Pathogenesis and Clinical Relevance of Diffuse Large B-Cell Lymphoma Proteogenotypes

Diffuse large B-cell lymphomas (DLBCL) are genetically and clinically heterogenous. Despite advances in the gene-expression and genomic characterization, the pathophysiology of high-risk DLBCL still remains incompletely understood. We report the first proteogenomic analysis of DLBCL tissues from 438 patients to elucidate disease pathophysiology, delineate so far undescribed high-risk tumor characteristics and inform diagnostic and therapeutic approaches. By integration of genetic, transcriptomic and mass-spectrometry-based quantitative proteomic data using machine learning approaches and latent variable modelling, we identify seven DLBCL proteogenotypes (PG) reflecting specific pathophysiological patterns and spanning cell-of-origin (COO) boundaries. These PGs differed regarding their cellular and immune microenvironment as well as B-cell-intrinsic oncogenic programs and differentiation patterns and could not be identified by mere genomics or transcriptomics. PG4 was discovered as high-risk DLBCL with inferior overall and progression-free survival upon R-CHOP-based therapy independently of known risk factors such as COO, genetic subtypes, lymphoma ecotypes and the international prognostic index. PG4 was validated as an independent risk factor in additional cohorts of de novo DLBCL (n=865 patients). It was enriched for specific subsets of activated B-cell-like DLBCL with MYD88/CD79b mutations (68.4 % of all ABC-MCD/MYD88 DLBCLs) and double-hit-signature-positive germinal center B-cell-like tumors (18.6 % of all Dhit-sig+ GCB DLBCLs) indicating heterogeneity within these genetic subtypes. PG4 cases shared a dark-zone related B-cell phenotype, an enrichment of BTG1 and TBL1XR1 mutations and enhanced B-cell receptor and MYC activity. Moreover, deregulated protein translation was a PG4-defining feature evident at the proteomic level only. Single-cell RNA and ATAC sequencing of 43 DLBCL cases (197,860 cells) with proteogenotype information confirmed enhanced BCR, MYD88 and PI3K activity and the dark-zone phenotype in the PG4 malignant B cells. Moreover, TCF3 and TCF4 transcription factors showed enhanced activity in GCB-PG4 and ABC-PG4 tumors, respectively. Analysis of the PG4 tumor microenvironment at single-cell granularity revealed a significant T-cell depletion and exhaustion of the CD8 T-cell effector memory compartment, likely contributing to resistance against conventional chemoimmunotherapy. Importantly, PG4 was detectable even at the subclonal level in single-cell sequencing data from individual tumors (n=103 patients, 504,444 cells). Here, 24 tumors had PG4-predicted subclones that biologically varied significantly from other subclones in the tumors (p<0.01), providing for the first time evidence for intratumoral proteogenomic heterogeneity. In addition to identifying PG4-DLBCLs as chemo-resistant tumors, we provide insight into how the identified PGs respond to innovative immunotherapies such as CAR T-cell therapy. In summary, our study provides an integrated proteogenomic framework up to the single cell level explaining so far unresolved disease heterogeneity and identifying molecular features of high-risk DLBCL as a basis for innovative diagnostic and therapeutic approaches. The diagnostic detection of PG4-DLBCL as chemo-resistant lymphoma has the potential to improve patient outcome by enabling the selection of more efficient therapies for these tumors.