CancerMIRNome

CancerMIRNome provides interactive analysis and visualization of microRNA (miRNA) expression profiles from TCGA and public circulating miRNome datasets to support miRNA biomarker discovery and pan-cancer studies.

Key Features:

• Extensive Data Integration: Integrates 10,998 samples across 33 TCGA projects and 21,993 samples from 40 public circulating miRNome datasets from NCBI GEO and ArrayExpress.
• Interactive Analysis: Supports identification and comparative analysis of dysregulated miRNAs across multiple cancer types.
• Advanced Bioinformatics Tools and Machine Learning Algorithms: Incorporates bioinformatics methodologies and machine learning algorithms to enable development and evaluation of diagnostic or prognostic miRNA signatures.
• Visualization Capabilities: Provides robust data visualization modules for representation and interpretation of complex miRNA expression data.

Scientific Applications:

• Biomarker Discovery: Enables discovery of tumor and circulating miRNA biomarkers for diagnostic and prognostic purposes.
• Non‑invasive Cancer Detection: Facilitates analysis of circulating miRNAs, which are secreted into circulation and exhibit structural stability, for potential non‑invasive early cancer detection.
• Pan‑cancer Analysis: Supports comparative pan‑cancer studies across 33 TCGA projects to identify common and cancer‑specific miRNA dysregulation.
• Signature Development: Enables development and assessment of diagnostic or prognostic miRNA expression signatures using machine learning approaches.

Methodology:

Integration of TCGA and public circulating miRNome datasets, interactive exploration of large‑scale miRNA expression data, and application of bioinformatics methodologies and machine learning algorithms for pan‑cancer analyses and signature development.