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Abstract Background Inter- and intra-tumor heterogeneity is considered a significant factor contributing to the development of endocrine resistance in breast cancer. Recent advances in single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) allow us to explore inter- and intra-tumor heterogeneity at single-cell resolution. However, such integrated single-cell analysis has not yet been demonstrated to characterize the transcriptome and chromatin accessibility in breast cancer endocrine resistance. Methods In this study, we conducted an integrated analysis combining scRNA-seq and scATAC-seq on more than 80,000 breast tissue cells from two normal tissues (NTs), three primary tumors (PTs), and three tamoxifen-treated recurrent tumors (RTs). A variety of cell types among breast tumor tissues were identified, PT- and RT-specific cancer cell states (CSs) were defined, and a heterogeneity-guided core signature (HCS) was derived through such integrated analysis. Functional experiments were performed to validate the oncogenic role of BMP7, a key gene within the core signature. Results We observed a striking level of cell-to-cell heterogeneity among six tumor tissues and delineated the primary to recurrent tumor progression, underscoring the significance of these single-cell level tumor cell clusters classified from scRNA-seq data. We defined nine CSs, including five PT-specific, three RT-specific, and one PT-RT-shared CSs, and identified distinct open chromatin regions of CSs, as well as a HCS of 137 genes. In addition, we predicted specific transcription factors (TFs) associated with the core signature and novel biological/metabolism pathways that mediate the communications between CSs and the tumor microenvironment (TME). We finally demonstrated that BMP7 plays an oncogenic role in tamoxifen-resistant breast cancer cells through modulating MAPK signaling pathways. Conclusions Our integrated single-cell analysis provides a comprehensive understanding of the tumor heterogeneity in tamoxifen resistance. We envision this integrated single-cell epigenomic and transcriptomic measure will become a powerful approach to unravel how epigenetic factors and the tumor microenvironment govern the development of tumor heterogeneity and to uncover potential therapeutic targets that circumvent heterogeneity-related failures.

Background: Inter- and intra-tumor heterogeneity is considered a significant factor contributing to the development of endocrine resistance in breast cancer. Recent advances in single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) allow us to explore inter- and intra-tumor heterogeneity at single-cell resolution. However, such integrated single-cell analysis has not yet been demonstrated to characterize the transcriptome and chromatin accessibility in breast cancer endocrine resistance. Methods: In this study, we conducted an integrated analysis combining scRNA-seq and scATAC-seq on more than 80,000 breast tissue cells from two normal tissues (NTs), three primary tumors (PTs), and three tamoxifen-treated recurrent tumors (RTs). A variety of cell types among breast tumor tissues were identified, PT- and RT-specific cancer cell states (CSs) were defined, and a heterogeneity-guided core signature (HCS) was derived through such integrated analysis. Functional experiments were performed to validate the oncogenic role of BMP7, a key gene within the core signature. Results: We observed a striking level of cell-to-cell heterogeneity among six tumor tissues and delineated the primary to recurrent tumor progression, underscoring the significance of these single-cell level tumor cell clusters classified from scRNA-seq data. We defined nine CSs, including five PT-specific, three RT-specific, and one PT-RT-shared CSs, and identified distinct open chromatin regions of CSs, as well as a HCS of 137 genes. In addition, we predicted specific transcription factors (TFs) associated with the core signature and novel biological/metabolism pathways that mediate the communications between CSs and the tumor microenvironment (TME). We finally demonstrated that BMP7 plays an oncogenic role in tamoxifen-resistant breast cancer cells through modulating MAPK signaling pathways. Conclusions: Our integrated single-cell analysis provides a comprehensive understanding of the tumor heterogeneity in tamoxifen resistance. We envision this integrated single-cell epigenomic and transcriptomic measure will become a powerful approach to unravel how epigenetic factors and the tumor microenvironment govern the development of tumor heterogeneity and to uncover potential therapeutic targets that circumvent heterogeneity-related failures. [ABSTRACT FROM AUTHOR]

Breast cancer is a complex and heterogeneous disease with varying cellular, genetic, epigenetic, and molecular expressions. The detection of intratumor heterogeneity in breast cancer poses significant challenges due to its complex multifaceted characteristics, yet its identification is crucial for guiding effective treatment decisions and understanding the disease progression. Currently, there exists no method capable of capturing the full extent of breast tumor heterogeneity. In this study, the aim is to identify and characterize metabolic heterogeneity in breast tumors using immune cells and an ultrafast laser-fabricated Immuno Nano Sensor. Combining spectral markers from both Natural Killer (NK) and T cells, a machine-learning approach is implemented to distinguish cancer from healthy samples, identify primary versus metastatic tumors, and determine estrogen receptor (ER)/progesterone receptor (PR) status at the single-cell level. The platform successfully distinguished heterogeneous breast cancer samples from healthy individuals, achieving 97.8% sensitivity and 92.2% specificity, and accurately identified primary tumors from metastatic tumors. Characteristic spectral signatures allow for discrimination between ER/PR-positive and negative tumors with 97.5% sensitivity. This study demonstrates the potential of immune cell-based metabolic profiling in providing a comprehensive assessment of breast tumor heterogeneity and paving the way for minimally invasive liquid biopsy approaches in breast cancer diagnosis and management., (© 2024 The Author(s). Small published by Wiley‐VCH GmbH.)