UNASSIGNED: Among patients with nasopharyngeal carcinoma (NPC), there is no established method to distinguish between patients with residual disease that may eventually progress and those who have achieved cured. We thus aimed to assess the prognostic value of magnetic resonance imaging (MRI)-based lymph node regression grade (LRG) in the risk stratification of patients with NPC following radiotherapy (RT).
UNASSIGNED: This study retrospectively enrolled 387 patients newly diagnosed with NPC between January 2010 and January 2013. A four-category MRI-LRG system based on the areal analysis of RT-induced fibrosis and residual tumor was established. Univariate analysis was performed using the Kaplan-Meier method, and comparisons were conducted via the log-rank test. Multivariate analyses were conducted using Cox regression models to calculate the hazard ratios (HRs) with 95% confidence intervals (CIs) and adjusted P values. Survival curves were calculated using the Kaplan-Meier method and compared using the log-rank test.
UNASSIGNED: The sum of MRI-LRG scores (LRG-sum) was an independent prognostic factor for progression-free survival (PFS) (HR 2.50, 95% CI: 1.28-4.90; P<0.001). LRG-sum ≤9 and >9 showed a poorer 5-year PFS rate than did LRG-sum ≤2 (66.1%, 42.9%, and 77.6%, respectively; P<0.001). A survival clustering analysis-based decision tree model showed more complex interactions among LRG-sum and pretreatment and post-RT Epstein-Barr virus (EBV) DNA, yielding four patient clusters with differentiated disease progression risks (5-year PFS rates of 89.5%, 76.4%, 57.6%, and 27.8%, respectively), which showed better risk stratification than did post-RT EBV DNA alone (P<0.001).
UNASSIGNED: The MRI-LRG system adds prognostic information and is a potentially reliable, noninvasive means to stratify treatment modalities for patients with NPC.

BACKGROUND: Uncontrolled cellular proliferation may result in the progression of diseases such as cancer that promote organism death. Programmed cell death (PCD) is an important mechanism that ensures the quality and quantity of cells, which could be developed as a potential biomarker for disease diagnosis and treatment.
METHODS: RNA-seq data and clinical information of nasopharyngeal carcinoma (NPC) patients were downloaded from the Gene Expression Omnibus (GEO), and 1548 PCD-related genes were collected. We used the \"limma\" package to analyze differentially expressed genes (DEGs). The STRING database was used for protein interaction analysis, and the least absolute shrinkage and selection operator (Lasso) and support vector machines (SVMs) regression analyses were used to identify biomarkers. Then, the timeROC package was used for classifier efficiency assessment, and the \"CIBERSORT\" package was used for immune infiltration analysis. Wound healing and transwell migration assay were performed to evaluate migration and invasion.
RESULTS: We identified 800 DEGs between our control and NPC patient groups, in which 59 genes appeared to be PCD-related DEGs, with their function closely associated with NPC progression, including activation of the PI3K-Akt, TGF-β, and IL-17 signaling pathways. Furthermore, based on the STRING database, Cytoscape and six algorithms were employed to screen 16 important genes (GAPDH, FN1, IFNG, PTGS2, CXCL1, MYC, MUC1, LTF, S100A8, CAV1, CDK4, EZH2, AURKA, IL33, S100A9, and MIF). Subsequently, two reliably characterized biomarkers, FN1 and MUC1, were obtained from the Lasso and SVM analyses. The Receiver operating characteristic (ROC) curves showed that both biomarkers had area under the curve (AUC) values higher than 0.9. Meanwhile, the enrichment analysis showed that in NPC patients, the FN1 and MUC1 expression levels correlated with programmed cell death-related pathways. The enrichment analysis and cellular experimental results indicated that FN1 and MUC1 were overexpressed in NPC cells and associated with programmed cell death-related pathways. Importantly, FN1 and MUC1 severely affected the ability of NPC cells to migrate, invade, and undergo apoptosis. Finally, medroxyprogesterone acetate and 8-Bromo-cAMP acted as drug molecules for the docking of FN1 and MUC1 molecules, respectively, and had binding capacities of -9.17 and -7.27 kcal/mol, respectively.
CONCLUSIONS: We examined the PCD-related phenotypes and screened FN1 and MUC1 as reliable biomarkers of NPC; our findings may promote the development of NPC treatment strategy.

UNASSIGNED: Centromere protein U (CENPU) is key for mitosis in the carcinogenesis of cancers. However, the roles of CENPU have not been inspected in nasopharyngeal carcinoma (NPC). Thus, we aimed to explore the functions and mechanisms of CENPU in NPC.
UNASSIGNED: Expression of CENPU was evaluated by real-time quantitative polymerase chain reaction, western blotting and immunohistochemistry. The biological functions of CENPU were evaluated in vitro and in vivo. Gene chip analysis, ingenuity pathway analysis, and coimmunoprecipitation experiments were used to explore the mechanisms of CENPU.
UNASSIGNED: CENPU was highly expressed in NPC. High expression of CENPU was associated with advanced tumor, node and metastasis (TNM) stage and poor overall survival. Cox regression analysis demonstrated that CENPU expression was an independent prognostic factor in NPC. Knockdown of CENPU inhibited proliferation and migration in vitro and in vivo. Knockdown of CENPU upregulated dual specificity phosphatase 6 (DUSP6) expression. The expression of CNEPU was inversely correlated with the expression of DUSP6 in NPC tissues. Mechanistic studies confirmed that CENPU increased the activation of the ERK1/2 and p38 signaling pathways by suppressing the expression of DUSP6.
UNASSIGNED: CENPU acts as an oncogene in NPC by interacting with DUSP6, and may represent a promising prognostic biomarker for patients with NPC.

Transmembrane protein 52B (TMEM52B), a newly identified tumor-related gene, has been reported to regulate various tumors, yet its role in nasopharyngeal carcinoma (NPC) remains unclear. Transcriptomic analysis of NPC cell lines reveals frequent overexpression of TMEM52B, and immunohistochemical results show that TMEM52B is associated with advanced tumor stage, recurrence, and decreased survival time. Depleting TMEM52B inhibits the proliferation, migration, invasion, and oncogenesis of NPC cells in vivo. TMEM52B encodes two isoforms, TMEM52B-P18 and TMEM52B-P20, differing in their N-terminals. While both isoforms exhibit similar pro-oncogenic roles and contribute to drug resistance in NPC, TMEM52B-P20 differentially promotes metastasis. This functional discrepancy may be attributed to their distinct subcellular localization; TMEM52B-P18 is confined to the cytoplasm, while TMEM52B-P20 is found both at the cell membrane and in the cytoplasm. Mechanistically, cytoplasmic TMEM52B enhances AKT phosphorylation by interacting with phosphoglycerate kinase 1 (PGK1), fostering NPC growth and metastasis. Meanwhile, membrane-localized TMEM52B-P20 promotes E-cadherin ubiquitination and degradation by facilitating its interaction with the E3 ubiquitin ligase NEDD4, further driving NPC metastasis. In conclusion, the TMEM52B-P18 and TMEM52B-P20 isoforms promote the metastasis of NPC cells through different mechanisms. Drugs targeting these TMEM52B isoforms may offer therapeutic benefits to cancer patients with varying degrees of metastasis.

In patients with nasopharyngeal carcinoma (NPC), the alteration of immune responses in peripheral blood remains unclear. In this study, we established an immune cell profile for patients with NPC and used flow cytometry and machine learning (ML) to identify the characteristics of this profile. After isolation of circulating leukocytes, the proportions of 104 immune cell subsets were compared between NPC group and the healthy control group (HC). Data obtained from the immune cell profile were subjected to ML training to differentiate between the immune cell profiles of the NPC and HC groups. We observed that subjects in the NPC group presented higher proportions of T cells, memory B cells, short-lived plasma cells, IgG-positive B cells, regulatory T cells, MHC II+ T cells, CTLA4+ T cells and PD-1+ T cells than subjects in the HC group, indicating weaker and compromised cellular and humoral immune responses. ML revealed that monocytes, PD-1+ CD4 T cells, memory B cells, CTLA4+ CD4 Treg cells and PD-1+ CD8 T cells were strongly contributed to the difference in immune cell profiles between the NPC and HC groups. This alteration can be fundamental in developing novel immunotherapies for NPC.

Phospholipase D (PLD) lipid-signaling enzyme superfamily has been widely implicated in various human malignancies, but its role and underlying mechanism remain unclear in nasopharyngeal carcinoma (NPC). Here, we analyze the expressions of 6 PLD family members between 87 NPC and 10 control samples through transcriptome analysis. Our findings reveal a notable upregulation of PLD1 in both NPC tumors and cell lines, correlating with worse disease-free and overall survival in NPC patients. Functional assays further elucidate PLD1\'s oncogenic role, demonstrating its pivotal promotion of critical tumorigenic processes such as cell proliferation and migration in vitro, as well as tumor growth in vivo. Notably, our study uncovers a positive feedback loop between PLD1 and the NF-κB signaling pathway to render NPC progression. Specifically, PLD1 enhances NF-κB activity by facilitating the phosphorylation and nuclear translocation of RELA (p65), which in turn binds to the promoter of PLD1, augmenting its expression. Moreover, RELA overexpression significantly rescues the inhibitory effects in PLD1-depleted NPC cells. Importantly, the application of the PLD1 inhibitor, VU0155069, significantly inhibits NPC tumorigenesis in a patient-derived xenograft model. Together, our findings identify PLD1/NF-κB signaling as a positive feedback loop with promising therapeutic and prognostic potential in NPC.

UNASSIGNED: Different image modalities capture different aspects of a patient. It is desirable to produce images that capture all such features in a single image. This research investigates the potential of multi-modal image fusion method to enhance magnetic resonance imaging (MRI) tumor contrast and its consistency across different patients, which can capture both the anatomical structures and tumor contrast clearly in one image, making MRI-based target delineation more accurate and efficient.
UNASSIGNED: T1-weighted (T1-w) and T2-weighted (T2-w) magnetic resonance (MR) images from 80 nasopharyngeal carcinoma (NPC) patients were used. A novel image fusion method, Pixelwise Gradient Model for Image Fusion (PGMIF), which is based on the pixelwise gradient to capture the shape and a generative adversarial network (GAN) term to capture the image contrast, was introduced. PGMIF is compared with several popular fusion methods. The performance of fusion methods was quantified using two metrics: the tumor contrast-to-noise ratio (CNR), which aims to measure the contrast of the edges, and a Generalized Sobel Operator Analysis, which aims to measure the sharpness of edge.
UNASSIGNED: The PGMIF method yielded the highest CNR [median (mdn) =1.208, interquartile range (IQR) =1.175-1.381]. It was a statistically significant enhancement compared to both T1-w (mdn =1.044, IQR =0.957-1.042, P<5.60×10-4) and T2-w MR images (mdn =1.111, IQR =1.023-1.182, P<2.40×10-3), and outperformed other fusion models: Gradient Model with Maximum Comparison among Images (GMMCI) (mdn =0.967, IQR =0.795-0.982, P<5.60×10-4), Deep Learning Model with Weighted Loss (DLMWL) (mdn =0.883, IQR =0.832-0.943, P<5.60×10-4), Pixelwise Weighted Average (PWA) (mdn =0.875, IQR =0.806-0.972, P<5.60×10-4) and Maximum of Images (MoI) (mdn =0.863, IQR =0.823-0.991, P<5.60×10-4). In terms of the Generalized Sobel Operator Analysis, a measure based on Sobel operator to measure contrast enhancement, PGMIF again exhibited the highest Generalized Sobel Operator (mdn =0.594, IQR =0.579-0.607; mdn =0.692, IQR =0.651-0.718 for comparison with T1-w and T2-w images), compared to: GMMCI (mdn =0.491, IQR =0.458-0.507, P<5.60×10-4; mdn =0.495, IQR =0.487-0.533, P<5.60×10-4), DLMWL (mdn =0.292, IQR =0.248-0.317, P<5.60×10-4; mdn =0.191, IQR =0.179-0.243, P<5.60×10-4), PWA (mdn =0.423, IQR =0.383-0.455, P<5.60×10-4; mdn =0.448, IQR =0.414-0.463, P<5.60×10-4) and MoI (mdn =0.437, IQR =0.406-0.479, P<5.60×10-4; mdn =0.540, IQR =0.521-0.636, P<5.60×10-4), demonstrating superior contrast enhancement and sharpness compared to other methods.
UNASSIGNED: Based on the tumor CNR and Generalized Sobel Operator Analysis, the proposed PGMIF method demonstrated its capability of enhancing MRI tumor contrast while keeping the anatomical structures of the input images. It holds promises for NPC tumor delineation in radiotherapy.

BACKGROUND: Shyonaka (Oroxylum indicum Vent) is widely used in Ayurveda and in ethnomedical practice for the treatment of inflammation, pain, diarrhea, non-healing ulcers, and cancer. Owing to the high prevalence of Epstein-Barr virus (EBV) infection in Nasopharyngeal carcinoma (NPC) patients, simultaneous targeting of proteins involved in both EBV replication and NPC proliferation might help to manage the disease effectively.
OBJECTIVE: This study is designed to identify potential dual targeting inhibitors from Oroxylum indicum having the potential to inhibit both EBV and NPC. This study also attempted quantitative analysis of Shyonaka Bark Decoction (SBD) to confirm the presence of Baicalein and Chrysin which are predominant marker compounds of Shyonaka.
METHODS: The HPLC analysis of stem bark and root bark of Oroxylum indicum was done to estimate the presence of marker compounds Baicalein and Chrysalin. The in-silico analysis included ADMET analysis followed by molecular docking of known compounds from Oroxylum indicum (retrieved from IMPPAT database) onto the target proteins of EBV (BHRF1, NEC1, dUTPase, Uracil DNA glycosylase) and NPC (COX-2, EGFR, and MDM2) using DOCK6 tool. Further validations were done using the molecular dynamics simulations of top screened molecules onto the selected target proteins using AMBER20 package and their corresponding MMGBSA binding free-energy values were calculated.
RESULTS: The molecular docking revealed that the key molecules from the plant, scutellarein 7-rutinoside (S7R), scutellarin (SCU) and 6-hydroxyluteolin, Baicalein and 5,7-Dihydroxy-2-phenyl-6-[3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2-yl]oxychromen-4-one (57D) are effectively intervening with the target proteins of EBV, one of the key causative factors of NPC and the NPC specific targets which have the potential to reduce tumor size and other consequences of NPC. The molecular dynamics simulations of S7R, Baicalein and 57D, Baicalein with MDM-2 protein and dUTPase protein, respectively, showed stable interactions between them which were further assessed by the binding energy calculations.
CONCLUSIONS: Overall, the in-silico evaluation of these phytochemicals with target proteins indicates their potential to inhibit both EBV and NPC which needs further in-vitro and in-vivo validations.

BACKGROUND: This study aimed to assess the long-term effect of level IIb clinical target volume (CTV) optimisation on survival, xerostomia, and dysphagia in patients with nasopharyngeal carcinoma (NPC).
METHODS: Clinical data of 415 patients with NPC treated with intensity-modulated radiotherapy between December 2014 and October 2018 were retrospectively analysed. The patients were categorised into modified and comparison groups. Late xerostomia and dysphagia were evaluated using Radiation Therapy Oncology Group/European Organisation for Research and Treatment of Cancer scoring. Survival analysis was performed using the Kaplan-Meier method. Differences in late toxicity and dose parameters between both groups were compared. Prognostic factors for survival and late toxicity were assessed using regression analyses.
RESULTS: Patients in the modified group developed late xerostomia and dysphagia less frequently than those in the comparison group did (P < 0.001). The mean dose (Dmean) and V26 of parotid glands; Dmean and V39 of submandibular glands; and Dmean of sublingual glands, oral cavity, larynx, and superior, middle, and lower pharyngeal constrictor muscles were lower in the modified group than those in the comparison group (all P < 0.001). Both groups had no significant differences in overall, local recurrence-free, distant metastasis-free, or progression-free survival. The Dmean of the parotid and sublingual glands was a risk factor for xerostomia. The Dmean of the parotid and sublingual glands and middle pharyngeal constrictor muscle was a risk factor for dysphagia.
CONCLUSIONS: Level IIb optimisation in NPC patients who meet certain criteria specially the exclusion of positive retropharyngeal nodes treated with intensity-modulated radiotherapy has the potential to better protect the salivary and swallowing structures, decreasing the development of late radiation-induced xerostomia and dysphagia while maintaining long-term survival.

Nasopharyngeal carcinoma is a significant health challenge that is particularly prevalent in Southeast Asia and North Africa. MRI is the preferred diagnostic tool for NPC due to its superior soft tissue contrast. The accurate segmentation of NPC in MRI is crucial for effective treatment planning and prognosis. We conducted a search across PubMed, Embase, and Web of Science from inception up to 20 March 2024, adhering to the PRISMA 2020 guidelines. Eligibility criteria focused on studies utilizing DL for NPC segmentation in adults via MRI. Data extraction and meta-analysis were conducted to evaluate the performance of DL models, primarily measured by Dice scores. We assessed methodological quality using the CLAIM and QUADAS-2 tools, and statistical analysis was performed using random effects models. The analysis incorporated 17 studies, demonstrating a pooled Dice score of 78% for DL models (95% confidence interval: 74% to 83%), indicating a moderate to high segmentation accuracy by DL models. Significant heterogeneity and publication bias were observed among the included studies. Our findings reveal that DL models, particularly convolutional neural networks, offer moderately accurate NPC segmentation in MRI. This advancement holds the potential for enhancing NPC management, necessitating further research toward integration into clinical practice.