An exome sequencing analysis pipeline was constructed to analyze NET germline and somatic samples. SNPs and INDELs were called and annotated from germline and somatic tissue. CNVs were also called for the tumor samples. This was accomplished using open source bioinformatics software that has been developed by the research community. Broad Institute "best practices" were followed. Some of the tools that were used include BWA, SAMtools, GATK, Varscan, VT, VEP, and GEMINI. Computational resources were provided by The University of Iowa NEON computer cluster. 57 germline samples and 15 tumor samples across 23 families with a history of NETs produced 4,452 germline variants, 1,695 somatic variants, 5,853 LOH events, and 627 CNV calls. False positive and driver candidacy filtering was applied. One family with Currarino syndrome has an inherited germline missense variant in MNX1. This variant has a phred-scaled Combined Annotation Dependant Depletion score of 35, putting it in the top 0.031% of deleterious variants. CNV analysis demonstrates that 8 of the 15 tumor samples have large-scale deletions of chromosome 18, three of which have nearly the entire chromosome deleted. An affected tumor suppressor gene in this region includes DCC, which is present in all three variant discovery techniques. Variant prioritization techniques are effective, but need further development to increase candidate variant/gene discovery rate.
Neuroendocrine genomics for tumor variant discovery
Abstract
Details
- Title: Subtitle
- Neuroendocrine genomics for tumor variant discovery
- Creators
- Jonathon Tessmann - University of Iowa
- Contributors
- Terry Braun (Advisor)Michael Schnieders (Committee Member)Benjamin Darbro (Committee Member)
- Resource Type
- Thesis
- Degree Awarded
- Master of Science (MS), University of Iowa
- Degree in
- Biomedical Engineering
- Date degree season
- Spring 2018
- DOI
- 10.17077/etd.eqodjq78
- Publisher
- University of Iowa
- Number of pages
- x, 351 pages
- Copyright
- Copyright © 2018 Jonathon Tessmann
- Comment
This thesis has been optimized for improved web viewing. If you require the original version, contact the University Archives at the University of Iowa: https://www.lib.uiowa.edu/sc/contact/.
- Language
- English
- Date submitted
- 08/29/2018
- Description illustrations
- illustrations
- Description bibliographic
- Includes bibliographical references (pages 31-34).
- Public Abstract (ETD)
Developing new drugs and therapies to treat cancer requires an understanding of the underlying genetic variants which are causing the cancer to develop. Variants in certain genes will affect the bodies’ ability to prevent tumor growth. This research aims to gain a better understanding of which genes are causing neuroendocrine tumors to form when they are mutated. We can accomplish this using programs and hardware that analyzes human genome samples. Once a person’s DNA has been sequenced, we reconstruct it and analyze it for any variations. These variations are then examined for their biological impact and effect on the human body. This can lead to clues about genes and their roles in normal health and in the disease process. The intention is for the knowledge gained from this research to lead to insights in neuroendocrine tumors and improve human health and wellness.
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering
- Record Identifier
- 9983776983702771