OutSplice: A Novel Tool for the Identification of Tumor-Specific Alternative Splicing Events-Reference-Cited by-全球学者库

OutSplice: A Novel Tool for the Identification of Tumor-Specific Alternative Splicing Events

Published:2023-10-08 Issue:4 Volume:3 Page:853-868
ISSN:2673-7426
Container-title:BioMedInformatics
language:en
Short-container-title:BioMedInformatics

Author:

Bendik Joseph¹^ORCID,Kalavacherla Sandhya¹,Webster Nicholas¹,Califano Joseph¹²³,Fertig Elana J.⁴⁵⁶⁷,Ochs Michael F.⁸,Carter Hannah¹⁹^ORCID,Guo Theresa¹²³^ORCID

Affiliation:

1. Moores Cancer Center, University of California San Diego, San Diego, CA 92037, USA

2. Gleiberman Head and Neck Cancer Center, University of California, San Diego, CA 92037, USA

3. Department of Otolaryngology-Head and Neck Surgery, University of California San Diego, San Diego, CA 92037, USA

4. Quantitative Sciences Division and Convergence Institute, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21224, USA

5. Department of Oncology, Johns Hopkins University, Baltimore, MD 21224, USA

6. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21224, USA

7. Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21224, USA

8. Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ 08628, USA

9. Division of Medical Genetics, Department of Medicine, University of California San Diego, San Diego, CA 92093, USA

Abstract

Protein variation that occurs during alternative splicing has been shown to play a major role in disease onset and oncogenesis. Due to this, we have developed OutSplice, a user-friendly algorithm to classify splicing outliers in tumor samples compared to a distribution of normal samples. Several tools have previously been developed to help uncover splicing events, each coming with varying methodologies, complexities, and features that can make it difficult for a new researcher to use or to determine which tool they should be using. Therefore, we benchmarked several algorithms to determine which may be best for a particular user’s needs and demonstrate how OutSplice differs from these methodologies. We find that despite detecting a lower number of genes with significant aberrant events, OutSplice is able to identify those that are biologically impactful. Additionally, we identify 17 genes that contain significant splicing alterations in tumor tissue that were discovered across at least 5 of the tested algorithms, making them good candidates for future studies. Overall, researchers should consider a combined use of OutSplice with other splicing software to help provide additional validation for aberrant splicing events and to narrow down biologically relevant events.

Funder

University of California San Diego Altman Clinical and Translational Research Institute

National Institute of General Medical Sciences

Gleiberman Early Career Faculty Fellow

Publisher

MDPI AG

Subject

Management Science and Operations Research,Mechanical Engineering,Energy Engineering and Power Technology

Link

https://www.mdpi.com/2673-7426/3/4/53/pdf

Reference55 articles.

1. Function of alternative splicing;Kelemen;Gene,2013

2. Alternative splicing and disease;Tazi;Biochim. Biophys. Acta,2009

3. Genomic Structure of DNA Encoding the Lymphocyte Homing Receptor Cd44 Reveals at Least 12 Alternatively Spliced Exons;Screaton;Proc. Natl. Acad. Sci. USA,1992

4. Significance of Cd44 Gene-Products for Cancer-Diagnosis and Disease Evaluation;Matsumura;Lancet,1992

5. The biology and role of CD44 in cancer progression: Therapeutic implications;Chen;J. Hematol. Oncol.,2018