Translational Control and Cellular Toxicity in Thoracic Malignancies
Programme Leader: John Le Quesne
Summary of Research Interests
i) Optimisation of host/tumour toxicities in cancer therapies
Current approaches to cancer treatment are being revolutionised by mutation-specific personalised treatments. These often show impressive effects upon tumour growth initially, but ultimately relapse, and there is as yet little evidence that overall survival is prolonged in comparison to conventional therapies.
There is great interest in alternative ‘network’ therapies that target regulatory cellular events that influence numerous downstream pathways; these show great promise, but also potentially inflict diverse toxic effects upon normal patient tissue. One of the most promising targets is the dysregulation of protein synthesis which is key to the growth of many tumours.
We are working to better target this approach, minimizing the toxic effects of possible inhibition of protein synthesis in normal tissue, and off-target effects in cancer cells, thereby enabling us to maximize therapeutic activity. This involves deriving biomarkers that identify tumours which are most dependent upon dysregulated protein synthesis for their growth, and, by altering drug regimens and precise target selection, eliminating any toxicities that may paradoxically be advantageous to the malignant cell.
ii) Quantitative digital histopathology
Human tumours are extraordinarily diverse in their appearance, in their genetic changes, and in their clinical behaviour. Our understanding of the genetic changes underlying these diseases is improving rapidly, but our understanding of the cell biological processes that this diverse histological appearance represents is poor. The traditional histopathological skills of tissue interpretation are enormously valuable but are underused as research tools, so we are using these skills, as well as automated image analytical techniques, to answer basic biological and translational questions in cancer tissues.
In collaboration with other groups in the Unit, we are using digital images in the assessment of explant tumour studies from mesothelioma tissues for the assessment of novel treatment regimens. This involves immunohistochemical compartmentisation of small tissue fragments into tumour and stromal areas, and by application of this information to digital images, further subcompartmental analysis of other immunohistochemical biomarkers.
We are also assembling large retrospective collections of tumour tissue, with associated clinicopathological data. Using digital pathology, we are collecting thousands of high-quality tissue images, and are using the same technology to capture and quantify data from in situ analyses applied to tissue microarrays (TMAs). We are using these collections of mesotheliomas and non-small cell lung cancers as substrates for biomarker discovery, and as a platform in which to validate cell biological hypotheses by correlating them with patient outcomes.
We are using these data to formulate novel classifications of human tumours which take account of cell biology as well as morphological and genomic features.