@article{0705a57e3446492095ecb74d825d5e18,
title = "Fusion genes as biomarkers in pediatric cancers: A review of the current state and applicability in diagnostics and personalized therapy",
abstract = "The incidence of pediatric cancers is rising steadily across the world, along with the challenges in understanding the molecular mechanisms and devising effective therapeutic strategies. Pediatric cancers are presented with diverse molecular characteristics and more distinct subtypes when compared to adult cancers. Recent studies on the genomic landscape of pediatric cancers using next-generation sequencing (NGS) approaches have redefined this field by providing better subtype characterization and novel actionable targets. Since early identification and personalized treatment strategies influence therapeutic outcomes, survival, and quality of life in pediatric cancer patients, the quest for actionable biomarkers is of great value in this field. Fusion genes that are prevalent and recurrent in several pediatric cancers are ideally suited in this context due to their disease-specific occurrence. In this review, we explore the current status of fusion genes in pediatric cancer subtypes and their use as biomarkers for diagnosis and personalized therapy. We discuss the technological advancements made in recent years in NGS sequencing and their impact on fusion detection algorithms that have revolutionized this field. Finally, we also discuss the advantages of pairing liquid biopsy protocols for fusion detection and their eventual use in diagnosis and treatment monitoring.",
keywords = "Fusion genes, Next-generation sequencing, Pediatric cancer, ctDNA",
author = "Vellichirammal, {Neetha Nanoth} and Chaturvedi, {Nagendra K.} and Joshi, {Shantaram S.} and Coulter, {Donald W.} and Chittibabu Guda",
note = "Funding Information: The authors are grateful to the Bioinformatics and Systems Biology Core at the University of Nebraska Medical Center (UNMC) for providing access to the computational infrastructure, which receives support from the Nebraska Research Initiative. Authors also acknowledge the Holland Computing Center of the University of Nebraska-Lincoln for high-performance computational resources. The authors also thank G. Sharp for providing valuable suggestions and comments on initial drafts. Funding Information: This work has been supported by the National Institutes of Health awards [ 5P20GM103427 , 1P30GM127200 , 5P30CA036727 ] and National Science Federation's EPSCoR Award [grant number OIA-1557417 ] to CG, LB905 Pediatric Cancer Research Funds from the State of Nebraska to DWC and the Fred & Pamela Buffett Cancer Center, which is supported by the National Cancer Institute under award number P30 CA036727 , in conjunction with the UNMC/Children's Hospital & Medical Center Child Health Research Institute Pediatric Cancer Research Group to NNV and NKC. Funding Information: This work has been supported by the National Institutes of Health awards [5P20GM103427, 1P30GM127200, 5P30CA036727] and National Science Federation's EPSCoR Award [grant number OIA-1557417] to CG, LB905 Pediatric Cancer Research Funds from the State of Nebraska to DWC and the Fred & Pamela Buffett Cancer Center, which is supported by the National Cancer Institute under award number P30 CA036727, in conjunction with the UNMC/Children's Hospital & Medical Center Child Health Research Institute Pediatric Cancer Research Group to NNV and NKC.The authors are grateful to the Bioinformatics and Systems Biology Core at the University of Nebraska Medical Center (UNMC) for providing access to the computational infrastructure, which receives support from the Nebraska Research Initiative. Authors also acknowledge the Holland Computing Center of the University of Nebraska-Lincoln for high-performance computational resources. The authors also thank G. Sharp for providing valuable suggestions and comments on initial drafts. Publisher Copyright: {\textcopyright} 2020",
year = "2021",
month = feb,
day = "28",
doi = "10.1016/j.canlet.2020.11.015",
language = "English (US)",
volume = "499",
pages = "24--38",
journal = "Cancer Letters",
issn = "0304-3835",
publisher = "Elsevier Ireland Ltd",
}