Abstract
Nasopharyngeal carcinoma (NPC) represents an Epstein–Barr virus (EBV)-associated malignancy showing elevated incidence in East and Southeast Asia. Early detection remains vital, as molecular abnormalities precede visible histological changes during tumor development. This review summarizes recent progress in decoding NPC’s molecular profile, including genetic mutations, epigenetic alterations, non-coding RNA networks and proteomic alterations. Importantly, these molecular discoveries are increasingly informing clinical approaches to disease management. Modern diagnostic integration of histopathology, EBV biomarkers and advanced imaging has improved detection, yet locoregional recurrence and distant metastasis remain major causes of mortality. Immunotherapy shows promising efficacy in recurrent/metastatic NPC, underscoring the potential of molecular insights to guide therapeutic innovation.
Keywords: nasopharyngeal carcinoma, Epstein–Barr virus, immunotherapy
1. Introduction
Nasopharyngeal carcinoma (NPC) tumorigenesis involves a multistep interplay of Epstein–Barr virus (EBV) oncogenesis, genetic susceptibility, environmental carcinogens and epigenetic dysregulation [1,2,3,4,5]. Notably, NPC exhibits distinct etiological heterogeneity across geographical regions. In high-incidence areas such as East and Southeast Asia, over 95% of cases are associated with EBV infection and are classified as non-keratinizing carcinomas [1]. In contrast, in low-incidence regions (e.g., North America and Europe), a substantial proportion of NPC cases are keratinizing squamous cell carcinomas with a weaker EBV association, where tobacco and alcohol are more prominent risk factors [6]. Given that EBV-associated NPC represents the predominant form globally and offers a unique model for studying virus-driven carcinogenesis, this review will focus primarily on this subtype, while acknowledging etiological variations where relevant.
Globally, NPC incidence shows marked geographical disparity. For instance, crude incidence and mortality rates in China have been reported as 3.09 and 1.57 per 100,000, respectively [1,7,8]. Locoregional recurrence and distant metastasis remain leading causes of mortality, contributing to a five-year survival rate of 50–60% for advanced-stage (III/IV) patients [9,10]. In contrast, early-stage (I/II) patients exhibit survival rates exceeding 90%, underscoring the importance of early detection [11,12]. Molecular alterations, including genetic mutations, epigenetic dysregulation and viral oncogenic mechanisms, precede histopathological changes. These early molecular events offer promising avenues for biomarker discovery and therapeutic innovation. Traditional treatment strategies such as radiotherapy, chemotherapy and surgery are often associated with severe adverse effects and limited efficacy. In recent years, immunotherapy has emerged as a promising approach, with growing clinical evidence supporting its safety and efficacy in NPC, particularly in EBV-associated cases.
This review aims to systematically decode the molecular landscape of NPC from a virology-oncology perspective, with an emphasis on EBV-driven pathways. The first objective is to identify early molecular alterations that could aid non-invasive detection and risk stratification. The second objective is to examine how these molecular insights can guide novel treatments. Based on this framework, we summarize recent advances in early detection and therapeutic innovation derived from this integrated understanding.
2. EBV Infection Mechanisms and Molecular Pathogenesis
NPC is an infection-associated malignancy primarily driven by EBV. EBV, the first identified human tumor virus, is strongly implicated in the etiology of multiple lymphoid and epithelial cancers [13]. B lymphocytes and epithelial cells are the main target cells of EBV. The lifecycle of EBV consists of two stages, the lytic cycle and the latent phase. Upon primary infection, EBV typically establishes a persistent, lifelong latent infection in memory B cells [13]. In addition to its role in B-cell persistence, EBV is also directly associated with epithelial cancers, most notably NPC and a subset of gastric cancers. Histologically, NPC is classified into keratinizing squamous cell carcinoma, differentiated non-keratinizing carcinoma, undifferentiated non-keratinizing carcinoma, and basaloid squamous cell carcinoma. Notably, EBV is detected in nearly all cases of undifferentiated NPC, particularly in endemic areas [1,14]. During EBV infection of epithelial cells, the viral BMRF2 protein first anchors to integrin. Subsequently, the gH/gL heterodimer cooperatively binds to both integrin and ephrin receptor A2. This binding triggers conformational activation of the fusion protein gB, which ultimately mediates the fusion of the viral envelope with the host cell plasma membrane [15,16]. Thus, the EBV envelope glycoproteins gH/gL and gB are critical mediators of EBV infection in epithelial cells. And gH/gL and gB represent potential targets for prophylactic vaccine development [17].
