Clinical and Translational Research
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Feb 24, 2024; 15(2): 208-242
Published online Feb 24, 2024. doi: 10.5306/wjco.v15.i2.208
Elucidating the molecular basis of ATP-induced cell death in breast cancer: Construction of a robust prognostic model
Hao-Ling Zhang, Sandai Doblin, Zhong-Wen Zhang, Zhi-Jing Song, Babu Dinesh, Yasser Tabana, Dahham Sabbar Saad, Mowaffaq Adam Ahmed Adam, Yong Wang, Wei Wang, Hao-Long Zhang, Sen Wu, Rui Zhao, Barakat Khaled
Hao-Ling Zhang, Sandai Doblin, Department of Biomedical Sciences, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Penang 13200, Malaysia
Zhong-Wen Zhang, School of Public Health, Gansu University of Chinese Medicine, Lanzhou 730000, Gansu Province, China
Zhi-Jing Song, Rui Zhao, Clinical College of Chinese Medicine, Gansu University of Chinese Medicine, Lanzhou 730000, Gansu Province, China
Babu Dinesh, Yasser Tabana, Barakat Khaled, Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton AB T6G 2E1, Canada
Dahham Sabbar Saad, Department of Science, University of Technology and Applied Sciences Rustaq, Rustaq 10 P.C. 329, Oman
Mowaffaq Adam Ahmed Adam, Department of Chemistry and Biochemistry, San Diego State University, San Diego, CA 92182, United States
Yong Wang, Department of Pathology Center, Gansu University of Chinese Medicine, Lanzhou 730000, Gansu Province, China
Wei Wang, College of Acupuncture-moxibustion and Tuina, Gansu University of Chinese Medicine, Lanzhou 730000, Gansu Province, China
Hao-Long Zhang, Universiti Sains Malaysia, Advanced Medical and Dental Institute, Penang 13200, Malaysia
Sen Wu, Department of Biomedical Science, Universiti Sains Malaysia, Penang 13200, Malaysia
Co-corresponding authors: Sandai Doblin and Song Zhi-Jing.
Author contributions: Zhang HL was responsible for drafting the primary manuscript and conducting the data analyses; Dinesh B, Tabana Y, Saad DS, Adam Ahmed Adam M, Zhang HL, Zhao R, Barakat K, Wang Y, and Wang W were involved in the data collection, and preparation of tables and charts; Sandai D, Zhang ZW, and Song ZJ had pivotal roles in the research design, guiding the research group, and orchestrating the collaborative efforts of all authors; Sandai D and Song ZJ gave detailed guidance on the paper; All authors have read and approved the final manuscript.
Supported by National Natural Science Foundation of China, No. 81960877; University Innovation Fund of Gansu Province, No. 2021A-076; Gansu Province Science and Technology Plan (Innovation Base and Talent Plan), No. 21JR7RA561; Natural Science Foundation of Gansu Province, No. 21JR1RA267 and No. 22JR5RA582; Education Technology Innovation Project of Gansu Province, No. 2022A-067; Innovation Fund of Higher Education of Gansu Province, No. 2023A-088; Gansu Province Science and Technology Plan International Cooperation Field Project, No. 23YFWA0005; and Open Project of Key Laboratory of Dunhuang Medicine and Transformation of Ministry of Education, No. DHYX21-07, No. DHYX22-05, and No. DHYX21-01.
Institutional review board statement: No experimental studies on human and animal ethics were designed in this study.
Informed consent statement: This study did not conduct clinical trials and did not involve informed consent signed by subjects and investigators.
Conflict-of-interest statement: The authors have no conflicts of interest to declare.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at [doblin@usm.my]. Participants gave informed consent for data sharing.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Sandai Doblin, PhD, Professor, Department of Biomedical Sciences, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Kepala Batas, Penang 13200, Malaysia. doblin@usm.my
Received: September 8, 2023
Peer-review started: September 8, 2023
First decision: November 30, 2023
Revised: December 10, 2023
Accepted: January 12, 2024
Article in press: January 12, 2024
Published online: February 24, 2024
Processing time: 165 Days and 6.7 Hours
ARTICLE HIGHLIGHTS
Research background

