Biomarkers for Predicting Radiotherapy Side Effects to Improve Lung Cancer Patient Outcomes
Dr Ximena Raffo-Iraolagoitia, Prof Leo Carlin and Prof Kevin Blyth, Dr Vanessa Smer-Barreto
Lab: Leukocyte Dynamics
Duration: 4 years, starting October 2026
Closing Date: Monday 18 May 2026
Interviews for this position will take place in July 2026
Background
Lung cancer (LC) remains the leading cause of cancer-related death worldwide. In Indonesia cancer is the second largest health care burden after cardiovascular disease and amongst all cancers LC has consistently led to the most deaths in the last decade1. In Scotland, LC incidence is significantly higher than the UK average, and rates are three times greater in the most deprived areas compared to the least deprived2. Alarmingly, two-thirds of cases are diagnosed at a late stage (III or IV)3, when tumours are often unresectable. For these patients, radical radiotherapy is the only curative treatment available. Despite advances in radiotherapy technologies, outcomes remain very poor, with only 10% 10-year survival rate, a figure that has changed little in the last 50 years4.
Radiotherapy can lead to a common side effect, radiation-induced lung injury (RILI), which compromises LC patients’ quality of life and may even be life-threatening. As such, RILI contributes substantially to patient morbidity. Research in our lab, using mouse models of LC, has identified a subset of tumour-associated alveolar macrophages with pro-fibrotic features among the leukocytes composing the immune-landscape5.
Since immune mediators are known to drive tissue injury following radiation, we hypothesise that immune cells already present in the tumour microenvironment before radiotherapy could influence susceptibility to RILI. However, no reliable predictors or accurate risk models currently exist in clinical practice.
Research Question
The broad aim of this project is to uncover predictive biomarker candidates of RILI to identify high-risk patients, enabling more personalized care through closer monitoring and mitigation of RILI’s impact on quality of life. In time we also aim to design neo/adjuvant strategies to mitigate these side effects. To achieve these aims, the student will:
- Analyse immune profiles in multiomics datasets in the Living Lab Radiogenomics database, that we recently gained approval to access (LLRG: Whole-exome sequencing and Bulk-RNA sequencing) from pre-treatment samples fron LC patients treated with radical radiotherapy and with known RILI outcomes. By integrating these data with clinical and demographic features, we will conduct a multimodal analysis to identify a distinctive RILI signature.
- Predictive biomarker candidates will be leveraged to design staining panels for multiplexed immunofluorescence imaging and explored as potential targets for neo/adjuvant strategies in preclinical mouse models of LC.
- Incorporate real-world data to estimate the likelihood of RILI presence, concomitant demand on healthcare services, and clinical impact in Scotland using linked healthcare databases from Public Health Scotland.
By combining biomarker discovery with real-world clinical data, this PhD project has the potential to inform treatment decisions, enable precision matching of patients to the most appropriate care, potentially reduce the burden on healthcare systems, and contribute to addressing disparities in LC outcomes in deprived communities.
Relevance to cancer challenges in Indonesia
Despite increasing life expectancy, as noted above LC has a huge healthcare burden in Indonesia. Additionally, radiotherapy is now reaching more patients than ever1. This project ultimately aims to help identify patients who might have poorer outcomes and be better served by other treatments.
Skills/Techniques that will be gained
The student will receive interdisciplinary training supported by experts in immunology, oncology, and bioinformatics.
Areas of training include, but are not limited to:
- Bioinformatics – Analysis of whole-exome sequencing, bulk RNA-seq, and single-cell RNA-seq data.
- Machine learning – Integrating immune features with genomic variants, demographic factors, and clinical characteristics.
- Multiplexed immunofluorescence and image analysis – Staining biomarker candidates in patient samples.
- Real-world data analysis – we aim to use healthcare databases from Public Health Scotland to assess clinical outcomes.
- Genetically engineered mouse models – Investigating neo/adjuvant candidates in preclinical models (the CRUK-SI is world leading in this area).
- Ex vivo functional assays – Characterizing immune cell responses to radiation using cell sorting, flow cytometry, and immunoassays.
- Live imaging techniques – Using confocal microscopy for precision-cut lung slices and incucyte systems for cell cultures to study immune cell behaviour in real time.
- Science communication across diverse settings – Engaging in public outreach, patient and public involvement activities, and presenting research at meetings and conferences.
This comprehensive training will equip the student with expertise in translational and precision oncology, integrating computational, cancer immunology, and clinical approaches, and prepare them for a successful career in research, academia, or industry.
For questions regarding the application process, PhD programme/studentships at the CRUK Scotland Institute or any other queries, please contact phdstudentships@crukscotlandinstitute.ac.uk.
Closing date: Monday 18 May 2026
For your application to be considered, you must upload your CV and a completed document CRUK-LPDP Recruitment Form(108 KB)
CRUK Recruitment Form Instructions
- We ask that you do not add your name or any Institution details to the document CRUK-LPDP Recruitment Form(108 KB) .
- Applications will be shortlisted by CRUK SI initially based on the document CRUK-LPDP Recruitment Form(108 KB) only. CVs will be used in further rounds of shortlisting to invite candidates to interview.
Relevant Publications
1Asmara, O.D. et al . J Thorac Oncol, 18, 1134-1145 (2023)
2Navani, N. et al. J Thorac Oncol 17, 186–193 (2022)
3https://www.gov.scot/publications/cancer-strategy-scotland-2023-2033/pages/3/
5Raffo-Iraolagoitia, X.L. et al. Sci. Adv. 2026 12(10):eadu8802.
