Comparative investigation of neoadjuvant immunotherapy versus adjuvant immunotherapy in perioperative patients with cancer: a global-scale, cross-sectional, large-sample informatics study.

BACKGROUND: Neoadjuvant and adjuvant immunotherapies for cancer have evolved through a series of remarkable and critical research advances; however, addressing their similarities and differences is imperative in clinical practice. Therefore, this study aimed to examine their similarities and differences from the perspective of informatics analysis. METHODS: This cross-sectional study retrospectively analyzed extensive relevant studies published between 2014 and 2023 using stringent search criteria, excluding non-peer-reviewed and non-English documents. The main outcome variables are publication volume, citation volume, connection strength, occurrence frequency, relevance percentage, and development percentage. Furthermore, an integrated comparative analysis was conducted using unsupervised hierarchical clustering, spatiotemporal analysis, regression statistics, and Walktrap algorithm analysis. RESULTS: This analysis included 1,373 relevant studies. Advancements in neoadjuvant and adjuvant immunotherapies have been promising over the last decade, with an annual growth rate of 25.18% vs. 6.52% and global collaboration (International Co-authorships) of 19.93% vs. 19.84%. Respectively, five dominant research clusters were identified through unsupervised hierarchical clustering based on machine learning, among which Cluster 4 (Balance of neoadjuvant immunotherapy efficacy and safety) and Cluster 2 (Adjuvant immunotherapy clinical trials) (Average Publication Year [APY]: 2021.70±0.70 vs. 2017.54±4.59) are emerging research populations. Burst and regression curve analyses uncovered domain pivotal research signatures, including microsatellite instability (R2=0.7500, P=0.0025) and biomarkers (R2=0.6505, P=0.0086) in neoadjuvant scenarios, and the tumor microenvironment (R2=0.5571, P=0.0209) in adjuvant scenarios. The Walktrap algorithm further revealed that "neoadjuvant immunotherapy, non-small cell lung cancer (NSCLC), immune checkpoint inhibitors, melanoma" and "adjuvant immunotherapy, melanoma, hepatocellular carcinoma, dendritic cells" (Relevance Percentage: 100% vs. 100%, Development Percentage: 37.5% vs. 17.1%) are extremely relevant to this field but remain underdeveloped, highlighting the need for further investigation. CONCLUSION: This study identified pivotal research signatures and provided substantial predictions for neoadjuvant and adjuvant cancer immunotherapies. In addition, comprehensive quantitative comparisons revealed a notable shift in focus within this field, with neoadjuvant immunotherapy taking precedence over adjuvant immunotherapy after 2020; such a qualitative finding facilitate proper decision-making for subsequent research and mitigate the wastage of healthcare resources.

Global research hotspots, development trends and prospect discoveries of phase separation in cancer: a decade-long informatics investigation.

Liquid-liquid phase separation (LLPS) is a complex and subtle phenomenon whose formation and regulation take essential roles in cancer initiation, growth, progression, invasion, and metastasis. This domain holds a wealth of underutilized unstructured data that needs further excavation for potentially valuable information. Therefore, we retrospectively analyzed the global scientific knowledge in the field over the last decade by using informatics methods (such as hierarchical clustering, regression statistics, hotspot burst, and Walktrap algorithm analysis). Over the past decade, this area enjoyed a favorable development trend (Annual Growth Rate: 34.98%) and global collaboration (International Co-authorship: 27.31%). Through unsupervised hierarchical clustering based on machine learning, the global research hotspots were divided into five dominant research clusters: Cluster 1 (Effects and Mechanisms of Phase Separation in Drug Delivery), Cluster 2 (Phase Separation in Gene Expression Regulation), Cluster 3 (Phase Separation in RNA-Protein Interaction), Cluster 4 (Reference Value of Phase Separation in Neurodegenerative Diseases for Cancer Research), and Cluster 5 (Roles and Mechanisms of Phase Separation). And further time-series analysis revealed that Cluster 5 is the emerging research cluster. In addition, results from the regression curve and hotspot burst analysis point in unison to super-enhancer (a=0.5515, R2=0.6586, p=0.0044) and stress granule (a=0.8000, R2=0.6000, p=0.0085) as the most potential star molecule in this field. More interestingly, the Random-Walk-Strategy-based Walktrap algorithm further revealed that "phase separation, cancer, transcription, super-enhancer, epigenetics"(Relevance Percentage[RP]=100%, Development Percentage[DP]=29.2%), "stress granule, immunotherapy, tumor microenvironment, RNA binding protein"(RP=79.2%, DP=33.3%) and "nanoparticle, apoptosis"(RP=70.8%, DP=25.0%) are closely associated with this field, but are still under-developed and worthy of further exploration. In conclusion, this study profiled the global scientific landscape, discovered a crucial emerging research cluster, identified several pivotal research molecules, and predicted several crucial but still under-developed directions that deserve further research, providing an important reference value for subsequent basic and clinical research of phase separation in cancer.

