Name: Cell Plasticity in Cancer Evolution
Start: 2025-05-19T10:00:00+02:00
End: 2025-05-22T19:30:00+02:00
Location: No location set

Cell Plasticity in Cancer Evolution

from Monday, 19 May 2025 (10:00) to Thursday, 22 May 2025 (19:30)

Monday, 19 May 2025

15:00 Welcome and check-in
Welcome and check-in
15:00 - 15:20
15:20 Welcome session - Arne Traulsen
Welcome session
- Arne Traulsen
15:20 - 16:00
16:00 Keynote: Susanne Sebens
Susanne Sebens
16:00 - 17:00
Contributions

16:00 The various shades of plasticity in pancreatic cancer - Susanne Sebens (Kiel University)
17:00 Coffee Break
Coffee Break
17:00 - 17:20
17:20 Mathematical modeling of blood cancers, chronic inflammation and treatment - Morten Andersen (Roskilde University , Denmark)
Mathematical modeling of blood cancers, chronic inflammation and treatment
- Morten Andersen (Roskilde University , Denmark)
17:20 - 17:40
Authors: M. Andersen, H. Hasselbalch, T. Stiehl, J.T. Ottesen Human blood cell production is maintained by hematopoietic stem cells (HSC) which give rise to all types of mature blood cells. Experimental observation of HSC in their physiologic bone-marrow microenvironment, the so-called stem cell niche, is challenging. Therefore, the details of HSC dynamics and the cellular interactions in the stem cell niche remain elusive. Mutations that lead to a competitive advantage are the cause of clinical challenges when treating HSC-derived malignancies such as acute myeloid leukemia or the myeloproliferative neoplasms (MPN). To investigate the significance of the interaction between the HSC and the stem cell niche in these malignancies, we propose and analyse a mechanism-based mathematical model of HSC dynamics within the bone-marrow microenvironment. The JAK2V617 mutation is a key driver for overproduction of blood cells in MPN with chronic inflammation acting as an additional driver of the disease. Long-term treatment with interferon-alfa (IFN) can reduce the disease burden of MPN patients. Determining individual patient responses to IFN therapy may allow for efficient personalized treatment, reducing both drop-out and disease burden. The mathematical model is calibrated to data of the randomized trial study DALIAH. Through comprehensive modeling of the effects of IFN, the model was related to individualized patient-data consisting of longitudinal hematologic and molecular measurements. We believe that this approach could have direct clinical relevance, offering expert guidance for clinical decisions about IFN treatment of MPN patients. If time permits we will address recent findings of mathematical modeling and data of pre-disease dynamics (CHIP) as well as experimental combination therapy for MPN patients receiving IFN combined with inflammation inhibitors.
17:40 Heritability and selection in clonal evolution of chronic lymphocytic leukaemia with bimodal CD49d expression - Riccardo Bergamin (University of Trieste, Italy)
Heritability and selection in clonal evolution of chronic lymphocytic leukaemia with bimodal CD49d expression
- Riccardo Bergamin (University of Trieste, Italy)
17:40 - 18:00
The traditional clonal evolution model integrates genetic mutations and clonal selection but often neglects the critical role of phenotypic plasticity. In this study, we combine longitudinal whole-genome sequencing and flow cytometry data to investigate the progression of chronic lymphocytic leukaemias with bimodal CD49d expression, a prime example of complex clonal evolution. We introduce a novel population genetics framework that incorporates reversible phenotypic switching into clonal dynamics, enabling the reconstruction of evolutionary trajectories for CD49d+ and CD49d- subpopulations. By