Identification and Validation of Golgi Apparatus-Related Signature for Predicting Prognosis and Immunotherapy Response in Breast Cancer

Author:

Chen Xin1,Tang Pengting2,Kong Ying1,Chen Deqin1,Tang Kejun1

Affiliation:

1. Women's Hospital School of Medicine Zhejiang University

2. Ninghai Maternity and Child Care Hospital

Abstract

Abstract Background: The Golgi apparatus plays a pivotal role in various aspects of cancer. This study aims to investigate the predictive value of Golgi apparatus-related genes (GARGs) in breast cancer prognosis and immunotherapy response evaluation. Methods: Transcriptional and clinical data from the TCGA-BRCA cohort and GSE96058 cohort were utilized to construct and validate a prognostic model for breast cancer using Cox regression analysis. Differences in immune landscape, somatic mutations, gene expression, drug sensitivity, and immunotherapy response between different risk groups were assessed. A prognostic nomogram for breast cancer was further developed and evaluated. qPCR and single-cell sequencing analysis were performed to validate the expression of GARGs. Results: A total of 394 GARGs significantly associated with breast cancer prognosis were identified, leading to the construction of a prognostic risk feature comprising 10 GARGs. This feature effectively stratified breast cancer patients into high-risk and low-risk groups, with the high-risk group exhibiting significantly worse prognosis. Meanwhile, significant differences in cliniopathological features, immune infiltration, drug sensitivity, and immunotherapy response were observed between the high- and low-risk groups. The constructed nomogram incorporating these factors showed superior performance in prognostic assessment for breast cancer patients. Ultimately, the utilization of qPCR and single-cell sequencing techniques substantiated the disparate expression patterns of these prognostic genes in breast cancer. Conclusions: Our findings demonstrate that a prognostic risk feature derived from GARGs holds promising application potential for predicting prognosis and evaluating immunotherapy response in breast cancer patients.

Publisher

Research Square Platform LLC

Reference33 articles.

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