TranscriptAchilles: a genome-wide platform to predict isoform biomarkers of gene essentiality in cancer
Keywords: 
Applications in cancer
TranscriptAchilles
Alternative splicing
Prognosis biomarker
Issue Date: 
2019
Publisher: 
Oxford University Press (OUP)
ISSN: 
2047-217X
Note: 
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation: 
Carazo Melo, F.(Fernando); Campuzano, L. (Lucía); Cendoya, X. (Xabier); et al. "TranscriptAchilles: a genome-wide platform to predict isoform biomarkers of gene essentiality in cancer". GigaScience. 8 (4), 2019, giz021
Abstract
Background Aberrant alternative splicing plays a key role in cancer development. In recent years, alternative splicing has been used as a prognosis biomarker, a therapy response biomarker, and even as a therapeutic target. Next-generation RNA sequencing has an unprecedented potential to measure the transcriptome. However, due to the complexity of dealing with isoforms, the scientific community has not sufficiently exploited this valuable resource in precision medicine. Findings We present TranscriptAchilles, the first large-scale tool to predict transcript biomarkers associated with gene essentiality in cancer. This application integrates 412 loss-of-function RNA interference screens of >17,000 genes, together with their corresponding whole-transcriptome expression profiling. Using this tool, we have studied which are the cancer subtypes for which alternative splicing plays a significant role to state gene essentiality. In addition, we include a case study of renal cell carcinoma that shows the biological soundness of the results. The databases, the source code, and a guide to build the platform within a Docker container are available at GitLab. The application is also available online. Conclusions TranscriptAchilles provides a user-friendly web interface to identify transcript or gene biomarkers of gene essentiality, which could be used as a starting point for a drug development project. This approach opens a wide range of translational applications in cancer.

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