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Summary: In nasopharyngeal carcinoma, deep-learning extracted signatures on MR images might be correlated with survival. In this study, we sought to develop an individualizing model using deep-learning MRI signatures and clinical data to predict survival and to estimate the benefit of induction chemotherapy on survivals of patients with nasopharyngeal carcinoma. Two thousand ninety-seven patients from three independent hospitals were identified and randomly assigned. When the deep-learning signatures of the primary tumor and clinically involved gross cervical lymph nodes extracted from MR images were added to the clinical data and TNM staging for the progression-free survival prediction model, the combined model achieved better prediction performance. Its application is among patients deciding on treatment regimens. Under the same conditions, with the increasing MRI signatures, the survival benefits achieved by induction chemotherapy are increased. In nasopharyngeal carcinoma, these prediction models are the first to provide an individualized estimation of survivals and model the benefit of induction chemotherapy on survivals.

PurposeCurrently, the relationship between radiation pneumonia (RP) and circulating immune cell in patients with esophageal squamous cell carcinoma (ESCC) remains unclear. This study aimed to explore the relationship between RP and circulating lymphocyte subsets in patients with ESCC receiving chemoradiotherapy (CRT), and develop a nomogram model to predict RP. Since we should implement clinical intervention to ≥ grade 2 RP, a nomogram model for ≥ grade 2 RP was also established to provide an early warning.Patients and methodsThis study retrospectively included 121 patients with ESCC receiving CRT from Guangxi Medical University Cancer Hospital from 2013 to 2021. Independent factors associated with occurrence of RP and ≥ grade 2 RP were identified by univariate and multivariate logistic regression analysis in the training cohort, and incorporated into nomograms. The predictive accuracy and discrimination of the model was assessed using Concordance Index (C-index), calibration curve and decision curve analysis (DCA). And each model was internally validated. Additionally, to verify the optimized predictive performance of the nomograms, the area under the ROC curve (AUC) of each nomogram was compared to that of single independent risk factors, lung V10 and lung V20, respectively. Moreover, each model was further evaluated for risk stratification to identify populations at high risk of RP and ≥ grade 2 RP.ResultsMultivariate analysis suggested that TNM stage, post-RT percentage of CD8+ T cell, and lung V15 were independent predictive factors of RP. Besides, pre- and post-RT percentage of CD8+ T cell, and V15 were independent factors of ≥ grade 2 RP. The C-indexes of RP and ≥ grade 2 RP nomograms were 0.809 (95% CI: 0.715-0.903) and 0.787 (95% CI: 0.685-0.889) in the training cohort, respectively. And the C-indexes of RP and ≥ grade 2 RP nomograms were 0.718 (95% CI: 0.544-0.892) and 0.621 (95% CI: 0.404-0.837) in the validation cohort, respectively. The calibration curves showed that the predicted values of model agreed well with actual observations. Moreover, DCA results indicated the applicability and accuracy of the models to predict RP and ≥ grade 2 RP. After stratification, the incidence of the high-risk group was significantly higher than that of the low-risk group with respect to either RP or ≥ grade 2 RP.ConclusionTNM stage, post-RT percentage of CD8+ T cell, and lung V15 were the independent predictors of RP toxicity. Pre- and post-RT percentage of CD8+ T cell, and lung V15 were the independent factors of ≥ grade 2 RP toxicity. The nomograms based on circulating lymphocyte subsets can robustly predict RP and ≥ grade 2 RP, guiding clinicians in risk stratification and early intervention.

Abstract Background The optimal dose and fractionation scheme of stereotactic body radiation therapy (SBRT) for hepatocellular carcinoma (HCC) remains unclear due to different tolerated liver volumes and degrees of cirrhosis. In this study, we aimed to verify the dose-survival relationship to optimize dose selection for treatment of HCC. Methods This multicenter retrospective study included 602 patients with HCC, treated with SBRT between January 2011 and March 2017. The SBRT dosage was classified into high dose, moderate dose, and low dose levels: SaRT (BED10 ≥ 100 Gy), SbRT (EQD2 > 74 Gy to BED10

