LOCATE: Local Oesophageal CAncer Treatment Engineering to advance the understanding and treatment of oesophageal adenocarcinoma.
Lead Research Organisation:
University of Manchester
Department Name: School of Biological Sciences
Abstract
Every year ~9000 people are diagnosed with oesophageal cancers in UK, and this disease is responsible for 5% of cancer-related deaths. Research efforts must continue to discover new therapies, in particular for oesophageal adenocarcinoma (OAC, the most common subtype of oesophageal cancers in Western Countries), because even cancers diagnosed at an operable stage have 50% of risk to recur after surgery and chemotherapy and the survival at 5 year from diagnosis and treatment remains very low (10-15%) (https://www.cancerresearchuk.org/about-cancer/oesophageal-cancer). Therefore, Cancer Research UK and Medical Research Council have described OAC as having urgent unmet need.
New medicines that boost the immune system against cancer (immunotherapies) can prolong life of patients with OAC and are effective in average for 10-20% of patients. One of the reasons why many cancers defy these medicines is related to a local immune-suppression that shuts the anti-cancer responses down. The research of our group has identified one of the critical mechanisms by which cancers shut the anti-cancer responses down, hence we are proposing a new strategy to release the brakes of the anti-cancer defences. We propose to use an RNA therapeutic, which requires to be prepared into nanomedicine similar to the COVID19 mRNA vaccines. Since adding up many systemic drugs (oral or intravenous medicines) to treatment protocols can significantly increase toxicity while retaining diluted effects where they are needed (e.g. inside the cancer), we also propose to perform an in-depth engineering study combined with bespoke biochemical technologies to allow this novel RNA-based nanomedicine to be delivered optimally inside the cancer, targeting a specific group of cells responsible for hampering the anti-cancer immunity. In our engineering, physics, biochemistry and immune-biology labs in London, Edinburgh and Manchester we will test if our ideas are feasible (Can engineering and physical simulations drive the creation of a new nanomedicine capable to achieve effective localised delivery and address a specific type of cells within the tumour? Can this new, very precise nanomedicine effectively restore anti-cancer immune responses?). If our results are demonstrated to be positive, this new therapeutic will bring new hope to OAC patients: although this proposal is for a proof of principle, early-stage preclinical study, our long-term plan is to move towards a clinical application (we will start to apply for funding for the necessary pre-clinical testing and identify funding and stakeholders for a Phase I clinical trial during Work Package 3). The results of our project will contribute not only to the engineering, biochemistry and immune-oncology academic knowledge, but also provide a potential useful tool against OAC for the medicine of the future. Also, our results would indirectly contribute to advance treatment of other cancers since our new strategy to design nanomedicines could be applied to other diseases.
New medicines that boost the immune system against cancer (immunotherapies) can prolong life of patients with OAC and are effective in average for 10-20% of patients. One of the reasons why many cancers defy these medicines is related to a local immune-suppression that shuts the anti-cancer responses down. The research of our group has identified one of the critical mechanisms by which cancers shut the anti-cancer responses down, hence we are proposing a new strategy to release the brakes of the anti-cancer defences. We propose to use an RNA therapeutic, which requires to be prepared into nanomedicine similar to the COVID19 mRNA vaccines. Since adding up many systemic drugs (oral or intravenous medicines) to treatment protocols can significantly increase toxicity while retaining diluted effects where they are needed (e.g. inside the cancer), we also propose to perform an in-depth engineering study combined with bespoke biochemical technologies to allow this novel RNA-based nanomedicine to be delivered optimally inside the cancer, targeting a specific group of cells responsible for hampering the anti-cancer immunity. In our engineering, physics, biochemistry and immune-biology labs in London, Edinburgh and Manchester we will test if our ideas are feasible (Can engineering and physical simulations drive the creation of a new nanomedicine capable to achieve effective localised delivery and address a specific type of cells within the tumour? Can this new, very precise nanomedicine effectively restore anti-cancer immune responses?). If our results are demonstrated to be positive, this new therapeutic will bring new hope to OAC patients: although this proposal is for a proof of principle, early-stage preclinical study, our long-term plan is to move towards a clinical application (we will start to apply for funding for the necessary pre-clinical testing and identify funding and stakeholders for a Phase I clinical trial during Work Package 3). The results of our project will contribute not only to the engineering, biochemistry and immune-oncology academic knowledge, but also provide a potential useful tool against OAC for the medicine of the future. Also, our results would indirectly contribute to advance treatment of other cancers since our new strategy to design nanomedicines could be applied to other diseases.
