Overexpression of PLK1 Molecule Following Incomplete Thermal Ablation Promotes the Proliferation and Invasion of Residual Hepatocellular Carcinoma.
Tong KangJiamin ChenWei-Jun WanJin-Shu PangRong WenXiu-Mei BaiLipeng LiYunjing PanYun HeHong YangPublished in: Molecular biotechnology (2024)
TAT, a widely used treatment for HCC, can exacerbate the progression of residual HCC. The present study investigated the mechanism of action of PLK1 following ITA of HCC. The PLK1 levels in HCC were determined using qRT-PCR from clinical patient samples, IHC from tissue microarray, and data from globally high-throughput data and microarrays. The PLK1 levels and their effect on the biological phenotype of heat-stress HCC cells were evaluated through in vitro experiments. We detected PLK1 abnormal expression in HCC models of nude mice subjected to ITA. We detected the effects of different PLK1 expression levels on EMT pathway proteins. PLK1 exhibited an overexpression in HCC tissues with an SMD of 1.19 (3414 HCC and 3036 non-HCC tissues were included), distinguishing HCC from non-HCC effectively (AUC = 0.9). The qRT-PCR data from clinical HCC patient samples and IHC from HCC tissue microarray results also indicated an overexpressed level. In the incomplete ablation models, an increased PLK1 expression was found in both heat-stress cells and subcutaneous tumors. The upregulation of PLK1 following ITA was found to enhance the malignancy of HCC and exacerbate the proliferation, migration, and invasion of residual HCC cells, whereas PLK1 knockdown suppressed the biological malignancy of HCC cells. Meanwhile, PLK1 has different regulatory effects on various EMT pathway proteins. PLK1 promotes the progression of residual HCC by activating EMT pathway after ITA, which might provide a novel idea for the treatment and prognosis of residual HCC.
Keyphrases
- heat stress
- induced apoptosis
- poor prognosis
- high throughput
- cell cycle arrest
- signaling pathway
- type diabetes
- gene expression
- cell proliferation
- epithelial mesenchymal transition
- cell death
- transcription factor
- atrial fibrillation
- metabolic syndrome
- case report
- artificial intelligence
- machine learning
- mass spectrometry
- combination therapy
- deep learning
- insulin resistance
- radiofrequency ablation
- single molecule
- catheter ablation