Therapeutic targeting of refractory/relapsed diffuse large B-cell lymphoma through systems biology

Lead Research Organisation: University of Sussex
Department Name: Brighton and Sussex Medical School

Abstract

More than 13,000 people are diagnosed with non-Hodgkin lymphoma, a cancer of immune cells, annually in the UK. The most common non-Hodgkin lymphoma is Diffuse Large B-cell lymphoma (DLBCL). A large proportion (~40%) of patients with DLBCL are not cured, resulting in relapsed/refractory DLBCL (RR-DLBCL), and for these patients the outlook is dismal. There has been remarkable recent progress revealing differences in genetics and molecular biology of healthy B-cells compared to DLBCL cancer cells. We are learning more and more about the way genetic changes in B-cells can lead to the processes controlling cell survival, cell division and cell differentiation, going wrong in DLBCL. Despite this progress, the standard treatment for DLBCL has remained unchanged for more than a decade. Standing in the way of progress towards new treatments is the remarkable differences between one DLBCL case and the next. Drugs that are targeted to molecular-scale interactions in RR-DLBCL often only work in subsets patients. The challenge faced, is understanding the molecular makeup of each person's RR-DLBCL, and using this to target a drug the "Achilles heel" of that patient's cancer.
Systems biology simulations are equations representing how the molecules in a cell change over time. It is possible to simulate how many individual B-cells respond to treatment by solving these equations. I have recently used this approach to discover new molecular interactions and show that cell fates are remarkably predictable. Excitingly, I found that I could use these simulations to predict promising and unexpected ways to control cells, that were confirmed when tested in the lab. I also found that when I simulate molecular-scale differences found in DLBCL, the simulations recreate the uncontrolled cell divisions and cell survival of cancer cells. My simulations are strikingly similar to two common subtypes of DLBCL seen in patients.
In this project, my group will use these simulations of B-cells, and add genetic mutations found in DLBCL patients, to create virtual laboratories of different types of DLBCL responding to therapy. In our virtual labs we will show how different mutations on the genetic scale can cause molecular-scale differences leading to cell-scale changes that eventually change how well treatments works.
The beauty of investigating RR-DLBCL with virtual labs is that we can do things that would be difficult or impossible in traditional laboratories. Here, we will simulate targeting drugs to each and every important molecular process in RR-DLBCL cells, to predict the most effective drug targets. We will use these virtual experiments to predict effective drug targets, and then validate the best approaches in the traditional lab. We will use simulations to identify "biomarkers", a property of cancer cells that we can measure, to predict the most effective drug for each patient. We will then test these biomarkers and treatments using traditional laboratory techniques such as measuring proteins and drugging cells that have different genetic mutations.
Another impossible experiment, that can be done with our systems biology simulations, is tracking concentrations of all important molecules inside cells simultaneously all the way from diagnosis to end of treatment. We will use this to "rewind the clock" in our simulations and predict which DLBCL cells a patient has when they're diagnosed become treatment resistant RR-DLBCL cells when the patient is treated. Then, by virtually drugging every target we will find the best way to either: kill these cells before standard treatment is given, or make these cells sensitive to the standard treatment.
This work enables us to develop new approaches to treating DLBCL. We will show that we can measure biomarkers in patients and put these measurements into simulations to create personalised "virtual patients", which we can then use to help decide the best treatment for each person.

