Predicting Survival for Patients with Malignant Pleural Effusion: Development of the CONCH Prognostic Model

Pericardial Fluid Analysis in Diagnosis and Prognosis of Patients Who Underwent Pericardiocentesis

In this study, we aimed to examine the diagnostic yield of pericardial fluid biochemistry and cytology and their prognostic significance in patients with percutaneously drained pericardial effusions, with and without malignancy. This is a single-center, retrospective study of patients who underwent pericardiocentesis between 2010 and 2020. Data were extracted from electronic patient records, including procedural information, underlying diagnosis, and laboratory results. Patients were grouped into those with and without underlying malignancy. A Cox proportional hazards model was used to analyze the association of variables with mortality. The study included 179 patients; 50% had an underlying malignancy. There were no significant differences in pericardial fluid protein and lactate dehydrogenase between the 2 groups. Diagnostic yield from pericardial fluid analysis was greater in the malignant group (32% vs 11%, p = 0.002); 72% of newly diagnosed malignancies had positive fluid cytology. The 1-year survival was 86% and 33% in nonmalignant and malignant groups, respectively (p <0.001). Of 17 patients who died within the nonmalignant group, idiopathic effusions were the largest group (n = 6). In malignancy, lower pericardial fluid protein and higher serum C-reactive protein were associated with increased risk of mortality. In conclusion, pericardial fluid biochemistry has limited value in determining the etiology of pericardial effusions; fluid cytology is the most important diagnostic test. Mortality in malignant pericardial effusions may be associated with lower pericardial fluid protein levels and a higher serum C-reactive protein. Nonmalignant pericardial effusions do not have a benign prognosis and close follow-up is required.

Novel 3D organotypic co-culture model of pleura

Pleural mesothelial cells are the predominant cell type in the pleural cavity, but their role in the pathogenesis of pleural diseases needs to be further elucidated. 3D organotypic models are an encouraging approach for an in vivo understanding of molecular disease development. The aim of the present study was to develop a 3D organotypic model of the pleural mesothelium. Specimens of human pleura parietalis were obtained from patients undergoing surgery at the University Hospital Leipzig, Germany. 3D co-culture model of pleura was established from human pleural mesothelial cells and fibroblasts. The model was compared to human pleura tissue by phase-contrast and light microscopy, immunochemistry and -fluorescence as well as solute permeation test. Histological assessment of the 3D co-culture model displayed the presence of both cell types mimicking the morphology of the human pleura. Vimentin and Cytokeratin, PHD1 showed a similar expression pattern in pleural biopsies and 3D model. Expression of Ki-67 indicates the presence of proliferating cells. Tight junctional marker ZO-1 was found localized at contact zones between mesothelial cells. Each of these markers were expressed in both the 3D co-culture model and human biopsies. Permeability of 3D organotypic co-culture model of pleura was found to be higher for 70 kDa-Dextran and no significant difference was seen in the permeability for small dextran (4 kDa). In summary, the presented 3D organoid of pleura functions as a robust assay for pleural research serving as a precise reproduction of the in vivo morphology and microenvironment.

Survival analysis and development of a prognostic nomogram for patients with malignant mesothelioma in different anatomic sites

Background

Malignant mesothelioma (MMe) is a rare and fatal cancer with a poor prognosis. Our study aimed to compare the overall survival (OS) of MMe patients across various sites and develop a prognostic model to provide a foundation for individualized management of MMe patients.

Methods

From the Surveillance, Epidemiology, and End Results (SEER) database, 1,772 individuals with malignant mesothelioma (MMe) were identified. The X-tile software was used to identify the optimal cut-off point for continuous variables. The Kaplan–Meier method was employed to compare the survival of MMe across different sites. The Cox proportional hazards model was applied to identify the independent risk factors of overall survival (OS) and a nomogram was constructed.

Results

In the survival analysis, MMe originating from the reproductive organs and hollow organs showed a relatively better prognosis than those originating from soft tissue, solid organs, and pleura. Age, gender, location, histological type, grade of differentiation, extent of disease, lymph node status, lymph node ratio (LNR), and chemotherapy were all found to be independent risk variables for the prognosis of MMe patients (P&lt;0.05) in a multivariate Cox analysis and were included in the construction of nomogram. In the training and testing sets, the C-index of the nomogram was 0.701 and 0.665, respectively, and the area under the ROC curve (AUROC) of the 1-, 3-, and 5-year overall survival rate was 0.749, 0.797, 0.833 and 0.730, 0.800, 0.832, respectively. The calibration curve shows that the nomogram is well-calibrated.

Conclusions

This is the first research to examine the prognosis of MMe patients based on the location. However, previous studies often focused on malignant pleural mesothelioma or malignant peritoneal mesothelioma with high incidence. Furthermore, a nomograph with good prediction efficiency was established according to the variables that influence patient survival outcomes, which provides us with a reference for clinical decision-making.

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).

Total Protein-Chloride Ratio in Pleural Fluid Independently Predicts Overall Survival in Malignant Pleural Effusion at the First Diagnosis

Objective

Pre-treatment biomarkers to estimate overall survival (OS) for malignant pleural effusion (MPE) are unidentified, especially those in pleural fluid. We evaluated the relationship between OS and total protein–chloride ratio in malignant pleural effusion (PE TPClR).

Materials and Methods

A retrospective study was undertaken to identify patients from 2006 to 2018 who had pathologically or cytologically confirmed MPE and received no tumor-targeted therapy. We recorded the pre-treatment clinicopathologic characteristics and follow-up status. OS was estimated by the Kaplan–Meier method, and the association between variables and OS was evaluated by Cox proportional hazards models.

Results

We screened 214 patients who met the eligibility criteria. The optimal cutoff value for the PE TPClR was set at 0.53. The univariate analysis showed that there was a significant correlation between PE TPClR and OS (P < 0.001). The multivariate analysis between OS and the variables selected from the univariate analysis showed that the levels of neutrophil, alkaline phosphatase, neuron-specific enolase, platelets, albumin in peripheral blood, and white blood cells in pleural effusion were also independent predictors of OS.

Conclusion

In patients with MPE, pre-treatment PE TPClR independently predicts OS. Although further research is necessary to generalize our results, this information will help clinicians and patients to determine the most appropriate treatment for MPE patients.