leveraging mutation data and white blood cell counts, we quantify patient-specific CD49d expression heritability and selection parameters. Our findings demonstrate that transitioning to CD49d+ frequently confers a selective advantage, driving differential growth rates between subpopulations. The heritability of CD49d expression varies across patients, reflecting a spectrum of selective pressures and plasticity. This enhanced clonal deconvolution and phylogenetic analysis underscores the interplay of genetic and epigenetic factors in shaping tumour clonal architecture, providing a robust foundation for developing personalised therapeutic strategies targeting phenotypic heterogeneity.
18:00 Characterization of cancer stemness phenotypes in pancreatic cancer - Lisa-Marie Philipp (UKSH)
Characterization of cancer stemness phenotypes in pancreatic cancer
- Lisa-Marie Philipp (UKSH)
18:00 - 18:20
Authors: Lisa-Marie Philipp, Axel Künstner, Anne-Sophie Mehdorn, Charlotte Hauser, Jan-Paul Gundlach, Olga Will, Sören Franzenburg, Hendrike Knaack, Udo Schumacher, Hauke Busch, Susanne Sebens Pancreatic ductal adenocarcinoma (PDAC) is mostly diagnosed at advanced or even metastasized stages limiting patient´s prognosis and overall survival. Metastasis requires strong cancer cell plasticity and high tumor cell heterogeneity implying phenotypic switching, notably, Epithelial-Mesenchymal-Transition (EMT) being associated with the gain of cancer stem cell (CSC) properties, in response to changing environments. To analyze whether CSC-properties are related to distinct EMT-phenotypes and if this CSC-EMT axis impacts malignancy-associated properties, this study aimed at characterizing mesenchymal-like and epithelial PDAC cell variants, with the focus on CSC populations. Single-cell cloning of PDAC cells revealed CSC (Holoclone) and non-CSC (Paraclone) clones from both mesenchymal-like (Panc1) and epithelial (Panc89) cells. Comparatively analyzing parental Panc1 and Panc89 as well as related Holo- and Paraclone cells, it was found that Panc1 and Panc89 cell variants exhibit differences in their colony formation ability, reflecting the potential to self-renew, as well as distinct transcriptional CSC and EMT signatures. While Panc1 cell variants show increased signatures of EMT, Panc89 cell variants exhibit increased self-renewal capacity and CSC signatures. Isolated Panc1 Holoclone cells show a mesenchymal phenotype dominated by high expression of the CSC marker Nestin, while Panc89 Holoclone cells exhibit a Sox2-dominated epithelial stemness phenotype. Functional analysis revealed decreased cell growth for Panc1 cell variants compared to Panc89 cell variants, while response to chemotherapy was overall higher Panc89 cell variants. Panc1 Holoclones show the weakest response to treatment, while Panc89 Holoclones showed the strongest affection to therapy. Invasion assays presented Panc1 cell variants to have an increased invasion potential compared to Panc89 cell variants, while Panc89 cell populations show stronger migration ability. Further detailed, Panc1 Holoclone cells are highly invasive in a mesenchymal-like invasion manner, while Panc89 Holoclone cells show pronounced cell migration in clusters. In vivo, Panc1 and Panc89 cell variants essentially differ with respect to their metastatic capacity, as Panc1 and Panc89 Holo- and Paraclone tumors varied regarding number and size of metastases formed as well as organ manifestation, leading to different survival outcomes. Overall, these data support the view of EMT-related plasticity and heterogeneity within cancer (stem) cells in PDAC, differentially impacting metastatic propensities.
18:20 Dinner
Dinner
18:20 - 19:20

