Single cell transcriptomic characterisation of ovarian tumour infiltrating leukocytes to identify biomarkers of chemotherapy resistance.
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Molecular. Genetics & Pop Health
Abstract
Project Summary:
Since Zhang et al (2003) it is apparent that the host immune response in the form of tumour infiltrating leukocytes (TILs) has significant clinical importance for ovarian cancer patients. It is known that the presence of immune cells at the tumour sites is crucial for patients to respond to chemotherapy and is generally indicative of a better prognosis. However, most ovarian cancer patients develop recurrent cancers which are resistant to chemotherapy (Matsuo et al., 2010). It is also apparent that not all immune responses are equally effective in aiding to eradicate the cancer, and the tumour microenvironment reprograms TILs to reduce the efficacy of the host anti-tumour response over the course of therapy. As of writing there are no classification or categories of immune cell response(s) which confer clinical meaning to ovarian cancer patients, despite knowing that the immune response is an essential element in ovarian cancer patient prognosis and survival. Therefore, there is an unmet need for immune cell characterisation in the context of ovarian cancer patients, and the understanding to infer in which cases the immune cell response will either promote remission in patients following chemotherapy or what the hallmarks are in chemotherapy resistance cases. The goal of this PhD project is to use single cell RNA sequencing to characterise the transcriptomes of immune cells within the tumour microenvironment of chemotherapy sensitive and resistant ovarian cancers to identify any pattern within multitude of cell types within the TILs which may correlate to the clinical phenotype. Secondly, we will define how TILs are reprogrammed during the course of chemotherapy as the patient's tumour goes from therapy responsive to therapy resistant. The main strength of single cell transcriptomics, is it can isolate single immune cell populations in ovarian cancer samples, and characterise the gene expression of these single immune cells to both identify them and resolve their function (i.e. what proteins are translated). This method requires optimisation of single cell dissociation from fresh ovarian tumours prior to Chromium 10x single cell sequencing.
This project will require fresh tumour samples, and each sample will be split into 2 arms, the single cell sequencing arm, which is a method currently in development in our lab; and batched processed arm. The aim of our single cell sequencing method is to develop a sophisticated bioinformatic algorithm which can identify the immune cell signatures found from single cell RNA sequences and can extrapolated to batched processed tumour samples (a bottom-up approach). This is different from the typical top-down approach of finding gene expression clusters and correlating them to an immune cell population. In addition, the tumour samples which the immune cells are isolated from will have full clinical annotation, i.e. response to chemotherapy (sensitive, non-sensitive or refractory). It is my hypothesis that the immune cell landscape is an important phenotype in predicting patient response to chemotherapy and that single cell sequencing will allow us to elucidate the highest resolution of the immune cell landscape of these tumour samples. With this information, we can study how the immune landscape of a patient's tumour changes over the course of treatment, and find signatures which can be used to indicate whether or not a patient's tumour is likely to respond to chemotherapy or biological therapy.
Ref:
Zhang, L., Conejo-Garcia, J., Katsaros, D., Gimotty, P., Massobrio, M., Regnani, G., Makrigiannakis, A., Gray, H., Schlienger, K., Liebman, M., Rubin, S. and Coukos, G. (2003). Intratumoral T Cells, Recurrence, and Survival in Epithelial Ovarian Cancer. New England Journal of Medicine, 348(3), pp.203-213.
Matsuo, K., Lin, Y., Roman, L. and Sood, A. (2010). Overcoming platinum resistance in ovarian carcinoma. Expert Opinion on Investigational Drugs, 19(11),), pp.1339-1354
Since Zhang et al (2003) it is apparent that the host immune response in the form of tumour infiltrating leukocytes (TILs) has significant clinical importance for ovarian cancer patients. It is known that the presence of immune cells at the tumour sites is crucial for patients to respond to chemotherapy and is generally indicative of a better prognosis. However, most ovarian cancer patients develop recurrent cancers which are resistant to chemotherapy (Matsuo et al., 2010). It is also apparent that not all immune responses are equally effective in aiding to eradicate the cancer, and the tumour microenvironment reprograms TILs to reduce the efficacy of the host anti-tumour response over the course of therapy. As of writing there are no classification or categories of immune cell response(s) which confer clinical meaning to ovarian cancer patients, despite knowing that the immune response is an essential element in ovarian cancer patient prognosis and survival. Therefore, there is an unmet need for immune cell characterisation in the context of ovarian cancer patients, and the understanding to infer in which cases the immune cell response will either promote remission in patients following chemotherapy or what the hallmarks are in chemotherapy resistance cases. The goal of this PhD project is to use single cell RNA sequencing to characterise the transcriptomes of immune cells within the tumour microenvironment of chemotherapy sensitive and resistant ovarian cancers to identify any pattern within multitude of cell types within the TILs which may correlate to the clinical phenotype. Secondly, we will define how TILs are reprogrammed during the course of chemotherapy as the patient's tumour goes from therapy responsive to therapy resistant. The main strength of single cell transcriptomics, is it can isolate single immune cell populations in ovarian cancer samples, and characterise the gene expression of these single immune cells to both identify them and resolve their function (i.e. what proteins are translated). This method requires optimisation of single cell dissociation from fresh ovarian tumours prior to Chromium 10x single cell sequencing.
This project will require fresh tumour samples, and each sample will be split into 2 arms, the single cell sequencing arm, which is a method currently in development in our lab; and batched processed arm. The aim of our single cell sequencing method is to develop a sophisticated bioinformatic algorithm which can identify the immune cell signatures found from single cell RNA sequences and can extrapolated to batched processed tumour samples (a bottom-up approach). This is different from the typical top-down approach of finding gene expression clusters and correlating them to an immune cell population. In addition, the tumour samples which the immune cells are isolated from will have full clinical annotation, i.e. response to chemotherapy (sensitive, non-sensitive or refractory). It is my hypothesis that the immune cell landscape is an important phenotype in predicting patient response to chemotherapy and that single cell sequencing will allow us to elucidate the highest resolution of the immune cell landscape of these tumour samples. With this information, we can study how the immune landscape of a patient's tumour changes over the course of treatment, and find signatures which can be used to indicate whether or not a patient's tumour is likely to respond to chemotherapy or biological therapy.
Ref:
Zhang, L., Conejo-Garcia, J., Katsaros, D., Gimotty, P., Massobrio, M., Regnani, G., Makrigiannakis, A., Gray, H., Schlienger, K., Liebman, M., Rubin, S. and Coukos, G. (2003). Intratumoral T Cells, Recurrence, and Survival in Epithelial Ovarian Cancer. New England Journal of Medicine, 348(3), pp.203-213.
Matsuo, K., Lin, Y., Roman, L. and Sood, A. (2010). Overcoming platinum resistance in ovarian carcinoma. Expert Opinion on Investigational Drugs, 19(11),), pp.1339-1354
Organisations
People |
ORCID iD |
| Charlie Gourley (Primary Supervisor) | |
| Thomas Parry (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/N013166/1 | 01/10/2016 | 30/09/2025 | |||
| 1939984 | Studentship | MR/N013166/1 | 01/09/2017 | 31/08/2021 | Thomas Parry |