A Method for Subtype Analysis with Somatic Mutations

• Activity Number: 209 - Statistical methods for genomic and epigenetic data analysis
• Type: Contributed
• Date/Time: Tuesday, August 10, 2021 : 1:30 PM to 3:20 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Meiling Liu* and Yang Liu and Michael C Wu and Li Hsu and Qianchuan He
• Companies: Fred Hutchinson Cancer Research Center and Wright State University and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center
• Keywords: Association test ; Multinomial traits; Somatic mutation ; subtypes ; SASOM

Abstract

Cancer is a highly heterogeneous disease, and virtually all types of cancer have subtypes. Understanding the association between cancers subtypes and genetic variations is fundamental to the development of targeted therapies for patients. Somatic mutation plays important roles in tumor development and has emerged as a new type of genetic variations for studying the association with cancer subtypes. However, the low prevalence of individual mutations poses a tremendous challenge to the related statistical analysis.

In this article, we propose an approach, SASOM, for the association analysis of cancer subtypes with somatic mutations. Our approach tests the association between a set of somatic mutations and subtypes, while incorporating functional information of the mutations into the analysis. Simulation studies show that the proposed approach has correct type I error and tends to be more powerful than possible alternative methods. In a real data application, we examine the somatic mutations from a cutaneous melanoma dataset, and identify a genetic pathway that is associated with immune-related subtypes.