Planned Impact

Diffuse Large B-cell Lymphoma (DLBCL) is the most common non-Hodgkin lymphoma and current treatment protocols lead to treatment refractory/relapsed disease (RR-DLBCL) in around 40% of patients. For these patients the outlook is dismal with secondary therapies only achieving median overall survival of ~6 months. Here I describe a novel interdisciplinary approach to gaining a mechanistic understanding of RR-DLBCL, rational therapeutic design and development of a personalised medicine approach to the disease. The goal of this project is to advance the scientific field by improving mechanistic insight into DLBCL, improve patient outcomes through identification of promising therapeutic techniques and contribute to the development of computationally-driven personalised medicine for substantial economic, commercial and societal impact within the timeline of this project and beyond.
The most immediate impact will be in the field of lymphoma research where we will provide a greater understanding of the mechanisms by which RR-DLBCL develops and link molecular understanding with lymphoma treatment/progression. In the longer-term, the systems biology research community broadly share a common goal: to construct virtual cells, organs and organisms to enable virtual experiments with clear substantial impact. The work here modelling B-cell fates in disease contributes to this and is likely to be incorporated in comprehensive models of whole organs and organisms as progress is made. Additionally, the successful application of computationally-generated insights to unmet needs in human health in this project will represent an exemplar project, motivating researchers, funding agencies and policy makers to accelerating progress towards the goal of virtual cells, organs and organisms.
Pharmaceutical companies will benefit from utilising systems approaches to accelerate drug discovery, stratify patients to identify sub-population in whom their drugs are likely to be efficacious, and reducing the cost of drug development by prioritising targets computationally predicted to be safe and effective (see support letter from NuCana PLC).
This work enables a personalised medicine approach. I aim to change the standard of care using computational models, personalised to patients as tools to facilitate therapeutic decision making in clinical practice. This approach has the potential for substantial impact beyond DLBCL, as it can be applied to any disease for which there is sufficient mechanistic understanding. The impact of this approach would be significant for health and wellbeing of patients receiving improved therapy, the economic competitiveness of the UK as it will attract substantial investment, and the efficacy of the NHS as it targets drugs to patients who will benefit. I expect initial clinical trials of personalised, model-assisted therapeutic decision making to be initialised on completion of this fellowship. Public outreach will also help improve understanding of systems medicine in the wider public and healthcare communities.
The impact of this fellowship on my career trajectory towards becoming a leader will be substantial. I will gain substantial expertise and experience through the delivery of this project, particularly in the areas of leading an interdisciplinary scientific team. These skills will complement my upward career trajectory to enable me to maximise my impact as I establish myself as a research and innovation leader.
The two postdoctoral research staff working on this project will both receive substantial training in computational biology, cancer biology, iterative experimental and systems studies, molecular and cellular biology, along with more general skills such as scientific communication, presentation skills, interdisciplinary collaboration and project management. This will position them well for high impact employment in the academic or commercial sectors.

Publications

10 25 50
 
Description - We have shown that through computational systems biology we can predict in the computer which drugs will work in which lymphoma cells, and we have validated computational predictions with lab experiements. This is described in a submitted article, which is currently a pre-print. We have identified biomarkers that may enable the optimum therapy to be assigned. Simualtions of resistance to therapy have revealed how the molecular networks adapt to create treatment resistance cell populations.
- We have established simuations of individual patients from large studies and shown that computational models can provide personalise predictions of outcomes and potential therapeutic targets.
- We have deveoped a new quantitative experimental analysis technique (called NF-kB fingerprinting) and find that it reveals a vast amount of previously uncaracterised heterogeneity in lymphoma.
- We have shown that computational modeling enables us to predict how tumour cells will respond to their microenvironment, and how this is determined by a combination of mutations and the level of protein expression in the cells.
Exploitation Route The models produced are freely available for the community and therefore others can take these approaches forward and use simualtions to make preditions on how drugs will impact lymphoma.
The experimental analysis techniques we have developed will enable other to determine the signaling state of cells from a variety of sources incuding patient tumour samples, blood, cell lines and others.
Take together our experimental and computational approaches will help other to get the right drugs into the right patietns in a variety of malignancies.
Sectors Healthcare

Pharmaceuticals and Medical Biotechnology

URL http://www.mitchell.science
 
Description A Systems Biology Approach to Tailoring Therapy for Diffuse Large B-Cell Lymphoma
Amount £123,522 (GBP)
Funding ID 2020/JGF/003 
Organisation Leukaemia UK 
Sector Charity/Non Profit
Country United Kingdom
Start 02/2021 
End 09/2023
 
