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

The lungs are covered by parietal and visceral pleural membranes, including a small amount of fluid (10–20 ml) in the pleural cavity that helps the lungs expand and contract smoothly. Pleural effusions (PE)1, an accumulation of pleural fluid, contain proteins originating from the plasma filtrate and are released by inflammatory or epithelial cells. PE is triggered by a variety of etiologies, including malignancies and benign diseases such as pneumonia (PN), tuberculosis (TB), pulmonary embolism, heart failure, renal dysfunction, and autoimmune disease (1). Based on their biochemical characteristics, PEs are classified as transudative or exudative; determination of the PE type is a crucial step in the differential diagnosis and management of PEs. Transudative effusions, generally caused by systemic diseases, can be effectively distinguished from exudative PEs using the established modified Light's criteria (2, 3). However, further discrimination among different exudate types such as malignant and nonmalignant effusions (e.g. paramalignancies or acute and chronic inflammatory diseases) is sometimes diagnostically challenging because of similar biochemical and/or cellular profiles. For example, neutrophil-rich fluid is generally observed in patients with bacterial PN whereas lymphocytic effusions are generally observed in cancer or chronic inflammatory diseases such as TB (4). PEs caused by cancer are generally divided into two categories, malignant (MPE) and paramalignant (PMPE). MPEs result when cancer cells metastasize to the pleural cavity (stage IV), wherein exfoliated malignant cells are observed in pleural fluid by cytological examination or detected in percutaneous pleural biopsy, thoracoscopy, thoracotomy, or at autopsy (5). PMPE occurs in cancer patients with no evidence of tumor invasion in the pleural space and may be caused by airway obstruction with lung collapse, lymphatic obstruction, or the systemic effects of cancer treatment (5). A high percentage of MPEs (>75%) arise from lung, breast, and ovarian cancer or lymphoma/leukemia. Lung cancer is a major etiology underlying MPE (6); however, only ∼40–87% patients with MPE can be accurately diagnosed upon initial examination (7). Inaccurate diagnosis of MPE and PMPE underestimates or overestimates the disease stage and leads to inappropriate therapy. Thus, it is important to identify a specific and powerful biomarker to distinguish MPE from benign diseases and PMPE. Notably, tumor-proximal body fluids are promising sources for biomarker discovery because they represent a reservoir of in vivo tumor-secreted proteins without a large dynamic range or complexity of plasma or serum (8). Tumor-proximal fluids include PEs, nipple aspirate, stool, saliva, lavage, and ascites fluid. Previously, we utilized the powerful analytical capability of high-abundance protein depletion followed by one-dimensional SDS-PAGE combined with nano-LC-MS/MS (GeLC-MS/MS) for biomarker discovery to generate a comprehensive MPE proteome data set from 13 pooled nonsmall cell lung cancer (NSCLC) patients (9). Because a variety of pathological conditions can lead to exudative effusions, generating different PE proteomic profiles would accelerate discovery of potential PE biomarkers that can be used to discriminate between malignant and nonmalignant pulmonary disorders. The aim of this study is to establish differential PE proteomes from six types of exudative PEs, including three MPEs (from NSCLC, breast, and gastric cancers), one PMPE from NSCLC, and two benign diseases (TB and PN), using a label-free semiquantitative proteomics approach. Our results were verified by clinical validation of three potential biomarkers using an enzyme-linked immunosorbent assay (ELISA; Fig. 1). Fig. 1. Biomarker discovery strategy for identifying differentially expressed proteins from six pleural effusion (PE) types. The strategy comprised prefractionation by removal of high-abundance proteins, GeLC-MS/MS, comparative analysis of the six PE proteomes ...