Technical Summary
Despite advances, outcomes of patients with oesophageal adenocarcinoma (OAC) remain bleak: survival for primary OAC remains at 10-15% 5 years after diagnosis. An immune-refractory microenvironment is a key reason for poor therapeutic response.
Systemic therapies cause severe toxicity and locoregional therapies are scarce: radiotherapy and radiofrequencies are mostly palliative and used in clinical trials with systemic therapies for inoperable patients, whilst oncolytic viruses are in clinical trials to enhance immunotherapy.
We propose a new way to engineer and deliver therapy for OAC. We will study in-depth the physical properties of the OAC tumour microenvironment. Using algorithms to analyse histological tissue and ultra-high-definition computed tomography we will model the fluid dynamics that determine diffusion in the tumour. Our simulation will drive our design of OAC-specific nanoparticles, so that their physics (e.g., dimension, shape, fluid viscosity) and chemistry (e.g., surface charge, embedding of monoclonal antibodies directed to cell-subset-specific targets) will optimise the diffusion, bioavailability and selectivity for a multi-level precision.
Then, we will synthesise nanoparticles in a controlled manner to maximise the delivery of a nucleic acid drug that we have identified as a novel immune-checkpoint, to a subset of "pro-cancer" immune cells to switch them from immune-suppressive to anti-cancer. We will use in-vitro data to select the nanoparticle with maximum selectivity and biological activity.
Last, we will inject the OAC surgical specimens from the patients with our nanoparticles to verify our prediction model. Thus, we will eventually tune our nanoparticles' parameters and adjust the design algorithms so that we can apply these to other clinical settings. If our proof of principle project is successful, we will design a phase I clinical trial to translate the results of our research into patients' benefit.
Systemic therapies cause severe toxicity and locoregional therapies are scarce: radiotherapy and radiofrequencies are mostly palliative and used in clinical trials with systemic therapies for inoperable patients, whilst oncolytic viruses are in clinical trials to enhance immunotherapy.
We propose a new way to engineer and deliver therapy for OAC. We will study in-depth the physical properties of the OAC tumour microenvironment. Using algorithms to analyse histological tissue and ultra-high-definition computed tomography we will model the fluid dynamics that determine diffusion in the tumour. Our simulation will drive our design of OAC-specific nanoparticles, so that their physics (e.g., dimension, shape, fluid viscosity) and chemistry (e.g., surface charge, embedding of monoclonal antibodies directed to cell-subset-specific targets) will optimise the diffusion, bioavailability and selectivity for a multi-level precision.
Then, we will synthesise nanoparticles in a controlled manner to maximise the delivery of a nucleic acid drug that we have identified as a novel immune-checkpoint, to a subset of "pro-cancer" immune cells to switch them from immune-suppressive to anti-cancer. We will use in-vitro data to select the nanoparticle with maximum selectivity and biological activity.
Last, we will inject the OAC surgical specimens from the patients with our nanoparticles to verify our prediction model. Thus, we will eventually tune our nanoparticles' parameters and adjust the design algorithms so that we can apply these to other clinical settings. If our proof of principle project is successful, we will design a phase I clinical trial to translate the results of our research into patients' benefit.
Organisations
Publications
Campana L
(2024)
Treatment strategies with electrochemotherapy for limb in-transit melanoma: Real-world outcomes from a European, retrospective, cohort study
in European Journal of Surgical Oncology
Pietrantonio F
(2024)
Controversies in upper GI: liquid biopsies
in ESMO Open
Yang Y
(2024)
Effect of infusion direction on convection-enhanced drug delivery to anisotropic tissue.
in Journal of the Royal Society, Interface
Yang Y
(2024)
Exploring tissue permeability of brain tumours in different grades: Insights from pore-scale fluid dynamics analysis.
in Acta biomaterialia
Yuan T
(2024)
A comprehensive review on modeling aspects of infusion-based drug delivery in the brain.
in Acta biomaterialia
| Description | BRC Pathway to Innovation course participation selection and travel grant |
| Amount | £300 (GBP) |
| Organisation | National Institute for Health and Care Research |
| Department | NIHR Biomedical Research Centre |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2024 |
| End | 01/2024 |
| Description | Chemotherapeutic opportunities of metabolic heterogeneity in oesophageal adenocarcinoma |
| Amount | £1,300,000 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 03/2025 |
| End | 03/2030 |
| Description | MCRC PhD studentship and project funding |
| Amount | £151,494 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 09/2025 |
| End | 09/2029 |
| Description | Manchester Biomedical Research Council Funding Early Career Investigator Pump Priming Grant |
| Amount | £20,000 (GBP) |
| Funding ID | internal reference R128172 C070704 |
| Organisation | National Institute for Health and Care Research |
| Department | NIHR Biomedical Research Centre Manchester |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 08/2024 |
| End | 04/2025 |
| Description | Tissue microfluidics from geometric and therapeutic translation |
| Amount | £121,000 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 06/2024 |
| End | 06/2028 |
| Title | 3D computational fluid dynamics for oesophageal adenocarcinoma |
| Description | 1 Acronyms Acronym Full name OAC Oesophageal Adenocarcinoma WP Work Package CFD Computational Fluid Dynamics XPCI X-ray Phase-Contrast Imaging 2 Work package overviews In this WP we aim to establish general parameters for intralesional injection of OAC by first modelling its geometrical architecture at the micro- and meso- scales, and then applying this physics ex vivo using a clinically implementable strategy. To achieve this, we will (i) provide a multiscale description of OAC tissue geometry, and (ii) create a platform for modelling drug delivery in silico. 3 Executive summary 3.1 Cell scale imaging This WP is led by Imperial and UCL. The Imperial team has worked out the protocol of obtaining cell-scale microstructure of the tumour sample. Two tumour samples were obtained from OAC patients in Hammersmith Hospital. One sample was sliced into 42 continuous slices with 5µm interval, and another was sliced with 1µm intervals. H&E staining was applied to the slices and each slice was scanned by Hamamatsu C9600-12 Nano Zoomer 2.0 HT Digital Slide Scanner with the resolution of 226nm. The cell-scale structures can be clearly seen. Figure 1. Histology of the OAC tumour slice. Top: x1.75 times. Bottom: x20 times. 3.2 Cell scale microstructural 3d reconstruction The slices were then registered (to align the same structures on different slices) based on distinct features, such as the glands. After choosing the target area, the slices were cropped, and a stack of slices were obtained. This stack of slices enabled the 3D microstructural reconstruction using open-source software InVesalius 3.1. 3.3 Computational fluid dynamics modelling Based on the 3D microstructure, Computational Fluid Dynamics (CFD) modelling was conducted in the open-resource CFD platform "OpenFOAM" to evaluate the fluid status inside the tumour environment, as shown in Figure 4. This will allow us to characterise the tissue permeability (?) based on Darcy's Law: ?=-QµL/A?P where Q is the flow rate inside the sample under a given pressure drop ?P, µ is the viscosity of the fluid, L is the length of the sample along the pressure drop direction, and A is the cross-section area of the sample orthogonal to the drop direction. Note that ? is independent of the pressure applied, the pressures were randomly chosen. 