Abstract P1-05-33: RNA in Extracellular vesicles used for the prediction of distant metastasis of breast cancer and the function of TGM2 in promoting breast cancer development

Abstract

Abstract Background: Extracellular vesicles (EVs) can be released by living cells during the process of tumor metastasis. Since EVs could contain various of molecular with high stability, a growing number of evidences indicated that those molecular can be utilized as biomarkers of liquid biopsy for metastatic prediction. Therefore, we aimed to identify genes and build a model that can predict the risk of metastasis in breast cancer patients with acceptable sensitivity and accuracy. Methods: Pretreatment plasma EV-RNAs of patients diagnosed at Fudan University Shanghai Cancer Center from 2017 to 2018 were extracted and analyzed by next generation sequencing (NGS) and bioinformatics, including breast cancer patients (n=114) and benign cases (n=18). Weighted correlation network analysis (WGCNA) was utilized to determine the relationship between clinical features and genes. The Kaplan-Meier was used for survival analysis in public database. By 100 times of 5 folds cross-validation, we used logistic regression analysis to set up the model. The receiver operating characteristic curve (ROC) and area under curve (AUC) were used to assess the predicted capacity of the model. QRT-PCR was conducted to further confirm the expression of genes selected by the predicting model in 175 breast cancer patients with and without metastasis, along with 5 EV-RNAs of tumor samples and paired normal adjacent breast tissues. The functions of candidate genes on cell proliferation, metastasis, and invasion were determined by a series of in vitro experiments in cancer lines. RNA sequencing and bioinformatic analysis were performed to explore the mechanism of the candidate genes. Moreover, co-immunoprecipitation (Co-IP) was used to reveal interacting proteins. Results: WGCNA screened 40 hub genes which were significantly associated with the distant metastasis in patients with breast cancer. A total of 207 upregulated genes were identified in patients with distant metastasis. After intersection, 6 genes were selected. Survival analysis suggested that high expression of IGFBP5, BCL6B, TGM2, and SH3PXD2A were correlated with poor distant metastasis-free survival (DMFS). The metastasis predicting model built based on those genes showed an AUC value of 0.923 with diagnostic accuracy of 91.2%. In the validation cohort, data showed the AUC value of each single gene were 0.835, 0.818, 0.845, 0.834, for TGM2, IGFBP5, BCL6B, and SH3PXD2A respectively. Among those four genes, TGM2 was significantly upregulated with clinical stages and correlated with poor prognosis. Moreover, TGM2 showed the highest abundance in tumor tissue EVs. Functional experiments revealed that TGM2 promoted breast cancer proliferation, metastasis, and invasion in vitro. The initially upregulated expression of TGM2 in EVs of cell lines was significantly decreased by adding the exosome release inhibitor GW4869. In addition, EVs from TGM2 overexpressed cells promoted cell migration and invasion of wild-type cells. Mechanistically, TGM2 was positively correlated with EMT, Hedgehog and IL6-JAK-STAT3 pathways. Co-IP assay found that TGM2 interacted with TMF1, which was an effector for degradation of STAT3 through the ubiquitin-proteasome pathway. Interfering the expression of TMF1 remarkably promoted the migration ability of cells and reversed by TGM2 overexpression. Conclusion: Based on the plasma EV-RNAs, we constructed a model with promising predicted capacity of distant metastasis in patients with breast cancer. TGM2, as the most effective predictor, can promote the progression and metastasis of breast cancer by targeting TMF1/STAT3. Key words Breast Cancer; Extracellular vesicles; Metastasis; Prediction model; TGM2 Citation Format: Jiong Wu, Yayun Chi. RNA in Extracellular vesicles used for the prediction of distant metastasis of breast cancer and the function of TGM2 in promoting breast cancer development [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-05-33.