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Updated: Aug 18, 2025
Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells
Published on: April 26, 2017
AS-CMC: a pan-cancer database of alternative splicing for molecular classification of cancer
Jiyeon Park1,2,3, Jin-Ok Lee3, Minho Lee4
1Precision Medicine Research Center, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-Gu, Seoul, 06591, Republic of Korea.
Abstract:
Alternative splicing (AS) is a post-transcriptional regulation that leads to the complexity of the transcriptome. Despite the growing importance of AS in cancer research, the role of AS has not been systematically studied, especially in understanding cancer molecular classification. Herein, we analyzed the molecular subtype-specific regulation of AS using The Cancer Genome Atlas data and constructed a web-based database, named Alternative Splicing for Cancer Molecular Classification (AS-CMC). Our system harbors three analysis modules for exploring subtype-specific AS events, evaluating their phenotype association, and performing pan-cancer comparison. The number of subtype-specific AS events was found to be diverse across cancer types, and some differentially regulated AS events were recurrently found in multiple cancer types. We analyzed a subtype-specific AS in exon 11 of mitogen-activated protein kinase kinase 7 (MAP3K7) as an example of a pan-cancer AS biomarker. This AS marker showed significant association with the survival of patients with stomach adenocarcinoma. Our analysis revealed AS as an important determinant for cancer molecular classification. AS-CMC is the first web-based resource that provides a comprehensive tool to explore the biological implications of AS events, facilitating the discovery of novel AS biomarkers.
Insights
Alternative splicing (AS) significantly impacts cancer molecular classification. A new database, AS-CMC, aids in discovering AS biomarkers for improved cancer subtyping and patient survival prediction.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Alternative splicing (AS) generates transcriptome complexity and is crucial in cancer research.
- Systematic study of AS in cancer molecular classification is lacking.
- Understanding AS's role is vital for advancing cancer subtyping.
Purpose of the Study:
- To analyze molecular subtype-specific alternative splicing regulation.
- To construct a web-based database (AS-CMC) for cancer molecular classification.
- To explore the biological implications and biomarker potential of AS events.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) data for AS analysis.
- Developed a web-based database (AS-CMC) with three analysis modules.
- Performed subtype-specific AS event exploration, phenotype association, and pan-cancer comparison.
Main Results:
- Identified diverse numbers of subtype-specific AS events across cancer types.
- Discovered recurrently differentially regulated AS events in multiple cancers.
- Validated a pan-cancer AS biomarker in mitogen-activated protein kinase kinase 7 (MAP3K7) exon 11, associated with stomach adenocarcinoma patient survival.
Conclusions:
- Alternative splicing is a key determinant in cancer molecular classification.
- AS-CMC is the first comprehensive web resource for exploring AS implications in cancer.
- Facilitates discovery of novel AS biomarkers for cancer research and clinical applications.
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