THE GENETIC SUBTYPES AND THE TUMOR MICROENVIRONMENT SIGNATURES ARE ASSOCIATED WITH DISTINCT OUTCOMES IN PERIPHERAL T‐CELL LYMPHOMA

Abstract

Background: Emerging evidence suggests the prognostic impact of the tumor microenvironment (TME) in peripheral T-cell lymphomas (PTCLs). To better understand PTCL pathobiology, we performed an integrative multi-omics study to explore the genetic subtypes and the TME signatures of PTCLs, especially nodal T-follicular helper T-cell lymphomas (nTFHLs) and PTCL, not otherwise specified (PTCL-NOS). Method: We performed whole-exome sequencing of 92 nTFHLs and 37 PTCL-NOSs, a total of 129 cases. Ninety-two nTFHLs included 85 angioimmunoblastic T-cell lymphomas (AITLs), four nPTCL with TFH phenotypes, two follicular T-cell lymphomas, and one unclassifiable nTFHL. Genetic drivers were integrated using non-negative matrix factorization consensus clustering (NMF). We estimated the proportion of immune cell fractions from bulk RNA sequencing data (n = 57) using CIBERSORTx and classified the TME signatures using hierarchical clustering. Results: NMF clustering analysis revealed three genetic subtypes within our cohort, except for 10 cases lacking recurrent genetic abnormalities (denoted as cluster 0). C2 was characterized by TP53 mutation, CDKN2A loss, PTEN loss, and chromosomal instability, corresponding to the previously described GATA3-PTCL subtype. C1 and C3 shared TFH-related genomic alterations, but C3 had significantly higher frequencies of chromosome (Chr) 5 gain, Chr 21 gain, RHOA, IDH2, and CD28 mutations. A higher frequency of rash and higher C-reactive protein levels than the other AITLs characterized C3-AITL. Pairwise association analysis of genomic alterations revealed that multiple TET2 mutations, rather than a single TET2 mutation, significantly co-occurred with IDH2 and RHOA mutations. A Bradley-Terry model estimated that the first TET2 and DNMT3A mutations occurred earlier, and the second or later TET2, RHOA, and IDH2 mutations occurred later. Compared to C1, significantly inferior survival was observed in C2 (hazard ratio (HR), 2.52; 95% CI, 1.37–4.63) and C3(HR, 2.14; 95% CI, 1.17–3.89; Figure A). The TME signatures were divided into TME1 (B-cells and follicular helper T-cells), TME2 (activated memory CD4 T-cells, M2 macrophages, and CD8 T-cells), and TME3 (naïve CD4 T-cells and activated mast cells). mTORC1 signaling was enriched in the TME2 signature compared to TME1 and TME3 signatures. The TME2 signature was significantly associated with shorter survival than the TME3 signature (HR: 3.4, 95% CI 1.6–7.5; Figure B). C2 had significantly more TME2 signature than C1 (64.3% vs. 7.7%), while C1 had significantly more TME3 signature than C2 (80.8% vs. 28.6%, p = 0.006; Figure C). Keywords: genomics, epigenomics, and other -omics, microenvironment Encore Abstract—previously submitted to EHA 2023 The research was funded by: Japan Society for the Promotion of Science KAKENHI grants (grant numbers: 19K23879, 22K19451, and 21H02945) and Japan Agency for Medical Research and Development (AMED) grants (20ck0106544 and 21ck0106644)