4.5 Article

Prediction and Assessment of Splicing Alterations: Implications for Clinical Testing

期刊

HUMAN MUTATION
卷 29, 期 11, 页码 1304-1313

出版社

WILEY
DOI: 10.1002/humu.20901

关键词

unclassified variant; splicing; bioinformatic prediction; cancer; oncology

资金

  1. Australian National Health and Medical Research Council
  2. NIH Breast Cancer Specialized Program in Research Excellence grant [P50 CA116201, CA116167]
  3. American Cancer Society award [RSG-04-220-01-CCE]
  4. Italian Association and Foundation for Cancer Research

向作者/读者索取更多资源

Sequence variants that may result in splicing alterations are a particular class of inherited variants for which consequences can be more readily assessed, using a combination of bioinformatic prediction methods and in vitro assays. There is also a general agreement that a variant would invariably be considered pathogenic on the basis of convincing evidence that it results in transcript(s) carrying a premature stop codon or an in-frame deletion disrupting known functional domain(s). This commentary discusses current practices used to assess the clinical significance of this class of variants, provides suggestions to improve assessment, and highlights the issues involved in routine assessment of potential splicing aberrations. We conclude that classification of sequence variants that may alter splicing is greatly enhanced by supporting in vitro analysis. Additional studies that assess large numbers of variants for induction of splicing aberrations and exon skipping are needed to define the contribution of splicing/exon skipping to cancer and disease. These studies will also provide the impetus for development of algorithms that better predict splicing patterns. To facilitate variant classification and development of more specific bioinformatic tools, we call for the deposition of all laboratory data from splicing analyses into national and international databases. Hum Mutat 29(11), 1304-1313, 2008. (C) 2008 Wiley-Liss, Inc.

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