Researchers from the Ontario Institute for Cancer Research, the University Health Network, and the UCLA Department of Human Genetics have created a novel method to determine whether a cancer will be lethal or not based on tumor clonality.
BACKGROUND:
Cancer occurs from the accumulation of mutations within a cell that cause the cell to behave in an abnormal, uncontrollable manner. Cancerous tumors can occur through a simple evolution, where the population of cancer cells all contain the same mutations, which is termed a monoclonal tumor. Alternatively, a tumor can undergo a more complex evolution and could contain two or more populations of cancerous cells. These tumours are called polyclonal, and can either arise from (1) two separate cells becoming cancerous at the same time, or (2) a monoclonal population slowly mutating into a polyclonal population over time. Current approaches towards treating cancer do not consider a patient’s personal tumor genotype and polyclonal tumors can confound current molecular detection techniques. It is also unknown how and why tumours follow these distinct evolutionary paths. As a result many patients receive too little or too much treatment, and therefore are either more likely to die of their disease or to suffer the personal and financial toxicities of treatment unnecessarily. There is thus an urgent clinical need for biomarkers that can accurately determine a patient’s risk level.
INNOVATION:
Researchers from the Ontario Institute for Cancer Research, the University Health Network, and the UCLA Department of Human Genetics have created a new computer program that allows them to diagnose and prognose cancer in a patient. The computer program can analyze the DNA sequences from a patient’s tumor and determine the diversity of cells within the tumor to determine the patient’s risk outcome and response to therapy. The risk level can help guide the treatment plan based on the patient’s personal tumor genotype. Currently, this method has been tested on prostate cancer samples.
POTENTIAL APPLICATIONS:
• Diagnosis of cancer, including prostate cancer
• Personalized treatment plans based on tumor clonality
• Cancer relapse risk
ADVANTAGES:
• Defines each individual patient’s unique personal tumor genotype
• Identifies number of cancer sub-populations within a tumor, allowing evolutionary treatment
• Integrates genomic, microenvironmental, evolutionary and clinical data into a single risk score
• Can identify cancer in patients with multi-clonal tumors, which existing molecular techniques struggle with
DEVELOPMENT-TO-DATE:
The researchers studied 293 tumors from patients with intermediate-risk prostate cancer and built an analysis framework that defines risk based on tumor genotype.
RELATED PAPERS:
Espiritu, S. M. G. et al. The Evolutionary Landscape of Localized Prostate Cancers Drives Clinical Aggression. Cell 173, 1003–1013.e15 (2018).
Fraser, M. et al. Genomic hallmarks of localized, non-indolent prostate cancer. Nature 541, 359–364 (2017).
Lalonde, E. et al. Translating a Prognostic DNA Genomic Classifier into the Clinic: Retrospective Validation in 563 Localized Prostate Tumors. European Urology 72, 22-31 (2017).
Lalonde, E. et al. Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study. Lancet Oncology 15, 1521-1532 (2016).