Websites
Enric Domingo
BSc, MSc, PhD
SENIOR RESEARCHER IN BIOINFORMATICS
Molecular pathology, Biomarkers, Colorectal cancer
RESEARCH SUMMARY
My work has always been focused on colorectal cancer and translational research, initially working in the wet lab and then moving onto computer-based research. My main goal is the identification of biomarkers that could be implemented clinically to improve healthcare. Accordingly, along my career I have reported highly relevant biomarkers in colorectal cancer (eg BRAF mutation to exclude germline predisposition; POLE mutation & imCMS for prognosis; PIK3CA mutation for benefit with aspirin; RSS signature & imCMS for response to radiotherapy).
My research is strongly focused on molecular profiling of human tumours. To that end, I apply a wide range of bioinformatical tools to interrogate multi-omic data (eg DNA sequencing, DNA methylation, RNA expression, protein expression) from clinical trials or other cohorts. As such, I lead bioinformatical analyses for S:CORT (a consortium looking for stratifiers for oxaliplatin, radiotherapy, prognosis and novel biological therapies) and transSCOT (translational analyses for the large clinical trial SCOT). I also lead my own research lines (eg some specific biomarker candidates, site of metastasis) and have tight collaborations with colleagues nationally and internationally.
BIOGRAPHY
I received a BSc in Biology (Autonomous University of Barcelona) and a MSc and PhD in Genetics (Vall d’Hebron Research Institute, Barcelona). I have also been a visiting fellow in INSERM (Paris) and postdoc in the CRUK London Research Institute (later on incorporated into The Francis Crick Institute) and the Centre for Human Genetics (Oxford).
I have over 80 publications with a mean impact factor of 20 and over 12,000 citations, including 13 first author publications and 4 as last and/or corresponding author.
I am also lecturer for MSc programmes in the Department of Oncology (Applied Cancer Sciences, Radiobiology) and the Centre for Human Genetics (Genomic Medicine).
Key publications
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Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors.
Domingo E. et al, (2024), EBioMedicine, 106
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Prognostic and Predictive Value of Immunoscore in Stage III Colorectal Cancer: Pooled Analysis of Cases From the SCOT and IDEA-HORG Studies.
Domingo E. et al, (2024), J Clin Oncol, 42, 2207 - 2218
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Mutation burden and other molecular markers of prognosis in colorectal cancer treated with curative intent: results from the QUASAR 2 clinical trial and an Australian community-based series.
Domingo E. et al, (2018), Lancet Gastroenterol Hepatol, 3, 635 - 643
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Somatic POLE proofreading domain mutation, immune response, and prognosis in colorectal cancer: a retrospective, pooled biomarker study.
Domingo E. et al, (2016), Lancet Gastroenterol Hepatol, 1, 207 - 216
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Evaluation of PIK3CA mutation as a predictor of benefit from nonsteroidal anti-inflammatory drug therapy in colorectal cancer.
Domingo E. et al, (2013), J Clin Oncol, 31, 4297 - 4305
Recent publications
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Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.
Hu Y. et al, (2025), Med Image Anal, 101
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TEX264 drives selective autophagy of DNA lesions to promote DNA repair and cell survival.
Lascaux P. et al, (2024), Cell, 187, 5698 - 5718.e26
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Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer.
Nowak M. et al, (2024), Cell Rep Med, 5
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Improving radiotherapy in immunosuppressive microenvironments by targeting complement receptor C5aR1.
Beach C. et al, (2024), J Clin Invest, 134
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Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors.
Domingo E. et al, (2024), EBioMedicine, 106