Work

Transcriptomic Study of Diffuse Large B-Cell Lymphoma Associated with HIV Infection: Identification of Novel Molecular Subtypes

Year: 2026

Type: article

Abstract: Background/Objectives: Transcriptomic studies of diffuse large cell lymphoma (DLCL) have made it possible to distinguish several profiles, including Germinal Centres (GC) and Activated B-Cells. These different types present a different pathophysiology and evolution, which may lead to different treatments. However, these profiles were determined in patients not infected with the human immunodeficiency virus (HIV), whereas lymphomas in the immunocompromised present certain specific characteristics. We therefore set out to determine the transcriptomic profile of DLCL occurring in HIV patients, in order to more precisely determine the pathophysiology of the different subtypes and to identify deregulated molecular pathways that could have a theragnostic value. Methods: We analysed 12 paraffin-embeddd samples of DLCL linked to HIV infection (two replicates per biological samples) using the Agilent's SurePrint G3 Human GE 8x60K v2 transccriptome chip. Unsupervised hierarchical clustering was performed on the normalized data (quantile normalization) to define the groups that separate the samples according to their gene expression profile. Results: From this sample of 12 DLCLs, we were able to clearly define two transcriptomic subgroups. Among the differences in gene expression, TP53 and BCL7A were overexpressed in cluster I, and BCL2 in cluster II. In terms of signalling pathways, the ‘immune system development’ pathway was under-expressed in cluster I and over-expressed in cluster II. Conclusions: Our results strongly suggest the existence of two different transcriptomic signatures which certainly underlie significant differences in pathophysiology. These differences may be due to the specific tumour environment associated with HIV infection. Our very preliminary study will need to be continued with a larger number of patients, and integrate proteomic, metabolomic and clinical data in order to define a theragnostic approach.

Source: Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics

DOI: 10.32604/or.2026.076241