Auxiliary diagnostic value of tumor biomarkers in pleural fluid for lung cancer-associated malignant pleural effusion.
ABSTRACT: BACKGROUND:Pleural effusion (PE) can be divided into benign pleural effusion (BPE) and malignant pleural effusion (MPE). There is no consensus on the identification of lung cancer-associated MPE using the optimal cut-off levels from five common tumor biomarkers (CEA, CYFRA 21-1, CA125, SCC-Ag, and NSE). Therefore, we aimed to find indicators for the auxiliary diagnosis of lung cancer-associated MPE by analyzing and then validating the optimal threshold levels of these biomarkers in pleural fluid (PF) and serum, as well as the PF/serum ratio. PATIENTS AND METHOD:The study has two sets of patients, i.e. the training set and the test set. In the training set, 348 patients with PE, between January 1, 2016 and December 31, 2017, were divided into BPE and MPE based on the cytological diagnosis. Subsequently, the optimal cut-off levels of tumor biomarkers were analyzed. In the test set, the diagnostic compliance rate was verified with 271 patients with PE from January 1, 2018 to July 31, 2019 to evaluate the auxiliary diagnostic value of the aforementioned indicators. RESULT:In the training set, PF CEA at the cut-off value of 5.23 ng/ml was the most effective indicator for MPE compared with other tumor biomarkers (all p?
Project description:BACKGROUND:This study aimed to establish and validate a novel scoring system based on a nomogram for the differential diagnosis of malignant pleural effusion (MPE) and benign pleural effusion (BPE). METHODS:Patients with PE and confirmed aetiology who underwent diagnostic thoracentesis were included in this study. One retrospective set (N = 1261) was used to develop and internally validate the predictive model. The clinical, radiological and laboratory features were collected and subjected to logistic regression analyses. The primary predictive model was displayed as a nomogram and then modified into a novel scoring system, which was externally validated in an independent set (N = 172). FINDINGS:The novel scoring system was composed of fever (3 points), erythrocyte sedimentation rate (4 points), effusion adenosine deaminase (7 points), serum carcinoembryonic antigen (CEA) (4 points), effusion CEA (10 points) and effusion/serum CEA (8 points). With a cutoff value of 15 points, the area under the curve, specificity and sensitivity for identifying MPE were 0.913, 89.10%, and 82.63%, respectively, in the training set, 0.922, 93.48%, 81.51%, respectively, in the internal validation set and 0.912, 87.61%, 81.36%, respectively, in the external validation set. Moreover, this scoring system was exclusively applied to distinguish lung cancer with PE from tuberculous pleurisy and showed a favourable diagnostic performance in the training and validation sets. INTERPRETATION:This novel scoring system was developed from a retrospective study and externally validated in an independent set based on six easily accessible clinical variables, and it exhibited good diagnostic performance for identifying MPE. FUNDING:NFSC grants (no. 81572942, no. 81800094).
Project description:BACKGROUND:Pleural fluid homocysteine (HCY) can be useful for diagnosis of malignant pleural effusion (MPE). There are no published studies comparing the diagnostic accuracy of HCY with other tumour markers in pleural fluid for diagnosis of MPE. The aim was to compare the accuracy of HCY with that of carcinoembryonic antigen (CEA), cancer antigen (CA) 15.3, CA19.9 and CA125 in pleural fluid and to develop a probabilistic model using these biomarkers to differentiate benign (BPE) from MPE. METHODS:Patients with pleural effusion were randomly included. HCY, CEA, CA15.3, CEA19.9 and CA125 were quantified in pleural fluid. Patients were classified into two groups: MPE or BPE. By applying logistic regression analysis, a multivariate probabilistic model was developed using pleural fluid biomarkers. The diagnostic accuracy was determined by receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). RESULTS:Population of study comprised 133 patients (72 males and 61 females) aged between 1 and 96 years (median = 70 years), 81 BPE and 52 MPE. The logistic regression analysis included HCY (p<0.0001) and CEA (p = 0.0022) in the probabilistic model and excluded the other tumour markers. The probabilistic model was: HCY+CEA = Probability(%) = 100×(1+e-z)-1, where Z = 0.5471×[HCY]+0.3846×[CEA]-8.2671. The AUCs were 0.606, 0.703, 0.778, 0.800, 0.846 and 0.948 for CA125, CA19.9, CEA, CA15.3, HCY and HCY+CEA, respectively. CONCLUSIONS:Pleural fluid HCY has higher accuracy for diagnosis of MPE than CEA, CA15.3, CA19.9 and CA125. The combination of HCY and CEA concentrations in pleural fluid significantly improves the diagnostic accuracy of the test.
