CSCD2

CSCD2 curates and annotates cancer-specific circular RNAs (circRNAs) to support analysis of their occurrences, interactions with miRNAs and RBPs, and predicted full-length and open reading frame sequences across human cancer and normal samples.

Key Features:

• Extensive Data Collection: Contains data from over 1000 samples, including 825 tissue samples and 288 cell lines.
• Comparative Coverage: Enables comparative analyses between cancerous and normal samples through inclusion of tissue and cell line datasets.
• Comprehensive circRNA Identification: Identifies 1,013,461 cancer-specific circRNAs, 1,533,704 circRNAs in normal-only samples, and 354,422 circRNAs present in both cancerous and normal contexts.
• miRNA–circRNA Interaction Predictions: Predicts miRNA-circRNA interactions using binding motifs from over 2000 microRNAs.
• RBP–circRNA Interaction Predictions: Infers RBP-circRNA interactions using binding motifs from more than 200 RNA-binding proteins (RBPs).
• Sequence Predictions: Predicts potential full-length sequences and open reading frames (ORFs) for circRNAs.

Scientific Applications:

• Functional and Regulatory Studies: Supports exploration of circRNA functions and regulatory mechanisms within oncogenic processes.
• Biomarker Discovery: Facilitates identification of circRNA-based biomarkers for cancer diagnosis or prognosis.
• Therapeutic Target Identification: Aids discovery of novel therapeutic targets by characterizing circRNA interactions with miRNAs and RBPs.

Methodology:

Integration of large-scale datasets from human cancer and normal tissues and cell lines; prediction of miRNA-circRNA interactions using binding motifs from over 2000 microRNAs; inference of RBP-circRNA interactions using binding motifs from more than 200 RBPs; and prediction of full-length and open reading frame sequences for circRNAs.