A key research objective is to know and understand genomic alterations that are driving the cancer – making it aggressive or resistant to treatment—and their consequences. This work can provide data driven explanations for previous treatment responses (e.g. poor or short-term response, significant side-effects), potential treatment options that target the driver alterations, or treatments that are unlikely to be effective.
The intensive pathway analyses and literature searches distinguish POG from other personalized cancer genomics approaches. These detailed assessments enable the global identification of biological processes that are potentially disrupted in individual cancers, with the aim of linking these processes to drugs and their mechanisms of action.
Collection | Samples (a biopsy sample and a blood sample) are collected from eligible study subjects. Additional information about patient diagnosis, past treatments and previously tested samples is also collected. All samples are assessed to confirm their quality and suitability for genome sequencing.
Data Generation and Analysis | From each sample, genome (from the biopsy and blood) and transcriptome (from the biopsy) sequence data are generated at the GSC. Professional data analysts (called computational biologists) analyse these data, looking for differences between the biopsy and the blood for novel features in the sequence, structure, size and activity of the genome and transcriptome.
Reporting | Both summary and detailed information is reported back to the clinician. The POG team reviews these and discusses possible interpretations of the data at the weekly tumour board meeting. The medical oncologist then works with the patient to decide if and how the information can inform decisions about treatment
Follow-up | Over time, the clinician reports back to the POG team on the progress of the patient, including whether the patient’s current treatment was informed by POG and what their current status is.