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Purpose: This study aimed to investigate the factors associated with pathologic node-negativity (ypN0) in patients who received neoadjuvant chemotherapy (NAC) to develop and validate an accurate prediction nomogram. Methods: The CSBrS-012 study (2010-2020) included female patients with primary breast cancer treated with NAC followed by breast and axillary surgery in 20 hospitals across China. In the present study, 7,711 eligible patients were included, comprising 6,428 patients in the primary cohort from 15 hospitals and 1,283 patients in the external validation cohort from five hospitals. The hospitals were randomly assigned. The primary cohort was randomized at a 3:1 ratio and divided into a training set and an internal validation set. Univariate and multivariate logistic regression analyses were performed on the training set, after which a nomogram was constructed and validated both internally and externally. Results: In total, 3,560 patients (46.2%) achieved ypN0, and 1,558 patients (20.3%) achieved pathologic complete response in the breast (bpCR). A nomogram was constructed based on the clinical nodal stage before NAC (cN), ER, PR, HER2, Ki67, NAC treatment cycle, and bpCR, which were independently associated with ypN0. The area under the receiver operating characteristic curve (AUC) for the training set was 0.80. The internal and external validation demonstrated good discrimination, with AUCs of 0.79 and 0.76, respectively. Conclusion: We present a real-world study based on nationwide large-sample data that can be used to effectively screen for ypN0 to provide better advice for the management of residual axillary disease in breast cancer patients undergoing NAC.
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Level of mRNA expression and gene polymorphism of human 8-hydroxyguanine glycosidase 1 (hOGG1) in patients with non-small cell lung cancer (NSCLC) were investigated. A polymorphism analysis of hOGG1 gene rs1052133 locus in 182 NSCLC patients (NSCLC group) surgically treated in Xiang Yang No. 1 People's Hospital, Hubei University of Medicine from January 2008 to January 2012 and 200 healthy individuals (control group) was performed. The expression level of hOGG1 was compared between cancer tissues and adjacent tissues of NSCLC patients, and the survival rate was analyzed. The expression level of hOGG1 was significantly higher in cancer tissues than that in adjacent tissues (P<0.001). Taqman probe method was used to detect the genotypes of hOGG1 polymorphism locus rs1052133, with the genotype distribution frequencies of NSCLC group (P=0.411) and control group (P=0.354) consistent with the Hardy-Weinberg equilibrium. The proportion of C/C gene was significantly higher in NSCLC group than that in control group (P=0.008, OR=2.2, 95%, CI=1.27-4.52). The median value of the hOGG1 expression level in detection results as the boundary, NSCLC patients were divided into hOGG1 high expression group (≥3.61) with 91 cases and hOGG1 low expression group (<3.61) with 91 cases. The 1-, 2- and 3-year survival rates of patients in hOGG1 low expression group were significantly higher than those in hOGG1 high expression group (P=0.007). The 3-year survival rate in hOGG1 low expression group is significantly higher than that in hOGG1 high expression group (P=0.007). The sensitivity, specificity and AUC of hOGG1 to patient survival prediction were 83.33%, 64.29%, and 0.816, respectively. In conclusion, hOGG1 is highly expressed in NSCLC tissues. Compared to S/S and S/C genotypes, the C/C gene was found to be more common in NSCLC group than in control group. Thus, hOGG1 has a high predictive value for patient survival.
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The clinical effect of interventional therapy on gastric cancer after chemotherapy and effect on inflammatory factors in peripheral blood serum of patients were investigated. A retrospective analysis of 429 patients with gastric cancer treated in Xiangyang No. 1 People's Hospital, Hubei University of Medicine from July 2008 to December 2014 was performed. Among them, 220 patients received interventional therapy after chemotherapy as the experimental group, and 209 patients received conventional therapy as the control group. Serum carcinoembryonic antigen (CEA), tumor markers CA19-9, interleukin-6 (IL-6), interleukin-8 (IL-8) and interleukin-10 (IL-10) levels were measured before and after chemotherapy. The correlation between the concentration of CEA and CA19-9 before and after treatment and the levels of IL-6, IL-8 and IL-10 were analyzed in the experimental group, and all patients were followed up for 3 years. There were no significant differences in CEA, CA19-9, IL-6, IL-8 and IL-10 between the two groups before chemotherapy (P>0.05). After treatment, the concentrations of CEA, CA19-9, IL-6, IL-8 and IL-10 in the experimental group were significantly lower than those in the control group before and after treatment (P<0.05). The clinical efficacy and adverse reactions of the experimental group were significantly better than those in the control group (P<0.05). Pearson's correlation analysis showed that the concentrations of CEA and CA19-9 in the serum of the experimental group before and after treatment were positively correlated with the levels of IL-6, IL-8 and IL-10 (P<0.05). The 3-year overall survival rate of the study group was significantly higher than that of the control group (P<0.05). Cox regression analysis showed that age, Borrmann classification, degree of differentiation, and history of Helicobacter pylori infection were independent prognostic factors for patients with gastric cancer. Compared with traditional treatment, interventional therapy can greatly improve the recovery of gastric cancer patients after chemotherapy, reduce the occurrence of complications and inflammation, and improve the survival rate of patients.
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Information processing tools and bioinformatics software have markedly advanced the ability of researchers to process and analyze biological data. Data from the genomes of humans and model organisms aid researchers to identify topics to study, which in turn improves predictive accuracy, facilitates the identification of relevant genes and simplifies the validation of laboratory data. The objective of the present study was to investigate the regulatory network constituted by long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and mRNA in hepatocellular carcinoma (HCC). Microarray data from HCC datasets were downloaded from The Cancer Genome Atlas database, and the Limma package in R was used to identify the differentially expressed genes (DEGs) between HCC and normal samples. Gene ontology enrichment analysis of DEGs was conducted using the Database for Annotation, Visualization, and Integrated Discovery. TargetScan, microcosm, miRanda, miRDB and PicTar were used to predict target genes. lncRNAs associated with HCC were probed using the lncRNASNP database, and a lncRNA-miRNA-mRNA regulatory network was visualized using Cytoscape. The present study identified 114 differentially expressed miRNAs and 2,239 differentially expressed mRNAs; of these, 725 were downregulated genes that were primarily involved in complement and coagulation cascades, fatty acid metabolism and butanoate metabolism, among others. The remaining 1,514 were upregulated genes principally involved in DNA replication, oocyte meiosis and homologous recombination, among others. Through the integrated analysis of associations between different types of RNAs and target gene prediction, the present study identified 203 miRNA-mRNA pairs, including 28 miRNAs and 170 mRNAs, and identified 348 lncRNA-miRNA pairs, containing 28 miRNAs. Therefore, owing to the association between lncRNAs-miRNAs-mRNAs, the present study screened out 2,721 regulatory associations. The data in the present study provide a comprehensive bioinformatic analysis of genes, functions and pathways that may be involved in the pathogenesis of HCC.