First-line sintilimab with pegaspargase, gemcitabine, and oxaliplatin in advanced extranodal natural killer/T cell lymphoma (SPIRIT): a multicentre, single-arm, phase 2 trial.

BACKGROUND: Programmed cell death protein 1 (PD-1) inhibitor sintilimab is effective in relapsed and refractory extranodal natural killer/T cell lymphoma (ENKTL), nasal type. We aimed to assess the safety and activity of sintilimab plus P-GEMOX (pegaspargase, gemcitabine, and oxaliplatin) in the first-line setting for advanced ENKTL. METHODS: The multicentre, single-arm, phase 2 trial was done at three medical centres in China. Patients aged 18-75 years with treatment-naive pathologically confirmed advanced ENKTL and an with Eastern Cooperative Oncology Group performance status score of 0-2 were eligible. Patients received intravenous sintilimab (200 mg on day 1), intramuscular pegaspargase (2000 U/m2 on day 1), intravenous gemcitabine (1 g/m2 on days 1 and 8), and intravenous oxaliplatin (130 mg/m2 on day 1) every 3 weeks for six cycles, followed by intravenous sintilimab (200 mg) every 3 weeks for up to 2 years or until disease progression or unacceptable toxicities. The primary endpoint was the complete response rate in the intention-to-treat population. The secondary endpoints were overall response rate (ORR), progression-free survival (PFS), disease-free survival (DFS), and overall survival. This trial is registered with ClinicalTrials.gov, NCT04127227. Enrolment has been completed, and follow-up is ongoing. FINDINGS: Between Nov 29, 2019, and Sept 7, 2022, 34 eligible patients were enrolled (median age 39 years [IQR 32-55]; 25 [74%] of 34 patients were male; nine [26%] were female; and all were of Asian ethnicity). At the data cutoff (July 20, 2023), the median follow-up was 21 months (IQR 13-32). The complete response rate was 85% (29 of 34 patients, 95% CI 70-94). Five patients (15%; 95% CI 7-30) attained partial response and the ORR was 100% (34 of 34 patients). 24-month PFS was 64% (95% CI 48-86), 24-month DFS was 72% (54-95), and 36-month overall survival was 76% (52-100). The most common grade 3 or 4 treatment-related adverse events were neutropenia (17 [50%] of 34 patients), anaemia (10 [29%] patients), and hypertriglyceridemia (10 [29%] patients). Hypothyroidism was the most frequent immune-related adverse event (18 [53%]), including grade 3 hypothyroidism in one (3%) patient that caused treatment termination. No severe adverse events occurred. There were three deaths: one due to haemophagocytic syndrome, one due to disease progression, and one due to unknown cause, which were not considered to be treatment related. INTERPRETATION: Combination of sintilimab with P-GEMOX seems to be an active and safe first-line regimen for patients with advanced ENKTL. FUNDING: National Key Research and Development Program and National Natural Science Foundation of China, Guangzhou Science and Technology Program and the Clinical Oncology Foundation of Chinese Society of Clinical Oncology.

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

Background: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented. Methods: After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism. Results: The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism. Conclusion: This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.

