Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance
Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, February, 2021
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2021
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| Online Access: | https://hdl.handle.net/1721.1/130830 |
| _version_ | 1826196103758872576 |
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| author | Marjanovic, Nemanja. |
| author2 | Aviv Regev and Tyler Jacks. |
| author_facet | Aviv Regev and Tyler Jacks. Marjanovic, Nemanja. |
| author_sort | Marjanovic, Nemanja. |
| collection | MIT |
| description | Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, February, 2021 |
| first_indexed | 2024-09-23T10:20:37Z |
| format | Thesis |
| id | mit-1721.1/130830 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:20:37Z |
| publishDate | 2021 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1308302021-05-26T03:29:12Z Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance Marjanovic, Nemanja. Aviv Regev and Tyler Jacks. Massachusetts Institute of Technology. Computational and Systems Biology Program. Massachusetts Institute of Technology. Computational and Systems Biology Program Computational and Systems Biology Program. Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, February, 2021 Cataloged from the official PDF of thesis. "February 2021." Includes bibliographical references. Tumor progression, from the single mutated cell to the advanced stages of cancer, represents an evolutionary process. During tumor progression, cancer cells acquire new genetic mutations, becoming more heterogeneous, leading to tumor progression and resistance to therapy. However, clear genetic drivers of progression, metastasis, and therapeutic resistance are identified in only a subset of tumors, pointing to non-genetic contributors to cancer progression. Also, somatic evolution in cancer is occurring at the level of the single cell. Therefore, the application of the single cell genomic method is crucial for deciphering phenotypic heterogeneity. Here, we profiled single cell transcriptomes from genetically engineered mouse lung tumors at seven stages spanning tumor progression from atypical adenomatous hyperplasia to lung adenocarcinoma. The diversity of transcriptional states spanned by tumor cells increased over time and was reproducible across tumors and mice, but was not explained by genomic copy number variation. Cancer cells progressively adopted alternate lineage identities, computationally predicted to be mediated through a common transitional, high-plasticity cell state (HPCS). HPCS cells prospectively isolated from mouse tumors had robust potential for phenotypic switching and tumor formation and were more chemoresistant in mice. Our study reveals transitions that connect cell states across tumor evolution and motivates therapeutic targeting of the HPCS. by Nemanja Marjanovic. Ph. D. Ph.D. Massachusetts Institute of Technology, Computational and Systems Biology Program 2021-05-25T18:21:57Z 2021-05-25T18:21:57Z 2021 Thesis https://hdl.handle.net/1721.1/130830 1252628047 eng MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 152 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Computational and Systems Biology Program. Marjanovic, Nemanja. Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance |
| title | Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance |
| title_full | Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance |
| title_fullStr | Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance |
| title_full_unstemmed | Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance |
| title_short | Application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance |
| title_sort | application of the single cell genomics in deciphering tumor heterogeneity and its role in tumor progression and drug resistance |
| topic | Computational and Systems Biology Program. |
| url | https://hdl.handle.net/1721.1/130830 |
| work_keys_str_mv | AT marjanovicnemanja applicationofthesinglecellgenomicsindecipheringtumorheterogeneityanditsroleintumorprogressionanddrugresistance |