Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type.

ABSTRACT: Cancer of Unknown Primary (CUP) occurs in 3-5% of patients when standard histological diagnostic tests are unable to determine the origin of metastatic cancer. Typically, a CUP diagnosis is treated empirically and has very poor outcomes, with median overall survival less than one year. Gene expression profiling alone has been used to identify the tissue of origin but struggles with low neoplastic percentage in metastatic sites which is where identification is often most needed. MI GPSai, a Genomic Prevalence Score, uses DNA sequencing and whole transcriptome data coupled with machine learning to aid in the diagnosis of cancer. The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai predicted t

SUBMITTER: Abraham J 

PROVIDER: S-EPMC7815805 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature