Epstein–Barr virus (EBV) was the first oncogenic virus identified in humans. It is primarily associated with multiple lymphoid and epithelial cancers, including nasopharyngeal carcinoma (NPC). However, its association with ferroptosis and its role in cancer therapy resistance have not been fully elucidated. Here, we show that EBV infection reduces the sensitivity of NPC cells to ferroptosis by activating the p62-Keap1-NRF2 signaling pathway in conjunction with upregulation of SLC7A11 and GPX4 expression. Knockdown of endogenous GPX4 or blockade of GPX4 using a specific inhibitor enhanced the chemosensitivity of EBV-infected NPC cells. Functional studies revealed that GPX4 knockdown suppresses the proliferation and colony formation of NPC cells. Mechanistically, GPX4 interacts with the TAK1-TAB1/TAB3 complex, regulates TAK1 kinase activity, and further activates downstream MAPK-JNK and NFκB pathways. High GPX4 expression is correlated with poor clinical outcomes in patients with NPC and other cancer types. Taken together, our findings suggest that EBV infection has important effects on redox homeostasis, revealing a previously unappreciated role for GPX4 in tumor progression. This novel mechanism provides a potential new target for the treatment of EBV-related tumors.

Previous studies demonstrated that the radiation therapy, image technology, and the application of chemotherapy have developed in the last 2 decades. This study explored the survival trends and treatment failure patterns of patients with nonmetastatic nasopharyngeal carcinoma (NPC) treated with radiation therapy. Furthermore, we evaluated the survival benefit brought by the development of radiation therapy, image technology, and chemotherapy based on a large cohort from 1990 to 2012. Data from 20,305 patients with nonmetastatic NPC treated between 1990 and 2012 were analyzed. Patients were divided into 4 calendar periods (1990-1996, 1997-2002, 2003-2007, and 2008-2012). Overall survival (OS) was the primary endpoint. Magnetic resonance imaging has replaced computed tomography as the most important imaging technique since 2003. Conventional 2-dimensional radiation therapy, which was the main radiation therapy technique in our institution before 2008, was replaced by intensity modulated radiation therapy later. An increasing number of patients have undergone chemotherapy since 2003. The 5-year OS across the 4 calendar periods increased at each TNM stage with progression-free survival (PFS) and locoregional relapse-free survival (LRFS) showing a similar trend, whereas distant metastasis-free survival showed small differences. Multivariate analyses showed that the application of intensity modulated radiation therapy and magnetic resonance imaging were independent protective factors in OS, PFS, LRFS, and distant metastasis-free survival. Chemotherapy benefited patients in OS, PFS, and LRFS. The main pattern of treatment failure shifted from recurrence to distant metastasis. The development of radiation therapy, image technology, and chemotherapy increased survival rates among patients with NPC because of excellent locoregional control. Distant failure has become the greatest challenge for NPC treatment.

Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as associated Epstein-Barr virus infection and high radiosensitivity. Radiotherapy has long been recognized as the mainstay for the treatment of NPC. However, the further efficacy brought by radical radiotherapy has reached the bottleneck in advanced patients, who are prone to develop recurrence and distant metastasis after treatment. The application of photon therapy makes it possible for radiation dose escalation in refractory cases and may provide second chance for recurrent patients with less unrecoverable tissue damage. The concept of adaptive radiotherapy is put forward in consideration of target volume shrinkage during treatment. The replanning procedure offers better protection for the organ at risk. However, the best timing and candidates for adaptive radiotherapy is still under debate. The current tendency of artificial intelligence in NPC mainly focuses on image recognition, auto-segmentation and dose prediction. Although artificial intelligence is still in developmental stage, the future of it is promising. To further improve the efficacy of NPC, multimodality treatment is encouraged. In-depth studies on genetic and epigenetic variations help to explain the great heterogeneity among patients, and could further be applied to precise screening and prediction, personalized radiotherapy and the evolution of targeted drugs. Given the clinical benefit of immunotherapy in other cancers, the application of immunotherapy, especially immune checkpoint inhibitor, in NPC is also of great potential. Results from ongoing clinical trials combining immunotherapy with radiotherapy in NPC are expected.

Background: Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning. Methods: An endoscopic images‐based nasopharyngeal malignancy detection model (eNPM‐DM) consisting of a fully convolutional network based on the inception architecture was developed and fine‐tuned using separate training and validation sets for both classification and segmentation. Briefly, a total of 28,966 qualified images were collected. Among these images, 27,536 biopsy‐proven images from 7951 individuals obtained from January 1st, 2008, to December 31st, 2016, were split into the training, validation and test sets at a ratio of 7:1:2 using simple randomization. Additionally, 1430 images obtained from January 1st, 2017, to March 31st, 2017, were used as a prospective test set to compare the performance of the established model against oncologist evaluation. The dice similarity coefficient (DSC) was used to evaluate the efficiency of eNPM‐DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images, by comparing automatic segmentation with manual segmentation performed by the experts. Results: All images were histopathologically confirmed, and included 5713 (19.7%) normal control, 19,107 (66.0%) nasopharyngeal carcinoma (NPC), 335 (1.2%) NPC and 3811 (13.2%) benign diseases. The eNPM‐DM attained an overall accuracy of 88.7% (95% confidence interval (CI) 87.8%–89.5%) in detecting malignancies in the test set. In the prospective comparison phase, eNPM‐DM outperformed the experts: the overall accuracy was 88.0% (95% CI 86.1%–89.6%) vs. 80.5% (95% CI 77.0%–84.0%). The eNPM‐DM required less time (40 s vs. 110.0 ± 5.8 min) and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background, with an average DSC of 0.78 ± 0.24 and 0.75 ± 0.26 in the test and prospective test sets, respectively. Conclusions: The eNPM‐DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant, and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images.