No abstract

Background Irradiation has emerged as a valid tool for nasopharyngeal carcinoma (NPC) in situ treatment; however, NPC derived from tissues treated with irradiation is a main cause cancer-related death. The purpose of this study is to uncover the underlying mechanism regarding tumor growth after irradiation and provided potential therapeutic strategy. Methods Fibroblasts were extracted from fresh NPC tissue and normal nasopharyngeal mucosa. Immunohistochemistry was conducted to measure the expression of α-SMA and FAP. Cytokines were detected by protein array chip and identified by real-time PCR. CCK-8 assay was used to detect cell proliferation. Radiation-resistant (IRR) 5-8F cell line was established and colony assay was performed to evaluate tumor cell growth after irradiation. Signaling pathways were acquired via gene set enrichment analysis (GSEA). Comet assay and γ-H2AX foci assay were used to measure DNA damage level. Protein expression was detected by western blot assay. In vivo experiment was performed subcutaneously. Results We found that radiation-resistant NPC tissues were constantly infiltrated with a greater number of cancer-associated fibroblasts (CAFs) compared to radiosensitive NPC tissues. Further research revealed that CAFs induced the formation of radioresistance and promoted NPC cell survival following irradiation via the IL-8/NF-κB pathway to reduce irradiation-induced DNA damage. Treatment with Tranilast, a CAF inhibitor, restricted the survival of CAF-induced NPC cells and attenuated the of radioresistance properties. Conclusions Together, these data demonstrate that CAFs can promote the survival of irradiated NPC cells via the NF-κB pathway and induce radioresistance that can be interrupted by Tranilast, suggesting the potential value of Tranilast in sensitizing NPC cells to irradiation.

Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and risk signature in LGG. Therefore, we identified six autophagy-related genes (BAG1, PTK6, EEF2, PEA15, ITGA6, and MAP1LC3C) to build in the training cohort (n = 305 patients) and verify the prognostic model in the validation cohort (n = 128) and the whole cohort (n = 433), based on the data from The Cancer Genome Atlas (TCGA). The six-gene risk signature could divide LGG patients into high- and low-risk groups with distinct overall survival in multiple cohorts (all p < 0.001). The prognostic effect was assessed by area under the time-dependent ROC (t-ROC) analysis in the training, validation, and whole cohorts, in which the AUC value at the survival time of 5 years was 0.837, 0.755, and 0.803, respectively. Cox regression analysis demonstrated that the risk model was an independent risk predictor of OS (HR > 1, p < 0.05). A nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its robust predictive capacity. KM analysis revealed a significant difference in the subgroup analyses’ survival. Functional enrichment analysis revealed that these autophagy-related signatures were mainly involved in the phagosome and immune-related pathways. Besides, we also found significant differences in immune cell infiltration and immunotherapy targets between risk groups. In conclusion, we built a powerful predictive signature and explored immune components (including immune cells and emerging immunotherapy targets) in LGG.

Background Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality worldwide. Currently, there is limited knowledge of dysregulation of cellular proliferation and apoptosis that contribute to the malignant phenotype in HCC. Copper metabolism gene MURR1 domain 10 (COMMD10) is initially identified as a suppressor gene in the pathogenesis of HCC in our observations. Here we aimed to explore its function and prognostic value in the progression of HCC. Methods Functional experiments were performed to explore the role of COMMD10 in HCC. The molecular mechanisms of COMMD10 were determined by luciferase assay, immunofluorescence, and immunoprecipitation. The nomogram was based on a retrospective and multicenter study of 516 patients who were pathologically diagnosed with HCC from three Chinese hospitals. The predictive accuracy and discriminative ability of the nomogram were determined by a C‐index and calibration curve and were compared with COMMD10 and the Barcelona Clinic Liver Cancer (BCLC) staging system. The primary endpoint was overall survival (OS). Results COMMD10 expression was significantly lower in HCC than that in normal liver tissues. In vitro and in vivo experiments revealed that COMMD10 suppressed cell proliferation and induced apoptosis in HCC. Mechanistically, COMMD10 inhibits TNFα mediated ubiquitination of IκBα and p65 nuclear translocation through the combination of COMMD10‐N terminal to the Rel homology domain of p65, which inhibited NF‐κB activity and increased expression of cleaved caspase9/3 in HCC. Clinically, COMMD10 stratifies early‐stage HCC patients into two risk groups with significantly different OS. Additionally, the nomogram based on COMMD10 and BCLC stage yielded more accuracy than BCLC stage alone for predicting OS of HCC patients in three cohorts. Conclusions COMMD10 suppresses proliferation and promotes apoptosis by inhibiting NF‐κB signaling and values up BCLC staging in predicting OS, which provides evidence for the identification of potential therapeutic targets and the accurate prediction of prognosis for patients with HCC.