Robust sub-types of DLBCL are identified by model-based clustering of genetic mutations in a large (n=928) population-based cohort.
With full follow-up data available for all sequenced patients, the prognostic significance of these sub-types is identified.
Based on the profile of genetic alterations occurring in tumor samples from selected diffuse-large-B-cell-lymphoma (DLBCL) patients, two recent whole exome sequencing studies proposed partially overlapping classification systems. Using clustering techniques applied to targeted sequencing data derived from a large unselected population-based patient cohort with full clinical follow-up (n=928), we investigated whether molecular subtypes can be robustly identified using methods potentially applicable in routine clinical practice. DNA extracted from DLBCL tumors diagnosed in patients residing in a catchment population of ~4 million (14 centers), were sequenced with a targeted 293-gene hematological-malignancy panel. Bernoulli mixture-model clustering was applied, and the resulting subtypes analyzed in relation to their clinical characteristics and outcomes. Five molecular subtypes were resolved, termed MYD88, BCL2, SOCS1/SGK1, TET2/SGK1 and NOTCH2, along with an unclassified group. The subtypes characterized by genetic alterations of BCL2, NOTCH2 and MYD88 respectively recapitulated recent studies showing good, intermediate and poor prognosis respectively. The SOCS1/SGK1 subtype showed biological overlap with primary mediastinal B-cell lymphoma and conferred excellent prognosis. Although not identified as a distinct cluster, NOTCH1 mutation was associated with poor prognosis. The impact of TP53 mutation varied with genomic subtypes, conferring no effect in the NOTCH2 subtype and poor prognosis in the MYD88 subtype. Our findings confirm the existence of molecular subtypes of DLBCL, providing evidence that genomic tests have prognostic significance in non-selected DLBCL patients. The identification of both good and poor risk subtypes in R-CHOP treated patients clearly demonstrate the clinical value of the approach; confirming the need for a consensus classification.