3.4 µCT scanning and regions registration The UCL team has built the protocol of building the tissue scale model by the X-ray Phase-Contrast Imaging (XPCI) technique. Due to the heterogeneity of the tumour, drug transport properties in different regions may significantly vary. Therefore, drug transport properties need to be characterised on a regional basis. The tissue scale 3D structure will be used to identify the regions and will enable the registration of different drug transport properties in different regions. 4 Concluding statement The protocol of building geometrical architecture at the micro- and meso- scales based on histology images and µCT has been successfully developed. CFD has been explored in the reconstructed 3D microstructure. It was found that 5µm slice spacing cannot be able to provide smooth reconstruction. Therefore, in the next steps, 1µm slice spacing will be adopted. |
| Type Of Material | Technology assay or reagent |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | Thanks to this method optimisation we can now build geometrical architecture at the micro- and meso-scales based on histology images and µCT. This will allow us to proceed with the fluid dynamics modelling based on 3D tissue scale structure, including the identification of the heterogeneity regions, and will enable the registration of different drug transport properties in different regions. We will then use this in-silico model to inform the physical properties of a nanoparticle with optimised diffusion for drug delivery into the microenvironment. |
| Title | Microstructural analysis and computational fluid dynamics model for drug transport oesophageal adenocarcinoma |
| Description | 1. Pore connectivity in the OAC tumour interstitium. Drugs have two ways of transport in the tumour interstitium, namely convection and diffusion. Convection is driven by a pressure gradient (i.e. drug injection) and diffusion is driven by a concentration gradient (i.e. Brownian motion of molecules). If the extracellular space (ECS) is well connected, drug injection can significantly facilitate drug movement. Otherwise, diffusion dominates the drug movement. Therefore, understanding the drug transport mechanism in tumour interstitium is necessary to design the drug delivery strategy. To address this, the Imperial team developed an algorithm and Python code to analyse ESC (pore) connectivity in tumour samples using 2D H&E slices. This connectivity is quantified by open porosity, which represents the volume fraction of interconnected pores where drug transport occurs via convection (Figure 1). A higher open porosity facilitates drug movement within the tumour interstitium during localised injection. Figure 1. Schematic representation of different types of pores in a porous medium. As shown in Figure 2a), three regions were analysed, namely tissue with the glands (region inside the blue square, 300µm*300µm), tissue inside the glands (region inside the orange square, 100µm*100µm), and tissue outside the glands (region inside the green square, 100µm*100µm). 60 positions from 6 slices were chosen to conduct the analysis. Note that the pore connection (open porosity) can be anisotropic, as shown in Figure 2b). Figure 2. a) Analysed regions and their sizes. b) Schematic representation of left-right connection and up-down connection. The results are shown in Figure 3. Since all the regions outside of glands have 0 open porosity, it can be concluded that no drug flow can develop outside of the glands. Likewise, limited drug flow can develop inside the glands as most of the regions have 0 open porosity. 25% of the tissues with glands have positive open porosities, indicating that drug movement can be facilitated in the highways around the glands, as shown in Figure 4. Figure 3. Results of open porosity of different tissues. Figure 4. CFD simulation shows that drug flow can develop (i.e. drug movement can be facilitated by local injection) in the highways around glands. a) shows the boundary conditions of the CFD simulation. b) shows simulation results. The contour shows the pressure distribution while the streamline shows the flow status. 2. Cell scale pore size distribution Figure 3 shows that most of the regions have a 0 open porosity, indicating that molecular diffusion is a dominant way of drug movement in the OAC tumour interstitium. Therefore, we further analysed the pore size distribution. Here, we treated the ECS as oval pores, as shown in Figure 5a). We developed a Python code to identify the pores (Figure 5b)) and summarise the distribution of the pore sizes in different regions. The results are shown in Figure 6. Figure 5. a) Schematic representation of the oval pores and its size definition. b) pores identified in an H&E slice. Figure 6. Pore size distribution in the OAC tumour interstitium. Through analysis in sections 1 and 2, it was found that (1) drug movement is dominated by diffusion and can only be facilitated by localised injection in the highways around glands, (2) particles smaller than 0.6 µm can reach more than 50% volume of the tumour interstitium. 