EBV exhibits three distinct latency programs (types I, II and III), defined by the specific repertoire of viral latent genes expressed. Type III latency (e.g., in post-transplant lymphoproliferative disease) involves expression of all EBNA proteins, LMP1 and LMP2 [16]. NPC is classically associated with type II latency, which is characterized by the expression of EBNA1, LMP1 and LMP2A/B, along with abundant non-coding RNAs such as BARTs and EBERs [16]. These type II latency molecules are not only central to oncogenesis but also serve as foundational targets for diagnostic biomarkers and therapeutic strategies. LMP1 acts as a constitutively active mimic of the tumor necrosis factor receptor (TNFR), hijacking multiple signaling pathways (including NF-κB, JAK/STAT and MAPK) to promote cell survival, proliferation and inflammation [16,18]. LMP1 is also detectable by immunohistochemistry, aiding clinical diagnosis [19]. LMP2A mimics B-cell receptor signaling and can enhance epithelial cell motility and survival. EBNA1 is essential for viral genome maintenance and also modulates host cell transcription and stability [16,18]. EBNA1 is a key target for both serological diagnosis and therapeutic vaccines [20,21]. Together with the non-coding RNAs, these viral products collectively disrupt key cellular homeostasis and drive malignant transformation through sustained proliferation, avoidance of immune detection, and inhibition of apoptosis [22]. However, as NPC progresses, lytic genes begin to be expressed. The immediate-early gene BZLF1 (encoding the Zta protein) serves as the master switch for initiating the lytic cycle [23]. In NPC, focal and abortive expression of BZLF1 is common and biologically active [23,24]. Detection of BZLF1 in tissues is associated with enhanced tumor metastasis and invasion, angiogenesis, resistance to cell death and immune evasion [23,24,25].
The high prevalence of EBV in this subtype underscores its central role in oncogenesis. Given its strong epidemiological association with NPC, EBV-derived biomarkers have become cornerstone tools for screening and diagnosis. Detections targeting EBV DNA and EBV antigens (anti-VCA IgA, anti-EBNA1-lgA and anti-EA IgG) are widely used for NPC screening in high-risk populations [26]. Additionally, anti-BZLF1 (anti-Zta) IgA reflects chronic EBV lytic activity and shows improved diagnostic sensitivity compared to VCA-IgA alone [27].
3. Current Diagnostic Landscape
Currently, the diagnosis of NPC relies on a multimodal and integrated system combining clinical examination, imaging, molecular biology and digital technologies (Figure 1).
Figure 1.
Diagnostic framework of NPC. Nasopharyngoscopy with biopsy of suspicious lesions remains the cornerstone of pathological confirmation. Advanced endoscopic techniques, including WLI and NBI, enhance the visualization of mucosal abnormalities and guide targeted biopsies. Imaging modalities such as high-resolution MRI, PET/CT and CE-CT provide critical adjunctive value for local and systemic staging, prognostic stratification, and surveillance. Given the strong etiological association of NPC with EBV infection, virological biomarkers play a central role. EBV DNA load and EBV-specific serological antibodies are pivotal for early screening, risk stratification and post-treatment monitoring. At the tissue level, in situ hybridization for EBER is the gold standard for confirming EBV association within tumor cells, complemented by immunohistochemical detection of LMP1.
3.1. Standard Diagnostic Protocol and Routine Clinical Practice
International guidelines, such as the ESMO-EURACAN Clinical Practice Guidelines, recommend a standardized multimodal protocol for NPC diagnosis. The gold standard for definitive diagnosis is endoscopic-guided biopsy of suspicious primary nasopharyngeal lesions [28]. High-resolution magnetic resonance imaging (MRI) and narrow-band imaging (NBI) serve as first-line investigations for detecting subtle mucosal abnormalities and guiding targeted biopsies in early-stage lesions that evade conventional endoscopic visualization [29,30,31]. However, MRI faces diagnostic challenges in distinguishing T1-stage NPC from benign hyperplasia and in identifying diffuse, symmetrical tumors that lack focal masses. Consequently, endoscopic correlation is often necessary, even though MRI demonstrates higher sensitivity than endoscopic examination alone [32]. Positron emission tomography/computed tomography (PET/CT) has demonstrated established feasibility and efficacy in tumor diagnosis, treatment planning, prognostic evaluation and disease surveillance. Several radiotracers, including fluciclovine F-18, gallium Ga-68 DOTATATE and lutetium Lu-177 DOTATATE, are FDA-approved for PET imaging [33]. At the tissue level, in situ hybridization for EBERs remains the gold standard for confirming EBV association, demonstrating near-universal positivity in NPC specimens [18,28]. For staging and risk assessment, routine work-up includes medical history, physical examination (including cranial nerves), complete blood count, serum biochemistry, nasopharyngoscopy and imaging [28]. MRI is the most accurate method for defining local and nodal tumor staging and should be the preferred imaging modality [28]. FDG-PET/CT provides further accuracy in nodal staging [28].
3.2. Augmentation by Advanced Imaging and Digital Pathology
The clinical application of artificial intelligence (AI) in NPC diagnosis is context-dependent, addressing specific challenges across different clinical scenarios. Specifically, a Siamese deep convolutional neural network integrating both white light (WLI) and NBI endoscopy images aids in distinguishing early-stage NPC from benign lesions, achieving high diagnostic accuracy [34]. This approach serves as a crucial computer-aided tool for clarifying ambiguous cases in screening. In histopathological diagnosis, AI-driven digital pathology tools primarily address workflow efficiency. Whole slide imaging enables AI analysis, reducing diagnostic time burdens [35]. Weakly supervised models, such as the Tokens-to-Token Vision Transformer (WS-T2T-ViT), are significant for settings with limited expert annotation resources. These models achieve high diagnostic accuracy on whole slide images using only slide-level labels, ensuring robust performance while minimizing labor [36].
