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Natural killer/T-cell lymphoma (NKTCL) is a rare subtype of non-Hodgkin lymphoma that is associated with a poor outcome. Currently, the treatment needs of NKTCL remain unmet, and efforts to further improve treatment are urgently needed. Herein, seven patients with NKTCL who failed to respond to various types of chemotherapies were treated with the anti-programmed death 1 (anti-PD-1) antibody pembrolizumab at 100 mg every 3 weeks. After a median of four cycles of treatment (range 2–18), four out of seven patients responded (two complete response, two partial response, overall response rate 57%). Expression of PD1-ligand available was 50, 20, 30, 70, and 30% of five patients respectively. It is negative in one patient and not tested in one patient. Adverse events, which mostly ranged from grade I to grade III, were tolerable and could be safely handled, although immune-related pneumonitis was notable. Overall, PD-1 blockade with pembrolizumab represents a favorable strategy for the treatment of refractory/relapsed NKTCL.

DDGP chemotherapy resulted in significant improvement in PFS, OS, and better tolerability compared with SMILE chemotherapy for newly diagnosed advanced NK/T-cell lymphoma patients. Clin Cancer Res; 22(21); 5223-8. ©2016 AACR.

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IMPORTANCEThe L-asparaginase-based SMILE (dexamethasone, methotrexate, ifosfamide, L-asparaginase, and etoposide) chemotherapy regimen has shown higher response rates and survival benefit over an anthracycline-containing regimen. However, the safety profile was not satisfied. A well-tolerated regimen with promising efficacy is lacking.OBJECTIVE To compare the efficacy and safety of the DDGP (dexamethasone, cisplatin, gemcitabine, and pegaspargase) regimen with the SMILE regimen in newly diagnosed advanced-stage (III/IV) extranodal natural killer/T-cell lymphoma (ENKL). DESIGN, SETTING, AND PARTICIPANTSThis was an open-label, multicenter, randomized clinical trial that took place across 12 participating hospitals in China from January 2011 to February 2019. Patients were eligible if they were 14 to 70 years old with newly diagnosed ENKL in stages III/IV and had an Eastern Cooperative Oncology Group performance status of 0 to 2. Eligible patients were evenly randomized to either the DDGP or SMILE group.INTERVENTIONS Patients in each group were treated with the assigned regimen every 21 days for 6 cycles. MAIN OUTCOMES AND MEASURESThe primary end point was progression-free survival (PFS), and secondary end points included overall response rate and overall survival (OS). The adverse events between the DDGP and SMILE groups were compared. RESULTS Among the 87 randomized patients, 80 received treatment (40 in the DDGP group and 40 in the SMILE group); the median (IQR) age was 43 (12) years, and 51 (64%) were male. The baseline characteristics were similar between the groups. At a median follow-up of 41.5 months, the median PFS was not reached in the DDGP group vs 6.8 months in the SMILE group (HR, 0.42; 95% CI, 0.23-0.77; P = .004), and the median OS was not reached in the DDGP group vs 75.2 months in the SMILE group (HR, 0.41; 95% CI, 0.19-0.89, P = .02). The PFS rate at 3 years and OS rate at 5 years were higher in the DDGP group vs the SMILE group (3-year PFS, 56.6% vs 41.8%; 5-year OS, 74.3% vs 51.7%). The overall response rate was higher in the DDGP group than in the SMILE group (90.0% vs 60.0%; P = .002). Grade 3 and 4 hematologic toxic effects were more frequently reported in the SMILE group vs the DDGP group (leukopenia, 85.0% vs 62.5%; neutropenia, 85.0% vs 65.0%). CONCLUSIONS AND RELEVANCEIn this randomized clinical trial, the DDGP regimen showed promising preliminary results for patients with newly diagnosed local advanced ENKL. A confirmation trial based on larger population is warranted.

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with poor prognosis. And different individuals respond to the same drug differently. Increasing evidence has confirmed that metabolism reprogramming was involved in the drug sensitivity of tumor cells. However, the potential molecular mechanism of 5‐fluorouracil (5‐FU) sensitivity remains to be elucidated in ESCC cells. In this study, we found that the 5‐FU sensitivity of TE1 cells was lower than that of EC1 and Eca109 cells. Gas chromatography‐mass spectrometry analysis results showed that nicotinate and nicotinamide metabolism and tricarboxylic acid cycle were significantly different in these three cell lines. Nicotinamide N‐methyltransferase (NNMT), a key enzyme of nicotinate and nicotinamide metabolism, was significantly higher expressed in TE1 cells than that in EC1 and Eca109 cells. Therefore, the function of NNMT on 5‐FU sensitivity was analyzed in vitro and in vivo. NNMT downregulation significantly increased 5‐FU sensitivity in TE1 cells. Meanwhile, the glucose consumption and lactate production were decreased, and the expression of glycolysis‐related enzymes hexokinase 2, lactate dehydrogenase A, and phosphoglycerate mutase 1 were downregulated in NNMT knockdown TE1 cells. Besides, overexpression of NNMT in EC1 and Eca109 cells caused the opposite effects. Moreover, when glycolysis was inhibited by 2‐deoxyglucose, the roles of NNMT on 5‐FU sensitivity was weakened. In vivo experiments showed that NNMT knockdown significantly increased the sensitivity of xenografts to 5‐FU and suppressed the Warburg effect. Overall, these results demonstrated that NNMT decreases 5‐FU sensitivity in human ESCC cells through promoting the Warburg effect, suggesting that NNMT may contribute to predict the treatment effects of the clinical chemotherapy in ESCC.

The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to develop machine learning models for predicting MB molecular subgroups based on multi-parameter magnetic resonance imaging (MRI) radiomics, tumor locations, and clinical factors. A total of 122 MB patients were enrolled retrospectively. After selecting robust, non-redundant, and relevant features from 5,529 extracted radiomics features, a random forest model was constructed based on a training cohort ( n = 92) and evaluated on a testing cohort ( n = 30). By combining radiographic features and clinical parameters, two combined prediction models were also built. The subgroup can be classified using an 11-feature radiomics model with a high area under the curve (AUC) of 0.8264 for WNT and modest AUCs of 0.6683, 0.6004, and 0.6979 for SHH, Group 3, and Group 4 in the testing cohort, respectively. Incorporating location and hydrocephalus into the radiomics model resulted in improved AUCs of 0.8403 and 0.8317 for WNT and SHH, respectively. After adding gender and age, the AUCs for WNT and SHH were further improved to 0.9097 and 0.8654, while the accuracies were 70 and 86.67% for Group 3 and Group 4, respectively. Prediction performance was excellent for WNT and SHH, while that for Group 3 and Group 4 needs further improvements. Machine learning algorithms offer potentials to non-invasively predict the molecular subgroups of MB.