Deciphering Cell-Cell Interactions in Triple-Negative Breast Cancer

Breast cancers are clinically stratified based on the expression of the estrogen receptor (ER), progesterone receptor (PR), and the overexpression or amplification of HER2 (ERBB2). This classification results in three primary subtypes that not only correlate with prognosis but also dictate treatment strategies: Luminal (ER+, PR+/-), HER2+ (HER2+, ER+/-, PR+/-), and triple-negative breast cancer (TNBC; ER-, PR-, HER2-). TNBC comprises 10%-20% of all breast cancers and often exhibits higher rates of early distant recurrence and a poorer 5-year prognosis compared to other subtypes.TNBC is notably heterogeneous. Our understanding of the cellular heterogeneity and tissue architecture of human breast cancers has largely stemmed from histological studies, bulk sequencing, low-dimensional hypothesis-based research, and experimental models. However, recent advancements in single-cell RNA sequencing (scRNA-Seq) and spatially resolved transcriptomics (SRT) present new opportunities to comprehensively characterize the cellular landscape of tumors, offering novel insights into cell biology, disease etiology, and drug response. The development of tumors is intricately linked to complex cell-cell interactions (CCIs). Recently, proximity labeling strategies have emerged as valuable tools in characterizing these interactions, combining detection, separation, and downstream analysis through in-situ labeling with enzymes or chemical molecules. Such neighborhood labeling strategies have advanced the detection of specific CCIs, particularly in tumor-immune cell interactions.
Therefore, the primary objective of this Research Topic is to enhance our understanding of CCIs in TNBC. We invite original studies that focus on unraveling the spatial architecture of the tumor microenvironment to reveal CCIs in TNBC. Review articles addressing these themes are also encouraged. By fostering research in these areas, we aim to advance the field and contribute to improved therapeutic strategies for TNBC.

Topics of interest include, but are not limited to:
1. Molecular mechanisms underlying the crosstalk between tumor cells and immune cells in TNBC.
2. Advancements in precise immunotherapeutic strategies targeting CCIs in TNBC.
3. Development of new algorithms for efficient data processing and precise cell classification in spatial transcriptomics to reconstruct cell interaction patterns.
4. Innovative strategies for monitoring cell-cell interactions.
5. Visualization of gene expression patterns in two-dimensional slices or interactive exploration of molecular features and spatial morphology in three-dimensional space specific to TNBC.

Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of the scope for this section and will not be accepted as part of this Research Topic.