For treatment stratification in locoregionally advanced NPC, contrast-enhanced CT radiomics provides functional prognostic information beyond anatomical TNM staging. A radiomics-based model integrating specific image features and N stage can identify patients with a favorable prognosis, thus helping to select candidates who may be suitable for deintensified therapy [37]. In post-treatment surveillance for recurrence, AI augmentation of MRI improves specificity. An AI-aided MRI model demonstrates performance approaching that of PET/CT in select cohorts, offering a potentially more accessible and cost-effective monitoring strategy for detecting local recurrence [38].
3.3. Integration of Molecular and Virological Biomarkers
Molecular alterations in premalignant lesions often precede morphological changes. highlighting the potential of molecular biomarkers for early detection and precision classification. For NPC, which is strongly associated with EBV infection, EBV-related biomarkers are crucial for early detection, risk stratification and monitoring [39]. Clinically validated markers include plasma EBV DNA load and serological antibodies (e.g., anti-VCA IgA, anti-EBNA1-IgA, anti-EA IgG) [1,40,41]. However, their application differs based on clinical context. Beyond viral load and serology, specific genetic variations in EBV also hold diagnostic and prognostic value. For instance, evolutionary analysis of the LMP1 gene, a key viral oncogene, has identified genetic variants associated with increased oncogenic potential. Certain LMP1 mutants are linked to a higher metastasis potential, providing a molecular layer for understanding tumor aggressiveness [42].
In population screening for early detection, serological antibodies are pivotal. A landmark trial demonstrated that combining VCA-IgA and EBNA1-IgA serology improved early NPC diagnosis rates and reduced NPC-related mortality [43,44]. For individuals with positive serology or high risk, confirmatory testing often involves plasma EBV DNA due to its higher specificity in resolving false positives [9,41,45]. Nasopharyngeal brushing offers a direct sampling alternative. Notably, for non-invasive screening, EBV DNA methylation analysis in nasopharyngeal brushing samples shows superior accuracy to DNA load quantification and avoids endoscopy [46].
In post-diagnosis surveillance and prognosis, plasma EBV DNA is the cornerstone biomarker [9,47,48]. Specifically, post-treatment persistence of EBV DNA correlates with poorer survival outcomes [49]. For detecting recurrence during follow-up, plasma EBV DNA demonstrates high sensitivity, particularly for distant metastasis [50]. Compared to seromarkers like EA-IgA, which also predicts survival, plasma EBV DNA provides a more immediate reflection of tumor burden and is superior to PBMC-based assays for monitoring [51,52].
These biomarkers are integrated into clinical algorithms based on purpose. Serology is preferred for initial mass screening. Plasma EBV DNA is central for confirming screen-positive cases, staging, prognostic stratification, and monitoring treatment response and recurrence. Emerging multi-analyte models combining these markers promise enhanced risk stratification.
4. Molecular Regulatory Networks of Nasopharyngeal Cancer
NPC pathogenesis arises from multifaceted molecular changes (Table 1). These changes include genetic mutations, epigenetic modifications and non-coding RNA/protein dysregulation. A comprehensive understanding of these mechanisms is crucial. However, the translational potential of these findings depends on rigorous validation and a clear understanding of their clinical applicability.
Table 1.
Key oncogenic mechanisms in nasopharyngeal carcinoma.
| Core Functional Theme | Genetic Alterations | Epigenetic Alterations | Non-Coding RNA Alterations | Proteomic Alterations |
|---|---|---|---|---|
| Cell proliferation | CHL1 downregulation; MYC amplification | ACAT1 hypermethylation-mediated silencing | miR-106a-5p upregulation; FAM225A and BC200 upregulation | |
| Metastasis and invasion | PIK3CA amplification | NFAT1 and ACAT1 hypermethylation-mediated silencing; FGF5 and S100A4 hypomethylation-mediated activation | EBV miR-BART22; FAM225A and BC200 upregulation | HSP70, sICAM-1, SAA, stathmin, 14-3-3sigma and annexin I upregulation |
| Immune evasion | 11q13 amplification; Deletions at 9p21.3; Deletions of TGFBR2, TRAF3 and CYLD | ELF3 hypomethylation-mediated activation | EBV miR-BART11 and BART17-3p; miR-106a-5p upregulation | |
| Therapy resistance | USP44 hypermethylation-mediated silencing; FGF5 hypomethylation-mediated activation | RRFERV, PVT1 and HOTAIRM1 upregulation |
4.1. Genetic Aberrations
NPC development involves cumulative genetic changes (Figure 2). This cancer has a relatively low mutation rate but frequent copy number alterations. Targeted next-generation sequencing of 40 primary NPC tumors identified recurrent mutations. The most frequently mutated genes included KMT2D, CYLD and TP53 [53]. This was a retrospective study using a targeted 450-gene panel. Its statistical power to define prevalence is limited by the small sample size. A separate study found mutations in the RB2/p130 (exons 19–22) gene in 30% of primary NPC tumors from a North African cohort [54]. This is an exploratory finding from a small, region-specific sample. Its generalizability is unclear and requires validation in larger, diverse cohorts. Whole-genome studies show recurrent chromosomal gains at 1q, 3q, 8q, 11q, 12p and 12q, and losses at 3p, 9p, 9q, 11q, 13q, 14q and 16q [55,56,57,58,59]. These alterations are not equal in functional importance. Some are likely passenger events, while others are drivers. Key amplified regions include 11q13.1–13.3 driving CCND1 overexpression [60]. CCND1 knockdown suppresses NPC cell proliferation [60]. Critically, 11q13 amplification is linked to clinical outcome. In a phase II trial, none of the 12 patients with this alteration responded to the anti-PD-1 therapy toripalimab [57]. This highlights a potential genetic determinant of immune resistance. PIK3CA amplification is found in 21.6% of cases in a Tunisian cohort [61]. This retrospective study of 88 patients found a strong association between PIK3CA amplification and advanced disease features, including metastasis and reduced overall survival. MYC (8q24) is another commonly amplified oncogene [58]. Frequent deletions also occur. Homozygous deletions at 9p21.3 (CDKN2A/CDKN2B and MTAP) and losses of TGFBR2, TRAF3 and CYLD drive NF-κB activation and immune evasion [62]. CHL1 (3p26.3) is downregulated in most tumors, and its re-expression suppresses growth [63]. In summary, NPC progression is driven by a combination of genetic events that disrupt tumor suppression, activate oncogenic pathways such as PI3K and MYC, and enhance immune evasion. The association between 11q13 amplification and immunotherapy resistance is a compelling example with direct clinical relevance.
