CstF64-Induced Shortening of the BID 3'UTR Promotes Esophageal Squamous Cell Carcinoma Progression by Disrupting ceRNA Cross-talk with ZFP36L2.
Ai LinPing JiXiangjie NiuXuan ZhaoYamei ChenWeiling LiuYachen LiuWenyi FanYanxia SunChuanwang MiaoShaosen ZhangWen TanDongxin LinEric J WagnerChen WuPublished in: Cancer research (2021)
The majority of human genes have multiple polyadenylation sites, which are differentially used through the process of alternative polyadenylation (APA). Dysregulation of APA contributes to numerous diseases, including cancer. However, specific genes subject to APA that impact oncogenesis have not been well characterized, and many cancer APA landscapes remain underexplored. Here, we used dynamic analyses of APA from RNA-seq (DaPars) to define both the 3'UTR APA profile in esophageal squamous cell carcinoma (ESCC) and to identify 3'UTR shortening events that may drive tumor progression. In four distinct squamous cell carcinoma datasets, BID 3'UTRs were recurrently shortened and BID mRNA levels were significantly upregulated. Moreover, system correlation analysis revealed that CstF64 is a candidate upstream regulator of BID 3'UTR length. Mechanistically, a shortened BID 3'UTR promoted proliferation of ESCC cells by disrupting competing endogenous RNA (ceRNA) cross-talk, resulting in downregulation of the tumor suppressor gene ZFP36L2. These in vitro and in vivo results were supported by human patient data whereby 3'UTR shortening of BID and low expression of ZFP36L2 are prognostic factors of survival in ESCC. Collectively, these findings demonstrate that a key ceRNA network is disrupted through APA and promotes ESCC tumor progression.Significance: High-throughput analysis of alternative polyadenylation in esophageal squamous cell carcinoma identifies recurrent shortening of the BID 3'UTR as a driver of disease progression.
Keyphrases
- rna seq
- single cell
- poor prognosis
- prognostic factors
- long non coding rna
- genome wide
- squamous cell carcinoma
- endothelial cells
- high throughput
- papillary thyroid
- binding protein
- induced pluripotent stem cells
- electronic health record
- lymph node metastasis
- induced apoptosis
- cell cycle arrest
- transcription factor
- drug induced
- bioinformatics analysis
- deep learning
- big data
- endoplasmic reticulum stress
- resting state
- machine learning