19:20 Keynote: Marco Gerlinger
Marco Gerlinger
19:20 - 20:20
Tuesday, 20 May 2025
09:00 Keynote: Peter Friedl
Peter Friedl
09:00 - 10:00
Contributions

09:00 Tumor microenvironment and nutrient deprivation: plasticity of biomechanics, invasion and metastasis - Peter Friedl (Radboud University Medical Centre, Netherlands)
10:00 Cancer Cells Sphingolipids Metabolic Plasticity Defines Cell Fitness in Adaptation to Harsh Tumor Microenvironments - Mehdi Damaghi (Stony Brook University)
Cancer Cells Sphingolipids Metabolic Plasticity Defines Cell Fitness in Adaptation to Harsh Tumor Microenvironments
- Mehdi Damaghi (Stony Brook University)
10:00 - 10:20
Authors: Raafat Chalar, Yujie Xiao, Joon-Hyun Song, Naheel Khatri, Jowana Obeid, Andrew Chen, Fabiola Velazquez, Daniel Canal, Yusuf Hannun, Giovanni D'Angello, Mehdi Damaghi Phenotypic plasticity and metabolic reprogramming in cancer cells are essential for their adaptation to their harsh tumor microenvironment (TME). Pre-existing cell states and phenotypic plasticity can define the evolutionary trajectories and eventually cell fates under TME selection pressures. Here we used spatial multi-omics approaches at single cell resolution followed by principles of ecology analysis to decipher the impact of the sphingolipid metabolic plasticity on the evolution of breast cancer cells under selection of acidic microenvironment. Cancer cells exposed to acute and chronic acid stress regulate their sphingolipid metabolism with an impressive level of plasticity to choose the ceramide metabolic pathway. Acute acid exposure induces ceramides accumulation that is toxic to the cells and needs to be cleared so the cells survive. Remarkably, cancer cells with long term acid exposure efficiently suppress ceramide accumulation by utilizing various ceramide metabolic pathways. CRISPR/Cas screening revealed the ceramide-> Sphingosin-1-P (S1P) pathway is essential for cancer cell viability under acidic conditions. Notably, multiple Ceramidases (CDases) and Sphingosine Kinase-1 (SPHK1) were significantly upregulated in both in vitro and in vivo acidic environments. When S1P was blocked, cancer cells still survived implying their plasticity. We then performed single cell multi-omics (RNA/ATAC) sequencing data to capture heterogeneity of response in response to acid seeking for alternatives for S1P path.Transcriptome analysis revealed over expression of several enzymes of glucosylceramide pathway in acid adapted cells. We then blocked both S-1-P and glucosylceramide pathways and cancer cells still survived. To explore the plasticity of ceramide metabolism, we investigated all four major metabolic pathways in 3D spheroids and patient-derived organoids. Using MALDI mass spectrometry, we confirmed the mechanisms of action of targeted inhibitors and observed pathway switching when one metabolic route was blocked. Our findings revealed a high degree of metabolic plasticity in cancer cells, showcasing their ability to adapt by redirecting metabolic flux under selective pressure. Leveraging this plasticity, we employed sphingolipid metabolism inhibitors in patient-derived organoids to manipulate cancer cell behavior and evolutionary trajectories. This approach aimed to shift the adaptive landscape of cancer cells as part of an evolutionary therapy strategy, offering a promising new therapeutic avenue that targets cancer cell resilience and adaptability.
10:20 Mitigating non-genetic resistance to checkpoint inhibition based on multiple states of immune exhaustion - Irina Kareva (Northeastern University)
Mitigating non-genetic resistance to checkpoint inhibition based on multiple states of immune exhaustion
- Irina Kareva (Northeastern University)
10:20 - 10:40
Authors: Irina Kareva, Jana Gevertz Despite the revolutionary impact of immune checkpoint inhibition on cancer therapy, the lack of response in a subset of patients, as well as the emergence of resistance, remain significant challenges. Here we explore the theoretical consequences of the existence of multiple states of immune cell exhaustion on response to checkpoint inhibition therapy. In particular, we consider the emerging understanding that T cells can exist in various states: fully functioning cytotoxic cells, reversibly exhausted cells with minimal cytotoxicity, and terminally exhausted cells. We hypothesize that inflammation augmented by drug activity triggers transitions between these phenotypes, which can lead to non-genetic resistance to checkpoint inhibitors. We introduce a conceptual mathematical model, coupled with a standard 2-compartment pharmacometric (PK) model, that incorporates these mechanisms. Simulations of the model reveal that, within this framework, the emergence of resistance to checkpoint inhibitors can be mitigated through altering the dose and the frequency of administration. Our analysis also reveals that standard PK metrics do not correlate with treatment outcome. However, we do find that levels of inflammation that we assume trigger the transition from the reversibly to terminally exhausted states play a critical role in therapeutic outcome. A simulation of a population that has different values of this transition threshold reveals that while the standard high-dose, low-frequency dosing strategy can be an effective therapeutic design for some, it is likely to fail a significant fraction of the population. Conversely, a metronomic-like strategy that distributes a fixed amount of drug over many doses given close together is predicted to be effective across the entire simulated population, even at a relatively low cumulative drug dose. We also demonstrate that these predictions hold if the transitions between different states of immune cell exhaustion are triggered by prolonged antigen exposure, an alternative mechanism that has been implicated in this process. Our theoretical analyses demonstrate the potential of mitigating resistance to checkpoint inhibitors via dose modulation.
