The clinical relevance of epithelial-mesenchymal transition and its correlations with tumorigenic immune infiltrates in hepatocellular carcinoma.
Zhi-Qiang QiuXiang WangXiang-Wen JiFen-Jun JiangXin-Ye HanWei-Li ZhangYi-Hua AnPublished in: Immunology (2022)
Hepatocellular carcinoma (HCC) is a cancer with extremely high mortality. Epithelial-mesenchymal transition (EMT) may play an important role in the occurrence, invasion and prognosis of HCC; however, its relationship with immunity in HCC has not yet been studied. Therefore, we investigated the diagnostic and prognostic values of EMT and explored its potential connections with tumorigenic immune infiltrates in HCC. We first proposed a quantitative metric of EMT activity, the EMT score. After applying this metric to 20 datasets from the Integrative Molecular Database of Hepatocellular Carcinoma, the Cancer Genome Atlas, and the Gene Expression Omnibus, we explored the ability of the EMT score to stratify across sample types. We then applied the EMT score for survival analysis and to differentiate patients with/without vascular invasion to test its prognostic value. We also collected and calculated data on the abundance of immune cells and immune cell markers in HCC and investigated their correlations with EMT scores. Finally, we synthesized and analyzed 20 datasets and constructed an EMT-gene-immune linkage network. The results showed higher EMT scores in HCC samples than in cirrhotic and normal livers. The cases with higher EMT scores also showed poorer performance in terms of prognostic factors such as vascular invasion and overall survival time. Our research demonstrated a broad correlation between EMT and the tumor immune microenvironment, and we uncovered multiple potential linkers associated with both EMT and immunity. Studying EMT has clinical relevance and high diagnostic and prognostic value for HCC.
Keyphrases
- epithelial mesenchymal transition
- transforming growth factor
- signaling pathway
- gene expression
- prognostic factors
- stem cells
- type diabetes
- machine learning
- cardiovascular disease
- dna methylation
- emergency department
- squamous cell carcinoma
- cell migration
- papillary thyroid
- coronary artery disease
- rna seq
- hepatitis c virus
- mass spectrometry
- climate change
- microbial community
- big data
- single cell
- antibiotic resistance genes
- squamous cell