CICADA: a circRNA effort toward the ghost proteome
Recent studies have confirmed that certain circRNAs encode proteins that are integral to various biological functions. In this study, we present CICADA, an algorithm specifically designed to assess the protein-coding potential and coding products of circRNAs at high throughput, which enables the identification of previously unknown circRNA-encoded proteins. By harnessing the potential of this algorithm, we identified a variety of functional, protein-coding circRNAs in esophageal squamous cell carcinoma and established circRNA translation profiles for diverse types of cancer. This advancement innovatively explores the hidden proteome within the genome, poised to catalyze discoveries in biomarkers and therapies for cancers and complex diseases. CICADA is accessible as a Python module (https://github.com/SunLab-biotool/CICADA).
Authors
- Liang Sun (ORCID: https://orcid.org/0000-0002-5213-6941)
- Li‐Yan Xu (ORCID: https://orcid.org/0000-0002-1618-4292)
- Xinyuan Zhou (ORCID: https://orcid.org/0000-0002-1374-8240)
- Lian‐Di Liao
- Haojie Yu (ORCID: https://orcid.org/0000-0002-0559-0252)
- Liyuan Fan (ORCID: https://orcid.org/0000-0002-9520-8482)
- Mian Li (ORCID: https://orcid.org/0000-0001-6514-2729)
- Hui Tian (ORCID: https://orcid.org/0000-0003-4516-2313)
- Anwei Gao
Institutions
- Academy of Medical Sciences (GB)
- Harbin Medical University (CN)
- Shantou University (CN)
- Shantou University Medical College (CN)
- Binzhou People's Hospital (CN)
- Qilu Hospital of Shandong University (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1093/nar/gkae1179
- Citations
- 6
- Primary Topic
- Circular RNAs in diseases
- Type
- article
- Field-Weighted Citation Impact
- 1.40
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Shandong First Medical University