Using long-read sequencing to identify new druggable targets in Multiple Myeloma
- Project No: NDORMS 2024/04
- Intake: 2024
Work within the Cribbs lab focuses on developing novel technology and computational analysis frameworks that empower new modes of treatment for disease. Recently, we have advanced several single-cell and bulk long-read (LR) sequencing methodologies, enhancing their applicability and precision1, 2. This technology allows for the measurement of translocations, variant calling, and alternative splicing in unprecedented detail.
Our latest undertaking involves deploying this cutting-edge technology to dissect the complex mechanisms behind drug resistance in Multiple Myeloma (MM). We believe that the multi-modal data derived from LR sequencing harbours untapped potential for deepening our understanding of functional genomics. By applying this technology, we aim to fine-tune the diagnosis and prognostication of MM with increased accuracy.
With this vision in mind, we are set to employ the most advanced machine learning methodologies to recognize and integrate the data modalities that best predict patient outcomes. This strategic approach promises not just the development of new diagnostic techniques, but also the identification of potential therapeutic targets. Thus, we are confident that we are making significant strides towards achieving our ultimate goal: providing personalized care for every MM patient.
The specific focus areas will be:
- Apply Oxford Nanopore Technologies (ONT) sequencing platform on 600 myeloma patients before and after the development of proteosome inhibitor treatment.
- Generate a machine learning model to understand multi-modal data generated by applying long read sequencing to MM patient samples.
- Identify potential novel therapeutic targets for drug resistant MM.
Short-read (SR) sequencing methods face challenges in fully elucidating the intricacies of both DNA and RNA rearrangements. Owing to its capacity to cover thousands of base pairs, long-reads possess the ability to detect mutations in regions where short-reads falter. They excel in identifying complex chromosomal rearrangements, especially those involving numerous chromosomes and heavily repetitive regions3.
At the RNA level, the challenge lies in accurately documenting alternative splicing events, which can generate a multitude of substrate combinations from the same gene, resulting in thousands of isoforms. Isoform shifts can change drug responses, as we have shown in the response to Immunomodulatory imide (IMiD) drugs in myeloma4. Existing SR-sequencing methods are inefficient at capturing this complexity, necessitating the use of LR-sequencing (Fig.1). LR enables end-to-end mRNA sequencing, effectively circumventing these limitations.
Finally, LR sequencing provides the added advantage of simultaneously detecting DNA modifications, such as methylation, in a single experiment, thereby enhancing our understanding of genetic information at multiple levels.
Research Objectives and Outcomes
Our main aim is to apply our long-read RNA and DNA technology to primary MM patient samples and then generate computational models that help us to understand the molecular mechanisms of drug resistance in patients with relapsed MM.
We will sequence 600 RNA samples isolated from several ongoing clinical trial samples with external collaborators at UCL, London, at baseline and following relapse. We have already generated pilot data on RNA and DNA isolated from 21 MM patients and identified several novel translocations not identified previously by SR-RNA sequencing (Fig2). We have a well-established wet-lab workflow with which we will generate data on 600 MM patients. It is anticipated that over half of the samples will have been sequenced by the start of the DPhil.
Collaboration, mentoring and environment
The student will receive training in the necessary cellular, molecular, and epigenetic biology for this project. This will involve wet-lab workflows for generating LR sequencing data. Extensive training in computational biology will be provided so that the student can analyse their own data. Specifically, this will include software development, data analytics, statistics and computational pipeline development. Outside the lab, the student will be expected to attend regular seminars with high profile external speakers, journal clubs and training in presentation skills, scientific writing, and data management.
Translational potential of the project
The stated aim of this project is to study the molecular mechanisms of Multiple Myeloma drug resistance and evaluate drug targets for therapy. By its very definition, this is likely to identify novel therapeutic intervention points within the development of Multiple Myeloma. We have extensive collaborations with several pharmaceutical partners, and we will utilise these interactions to explore the translational potential of targets.
- 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. https://www.nature.com/articles/s41587-021-00965-w.pdf
Cribbs et al 2020, Dissecting the role of BET bromodomain proteins BRD2 and BRD4 in Human NK cell function. Frontiers in Immunology https://www.frontiersin.org/articles/10.3389/fimmu.2021.626255/pdf
Cottone et al 2020. Inhibition of H3K27 demethylases inactivated Brachyury and promotes chordoma cell death. Cancer research https://aacrjournals.org/cancerres/article-pdf/80/20/4540/2871878/4540.pdf
Cribbs et al 2020. Histone H3K27me3 demethylases regulate human Th17 cell development and effector functions by impacting on metabolism. PNAS. https://www.pnas.org/doi/epdf/10.1073/pnas.1919893117
The Research group
The multi-disciplinary group is led by Ass Prof Cribbs (https://www.ndorms.ox.ac.uk/team/adam-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 long-read applications 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 Sarah Gooding is a myeloma clinician scientist funded by Cancer Research UK. She focuses on precision target discovery for high-risk myeloma patients, is NCRI myeloma subgroup translational lead, and leads targeted panel sequencing in the UK Myeloma XV/RADAR trial and NHS laboratories. Her experience includes using patient molecular data to guide therapeutic decisions and identify drug-specific responses. Prof Anjan Thakurta is a molecular biologist with an industrial background in translational medicine. Over the past five years, he has spearheaded collaborative efforts to decode the Myeloma Genome, culminating in the creation of the most extensive database for this disease. His involvement will undoubtedly guide the project closer to its translational objectives.
For general inquiries: Sam Burnell (Samuel.email@example.com), Graduate Studies Officer.
For project related inquiries: Adam Cribbs (firstname.lastname@example.org), 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
It is recommended that, in the first instance, you contact the relevant supervisor(s) and the Graduate Studies Office (email@example.com), 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 D.Phil or MSc (by research) will commence in October 2024.
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)
MSc by research in Molecular and Cellular Medicine (course code: RM_MP1)
For further information, please visit http://www.ox.ac.uk/admissions/graduate/applying-to-oxford.