Effectiveness and Safety of Low-Dose Radiotherapy in Eosinophilic Lymphoid Granuloma.

Objective: To investigate the efficacy and safety of low-dose radiotherapy in treating eosinophilic lymphoid granuloma. Method: This study included a total of 20 patients diagnosed with eosinophilic lymphoid granuloma. All patients underwent low-dose three-dimensional conformal intensity-modulated radiotherapy for their lesions. We analyzed the control status of the lesions and any adverse reactions related to radiotherapy. Results: The overall effectiveness of low-dose radiotherapy in treating eosinophilic lymphoid granuloma was 90%. The incidence of grade I and grade II adverse reactions induced by radiotherapy was 70% and 30%, respectively. Over a median follow-up period of 23.6 months, all patients showed controlled lesions within the target delineation of radiotherapy. After radiotherapy, four patients experienced occasional pruritus, and one patient had a recurrence outside the target area three years later. No long-term severe adverse reactions related to radiotherapy were observed during the follow-up period. Conclusions: Low-dose radiotherapy demonstrates an apparent therapeutic effect on eosinophilic lymphoid granuloma with acceptable adverse reactions.

AEG-1 Knockdown Sensitizes Glioma Cells to Radiation Through Impairing Homologous Recombination Via Targeting RFC5.

Radiotherapy is the most important adjuvant treatment for glioma; however, radioresistance is the major cause for inevitable recurrence and poor survival of glioma patients. Thus, this study aims to investigate the effect of astrocyte elevated gene-1 (AEG-1) on the radiosensitivity of glioma cells. Immunohistochemistry assay found that AEG-1 was generally overexpressed in glioma tissues and was correlated with poor clinicopathological features of glioma patients. AEG-1 knockdown inhibited proliferation of glioma cells. And γ-H2AX foci assay, colony formation assay, and flow cytometry analysis demonstrated that AEG-1 depletion enhanced radiosensitivity and promoted apoptosis as well as cell cycle arrest in G2 phase of glioma cells treated by ionizing radiation. Moreover, replication factor C5 (RFC5) was screened as the target of AEG-1 by using Affymetrix human gene expression array, and RFC5 expression was downregulated in AEG-1 knockdown glioma cells. Mechanistically, AEG-1 knockdown impaired homologous recombination repair activity induced by radiation through inhibiting RFC5 expression. Furthermore, the Kaplan-Meier analysis and multivariate Cox regression analysis indicated that high levels of AEG-1 and RFC5 were related to poor prognosis of glioma patients treated with radiotherapy. Taken together, our findings indicate that AEG-1 may serve as a reliable radiosensitizing target for glioma radiotherapy.

Genome-wide analysis of lncRNAs, miRNAs, and mRNAs forming a prognostic scoring system in esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal carcinoma. Protein coding genes and non-coding RNAs can be powerful prognostic factors in multiple cancers, including ESCC. However, there is currently no model that integrates multiple types of RNA expression signatures to predict clinical outcomes. METHODS: The sequencing data (RNA-sequencing and miRNA-sequencing) and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) database, and Differential gene expression analysis, Cox regression analysis and Spearman correlation analysis were used to construct prognosis-related lncRNA-mRNA co-expression network and scoring system with multiple types of RNA. The potential molecular mechanisms of prognostic mRNAs were explored by functional enrichment analysis. RESULTS: A total of 62 prognostic lncRNAs, eight prognostic miRNAs and 66 prognostic mRNAs were identified in ESCC (P-value < 0.05) and a prognosis-related lncRNA-mRNA co-expression network was created. Five prognosis-related hub RNAs (CDCA2, MTBP, CENPE, PBK, AL033384.1) were identified. Biological process analysis revealed that mRNAs in prognosis-related co-expression RNA network were mainly enriched in cell cycle, mitotic cell cycle and nuclear division. Additionally, we constructed a prognostic scoring system for ESCC using ten signature RNAs (MLIP, TNFSF10, SIK2, LINC01068, LINC00601, TTTY14, AC084262.1, LINC01415, miR-5699-3p, miR-552-5p). Using this system, patients in the low-risk group had better long-term survival than those in the high-risk group (log-rank, P-value < 0.0001). The area under the ROC curve (AUCs) revealed that the accuracy of the prediction model was higher than the accuracy of single type of RNA prediction model. CONCLUSION: In brief, we constructed a prognostic scoring system based on multiple types of RNA for ESCC that showed high predicting prognosis performance, and deeply understood the regulatory mechanism of prognosis-related lncRNA-mRNA co-expression network.