Stephansenknapp9261

DNA methylation has been reported to serve an important role in the carcinogenesis and development of gastric cancer. Our aim was to systematically develop an individualized prediction model of the survival risk combing clinical and methylation factors in gastric cancer. A univariate Cox proportional risk regression analysis was used to identify the prognosis-associated methylation sites based on the differentially expressed methylation sites between early and advanced gastric cancer group, then we applied least absolute shrinkage and selection operator (LASSO) Cox regression model to screen candidate methylation sites. Subsequently, multivariate Cox proportional risk regression analysis was conducted to identify predictive signature according to the candidate sites. Relative operating characteristic curve (ROC) analysis manifested that an 11-methylation signature exhibited great predictive efficiency for 1-, 3-, 5-year survival events. Patients in the low-risk group classified according to 11-methylation signature-based risk score yield significantly better survival than that in high-risk group. Moreover, Cox regression analysis combing methylation-based risk score and other clinical factors indicated that 11-methylation signature served as an independent risk factor. The predictive value of risk score was validated in the testing dataset. In addition, a nomogram was constructed and the ROC as well as calibration plots analysis demonstrated the good performance and clinical application of the nomogram. In conclusion, the result suggested the 11-DNA methylation signature may be potentially independent prognostic marker and functioned as a significant tool for guiding the clinical prediction of gastric cancer patients' overall survival.Purpose We aimed to investigate the association of single-nucleotide polymorphisms (SNPs) in HMGB1, REV3L, and NFE2L2 with prognosis in lung cancer patients with platinum-based chemotherapy. Methods We have recruited 348 lung cancer patients treated with platinum. Log-rank test and Cox regression analysis were used to assess overall survival (OS) and progression-free survival (PFS) among SNP genotypes. Results The results revealed that patients carrying TC or CC genotype in REV3L rs462779 (HR=0.67, 95% CI=0.51-0.90, P=0.007) and AG or GG genotype in HMGB1 rs1045411 (HR=0.61, 95% CI=0.38-0.99, P=0.046) had a better overall survival. Additionally, carrying TC or TT genotype in rs462779 had a lower risk (OR=0.38, 95% CI=0.17-0.89, P=0.025) of lymph node metastasis, carrying AG or AA genotype in rs1045411 was significantly related to early T stage (OR=0.47, 95% CI=0.29-0.76, P=0.002). In stratified analysis, patients with TC or CC genotype in rs462779 were significantly associated with overall survival in male patients, never-smokers, patients with younger age (≤56), no family history of cancer, adenocarcinoma, advanced stage (stage III or IV), or ECOG PS 0-1. While patients with AG or GG genotype in rs1045411 were significantly associated with overall survival in patients with advanced stage (stage III or IV) or ECOG PS 0-1. Conclusion Our results indicate that the TC or CC genotype in rs462779 and AG or GG genotype in rs1045411 are contributed to better overall survival. The REV3L rs462779 and HMGB1 rs1045411 may serve as prognosis markers in lung cancer patients with platinum-based chemotherapy.Esophagogastric junction cancer poses a great threat to human beings both in western countries and East Asia, especially in China and Japan, and its incidence has increased during recent decades. The 5-year survival rate of esophagogastric junction cancer is quite poor compared with that of other gastric cancer sites. Until now, the traditional TNM staging system has been widely used in clinical practice for prognosis. However, the TNM system is based on pathology after surgical resection or radiology using CT and MRI, not on blood markers. Evidently, some research has been reported concentrated on the prognostic value of blood-based markers with the character of non-invasive and non-radioactive in EJA. Hematologic, biochemical and coagulation parameters could be obtained from clinical data and utilized to analyze their prognostic values. Tumor-associated antigens, microRNAs and circulating tumor cells have also been reported in EJC prognosis. In this article, we review research focused on blood-based markers to evaluate their prognostic value in esophagogastric junction cancer, especially its main subtype adenocarcinoma.Objective To explore the independent risk factors of infection during the intravesical instillation of bladder cancer and establish a prediction model, which may reduce probability of infection for bladder cancer patients. Material and Methods 533 patients with newly discovered NMIBC at two hospitals from January 2017 to December 2019 were enrolled in this study. The patients were divided into "infection positive group" and "infection negative group". The clinical data of the two groups were analyzed by logistic regression analyses. Nomogram was generated and ROC curve, calibration curve were structured to assess the accuracy of nomogram. find more An independent cohort included 174 patients from another hospital validated the nomogram prediction model. Results Of 533 patients, 185 patients had an infection. Univariate and multivariate logistic regression analyses showed diabetes mellitus, hemiplegia, patients without antibiotics and perfusion frequency (≥2 times/month) were the independent risk factors. AUC of the ROC was 0.858 (0.762-0.904). The nomogram could predict the probability of infection during the intravesical instillation of bladder tumor calibration curve showed good agreement. The external data validation gained good sensitivity and specificity, which indicated that the nomogram had great value of prediction. Conclusions Individualized prediction of the probability of infection may reduce the incidence of infection by argeted preventive measures.Objective Pancreatic cancer (PC) is a malignant tumor with limited therapeutic choices and extremely poor prognosis. Personalized therapy based on gene alternations is a promising choice. Considering tumor heterogeneity, the practice of ctDNA analysis has drawn the attention. Here, we try to assess the applicability of ctDNA in PC. Methods and materials Next generation sequencing (NGS) was performed from blood samples of 223 PC patients and tissue sample of 564 PC patients. Genomic data from the TCGA database were also utilized. In addition, two cases received personalized treatment based on ctDNA sequencing results were reported. Results Based on ctDNA sequencing, the genomic features of PC was revealed. Totally, 68.2% of patients detected at least one reportable genomic alteration (GA) from ctDNA. The frequently altered genes were KRAS (53.5%), followed by TP53 (52.8%), and CDKN2A (15.1%). Cell cycle control (8%) and DNA damage response (8%) pathways enriched the most mutated genes. Compared with mutations from tissue samples and a tissue-genomic database, similar frequencies of GAs were detected from ctDNA.