Figure 2.
Genetic and Molecular Drivers of NPC Pathogenesis. NPC exhibits a relatively low mutation rate with frequent copy number alterations. The disease progression is driven by cumulative genetic alterations that disrupt tumor suppression mechanisms, activate oncogenic signaling pathways, and enhance immune evasion capabilities. KMT2D, TP53, and RB2/p130 are the most frequently mutated genes. Whole-genome sequencing identified recurrent chromosomal imbalances, including frequent gains at 1q, 3q, 8q, 11q, 12p and 12q, with key amplified oncogenes (CCND1, FGF14, FGF3, FGF4, PIK3CA and MYC). High-frequency allelic losses occur at 3p, 9p, 9q, 11q, 13q, 14q, and 16q, involving critical tumor suppressor genes (CDKN2A/CDKN2B, MTAP, TGFBR2, TRAF3, CYLD and CHL1).
4.2. Epigenetic Dysregulation
DNA methylation is a pivotal epigenetic mechanism in NPC [64,65]. Aberrant promoter methylation silences tumor suppressor genes and activates oncogenes. Hypermethylation silences genes like NFAT1, ACAT1 and USP44 and HOPX [66,67,68]. Hypomethylation activates genes like FGF5, ELF3 and S100A4 [69,70,71]. These changes promote proliferation, metastasis and therapy resistance. Methylation markers show promise for diagnosis. Multi-gene panels in tissue show high diagnostic specificity but variable sensitivity (26–66%) [72]. Liquid biopsy approaches are increasingly promising for non-invasive detection. For example, RERG/ZNF671 methylation in circulating cell-free DNA (ccfDNA) showed high diagnostic accuracy [73]. A four-gene panel (RASSF1A, WIF1, DAPK1, RARβ2) in plasma and nasopharyngeal brushing improved early detection when combined with EBV DNA testing [74]. Blind brushing combining EBV-BILF2 and host IMPA2 methylation achieved 84.62% sensitivity and 98.44% specificity [75]. SEPT9 methylation in nasopharyngeal swabs is also a potential early biomarker [76]. However, most studies are exploratory and retrospective. Their clinical utility requires validation in larger, prospective cohorts. Methylation also has prognostic value. Hypermethylation of WIF1, UCHL1, RASSF1A, CCNA1, TP73 and SFRP1 correlates with poorer survival [77]. HOPX hypermethylation predicts advanced stage and poor outcome [78]. Despite strong potential, key challenges for clinical implementation remain. These include assay standardization, defining optimal biomarker panels, and integrating tests into existing screening workflows.
4.3. MicroRNA Dysregulation
MicroRNAs (miRNAs) regulate gene expression post-transcriptionally [79,80,81]. In NPC, EBV-encoded and host miRNAs interact, promoting tumorigenesis and immune evasion [82,83,84]. A study analyzed serum from 208 NPC patients and 238 healthy controls. It reported a 5-miRNA panel (let-7b-5p, miR-140-3p, miR-192-5p, miR-223-3p and miR-24-3p) with high diagnostic accuracy [85]. The AUC values were 0.910, 0.916 and 0.968 across training, testing and external validation stages, respectively [85]. A 4-miRNA (miR-22, miR-572, miR-638 and miR-1234) signature predicted survival [86]. Plasma EBV-miR-BART8-3p levels correlate with reduced survival [87]. Platelet-absorbed miR-34c-3p and miR-18a-5p showed high diagnostic accuracy (combined AUC = 0.954) [88]. Salivary miRNAs represent a promising non-invasive source of biomarkers. A pilot microarray study on saliva from 22 NPC patients and 25 healthy controls identified a signature of 12 down-regulated miRNAs (miR-30b-3p, miR-575, miR-650, miR-937-5p, miR-1202, miR-1203, miR-1321, miR-3612, miR-3714, miR-4259, miR-4478 and miR-4730) with an exceptional reported AUC of 0.999 [89]. However, such exceptionally high performance requires critical evaluation. Factors like sample size, population heterogeneity and the need for independent validation are important limitations. Therapeutically, strategies aim to suppress oncogenic miRNAs (miR-28-3p or EBV-miR-BART22) or restore tumor-suppressive ones (miR-205 or miR-873) [83,90,91,92]. Importantly, miRNA networks do not operate in isolation. Their dysregulation is often downstream of genetic and epigenetic alterations, such as the methylation-mediated silencing of miRNA host genes. Future work should integrate these layers to define unified regulatory circuits.
