| Title : Pan-cancer analysis of acetylcholinesterase (AChE) expression by a data-driven approach: future directions of AChE in cancer neuroscience - An_2025_Chem.Biol.Interact_15ChEPon__111647 |
| Author(s) : An J , Xie HQ , Yan Z , Chen X , Zhu R , Yang G , Xu L , Kovarik Z , Tsim KWK |
| Ref : Chemico-Biological Interactions , :111647 , 2025 |
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Abstract :
There is evidence that the expression of acetylcholinesterase (AChE) is associated with the development of certain cancers. However, there are still insufficient studies to reveal the correlation between AChE expression and cancer development and prognosis from the perspective of pan-cancer. In this study, a comprehensive bioinformatics analysis of the pan-cancer expression signature of AChE was conducted through a data-driven approach. Pan-cancer datasets were obtained through online databases, including the Cancer Genome Atlas and Genotypic Tissue Expression databases. The correlation between ACHE expression and cancer prognosis was predicted by survival analysis. The results showed differences in the expression levels of the ACHE gene in cancer and paired normal tissues. However, the alterations in cancer tissue ACHE expression were different depending on the cancer type, e.g., higher ACHE expression was found in pancreatic adenocarcinoma, and lower ACHE expression was found in glioblastoma multiforme (GBM). In addition, ACHE expression was found to have dual prognostic significance, e.g., cutaneous melanoma with higher levels of ACHE expression had better overall survival, while the opposite outcome was found in uveal melanoma. The function of ACHE-expressing cells in primary and metastatic tumors was predicted using single-cell RNA sequencing datasets from patients with GBM. Differences in cell type preferences for ACHE expression were found in primary and metastatic GBM, and different functional enrichment features were identified, suggesting a potential role of ACHE expression in GBM progression. Overall, our study highlights the potential of AChE as a target for cancer research. |
| PubMedSearch : An_2025_Chem.Biol.Interact_15ChEPon__111647 |
| PubMedID: 40651751 |
An J, Xie HQ, Yan Z, Chen X, Zhu R, Yang G, Xu L, Kovarik Z, Tsim KWK (2025)
Pan-cancer analysis of acetylcholinesterase (AChE) expression by a data-driven approach: future directions of AChE in cancer neuroscience
Chemico-Biological Interactions
:111647
An J, Xie HQ, Yan Z, Chen X, Zhu R, Yang G, Xu L, Kovarik Z, Tsim KWK (2025)
Chemico-Biological Interactions
:111647