Suitable for PhD, Masters or Honours Students. The project requires knowledge of python or R, preferably both.
Next generation sequencing has allowed researchers to characterise the somatic landscape of cancer genomes, which has led to the discovery of biomarkers that may be predictive and prognostic to targeted therapies. However, the efficacy of current targeted therapies has failed to raise the overall survival curve in many tumour types. Immunotherapy has shown a promising benefit in treating many tumours and demonstrated remarkable responses in some patients even at recurrent, relapse and metastasis stage. The challenge now is to determine who and why some patients respond to treatment. Somatic mutations within the genomes of cancer cells may result in neoantigens that are presented on the tumour cell surface. These can then be seen by the immune system and killed by the patient’s immune system. This project will test and develop bioinformatic approaches that can be applied to understand complex tumour-immune interactions. Specifically, the project will use genome and RNAseq data to predict neoantigens and determine which of these be important in immunotherapy. The findings from this work are likely to shed new insight into tumour immunology and may predict which patients will respond to immunotherapy.