Presented by: Pauline Funchain, M.D, Associate Professor of Medicine Stanford University, Stanford, CA.
Covered by: Abdul Moiz Khan, M.D, Chief Fellow of Hematology and Oncology at Karmanos Cancer Institute, Detroit, MI.
Dr. Funchain discussed that despite ongoing advances in precision medicine, there is still a long way to go when it comes to optimum patient selection to derive maximum benefits of our therapies. She reviewed the value of genomic markers such as tumor mutational burden (TMB) and neo-antigen load in predicting immunotherapy response. Additionally, germline testing can be very informative in immuno-oncology. Certain Human leukocyte antigen (HLA) types and family history of cancer also serve as predictors of efficacy of immunotherapy.
The real challenge lies in translating our knowledge of genetics to bedside. Germline mutations in genes such as BAP1, BRCA1/2 and CDKN2A have well-known association with melanoma and extended genetic testing may enable recognition of more genes of interest. The somatic and germline mutation profile of patients can be predictive and has formed the basis of patient selection in recent clinical trials. Finally, circulating tumor DNA (ctDNA) predicts for relapse and survival in high-risk resected melanoma patients. In future, our increasing understanding of the genomic landscape of melanoma, multispecialty collaboration, and utilization of artificial intelligence may result in better patient selection and outcomes.
- Van Allen, E. M., et al. (2015). Science, 350(6257), 207-211.
- Rizvi, N. A., et al. (2015). Science, 348(6230), 124-128.
- Chowell D et al. (2018). Science, 359(6375), 582-587.
- Lee et al. (2018). Annals of Oncology, 29(2), 490-496.