4.4. Long Non-Coding RNA Alterations
Long non-coding RNAs (lncRNAs) are transcripts exceeding 200 nucleotides in length [93]. They function as competing endogenous RNAs (ceRNAs) or activating RNAs [94]. For instance, FAM225A promotes NPC tumorigenesis and metastasis by sponging miR-590-3p and miR-1275, leading to the activation of ITGB3 and the FAK/PI3K/AKT pathway [95]. Similarly, the EBV-upregulated lncRNA BC200 acts as a ceRNA for miR-6834-5p, resulting in increased expression of the TYMS, which is implicated in cancer progression [96]. A prominent functional theme among NPC-associated lncRNAs is the mediation of radiation resistance, a major clinical challenge. A study analyzing 220 formalin-fixed NPC specimens retrospectively linked high RRFERV expression to poor clinical outcomes [97]. Mechanistically, it acts as a ceRNA, sponging miR-615-5p and miR-1293 to stabilize TEAD1, thereby promoting radioresistance [97]. Similarly, PVT1 and HOTAIRM1 have been reported to drive radioresistance through pathways involving DNA repair and m6A modification, respectively [98,99]. While these mechanistic discoveries are rich, the clinical translation of lncRNAs as biomarkers or therapeutic targets remains preliminary. Some studies have proposed circulating lncRNAs like POU3F3, MALAT1, AFAP1-AS1 and AL359062 as potential diagnostic or prognostic biomarkers [100,101]. However, many of these findings are exploratory, often derived from single-center, retrospective studies with limited sample sizes and lacking independent validation cohorts. A major challenge for their clinical application is the typically low abundance of many lncRNAs in circulation, coupled with the complexity of their regulatory networks, which complicates reliable detection and therapeutic targeting.
4.5. Proteomic Alterations
Proteomic studies bridge genomic alterations with functional phenotypes and offer a direct route for biomarker discovery. However, the clinical translation of most findings remains at an exploratory stage, pending rigorous validation in large-scale, prospective cohorts. Secretome analysis identified plasma CCL5 as a diagnostic biomarker (AUC = 0.801), but this finding was based on a limited cohort and has not been widely adopted in clinical practice [102]. A serum study identified HSP70, sICAM-1 and SAA as potential metastasis markers [103]. These proposed biomarkers originate from single-center studies with limited sample sizes and lack clear demonstration of superior diagnostic advantage over established standards. Early studies using 2D electrophoresis and mass spectrometry identified differentially expressed proteins like stathmin, 14-3-3sigma and annexin I in NPC tissues, with their expression levels related to metastatic potential [104]. However, these early findings currently lack independent validation. The most significant translational progress involves combining proteomic markers with the established gold standard. Serum exosomal cyclophilin A combined with EBV-VCA-IgA improved diagnostic specificity [105]. Combining plasma EBV DNA load with serum C-reactive protein improved prognosis in advanced cases [106]. These studies highlight the biomarker discovery value of proteomics. However, few proposed protein biomarkers offer a clear advantage over established markers like EBV DNA. Proteomics also clarifies host–virus interactions. iTRAQ-based profiling identified 12 upregulated proteins (VDAC1, S100-A2, Hip-70, Ubiquitin, TPT1-like protein, 4F2hc, Keratin-75, TB8, Dynein light chain 1, LDH-B, TIM and HMG-1) in EBV-infected cells [107]. The proteomic landscape of NPC is richly characterized at a discovery level. However, the proposed protein biomarkers generally lack the extensive multi-center validation and proven clinical utility.
5. Immunotherapy for Nasopharyngeal Carcinoma: Bridging Molecular Insights and Clinical Translation
More than 70% of NPC patients present with stage III/IV disease at initial diagnosis due to the nasopharynx’s concealed anatomy and nonspecific early symptoms [108]. While standard chemoradiotherapy remains foundational, 20–30% of patients experience recurrence, highlighting the need for novel strategies [109,110]. The profound molecular underpinnings of NPC, particularly its universal association with EBV, directly create a rationale for immunotherapy (Table 2). EBV-driven oncogenesis establishes a unique tumor microenvironment (TME) characterized by immune evasion mechanisms, which these therapies aim to reverse.
