Predicting Cancer Tissue-of-Origin by a Machine Learning Method Using DNA Somatic Mutation Data.

ABSTRACT: Patients with carcinoma of unknown primary (CUP) account for 3-5% of all cancer cases. A large number of metastatic cancers require further diagnosis to determine their tissue of origin. However, diagnosis of CUP and identification of its primary site are challenging. Previous studies have suggested that molecular profiling of tissue-specific genes could be useful in inferring the primary tissue of a tumor. The purpose of this study was to evaluate the performance somatic mutations detected in a tumor to identify the cancer tissue of origin. We downloaded the somatic mutation datasets from the International Cancer Genome Consortium project. The random forest algorithm was used to extract features, and a classifier was established based on the logistic regression. Specifically, the somatic

SUBMITTER: Liu X 

PROVIDER: S-EPMC7372518 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature