Dr Alan Serrels, University of Edinburgh, Prof Jen Morton, CRUK Scotland Institute & Prof David Chang, University of Glasgow
Background
The contribution of pancreatic cancer to global cancer-related mortality continues to rise, with an almost uniformly fatal outcome. At diagnosis, only a small minority of patients are eligible for surgical resection which remains the only treatment option with curative potential. Even after surgery, relapse is common and for most patients, current chemotherapy regimens have only modest activity despite significant toxicity. With objective response rates to standard-of-care chemotherapy approximately 30-40%, understanding mechanisms of resistance and identifying new therapies will be critical to improving patient outcomes.
Pancreatic cancer is a genetically heterogeneous disease. Activating mutations in the KRAS gene are near ubiquitous and are often accompanied by a loss-of-function mutation in at least one tumour suppressor gene, most commonly TP53, CDKN2A and/or SMAD4, resulting in a range of different combinations across the patient population. How this underlying heterogeneity impacts the tumour microenvironment (TME) and mechanisms of immune evasion is not clear. To explore this, we have used CRISPR-Cas9 genome editing to generate new isogenic cell-based models of pancreatic cancer by engineering the most common driver-gene expression states found in human PDAC into genetically pristine murine primary acinar cells. Extensive benchmarking of the TME in these models against the human disease has identified CD8 T-cell enriched sub-tumour microenvironments, similar to those observed in human PDAC. What immune regulatory pathways are expressed within these CD8 T-cell enriched sub-TMEs to drive immune evasion is unknown. Similarly, what immune regulatory mechanisms drive CD8 T-cell exclusion from other regions of the tumour is also not clear.
Combining our new models with the analysis of human PDAC tissue, we have used spatial transcriptomics to interrogate mechanisms of immune evasion in CD8 T-cell enriched sub-TMEs and immune desert (lacking CD8 T-cells) regions enriched for cancer cells, macrophages or cancer-associated fibroblasts. This has enabled us to identify spatially restricted mechanisms of immune evasion that are conserved between human PDAC and our novel mouse models, and their association with the loss of CDKN2A and/or SMAD4. Leveraging this information, we now aim to develop and test novel therapeutic combinations coupled with patient stratification hypotheses to identify new treatment options for this disease of unmet clinical need.
Current treatment options for patients diagnosed with advanced disease are limited, with most eligible patients receiving either FOLFIRINOX or a combination of Gemcitabine and Abraxane. Using our model systems, we have identified that tumour driver-gene expression impacts response to FOLFIRINOX and plays an important role in dictating how FOLFIRINOX treatment reprograms the TME and mechanisms of immune evasion. Therefore, understanding the interplay between tumour driver-gene expression and treatment-associated TME reprogramming will be important in identifying downstream treatment options following the onset of resistance and disease relapse. Recently, a number of KRAS inhibitors have entered clinical trials in PDAC, with initial data suggesting robust anti-tumour efficacy but the rapid onset of resistance. Therefore, we propose to build on our current findings by leveraging our model systems to address the impact of CDKN2A and SMAD4 expression on response to KRAS inhibition. Specifically, we aim to understand how KRAS inhibition impacts mechanisms of immune regulation within CD8 T-cell sub-TMEs and immune desert regions, and how this is influenced by CDKN2A and SMAD4 expression status. In doing so, we seek to identify immunotherapeutic opportunities emerging as a consequence of resistance to KRAS inhibition.
Skills/Techniques that will be gained
This project will use mouse models of PDAC in combination with spatial transcriptomics, immunohistochemistry, multiplex immunofluorescence, and computational biology to identify, develop and test novel immunotherapy approaches and patient stratification hypotheses for the treatment of pancreatic cancer.
The supervisory team already has extensive expertise in the model systems and techniques to be used and will support the candidate with all required training needs.
For further information on the project or informal enquiries, please contact Dr Alan Serrels, This email address is being protected from spambots. You need JavaScript enabled to view it.
When submitting your application please also upload the completed EDI recruitment form.
To place an application, please visit this site at the University of Edinburgh.
Duration: 4 years, starting October 2026
Closing Date: Wednesday 6th May 2026
Interview for this position will take place in June 2026
Lab Websites
References
Tumour genotype shapes blood biomarker expression for use in pancreatic cancer detection and diagnosis. Canel M, Lonergan DW, Ferguson C, Gautier P, Morton JP, Kriegsheim AV, Serrels A. BioRxiv, 2025
FAK suppresses antigen processing and presentation to promote immune evasion in pancreatic cancer. Canel M, Sławińska AD, Lonergan DW, Kallor AA, Upstill-Goddard R, Davidson C, von Kriegsheim A, Biankin AV, Byron A, Alfaro J, Serrels A. Gut. 2023 Dec 7;73(1):131-155.
FAK promotes stromal PD-L2 expression associated with poor survival in pancreatic cancer. Davidson C, Taggart D, Sims AH, Lonergan DW, Canel M, Serrels A. Br J Cancer. 2022 Nov;127(10):1893-1905.
Sequential ATR and PARP inhibition overcomes acquired DNA damaging agent resistance in pancreatic ductal adenocarcinoma. Herbert KJ, Upstill-Goddard R, Dreyer SB, Rebus S, Pilarsky C, Debabrata M, Lord CJ, Biankin AV, Froeling FEM, Chang DK. Br J Cancer. 2025 Aug;133(3):381-393.
Targeted irradiation in an autochthonous mouse model of pancreatic cancer. Tesson M, Stevenson K, Karim SA, Nixon C, Chalmers AJ, Sansom OJ, O'Neill E, Jones K, Morton JP. Dis Model Mech. 2024 Mar 1;17(3)