10:40 Coffee break
Coffee break
10:40 - 11:20
11:20 Liquid biopsy for non-invasive molecular characterisation and MRD analysis in progressive multiple myeloma - Cyrus Khandanpour (UKSH)
Liquid biopsy for non-invasive molecular characterisation and MRD analysis in progressive multiple myeloma
- Cyrus Khandanpour (UKSH)
11:20 - 11:40
Authors: A. Schilhabel, M. Khouja, S. Neumann, T. Stadler, H. Ahmed, E. Dazert, T. Gemoll, U. Günther, I. König, M. Kotrova, H. Busch, C. Baldus, C. Pott, N. von Bubnoff, M. Brüggemann, C. Khandanpour MM is a rare hematological malignancy in Europe and is not curable(1). It relapses and the time interval from each line to the next one decreases, requiring frequent changes of regime(2). Bispecific antibody have the potential to transform the treatment paradigm of MM(2, 3). However, also for Bispecific antibody current practice mandates continuous therapy for all patients in complete remission, even though the impact on disease control remains uncertain and potential side effects may worsen over time. Moreover, prolonged administration of Bispecific antibody can exhaust T-cells, potentially impairing their therapeutic efficacy (Fig. 1). Hence, we aim to alter the application method of Bispecific antibody. Continuous therapy with bispecific antibodies might exhaust T-cells worsens prognosis and contributes to cloneal evolution. It also increases infectious complications and is associated with high cost. From (4). Assessment of response rate (either CR or CR combined with MRD-negativity) could identify patients with sustainable response, who do not require continuous therapy but potentially a reduced rate of application. It could even improve outcome of patients by reducing T-cell exhaustion and other negative effects without hampering disease control (3, 5). Simultaneously, therapy will be promptly restarted if MRD relapse is indicating imminent loss of CR. Current practice for determining MRD relies on invasive and painful bone marrow punctures. In addition, single bone marrow samplings do not accurately reflect the whole disease status, given the MM heterogeneity, high clonal evolution and sampling errors. Liquid biopsies are promising non-invasive alternative sources for MRD assessment that may overcome these limitations.
11:40 Vaccination impact on impending HIV-COVID-19 dual epidemic with autogenous behaviour modification - Samares Pal (University of Kalyani, India)
Vaccination impact on impending HIV-COVID-19 dual epidemic with autogenous behaviour modification
- Samares Pal (University of Kalyani, India)
11:40 - 12:00
Authors: Madhuri Majumder and Samares Pal An HIV-COVID-19 co-infection dynamics is modelled mathematically assimilating vaccination mechanism that incorporates endogenous modification of human practices generated by the COVID-19 prevalence, absorbing the relevance of treatment mechanism in suppressing the co-infection burden. Envisaging COVID-19 situation, HIV-subsystem is analysed by introducing COVID-19 vaccination for the HIV infected population as a prevention. It has been observed that Co-infection treatment needs to be emphasized parallelly with single infection medication under dual-epidemic situation. Further, an optimization technique is introduced to the co-infection model integrating vaccination and treatment control mechanisms, which approves the strategy combining vaccination with awareness and medication as the ideal one for epidemic and economic gain.
12:00 CAR-T induced pseudo progression in B-cell lymphomas - Gustav Lindwall (MPI for Evolutionary Biology)
CAR-T induced pseudo progression in B-cell lymphomas
- Gustav Lindwall (MPI for Evolutionary Biology)
12:00 - 12:20
CAR-T therapy, where T cell are genetically modified to respond to CD19-presenting B cells, has revolutionized the treatment of several blood cancers. The immediate effect of this immunotherapy is associated with a significant inflammatory response in the patient, sometimes leading to a tumor that seemingly swells in the days following CAR-T cell injection. This is referred to as pseudo-progression, and in this project we present a mathematical model of CAR-T cell therapy where pro-inflammatory cytokines play a crucial role. The model is capable of capturing a wide range of behaviors, including long-term successful treatments, failed treatments and pseudo-progression. The parametrization of the model maps on to measurable patient characteristics, and we discuss how these parameters impact the long term behavior of the model.
12:20 Lunch
Lunch
12:20 - 13:20
13:20 Keynote: Fabian Spill
Fabian Spill
13:20 - 14:20
Contributions

