A genomic-augmented multivariate prognostic model for the survival of natural-killer/T-cell lymphoma patients from an international cohort.

With lowering costs of sequencing and genetic profiling techniques, genetic drivers can now be detected readily in tumors but current prognostic models for Natural-killer/T cell lymphoma (NKTCL) have yet to fully leverage on them for prognosticating patients. Here, we used next-generation sequencing to sequence 260 NKTCL tumors, and trained a genomic prognostic model (GPM) with the genomic mutations and survival data from this retrospective cohort of patients using LASSO Cox regression. The GPM is defined by the mutational status of 13 prognostic genes and is weakly correlated with the risk-features in International Prognostic Index (IPI), Prognostic Index for Natural-Killer cell lymphoma (PINK), and PINK-Epstein-Barr virus (PINK-E). Cox-proportional hazard multivariate regression also showed that the new GPM is independent and significant for both progression-free survival (PFS, HR: 3.73, 95% CI 2.07-6.73; p < .001) and overall survival (OS, HR: 5.23, 95% CI 2.57-10.65; p = .001) with known risk-features of these indices. When we assign an additional risk-score to samples, which are mutant for the GPM, the Harrell's C-indices of GPM-augmented IPI, PINK, and PINK-E improved significantly (p < .001, χ2 test) for both PFS and OS. Thus, we report on how genomic mutational information could steer toward better prognostication of NKTCL patients.

A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma.

Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision making. Data from 722 patients with ENKTL from international centers were analyzed. A 7-SNP-based classifier was constructed using LASSO Cox regression in the training cohort (n = 336) and further validated in the internal testing cohort (n = 144) and in 2 external validation cohorts (n = 142 and n = 100). The 7-SNP-based classifier showed good prognostic predictive efficacy in the training cohort and the 3 validation cohorts. Patients with high- and low-risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all P < .001). The 7-SNP-based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. Application of the 7-SNP-based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significantly improved PFS and OS vs radiotherapy alone in high-risk Ann Arbor stage I patients, whereas there was no statistical difference between the 2 therapeutic modalities among low-risk patients. A nomogram was constructed comprising the classifier and clinicopathological variables; it showed remarkably better predictive accuracy than either variable alone. The 7-SNP-based classifier is a complement to existing risk-stratification systems in ENKTL, which could have significant implications for clinical decision making for patients with ENKTL.

Evaluation of the PIK3 pathway in peripheral T-cell lymphoma and NK/T-cell lymphoma.

Peripheral T-cell lymphomas (PTCL) and natural killer (NK)/T-cell lymphomas (NKTCL) are a heterogeneous group of aggressive malignancies with dismal outcomes and limited treatment options. While the phosphatidylinositol 3-kinase (PIK3) pathway has been shown to be highly activated in many B-cell lymphomas, its therapeutic relevance in PTCL and NKTCL remains unclear. The aim of this study is to investigate the expression of PIK3 and phosphatase and tensin homolog (PTEN) in these subtypes of lymphoma and to identify potential therapeutic targets for clinical testing. Therefore, the expression of PIK3α, PIK3ß, PIK3γ, PIK3δ and PTEN was analyzed in 88 cases of PTCL and NKTCL samples by immunohistochemistry. All PTCL and NKTCL samples demonstrated high expression of PIK3 isoforms. In particular, high PIK3α expression was significantly associated with poor survival, even after adjustment for age, International Prognostic Index (IPI) score and anthracycline-based chemotherapy in first line. Notably, copanlisib, a pan-class I inhibitor with predominant activities towards PIK3α and PIK3δ isoforms, effectively inhibited phosphorylation of AKT, 4E-BP-1 and STAT3, causing G0 /G1 cell cycle arrest and resulting in suppression of tumour cell growth in vitro and in vivo. This study provides evidence that targeting the PIK3 pathway, particularly simultaneous inhibition of PIK3α and δ, could be a promising approach for the treatment of PTCL and NKTCL.

Oncogenic activation of the STAT3 pathway drives PD-L1 expression in natural killer/T-cell lymphoma.

Mature T-cell lymphomas, including peripheral T-cell lymphoma (PTCL) and extranodal NK/T-cell lymphoma (NKTL), represent a heterogeneous group of non-Hodgkin lymphomas with dismal outcomes and limited treatment options. To determine the extent of involvement of the JAK/STAT pathway in this malignancy, we performed targeted capture sequencing of 188 genes in this pathway in 171 PTCL and NKTL cases. A total of 272 nonsynonymous somatic mutations in 101 genes were identified in 73% of the samples, including 258 single-nucleotide variants and 14 insertions or deletions. Recurrent mutations were most frequently located in STAT3 and TP53 (15%), followed by JAK3 and JAK1 (6%) and SOCS1 (4%). A high prevalence of STAT3 mutation (21%) was observed specifically in NKTL. Novel STAT3 mutations (p.D427H, E616G, p.E616K, and p.E696K) were shown to increase STAT3 phosphorylation and transcriptional activity of STAT3 in the absence of cytokine, in which p.E616K induced programmed cell death-ligand 1 (PD-L1) expression by robust binding of activated STAT3 to the PD-L1 gene promoter. Consistent with these findings, PD-L1 was overexpressed in NKTL cell lines harboring hotspot STAT3 mutations, and similar findings were observed by the overexpression of p.E616K and p.E616G in the STAT3 wild-type NKTL cell line. Conversely, STAT3 silencing and inhibition decreased PD-L1 expression in STAT3 mutant NKTL cell lines. In NKTL tumors, STAT3 activation correlated significantly with PD-L1 expression. We demonstrated that STAT3 activation confers high PD-L1 expression, which may promote tumor immune evasion. The combination of PD-1/PD-L1 antibodies and STAT3 inhibitors might be a promising therapeutic approach for NKTL, and possibly PTCL.