A Machine Learning Method to Trace Cancer Primary Lesion Using Microarray-Based Gene Expression Data.

ABSTRACT: Cancer of unknown primary site (CUP) is a heterogeneous group of cancers whose tissue of origin remains unknown after detailed investigation by conventional clinical methods. The number of CUP accounts for roughly 3%-5% of all human malignancies. CUP patients are usually treated with broad-spectrum chemotherapy, which often leads to a poor prognosis. Recent studies suggest that the treatment targeting the primary lesion of CUP will significantly improve the prognosis of the patient. Therefore, it is urgent to develop an efficient method to accurately detect tissue of origin of CUP in clinical cancer research. In this work, we developed a novel framework that uses Extreme Gradient Boosting (XGBoost) to trace the primary site of CUP based on microarray-based gene expression data. First, we d

SUBMITTER: Lu Q 

PROVIDER: S-EPMC9071249 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature