Research focus

Studying tumor ecology

The main focus of the Yuan lab is to foster technological advances for studying cancer, fusing histological image analysis, ecological statistics and bioinformatics. Our aim is to understand how the normal cells surrounding cancer cells help or prevent cancer growth and spread. The novel concept of tumors as evolving ecosystems may help us understand why cancer is so difficult to treat, and direct new therapeutic interventions - akin to draining the swamps to get rid of mosquitoes as one way of eradicating malaria.

Our work has changed the way we think of the microenvironment and its critical roles in different cancers by examining cancer cells in the spatial context of their microenvironment. We are now working on developing computational approaches to study the influence of tumour microenvironment on cancer progression and evolution. Understanding how cancer cells adapt to their microenvironment is key to appreciating how they develop and evolve, and can direct therapeutic interventions to alter or stop the selective pressures.

We are part of the new Centre for Evolution and Cancer at the ICR and the Centre for Molecular Pathology at the Royal Marsden Hospital. Using our highly interdisciplinary approaches, our goals are to deliver scientific advances and clinical innovations by dissecting the spatial and molecular heterogeneity of tumour microenvironment, to foster new developments in machine learning for applications in oncology and pathology, and to develop objective methodologies for directing cancer therapeutic strategies.


Deciphering the tumour microenvironment

Histopathological images can provide spatial mapping of the tumour microenvironment. With computer vision technologies, we quantify the spatial dependencies between different types of cells, and use machine learning methods to advance our understanding in intra-tumour heterogeneity which is a major challenge in cancer therapeutics. This integrative study aims to reveal the functional roles of normal cells including fibroblasts and lymphocytes in cancer progression.

Computational pathology to explore the spatial dimension of tumor ecology

Cancer and normal cells exhibit both co-operative and competitive relationships, analogous to living organisms. Considering the tumour as an ecological habitat, we use a combination of ecological statistics and medical advances to analyse the ecological relationships in tumours using data derived from tumour histology. This novel way of studying the tumour microenvironment can expand our knowledge of cancer progression and reveal new clinical prognosticators. Read our review paper Computational pathology: Exploring the spatial dimension of tumor ecology
Nawaz S, Yuan Y* Cancer Letters (2015)


Centre for Evolution and Cancer & Division for Molecular Pathology,
The Institute of Cancer Research, London
Centre for Molecular Pathology,
The Royal Marsden Hospital

Open positions

A variety of opportunities are available. Qualification in computer science, statistics, ecology or other quantitative disciplines is usually required. Good programming skills, preferably in R, Matlab, Python or C, and experience in image analysis, machine learning or statistics are essential. All positions except for the student scholarship are immediately available, but start dates are negotiable. Enquiry can be sent to yinyin.yuan (a), but applications need to be sent through ICR website for:

Image analysis postdoc position to investigate treatment resistance in 4,500 breast cancers in collaboration with Prof Mitch Dowsett's team at the ICR (deadline 30/01/2017 with a potential start date of 01/03/2017).

Bioinformatics Officer to lead the development of bioinformatics pipelines for integrative analysis of digital pathology and genomic data (deadline 18/02/2017 with a potential start date of 01/04/2017).

Summer intern scholarship A 8-weeks project that will be customised based on the skill set and interests of the successful candidate (deadline 27/02/2017).

Image analysis postdoc position to work on TRACERx, the largest study of lung cancer evolution to date in a collaboration with Prof Charles Swanton at the Francis Crick Institute (deadline 01/03/2017 with a potential start date of 01/05/2017).

Selected publications

Biopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score.
Khan AM, Yuan Y*
Nature Scientific Reports (2016)

We systematically investigate biopsy variability for the lymphocytic infiltrate in 998 breast tumours using a novel virtual biopsy method. Interestingly, biopsy variability of lymphocytic infiltrate differs considerably among breast cancer subtypes, with the HER2+ subtype having the highest variability.

Microenvironmental heterogeneity parallels breast cancer progression: A histology-genomics integration analysis
Natrajan R, Sailem H, Mardakheh FM, Arias MG, Dowsett M, Bakal C, Yuan Y*
PLOS Medicine (2016) [Sweave; R package beta version]

We propose a clinically relevant role of tumour microenvironmental diversity for advanced breast tumors and highlight that ecological statistics can be translated into medical advances for identifying new biomarkers and for understanding the synergistic interplay between the microenvironment and cancer genomics.