Article Text
Abstract
Background Lung cancer, frequently presents with advanced stage disease with approximately 15–30% of patients first diagnosed by a malignant pleural effusion (MPE).Currently, we have limited understanding of the cellular complex immune landscape compositions of MPE and how this cellular composition impacts response to therapy. Therefore, in this pilot study, we aimed to characterize the cellular composition of MPE in patients with metastatic lung adenocarcinoma (LADC).
Methods A custom multiplex immunofluorescence (mIF) panel was designed and optimized using the Opal™ 7 color Kit (Akoya Biosciences) against six immune markers including cytokeratins (CK), PD-L1, PD-1, CD3 CD8, and CD68 (figure 1). We selected 4 MPE cases from LADC patients to validate this mIF panel. Regions of interest (ROI) were scanned in high magnification using the multispectral microscopy Vectra Polaris (Akoya Biosciences) to capture the multiplex immune cell phenotypes and to be analyzed by the image analysis InForm software.
Results The median number of cells observed was 4,883.5 (range 1773–8292 cells).The median cells expressing CK was 15% (including tumor and mesothelial cells), CD3+ T-cell was 38%, cytotoxic T-cells CD3+CD8+ was 3%, and macrophages CD68+ was 14% (table1). The median number of CK+ cells expression PD-L1 was 1%. Additionally, the median number of CD3 T-cells expressing PD-1 or PD-L1 was in total 1%. Interestingly, with didn’t see macrophages CD68+ expressing PD-L1 in this small cohort. Furthermore, an exploratory observation showed that patients with high percentage of cytotoxic T-cells CD3+CD8+ and high percentage of macrophages CD68+ had better overall survival (table 2).
Conclusions In our cohort of MPE, we were able to assess, with extraordinary fidelity according to the antibodies included in the panel, several cell phenotypes, showing that we successfully multiplexed these biomarkers using mIF. These results demonstrate the practical scalability of this method for studying different aspects of cytological material and the data generated with the image analysis can be used to explore prognosis and potential therapeutic response in the future.
References
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