LIMD2 Regulates Key Steps of Metastasis Cascade in Papillary Thyroid Cancer Cells via MAPK Crosstalk
Although papillary thyroid carcinoma (PTC) has a good prognosis, 20-90% of patients show metastasis to regional lymph nodes and 10-15% of patients show metastasis to distant sites. Metastatic disease represents the main clinical challenge that impacts survival rate. We previously showed that LIMD2 was a novel metastasis-associated gene. In this study, to interrogate the role of LIMD2 in cancer invasion and metastasis, we used CRISPR-mediated knockout (KO) of LIMD2 in PTC cells (BCPAP and TPC1). Western blot and high-content screening (HCS) analysis confirmed functional KO of LIMD2. LIMD2 KO reduced in vitro invasion and migration. Ultrastructural analyses showed that cell polarity and mitochondria function and morphology were restored in LIMD2 KO cells. To unveil the signals supervising these phenotypic changes, we employed phospho-protein array. Several members of the MAPK superfamily showed robust reduction in phosphorylation. A Venn diagram displayed the overlap of kinases with reduced phosphorylation in both cell lines and showed that they were able to initiate or sustain the epithelial-mesenchymal transition (EMT) and DNA damage checkpoint. Flow cytometry and HCS validation analyses further corroborated the phospho-protein array data. Collectively, our findings show that LIMD2 enhances phosphorylation of kinases associated with EMT and invasion. Through cooperation with different kinases, it contributes to the increased genomic instability that ultimately promotes PTC progression.Keywords:BRAF V600E; CRISPR/Cas9; LIMD2; epithelial-to-mesenchymal transition; papillary thyroid carcinoma.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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