Open Access

ARTICLE

Identification of Molecular Subtypes and Prognostic Features for Triple-Negative Breast Cancer Based on Golgi Apparatus-Related Gene Signature

Zhun Yu^1,2, Jie Wang^1,2, Guoping Xu^1,2,*

1 Department of Breast, International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
2 Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, 200030, China

* Corresponding Author: Guoping Xu. Email:

(This article belongs to the Special Issue: Breast Cancer Biomarkers and Drug Targets Discoveries Towards a More Personalized Treatment Setting)

Oncology Research 2025, 33(8), 2013-2035. https://doi.org/10.32604/or.2025.061757

Received 02 December 2024; Accepted 15 April 2025; Issue published 18 July 2025

Abstract

Objectives: Triple-negative breast cancer (TNBC) presents a major treatment challenge due to its aggressive behavior. The dysfunction of the Golgi apparatus (GA) contributes to the development of various cancers. This study aimed to utilize GA-related genes (GARGs) to forecast the prognosis and immune profile of TNBC. Methods: The data were downloaded from The Cancer Genome Atlas (TCGA) database, including 175 TNBC and 99 healthy samples. The differentially expressed GARGs (DEGARGs) were analyzed using the TCGA biolinks package. The patients with TNBC were classified into two clusters utilizing the ConsensusClusterPlus package according to prognosis-related DEGARGs, followed by comparing the differences in prognosis and immune infiltration between the two clusters. Next, LASSO and stepwise Cox regression were applied to establish a GARGs signature to forecast the TNBC prognosis. The association of the GARGs signature with immune infiltrates and drug sensitivity was further explored. Results: In total, 430 DEGARGs were identified between TNBC and healthy samples, among which 20 were related to TNBC prognosis. Two GARG-related molecular clusters associated with different survival times and immune heterogeneity were identified. A risk model for TNBC was established based on six GARGs, and the high-risk (HR) group exhibited a poor prognosis. The HR group demonstrated a distinctly high M2 macrophage infiltration and low M1 macrophage infiltration, which contributed to an immunosuppressive tumor microenvironment and thus led to poor prognosis of the HR group. Immune dysfunction scores and programmed cell death ligand 1 (PD-L1) expression were substantially elevated in the HR group. The HR group showed increased sensitivity to anticancer drugs, such as cisplatin. Conclusion: Our findings suggest that GARGs are involved in the pathogenesis of TNBC and provide new insights into prognostic prediction. The identified clusters and GARGs signatures have the potential to guide individualized therapy.

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Keywords

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Supplementary Material

Supplementary Material File

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