Summary
I am an MRC Investigator (Programme Leader) at the MRC Biostatistics Unit and a CRUK Career Establishment Fellow. 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. We 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 been previously in the Spanish National Cancer Centre (CNIO) as a graduate student and in CRUK as a postdoc, as part of the Caldas Lab.
A complete list of publications is available in my Google Scholar profile (https://scholar.google.co.uk/citations?user=Kt2arkkAAAAJ&hl=en)
Selected Publications
- Shea A, Eyal-Lubling Y, Guerrero-Romero D, Manzano Garcia R, Greenwood W, O'Reilly M, Georgopoulou D, Callari M, Lerda G, Wix S, Giovannetti A, Masina R, Esmaeilishirazifard, Martin AG, Nagano A, Young L, Kupczak S, Cheng Y, Bardwell H, Provenzano E, Kane J, Lay J, Grybowicz L, McAdam K, Caldas C, Abraham J, Rueda OM, and Bruna A. Modelling drug responses and evolutionary dynamics using triple negative breast cancer patient-derived xenografts. Can. Res. 2025 85(3);567-584
- Sammut S-J, Crispin-Ortuzar M, Chin SF, Provenzano E, Bardwell HA, Ma W, Cope W, Dariush A, Dawson SJ, Abraham JE, Dunn J, Hiller L, Thomas J, Cameron DA, Bartlett JMS, Hayward L, Pharoah PD, Markowetz F, Rueda OM, Earl HM, Caldas C.
Multi-omic machine learning predictor of breast cancer therapy response.
Nature. 2022 Jan;601(7894):623-629. - Rueda OM, Sammut S-J, Seoane JA, Chin S-F, Caswell-Jin JL, Callari M, Batra R, Pereira B, Bruna A, Ali HR, Provenzano E, Liu B,Parisien M, Gillett C, McKinney S, Green AR, Murphy L, Purushotham A, Ellis IO, Pharoah PD, Rueda C, Aparicio S , Caldas C, and Curtis C. Dynamics of breast cancer relapse reveal molecularly defined late recurring ER-positive subgroups. Nature. 2019, 567(7748):399-404.
- Bruna A, Rueda OM, Greenwood W, Batra AS, Callari M, Batra RN, Pogrebniak K, Sandoval J, Cassidy JW, Tufegdzic-Vidakovic A, Sammut SJ, Jones L, Proven- zano E, Baird R, Eire P, Hadfield J, Eldridge M, McLaren-Douglas A, Barthorpe A, Lightfoot H, O’Connor MJ, Gray J, Cortes J, Baselga J, Marangoni E, Welm AL, Aparicio S, Serra V, Garnett MJ, Caldas C. A Biobank of Breast Cancer Explants with Preserved Intra-tumor Heterogeneity to Screen Anticancer Compounds Cell. 2016 Sep 14. pii: S0092-8674(16)31138-2
- Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Gra}f S, Ha G, Haffari G, Bashashati A, Russell R, McKinney S, METABRIC Group, Langerød A, Green A, Provenzano E, Wishart G, Pinder S, Watson P, Markowetz F, Murphy L, Ellis I, Purushotham A, Børesen-Dale AL, Brenton JD, Tavare S, Caldas C, Aparicio S.The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486(7403):346-352.
Current Members
Post-doctoral researchers:
- Valeria Leiva
- Solon Karapanagiotis
- Dom Kirkham
PhD students:
- Raquel Manzano Garcia (member of CRUK Cambridge Institute, Markowetz/Caldas Lab, co-supervised)
Previous members:
- Daniel Guerrero Romero (finished PhD, now postdoc at EBI)
- Richard Moulange (finished PhD, now AI-Biosecurity Policy Manager at the Centre for Long-term resilience)
- Izzy Newsham (finished PhD)
- Rong Zhu (postdoc, now at the School of Mathematics and Statistics, Beijing Institute of Technology)
- Kevin Tu (finished Master, now at University of Maryland)
- Cameron Young (finished Master, now at Harvard Medical School)
- Marco Barreca (visiting PhD student, Fondazione Michelangelo)
