2 options
Advancing immunotherapy through proteogenomics : identification and validation of DLK1 as a target in neuroblastoma / Amber Kathryn Weiner.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Weiner, Amber Kathryn, author.
- Language:
- English
- Subjects (All):
- Oncology.
- Bioinformatics.
- Biochemistry.
- Datasets.
- Collaboration.
- Immunotherapy.
- Viral infections.
- Ontology.
- Kinases.
- Mutation.
- Genomics and computational biology--Penn dissertations.
- Penn dissertations--Genomics and computational biology.
- Local Subjects:
- Oncology.
- Bioinformatics.
- Biochemistry.
- Datasets.
- Collaboration.
- Immunotherapy.
- Viral infections.
- Ontology.
- Kinases.
- Mutation.
- Genomics and computational biology--Penn dissertations.
- Penn dissertations--Genomics and computational biology.
- Genre:
- Academic theses.
- Physical Description:
- 1 online resource (139 pages)
- Contained In:
- Dissertations Abstracts International 83-02B.
- Place of Publication:
- [Philadelphia, Pennsylvania] : University of Pennsylvania ; Ann Arbor : ProQuest Dissertations & Theses, 2021.
- Language Note:
- English
- System Details:
- Mode of access: World Wide Web.
- text file
- Summary:
- Neuroblastoma is an embryonal tumor of the sympathetic nervous system that accounts for 12% of childhood cancer deaths. Despite multimodal therapy, survival probability for high-risk neuroblastoma patients remains below 50% and relapsed neuroblastoma is largely incurable. While the introduction of GD2 immunotherapy provided a significant improvement in overall survival, neuroblastoma patients often experience severe adverse effects given that GD2 is also expressed on pain fibers, suggesting more suitable targets could exist. To date, the cell surface landscape (surfaceome) of neuroblastoma remains poorly defined. An unbiased survey of these proteins will facilitate the identification of candidate immunotherapeutic targets for preclinical validation. Since previous studies relied on RNA-sequencing, we sought to use a proteogenomic approach and incorporate mass spectrometry into our discovery efforts. In this thesis, we created a one-click mass spectrometry data analysis software called GiaPronto (Graphical Interpretation and Analysis of Proteins and their Ontologies), since there was a lack of simple to use tools to perform data normalization, assess data quality, identify relevant proteins and generate custom data visualization. Next, we utilized a proteogenomic approach to evaluate neuroblastoma compared to normal tissue to identify biologically relevant cell surface proteins that can serve as new immunotherapeutic targets. We prioritized DLK1 as an epigenetically regulated oncoprotein and candidate immunotherapeutic target. We tested ADCT-701, a DLK1 directed antibody drug conjugate, where we demonstrated potent and specific activity. In order to release these harmonized data to the scientific community, we developed a shiny application called PIONEER (Pediatric Integrative Omics Network Enhancing Early Research). By providing a web-based interface to disseminate and harness proteogenomic surfaceome data, PIONEER serves to enhance immunotherapeutic target discovery and development for high-risk childhood cancers. Lastly, we discuss advancing pediatric cancer research through collaboration between young investigator and patient advocates. We see this as a mechanism to gain experience in science communication, legislation/government, regulatory science, central internal review board protocols, and fundraising. We view this collaborative partnership as a model for team science by combining expertise to drive innovation forward and positively impact pediatric cancer patients, and perhaps those with adult malignancies.
- Notes:
- Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
- Advisors: Diskin, Sharon J.; Maris, John M.; Committee members: Wang, Li-San; Minn, Andy J.; Jensen, Shane T.; Hunt, Donald F.
- Department: Genomics and Computational Biology.
- Ph.D. University of Pennsylvania 2021.
- Local Notes:
- School code: 0175
- ISBN:
- 9798535566740
- Access Restriction:
- Restricted for use by site license.
- This item is not available from ProQuest Dissertations & Theses.
- This item must not be sold to any third party vendors.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.