A nomogram for predicting pathologic node negativity after neoadjuvant chemotherapy in breast cancer patients: a nationwide, multicenter retrospective cohort study (CSBrS-012).

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.

Efficacy of interventional therapy and effect on inflammatory factors in patients with gastric cancer after chemotherapy.

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.

Correlation analysis of mRNA expression and prognosis of hOGG1 gene polymorphism in patients with non-small cell lung cancer.

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.

Gene-gene interaction network analysis of hepatocellular carcinoma using bioinformatic software.

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).