13:20 Spatial, geometrical and mechanical features of the tumour microenvironment - Fabian Spill (University of Birmingham)
14:20 Coffee break
Coffee break
14:20 - 14:40
14:40 The role of phenotypic plasticity in adaptive therapies of cancer - Alexander Stein (Barts Cancer Institute, Queen Mary University of London)
The role of phenotypic plasticity in adaptive therapies of cancer
- Alexander Stein (Barts Cancer Institute, Queen Mary University of London)
14:40 - 15:00
Treatment resistance is a major obstacle in cancer treatment. While whole-genome sequencing revealed that single mutations are sometimes sufficient to explain resistance, recent studies demonstrate that more often resistance is a multi-factorial process including non-genetic mechanism. In particular, epigenetic and phenotypic changes that take place at higher frequencies than the acquisition of genetic aberrations are now known to contribute treatment resistance. Adaptive therapies try to overcome these resistance obstacles with adaptive drug dosing that exploits cell-cell competition and balances tumour burden with drug sensitivity. Yet, a systematic study of the impact of phenotypic plasticity is lacking. In this presentation, we analyse birth-death processes and their deterministic counterparts including cell-cell competition and phenotypic switching. We determine parameter ranges for which cancers go extinct or can be contained for infinite time. In case, neither extinction nor containment is possible, we investigate the time to progression. We find that if cell-cell competition is absent, parameter ranges for infinite containment are equivalent to those for extinction. Our results show how biases and convexity in phenotypic switching rates impact phenotype distributions and treatment outcomes. Eventually, we discuss how epigenetic and transcriptomic data can be used as proxies to determine phenotype distributions in patients, and how treatments that affect switching rates could be used to improve treatment outcomes.
15:00 Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy - Simon Syga (TU Dresden)
Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy
- Simon Syga (TU Dresden)
15:00 - 15:20
Authors: Simon Syga, Haralampos Hatzikirou, Andreas Deutsch Cancer is a significant global health issue, with treatment challenges arising from intratumor heterogeneity. We study the complex relationship between somatic evolution and phenotypic plasticity, explicitly focusing on the interplay between cell migration and proliferation. We propose that evolution does not act directly on phenotypic traits, like the proliferation rate, but on the phenotypic plasticity in response to the microenvironment. We study this hypothesis using a novel, spatially explicit model that tracks individual cells' phenotypic and genetic states. We assume cells change between mobile and growing states controlled by inherited and mutation-driven genotypes and the cells' microenvironment. We observe that cells at the tumor edge evolve to favor migration over proliferation and vice versa in the tumor bulk. However, this phenotypic heterogeneity can be realized by distinct regulations of the phenotypic switch, which depend on the apoptosis rate and the cells' ability to sense their environment. Emerging synthetic tumors display varying levels of heterogeneity, which we show are predictors of the cancer's recurrence time after treatment. Interestingly, higher phenotypic heterogeneity predicts poor treatment outcomes, unlike genetic heterogeneity.
15:20 Plasticity of Cell Fate Commitments in Development, Evolution, and Disease - Markéta Kaucká (MPI for Evolutionary Biology)
Plasticity of Cell Fate Commitments in Development, Evolution, and Disease
- Markéta Kaucká (MPI for Evolutionary Biology)
15:20 - 16:00
Cell plasticity refers to the ability of cells to change their identity or function in response to internal or external cues. This remarkable ability is traditionally associated with embryonic development, where stem cells and progenitors choose from multiple downstream fates to form specialized, functional tissues and organs. Under normal conditions, cell fate commitments are stable, ensuring the proper functioning of specialized tissues throughout life. In the last two decades, it has been shown that cell plasticity can be induced experimentally but also occurs naturally and in response to chronic physiological and pathological stresses. In terminally differentiated adult cells, cell plasticity primarily serves as a mechanism for tissue adaptation and repair. While it is certainly advantageous in these contexts, this plasticity also carries risks, as evidenced by its involvement in various disorders, including cancer. Our research explores how cells make decisions during embryonic development and investigates the extent to which these decisions are reversible. To understand the plasticity of cell fate commitment, we employ single-cell sequencing and genetic tracing techniques. This phenomenon is of particular interest to us because of an evolutionary perspective: as organisms became more complex, they lost much of their regenerative capacity compared to simpler organisms. While species like planarians can regenerate large portions of their bodies, most higher vertebrates have a much more limited regenerative ability. We hypothesize that, to compensate for this loss, complex organisms have evolved to utilize cell plasticity, particularly in certain cell types. Infrastructures such as blood vessels and peripheral innervation, which reach virtually every part of the body, harbour specialized cells capable of dedifferentiation, giving rise to a spectrum of other cell types. While this adaptation enables the organism to replenish needed cell types, it is also implicated in pathological conditions such as congenital syndromes, diseases, and cancer. I will summarize our findings on the plasticity of cell fate decisions, emphasizing how these insights can advance our understanding of cellular processes in the context of cancer and regenerative medicine.
16:00 Coffee break
Coffee break
16:00 - 16:20