Novel target and treatment agents for natural killer/T-cell lymphoma.

The rapidly increasing use of high-throughput screening had produced a plethora of expanding knowledge on the molecular basis of natural killer/T-cell lymphoma (NKTCL), which in turn has revolutionized the treatment. Specifically, the use of asparaginase-containing regimens has led to substantial improvement in survival outcomes in NKTCL patients. Novel treatment strategies that are currently under development include cell-surface-targeted antibodies, immune checkpoint inhibitors, Epstein-Barr virus targeted cytotoxic T lymphocyte, immunomodulatory agents, chimeric antigen receptor T cells, signaling pathway inhibitors and epigenetic targeted agents. In almost all cases, initial clinical studies of newly developed treatment are conducted in patients relapsed, and refractory NKTCL due to very limited treatment options. This review summarizes the results of these novel treatments for NKTCL and discusses their potential for likely use in NKTCL in a wider setting in the future.

A scientometrics and visualization analysis of oxidative stress modulator Nrf2 in cancer profiles its characteristics and reveals its association with immune response.

Background: Nrf2, an essential and fascinating transcription factor, enjoys a dual property in the occurrence and development of inflammation and cancer. For over two decades, numerous studies regarding Nrf2 in cancer have been reported, whereas there is still a lack of a scientometrics and visualization analysis of Nrf2 in cancer. Hence, a scientometric study regarding the oxidative stress modulator Nrf2 was implemented. Methods: After the quality screening, we defined 7168 relevant studies from 2000 to 2021. CiteSpace, VOSviewer, R software, and GraphPad Prism were used for the following scientometric study and visualization analysis, including field profiles, research hotspots, and future predictions. Results: The total number of publications and citations are 1058 and 54,690, respectively. After polynomial fitting curve analysis, two prediction functions of the annual publication number (y = 3.3909x2 - 13585x + 1 E+07) and citation number (185.45x2 - 743669x + 7 E+08) were generated. After scientometric analysis, we found that Biochemistry Molecular Biology correlates with Nrf2 in cancer highly, and Free Radical Biology and Medicine is a good choice for submitting Nrf2-related manuscripts. The current research hotspots of Nrf2 in cancer mainly focus on cancer therapy and its cellular and molecular mechanisms. "antioxidant response element (87.5)", "gene expression (43.98)", "antioxidant responsive element (21.14)", "chemoprevention (20.05)", "carcinogenesis (19.2)", "cancer chemoprevention (18.45)", "free radical (17.15)", "response element (14.17)", and "chemopreventive agent (14.04)" are important for cancer therapy study. In addition, "glutathione-S-transferase (47)", "keap1 (15.39)", and "heme oxygenase 1 gene (24.35)" are important for inflammation and cell fate study. More interestingly, by performing an "InfoMap" algorithm, the thematic map showed that the "immune response" is essential to oxidative stress modulator Nrf2 but not well developed, indicating it deserves further exploration. Conclusion: This study revealed field profiles, research hotspots, and future directions of oxidative stress modulator Nrf2 in inflammation and cancer research, and our findings will offer a vigorous roadmap for further studies in this field.

PHB promotes bladder cancer cell epithelial-mesenchymal transition via the Wnt/ß-catenin signaling pathway.

As a member of PHB (prohibitin1) family, PHB plays important roles in many cancers, but its property in bladder carcinoma aggressiveness is unknown. This research was to explore the function and potential mechanism of PHB in bladder carcinoma in vivo and in vitro. The invasive abilities of cancer cell were determined by transwell and wound-healing assays. The function of PHB was confirmed by gene knockdown and overexpression methods. Further in vivo confirmation was performed in a nude mouse model with lung metastasis. The relationship of PHB and ß-catenin was confirmed by immunoprecipitation and immunofluorescence staining assays. The protein expression of epithelial-mescenchymal transition (EMT) and Wnt/ß-catenin signaling pathway was tested by immunofluorescence staining and western blotting assay. The depletion of PHB prevented bladder cancer cell invasiveness and inhibited EMT. Contrarily，the abilities of bladder carcinoma cells migration and invasion in vitro as well as metastasis in vivo were enhanced when the PHB overexpressed unnormally. Importantly, the ß-catenin was identified to be bound by PHB and ß-catenin knockdown reduced the cancer cell migration, invasion and EMT in PHB overexpressing cells. In addition, PHB stabilized ß-catenin by inhibiting its ubiqutin-mediated degradation thus leading to increased Wnt/ß-catenin signaling. These observations indicate that PHB could promote bladder cancer aggressiveness by binding with ß-catenin to prevent the degradation of ß-catenin and the localized invasive bladder cancer patients with PHB overexpression should take more aggressive postsurgical adjuvant anticancer therapies.

