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Multivariate analysis revealed a better survival in overall patients with OBC patients according to breast cancer-specific survival (BCSS) and overall survival (OS). Propensity score analysis also achieved a similar result for OBC patients. Stratified analyses by nodal status and molecular subtypes indicated that these survival advantage were mainly presented in patients with AJCC N2/N3 stage or hormone receptor (HR)-positive tumors. In addition, nodal status, HER-2 status, and radiation status were demonstrated to be three independent prognostic factors for OBC patients. Conclusion Patients with OBC retained exclusive clinical characteristics and were shown to have a better outcome compared with non-OBC patients, especially for those with N2/N3 stage or HR-positive tumors.Introduction The prognostic role of plasma Epstein-Barr virus (EBV) DNA clearance when intensity-modulated radiotherapy (IMRT) and the 8th edition of American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) TNM Staging Classification are fully implemented remains undeciphered. We investigated if its half-life clearance during radical treatment for non-metastatic nasopharyngeal carcinoma (NPC) was an early prognosticator. Patients and methods Patients with previously untreated non-metastatic NPC were prospectively treated with radical IMRT and concurrent chemotherapy +/- induction/adjuvant chemotherapy from 2014 to 2018. Their plasma EBV DNA was measured immediately before treatment followed by weekly schedules until 0 copy/ml in two consecutive measurements. TGFbeta inhibitor Cox regression models were employed to identify prognostic factors. Results Forty-five patients were prospectively recruited and analyzed. After a median follow-up of 30.3 months, 2 (4.5%), 1 (2.3%), and 6 (13.6%) patients ellance during treatment should be considered. Clinical Trial Registration This study has been registered with ClinicalTrials.gov (Identifier NCT03830996).Objective The aim of this study is to evaluate whether radiomics imaging signatures based on computed tomography (CT) could predict peritoneal metastasis (PM) in gastric cancer (GC) and to develop a nomogram for preoperative prediction of PM status. Methods We collected CT images of pathological T4 gastric cancer in 955 consecutive patients of two cancer centers to analyze the radiomics features retrospectively and then developed and validated the prediction model built from 292 quantitative image features in the training cohort and two validation cohorts. Lasso regression model was applied for selecting feature and constructing radiomics signature. Predicting model was developed by multivariable logistic regression analysis. Radiomics nomogram was developed by the incorporation of radiomics signature and clinical T and N stage. Calibration, discrimination, and clinical usefulness were used to evaluate the performance of the nomogram. Results In training and validation cohorts, PM status was associated with the radiomics signature significantly. It was found that the radiomics signature was an independent predictor for peritoneal metastasis in multivariable logistic analysis. For training and internal and external validation cohorts, the area under the receiver operating characteristic curves (AUCs) of radiomics signature for predicting PM were 0.751 (95%CI, 0.703-0.799), 0.802 (95%CI, 0.691-0.912), and 0.745 (95%CI, 0.683-0.806), respectively. Furthermore, for training and internal and external validation cohorts, the AUCs of radiomics nomogram for predicting PM were 0.792 (95%CI, 0.748-0.836), 0.870 (95%CI, 0.795-0.946), and 0.815 (95%CI, 0.763-0.867), respectively. Conclusions CT-based radiomics signature could predict peritoneal metastasis, and the radiomics nomogram can make a meaningful contribution for predicting PM status in GC patient preoperatively.Objective Meningiomas presented preferred intracranial distribution, which may reflect potential biological natures. This study aimed to analyze the preferred locations of meningioma according to different biological characteristics. Method A total of 1,107 patients pathologically diagnosed with meningiomas between January 2012 and December 2016 were retrospectively analyzed. Preoperative MRI were normalized, and lesions were semiautomatically segmented. The stereospecific frequency and p value heatmaps were constructed to compare two biological phenotypes using two-tailed Fisher’s exact test. Age, sex, WHO grades, extent of resection (EOR), recurrence, and immunohistochemical markers including p53, Ki67, epithelial membrane antigen (EMA), progesterone receptor (PR), and CD34 were statistically analyzed. Recurrence-free survival (RFS) were analyzed by Kaplan-Meier method. Result Of 1,107 cases, convexity (20.8%), parasagittal (16.1%), and falx (11.4%) were the most predominant loci of meningiomas. The p-valuet sphenoid wing. Tumor recurrence rates for grades I, II, and III were 2.8, 7.9, and 53.8%, respectively. Inferior RFS, higher Ki67 index, grades II and III, and a larger preoperative volume were observed in older patients. Recurrent meningiomas were more frequently found at the occipital convexity, tentorium, sellar regions, parasagittal sinus, and left sphenoid wing. Conclusion The preferred locations of meningioma could be observed according to different biological characteristics, which might be helpful for clinical decisions.Background The spontaneous regression of neuroblastoma (NB) is most prevalent and well-documented in stage 4s NB patients. However, whether autophagy plays roles in the spontaneous regression of NB is unknown. Objective This study aimed to identify autophagy-related genes (ARGs) and autophagy-related long non-coding RNAs (lncRNAs) differentially expressed in stage 4 and stage 4s NB and to build prognostic risk signatures on the basis of the ARGs and autophagy-related lncRNAs. Methods One RNA-sequence (RNA-Seq) dataset (TARGET NBL, n = 153) was utilized as discovery cohort, and two microarray datasets (n = 498 and n = 223) were used as validation cohorts. Differentially expressed ARGs were identified by comparing stage 4s and stage 4 NB samples. An ARG signature risk score and an autophagy-related lncRNA signature risk score were constructed. The receiver operating characteristic (ROC) curve analyses were used to evaluate the survival prediction ability of the two signatures. Gene function annotation and Gene Set Enrichment Analysis (GSEA) were performed to clarify the autophagic biological processes enriched in different risk groups.