Project description:Discriminating between malignant pleural effusion (MPE) and benign pleural effusion (BPE) remains difficult. Thus, novel and efficient biomarkers are required for the diagnosis of pleural effusion (PE). The aim of this study was to validate calprotectin as a diagnostic biomarker of PE in clinical settings. A total of 425 patients were recruited, and the pleural fluid samples collected had BPE in 223 cases (53.7%) or MPE in 137 patients (33%). The samples were all analysed following the same previously validated clinical laboratory protocols and methodology. Calprotectin levels ranged from 772.48 to 3,163.8?ng/mL (median: 1,939?ng/mL) in MPE, and 3,216-24,000?ng/mL in BPE (median: 9,209?ng/mL; p?<?0.01), with an area under the curve of 0.848 [95% CI: 0.810-0.886]. For a cut-off value of ? 6,233.2?ng/mL, we found 96% sensitivity and 60% specificity, with a negative and positive predictive value, and negative and positive likelihood ratios of 96%, 57%, 0.06, and 2.4, respectively. Multivariate analysis showed that low calprotectin levels was a better discriminator of PE than any other variable [OR 28.76 (p?<?0.0001)]. Our results confirm that calprotectin is a new and useful diagnostic biomarker in patients with PE of uncertain aetiology which has potential applications in clinical practice because it may be a good complement to cytological methods.
Project description:BACKGROUND:Malignant pleural effusion (MPE) causes substantial symptomatic burden in advanced malignancy. Although pleural fluid cytology is a commonly accepted gold standard of diagnosis, its low diagnostic yield is a challenge for clinicians. The aim of this study was to determine whether pro-cathepsin D can serve as a novel biomarker to discriminate between MPE and benign pleural effusion (BPE). METHODS:This study included 81 consecutive patients with exudative pleural effusions who had underwent thoracentesis or pleural biopsy. Pleural fluid and serum were collected as a standard procedure for all individuals at the same time. The level of pro-cathepsin D was measured by the sandwich enzyme-linked immunosorbent assay method. RESULTS:Though there were no significant differences in plasma pro-cathepsin D between the two groups, the level of pleural fluid pro-cathepsin D was significantly higher in the MPE group than the BPE group (0.651 versus 0.590?pg/mL, P?=?0.034). The discriminative power of pleural fluid pro-cathepsin D for diagnosing MPE was moderate, with 81% sensitivity and 53% specificity at a pro-cathepsin D cut-off ?0.596?pg/mL (area under the curve: 0.656). Positive and negative predictive values for MPE were 38 and 89%, respectively, with pro-cathepsin D cut-off value (>?0.596?pg/mL). CONCLUSIONS:The level of pleural fluid pro-cathepsin D was found to be significantly higher in MPE than in BPE. Although results of this study could not support the sole use of pleural fluid pro-cathepsin D to diagnose MPE, pleural fluid pro-cathepsin D can be added to pre-existing diagnostic methods for ruling-in or ruling-out MPE.
Project description: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.
Project description:BACKGROUND:Malignant pleural effusion (MPE) and tuberculosis pleural effusion (TPE) are 2 kinds of common pleural diseases. Finding efficient and accurate biomarkers to distinguish the 2 is of benefit to basic and clinical research. In the present study, we carried out the first high-throughput autoantibody chip to screen the beneficial biomarker with samples of MPE and TPE and the corresponding serum. METHODS:We collected pleural effusion and serum of patients with MPE (n?=?10) and TPE (n?=?10) who had been in Beijing Chao-Yang hospital from June 2013 to August 2014. Using RayBio Human Protein Array-G2 to measure the concentration of 487 defined autoantibodies. RESULTS:Fold changes of Bcl-2-like protein 11 (BIM) autoantibody in MPE-serum/TPE-serum and MPE/TPE groups were 10 (P?=?.019) and 6 (P?=?.001); for decorin autoantibody, MPE-serum/TPE-serum ratio was 0.6 (P?=?.029), and MPE/TPE ratio was 0.3 (P?<?.001). CONCLUSION:BIM autoantibody is a promising MPE biomarker by high-throughput autoantibody analysis in MPE and TPE.
Project description:Background:Malignant pleural effusion (MPE) is a common medical problem caused by multiple malignancies, especially lung cancers, and always comes along with a poor outcome. Early detection and diagnosis are important for improving the prognosis in patients with MPE. Salivary microRNAs (miRNAs) may represent a relatively convenient way for diagnosing MPE. We investigated the characteristics of salivary miRNAs of MPE patients, benign pleural effusion (BPE) patients, patients with a malignant tumor but without pleural effusion (MT), and healthy controls (HCs). We believe that they may show potential as a non-invasive and convenient biomarker for diagnosing MPE. Methods:From January 1, 2019, to July 1, 2019, 57 MPE patients, 33 BPE patients, 50 MT patients, and 49 HCs were enrolled. To select candidate biomarkers, in the discovery phase, the salivary miRNA profiles were detected in three MPE patients and three HCs. Then, qPCR was used in the validation phase with 54 MPE patients, 33 BPE patients, 50 MT patients, and 46 HCs to assay the selected miRNAs. Results:hsa-miR-4484 and hsa-miR-3663-3p were identified as potential biomarkers to diagnose MPE patients, with areas under the curve (AUC) of 0.768 and 0.666, respectively. The diagnostic efficacy was higher when the combination of both miRNAs was used, with an AUC of 0.802. No correlation was found between the volume of MPE and the expression of salivary miRNAs. Conclusions:This study reports the characterization of salivary miRNAs collected from MPE patients. A combination of hsa-miR-4484 and hsa-miR-3663-3p showed potential discriminatory power for MPE detection, and it may be helpful for the early diagnosis of MPE, i.e., before the pleural effusion volume is too large.
