Myoepithelial Cells Influence on Triple-Negative Breast Cancer

Role of Myoepithelial Cells in Triple-Negative Breast Cancer

Myoepithelial cells are essential in maintaining the structural integrity and function of normal breast tissue. They act as a barrier between luminal epithelial cells and the surrounding stroma, secreting various factors that inhibit tumorigenesis. However, in the context of TNBC, MECs undergo significant alterations in function. Studies have shown that MECs in TNBC exhibit enhanced expression of proliferation-related genes like KRT14 and KRT17, while downregulating genes associated with inflammation and extracellular matrix remodeling (Yu et al., 2025). This functional reprogramming allows MECs to transition from tumor-suppressive roles to promoting tumor invasion and metastasis.

The loss of MECs has been correlated with worse clinical outcomes in TNBC patients, indicating their protective role against malignant transformation. The decreased presence of MECs in TNBC is associated with increased tumor cell invasiveness and a more aggressive tumor phenotype (Deussom et al., 2025). Therefore, investigating the mechanisms through which MECs influence TNBC progression is crucial for developing targeted therapeutic strategies.

Impact of Gene Expression Alterations in Tumor Microenvironment

The tumor microenvironment (TME) is composed of various cell types, including cancer cells, fibroblasts, endothelial cells, and immune cells, which interact dynamically to influence tumor behavior. Alterations in gene expression within the TME can significantly impact tumor development and response to treatment. In TNBC, MECs exhibit distinct gene expression profiles, with significant upregulation of genes related to cell proliferation and immune responses, which can facilitate tumor growth and immune evasion (Tian et al., 2025).

For instance, the expression of inflammatory cytokines and growth factors by MECs can create a favorable niche for tumor progression. The altered gene expression patterns in MECs can lead to enhanced recruitment of immune cells, contributing to a more immunosuppressive environment that allows tumor cells to thrive. Understanding these alterations is essential for identifying potential biomarkers and therapeutic targets for TNBC.

Prognostic Models Based on Myoepithelial Cell Genes

Prognostic models that incorporate the gene expression profiles of myoepithelial cells can provide valuable insights into patient outcomes in TNBC. Advanced modeling techniques, such as CoxBoost, have been employed to develop risk scores based on the expression of key myoepithelial cell genes. These models can stratify patients into high-risk and low-risk groups based on their likelihood of recurrence and overall survival (Tian et al., 2025).

For example, a CoxBoost-based prognostic model using gene expression data from TNBC cohorts demonstrated that high-risk patients exhibited enriched pathways related to the cell cycle and DNA replication, as well as reduced expression of immune checkpoint molecules. This highlights the potential of myoepithelial cell gene expression as a predictor of treatment response and disease progression in TNBC.

Table 1: Prognostic Model Performance Metrics

Cytotoxicity and Anti-Inflammatory Properties of Compounds

The search for effective therapies against TNBC has led to the exploration of compounds with cytotoxic and anti-inflammatory properties. Recent studies have synthesized multi-target esters derived from anti-inflammatory agents like ibuprofen, cinnamic acid, and salicylic acid, which have shown promising results in inhibiting tumor growth and modulating the tumor microenvironment (Deussom et al., 2025).

In vitro studies using the MTT assay demonstrated that these compounds possess varying degrees of cytotoxicity, with some exhibiting IC50 values as low as 0.002 mM, indicating their potential for use in TNBC treatment. Additionally, these compounds have been shown to inhibit nitric oxide production, a key mediator of inflammation, thereby reducing the inflammatory response associated with tumor progression.

Table 2: IC50 Values of Compounds Tested for Cytotoxicity

Advancements in Spatial Multiomics for Cancer Research

Recent advancements in spatial multiomics have provided unprecedented insights into the tumor microenvironment and cellular interactions in TNBC. Techniques such as spatial transcriptomics and metabolomics allow researchers to visualize gene expression and metabolite distribution within their native tissue context, enabling a better understanding of tumor biology (Neumann, 2025).

The integration of spatial metabolomics with transcriptomics and proteomics provides a comprehensive view of the molecular landscape in TNBC, aiding in the identification of novel therapeutic targets and biomarkers. Spatial multiomics is expected to reveal the complex interplay between myoepithelial cells and tumor cells, shedding light on their roles in tumor progression and response to treatment.

Table 3: Key Technologies in Spatial Multiomics

Frequently Asked Questions (FAQ)

What are myoepithelial cells?

Myoepithelial cells are specialized cells located between the basement membrane and epithelial cells in glandular tissues, including the breast. They play crucial roles in maintaining tissue structure and regulating cellular activities.

How do myoepithelial cells influence TNBC?

In TNBC, myoepithelial cells can undergo functional changes that promote tumor progression. They may alter their gene expression to support tumor growth, immune evasion, and metastasis.

What is a prognostic model in cancer research?

A prognostic model is a statistical tool that predicts patient outcomes, such as survival or recurrence risk, based on clinical and biological data, including gene expression profiles.

How can compounds derived from anti-inflammatory agents help in TNBC treatment?

Compounds derived from anti-inflammatory agents have shown cytotoxic effects on TNBC cells and can inhibit inflammatory processes that contribute to tumor growth, making them potential therapeutic candidates.

What is spatial multiomics?

Spatial multiomics is an integrative approach that combines various omics technologies—such as genomics, transcriptomics, proteomics, and metabolomics—to study biological systems in their native spatial context, providing a comprehensive understanding of cellular interactions and functions.

References

1. Deussom, P. M., Ewonkem, M. B., Mbock, M. A., Tiakouang, E. N., Toze, F. A., & Fotsing, M. C. D. (2025). Synthesis and biological evaluation of esterified anti-inflammatory drugs with ethylene glycol linkers: Cytotoxicity, anti-inflammatory and antioxidant properties. Royal Society Open Science. doi:10.1098/rsos.241413

2. Tian, Y., Yu, X., Zhang, R., & Yang, Y. (2025). Decoding the tumor microenvironment of myoepithelial cells in triple-negative breast cancer through single-cell and transcriptomic sequencing and establishing a prognostic model based on key myoepithelial cell genes. International Journal of Genomics. doi:10.1155/ijog/6454413

3. Neumann, E. K. (2025). Spatial Multiomics Toward Understanding Neurological Systems. Journal of Mass Spectrometry. doi:10.1002/jms.5143

4. Yu, X., Tian, Y., Zhang, R., & Yang, Y. (2025). Myoepithelial Cells Influence on Triple-Negative Breast Cancer. International Journal of Genomics. doi:10.1155/ijog/6454413