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ISOexpresso: a web-based platform for isoform-level expression analysis in human cancer

Authors
 In Seok Yang  ;  Hyeonju Son  ;  Sora Kim  ;  Sangwoo Kim 
Citation
 BMC GENOMICS, Vol.17(1) : 631, 2016 
Journal Title
BMC GENOMICS
Issue Date
2016
MeSH
Databases, Factual ; Forkhead Box Protein M1/genetics ; Forkhead Box Protein M1/metabolism ; Gene Expression Profiling/instrumentation* ; Gene Expression Regulation, Neoplastic* ; Humans ; Internet ; Mutation ; Neoplasm Proteins/genetics ; Neoplasm Proteins/metabolism* ; Neoplasms/metabolism* ; Protein Isoforms/genetics ; Protein Isoforms/metabolism ; User-Computer Interface*
Keywords
Differential expression ; Isoform ; Tissue ; Tumor-specific isoform
Abstract
BACKGROUND: Alternative splicing events that result in the production of multiple gene isoforms reveals important molecular mechanisms. Gene isoforms are often differentially expressed across organs and tissues, developmental stages, and disease conditions. Specifically, recent studies show that aberrant regulation of alternative splicing frequently occurs in cancer to affect tumor cell transformation and growth. While analysis of isoform expression is important for discovering tumor-specific isoform signatures and interpreting relevant genomic mutations, there is currently no web-based, easy-to-use, and publicly available platform for this purpose.

DESCRIPTION: We developed ISOexpresso to provide information regarding isoform existence and expression, which can be grouped by cancer vs. normal conditions, cancer types, and tissue types. ISOexpresso implements two main functions: First, the Isoform Expression View function creates visualizations for condition-specific RNA/isoform expression patterns upon query of a gene of interest. With this function, users can easily determine the major isoform (the most expressed isoform in a sample) of a gene with respect to the condition and check whether it matches the known canonical isoform. ISOexpresso outputs expression levels of all known transcripts to check alterations of expression landscape and to find potential tumor-specific isoforms. Second, the User Data Annotation function supports annotation of genomic variants to determine the most plausible consequence of a variation (e.g., an amino acid change) among many possible interpretations. As most coding sequence mutations are effective through the subsequent transcription and translation, ISOexpresso automatically prioritizes transcripts that act as backbones for mutation effect prediction by their relative expression. By employing ISOexpresso, we could investigate the consistency between the most expressed and known canonical/principal isoforms, as well as infer candidate tumor-specific isoforms based on their expression levels. In addition, we confirmed that ISOexpresso could easily reproduce previously known isoform expression patterns: recurrent observation of a major isoform across tissues, differential isoform expression patterns in a given tissue, and switching of major isoform during tumorigenesis.

CONCLUSIONS: ISOexpresso serves as a web-based, easy-to-use platform for isoform expression and alteration analysis based on large-scale cancer database. We anticipate that ISOexpresso will expedite formulation and confirmation of novel hypotheses by providing isoform-level perspectives on cancer research. The ISOexpresso database is available online at http://wiki.tgilab.org/ISOexpresso/ .
Files in This Item:
T201603796.pdf Download
DOI
10.1186/s12864-016-2852-6
Appears in Collections:
1. College of Medicine (의과대학) > BioMedical Science Institute (의생명과학부) > 1. Journal Papers
Yonsei Authors
Kim, Sangwoo(김상우) ORCID logo https://orcid.org/0000-0001-5356-0827
Yang, In Seok(양인석) ORCID logo https://orcid.org/0000-0001-5224-2587
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/152213
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