5.1. Adoptive T-Cell Therapy: Reconstituting Antiviral Immunity
Adoptive T-cell therapy (ACT) aims to compensate for the immune system’s inability to adequately control latent EBV infection. This approach involves ex vivo expansion and infusion of cytotoxic T lymphocytes (CTLs) specific for EBV latent cycle antigens (EBNA1, LMP1, LMP2) [111,112,113]. Clinical studies report disease control in a subset of patients with refractory NPC, validating the concept of targeting these viral oncoproteins [111,112,113]. However, the tumor microenvironment can resist ACT through mechanisms including upregulation of immune checkpoints and secretion of immunosuppressive cytokines.
5.2. Immune Checkpoint Blockade: Targeting Virus and Epigenetically Induced Immunosuppression
A primary molecular feature enabling immunotherapy in NPC is the high tumor cell expression of programmed death-ligand 1 (PD-L1), observed in over 80% of cases [109,114]. This expression is not stochastic but is orchestrated by EBV through a multi-layer regulatory network involving the key oncoprotein LMP1 and immune-modulatory miRNAs like miR-BART11 and miR-BART17-3p [82,115]. This molecular backdrop justifies the clinical efficacy of PD-1 inhibitors (toripalimab, camrelizumab, tislelizumab, sintilimab) combined with chemotherapy, as established in phase 3 trials for recurrent/metastatic NPC [109,114,116,117]. However, intrinsic and acquired resistance limits monotherapy efficacy. Resistance mechanisms may involve compensatory upregulation of alternative checkpoints, such as lymphocyte-activation gene 3 (LAG-3) or Cytotoxic T-lymphocyte antigen 4 (CTLA-4) [118,119,120]. Consequently, combination strategies targeting multiple pathways are critical. Dual PD-1/CTLA-4 blockade (e.g., nivolumab/ipilimumab) shows enhanced efficacy, potentially by overcoming T-cell exhaustion states reinforced by the co-expression of these checkpoints [121]. The clinical activity of bispecific antibodies targeting PD-1 and CTLA-4, such as cadonilimab and QL1706, further supports the mechanistic synergy of co-inhibitory pathway blockade [122,123]. Emerging targeting of LAG-3, as with LBL-007 combined with toripalimab, represents a logical extension of this principle, aiming to restore the function of T-cell populations [124].
5.3. EBV-Targeted Strategies: From Prophylaxis to Therapeutic Vaccination
Given the etiological role of EBV, therapeutic strategies directly targeting viral antigens are a paradigm of translational innovation rooted in molecular virology. Prophylactic vaccine development focuses on glycoproteins gH/gL and gB, which are critical for epithelial cell entry. Nanoparticle vaccines displaying these antigens, such as gH/gL NPs or gB-I53-50 NPs, are designed based on structural virology to elicit potent neutralizing antibodies, showing protective efficacy in preclinical models [17,125]. For therapeutic vaccination in established NPC, the target shifts to latent phase antigens. The choice of EBNA1 and LMP2 as targets is mechanistically informed. EBNA1 is essential for viral genome maintenance and is a dominant CD4+ T-cell target; LMP2 is expressed in type II latency and provides epitopes for CD8+ T cells [21,126]. Clinical trials of vaccines like MVA-EL (encoding EBNA1/LMP2) demonstrate the expansion of specific T-cell populations, confirming immune priming [127,128]. A key challenge for therapeutic efficacy is the relatively low and heterogeneous expression of these target antigens in tumor cells, which can be further downregulated by epigenetic mechanisms, allowing immune escape.
Table 2.
Progress in immunotherapy strategies.
| Treatment Strategy | Setting/Trial Identifier | Phase | Treatment | Sample | Sample Size | Efficacy | Reference |
|---|---|---|---|---|---|---|---|
| Immune checkpoint blockade |
NCT03581786 (JUPITER-02) |
Phase III | Toripalimab + chemotherapy | Recurrent/metastatic NPC | 289 | Median PFS: 21.4 months; ORR: 78.8%; DCR: 88.4%; Median DOR: 18.0 months | [114] |
|
NCT03707509 (CAPTAIN-1st) |
Phase III | Camrelizumab + chemotherapy | Recurrent/metastatic NPC | 263 | ORR: 87.3%; DCR: 96.3% | [116] | |
|
NCT03924986 (RATIONALE-309) |
Phase III | Tislelizumab + chemotherapy | Recurrent/metastatic NPC | 263 | ORR: 69.5%; DCR: 89.3%; Median DOR: 8.5 months | [117] | |
|
NCT03700476 (CONTINUUM) |
Phase III | Sintilimab + chemotherapy | Locoregionally advanced NPC patients (stage III–IVa) | 425 | EFS rate at 36 months: 86%; DMFS rate at 36 months: 90%; LRFS rate at 36 months: 93%; OS rate at 36 months: 92% | [109] | |
| NCT03097939 | Phase II | Nivolumab + ipilimumab | Recurrent/metastatic EBV-associated NPC | 40 | PR: 37.5%; SD: 17.5%; PD: 42.5%; DCR: 55% | [121] | |
| ChiCTR2200067057 | Phase II | Cadonilimab (PD-1/CTLA-4 bispecific) + chemotherapy | Anti-PD-1-resistant recurrent/metastatic NPC | 25 | ORR: 68%; DCR: 92%; CR: 12%; PR: 56%; SD: 24%; PD: 4% | [122] | |
| NCT04296994 and NCT05171790 | Phase I/Ib | QL1706 (PD-1/CTLA-4 bispecific) | NPC | 110 | CR: 0%; PR: 24.5%; SD: 24.5%; PD: 47.3%; ORR: 24.5%; DCR: 49.1% | [123] | |
| NCT05102006 | Phase Ib/II | LBL-007 (LAG-3) + toripalimab | Advanced NPC | 30 | PR: 33.3%; SD: 41.7%; PD: 25.0%; ORR: 33.3%; DCR: 75.0% | [124] | |
