Cuproptosis Engages in C-Myc-mediated Breast Cancer Stemness

Overview

Journal J Transl Med

Publisher Biomed Central

Specialties Biomedical Engineering
General Medicine

Date 2023 Jun 23

PMID 37353799

Authors

Runtian Wang

Kun Xu

Qin Chen

Qin Hu

Jian Zhang

Xiaoxiang Guan

Affiliations

Soon will be listed here.

Abstract

Background: Intra-tumoral heterogeneity (ITH) is a distinguished hallmark of cancer, and cancer stem cells (CSCs) contribute to this malignant characteristic. Therefore, it is of great significance to investigate and even target the regulatory factors driving intra-tumoral stemness. c-Myc is a vital oncogene frequently overexpressed or amplified in various cancer types, including breast cancer. Our previous study indicated its potential association with breast cancer stem cell (BCSC) biomarkers.

Methods: In this research, we performed immunohistochemical (IHC) staining on sixty breast cancer surgical specimens for c-Myc, CD44, CD24, CD133 and ALDH1A1. Then, we analyzed transcriptomic atlas of 1533 patients with breast cancer from public database.

Results: IHC staining indicated the positive correlation between c-Myc and BCSC phenotype. Then, we used bioinformatic analysis to interrogate transcriptomics data of 1533 breast cancer specimens and identified an intriguing link among c-Myc, cancer stemness and copper-induced cell death (also known as "cuproptosis"). We screened out cuproptosis-related characteristics that predicts poor clinical outcomes and found that the pro-tumoral cuproptosis-based features were putatively enriched in MYC-targets and showed a significantly positive correlation with cancer stemness.

Conclusion: In addition to previous reports on its oncogenic roles, c-Myc showed significant correlation to stemness phenotype and copper-induced cell toxicity in breast cancer tissues. Moreover, transcriptomics data demonstrated that pro-tumoral cuproptosis biomarkers had putative positive association with cancer stemness. This research combined clinical samples with large-scale bioinformatic analysis, covered description and deduction, bridged classic oncogenic mechanisms to innovative opportunities, and inspired the development of copper-based nanomaterials in targeting highly heterogeneous tumors.

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