Kening Zhao
Pronouns: she/her
Research Mentor(s): Chandan Kumar
Research Mentor School/College/Department: Pathology / Medicine
Program: UROPF
Session: Session 2 (10:00am – 10:50am)
Authors: Kening Zhao, Chandan Kumar, Kening Zhao
Abstract
As the second-leading cause of death in the world, cancer represents a situation of natural selection in which defective cells undergo randomized mutations that give a selective advantage to the cancer. Generally, cancer acquires one or a few selective strong mutations, known as drivers. At the Michigan Oncology Sequencing Program (MI-ONCOSEQ), cancer patients’ tumor and germline DNA, and tumor RNA are sequenced, and clinically actionable and informative findings are reported to the physicians. For the purpose of this study, we are interested in generating landscapes of the mutations, copy number changes, gene fusions, and tumor mutation burden from the cohort of biliary tract cancers in order to observe the recurrent presence of strong drivers. After compiling reported molecular aberrations in over two hundred cases in the BTC cohort, we summarized the data in a visually intuitive Oncoprint to highlight the mutual exclusivity of strong drivers, and GISTIC Plot to display the landscape of recurrent copy number aberrations. based on these aberrations, patients at individual case level are matched with targeted therapies, which are different from most traditional non-specific chemotherapeutic drugs in that the former precisely target certain genes and exerts a biological function with lesser adverse effects. Furthermore, the landscapes help to identify cases that are not actionable, in which we can search for targeted therapy for those genes in future studies.
