Novel bioinformatic classification system for genetic signatures identification in diffuse large B-cell lymphoma.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is a spectrum of disease comprising more than 30% of non-Hodgkin lymphomas. Although studies have identified several molecular subgroups, the heterogeneous genetic background of DLBCL remains ambiguous. In this study we aimed to develop a novel approach and to provide a distinctive classification system to unravel its molecular features. METHOD: A cohort of 342 patient samples diagnosed with DLBCL in our hospital were retrospectively enrolled in this study. A total of 46 genes were included in next-generation sequencing panel. Non-mutually exclusive genetic signatures for the factorization of complex genomic patterns were generated by random forest algorithm. RESULTS: A total of four non-mutually exclusive signatures were generated, including those with MYC-translocation (MYC-trans) (n = 62), with BCL2-translocation (BCL2-trans) (n = 69), with BCL6-translocation (BCL6-trans) (n = 108), and those with MYD88 and/or CD79B mutations (MC) signatures (n = 115). Comparison analysis between our model and traditional mutually exclusive Schmitz's model demonstrated consistent classification pattern. And prognostic heterogeneity existed within EZB subgroup of de novo DLBCL patients. As for prognostic impact, MYC-trans signature was an independent unfavorable prognostic factor. Furthermore, tumors carrying three different signature markers exhibited significantly inferior prognoses compared with their counterparts with no genetic signature. CONCLUSION: Compared with traditional mutually exclusive molecular sub-classification, non-mutually exclusive genetic fingerprint model generated from our study provided novel insight into not only the complex genetic features, but also the prognostic heterogeneity of DLBCL patients.

An oxidative stress-based mechanism of doxorubicin cytotoxicity suggests new therapeutic strategies in ABC-DLBCL.

Diffuse large B-cell lymphomas (DLBCLs) contain 2 major molecular subtypes; namely, the germinal center B-cell-like (GCB) and the activated B-cell-like (ABC) DLBCLs. It is well documented that ABC-DLBCL cases have a significantly poorer survival response than GCB-DLBCLs in both the CHOP (cyclophosphamide, vincristine, doxorubicin, and prednisone) and the rituximab (R)-CHOP eras. However, the underlying cause of this subtype disparity is poorly understood. Nevertheless, these clinical observations raise the possibility for an ABC-DLBCL-specific resistance mechanism that is directed toward 1 of the CHOP components and is inadequately addressed by rituximab. Here, we report that the main cytotoxic ingredient in CHOP, doxorubicin (Dox), has subtype-specific mechanisms of cytotoxicity in DLBCLs resulting from differences in the subcellular distribution pattern. Specifically, in cell line models of ABC-DLBCL, Dox is often enriched in the cytoplasm away from the nuclear DNA. As a result, Dox-induced cytotoxicity in ABC-DLBCLs is often dependent on oxidative stress, rather than DNA damage response. These findings are corroborated by gene signature analysis, which demonstrates that basal oxidative stress status predicts treatment outcome among patients with ABC-DLBCL, but not patients with GCB-DLBCL. In terms of redox-related resistance mechanism, our results suggest that STAT3 confers Dox resistance in ABC-DLBCLs by reinforcing an antioxidant program featuring upregulation of the SOD2 gene. Furthermore, a small-molecule STAT3 inhibitor synergizes with CHOP to trigger oxidative stress and kill ABC-DLBCL cells in preclinical models. These results provide a mechanistic basis for development of novel therapies that target either STAT3 or redox homeostasis to improve treatment outcomes for ABC-DLBCLs.

Genomic and transcriptomic landscapes of Epstein-Barr virus in extranodal natural killer T-cell lymphoma.

Extranodal natural killer T-cell lymphoma (nasal type; NKTCL) is an aggressive malignancy strongly associated with Epstein-Barr virus (EBV) infection. However, the role of EBV in NKTCL development is unclear, largely due to the lack of information about EBV genome and transcriptome in NKTCL. Here, using high-throughput sequencing, we obtained whole genome (n = 27) and transcriptome datasets (n = 18) of EBV derived from NKTCL tumor biopsies. We assembled 27 EBV genomes and detected an average of 1,152 single nucleotide variants and 44.8 indels (<50 bp) of EBV per sample. We also identified frequent focal EBV genome deletions and integrated EBV fragments in the host genome. Moreover, Phylogenetic analysis revealed that NKTCL-derived EBVs are closely clustered; transcriptome analysis revealed less activation of both latent and lytic genes and larger amount of T-cell epitope alterations in NKTCL, as compared with other EBV-associated cancers. Furthermore, we observed transcriptional defects of the BARTs miRNA by deletion, and the disruption of host NHEJ1 by integrated EBV fragment, implying novel pathogenic mechanisms of EBV. Taken together, we reported for the first time global mutational and transcriptional profiles of EBV in NKTCL clinical samples, revealing important somatic events of EBV and providing insights to better understanding of EBV's contribution in tumorigenesis.