16:20 Discussion: Session 1
Session 1
16:20 - 18:00

18:00 Fingerfood Dinner
Fingerfood Dinner
18:00 - 19:00

19:00 Poster session

19:00 - 20:00
Wednesday, 21 May 2025
09:00 Keynote: Gaetano Gargiulo
Gaetano Gargiulo
09:00 - 10:00
Contributions

09:00 How a single oncogene controls lung cancer heterogeneity and evolution - Gaetano Gargiulo (Max-Delbrück-Center for Molecular Medicine (MDC)
10:00 Investigating Possible Mechanism of Relapse in Acute Lymphoblastic Leukemia through Stochastic Modeling of Minimal Residual Disease - Qianci Yang (MPI for Evolutionary Biology)
Investigating Possible Mechanism of Relapse in Acute Lymphoblastic Leukemia through Stochastic Modeling of Minimal Residual Disease
- Qianci Yang (MPI for Evolutionary Biology)
10:00 - 10:20
Acute lymphoblastic leukemia (ALL) is a type of cancer in which the bone marrow produces too many lymphocytes without further differentiation into mature blood cells. The primary treatment for most ALL cases is chemotherapy; however, after the intense treatment phase, relapse is observed in some patients. Early-stage relapses might be due to some remaining leukemia cells not being detectable by conventional cytomorphology. The molecular tests on minimal residual disease (MRD) can quantify disease burden at relatively low levels, thus helping track cancer remission and relapse. We investigated the dynamics of residual disease to describe the observed response and relapse kinetics heterogeneity. We developed stochastic, patient-specific models based on longitudinal MRD data to further the understanding of the driving factors of relapse, aiming to quantify better prediction of likelihood and timing of relapse in individual patients based on individual treatment choices.
10:20 Impacts of competition and phenotypic plasticity on the viability of adaptive therapy - B Vibishan (IISc Bangalore)
Impacts of competition and phenotypic plasticity on the viability of adaptive therapy
- B Vibishan (IISc Bangalore)
10:20 - 10:40
Authors: B Vibishan, Paras Jain, Vedant Sharma, Kishore Hari, Jason T George, Mohit Kumar Jolly Cancer is a heterogeneous disease and variability in drug sensitivity is widely documented across cancer types. Adaptive therapy is an emerging modality of cancer treatment that leverages this heterogeneity in drug resistance to achieve better therapeutic outcomes. Current treatments typically eliminate a large fraction of drug- sensitive cells and release drug-resistant cells from competitive inhibition, but adaptive therapy maintains some frequency of drug-sensitive cells that limit the growth of resistant cells through biotic competition. While early clinical trials of such a strategy have shown promise, optimisation of adaptive therapy is still a subject of active study. In this context, current methods largely assume cell phenotypes to remain constant, even though cell-state transitions could allow drug-sensitive and -resistant phenotypes to interchange and thus escape therapy. Here, we address this gap in the literature using a deterministic model of population growth in which sensitive and resistant cells grow under competition as well as cell-state transitions. Based on the model’s steady-state behaviour and temporal dynamics, we identify distinct balances of competition and cell-state transitions that are suitable for effective adaptive versus constant dose therapy. Our data indicate that under adaptive therapy, the frequency of fluctuations varies systematically across models with different levels of competition and cell-state transitions . Our analyses also identify key limitations of applying phenomenological models in clinical practice for therapy design and implementation, particularly when cell-state transitions are involved. These findings provide an overall perspective on the relevance of phenotypic plasticity for emerging cancer treatment strategies using population dynamics as a investigation framework.
10:40 Coffee break
Coffee break
10:40 - 11:20
11:20 Keynote: Heike Siebert
Heike Siebert
11:20 - 12:20
Contributions

