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We aim to embed the role of pathology across all research for the benefit of patients and to bring about improvements in the quality of reseach. Our team have interests in a wide range of projects including in digital pathology and image analysis, and multimodal and molecular pathology. Our group also includes Oxford Biocore, the recently formed NDS Tissue Handling Platform.

Histology slide
Histology slide

Histopathology, the microscopic study of diseased tissue, is an important tool in research, since accurate diagnosis and analysis of cancer and other diseases allows researchers to better understand the effects on patients and their prognosis.  It enables clinicians to stratify patients into risk groups and, in some cases, can ensure patients are not over or under treated.  Samples of tissue are often stained for various markers to help diagnose and understand abnormal cells found in tumours, and to detect cellular events such as cell death which may help in understanding the behaviours in certain cancers, and the implications for disease progression.   For instance, using immunohistochemistry staining for expression of a protein kinase in prostate cancer may be a marker of response to radiotherapy allowing clinicians to determine the effectiveness of the treatment. 

Molecular pathology assesses the changes in tissues together with an understanding of the molecular and genetic changes in human diseases (especially cancer), and includes the design and validation of predictive biomarkers for treatment response and disease progression. It enables researchers to understand why individuals of different genetic constitutions go on to develop disorders whereas others do not.  Various techniques are used in molecular pathology and include  quantitative polymerase chain reaction (qPCR), multiplex PCR, DNA microarray and DNA sequencing, and antibody based immunofluorescence tissue assays.  More accurate diagnosis is possible when the diagnosis is based on both the morphologic changes in tissues and on molecular testing.  For example, the 100,000 Genomes Project aims to sequence the DNA from around 70,000 patients.  By comparing  DNA from a patient’s tumour and healthy cells researchers will gain insight into the exact nature and genomic changes that are causing an individual’s cancer.  For more information, see:

Multimodal pathology and digital pathology enables researchers to convert glass slides, which have usually been stained with various markers,  to digitised images and to use various tools such as machine learning programmes to determine various histological features.  Algorithms can be used to automate processes such as the manual counting of cell types, or to determine the number and type of cells in tumour and non tumour tissue.  The aim is to reduce human error, improve accuracy of diagnosis and enable researchers to determine the differences in cell type, number and architecture in various cancers and other diseases and the effect on patient outcome.   For instance, by using an algorithm to assess the different density/distribution of tumour infiltrating lymphocytes in both cancer and non cancer tissue, and using this information in association with information about the patient’s disease progression,e.g  the clinical stage at presentation or disease relapse , it may be possible to improve patient prognosis in the longer term by determining histological features in testicular tumours and their association with outcome.

Digital slides are also easier to share than physical slides and could lead to developments allowing better patient outcomes such as enabling experts to consult on rare cases or to take part in virtual multi-disciplinary team meetings (MDT’s) where consultations can take place much more quickly and efficiently.   



Members of the Verrill Pathology Group

Our team

Related research themes