| EBV-directed vaccination | Preclinical | gH/gL nanoparticle vaccine | Humanized mice | Induced neutralizing antibodies; prevented lethal EBV challenge | [17] | ||
| Preclinical | gB nanoparticle vaccine | Mice/non-human primate | Induced neutralizing antibodies; prevented lethal EBV challenge | [125] | |||
| NCT01256853 | Phase I | MVA-EL (encode an EBNA1/LMP2 fusion protein) | EBV-positive NPC | 18 | Enhanced T-cell responses in 15/18 patients | [127] | |
| NCT01147991 | Phase I | MVA-EL (encode an EBNA1/LMP2 fusion protein) | EBV-positive NPC | 14 | Enhanced T-cell responses in 8/14 patients | [128] | |
| Adoptive T-cell therapy | Clinical trial | Autologous EBV-specific CTLs | Stage IV NPC | 10 | Induces LMP-2 specific immune responses | [111] |
6. Conclusions and Future Directions
NPC remains a significant clinical challenge. Its etiology involves a complex interplay of EBV infection, genetic susceptibility and environmental factors. Over recent decades, research has successfully decoded the molecular landscape of this disease. This includes genetic mutations, epigenetic reprogramming and non-coding RNA dysregulation. These discoveries have directly informed clinical practice. They have improved early detection through advanced EBV biomarker profiling. They have also guided the development of novel immunotherapies. Looking forward, the integration of emerging technologies promises to deepen our understanding. It will also enable more precise and personalized management of NPC.
Current diagnostic paradigms effectively integrate histopathology, EBV biomarkers and advanced imaging. Future refinements will focus on enhancing accuracy and accessibility. AI models are being developed to interpret endoscopic and radiological images. These models can improve the identification of early-stage tumors and assist in treatment planning. For example, an AI-powered endoscopic analysis system trained on thousands of images significantly improved diagnostic accuracy [129]. Furthermore, AI-based radiomics extracts subtle features from medical images for prognosis prediction and recurrence monitoring [130]. The next generation of diagnostic platforms will integrate these AI tools with molecular data streams. This integration will enable more precise and dynamic patient assessment.
A deep understanding of molecular regulatory networks is fundamental for advancing therapy. NPC pathogenesis involves genetic, epigenetic, and non-coding RNA alterations. Key genetic events like 11q13 amplification are linked to immunotherapy resistance. Epigenetic changes such as DNA methylation silence tumor suppressor genes. Non-coding RNAs, including both EBV-encoded and host miRNAs, are central to immune evasion. These interconnected layers of regulation drive tumor progression and treatment failure. Future research must continue to decipher these complex networks to identify new vulnerabilities.
Prevention and therapy are becoming increasingly targeted, guided by molecular insights. Immunotherapy is now a cornerstone for recurrent or metastatic NPC. The efficacy of PD-1 inhibitors combined with chemotherapy is established. However, resistance remains a challenge. Future strategies involve rational combination therapies, such as dual blockade of PD-1 with CTLA-4 or LAG-3, to overcome resistance. Adoptive T-cell therapy infusing EBV-specific T cells has shown disease control in refractory patients. EBV-targeted vaccine strategies span from prevention to treatment. Prophylactic vaccines aim to block viral entry. Therapeutic vaccines target latent antigens in tumor cells. A key ongoing challenge is the low and heterogeneous expression of these target antigens.
Future research in NPC will be transformed by advanced molecular profiling technologies. Spatial transcriptomics is a key emerging tool. This technology can map the precise location of specific cell populations and molecular pathways. For instance, a recent study combined single-cell and spatial transcriptomics. It revealed the molecular and histological mechanisms underlying radio-resistance and immune escape in recurrent NPC [131]. This approach can identify distinct tumor subregions. It can also clarify stromal-immune cell interactions. These are crucial for understanding treatment failure. Single-cell multi-omics goes a step further. It enables simultaneous profiling of the genome, transcriptome, epigenome, and proteome within individual cells. Applying these technologies to premalignant lesions and paired primary-metastatic samples is a clear future direction. It will uncover the cellular origins of NPC and the dynamics of metastatic evolution.
In conclusion, the field of NPC research is at a pivotal point. The traditional approach is giving way to a new paradigm. This paradigm is based on spatial context, single-cell resolution, and computational data integration. By embracing these technologies, future research will bridge the gap between molecular discovery and clinical application. This will enable true precision medicine. It promises improved risk prediction, earlier diagnosis, and personalized treatment strategies for every NPC patient.
