3 research outputs found
EEG measures of sensorimotor processing and their development are abnormal in children with isolated dystonia and dystonic cerebral palsy
Therapeutic Alliance in Cognitive Remediation: evaluating its contribution to therapy outcomes and its predictors
Deconvolution of malignant pleural effusions immune landscape unravels a novel macrophage signature associated with worse clinical outcome in lung adenocarcinoma patients
Background: Immune checkpoint inhibitors are still unable to provide clinical benefit to the large majority of non-small cell lung cancer (NSCLC) patients. A deeper characterization of the tumor immune microenvironment (TIME) is expected to shed light on the mechanisms of cancer immune evasion and resistance to immunotherapy. Here, we exploited malignant pleural effusions (MPEs) from lung adenocarcinoma (LUAD) patients as a model system to decipher TIME in metastatic NSCLC. Methods: Mononuclear cells from MPEs (PEMC) and peripheral blood (PBMC), cell free pleural fluid and/or plasma were collected from a total of 24 LUAD patients and 12 healthy donors. Bulk-RNA sequencing was performed on total RNA extracted from PEMC and matched PBMC. The DEseq2 Bioconductor package was used to perform differential expression analysis and CIBERSORTx for the regression-based immune deconvolution of bulk gene expression data. Cytokinome analysis of cell-free pleural fluid and plasma samples was performed using a 48-Plex Assay panel. THP-1 monocytic cells were used to assess macrophage polarization. Survival analyses on NSCLC patients were performed using KM Plotter (LUAD, N=672; lung squamous cell carcinoma, N=271). Results: Transcriptomic analysis of immune cells and cytokinome analysis of soluble factors in the pleural fluid depicted MPEs as a metastatic niche in which all the components required for an effective antitumor response are present, but conscripted in a wound-healing, proinflammatory and tumor-supportive mode. The bioinformatic deconvolution analysis revealed an immune landscape dominated by myeloid subsets with the prevalence of monocytes, protumoral macrophages and activated mast cells. Focusing on macrophages we identified an MPEs-distinctive signature associated with worse clinical outcome in LUAD patients. Conclusions: Our study reports for the first time a wide characterization of MPEs LUAD microenvironment, highlighting the importance of specific components of the myeloid compartment and opens new perspectives for the rational design of new therapies for metastatic NSCLC