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Objective To investigate the X-ray-specific sensitive genes and potential signaling pathways involved in the latent period of radiation-induced lung injury (RILI) in mouse models. Method Mice were randomized into groups for whole thoracic irradiation with a single fraction of 20 Gy X-ray or 12.5 Gy carbon heavy ion. Lungs were harvested 3 weeks after the irradiation, whole RNA was extracted and detected with the genome-wide transcriptional microarrays. Differentially expressed genes (DEGs) were calculated for each group and the X-ray-specific sensitive genes were determined, followed by the gene enrichment analysis of those DEGs exploring the potentially relevant signaling pathways and biological processes in latent RILI. Results Three weeks after irradiation, gene expression levels varied between groups. 76 up-regulated DEGs were determined with mice in the X-ray group and gene ontology enrichment analysis for biological process (GO-BP) obtained several processes which were associated with radiation reaction, mitotic, immune cell chemotaxis or metastasis, immune factors, p53 apoptosis, and tissue remodeling. KEGG signaling pathway enrichment analysis showed that those 76 up-regulated DEGs were enriched in p53, IL-17, FoXO, melanoma, and non-small-cell lung cancer signaling pathways. By comparing the DEGs in X-ray and heavy ion groups, X-ray-specific sensitive genes were determined, the top 10 genes were Adamts9, Aacs, Col6a2, Fdps, Mdk, Mcam, Stbd1, Lbh, Ak3, and Emid1. The expression level of the top 10 genes was found to be significantly higher in the X-ray group than in the control and heavy ion groups. Conclusion Our research determined the X-ray-specific sensitive gene set in mice lungs after exposure to radiation. The gene set could be used as a genetic marker to suggest the latency of RILI. The enrichment analysis results suggested that the relevant signaling pathways were potentially involved in the development of RILI. Further validation of those genes and signaling pathways is needed to confirm these findings.

Background: Gliomas are the malignance of a poor prognosis. The current WHO classification remains unable to predict survival outcomes accurately. Novel surrogates are highly required for improved stratification of patients and hence, allowing to delivery of the most appropriate treatment. Methods: Transcriptional profiles of 301 glioma cases on the platform of Chinese Glioma Genome Atlas (CGGA) were retrospectively studied. Results: Extracellular matrix (ECM) scores were established by integrating a panel of most featured gene-signatures, correlating well with pathological tumor stages. Linear regression analysis revealed that the ECM score corroborated with the infiltration status of monocytes, M0 and M1 macrophages. Furthermore, the WHO stage II-IV dependent abundance of those 3 immune cells was determined. Univariate and multivariate analysis of clinicopathological characteristics in the GBM cohort identified M1 enrichment score as an independent risk factor. A high abundance of M1 macrophages was associated with poor survival outcomes and radiotherapy response in IDH-wildtype GBM. Conclusions: Our study demonstrated that M1 macrophages correlated with WHO grades and predicted robustly for the survival performance for GBM patients. Increased infiltration of M1 macrophages was associated with a poor radiation response for IDH-wildtype GBM. Together, it will facilitate more precise stratifications of glioma patients based on molecular and immunological surrogates.