Professor Claude Chelala

BSc, MSc, DEA, PhD
Co-Director, Centre for Computational Biology, LSI; Professor of Bioinformatics
Deputy Centre Lead, Group Leader
Research Focus

My research interests lie in the area of translational bioinformatics. Current research projects are focused in high-throughput data analysis, integration with clinical data, databases and software development, particularly for pancreatic cancer and breast cancer.

Key Publications

Longitudinal profiling of circulating tumour DNA for tracking tumour dynamics in pancreatic cancer. BMC Cancer (2022) 22(1):369. PMID: 35392854

COVID-19 in patients with hepatobiliary and pancreatic diseases: a single-centre cross-sectional study in East London. BMJ Open (2021) 11(4):e045077. PMID: 33875444

Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer. NPJ Breast Cancer (2020). 6:38. PMID: 32885042

SNPnexus: a web server for functional annotation of human genome sequence variation (2020 update). Nucleic Acids Res (2020) 48(W1):W185-W192. PMID: 32496546

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)
Other Activities
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

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

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)

The molecular landscape of pancreatic ductal adenocarcinoma Sivapalan L, Kocher HM, Ross-Adams H et al. Pancreatology (2022) 22(7) 925-936

Expression Profile of Myoepithelial Cells in DCIS: Do They Change from Protective Angels to Wicked Witches? Dawoud MM, Jones DT, Chelala C et al. Applied Immunohistochemistry and Molecular Morphology (2022) 30(7) 397-409

Field cancerization in breast cancer Gadaleta E, Thorn GJ, Ross-Adams H et al. Journal of Pathology (2022) 257(7) 561-574

A biobank perspective on use of tissue samples donated by trial participants Speirs V, Cox A, Chelala C et al. The Lancet Oncology (2022) 23(7) e205

MHC class II molecules on pancreatic cancer cells indicate a potential for neo-antigen-based immunotherapy Baleeiro RB, Bouwens CJ, Liu P et al. OncoImmunology (2022) 11(7)

Temporality of clinical factors associated with pancreatic cancer: a case-control study using linked electronic health records Dayem Ullah AZM, Stasinos K, Chelala C et al. BMC Cancer (2021) 21(7)

Erratum: mTOR-dependent translation amplifies microglia priming in aging mice (Journal of Clinical Investigation (2021) 131:1 (1–16) DOI: 10.1172/JCI132727) Keane L, Antignano I, Riechers SP et al. Journal of Clinical Investigation (2021) 131(7)

Erratum: A virus-infected, reprogrammed somatic cell-derived tumor cell (VIReST) vaccination regime can prevent initiation and progression of pancreatic cancer (Clinical Cancer Research (2020) 26 (465-476) DOI: 10.1158/1078-0432.CCR-19-1395) Lu S, Zhang Z, Du P et al. Clinical Cancer Research (2021) 27(7) 2663

P020. Defining molecular signatures to personalise management of patients with early breast cancer Allen N, Allen M, Gomm J et al. European Journal of Surgical Oncology (2021) 47(10) e301

For additional publications, please click here
Team

Postdoctoral Researchers in this group
Dr Emanuela GadaletaDr Jorge OscanoaDr Helen Ross-AdamsDr Dayem Ullah, Dr Maryam Abdollahyan, Dr Graeme Thorn

PhD Students
Ms Pauline Fourgoux, Ms Lavanya Sivapalan

Data Manager
Millahat Asif

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.