Elucidating the molecular basis of ATP-induced cell death in breast cancer: Construction of a robust prognostic model

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.