Related Experiment Video
Updated: Jun 13, 2026

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer
Published on: March 14, 2019
Predictive and Prognostic Value of TRIM58 Protein Expression in Patients with Breast Cancer Receiving Neoadjuvant
Yi-Zi Zheng1, Jia-Ying Li2,3, Lv-Wen Ning3
1Department of Thyroid and Breast Surgery, Shenzhen Breast Tumor Research Center for Diagnosis and Treatment, the First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen University, Shenzhen, Guangdong, People's Republic of China.
Introduction:
Tripartite motif-containing protein (TRIM) family members play crucial roles in carcinogenesis and chemotherapy resistance. In this study, we aimed to determine whether TRIM58 protein expression is related to patient responses to neoadjuvant therapy (NAT) and their survival outcome.
Methods:
Immunohistochemistry was performed on female breast cancer samples from biopsies before NAT in Shenzhen Second People's Hospital. Univariate and multivariate logistic regression tests were used to analyze the association between TRIM58 protein expression and pathological complete response (pCR). The Cox proportional hazards model was used to calculate the adjusted hazard ratio (HR) with a 95% confidence interval (95% CI). The Kaplan-Meier plotter database was used to analyze the prognostic value of TRIM58.
Results:
High TRIM58 expression was associated with small tumor size in all the patients (n = 58). Multivariate analysis suggested that low TRIM58 expression was an independent predictive factor for higher pCR (odds ratio = 0.06, 95% CI 0.005-0.741, P = 0.028). The Kaplan-Meier Plotter dataset suggested that the TRIM58 high-expression group showed a worse 5-year overall survival than the low-expression group (HR = 1.34, 95% CI 1.07-1.67, P = 0.01). Pathway analysis revealed the potential mechanisms of TRIM58 in chemoresistance.
Discussion:
Our study suggests that TRIM58 is a promising biomarker for both neoadjuvant chemosensitivity and long-term clinical outcomes in breast cancer. It may also help to identify candidate responders and determine treatment strategies.
More Related Videos
07:41Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
07:47Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies
Published on: September 15, 2023