ATP-induced cell death (AICD) is a unique mode of cell death caused by high levels of extracellular ATP and is closely linked to various cancer advancements. It has a dual impact on breast cancer by participating in the regulation of death pathways and leading to increased extracellular ATP levels, creating an interconnected regulatory loop. AICD is a pivotal mechanism regulated by genes and microRNAs (miRNAs), contributing to breast cancer progression. However, the precise nature of their interactions requires further research. Manipulating ATP levels and receptors can alter breast cancer cell proliferation, invasion, and metastasis, highlighting the potential for AICD in breast cancer treatment. AICD is a multifaceted process, with overarching mechanisms including purinergic receptor activation, particularly P2X purinoceptor 7 receptor (P2X7R), elevation of intracellular calcium ion concentration, inflammatory responses, and mitochondrial function disruption. miRNAs are key regulators of gene expression, functioning as either tumor suppressors or promoters, and their expression can be influenced by ATP levels. The relationship between AICD and miRNA involves two distinct mechanisms: miRNA targeting of essential genes in ATP-related signaling pathways and alterations in ATP levels influencing miRNA expression. Prognostic models, both gene and miRNA-based, are valuable for personalized treatment and prognosis assessment despite their limitations. The concurrent use of both models may provide a more comprehensive understanding of cancer prognosis.

Research motivation

No studies to date have investigated the impact of AICD regulatory mechanisms in breast cancer. Therefore, the primary goal of this paper was to look into the potential prognostic importance of AICD genes in breast cancer, as well as the interaction among AICD genes and prognostic gene-associated miRNAs in breast cancer.

Research objectives

This study conducted a comprehensive investigation into the primary mechanism underlying AICD and performed an in-depth analysis of the associated mRNA expression patterns. Notably, mRNA and miRNA characteristic models were successfully established and specifically tailored to AICD, both of which exhibit potential as independent prognostic factors. Leveraging these two models achieved heightened precision in estimating patient survival status and simplified the decision-making process regarding relevant therapeutic interventions. Consequently, the findings offer a robust scientific foundation for comprehending the fundamental logic governing cell death. Moreover, the clinical implications of this research are highly significant, as they shed light on the regulatory mechanisms of cell death and provide valuable guidance for the treatment and prognosis evaluation of breast cancer.

Research methods

The foundational genes orchestrating AICD mechanisms were extracted from the scholarly literature, underpinning the establishment of a prognostic model. Simultaneously, a miRNA prognostic model was constructed that mirrored the gene-based prognostic model. Distinctions between high and low-risk cohorts within mRNA and miRNA characteristic models were scrutinized, with the aim of delineating common influence mechanisms, substantiated through enrichment analysis and immune infiltration assessment.

Research results

The mRNA prognostic model in this study encompassed four specific mRNAs—P2X4, pannexin 1, caspase 7, and cyclin D2. The miRNA prognostic model integrated four pivotal miRNAs: hsa-miR-615-3p, hsa-miR-519b-3p, hsa-miR-342-3p, and hsa-miR-324-3p. B cells, CD4+ T cells, CD8+ T cells, endothelial cells, and macrophages exhibited inverse correlations with risk scores across all breast cancer subtypes. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis revealed that genes differentially expressed in response to mRNA risk scores significantly enriched 25 signaling pathways, while miRNA risk scores significantly enriched 29 signaling pathways, with 16 pathways being jointly enriched.

Research conclusions

This study conducted a comprehensive investigation into the primary mechanism underlying AICD and performed an in-depth analysis of the associated mRNA expression patterns. Notably, mRNA and miRNA characteristic models were successfully established and specifically tailored to AICD, both of which exhibit potential as independent prognostic factors. Leveraging these two models achieved heightened precision in estimating patient survival status and simplified the decision-making process regarding relevant therapeutic interventions. Consequently, the findings offer a robust scientific foundation for comprehending the fundamental logic governing cell death. Moreover, the clinical implications of this research are highly significant, as they shed light on the regulatory mechanisms of cell death and provide valuable guidance for the treatment and prognosis evaluation of breast cancer.

Research perspectives

Future investigations need to allocate greater focus on the examination, analysis, and discourse of discrete cancer cells, in order to reach more exacting insights. Recognizing the fact that the domain of cancer research is inherently rooted in single-cell substrates, it is imperative to note that a dearth of single-cell analyses for individual patients could potentially undermine the comprehensive nature of these studies. Subsequent to this, the primary objectives include giving precedence to functional insights at the single-cell level, thereby ensuring that later research provides actionable and targeted insights.