On the origin, progression, and evolution of ovarian cancer
<p>High-grade serous ovarian cancer (HGSOC) is amongst the deadliest of cancers. Despite decades of research on this disease, the exact mechanisms through which this carcinoma initiates, spreads, and relapses remain unclear. I believe the main reason behind this discrepancy between importance...
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| Format: | Thesis |
| Language: | English |
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2018
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| _version_ | 1826299107417784320 |
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| author | KaramiNejadRanjbar, M |
| author2 | Hassan, B |
| author_facet | Hassan, B KaramiNejadRanjbar, M |
| author_sort | KaramiNejadRanjbar, M |
| collection | OXFORD |
| description | <p>High-grade serous ovarian cancer (HGSOC) is amongst the deadliest of cancers. Despite decades of research on this disease, the exact mechanisms through which this carcinoma initiates, spreads, and relapses remain unclear. I believe the main reason behind this discrepancy between importance and available knowledge roots in the fact that currently available genomics methods are not sensitive enough for accurate study of limited amount of clinical materials. </p> <p>To address this issue, I optimised a novel library preparation protocol called DigiPico to generate reliable next generation sequencing data from picogram quantities of DNA that can be obtained from 10-20 human cells. Moreover, I implemented DigiTitan and MutLX analysis algorithms to identify clone-specific copy number alterations and small nucleotide variations from DigiPico data. Validating MutLX algorithm using experimental and simulated data I demonstrated that DigiPico/MutLX is a uniquely sensitive, accurate, and reliable method for analysis of micro-heterogeneity in solid tumours. </p> <p>Next, using DigiPico, I conducted the first accurate case study of genetic micro-heterogeneity on a collection of pre-chemotherapy tumour islets and post-chemotherapy microscopic residual disease (MRD) samples from one HGSOC patient. Analysing the results using DigiTitan and MutLX, firstly, I introduced tumour heterogeneity and genetic diversity as a hallmark of HGSOC. Secondly, based on new observations from this study, I challenged a pre-existing notion that mutations in TP53 gene are responsible for the initiation of HGSOC. I proposed that mutations in the regulatory regions that adversely affect the DNA repair machinery which can lead to subsequent large-scale genomic alterations precede the loss of TP53 function in the tumorigenesis pathway of HGSOC. Thirdly, comparing the somatic mutation load of pre-chemotherapy, MRD and recurrent tumours, I demonstrated that MRD harbours the least number of somatic mutations. Thereby, I hypothesized that MRD is likely to be composed of stem cell-like tumour cells that have survived the chemotherapy therefore suggesting that MRD is likely be the recurrence precursor. Lastly, I propose experimental approaches that are required to effectively validate or nullify these hypotheses.</p> |
| first_indexed | 2024-03-07T04:56:53Z |
| format | Thesis |
| id | oxford-uuid:d6e7885c-d245-41d1-a5ea-2f8bf7e66321 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:56:53Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | oxford-uuid:d6e7885c-d245-41d1-a5ea-2f8bf7e663212022-03-27T08:37:06ZOn the origin, progression, and evolution of ovarian cancerThesishttp://purl.org/coar/resource_type/c_db06uuid:d6e7885c-d245-41d1-a5ea-2f8bf7e66321CancerGenomicsEnglishORA Deposit2018KaramiNejadRanjbar, MHassan, BAhmed, A<p>High-grade serous ovarian cancer (HGSOC) is amongst the deadliest of cancers. Despite decades of research on this disease, the exact mechanisms through which this carcinoma initiates, spreads, and relapses remain unclear. I believe the main reason behind this discrepancy between importance and available knowledge roots in the fact that currently available genomics methods are not sensitive enough for accurate study of limited amount of clinical materials. </p> <p>To address this issue, I optimised a novel library preparation protocol called DigiPico to generate reliable next generation sequencing data from picogram quantities of DNA that can be obtained from 10-20 human cells. Moreover, I implemented DigiTitan and MutLX analysis algorithms to identify clone-specific copy number alterations and small nucleotide variations from DigiPico data. Validating MutLX algorithm using experimental and simulated data I demonstrated that DigiPico/MutLX is a uniquely sensitive, accurate, and reliable method for analysis of micro-heterogeneity in solid tumours. </p> <p>Next, using DigiPico, I conducted the first accurate case study of genetic micro-heterogeneity on a collection of pre-chemotherapy tumour islets and post-chemotherapy microscopic residual disease (MRD) samples from one HGSOC patient. Analysing the results using DigiTitan and MutLX, firstly, I introduced tumour heterogeneity and genetic diversity as a hallmark of HGSOC. Secondly, based on new observations from this study, I challenged a pre-existing notion that mutations in TP53 gene are responsible for the initiation of HGSOC. I proposed that mutations in the regulatory regions that adversely affect the DNA repair machinery which can lead to subsequent large-scale genomic alterations precede the loss of TP53 function in the tumorigenesis pathway of HGSOC. Thirdly, comparing the somatic mutation load of pre-chemotherapy, MRD and recurrent tumours, I demonstrated that MRD harbours the least number of somatic mutations. Thereby, I hypothesized that MRD is likely to be composed of stem cell-like tumour cells that have survived the chemotherapy therefore suggesting that MRD is likely be the recurrence precursor. Lastly, I propose experimental approaches that are required to effectively validate or nullify these hypotheses.</p> |
| spellingShingle | Cancer Genomics KaramiNejadRanjbar, M On the origin, progression, and evolution of ovarian cancer |
| title | On the origin, progression, and evolution of ovarian cancer |
| title_full | On the origin, progression, and evolution of ovarian cancer |
| title_fullStr | On the origin, progression, and evolution of ovarian cancer |
| title_full_unstemmed | On the origin, progression, and evolution of ovarian cancer |
| title_short | On the origin, progression, and evolution of ovarian cancer |
| title_sort | on the origin progression and evolution of ovarian cancer |
| topic | Cancer Genomics |
| work_keys_str_mv | AT karaminejadranjbarm ontheoriginprogressionandevolutionofovariancancer |