Professor Oscar Rueda
(he/him/his)About Professor Oscar Rueda
I am a Group Leader at the MRC Biostatistics Unit, and a CRUK Career Establishment Awardee.
I am interested in the development of statistical models for the analysis of large genomic and transcriptomic datasets. Specifically, my goal is to integrate large breast cancer datasets in order to identify biomarkers that can be used to stratify patients and to identify potential drug candidates for specific subtypes. These biomarkers can be integrated in prognostic models that can be used to highlight patients at risk of relapse and to monitor patients while on treatment. The combination of clinical samples and preclinical models can accelerate the clinical implementation of new drugs, however there are multiple statistical challenges that need to be solved in order to bridge the gap between what we observe in vitro, in animal models and in the patient. They employ classical statistical models together with more recent machine learning approaches.
I have a PhD in Mathematics (Statistics) from the University of Valladolid, Spain. I have previously been in the Spanish National Cancer Centre (CNIO) and in CRUK as a postdoc.
Publications
Showing 1 to 10 of 102 publications
Real-time cell viability monitoring for high-throughput drug screening using tumor xenograft-derived cells.
Authors: E Esmaeilishirazifard, D Guerrero-Romero, AJW Lui, A Shea, LV Nguyen, M Callari, R Masina, K Tu, R Baird, P Edwards, W Greenwood, S Fuller, C Crafter, M Lawson, A Bruna, OM Rueda, C Caldas
Published:
Journal: Cell Rep Methods
DOI: 10.1016/j.crmeth.2026.101464
Figure 6 from Modeling Drug Responses and Evolutionary Dynamics Using Patient-Derived Xenografts Reveals Precision Medicine Strategies for Triple-Negative Breast Cancer
Authors: A Shea, Y Eyal-Lubling, D Guerrero-Romero, R Manzano Garcia, W Greenwood, M O’Reilly, D Georgopoulou, M Callari, G Lerda, S Wix, A Giovannetti, R Masina, E Esmaeilishirazifard, W Cope, AG Martin, A Nagano, L Young, S Kupczak, Y Cheng, H Bardwell, E Provenzano, J Kane, J Lay, L Grybowicz, K McAdam, C Caldas, J Abraham, OM Rueda, A Bruna
Published:
DOI: 10.1158/0008-5472.28329134
Novel Influence Diagnostics in Multistate Models for Breast Cancer.
Authors: V Leiva-Yamaguchi, A Tapia, M Galea, OM Rueda
Journal: Stat Med
DOI: 10.1002/sim.70556
Novel Influence Diagnostics in Multistate Models for Breast Cancer
Authors: V Leiva‐Yamaguchi, A Tapia, M Galea, OM Rueda
Journal: Statistics in Medicine
DOI: 10.1002/sim.70556
The molecular cartography of malignant and benign sebaceous tumours.
Authors: I Ferreira, OM Rueda, L van der Weyden, S Sahni, O Cast, K Wong, M Del Castillo Velasco-Herrera, H Caldwell, JM Boccacino, T Alegbe, I Mehta, A Gunjur, P Gupta, V Harle, K Koga, I Matzusaki, M Fujimoto, K Wiedemeyer, A Stratigos, A Oniscu, K Wang, E Ruppin, P Demetter, IM Frayling, MJ Arends, T Brenn, DJ Adams
Published:
Journal: Nat Commun
DOI: 10.1038/s41467-025-66584-0
Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data.
Authors: R Zhu, K Eason, S-F Chin, PAW Edwards, R Manzano Garcia, R Moulange, JW Pan, SH Teo, S Mukherjee, M Callari, C Caldas, S-J Sammut, OM Rueda
Journal: Mol Oncol
DOI: 10.1002/1878-0261.70041
A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival.
Authors: EJ Beddowes, M Ortega Duran, S Karapanagiotis, A Martin, M Gao, R Masina, R Woitek, J Tanner, F Tippin, J Kane, J Lay, A Brouwer, S-J Sammut, S-F Chin, D Gale, DWY Tsui, S-J Dawson, N Rosenfeld, M Callari, OM Rueda, C Caldas
Journal: Mol Oncol
DOI: 10.1002/1878-0261.70015
Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data
Authors: R Zhu, K Eason, S Chin, PAW Edwards, R Manzano Garcia, R Moulange, JW Pan, SH Teo, S Mukherjee, M Callari, C Caldas, S Sammut, OM Rueda
Journal: Molecular Oncology
DOI: 10.1002/1878-0261.70041
The tumor microenvironment of 14,837 breast cancers is associated with clinical outcome independently of genomic subtypes.
Authors: KJ Tu, D Guerrero-Romero, K Eason, R Manzano Garcia, J Wern, S-H Teo, L Nguyen, S-J Sammut, F Markowetz, OM Rueda, C Caldas
Published:
Journal: Cell Rep Med
DOI: 10.1016/j.xcrm.2025.102450
Fitness and transcriptional plasticity of human breast cancer single-cell-derived clones.
Authors: LV Nguyen, Y Eyal-Lubling, D Guerrero-Romero, S Kronheim, S-F Chin, R Manzano Garcia, S-J Sammut, G Lerda, AJW Lui, HA Bardwell, W Greenwood, HJ Shin, R Masina, K Kania, A Bruna, E Esmaeilishirazifard, EA Kolyvas, S Aparicio, OM Rueda, C Caldas
Published:
Journal: Cell Rep
DOI: 10.1016/j.celrep.2025.115699