The Mark Foundation Institute for Integrated Cancer Medicine at the University of Cambridge is establishing a new cancer treatment paradigm using cutting-edge analytics to maximize the use of diverse, high-volume data sets. Advances in machine learning are exploited to capture, integrate, and derive insights from clinical data, genomics, liquid biopsies (detecting tumor DNA in the blood), molecular/digital imaging, and 3D tumor mapping collated from hundreds of patients in real time.
Laboratory, clinic-based researchers, and data experts work together to develop sophisticated computational integration of the diverse data into a single platform which can inform and predict the best treatment decisions for each individual patient. These computational approaches are being evaluated through prospective clinical trials in breast, pancreatic, renal, and hematological malignancies. The institute is also developing novel ligands that can monitor patient response to treatment faster and more specifically than conventional techniques.
PUBLISHED RESEARCH
Sammut SJ, 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. 2021.
Woitek R, McLean M, Ursprung S, Rueda OM, Manzano Garcia R, Locke MJ, Beer L, Baxter G, Rundo L, Provenzano E, Kaggie JD, Patterson A, Frary A, Field-Rayner J, Papalouka V, Kane J, Vinoj Benjamin AJ, Gill AB, Priest AN, Lewis DY, Russell R, Grimmer A, White B, Latimer EC, Patterson I, Schiller A, Carmo B, Slough R, Lanz T, Wason J, Schulte RF, Chin SF, Graves MJ, Gilbert FJ, Abraham JE, Caldas C, Brindle KM, Sala E, Gallagher FA. Hyperpolarized carbon-13 MRI for early response assessment of neoadjuvant chemotherapy in breast cancer patients. Cancer Res. 2021.
Heil BJ, Hoffman MM, Markowetz F, Lee SI, Greene CS, Hicks SC. Reproducibility standards for machine learning in the life sciences. Nat Methods. 2021.
Woitek R, Gallagher FA. The use of hyperpolarised 13C-MRI in clinical body imaging to probe cancer metabolism. Br J Cancer. 2021.
Beer L, Martin-Gonzalez P, Delgado-Ortet M, Reinius M, Rundo L, Woitek R, Ursprung S, Escudero L, Sahin H, Funingana IG, Ang JE, Jimenez-Linan M, Lawton T, Phadke G, Davey S, Nguyen NQ, Markowetz F, Brenton JD, Crispin-Ortuzar M, Addley H, Sala E. Ultrasound-guided targeted biopsies of CT-based radiomic tumour habitats: technical development and initial experience in metastatic ovarian cancer. Eur Radiol. 2020.
Martin-Gonzalez P, Crispin-Ortuzar M, Rundo L, Delgado-Ortet M, Reinius M, Beer L, Woitek R, Ursprung S, Addley H, Brenton JD, Markowetz F, Sala E. Integrative radiogenomics for virtual biopsy and treatment monitoring in ovarian cancer. Insights Imaging. 2020.
Crispin-Ortuzar M, Gehrung M, Ursprung S, Gill AB, Warren AY, Beer L, Gallagher FA, Mitchell TJ, Mendichovszky IA, Priest AN, Stewart GD, Sala E, Markowetz F. Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform. JCO Clin Cancer Inform. 2020.
Beer L, Sahin H, Bateman NW, Blazic I, Vargas HA, Veeraraghavan H, Kirby J, Fevrier-Sullivan B, Freymann JB, Jaffe CC, Brenton J, Miccó M, Nougaret S, Darcy KM, Maxwell GL, Conrads TP, Huang E, Sala E. Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis. Eur Radiol. 2020.
Woitek R, McLean MA, Gill AB, Grist JT, Provenzano E, Patterson AJ, Ursprung S, Torheim T, Zaccagna F, Locke M, Laurent MC, Hilborne S, Frary A, Beer L, Rundo L, Patterson I, Slough R, Kane J, Biggs H, Harrison E, Lanz T, Basu B, Baird R, Sala E, Graves MJ, Gilbert FJ, Abraham JE, Caldas C, Brindle KM, Gallagher FA. Hyperpolarized 13C MRI of Tumor Metabolism Demonstrates Early Metabolic Response to Neoadjuvant Chemotherapy in Breast Cancer. Radiol Imaging Cancer. 2020.
Wan JCM, Heider K, Gale D, Murphy S, Fisher E, Mouliere F, Ruiz-Valdepenas A, Santonja A, Morris J, Chandrananda D, Marshall A, Gill AB, Chan PY, Barker E, Young G, Cooper WN, Hudecova I, Marass F, Mair R, Brindle KM, Stewart GD, Abraham JE, Caldas C, Rassl DM, Rintoul RC, Alifrangis C, Middleton MR, Gallagher FA, Parkinson C, Durrani A, McDermott U, Smith CG, Massie C, Corrie PG, Rosenfeld N. ctDNA monitoring using patient-specific sequencing and integration of variant reads. Sci Transl Med. 2020.
Clarke MA, Fisher J. Executable cancer models: successes and challenges. Nat Rev Cancer. 2020.
Ursprung S, Beer L, Bruining A, Woitek R, Stewart GD, Gallagher FA, Sala E. Radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma-a systematic review and meta-analysis. Eur Radiol. 2020.
Jiménez-Sánchez A, Cybulska P, Mager KL, Koplev S, Cast O, Couturier DL, Memon D, Selenica P, Nikolovski I, Mazaheri Y, Bykov Y, Geyer FC, Macintyre G, Gavarró LM, Drews RM, Gill MB, Papanastasiou AD, Sosa RE, Soslow RA, Walther T, Shen R, Chi DS, Park KJ, Hollmann T, Reis-Filho JS, Markowetz F, Beltrao P, Vargas HA, Zamarin D, Brenton JD, Snyder A, Weigelt B, Sala E, Miller ML. Unraveling tumor-immune heterogeneity in advanced ovarian cancer uncovers immunogenic effect of chemotherapy. Nat Genet. 2020.
Rundo L, Beer L, Ursprung S, Martin-Gonzalez P, Markowetz F, Brenton JD, Crispin-Ortuzar M, Sala E, Woitek R. Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering. Comput Biol Med. 2020.
Smith CG, Moser T, Mouliere F, Field-Rayner J, Eldridge M, Riediger AL, Chandrananda D, Heider K, Wan JCM, Warren AY, Morris J, Hudecova I, Cooper WN, Mitchell TJ, Gale D, Ruiz-Valdepenas A, Klatte T, Ursprung S, Sala E, Riddick ACP, Aho TF, Armitage JN, Perakis S, Pichler M, Seles M, Wcislo G, Welsh SJ, Matakidou A, Eisen T, Massie CE, Rosenfeld N, Heitzer E, Stewart GD. Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors. Genome Med. 2020.
Gallagher FA, Woitek R, McLean MA, Gill AB, Manzano Garcia R, Provenzano E, Riemer F, Kaggie J, Chhabra A, Ursprung S, Grist JT, Daniels CJ, Zaccagna F, Laurent MC, Locke M, Hilborne S, Frary A, Torheim T, Boursnell C, Schiller A, Patterson I, Slough R, Carmo B, Kane J, Biggs H, Harrison E, Deen SS, Patterson A, Lanz T, Kingsbury Z, Ross M, Basu B, Baird R, Lomas DJ, Sala E, Wason J, Rueda OM, Chin SF, Wilkinson IB, Graves MJ, Abraham JE, Gilbert FJ, Caldas C, Brindle KM. Imaging breast cancer using hyperpolarized carbon-13 MRI. Proc Natl Acad Sci U S A. 2020.
Simidjievski N, Bodnar C, Tariq I, Scherer P, Andres Terre H, Shams Z, Jamnik M, Liò P. Variational autoencoders for cancer data integration: design principles and computational practice. Front Genet. 2019.
Kreuzaler P, Clarke MA, Brown EJ, Wilson CH, Kortlever RM, Piterman N, Littlewood T, Evan GI, Fisher J. Heterogeneity of Myc expression in breast cancer exposes pharmacological vulnerabilities revealed through executable mechanistic modeling. Proc Natl Acad Sci U S A. 2019.
Himoto Y, Veeraraghavan H, Zheng J, Zamarin D, Snyder A, Capanu M, Nougaret S, Vargas HA, Shitano F, Callahan M, Wang W, Sala E and Lakhman Y. Computed Tomography–Derived Radiomic Metrics Can Identify Responders to Immunotherapy in Ovarian Cancer. JCO Precis. Oncol. 2019.
Ascolani G, Liò P. Modeling breast cancer progression to bone: how driver mutation order and metabolism matter. BMC Med Genomics. 2019.
Wilkinson I, Basu B, Lomas DJ, Graves MJ, Brindle KM, Gallagher FA. Quantifying normal human brain metabolism using hyperpolarized [1-13C]pyruvate and magnetic resonance imaging. Neuroimage. 2019.
Rueda OM, Sammut SJ, Seoane JA, Chin SF, 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, Curtis C. Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups. Nature. 2019.