Peripheral blood of Neutrophil-to-Lymphocyte ratio (NLR), carcinoma embryonic antigen (CEA), cancer antigen 125 (CA125) and cancer antigen 15–3 (CA15-3) could be used as prognostic indicators for several types of tumors. The purpose of this study was to evaluate the predictive value of inflammatory cell ratio and tumor markers for postoperative breast cancer patients. Clinical data concerning 190 breast cancer patients who underwent radical surgery in Zhejiang Provincial Hospital of Chinese Medicine from 2013 and 2016 were retrospectively analyzed. The effects of NLR, CEA, CA125, and CA153 on the disease-free survival (DFS) of patients with breast cancer were analyzed by χ ² test and Cox regression analyses. There were totally 32 of 190 patients had local or distant metastases within 5 years after surgery. The peripheral blood NLR, CEA, CA125, and CA15-3 areas under the curve (AUC) were 0.8272, 0.667, 0.702, and 0.715, and the optimal cutoff values were 2.65, 1.47, 10.55, and 10.55, respectively. Univariate analysis and Kaplan-Meier survival analysis revealed that the serum NLR, CEA, CA125, and CA15-3 were related to postoperative 5-year DFS (P < .05). In addition, multivariate survival analysis identified the following independent prognostic factors: NLR (P < .001), CA125 (P = .045) and ki-67 (P = .020). Preoperative serum inflammatory biomarker of NLR and tumor marker of CA125 have potential prognostic value for breast carcinoma.

You-Gui-Yin (YGY) is a classic prescription for warming up kidney-Yang and filling in kidney essence in traditional Chinese medicine, and has been used to treat osteonecrosis of the femoral head (ONFH) effectively. However, the underlying mechanisms are still unknown. This study is aimed at exploring the possible mechanisms of action of the YGY in the treatment of ONFH based on network pharmacology and molecular docking. TCMSP was used to screen the active components and targets of YGY. The disease targets of ONFH were collected in several public databases. The protein-protein interaction (PPI) Network was constructed using the STRING platform. The Metascape database platform was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The key active components and core target proteins of YGY in the treatment of ONFH were verified by the molecular docking. 120 active components were obtained from YGY, among which 73 components were hit by the 117 drug-disease intersection targets. Key effective components included quercetin, kaempferol, beta-sitosterol, glycitein, beta-carotene, and so on. Core target proteins included ALB, AKT1, TNF, IL6, TP53, and so on. According to GO and KEGG analyses, there were 1762 biological processes, 94 cellular component, 138 molecular function and 187 signaling pathways involved. we selected the top 20 biological processes (BP), cellular components (CC), molecular functions (MF) and signaling pathways to draw the heat maps, showing that Lipid and atherosclerosis signaling pathway, IL-17 signaling pathway, HIF-1 signaling pathway, relaxin signaling pathway and MAPK signaling pathway and other pathways may play a key role in the treatment of ONFH by YGY. The results of molecular docking showed that key effective components and corresponding core target proteins exhibited the good binding activity. YGY can treat ONFH through multicomponents, multitargets, and multipathways, which provides a reference for the subsequent research, development of targeted drugs and clinical application.

The extensive and intricate relationships between circadian rhythm and cancer have been reported in numerous studies. However, in breast cancer (BC), the potential role of circadian clock-related genes (CCRGs) in prognosis prediction has not been fully clarified. The transcriptome data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. A CCRGs-based risk signature was established by differential expression analysis, univariate, Lasso and multivariate Cox regression analyses. we conducted a gene set enrichment analysis (GSEA) between groups. A nomogram integrating independent clinical factors and risk score was generated and evaluated by calibration curves and decision curve analysis (DCA). Differentially expression analysis revealed 80 differentially expressed CCRGs, and 27 of them were significantly associated with the overall survival (OS) of BC. BC can be classified into 4 molecular subtypes with significant differences in prognosis based on the 27 CCRGs. Three prognostic CCRGs, including desmocollin 1 (DSC1), LEF1, and protocadherin 9 (PCDH9), were identified to be independent risk factors of BC prognosis and were used to construct a risk score model. BC patients were divided into high- and low-risk groups, and there were significant differences in prognosis between the 2 groups both in the training and validation cohorts. It was found that patients in different groups of race, status, or T stage had significant levels of risk score. Furthermore, patients of different risk levels exhibit varying degrees of sensitivity to vinorelbine, lapatinib, metformin, and vinblastine. GSEA showed that in the high-risk group, immune response-related activities were dramatically repressed whereas cilium-related processes were significantly stimulated. Cox regression analysis demonstrated that age, N stage, radiotherapy and the risk score were independent prognostic risk factors of BC, and a nomogram was established based on these variables. The nomogram exerted a favorable concordance index (0.798) as well as calibration performance, which strongly supports the clinical application of the nomogram. Our study indicated the disruption of the expression of CCRGs in BC and built a favorable prognostic risk model based on 3 independent prognostic CCRGs. These genes may be applied as candidate molecular targets for the diagnosis and therapy of BC.