Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response
BackgroundThe tumor boundary of breast cancer represents a highly heterogeneous region. In this area, the interactions between malignant and non-malignant cells influence tumor progression, immune evasion, and drug resistance. However, the spatial transcriptional profile of the tumor boundary and it...
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Frontiers Media S.A.
2025-03-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2025.1570696/full |
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| author | Yuanyuan Wu Youyang Shi Zhanyang Luo Xiqiu Zhou Yonghao Chen Xiaoyun Song Sheng Liu |
| author_facet | Yuanyuan Wu Youyang Shi Zhanyang Luo Xiqiu Zhou Yonghao Chen Xiaoyun Song Sheng Liu |
| author_sort | Yuanyuan Wu |
| collection | DOAJ |
| description | BackgroundThe tumor boundary of breast cancer represents a highly heterogeneous region. In this area, the interactions between malignant and non-malignant cells influence tumor progression, immune evasion, and drug resistance. However, the spatial transcriptional profile of the tumor boundary and its role in the prognosis and treatment response of breast cancer remain unclear.MethodUtilizing the Cottrazm algorithm, we reconstructed the intricate boundaries and identified differentially expressed genes (DEGs) associated with these regions. Cell-cell co-positioning analysis was conducted using SpaCET, which revealed key interactions between tumor-associated macrophage (TAMs) and cancer-associated fibroblasts (CAFs). Additionally, Lasso regression analysis was employed to develop a malignant body signature (MBS), which was subsequently validated using the TCGA dataset for prognosis prediction and treatment response assessment.ResultsOur research indicates that the tumor boundary is characterized by a rich reconstruction of the extracellular matrix (ECM), immunomodulatory regulation, and the epithelial-to-mesenchymal transition (EMT), underscoring its significance in tumor progression. Spatial colocalization analysis reveals a significant interaction between CAFs and M2-like tumor-associated macrophage (TAM), which contributes to immune exclusion and drug resistance. The MBS score effectively stratifies patients into high-risk groups, with survival outcomes for patients exhibiting high MBS scores being significantly poorer. Furthermore, drug sensitivity analysis demonstrates that high-MB tumors had poor response to chemotherapy strategies, highlighting the role of the tumor boundary in modulating therapeutic efficacy.ConclusionCollectively, we investigate the spatial transcription group and bulk data to elucidate the characteristics of tumor boundary molecules in breast cancer. The CAF-M2 phenotype emerges as a critical determinant of immunosuppression and drug resistance, suggesting that targeting this interaction may improve treatment responses. Furthermore, the MBS serves as a novel prognostic tool and offers potential strategies for guiding personalized treatment approaches in breast cancer. |
| format | Article |
| id | doaj-art-bdaacddf119441eb8bb68d9045177848 |
| institution | DOAJ |
| issn | 2296-634X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj-art-bdaacddf119441eb8bb68d90451778482025-08-20T02:40:48ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2025-03-011310.3389/fcell.2025.15706961570696Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy responseYuanyuan Wu0Youyang Shi1Zhanyang Luo2Xiqiu Zhou3Yonghao Chen4Xiaoyun Song5Sheng Liu6Department of Breast Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaDepartment of Breast Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaShanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, ChinaDepartment of Breast Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaWest China Hospital of Sichuan University, Chengdu, ChinaDepartment of Breast Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaDepartment of Breast Surgery, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaBackgroundThe tumor boundary of breast cancer represents a highly heterogeneous region. In this area, the interactions between malignant and non-malignant cells influence tumor progression, immune evasion, and drug resistance. However, the spatial transcriptional profile of the tumor boundary and its role in the prognosis and treatment response of breast cancer remain unclear.MethodUtilizing the Cottrazm algorithm, we reconstructed the intricate boundaries and identified differentially expressed genes (DEGs) associated with these regions. Cell-cell co-positioning analysis was conducted using SpaCET, which revealed key interactions between tumor-associated macrophage (TAMs) and cancer-associated fibroblasts (CAFs). Additionally, Lasso regression analysis was employed to develop a malignant body signature (MBS), which was subsequently validated using the TCGA dataset for prognosis prediction and treatment response assessment.ResultsOur research indicates that the tumor boundary is characterized by a rich reconstruction of the extracellular matrix (ECM), immunomodulatory regulation, and the epithelial-to-mesenchymal transition (EMT), underscoring its significance in tumor progression. Spatial colocalization analysis reveals a significant interaction between CAFs and M2-like tumor-associated macrophage (TAM), which contributes to immune exclusion and drug resistance. The MBS score effectively stratifies patients into high-risk groups, with survival outcomes for patients exhibiting high MBS scores being significantly poorer. Furthermore, drug sensitivity analysis demonstrates that high-MB tumors had poor response to chemotherapy strategies, highlighting the role of the tumor boundary in modulating therapeutic efficacy.ConclusionCollectively, we investigate the spatial transcription group and bulk data to elucidate the characteristics of tumor boundary molecules in breast cancer. The CAF-M2 phenotype emerges as a critical determinant of immunosuppression and drug resistance, suggesting that targeting this interaction may improve treatment responses. Furthermore, the MBS serves as a novel prognostic tool and offers potential strategies for guiding personalized treatment approaches in breast cancer.https://www.frontiersin.org/articles/10.3389/fcell.2025.1570696/fullbreast cancerspatial transcriptomicstumor boundaryCAF-M2 interactiontherapy resistanceprognostic model |
| spellingShingle | Yuanyuan Wu Youyang Shi Zhanyang Luo Xiqiu Zhou Yonghao Chen Xiaoyun Song Sheng Liu Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response Frontiers in Cell and Developmental Biology breast cancer spatial transcriptomics tumor boundary CAF-M2 interaction therapy resistance prognostic model |
| title | Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response |
| title_full | Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response |
| title_fullStr | Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response |
| title_full_unstemmed | Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response |
| title_short | Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response |
| title_sort | spatial multi omics analysis of tumor stroma boundary cell features for predicting breast cancer progression and therapy response |
| topic | breast cancer spatial transcriptomics tumor boundary CAF-M2 interaction therapy resistance prognostic model |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2025.1570696/full |
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