Jeffrey C Thompson1, Ryan Fan2, Taylor Black2, Gordon H Yu3, Samantha L Savitch2, Austin Chien2, Stephanie S Yee2, Moen Sen2, Wei-Ting Hwang4, Sharyn I Katz5, Michael Feldman6, Anil Vachani7, Erica L Carpenter8. 1. Division of Pulmonary, Allergy and Critical Care Medicine, Thoracic Oncology Group, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States. Electronic address: jeffrey.thompson@uphs.upenn.edu. 2. Division of Hematology-Oncology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States. 3. Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine Philadelphia, PA, United States. 4. Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, United States; Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States. 5. Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States. 6. Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine Philadelphia, PA, United States; Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States. 7. Division of Pulmonary, Allergy and Critical Care Medicine, Thoracic Oncology Group, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States. 8. Division of Hematology-Oncology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.
Abstract
OBJECTIVES: A malignant pleural effusion (MPE) is a common complication in non-small cell lung cancer (NSCLC) with important staging and prognostic information. Patients with MPEs are often candidates for advanced therapies, however, the current gold standard, cytological analysis of pleural fluid samples, has limited sensitivity. We aimed to demonstrate the feasibility of non-invasive enumeration and immunophenotyping of EpCAM-positive cells in pleural fluid samples for the diagnosis of a MPE in NSCLC patients. MATERIALS AND METHODS: Pleural fluid specimens were prospectively collected from patients with NSCLC and the CellSearch® technology was utilized for the enumeration of pleural EpCAM-positive cells (PECs) and determination of PD-L1 expression on PECs from pleural fluid samples. The diagnostic performance of the enumeration of single PECs and PEC clusters was assessed using receiver operating characteristic (ROC) curves. The Kaplan-Meier method and Cox proportional hazards model was used to assess the impact of PECs and PEC clusters on overall survival (OS). RESULTS: 101 NSCLC patients were enrolled. The median number of PECs was significantly greater in the malignant (n = 84) versus non-malignant group (n = 17) (730 PECs/mL vs 1.0 PEC/mL, p < 0.001). The area under the ROC curve was 0.91. A cutoff value of 105 PECs/mL had a sensitivity and specificity of 73% and 100% for the diagnosis of a MPE, respectively. Among 69 patients with a pathology-confirmed MPE and tissue immunohistochemistry (IHC) results, 15 (22%) had greater than 50% PD-L1+ PECs. Overall concordance between tissue and PEC PD-L1 expression was 76%. Higher numbers of pleural effusion single PECs were associated with inferior overall survival (Cox adjusted HR 1.8, 95% CI: 1.02-3.05 p = 0.043). CONCLUSION: Non-invasive measurement of PECs in NSCLC patients, using an automated, clinically available approach, may improve the diagnostic accuracy of a MPE, allow for immunophenotyping of PECs, and provide prognostic information. Published by Elsevier B.V.
OBJECTIVES: A malignant pleural effusion (MPE) is a common complication in non-small cell lung cancer (NSCLC) with important staging and prognostic information. Patients with MPEs are often candidates for advanced therapies, however, the current gold standard, cytological analysis of pleural fluid samples, has limited sensitivity. We aimed to demonstrate the feasibility of non-invasive enumeration and immunophenotyping of EpCAM-positive cells in pleural fluid samples for the diagnosis of a MPE in NSCLCpatients. MATERIALS AND METHODS:Pleural fluid specimens were prospectively collected from patients with NSCLC and the CellSearch® technology was utilized for the enumeration of pleuralEpCAM-positive cells (PECs) and determination of PD-L1 expression on PECs from pleural fluid samples. The diagnostic performance of the enumeration of single PECs and PEC clusters was assessed using receiver operating characteristic (ROC) curves. The Kaplan-Meier method and Cox proportional hazards model was used to assess the impact of PECs and PEC clusters on overall survival (OS). RESULTS: 101 NSCLCpatients were enrolled. The median number of PECs was significantly greater in the malignant (n = 84) versus non-malignant group (n = 17) (730 PECs/mL vs 1.0 PEC/mL, p < 0.001). The area under the ROC curve was 0.91. A cutoff value of 105 PECs/mL had a sensitivity and specificity of 73% and 100% for the diagnosis of a MPE, respectively. Among 69 patients with a pathology-confirmed MPE and tissue immunohistochemistry (IHC) results, 15 (22%) had greater than 50% PD-L1+ PECs. Overall concordance between tissue and PECPD-L1 expression was 76%. Higher numbers of pleural effusion single PECs were associated with inferior overall survival (Cox adjusted HR 1.8, 95% CI: 1.02-3.05 p = 0.043). CONCLUSION: Non-invasive measurement of PECs in NSCLCpatients, using an automated, clinically available approach, may improve the diagnostic accuracy of a MPE, allow for immunophenotyping of PECs, and provide prognostic information. Published by Elsevier B.V.
Authors: Moen Sen; Ryan M Hausler; Keely Dulmage; Taylor A Black; William Murphy; Charles H Pletcher; Ling Wang; Chang Chen; Stephanie S Yee; Scott J Bornheimer; Kara N Maxwell; Ben Z Stanger; Jonni S Moore; Jeffrey C Thompson; Erica L Carpenter Journal: Clin Transl Med Date: 2022-07