Description BSMS 20 Studentship
Amount £120,000 (GBP)
Funding ID BSMS20 
Organisation University of Sussex 
Sector Academic/University
Country United Kingdom
Start 09/2024 
End 09/2027
 
Description International Exchanges 2023 Cost Share (JSPS)
Amount £24,000 (GBP)
Funding ID IEC\R3\233004 
Organisation The Royal Society 
Sector Charity/Non Profit
Country United Kingdom
Start 04/2024 
End 04/2026
 
Description Travel grant to present work at EBMO workshop
Amount € 1,000 (EUR)
Organisation European Molecular Biology Organisation 
Sector Charity/Non Profit
Country Germany
Start 11/2023 
End 12/2023
 
Description Unviersity of Brighton PGR mobilisation scheme
Amount £8,000 (GBP)
Funding ID Travel Award 
Organisation University of Brighton 
Sector Academic/University
Country United Kingdom
Start 05/2024 
End 07/2024
 
Title A novel computational model of apoptosis 
Description The ordinary differential equation model enables simulation of the response of lymphoma to BH3 mimetic, the predictions are validated by experiments. It is described in this preprint. 
Type Of Material Computer model/algorithm 
Year Produced 2023 
Provided To Others? Yes  
Impact In healthy cells, pro- and anti-apoptotic BCL2 family and BH3-only proteins are expressed in a delicate equilibrium. In contrast, this homeostasis is frequently perturbed in cancer cells due to the overexpression of anti-apoptotic BCL2 family proteins. Variability in the expression and sequestration of these proteins in Diffuse Large B cell Lymphoma (DLBCL) likely contributes to variability in response to BH3-mimetics. Successful deployment of BH3-mimetics in DLBCL requires reliable predictions of which lymphoma cells will respond. Here we show that a computational systems biology approach enables accurate prediction of the sensitivity of DLBCL cells to BH3-mimetics. We found that fractional killing of DLBCL, can be explained by cell-to-cell variability in the molecular abundances of signaling proteins. Importantly, by combining protein interaction data with a knowledge of genetic lesions in DLBCL cells, our in silico models accurately predict in vitro response to BH3-mimetics. Furthermore, through virtual DLBCL cells we predict synergistic combinations of BH3-mimetics, which we then experimentally validated. These results show that computational systems biology models of apoptotic signaling, when constrained by experimental data, can facilitate the rational assignment of efficacious targeted inhibitors in B cell malignancies, paving the way for development of more personalized approaches to treatment. The model can predict the response to drugs without the use of animal experiments. 
URL https://github.com/SiFTW/BH3Models
 
Description Aquisition of clinical samples from Eastbourne General Hospital with John Jones 
Organisation University Hospitals Sussex NHS Foundation Trust
Country United Kingdom 
Sector Hospitals 
PI Contribution Our Team analyse lymphoma samples provided by Dr Jones and assist with processing and freezing of primary material from patients with haematological malignancies.
Collaborator Contribution Anonymised DLBCL patients samples and clinical information relating to the sample.
Impact We have performed NF-kB fingerprinting on these samples and report these results in a recent paper that has been submitted and is currently under review.
Start Year 2022
 
Description Collaboration with Koushik Roy in Utah 
Organisation University of Utah
Country United States 
Sector Academic/University 
PI Contribution I perform computational modelling of immune reactions to provide mechanistic insight into experimental data from the lab of Koushik Roy, Assistant Professor of Microbiology & Immunology at the University of Utah
Collaborator Contribution Koushik Roy provides experimental validation and novel data to our collaboration using specialised mouse models and experimental approaches.
Impact Papers are upcoming. This is a multidisciplinary collaboration involving computational biology, mathematics, experimental immunology in both cell lines and mice.
Start Year 2023
 
