| 描述信息 |
Mechanical stress, simulated by matrix application, enhanced LUAD cell migration and invasion, correlating with ECM alterations and EMT pathway activation. Machine learning-based SVM_Score predicted LUAD patient prognosis across multiple datasets, revealing its robust prognostic capabilities. Lower SVM_Scores were associated with worse survival outcomes, increased cancer-related pathways, higher Tumor Mutation Burden, and altered immune microenvironment characteristics. SVM_Score was also linked to myofibroblast-secreted COL5A1, a key marker for mechanical stress. Patient tissues with low SVM_Scores exhibited higher COL5A1 expression, enhanced EMT propensity, and increased internal mechanical stress. Sorafenib, by inhibiting COL5A1 secretion, attenuated the pro-tumor effects of myofibroblasts, rendering LUAD cells more sensitive to chemotherapy. |
