Wellcome Sanger Institute

Cancer Dependency Map Analytics

Cancer, Ageing and Somatic Mutation

We design algorithms and computational tools for the analysis of large-scale cancer pharmacogenomics and functional genomics datasets (from chemical and genome-editing screens) to the aim of identifiying new oncology therapeutic targets and markers of gene-essentiality/drug-response.

In partnership with Open Targets, we provide computational support and analytic solutions to the international Cancer Dependency Map consortium, and to other projects engaged in the analysis of data from large-scale chemo/genetic screens.

Our people

Group lead

Photo of Dr Francesco Iorio

Dr Francesco Iorio

Principal Staff Scientist

Francesco leads the development of new algorithms and computational tools for the analysis of large-scale cancer pharmacogenomics and functional genomics datasets (from chemical and genome editing screens), to identify molecular markers of drug response and new oncology therapeutic targets. Toward this aim, he is responsible for the design of analytical methods and software, and the management of day-by-day operations to deliver scientific milestones toward the definition of a global Cancer Dependency Map: an atlas of genetic dependencies and vulnerabilities, at an individual cancer cell resolution, which could be exploited for the development of cancer targeted and personalized therapies. Francesco completed his PhD in the Systems, Synthetic and Computational Biology Laboratory of the TeleThon Institute of Genetics and Medicine (TIGEM, Naples, Italy), focusing on computational methods for drug discovery and repositioning based on the analysis of large compendia of gene expression profiles. Subsequently he was awarded a joint EMBL-EBI/Sanger postdoctoral fellowship (ESPOD) and he worked on integrative computational frameworks for predicting and dissecting drug susceptibility in cancer based on the analysis of data from large-scale drug screens. Prior joining CASM at the Wellcome Sanger Institute, he has been the leading computational scientist in a project funded by Open Targets (a public-private initiative spearheaded by EMBL-EBI, GSK, Biogen and the Wellcome Sanger Institute), aiming at identifying new therapeutic targets and synthetic lethalities in cancer, through the analysis of data from a large-scale, genome-wide CRISPR-Cas9 knockout screen across hundreds of cancer cell lines. Within Open Targets he currently leads the CELLector project to systematically evaluate the disease relevance of cancer in-vitro models, and he has been coleading the DoRothEA project linking trascription factors activities to somatic mutations and cancer response to therapy. Francesco is also interested in designing computationally efficient methods simulating constrained null models for testing combinatorial properties in cancer genomics datasets and networks; unsupervised machine learning; data visualisation; information theory and theoretical computer science.

Core team

Photo of Dr Hanna Najgebauer

Dr Hanna Najgebauer

Open Targets Postdoctoral Fellow

Photo of Dr Clare Pacini

Dr Clare Pacini

Postdoctoral Fellow

Photo of Dr Emre Karakoc

Dr Emre Karakoc

Principal Bioinformatician

Photo of Valeria Mirici Cappa

Valeria Mirici Cappa

Visiting Scientist

Previous team members

Photo of Dr Ichcha Manipur

Dr Ichcha Manipur

Visiting Scientist

Photo of Alessandro Vinceti

Alessandro Vinceti

Visiting Scientist


We work with the following groups


Open Targets

Open Targets is a pioneering public-private partnership between Biogen, Celgene, EMBL-EBI, GlaxoSmithKline (GSK), Takeda, and the Wellcome Sanger Institute and is located on the Wellcome Genome Campus. Open Targets brings together expertise from six complementary institutions to systematically identify and prioritise targets from which safe and effective medicines can be developed, to help others find good targets, and to get those targets adopted into drug discovery pipelines.Current focuses are oncology, immunology and neurodegeneration through an R&D framework that can be applied to all aspects of human disease.

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Non-COVID19 news. Cancer evolution is unstoppable, but is it predictable? If so, is it controllable? In our latest work by Acar, Nichol et al. we show it is possible to ‘steer’ cancer evolution in a controlled manner to design evolution-aware treatments: https://www.nature.com/articles/s41467-020-15596-z