Description Collaboration with Prof Andrea Pepper 
Organisation University of Sussex
Department Brighton and Sussex Medical School
Country United Kingdom 
Sector Academic/University 
PI Contribution My team provide systems biology (computational and experimental) expertise into projects focused on cell signalling in CLL and DLBCL.
Collaborator Contribution Prof Andrea Pepper's team provide patient samples and experimental data along with providing supervision and training of members of my team.
Impact 1: Burley TA, Kennedy E, Broad G, Boyd M, Li D, Woo T, West C, Ladikou EE, Ashworth I, Fegan C, Johnston R, Mitchell S, Mackay SP, Pepper AGS, Pepper C. Targeting the Non-Canonical NF-?B Pathway in Chronic Lymphocytic Leukemia and Multiple Myeloma. Cancers (Basel). 2022 Mar 15;14(6):1489. doi: 10.3390/cancers14061489. PMID: 35326640; PMCID: PMC8946537. 2: Kennedy E, Coulter E, Halliwell E, Profitos-Peleja N, Walsby E, Clark B, Phillips EH, Burley TA, Mitchell S, Devereux S, Fegan CD, Jones CI, Johnston R, Chevassut T, Schulz R, Seiffert M, Agathanggelou A, Oldreive C, Davies N, Stankovic T, Liloglou T, Pepper C, Pepper AGS. TLR9 expression in chronic lymphocytic leukemia identifies a promigratory subpopulation and novel therapeutic target. Blood. 2021 Jun 3;137(22):3064-3078. doi: 10.1182/blood.2020005964. PMID: 33512408; PMCID: PMC8176769. 3: Burley TA, Hesketh A, Bucca G, Kennedy E, Ladikou EE, Towler BP, Mitchell S, Smith CP, Fegan C, Johnston R, Pepper A, Pepper C. Elucidation of Focal Adhesion Kinase as a Modulator of Migration and Invasion and as a Potential Therapeutic Target in Chronic Lymphocytic Leukemia. Cancers (Basel). 2022 Mar 22;14(7):1600. doi: 10.3390/cancers14071600. PMID: 35406371; PMCID: PMC8996841. Highly interdisciplinary collaboration with experimental experts.
Start Year 2021
 
Description Collaboration with Prof Chris Pepper 
Organisation University of Sussex
Department Brighton and Sussex Medical School
Country United Kingdom 
Sector Academic/University 
PI Contribution My group provide computational input into collaborative projects investigating NF-kB signalling in DLBCL and CLL.
Collaborator Contribution Prof Chris Pepper provides cell lines, experimental reagants and equipment, along with substantial supervision and mentorship of my team.
Impact 1: Burley TA, Kennedy E, Broad G, Boyd M, Li D, Woo T, West C, Ladikou EE, Ashworth I, Fegan C, Johnston R, Mitchell S, Mackay SP, Pepper AGS, Pepper C. Targeting the Non-Canonical NF-?B Pathway in Chronic Lymphocytic Leukemia and Multiple Myeloma. Cancers (Basel). 2022 Mar 15;14(6):1489. doi: 10.3390/cancers14061489. PMID: 35326640; PMCID: PMC8946537. 2: Kennedy E, Coulter E, Halliwell E, Profitos-Peleja N, Walsby E, Clark B, Phillips EH, Burley TA, Mitchell S, Devereux S, Fegan CD, Jones CI, Johnston R, Chevassut T, Schulz R, Seiffert M, Agathanggelou A, Oldreive C, Davies N, Stankovic T, Liloglou T, Pepper C, Pepper AGS. TLR9 expression in chronic lymphocytic leukemia identifies a promigratory subpopulation and novel therapeutic target. Blood. 2021 Jun 3;137(22):3064-3078. doi: 10.1182/blood.2020005964. PMID: 33512408; PMCID: PMC8176769. 3: Burley TA, Hesketh A, Bucca G, Kennedy E, Ladikou EE, Towler BP, Mitchell S, Smith CP, Fegan C, Johnston R, Pepper A, Pepper C. Elucidation of Focal Adhesion Kinase as a Modulator of Migration and Invasion and as a Potential Therapeutic Target in Chronic Lymphocytic Leukemia. Cancers (Basel). 2022 Mar 22;14(7):1600. doi: 10.3390/cancers14071600. PMID: 35406371; PMCID: PMC8996841. Multi-disciplinary collaboration with experimental experts.
Start Year 2021
 
