A refined cell-of-origin classifier with targeted NGS and artificial intelligence shows robust predictive value in DLBCL.

ABSTRACT: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity of B-cell lymphoma. Cell-of-origin (COO) classification of DLBCL is required in routine practice by the World Health Organization classification for biological and therapeutic insights. Genetic subtypes uncovered recently are based on distinct genetic alterations in DLBCL, which are different from the COO subtypes defined by gene expression signatures of normal B cells retained in DLBCL. We hypothesize that classifiers incorporating both genome-wide gene-expression and pathogenetic variables can improve the therapeutic significance of DLBCL classification. To develop such refined classifiers, we performed targeted RNA sequencing (RNA-Seq) with a commercially available next-generation sequencing (NGS) platform in a large cohort

SUBMITTER: Xu-Monette ZY 

PROVIDER: S-EPMC7391158 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature