Harnessing pre-clinical lung cancer patient models for precision immuno-oncology (360G-Wellcome-209199_Z_17_Z)

<p>Only 16% of non-small cell lung cancer (NSCLC) patients survive for 5 years. Improvement in survival has been slow as the histological and genomic features of the disease are heterogeneous. Tumour heterogeneity poses a challenge for therapy development and suggests the importance of a personalised medicine approach. One approach is to expand the subset of tumour-infiltrating lymphocytes (TILs) that target neoantigens generated by tumour mutations; however, the lack of model systems that recapitulate the complexity of human disease is a significant barrier to research in this area. Patient-derived xenografts (PDXs) have considerable advantages over murine cancer models and cell lines so I will generate PDX models from patients enrolled in the TRACERx clinical study, which aims to delineate the evolutionary trajectories of NSCLC through multi-region genetic analyses of primary, recurrence and metastatic tumours. My first goal is to establish the extent to which PDX tumours represent patient intratumour heterogeneity using the extensive TRACERx dataset. I will further use these models - along with patient-matched TILs - in&nbsp;<em>in vitro</em>&nbsp;and&nbsp;<em>in vivo</em>&nbsp;assays to investigate the key determinants of the ability of TILs to destroy cancer cells and to investigate the effect of dual checkpoint inhibitor and TIL therapy.</p>

£250,000

08 Nov 2017