Description Computational input into quantifying RNA dynamics with Prof Newbury's lab 
Organisation University of Sussex
Department Brighton and Sussex Medical School
Country United Kingdom 
Sector Academic/University 
PI Contribution I developed a computational pipeline for the analysis of SLAM-seq data to enable analysis of the mechanisms underlying the regulation of cell proliferation and stress by the exoribonuclease DIS3L2.
Collaborator Contribution The Newbury lab performed all data generation and conceived the study.
Impact Poster presentation at RNA UK 2022. This is a muiti-disciplinary collaboration as we provided computational expertise to the project while the experimental and translational work was performed by the Newbury Group.
Start Year 2021
 
Description Computational modelling of myeloma signalling Erika Mancini lab (2021 - Still Active) 
Organisation University of Sussex
Department School of Life Sciences Sussex
Country United Kingdom 
Sector Academic/University 
PI Contribution I provided computational modelling as part of a collaboration investigating targetting cell signalling in multiple myeloma.
Collaborator Contribution Data generated by the collaborators was used to inform the computational modelling
Impact This work has conributed to a PhD thesis, and the following paper: 1: Agnarelli A, Mitchell S, Caalim G, Wood CD, Milton-Harris L, Chevassut T, West MJ, Mancini EJ. Dissecting the impact of bromodomain inhibitors on the Interferon Regulatory Factor 4-MYC oncogenic axis in multiple myeloma. Hematol Oncol. 2022 Aug;40(3):417-429. doi: 10.1002/hon.3016. Epub 2022 May 18. PMID: 35544413; PMCID: PMC9543246.
Start Year 2021
 
Description International Collaborations wth the Institute for Protein Research 
Organisation Osaka University
Department Institute of Protein Research
Country Japan 
Sector Academic/University 
PI Contribution In a new collaboration we are applying our success in lymphoma to breast cancer. I have made knowledge exchange visits with Osaka University funded by Osaka Unviersity. We have successfully secured a Royal Society/JSPS cost share international exchange grant with a value of 12,000 to our lab.
Collaborator Contribution In a new collaboration we are applying our success in lymphoma to breast cancer. Prof Okada's group provide new insight into personalising models, machine learning and breast cancer to this project. We have successfully secured a Royal Society/JSPS cost share international exchange grant with a value of 12,000 to our lab.
Impact JSPS/Royal Society International Exchange Grant,
Start Year 2023
 
Description Investigating signalling heterogeneity in DLBCL lines by Flow Cytommetry and computational modelling with Martin Dyer 
Organisation University of Leicester
Department The Ernest and Helen Scott Haematological Research Institute
Country United Kingdom 
Sector Academic/University 
PI Contribution We e have provided insight into the regulation of apoptosis and NF-kB obtained through our computational modelling efforts. The first results of this collaboration are going to be submitted to the European Hematology Association (EHA)'s annual congress 2022 as a joint abstract.
Collaborator Contribution Martin Dyer at the University of Leicester has provided us with cell lines for the study of NF-kB by flow cytommetry. We have had a number of meetings discussing our results with him and his team. He has helped guide our research direction and avoid pitfalls while also mentoring me and our team.
Impact Abstract was presented at EHA 2022. A new computational model (software simulation) of cell death has been constructed from this collaboration. A Presentation given at ESH (European School of Haematology) 6th Translational Research Conference "LYMPHOID MALIGNANCIES" has resulted from this collaboration. The following preprint is a result of this collaboration: Cloete I, Smith VM, Jackson RA, Pepper A, Pepper C, Vogler M, Dyer MJ, Mitchell S. Computational modeling of DLBCL predicts response to BH3-mimetics. doi:10.1101/2023.02.01.526592. PPR:PPR611457. This collaboration is multi-disciplinary as we provide computational and theoretical skills while our collaborators have substantial expertise in laboratory and clinical sciences.
Start Year 2021
 
