My research group uses unique proteomics and computational approaches to understand how cell signalling pathways driven by the activity of protein kinases contribute to the development of cancer. Increasing this knowledge will be invaluable in advancing personalised cancer therapies.
Computational Analysis of Cholangiocarcinoma Phosphoproteomes Identifies Patient-Specific Drug Targets. Cancer Res (2021) 81(22):5765-5776. PMID: 34551960
Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs. Nat Commun (2021) 12(1):1850. PMID: 33767176
Reconstructing kinase network topologies from phosphoproteomics data reveals cancer-associated rewiring. Nat Biotechnol (2020) 38(4):493-502. PMID: 31959955
Proteomic and genomic integration identifies kinase and differentiation determinants of kinase inhibitor sensitivity in leukemia cells. Leukemia (2018) 32(8):1818-1822. PMID: 29626197
I am interested in understanding how cell signalling pathways driven by the activity of protein kinases contribute to the development of cancer. Signalling pathways do not work in isolation but form a complex network of biochemical reactions that integrate extracellular signals into a coordinated cell biological response.
Essentially all cancers deregulate one or several components of this biochemical network, but unfortunately, cancers are heterogeneous in the way signalling is perturbed. In practice, this means that novel targeted therapies against signalling nodes do not work equally well in all patients. Even those patients that initially respond eventually develop resistance.
To understand the mechanisms underlying this heterogeneity, I developed methodology based on a technique named mass spectrometry and on computational science. These techniques can be used to measure how the signalling network is wired in individual cancer populations in a comprehensive and unbiased manner.
My group is now using these unique resources to investigate the fundamental properties of signalling networks and to understand how signalling heterogeneity in cancer (with particular focus on haematological malignancies) contribute to intrinsic and acquired resistance to compounds that target signalling enzymes.
Targeting the lysine-specific demethylase 1 rewires kinase networks and primes leukemia cells for kinase inhibitor treatment. Pedicona F, Casado P, Hijazi M et al. Sci Signal (2022) 15(2) eabl7989
BLOCKING ROR2 IMPROVES CARTILAGE INTEGRITY AND PROVIDES PAIN RELIEF IN OSTEOARTHRITIS, IN PART BY MODULATING YAP SIGNALLING Thorup A-S, Wilson J, Strachan D et al. Osteoarthritis and Cartilage (2022) 30(10) s159
Suppression of endothelial cell FAK expression reduces pancreatic ductal adenocarcinoma metastasis after gemcitabine treatment. Roy-Luzarraga M, Reynolds LE, de Lux N-Delgado B et al. Cancer Res (2022) (2)
Elucidating the role of the kinase activity of endothelial cell focal adhesion kinase in angiocrine signalling and tumour growth Newport E, Pedrosa AR, Lees D et al. Journal of Pathology (2022) 256(7) 235-247
Disruption of pancreatic stellate cell myofibroblast phenotype promotes pancreatic tumor invasion Murray ER, Menezes S, Henry JC et al. Cell Reports (2022) 38(7)
Implementation of Clinical Phosphoproteomics and Proteomics for Personalized Medicine. Casado P, Hijazi M, Gerdes H et al. (2022) 2420(2) 87-106
Abstract LBA013: Phosphoproteomics reveals active drug targets on pathways of resistance and predicts response to midostaurin plus chemotherapy in FLT3 mutant-positive acute myeloid leukemia Nobre LV, Basanta CC, Pedicona SF et al. (2021) (10) lba013-lba013
Activating mutations in BRAF disrupt the hypothalamo-pituitary axis leading to hypopituitarism in mice and humans Gualtieri A, Kyprianou N, Gregory LC et al. Nature Communications (2021) 12(7)
Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs Gerdes H, Casado P, Dokal A et al. Nature Communications (2021) 12(7)
Computational Analysis of Cholangiocarcinoma Phosphoproteomes Identifies Patient-Specific Drug Targets. Khorsandi SE, Dokal AD, Rajeeve V et al. Cancer Res (2021) 81(2) 5765-5776
I graduated with a PhD in 2004 from UCL. My studies (completed in the laboratories of Prof Mike Waterfield, Prof Rainer Cramer and Prof Al Burlingame) were on a project that investigated kidney physiology and were supervised by Prof Robert Unwin. I then completed postdoctoral training at the Ludwig Institute for Cancer Research (UCL branch).
In 2007, I became lecturer at the Centre for Cell Signalling and in 2010 I was promoted to Senior Lecturer. After a period in the MRC Clinical Sciences Centre (2012-2013), where I was Head of the Mass Spectrometry and Proteomics, I joined the Centre for Haemoto-Oncology in 2013 where I now lead the Integrative Cell Signalling and Proteomics Group.
I am part of the Programme Team for the Cancer Genomics & Data Sciences MSc Programme at BCI, Queen Mary University of London.