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Multimodal Data Integration Applied to Cancer Evolution and Signaling
Multimodal Data Integration Applied to Cancer Evolution and Signaling
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151509
- ISBN
- 9798383280287
- DDC
- 574
- 저자명
- Officer, Adam.
- 서명/저자
- Multimodal Data Integration Applied to Cancer Evolution and Signaling
- 발행사항
- [Sl] : University of California, San Diego, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 88 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-01, Section: B.
- 주기사항
- Advisor: Tamayo, Pablo;Gutkind, J. Silvio.
- 학위논문주기
- Thesis (Ph.D.)--University of California, San Diego, 2024.
- 초록/해제
- 요약Tumors evolve from normal cells due to aberrant activation or repression of cell signaling. Our understanding of how these signaling pathways affect the phenotype of the malignant cells themselves, as well as the surrounding microenvironment, is lacking. As the era of precision medicine approaches, a more holistic understanding of cancer intrinsic signaling and its effect on the epigenome of tumor cells, as well as how these tumor cells interact with surrounding normal cells, is key to unlocking novel therapeutic targets and biomarkers. Through three examples of cancer evolution and signaling I will show the value of integrative data modeling to better understand the biology of this disease.First, in the context of breast cancer progression, I developed a microenvironment modeling approach to identify several novel intercellular signaling pathways that are altered in the transition from in situ to invasive disease. Second, in uveal melanoma, a cancer caused by aberrant GNAQ signaling, I generated and integrated transcriptional and protein level datasets together to nominate p53, and other pathways, as novel downstream targets of GNAQ. And third, in the context of head and neck cancer progression, I characterized the role of YAP activation in malignant transformation and cell signaling through EGFR and mTOR.
- 일반주제명
- Bioinformatics
- 일반주제명
- Cellular biology
- 일반주제명
- Biomedical engineering
- 일반주제명
- Oncology
- 키워드
- Tumors
- 키워드
- Cancer evolution
- 키워드
- Cell signaling
- 기타저자
- University of California, San Diego Bioinformatics and Systems Biology
- 기본자료저록
- Dissertations Abstracts International. 86-01B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211151509
■006m o d
■007cr#unu||||||||
■020 ▼a9798383280287
■035 ▼a(MiAaPQ)AAI31299491
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a574
■1001 ▼aOfficer, Adam.
■24510▼aMultimodal Data Integration Applied to Cancer Evolution and Signaling
■260 ▼a[Sl]▼bUniversity of California, San Diego▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a88 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-01, Section: B.
■500 ▼aAdvisor: Tamayo, Pablo;Gutkind, J. Silvio.
■5021 ▼aThesis (Ph.D.)--University of California, San Diego, 2024.
■520 ▼aTumors evolve from normal cells due to aberrant activation or repression of cell signaling. Our understanding of how these signaling pathways affect the phenotype of the malignant cells themselves, as well as the surrounding microenvironment, is lacking. As the era of precision medicine approaches, a more holistic understanding of cancer intrinsic signaling and its effect on the epigenome of tumor cells, as well as how these tumor cells interact with surrounding normal cells, is key to unlocking novel therapeutic targets and biomarkers. Through three examples of cancer evolution and signaling I will show the value of integrative data modeling to better understand the biology of this disease.First, in the context of breast cancer progression, I developed a microenvironment modeling approach to identify several novel intercellular signaling pathways that are altered in the transition from in situ to invasive disease. Second, in uveal melanoma, a cancer caused by aberrant GNAQ signaling, I generated and integrated transcriptional and protein level datasets together to nominate p53, and other pathways, as novel downstream targets of GNAQ. And third, in the context of head and neck cancer progression, I characterized the role of YAP activation in malignant transformation and cell signaling through EGFR and mTOR.
■590 ▼aSchool code: 0033.
■650 4▼aBioinformatics
■650 4▼aCellular biology
■650 4▼aBiomedical engineering
■650 4▼aOncology
■653 ▼aTumors
■653 ▼aCancer progression
■653 ▼aCancer evolution
■653 ▼aCell signaling
■690 ▼a0715
■690 ▼a0379
■690 ▼a0541
■690 ▼a0992
■71020▼aUniversity of California, San Diego▼bBioinformatics and Systems Biology.
■7730 ▼tDissertations Abstracts International▼g86-01B.
■790 ▼a0033
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17161973▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
