Increased ONECUT2 induced by Helicobacter pylori promotes gastric cancer cell stemness via an AKT-related pathway.
Mi LinRu-Hong TuSheng-Ze WuQing ZhongKai WengYu-Kai WuGuang-Tan LinJia-Bin WangChao-Hui ZhengJian-Wei XieJian-Xian LinQi-Yue ChenChang-Ming HuangLong-Long CaoPing LiPublished in: Cell death & disease (2024)
Helicobacter pylori (HP) infection initiates and promotes gastric carcinogenesis. ONECUT2 shows promise for tumor diagnosis, prognosis, and treatment. This study explored ONECUT2's role and the specific mechanism underlying HP infection-associated gastric carcinogenesis to suggest a basis for targeting ONECUT2 as a therapeutic strategy for gastric cancer (GC). Multidimensional data supported an association between ONECUT2, HP infection, and GC pathogenesis. HP infection upregulated ONECUT2 transcriptional activity via NFκB. In vitro and in vivo experiments demonstrated that ONECUT2 increased the stemness of GC cells. ONECUT2 was also shown to inhibit PPP2R4 transcription, resulting in reduced PP2A activity, which in turn increased AKT/β-catenin phosphorylation. AKT/β-catenin phosphorylation facilitates β-catenin translocation to the nucleus, initiating transcription of downstream stemness-associated genes in GC cells. HP infection upregulated the reduction of AKT and β-catenin phosphorylation triggered by ONECUT2 downregulation via ONECUT2 induction. Clinical survival analysis indicated that high ONECUT2 expression may indicate poor prognosis in GC. This study highlights a critical role played by ONECUT2 in promoting HP infection-associated GC by enhancing cell stemness through the PPP2R4/AKT/β-catenin signaling pathway. These findings suggest promising therapeutic strategies and potential targets for GC treatment.
Keyphrases
- helicobacter pylori
- cell proliferation
- epithelial mesenchymal transition
- signaling pathway
- poor prognosis
- stem cells
- induced apoptosis
- gas chromatography
- helicobacter pylori infection
- transcription factor
- long non coding rna
- cell cycle arrest
- pi k akt
- immune response
- mesenchymal stem cells
- mass spectrometry
- risk assessment
- machine learning
- big data
- cell death
- drug delivery
- oxidative stress
- data analysis
- climate change
- nuclear factor
- toll like receptor
- artificial intelligence
- deep learning
- single molecule
- living cells