3 Gland scale microstructure reconstruction. The UCL team has developed a protocol to scan the gland structures of the tumour using X-ray Phase-Contrast Imaging (XPCI) µCT. The imaging resolution is 1µm. The UCL team also developed a machine learning model that automatically segment the gland structures. Since it is confirmed that flow can develop in the highways between glands, the Imperial team adopted the segmented µCT slice obtained and developed a protocol to reconstruct the gland-scale microstructure of the OAC tumour based on the open-source platform 3D Slicer, as shown in Figure 7. Figure 7. Gland scale microstructural reconstruction based on the segmented µCT slice using 3D slicer. The top right panel shows the reconstructed 3D structure. 4. Computational fluid dynamics modelling Based on the 3D microstructure. Computational Fluid Dynamics (CFD) modelling was conducted using the open-source CFD platform "OpenFOAM" to simulate the fluid status inside the tumour environment. The simulation results in Figure 8 show that drug transport in the 3D microstructure is anisotropic, indicated by the anisotropic distribution of pressure and streamlines. We will correlate the streamlines and 3D structures with H&E slices to further understand the effects of glands distribution on the drug transport inside the OAC tumour interstitium. These simulations allows us to (1) correlate the drug flow status with the gland distribution inside the tumour, providing insights into the optimal injection position, and (2) characterise the tissue permeability (?) based on Darcy's Law: ?=-QµL/A?P, where Q is the flow rate inside the sample under a given pressure drop ?P, µ is the viscosity of the fluid, L is the length of the sample along the pressure drop direction, and A is the cross-section area of the sample orthogonal to the drop direction. ? is independent of the pressure applied, the pressures were randomly chosen. Note that this was based on the assumption that no flow can develop inside the glands as the cells are very densely packed inside the glands. A higher permeability indicates faster drug movement during injection under the same injection pressure. Therefore, for tissues with a high permeability, a lower injection pressure can be applied to avoid tumour breakage while facilitating drug penetration. Figure 8. Simulation results of drug transport. a) pressure distribution. b) flow streamlines. Note that the left and right are the same structure, but the injection directions are different. This set-up can assess the anisotropy of the tumour. 5. Concluding statement. (1) The pore connectivity and pore size distribution in the OAC tumour interstitium were thoroughly evaluated. The results show that (a) drug movement is dominated by diffusion and can only be facilitated by localised injection in the highways around glands, (b) particles smaller than 0.6 µm can reach more than 50% volume of the tumour interstitium. (2) The protocol of building gland-scale microstructure based on µCT has been successfully developed. (3) The CFD model based on OpenFoam and reconstructed 3D microstructure has been successfully developed. |
| Type Of Material | Technology assay or reagent |
| Year Produced | 2025 |
| Provided To Others? | No |
| Impact | (1) The pore connectivity and pore size distribution analysis not only confirm that local infusion could increase the drug penetration depth in OAC tumour but also informs the design of drug nanoparticles. (2) The pipeline of reconstructing the gland scale microstructure based on µCT and conducting CFD simulations using the gland scale microstructure is a significant milestone in LOCATE. This enables us to analyse drug transport properties of OAC tumours in different grades and design patient-specific drug delivery strategy. |
| Description | Funding announcement |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | The project funding media announcement on Christie newsletter and LinkedIn, with details of the study, had 750 engagements in total. This was in addition to the media engagement that followed the message of the Prime Minister on LinkedIn. |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.linkedin.com/posts/sara-valpione-730345291_high-risk-but-high-reward-research-tackling-a... |
