Targeting CLK4 inhibits the metastasis and progression of breast cancer by inactivating TGF-β pathway.
Eunji KangKanggeon KimSook Young JeonJi Gwang JungHong Kyu KimHan-Byoel LeeWonshik HanPublished in: Cancer gene therapy (2022)
Triple-negative breast cancer (TNBC) represents the most aggressive subtype of breast cancer that is highly resistant to current therapeutic options. According to the public databases Oncomine and KM plotter, the CLK4 expression is correlated with poor patient survival in TNBC, especially in mesenchymal-like TNBC (MES-TNBC) that has strong metastatic potential. Therefore, we investigated the potential involvement of CLK4 in the metastasis and progression of MES-TNBC. In the MES-TNBC cell lines, the CLK4 expression was elevated. Notably, the RNAi-mediated silencing of CLK4 reduced the expression of multiple epithelial-mesenchymal transition (EMT) genes that mediate metastasis. Furthermore, CLK4 silencing reduced both the invasive behaviors of the cultured cells and tumor metastasis in the mouse xenograft model. It is also noteworthy that CLK4 silencing repressed the invasive and cancer stem cell (CSC) properties that are induced by the TGF-β signaling. Importantly, the pharmacological inhibition of CLK4 potently repressed the invasion and proliferation of MES-TNBC cell lines and patient-derived cells, which demonstrates its clinical applicability. Collectively, our results suggest that CLK4 plays a crucial role in invasion and proliferation of MES-TNBC, especially in the processes that are induced by TGF-β. Also, this study characterizes CLK4 as a novel therapeutic target in breast cancer.
Keyphrases
- epithelial mesenchymal transition
- poor prognosis
- transforming growth factor
- induced apoptosis
- signaling pathway
- small cell lung cancer
- squamous cell carcinoma
- cell cycle arrest
- stem cells
- healthcare
- binding protein
- mental health
- cell proliferation
- long non coding rna
- young adults
- drug delivery
- gene expression
- climate change
- mass spectrometry
- artificial intelligence
- atomic force microscopy
- childhood cancer
- breast cancer risk
- bioinformatics analysis