Combining gene expression profiling and machine learning to diagnose B-cell non-Hodgkin lymphoma.

ABSTRACT: Non-Hodgkin B-cell lymphomas (B-NHLs) are a highly heterogeneous group of mature B-cell malignancies. Their classification thus requires skillful evaluation by expert hematopathologists, but the risk of error remains higher in these tumors than in many other areas of pathology. To facilitate diagnosis, we have thus developed a gene expression assay able to discriminate the seven most frequent B-cell NHL categories. This assay relies on the combination of ligation-dependent RT-PCR and next-generation sequencing, and addresses the expression of more than 130 genetic markers. It was designed to retrieve the main gene expression signatures of B-NHL cells and their microenvironment. The classification is handled by a random forest algorithm which we trained and validated on a large cohort of mo

SUBMITTER: Bobee V 

PROVIDER: S-EPMC7244768 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature