Research

Selected relevant ongoing research projects are detailed below:

• Creating Tissue Banking Ecosystem with interlinking clinical, in vivo, in vitro and in silico resources

I lead the IT for the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB) and the bioinformatics for both the PCRFTB and the Breast Cancer Now Tissue Bank (BCNTB). The platforms that we develop bring together the largest collection of multi-dimensional cancer data and allow users to analyse a broad range of specimen/experimental types, including healthy/patient tissue and body fluid specimens, cell lines and murine models as well as related treatments/drugs data. Ultimately, the aim is to provide the cancer research community with the means to harness the clinical data and molecular findings and create virtual patient models. 

• Innovative translational bioinformatics for a better understanding of the role of genetic variations to prioritise clinically relevant ones facilitating the promise of precision medicine

My group has a lead in this development by designing SNPnexus to address the data analysis challenge (www.snp-nexus.org). SNPnexus is a powerful platform for understanding a phenotype at a molecular level. SNPnexus has a constantly growing, national and international user community.

• Comprehensive analysis of morphologically normal tissue resected proximal and distant from breast primary tumour

We use next-generation sequencing/proteomics analysis to understand the molecular subtypes within matched adjacent normal samples and investigate their distinct prognostic and therapeutic capabilities. 

• Tracking clonal evolution in pancreatic cancer using sequential non invasive liquid biopsies. 

We use next-generation sequencing of matched germline, tumour and serial circulating tumour DNA (ctDNA) samples to explore the clonal evolution of pancreatic cancer, and isolate markers of disease progression, treatment response and acquired resistance. 

• Computational/integrative cancer bioinformatics and biomarker discovery

My team has developed several analytical pipelines, directly applicable to patient data, and the study of the transcriptional/mutational landscapes and evolutionary dynamics of different cancer types to identify therapeutic targets and prognostic biomarkers. 

Other Activities

• Director of training, Health Data Research (HDR) UK London Site
• Honorary Professor, American University of Beirut, Lebanon

Panel membership:

• Medical Research Council, Methodology Research
• Medical Research Council, Capacity and Skills
• UKRI, Future Leaders Fellowships
• EPSRC, Hubs for Mathematical Sciences in Healthcare
• European Commission, Innovative Medicines Initiative
• European Commission, Horizon 2020
• Research Council of Norway, Health Sciences and Biology
• Academy of Finland R'Life 

Major Funding

• 2021-2023- Data-driven risk and prognosis prediction from EHRs, CAP-AI, £100K  
• 2021-2026- Precision Medicine - Unlocking the longitudinal Electronic Health Record phenotype from multi-dimensional data, Barts Charity, £5.7M, Co-PI  
• 2019-2024- Breast Cancer Now, Breast Cancer Now Tissue Bank Bioinformatics £395,264.18
• 2018-2023- CHANEL PARFUMS BEAUTE, Multi-omics approach to skin biology using a large scale Genome cohort, £480,887
• 2017-2022- Barts Charity, Functional annotation of genetic variations from NGS, £180,314
• 2015-2024- Pancreatic Cancer Research Fund Tissue Bank, £2,340,000 (co-PI)

Recent Publications

Personalized neoantigen viro-immunotherapy platform for triple-negative breast cancer Brito Baleeiro R, Liu P, Chard Dunmall LS et al. Journal for ImmunoTherapy of Cancer (2023) 11(7)

A role for macrophages under cytokine control in mediating resistance to ADI-PEG20 (pegargiminase) in ASS1-deficient mesothelioma Phillips MM, Pavlyk I, Allen M et al. Pharmacological Reports (2023) 75(7) 570-584

Chairwomen: Diagnostic studies for pancreatic cancer Chelala C, Costello-Goldring E Pancreatology (2023) 23(10) e2

Correction: A role for macrophages under cytokine control in mediating resistance to ADI-PEG20 (pegargiminase) in ASS1-deficient mesothelioma (Pharmacological Reports, (2023), 75, 3, (570-584), 10.1007/s43440-023-00480-6) Phillips MM, Pavlyk I, Allen M et al. Pharmacological Reports (2023) 75(7) 753

541 Gene set enrichment analysis identifies biological networks associated with skin aging in a large Japanese population: Data from the Nagahama cohort Latreille J, Thorn G, Jdid R et al. Journal of Investigative Dermatology (2023) 143(10) s93

902 Development of a web-based platform to facilitate research to uncover the skin ageing mechanism Oscanoa J, Latreille J, Le Clerc S et al. Journal of Investigative Dermatology (2023) 143(10) s154

Dynamic Biobanking for Advancing Breast Cancer Research Abdollahyan M, Gadaleta E, Asif M et al. Journal of Personalized Medicine (2023) 13(7)

Differentiating Ductal Adenocarcinoma of the Pancreas from Benign Conditions Using Routine Health Records: A Prospective Case-Control Study Zardab M, Balarajah V, Banerjee A et al. Cancers (2023) 15(7)

A survey on clinical natural language processing in the United Kingdom from 2007 to 2022 Wu H, Wang M, Wu J et al. npj Digital Medicine (2022) 5(7)

Longitudinal profiling of circulating tumour DNA for tracking tumour dynamics in pancreatic cancer Sivapalan L, Thorn GJ, Gadaleta E et al. BMC Cancer (2022) 22(7)

Team

Biography

In 2002, I was awarded a PhD in Computational Biology/Radiation Biology from Paris-Sud University/Curie Institute and a degree in Structural Bioinformatics from Paris Descartes University. My first post-doctoral experience at the National Centre for Scientific Research (CNRS) involved the development of novel tools to gather information for automated analysis of genome maps and distribution study of the disease-related genes.

In 2004, I joined the Pasteur Institute in Paris to work on large-scale analysis of genetic variation, integration with clinical data and the association with type 1 diabetes. I worked on developing tools to transfer, integrate and analyse the genetic, genomic and proteomic data. My later studies have centred on cancer research.

In 2006, I joined Barts Cancer Institute (BCI) driven by a high motivation to translate my work from a substantial basic/computational research platform into a translational/patient setting. I established an interdisciplinary research team with complementary expertise in translational bioinformatics, clinical informatics, computer science, molecular biology, databases and software engineering. My research is very collaborative with clinical and basic scientists at the Barts & The London School of Medicine (SMD) and Barts Health. 

My most challenging, and most rewarding, role is being a mother of two young boys. Not surprisingly, I am very passionate about communicating my love of data science to young children. With the help of my team, we have engaged with primary school children to encourage interest in data science and ultimately inspire the next generation of health data researchers.