Understanding the clonality of Multiple Myeloma drug resistance mechanisms using long-read single-cell sequencing
- Project No: NDORMS 2022/4
- Intake: 2022
Multiple Myeloma is a cancer of plasma cells and is the second most prevalent haematological malignancy worldwide, with varied response rates to treatment and a mean survival age of 4-5 years. MM is currently incurable, albeit clinically manageable, with the introduction of several immunomodulatory agents and proteosome inhibitors increasing the overall patient survival rates. Despite this, most patients will relapse with the development of multi-drug resistance. Clinical management of the disease is currently composed of monitoring the development of clinical drug resistance. However, most prognostic measures fail to pick up the clonotypic tumour cells responsible for developing drug resistance.
The emergence of drug resistant clones underpins the relapse seen in most patients. It has been suggested that the failure to eliminate the malignant clone in MM is one of the major causes of consecutive relapse. If we are to predict those patients who relapse, then we need to reliably identify and characterise drug resistant clones so we can identify or develop better targeted therapeutics.
The advent of single-cell technologies has led to a better understanding of the complexity and diversity of the tumour microenvironment. However, current short read single-cell technologies focused on gene expression analyses limit our ability to identify clones. Clonality needs to be measured at the genetic level through copy number or mutational markers. Therefore, we need more informative single-cell sequencing measurements that provide us with useful readouts that we can use to understand the clonality of disease.
To overcome these challenges, we recently developed an approach to perform accurate long-read single-cell sequencing (termed scCOLOR-seq; pronounced “scholar seq”). This method allows us to simultaneously measure exon mutations, exon SNPs and gene fusion events (translocations), at the same time as quantify full-length mRNA at the single-cell level. We are therefore able to gain a better molecular profile of cells than that currently offered by short-read single-cell sequencing. We will apply this technology to understand the relationship between clonality and drug resistance mechanisms within MM.
The specific focus areas will be:
- Apply scCOLOR-seq to multiple myeloma patients before and after the development of proteosome inhibitor treatment.
- Generate a machine learning model to understand the key features that allow us to infer clonality in MM.
- Identify potential novel therapeutic or diagnostic markers for drug resistant MM.
- Computational biology
- Single-cell sequencing
- Machine learning
- Multiple Myeloma
- Drug resistance
- Hold or be about to obtain a first or upper second-class BSc degree or a Master degree (or equivalent) in subjects relevant to 1) biology or 2) computer science, engineering, statistics, maths or data science.
- Proficient in or have a desire to learn R and/or Python programming.
- The desire to learn state of the art wet-lab molecular biology techniques.
- Philpott et al 2021, Nanopore sequencing of single-cell transcriptomes with scCOLOR-seq. Nature Biotechnology.
- Cribbs et al 2020, Dissecting the role of BET bromodomain proteins BRD2 and BRD4 in Human NK cell function. Frontiers in Immunology
- Cottone et al 2020. Inhibition of H3K27 demethylases inactivated Bracyury and promotes chordoma cell dealth. Cancer research
- Cribbs et al 2020. Histone H3K27me3 demethylases regulate human Th17 cell development and effector functions by impacting on metabolism. PNAS.
Dr Adam Cribbs – primary supervisor
Prof Udo Opperman – co-supervisor
Dr Martin Philpott – co-supervisor
The Research group
The multi-disciplinary group is led by Dr Cribbs, Principal Investigator (PI) at the Botnar Research Centre, University of Oxford, and a current recipient of an MRC Career Development Fellowship in systems biology of Multiple Myeloma. Work in the Cribbs group focuses on developing novel single-cell technology and computational analysis frameworks that empower new modes of treating disease (https://www.acribbs.co.uk). Prof Udo Oppermann holds the Chair in Musculoskeletal Sciences at Oxford University, is director of Laboratory Sciences at the Botnar Research Centre and co-Director of the Oxford Translational Multiple Myeloma Centre. Work within the Oppermann laboratory focuses on drug discovery and target validation in several therapeutic areas, including oncology using chemogenomic approaches. Dr Martin Philpott is Director of the of the Next-Generation sequencing facility at the Botnar Research Centre. Dr Philpott works closely with Dr Cribbs and Prof Oppermann on developing novel single-cell technology and also leads the Oxford/Bayer-Alliance for Women’s Health Systems Biology of Uterine Fibroids project.
For general inquiries: Sam Burnell, Graduate Studies Officer.
For project related inquiries: Dr Adam Cribbs, Botnar Research Centre, University of Oxford.
The Botnar Research Centre plays host to the University of Oxford's Institute of Musculoskeletal Sciences, which enables and encourages research and education into the causes of musculoskeletal disease and their treatment. Training will be provided in wet-lab techniques including state of the art molecular and cell biology, compound screening and single-cell sequencing techniques. Furthermore, the successful candidate will be provided advanced computational training in software development, machine learning approaches, data analysis and pipeline development.
A core curriculum of lectures will be taken in the first term to provide a solid foundation in a broad range of subjects including musculoskeletal biology, inflammation, epigenetics, translational immunology, data analysis and the microbiome. Students will also be required to attend regular seminars within the Department and those relevant in the wider University.
Students will be expected to present data regularly in Departmental seminars, the Cribbs group and to attend external conferences to present their research globally, with limited financial support from the Department.
Students will also have the opportunity to work closely with members of the research group within the Botnar Research Centre. They will also benefit from the lab’s collaborations with researchers at the Target Discovery Institute, Kennedy Institute, and Weatherall Institute for Molecular Medicine. In addition to being part of the international Human Cell Atlas network of researchers.
Students will have access to various courses run by the Medical Sciences Division Skills Training Team and other Departments. All students are required to attend a 2-day Statistical and Experimental Design course at NDORMS and run by the IT department (information will be provided once accepted to the programme).
How to Apply
The Department accepts applications throughout the year but it is recommended that, in the first instance, you contact the relevant supervisor(s) or the Graduate Studies Officer, Sam Burnell, who will be able to advise you of the essential requirements.
Interested applicants should have, or expect to obtain, a first or upper second-class BSc degree or equivalent in a relevant subject and will also need to provide evidence of English language competence (where applicable). The application guide and form is found online and the DPhil or MSc by research will commence in October 2022.
Applications should be made to one of the following programmes using the specified course code:
D.Phil in Molecular and Cellular Medicine (course code: RD_MP1)
For further information, please visit the University Graduate Study page.