Title The NF-kB multidimer system model: A knowledge base to explore diverse biological contexts 
Description This model allows people to simulate the NF-kB signalling network in a variety of cellular contexts, including health and disease. 
Type Of Technology Software 
Year Produced 2023 
Open Source License? Yes  
Impact We have published the model in Science Signalling (in press 2023). 
URL https://zenodo.org/record/7669508#.ZAsLirTP2aw
 
Description BSMS Outreach lecture 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Schools
Results and Impact Anyone could attend this outreach lecture, but it was aimed at school students considering attending medical school.
We had 77 unique attendees to the session, with attendees tuning in from the UK, Hungary, and Trinidad and Tobego.
The questions at the end indicated interest in systems biology approaches and what it means for the future of medicine.
The talk is also on YouTube.
Year(s) Of Engagement Activity 2022
URL https://www.youtube.com/watch?app=desktop&v=xhPCPfK4ksw
 
Description Co-hosted Blood Cancer Research Showcase & Lab Tour - Friday 3rd November 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Patients, carers and/or patient groups
Results and Impact We invited patients, carers and families to come and meet the team of blood cancer researchers at Brighton and Sussex Medical School. The afternoon started with a tour of our research labs, followed by an opportunity to chat with the team over refreshments with poster presentations. As well as seeing how we work and meeting the team, we used the opportunity to better understand what is important to patients and their families.
Year(s) Of Engagement Activity 2024
URL https://www.sussexcancerfund.co.uk/blood-cancer-research-showcase-lab-tour-friday-3rd-november/
 
Description Co-hosted Patient Directed Research - Blood Cancer Research Patient Forum 7th October 2022 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Patients, carers and/or patient groups
Results and Impact I co-organised (with Profs Chris Pepper, Andrea Pepper and the Sussex Cancer Fund) Patient Directed Research - Blood Cancer Research Patient Forum 7th October 2022. The goal was for patient's and their families to help us shape the direction of blood cancer research at Sussex.
It was attended by patient's, families and the local charity Sussex Cancer Fund. Feedback indicated all patient's left with a greater understanding of their disease, of the research taking place into their disease and the work done by our teams in this area.
Year(s) Of Engagement Activity 2022
URL https://www.sussexcancerfund.co.uk/blood-cancer-research-patient-forum/
 
Description Hosted Lymit 2022. A new meeting focused on highlighting exciting novel research that uses interdisciplinary techniques to understand blood cancer. 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact LyMIT 2022 was hosting on the 6th September at the University of Sussex and attracted an international lineup of speakers and attendee. Feedback was overwhelmingly positive with calls to make the event a recurring event.
Year(s) Of Engagement Activity 2022
URL https://www.mitchell.science/lymit2022/
 
Description Invited talk (Southampton University) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact Gave invited talk at Southampton University titled: "Systems Biology of B-cells in health and lymphoma"
The talk was followed and proceeded by meetings with the senior academic staff at the University of Southampton, which has sparked a number of collaborative oppotunities.
Year(s) Of Engagement Activity 2021
 
Description Invited talk (University of Leicester) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Other audiences
Results and Impact Gave invited talk at University of Leicester. The talk was followed by discussions the senior academic staff. This has lead to an ongoing and productive collaboration with prof Martin Dyer.
Year(s) Of Engagement Activity 2021