BackgroundRadiation-induced lung injury (RILI) is a severe side effect of radiotherapy for non-small cell lung cancer (NSCLC) ,and one of the major hindrances to improve the efficacy of radiotherapy. Previous studies have confirmed that sodium butyrate (NaB) has potential of anti-radiation toxicity. However, the mechanism of the protective effect of NaB against RILI has not yet been clarified. This study aimed to explore the underlying protective mechanisms of NaB against RILI in NSCLC through network pharmacology, molecular docking, molecular dynamic simulations and in vivo experiments.MethodsThe predictive target genes of NaB were obtained from the PharmMapper database and the literature review. The involved genes of RILI and NSCLC were predicted using OMIM and GeneCards database. The intersectional genes of drug and disease were identified using the Venny tool and uploaded to the Cytoscape software to identify 5 core target genes of NaB associated with RILI. The correlations between the 5 core target genes and EGFR, PD-L1, immune infiltrates, chemokines and chemokine receptors were analyzed using TIMER 2.0, TIMER and TISIDB databases. We constructed the mechanism maps of the 3 key signaling pathways using the KEGG database based on the results of GO and KEGG analyses from Metascape database. The 5 core target genes and drug were docked using the AutoDock Vina tool and visualized using PyMOL software. GROMACS software was used to perform 100 ns molecular dynamics simulation. Irradiation-induced lung injury model in mice were established to assess the therapeutic effects of NaB.ResultsA total of 51 intersectional genes involved in NaB against RILI in NSCLC were identified. The 5 core target genes were AKT1, TP53, NOTCH1, SIRT1, and PTEN. The expressions of the 5 core target genes were significantly associated with EGFR, PD-L1, immune infiltrates, chemokines and chemokine receptors, respectively. The results from GO analysis of the 51 intersectional genes revealed that the biological processes were focused on the regulation of smooth muscle cell proliferation, oxidative stress and cell death, while the three key KEGG pathways were enriched in PI3K-Akt signal pathway, p53 signal pathway, and FOXO signal pathway. The docking of NaB with the 5 core target genes showed affinity and stability, especially AKT1. In vivo experiments showed that NaB treatment significantly protected mice from RILI, with reduced lung histological damage. In addition, NaB treatment significantly inhibited the PI3K/Akt signaling pathway.ConclusionsNaB may protect patients from RILI in NSCLC through multiple target genes including AKT1, TP53, NOTCH1, SIRT1 and PTEN, with multiple signaling pathways involving, including PI3K-Akt pathway, p53 pathway, and FOXO pathways. Our findings effectively provide a feasible theoretical basis to further elucidate the mechanism of NaB in the treatment of RILI.

In order to solve the problem that the laser satellite terminal can realize the ranging function while completing the communication function, this paper designs a method based on the Delta-Sigma modulation to realize the laser phase ranging, which can integrate the functions of communication and ranging. Multi-frequency point phase ranging is used to balance ranging range and ranging accuracy. Multi-frequency modulation signals are generated using high-speed digital Input and Output (I/O) ports based on Delta-Sigma modulation without any Digital-to-Analog Converter (DAC). Based on the Delta-Sigma modulation method, multiple frequency points for multi-frequency phase ranging can be generated at the same time, which is better than the traditional method of generating each single frequency point separately. Selecting the high frequency of 187.50 MHz and the low frequency of 1.50 MHz, the ranging accuracy can achieve 1 mm in the range of less than 100 m.

RING finger protein 135 has an important role in the occurrence of many cancers; however its regulation and function of RNF135 in hepatocellular carcinoma remains unknown. The promoter methylation status and mRNA expression of RNF135 was evaluated by methylation-specific PCR, semi-quantitative RT-PCR, and real-time quantitative PCR in HCC tissues and cell lines, and further analyzed from The Cancer Genome Atlas database. Wound healing assay, transwell migration, cell viability, and colony formation assay were performed to investigate the function of RNF135. GSEA analysis, TIMER database, and ESTIMATE algorithm were used to decipher the associated pathway and immune infiltration. The survival analysis was applied to assess the prognostic value of RNF135. RNF135 expression was downregulated in HCC tissues and 5 of 8 HCC cell lines, and was negatively correlated with its promoter hypermethylation. Demethylating regent decitabine restored RNF135 expression on the cellular level. Knockdown of RNF135 expression enhanced the migration of HCC cells, while RNF135 overexpression and decitabine treatment repressed cell migration. Bioinformatics analysis and immunohistochemistry revealed a positive relationship between RNF135 expression and six immune cell infiltrates (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells). Survival analysis disclosed that RNF135 hypermethylation is independently associated with poor clinical outcomes in HCC. Decreased RNF135 expression driven by promoter hypermethylation frequently occurred in HCC and associated with prognosis of HCC. RNF135 functions as a tumor suppressor and is involved in tumor immune microenvironment in HCC.