circRNAome Profiling in Oral Carcinoma Unveils a Novel circFLNB that Mediates Tumour Growth-Regulating Transcriptional Response.
Yi-Tung ChenIan Yi-Feng ChangChia-Hua KanYu-Hao LiuYu-Ping KuoHsin-Hao TsengHsing-Chun ChenHsuan LiuYu-Sun ChangJau-Song YuKai-Ping ChangBertrand Chin-Ming TanPublished in: Cells (2020)
Deep sequencing technologies have revealed the once uncharted non-coding transcriptome of circular RNAs (circRNAs). Despite the lack of protein-coding potential, these unorthodox yet highly stable RNA species are known to act as critical gene regulatory hubs, particularly in malignancies. However, their mechanistic implications in tumor outcome and translational potential have not been fully resolved. Using RNA-seq data, we profiled the circRNAomes of tumor specimens derived from oral squamous cell carcinoma (OSCC), which is a prevalently diagnosed cancer with a persistently low survival rate. We further catalogued dysregulated circRNAs in connection with tumorigenic progression. Using comprehensive bioinformatics analyses focused on co-expression maps and miRNA-interaction networks, we delineated the regulatory networks that are centered on circRNAs. Interestingly, we identified a tumor-associated, pro-tumorigenic circRNA, named circFLNB, that was implicated in maintaining several tumor-associated phenotypes in vitro and in vivo. Correspondingly, transcriptome profiling of circFLNB-knockdown cells showed alterations in tumor-related genes. Integrated in silico analyses further deciphered the circFLNB-targeted gene network. Together, our current study demarcates the OSCC-associated circRNAome, and unveils a novel circRNA circuit with functional implication in OSCC progression. These systems-based findings broaden mechanistic understanding of oral malignancies and raise new prospects for translational medicine.
Keyphrases
- single cell
- rna seq
- genome wide
- transcription factor
- induced apoptosis
- poor prognosis
- gene expression
- long non coding rna
- papillary thyroid
- signaling pathway
- copy number
- cell proliferation
- lymph node metastasis
- binding protein
- big data
- squamous cell carcinoma
- deep learning
- anti inflammatory
- machine learning
- electronic health record
- endoplasmic reticulum stress
- oxidative stress
- nucleic acid
- heat shock