{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T11:26:58Z","timestamp":1786706818981,"version":"build-2736575974"},"reference-count":67,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T00:00:00Z","timestamp":1770076800000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["H2020406049"],"award-info":[{"award-number":["H2020406049"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The study is to investigate differential signaling pathways within the tumor microenvironment across molecular subtypes of breast cancer (BC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Single\u2010cell RNA (scRNA\u2010seq) sequencing data of BC samples were obtained from the Gene Expression Omnibus database. Cell types were identified using the SingleR package, in conjunction with the analysis of marker genes. Subsequently, Monocle was used for pseudotime analysis of epithelial cells, fibroblasts, and macrophages to characterize their differentiation states. CellChat was employed to study the ligand\u2010receptor interactions among various cell types across different BC molecular subtypes. In addition, we used common bulk RNA sequencing data from The Cancer Genome Atlas to investigate the correlation between key signaling pathway factors identified by scRNA\u2010seq and clinical outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Inference of copy number variation analysis using T cells revealed significantly elevated copy number variation scores in epithelial cells and fibroblasts. In the communication between epithelial cells and fibroblasts, the ANGPTL pathway is critical in estrogen receptor\u2010positive breast cancer (ER+BC), while the PTN pathway plays a key role in both ER+BC and human epidermal growth factor receptor 2\u2010positive breast cancer (HER2+BC), and the GAS pathway is associated with poor prognosis in triple\u2010negative breast cancer (TNBC). In the interaction between fibroblasts and macrophages, the macrophage subpopulation supporting tumor angiogenesis exhibits significant activity in ER+BC, with the associated SPP1 and GRN pathways strongly influencing tumor progression. The SEMA3 pathway mainly acts through dividing tumor\u2010associated fibroblast clusters across all BC subtypes. When exploring the role of lymphocytes, the PTN pathway also plays a role in HER2+BC, while in TNBC, CXCL and CD70 pathways are significantly involved in immune response modulation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our comprehensive analysis of cell\u2013cell communication networks among epithelial cells, fibroblasts, macrophages, and lymphocytes across BC subtypes focuses on ligand\u2010receptor interactions. This study revealed that certain molecules within these networks exhibit significant prognostic value and therapeutic promise.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cam4.71600","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T05:52:18Z","timestamp":1770184338000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Single\u2010Cell\n                    <scp>RNA<\/scp>\n                    Sequencing and Bulk\n                    <scp>RNA<\/scp>\n                    Sequencing Revealed the Interplay Between Intratumoral Heterogeneity and the Tumor Microenvironment in Breast Cancer"],"prefix":"10.1002","volume":"15","author":[{"given":"Yunlong","family":"Zhao","sequence":"first","affiliation":[{"name":"Laboratory of Gene Engineering and Genomics, School of Basic Medical Sciences Chengde Medical University  Chengde China"},{"name":"Graduate School of Chengde Medical 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