Validation of the effects of TGF-β1 on tumor recurrence and prognosis through tumor retrieval and cell mechanical properties

Abstract

Abstract Background In vivo, the transforming growth factor-beta1 (TGF-β1)-induced epithelial to mesenchymal transition (EMT) occurs in seconds during cancer cells intravasation and extravasation. Although it has been established that cellular stiffness can change as a cancer cell transformed, the precise relationship between TGF-β1-induced mesenchymal stem cell mechanics and cancer prognosis remains unclear. Accordingly, it is hard to define the effects of EMT on cell mechanical properties (CMs), tumor recurrence and metastasis risks. This study bridges physical and pathological disciplines to reconcile single-cell mechanical measurements of tumor cells. Methods and results We developed a microplate measurement system (MMS) and revealed the intrinsic divergent tumor composition of retrieval cells by cell stiffness and adhesion force and flow cytometry analysis. After flow cytometry sorting, we could measure the differences in CMs of the Sca-1+-CD44+ (mesenchymal-stem-cell-type) and the other subgroups. As well as the stiffer and heterogeneous compositions among tumor tissues with higher recurrence risk were depicted by MMS and atomic force microscopy (AFM). An in vitro experiment validated that Lewis lung carcinoma (LLC) cells acquired higher CMs and motility after EMT, but abrogated by SB-505124 inhibition. Concomitantly, the CD31, MMP13 and TGF-β1 enriched micro-environment in the tumor was associated with higher recurrence and distal lung metastasis risks. Furthermore, we report a comprehensive effort to correlate CMs to tumor-prognosis indicators, in which a decreased body weight gain ratio (BWG) and increased tumor weight (TW) were correlated with increased CMs. Conclusions Together, we determined that TGF-β1 was significantly associated with malignant tumor progressing. In terms of clinical applications, local tumor excision followed by MMS analysis offers an opportunity to predict tumor recurrence and metastasis risks.