AS-CMC

AS-CMC provides systematic analysis of alternative splicing (AS) events across cancer types to support molecular classification and identification of AS-associated biomarkers.

Key Features:

• Systematic Analysis of AS Events: Leverages cancer genomic data from The Cancer Genome Atlas (TCGA) to analyze subtype-specific alternative splicing events across multiple cancer types.
• Exploration Module: Investigates specific AS events that are unique or prevalent within particular cancer subtypes.
• Phenotype Association Evaluation Module: Assesses associations between AS events and phenotypic traits, including clinical outcomes such as patient survival.
• Pan-Cancer Comparison Module: Performs cross-cancer comparisons to identify recurrently regulated AS events that may serve as universal biomarkers.
• Discovery of Pan-Cancer Biomarkers: Identifies candidate pan-cancer biomarkers, including a reported subtype-specific splicing event in exon 11 of MAP3K7 associated with patient survival in stomach adenocarcinoma.
• Facilitation of Novel Biomarker Discovery: Supports discovery of novel biomarkers through comprehensive AS data analysis and cross-subtype comparisons.

Scientific Applications:

• Molecular Classification: Refining cancer subtype definitions by profiling alternative splicing events.
• Biomarker Identification: Discovering AS-derived biomarkers for potential diagnostic, prognostic, or therapeutic use.
• Clinical Research: Investigating correlations between specific AS events and clinical outcomes to inform personalized medicine approaches.

Methodology:

Integrates TCGA cancer genomic data and applies bioinformatics analyses to identify and characterize subtype-specific AS events, evaluate phenotypic associations (including survival), and perform cross-cancer comparisons.