The ß-catenin-LINC00183-miR-371b-5p-Smad2/LEF1 axis promotes adult T-cell lymphoblastic lymphoma progression and chemoresistance.

BACKGROUND: High-intensity chemotherapy regimens are often used in adult T-cell lymphoblastic lymphoma (T-LBL) patients. Nevertheless, the response rate remains unsatisfactory due to emergence of chemoresistance. Growing evidence has shown that long non-coding RNAs (lncRNAs) are involved in tumor progression and chemoresistance. Herein, we investigated the potential role of lncRNAs in T-LBLs. METHODS: RNAseq was used to screen and identify candidate lncRNAs associated with T-LBL progression and chemoresistance. Luciferase reporter assay was used to examine the binding of miR-371b-5p to the 3'UTR of Smad2 and LEF1, and the binding of TCF-4/LEF1 to the promoter of LINC00183. Chromatin immunoprecipitation assay was undertaken to analyze the connection between LEF1 and the LINC00183 promoter region. RNA immunoprecipitation assays were used to explore the mechanism whereby LINC00183 regulated miR-371b-5p. MTT and flow cytometry assays were used to measure apoptosis of T-LBL cells. RESULTS: LINC00183 was upregulated in T-LBL progression and chemoresistant tissues in both the Sun Yat-sen University Cancer Center dataset and the First Affiliated Hospital of Anhui Medical University dataset. High expression of LINC00183 was correlated with poorer overall survival and progression-free survival of T-LBL patients compared to those with low expression of LINC00183. Furthermore, miR-371b-5p was negatively regulated by LINC00183. In vivo and in vitro assays showed that LINC00183-mediated T-LBL chemoresistance depended on miR-371b-5p expression. The direct binding of miR-371b-5p to Smad2 and LEF1 was verified by luciferase assays. It was shown that TCF4/LEF1 could bind to the LINC00183 promoter site and increase its transcript level. Downregulation of miR-371b-5p led to increased expression of Smad2/LEF1, and in turn increased LINC00183 expression. Additionally, phospho-Smad2 promotes nuclear translocation of ß-catenin, LINC00183 downregulation decreased chemoresistance induced by ß-catenin and TGF-ß1 in T-LBL cells. CONCLUSION: We unraveled a ß-catenin-LINC00183-miR-371b-5p-Smad2/LEF1 feedback loop that promotes T-LBL progression and chemoresistance, indicating that LINC00183 may serve as a potential therapeutic target in T-LBLs.

Diagnostic performance and prognostic value of circulating tumor DNA methylation marker in extranodal natural killer/T cell lymphoma.

Circulating tumor DNA (ctDNA) carries tumor-specific genetic and epigenetic variations. To identify extranodal natural killer/T cell lymphoma (ENKTL)-specific methylation markers and establish a diagnostic and prognosis prediction model for ENKTL, we describe the ENKTL-specific ctDNA methylation patterns by analyzing the methylation profiles of ENKTL plasma samples. We construct a diagnostic prediction model based on ctDNA methylation markers with both high specificity and sensitivity and close relevance to tumor staging and therapeutic response. Subsequently, we built a prognostic prediction model showing excellent performance, and its predictive accuracy is significantly better than the Ann Arbor staging and prognostic index of natural killer lymphoma (PINK) risk system. Notably, we further establish a PINK-C risk grading system to select individualized treatment for patients with different prognostic risks. In conclusion, these results suggest that ctDNA methylation markers are of great value in diagnosis, monitoring, and prognosis, which might have implications for clinical decision-making of patients with ENKTL.

Comprehensive analysis of tumor necrosis factor-α-inducible protein 8-like 2 (TIPE2): A potential novel pan-cancer immune checkpoint.

Tumor necrosis factor-α-inducible protein 8-like 2 (TIPE2) is encoded by TNFAIP8L2 and is a newly identified negative regulator of natural and acquired immunity that plays a critical function in maintaining immune homeostasis. Recently, CAR-NK immune cell therapy has been a focus of major research efforts as a novel cancer therapeutic strategy. TIPE2 is a potential checkpoint molecule for immune cell maturation and antitumor immunity that could be used as a novel NK cell-based immunotherapeutic approach. In this study, we explored the expression of TNFAIP8L2 across various tumor types and found that TNFAIP8L2 was highly expressed in most tumor types and correlated with prognosis. Survival analysis showed that TNFAIP8L2 expression was predictive of improved survival in cervical-squamous-cell-carcinoma (CESC), sarcoma (SARC) and skin-cutaneous-melanoma (SKCM). Conversely, TNFAIP8L2 expression predicted poorer survival in acute myeloid leukemia (LAML), lower-grade-glioma (LGG), kidney-renal-clear-cell-carcinoma (KIRC) and uveal-melanoma (UVM). Analysis of stemness features and immune cell infiltration indicated that TNFAIP8L2 was significantly associated with cancer stem cell index and increased macrophage and dendritic cell infiltration. Our data suggest that TNFAIP8L2 may be a novel immune checkpoint biomarker across different tumor types, particularly in LAML, LGG, KIRC and UVM, and may have further utility as a potential target for immunotherapy.

Efficacy and safety of decitabine combined with HAAG (homoharringtonine, aclarubicin, low-dose cytarabine and G-CSF) for newly diagnosed acute myeloid leukemia.

The 7 + 3 regimen is the front-line induction chemotherapy in patients with newly diagnosed acute myeloid leukemia, with a response rate of 60-80%. But it's not suitable for all patients especially old/unfit patients because of a higher treatment related toxicity. Therefore, safer and more effective induction therapies are required. In this retrospective study, 50 patients with newly diagnosed acute myeloid leukemia received decitabine combined with HAAG (homoharringtonine, aclarubicin, low-dose cytarabine and G-CSF) as induction chemotherapy. Complete remission (CR) rate was 96% (48/50) and overall response rate was 100%. Of note, All 7 patients harboring FLT3-ITD mutation achieved CR. The median overall survival (OS) was 40.0 months (range 2.0, 58.0). The OS at 1, 3, and 5 years were 75.3%, 54.2%, and 49.3%. The median relapse free survival (RFS) was 38.0 months (range 2.0, 58.0). The RFS at 1, 3, and 5 years were 67.3%, 48.9%, and 45.1%. The OS and RFS of patients who received hematopoietic stem cell transplantation (HSCT) were significantly higher than those who did not undergo HSCT (p=0.017; 0.016). The incidence of grade 3-4 neutropenia and thrombocytopenia was 84% and 88%. Meanwhile, the incidence of grade 3-4 infection and bleeding was only 16% and 6%. There was no early death. In conclusion, DAC+HAAG regimen is effective and well-tolerated as induction therapy in patients with newly diagnosed AML.

Mechanism of Abnormal Coagulation Induced by Tigecycline in Cancer Patients.

