Targetable subsets of non-Hodgkin lymphoma in Malawi define therapeutic opportunities

Abstract

Diagnostics and supportive care for patients with non-Hodgkin lymphoma (NHL) in lower- and middle-income countries (LMICs) are lacking. We hypothesized that high-throughput transcription-based diagnostics could classify NHL specimens from Malawi amenable to targeted therapeutics. We established tissue microarrays and classified 328 cases diagnosed by hematoxylin and eosin as NHL at University of Malawi College of Medicine using immunohistochemistry (IHC) for conventional markers and therapeutic targets. A subset was analyzed using NanoString-based expression profiling with parsimonious transcriptional classifiers. Overall, 72% of lymphomas were high-grade B-cell tumors, subsets of which were enriched for expression of MYC, BCL2, and/or PD-L1. A 21-gene transcriptional classifier, previously validated in Western cohorts, divided 96% of diffuse large B-cell lymphomas (DLBCLs) with 100% of B-cell lymphomas, unclassifiable, into 1 cluster and 88% of Burkitt lymphomas into a separate cluster. Cell-of-origin categorization of 36 DLBCLs by NanoString lymphoma subtyping test (LST) revealed 69% concordance with IHC. All discordant cases were classified as germinal center B cell-like (GCB) by LST but non-GCB by IHC. In summary, utilization of advanced diagnostics facilitates objective assessment and segregation of biologically defined subsets of NHL from an LMIC without expert review, thereby establishing a basis for the implementation of effective and less toxic targeted agents.

Graphical abstract

Figure 1.

Classification by morphology and immunophenotype. Representative examples of H&E staining at UOMCOM and BWH, as well as immunostaining at BWH, for cases of DLBCL, BL, and BCL-U. Original magnification ×40 for all panels (original magnification ×100 for insets).

Figure 2.

Unsupervised hierarchical clustering of transcriptional profiles of DLBCL, BCL-U, and BL cases based on the 21-gene classifier. Red indicates upregulation and blue downregulation of gene expression. Each row represents a gene, and each column represents a sample.