Unraveling Benign and Malignant Tumor Heterogeneity Through Spatial Transcriptomics

Breast cancer is one of the most common malignant tumors among women worldwide, and its high heterogeneity poses significant challenges for early diagnosis and precise treatment. Despite the continuous development of molecular typing and targeted therapy, how to precisely distinguish the benign and malignant regions of tumors at the spatial level and analyze their molecular characteristics remains an urgent problem to be solved. This study is based on spatial transcriptomics technology on the 10x Genomics Visium platform. Systematic transcriptional analyses were conducted on human breast cancer tissue sections. Through differential expression analysis of DCIS/LCIS and IDC regions, a total of 1,143 significantly differentially expressed genes were identified, among which genes such as S100A6, STC2, and TFF3 were significantly upregulated in breast cancer progression, suggesting a key role in malignant transformation of tumors. Gene ontology enrichment analysis revealed that the differentially expressed genes were significantly aggregated in key functional modules such as metabolic pathways, MAPK signaling pathways, cell cycle and cancer-related pathways. in particular, the significant enrichment of the Rap1 signaling pathway and Pathways in cancer revealed the synergistic activation mechanism of multi-level biological processes such as cell adhesion, migration, and matrix degradation during the transformation of breast cancer from benign to malignant. In summary, this study revealed the molecular heterogeneity in the benign and malignant regions of breast cancer and the spatial distribution characteristics of key signaling pathways at the tissue level through spatial transcriptomics, providing new theoretical basis and spatial omics evidence for spatial molecular typing of breast cancer, targeted drug development, and optimization of individualized treatment strategies.