Background To construct a predictive model of immunotherapy efficacy for patients with lung squamous cell carcinoma (LUSC) based on the degree of tumor-infiltrating immune cells (TIIC) in the tumor microenvironment (TME). Methods The data of 501 patients with LUSC in the TCGA database were used as a training set, and grouped using non-negative matrix factorization (NMF) based on the degree of TIIC assessed by single-sample gene set enrichment analysis (GSEA). Two data sets (GSE126044 and GSE135222) were used as validation sets. Genes screened for modeling by least absolute shrinkage and selection operator (LASSO) regression and used to construct a model based on immunophenotyping score (IPTS). RNA extraction and qPCR were performed to validate the prognostic value of IPTS in our independent LUSC cohort. The receiver operating characteristic (ROC) curve was constructed to determine the predictive value of the immune efficacy. Kaplan–Meier survival curve analysis was performed to evaluate the prognostic predictive ability. Correlation analysis and enrichment analysis were used to explore the potential mechanism of IPTS molecular typing involved in predicting the immunotherapy efficacy for patients with LUSC. Results The training set was divided into a low immune cell infiltration type (C1) and a high immune cell infiltration type (C2) by NMF typing, and the IPTS molecular typing based on the 17-gene model could replace the results of the NMF typing. The area under the ROC curve (AUC) was 0.82. In both validation sets, the IPTS of patients who responded to immunotherapy were significantly higher than those who did not respond to immunotherapy (P = 0.0032 and P = 0.0451), whereas the AUC was 0.95 (95% CI = 1.00–0.84) and 0.77 (95% CI = 0.58–0.96), respectively. In our independent cohort, we validated its ability to predict the response to cancer immunotherapy, for the AUC was 0.88 (95% CI = 1.00–0.66). GSEA suggested that the high IPTS group was mainly involved in immune-related signaling pathways. Conclusions IPTS molecular typing based on the degree of TIIC in the TME could well predict the efficacy of immunotherapy in patients with LUSC with a certain prognostic value.
Objective: This study aims to describe the imaging features of naïve asthma patients, defined as not receiving corticosteroids or other asthma medications for at least 1 month, and their association with therapeutic response, and to discover novel unbiased imaging phenotypes. Methods: A total of 109 naïve asthma patients and 50 healthy controls were enrolled in this study. Clinical data and imaging indices of high-resolution computed tomography were collected. The correlation between imaging indices and clinical features was analyzed. Cluster analyses were adopted to determine three novel imaging phenotypes. Results: Compared with healthy controls, naïve asthma patients presented higher scores of airway remodeling, bronchiectasis, and mucus plugs. Mean airway wall area (WA)% was inversely correlated with mid-expiratory flow velocity% predicted. The extent score of bronchiectasis was positively correlated with smoking history and significantly increased in the high mucus group. Mucus plugs were related to improving lung function and type 2 (T2) inflammation, as assessed by sputum and blood eosinophils and fraction of exhaled nitric oxide. Cluster 1 patients had a high proportion of emphysema, the best lung function, and the lowest T2 inflammation; cluster 2 patients had severe airway remodeling, relatively good lung function, and moderate T2 inflammation; cluster 3 patients had severe airway remodeling, mucus plugs, and bronchiectasis, and showed the worst lung function and highest T2 inflammation. Conclusion: Naïve asthma patients had the imaging traits of airway remodeling, bronchiectasis, and mucus plugs. The unbiased imaging phenotypes had good consistency with clinical characteristics, therapeutic response, and T2 inflammation expression in naïve asthma patients.
Immune checkpoint inhibitors (ICIs) therapy have revolutionized advanced lung cancer care. Interestingly, the host responses for patients received ICIs therapy are distinguishing from those with cytotoxic drugs, showing potential initial transient worsening of disease burden, pseudoprogression and delayed time to treatment response. Thus, a new imaging criterion to evaluate the response for immunotherapy should be developed. ICIs treatment is associated with unique adverse events, including potential life‐threatening immune checkpoint inhibitor‐related pneumonitis (ICI‐pneumonitis) if treated patients are not managed promptly. Currently, the diagnosis and clinical management of ICI‐pneumonitis remain challenging. As the clinical manifestation is often nonspecific, computed tomography (CT) scan and X‐ray films play important roles in diagnosis and triage. This article reviews the complications of immunotherapy in lung cancer and illustrates various radiologic patterns of ICI‐pneumonitis. Additionally, it is tried to differentiate ICI‐pneumonitis from other pulmonary pathologies common to lung cancer such as radiation pneumonitis, bacterial pneumonia and coronavirus disease of 2019 (COVID‐19) infection in recent months. Maybe it is challenging to distinguish radiologically but clinical presentation may help.
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