Project description:BACKGROUND:Tuberculosis pleural effusion (TPE) and malignant pleural effusion (MPE) are very common clinical complications. Considering the totally different prognosis and clinical treatment of TPE and MPE, the accurate and non-invasive diagnosis are very critical for patients with pleural effusion to initiate efficient management and treatment. However, effective clinical biomarkers were rarely explored to distinguish benign from MPE. The purpose of this study is to identify potential miRNAs which can probably be used to differentiate malignant pleural effusion from TPE. RESULTS:A total of 23 significantly differentially expressed miRNAs were identified in MPE, with 18 up-expressed and 5 down-expressed. And the target genes of the miRNAs mainly involved in the biology process of nervous system, cancer, immune system and metabolic process etc. Three high confident target genes, AGO4, FGF9 and LEF1 can be regulated by miR-195-5p, miR-182-5p and miR-34a-5p respectively. And these genes participate in the canonical pathway of regulation of the Epithelial-Mesenchymal and the biological functions of apoptosis, growth of tumor and cell proliferation of tumor cell lines. Further, RT-PCR validation results based on 64 collected individuals showed that the expression levels of the three miRNAs were 2-5 times higher in MPE samples, which were consistent with the microarray results. In addition, ROC curve analysis demonstrated that the combination of the three miRNAs can achieve higher AUC of 0.93 (p-value<?0.0001) to differentiate MPE from TPE. CONCLUSIONS:The identified miR-195-5p, miR-182-5p and miR-34a-5p can become potential diagnostic biomarkers for MPE with further evidences.
Project description:Pleural effusion is a common respiratory disease worldwide; however, rapid and accurate diagnoses of tuberculosis pleural effusion (TPE) and malignancy pleural effusion (MPE) remain challenging. Although extracellular vesicles (EVs) have been confirmed as promising sources of disease biomarkers, little is known about the metabolite compositions of its subpopulations and their roles in the diagnosis of pleural effusion. Here, we performed metabolomics and lipidomics analysis to investigate the metabolite characteristics of two EV subpopulations derived from pleural effusion by differential ultracentrifugation, namely large EVs (lEVs, pelleted at 20,000 × g) and small EVs (sEVs, pelleted at 110,000 × g), and assessed their metabolite differences between tuberculosis and malignancy. A total of 579 metabolites, including amino acids, acylcarnitines, organic acids, steroids, amides and various lipid species, were detected. The results showed that the metabolic profiles of lEVs and sEVs overlapped with and difference from each other but significantly differed from those of pleural effusion. Additionally, different type of vesicles and pleural effusion showed unique metabolic enrichments. Furthermore, lEVs displayed more significant and larger metabolic alterations between the tuberculosis and malignancy groups, and their differential metabolites were more closely related to clinical parameters than those of sEV. Finally, a panel of four biomarker candidates, including phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3, in pleural lEVs was defined based on the comprehensive discovery and validation workflow. This panel showed high performance for distinguishing TPE and MPE, particularly in patients with delayed or missed diagnosis, such as the area under the receiver-operating characteristic curve (AUC) >0.95 in both sets. We conducted comprehensive metabolic profiling analysis of EVs, and further explored the metabolic reprogramming of tuberculosis and malignancy at the level of metabolites in lEVs and sEVs, providing insight into the mechanism of pleural effusion, and identifying novel biomarkers for diagnosing TPE and MPE.
Project description:The aim of this study was to explore the diagnostic value of IL-31 levels in the pleural fluid and plasma to differentially diagnose tuberculous and malignant pleural effusion. We enrolled 91 cases, including tuberculous pleural effusion (TPE, n = 50), malignant pleural effusion (MPE, n = 41), other cases including pneumonia with pleural fluid, pulmonary tuberculosis and healthy people as controls. Whole blood was stimulated with the M. tuberculosis-specific antigens and plasma was collected. The multiplex bead-based cytokine immunoassay was employed to measure the levels of various cytokines. IL-31 was found to be the most prominent cytokine (P < 0.0001), and with an optimal cut-off value of 67.5 pg/mL, the sensitivity and specificity for the diagnosis of TPE were 86% and 100%, respectively. Furthermore, the tuberculosis-specific IL-31 levels in the plasma of TPE patients were higher than that of MPE patients (P = 0.0002). At an optimal cut-off value of 23.9 pg/mL, the sensitivity and specificity for the diagnosis of TPE were 92.9% and 85.7%, respectively. Ultimately, the combination of pleural fluid with the plasma tuberculosis-specific IL-31 levels improved the sensitivity and specificity to 94.0% and 95.1%, respectively. Thus, we identified a novel biomarker for the diagnosis of TPE for clinical application.