Tigecycline is a broad-spectrum active intravenous antibiotic that is active against methicillin-resistant staphylococcus aureus. In Phase 3 and 4 clinical trials, increased all-cause mortality was observed in patients treated with tigecycline compared to patients in the control group. The reason for the increase is unclear. In this study, we found that tigecycline cause abnormal coagulation in tumor patients, especially in patients with hematological malignancies. The main manifestations were decreased fibrinogen and prolonged activated prothrombin time (APTT), thrombin time (TT), and D-dimer. In addition, through functional studies, we found that tigecycline inhibit platelet adhesion and aggregation, and the coagulation function of patients gradually recover after discontinuation. Gene sequencing results suggested that tigecycline significantly regulate the expression of genes related to platelet function pathways and increase the incidence of single nucleotide polymorphisms and the number of alternative splices in the Chinese hamster ovary (CHO) cells treated with tigecycline. An abnormal function and low numbers of platelets are common in patients with hematological malignancies. Our study can explain the mechanism of abnormal coagulation caused by tigecycline. Additionally, doctors who apply tigecycline to cure infections in tumor patients should be warned.

Erratum: Acidic Microenvironment Up-Regulates Exosomal miR-21 and miR-10b in Early-Stage Hepatocellular Carcinoma to Promote Cancer Cell Proliferation and Metastasis: Erratum.

[This corrects the article DOI: 10.7150/thno.30958.].

A prognostic immune risk score for diffuse large B-cell lymphoma.

We constructed a prognostic score for persons with diffuse large B-cell lymphoma (DLBCL) based on infiltrating immune cells. Data of 956 consecutive subjects were retrieved from the Gene Expression Omnibus database and assigned to training (GSE10846, n = 305) or validation (GSE87371 n = 206 and GSE117556 n = 445 combined) cohorts. Proportions of non-lymphoma cells in the sample were inferred using the ESTIMATE algorithm. An immune risk score was constructed comprised of eight types of non-lymphoma immune cells calculated using the CIBERSORT algorithm. Five-year survival of subjects with an immune risk score ≤ 0·45 in the training cohort was better than that of subjects with a score > 0·45 (hazard ratio [HR] = 3·99; 95% confidence interval [CI] = 2·74, 5·82; P < 0·001). HR in the validation cohort was HR = 2·17 (1·47, 3·21; P < 0·001). Enrichment analyses indicated correlations with genes controlling immune-related biological processes and pathways. A nomogram comprised of the immune risk score and most covariates including age, lactate dehydrogenase concentration (LDH), lymphoma-type (germinal centre B cell [GCB] versus non-GCB), Eastern Cooperative Oncology Group performance status (ECOG-PS) and rituximab therapy had a C-statistic of 0·76 compared with C-statistics of 0·69 and 0·69 for the International Prognostic Index (IPI) and Revised International Prognostic Index (R-IPI). These data indicate the immune risk score is an accurate, independent survival predictor in persons with DLBCL.

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.

The ß-catenin/TCF-4-LINC01278-miR-1258-Smad2/3 axis promotes hepatocellular carcinoma metastasis.

Hepatocellular carcinoma (HCC) metastasis is largely responsible for HCC-associated recurrence and mortality. We aimed to identify metastasis-related long non-coding RNAs (lncRNAs) to understand the molecular mechanism of HCC metastasis. We first identified that miR-1258 was downregulated in HCC tissues both in The Cancer Genome Atlas (TCGA) and Sun Yat-sen University Cancer Center (SYSUCC) dataset. MiR-1258 expression negatively correlated with recurrence-free survival and overall survival of HCC patients. MiR-1258 overexpression inhibited migration and invasion of HCC cells both in vitro and in vivo, whereas miR-1258 downregulation promoted cell metastasis. Luciferase assays verified direct binding of miR-1258 to Smad2 and Smad3, thereby attenuating TGF-ß/Smad signaling. We further established that lncRNA LINC01278 was a negative regulator of miR-1258. In vivo and in vitro assays demonstrated that LINC01278-mediated HCC metastasis was dependent on miR-1258 expression. Furthermore, miR-1258 downregulation in turn increased LINC01278 expression. We also observed that TCF-4 could bind to the LINC01278 promoter site. In addition, LINC01278 downregulation decreased migration and invasion of HCC cells induced by ß-catenin and TGF-ß1 both in vitro and in vivo. We uncovered a novel mechanism for ß-catenin/TCF-4-LINC01278-miR-1258-Smad2/3 feedback loop activation in HCC metastasis, and the study indicated that LINC01278 could serve as a therapeutic target for HCC metastasis.