11:20 Investigating phenotype plasticity and therapeutic strategies using logical modeling - Heike Siebert (Kiel University)
12:20 Lunch
Lunch
12:20 - 13:10
13:10 Keynote: Sara Hamis
Sara Hamis
13:10 - 14:10
Contributions

13:10 Growth rate-driven modelling reveals how phenotypic adaptation drives drug resistance in BRAFV600E-mutant melanoma - Sara Hamis (Uppsala University)
14:10 Group photo
Group photo
14:10 - 14:30

14:30 Discussion: Boat trip (with discussion)
Boat trip (with discussion)
14:30 - 17:30
Thursday, 22 May 2025
09:00 Keynote: Purificación Muñoz Moruno
Purificación Muñoz Moruno
09:00 - 10:00
Contributions

09:00 Impact of Cancer Cell Plasticity on Therapy Response - Purificación Muñoz Moruno (Bellvitge Biomedical Research Institute (IDIBELL))
10:00 Quantitative measurement of phenotype dynamics during cancer drug resistance evolution using genetic barcoding - Freddie Whiting (The Institute of Cancer Research)
Quantitative measurement of phenotype dynamics during cancer drug resistance evolution using genetic barcoding
- Freddie Whiting (The Institute of Cancer Research)
10:00 - 10:20
Authors: Frederick J.H. Whiting, Maximilian Mossner, Calum Gabbutt, Christopher Kimberley, Chris P Barnes, Ann-Marie Baker, Andrea Sottoriva, Richard A. Nichols, Trevor A Graham Effective cancer treatment frequently fails due to the evolution of drug resistant cell phenotypes caused by underlying genetic or non-genetic changes. The origin of these adaptations, their timing and rate of spread is key information for distinguishing the mechanism(s) of drug resistance, yet the dynamics cannot be observed directly. Here, we construct a mathematical framework to infer the dynamics of drug resistance without the need for direct measurement of the resistance phenotype using only genetic lineage tracing and population size data. The veracity of the framework is demonstrated through experimental evolution to 5-Fu chemotherapy in two common colorectal cancer cell lines: SW620 and HCT116. In SW620 cells, a stable pre-existing resistant subpopulation was inferred. In HCT116 cells resistance emerged through phenotypic switching into a slow growing resistant state with stochastic exiting into a fully resistant phenotype. Extensive functional assays, including scRNA-seq and scDNA-seq confirmed these distinct evolutionary routes and their molecular nature. Our mathematical framework can be extended to diverse experimental designs to infer the evolutionary dynamics of cancer cell therapy resistance evolution from readily obtained experimental data, enabling more rapid characterisation of resistance mechanisms.
10:20 A multi-step completion process model of cell plasticity - Rosemary Yu (Radboud University)
A multi-step completion process model of cell plasticity
- Rosemary Yu (Radboud University)
10:20 - 10:40
Authors: Chen M. Chen, Rosemary Yu Plasticity is the potential for cells or cell populations to change their phenotypes and behaviours in response to internal or external cues. Plasticity is fundamental to many complex biological processes, yet to date there remains a lack of mathematical models that can elucidate and predict molecular behaviours in a plasticity programme. Here we report a new mathematical framework that models cell plasticity as a multi-step completion process, where the system moves from the initial state along a path guided by multiple intermediate attractors until the final state (i.e. a new homeostasis) is reached. Using omics time-series data as model input, we show that our method fits data well, and identifies attractor states by their timing and molecular markers which are well-aligned with domain knowledge. Importantly, our model can make non-trivial predictions such as the molecular outcomes of blocking a plasticity programme from reaching completion, in a quantitative and time-resolved manner.
10:40 Coffee break
Coffee break
10:40 - 11:20

11:20 Discussion: Session 2
Session 2
11:20 - 12:20

12:20 Lunch
Lunch
12:20 - 13:20

13:20 Discussion: Report
Report
13:20 - 14:00
14:00 Closing remarks - Philipp Altrock (MPI for Evolutionary Biology)
Closing remarks
- Philipp Altrock (MPI for Evolutionary Biology)
14:00 - 14:20
17:30 BBQ
BBQ
17:30 - 19:30

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