. However, some secreted proteins from cell cultures are difficult to detect because of their intrinsically low abundance; they are frequently masked by the released proteins from lysed cells and the substantial amounts of serum proteins used in culture medium. The hollow fiber culture (HFC) system is a commercially available system composed of small fibers sealed in a cartridge shell; cells grow on the outside of the fiber. Recently, because this system can help cells grow at a high density, it has been developed and applied in a novel analytical platform for cell secretome collection in cancer biomarker discovery. This article focuses on the advantages of the HFC system, including the effectiveness of the system for collection of secretomes, and reviews the process of cell secretome collection by the HFC system and proteomic approaches to discover cancer biomarkers. The HFC system not only provides a high-density three-dimensional (3D) cell culture system to mimic tumor growth conditions in vivo but can also accommodate numerous cells in a small volume, allowing secreted proteins to be accumulated and concentrated. In addition, cell lysis rates can be greatly reduced, decreasing the amount of contamination by abundant cytosolic proteins from lysed cells. Therefore, the HFC system is useful for preparing a wide range of proteins from cell secretomes and provides an effective method for collecting higher amounts of secreted proteins from cancer cells. This article is part of a Special Issue entitled: An Updated Secretome.

Global secretome analysis identifies novel mediators of bone metastasis

Bone is the one of the most common sites of distant metastasis of solid tumors. Secreted proteins are known to influence pathological interactions between metastatic cancer cells and the bone stroma. To comprehensively profile secreted proteins associated with bone metastasis, we used quantitative and non-quantitative mass spectrometry to globally analyze the secretomes of nine cell lines of varying bone metastatic ability from multiple species and cancer types. By comparing the secretomes of parental cells and their bone metastatic derivatives, we identified the secreted proteins that were uniquely associated with bone metastasis in these cell lines. We then incorporated bioinformatic analyses of large clinical metastasis datasets to obtain a list of candidate novel bone metastasis proteins of several functional classes that were strongly associated with both clinical and experimental bone metastasis. Functional validation of selected proteins indicated that in vivo bone metastasis can be promoted by high expression of (1) the salivary cystatins CST1, CST2, and CST4; (2) the plasminogen activators PLAT and PLAU; or (3) the collagen functionality proteins PLOD2 and COL6A1. Overall, our study has uncovered several new secreted mediators of bone metastasis and therefore demonstrated that secretome analysis is a powerful method for identification of novel biomarkers and candidate therapeutic targets.