Author Contributions
N.L.: Conceptualization, Visualization, Writing—original draft. B.M.: Review and editing, Visualization. Y.L.: Review and editing, Visualization. M.T.: Review and editing, Visualization. Y.C.: Supervision, Funding acquisition. L.S.: Supervision, Funding acquisition. F.S.: Supervision, Writing—Review and Editing, Funding acquisition. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
No datasets were generated or analyzed during the current study.
Conflicts of Interest
The authors declare no competing interests.
Funding Statement
This study was supported by National Natural Science Foundation of China (82573064, 82303137 and 82073030), Hunan Provincial Natural Science Foundation of China (2025JJ60499 and 2022JJ20083), Hunan Provincial Postgraduate Research and Innovation Project (CX20250184) and the Independent Exploration and Innovation Project for Postgraduate Students at Central South University (2025ZZTS0234).
Footnotes
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References
- 1.Chen Y.P., Chan A.T.C., Le Q.T., Blanchard P., Sun Y., Ma J. Nasopharyngeal carcinoma. Lancet. 2019;394:64–80. doi: 10.1016/S0140-6736(19)30956-0. [DOI] [PubMed] [Google Scholar]
- 2.Lin D.C., Meng X., Hazawa M., Nagata Y., Varela A.M., Xu L., Sato Y., Liu L.Z., Ding L.W., Sharma A., et al. The genomic landscape of nasopharyngeal carcinoma. Nat. Genet. 2014;46:866–871. doi: 10.1038/ng.3006. [DOI] [PubMed] [Google Scholar]
- 3.Lo K.W., Chung G.T., To K.F. Deciphering the molecular genetic basis of NPC through molecular, cytogenetic, and epigenetic approaches. Semin. Cancer Biol. 2012;22:79–86. doi: 10.1016/j.semcancer.2011.12.011. [DOI] [PubMed] [Google Scholar]
- 4.Cao Y., DePinho R.A., Ernst M., Vousden K. Cancer research: Past, present and future. Nat. Rev. Cancer. 2011;11:749–754. doi: 10.1038/nrc3138. [DOI] [PubMed] [Google Scholar]
- 5.Cao Y. EBV based cancer prevention and therapy in nasopharyngeal carcinoma. npj Precis. Oncol. 2017;1:10. doi: 10.1038/s41698-017-0018-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Vaughan T.L., Shapiro J.A., Burt R.D., Swanson G.M., Berwick M., Lynch C.F., Lyon J.L. Nasopharyngeal cancer in a low-risk population: Defining risk factors by histological type. Cancer Epidemiol. Biomark. Prev. 1996;5:587–593. [PubMed] [Google Scholar]
- 7.Bray F., Ferlay J., Soerjomataram I., Siegel R.L., Torre L.A., Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018;68:394–424. doi: 10.3322/caac.21492. [DOI] [PubMed] [Google Scholar]
- 8.Wei K.R., Zheng R.S., Zhang S.W., Liang Z.H., Li Z.M., Chen W.Q. Nasopharyngeal carcinoma incidence and mortality in China, 2013. Chin. J. Cancer. 2017;36:90. doi: 10.1186/s40880-017-0257-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Qu H., Huang Y., Zhao S., Zhou Y., Lv W. Prognostic value of Epstein-Barr virus DNA level for nasopharyngeal carcinoma: A meta-analysis of 8128 cases. Eur. Arch. Otorhinolaryngol. 2020;277:9–18. doi: 10.1007/s00405-019-05699-9. [DOI] [PubMed] [Google Scholar]
- 10.Chua M.L.K., Wee J.T.S., Hui E.P., Chan A.T.C. Nasopharyngeal carcinoma. Lancet. 2016;387:1012–1024. doi: 10.1016/S0140-6736(15)00055-0. [DOI] [PubMed] [Google Scholar]
- 11.Lee A.W., Sze W.M., Au J.S., Leung S.F., Leung T.W., Chua D.T., Zee B.C., Law S.C., Teo P.M., Tung S.Y., et al. Treatment results for nasopharyngeal carcinoma in the modern era: The Hong Kong experience. Int. J. Radiat. Oncol. Biol. Phys. 2005;61:1107–1116. doi: 10.1016/j.ijrobp.2004.07.702. [DOI] [PubMed] [Google Scholar]
- 12.Mao Y.P., Li W.F., Chen L., Sun Y., Liu L.Z., Tang L.L., Cao S.M., Lin A.H., Hong M.H., Lu T.X., et al. A clinical verification of the Chinese 2008 staging system for nasopharyngeal carcinoma. Chin. J. Cancer. 2009;28:1022–1028. doi: 10.5732/cjc.009.10425. [DOI] [PubMed] [Google Scholar]
- 13.Liu N., Shi F., Yang L., Liao W., Cao Y. Oncogenic viral infection and amino acid metabolism in cancer progression: Molecular insights and clinical implications. Biochim. Biophys. Acta Rev. Cancer. 2022;1877:188724. doi: 10.1016/j.bbcan.2022.188724. [DOI] [PubMed] [Google Scholar]
- 14.Tsao S.W., Tsang C.M., Lo K.W. Epstein-Barr virus infection and nasopharyngeal carcinoma. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2017;372:20160270. doi: 10.1098/rstb.2016.0270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Cui X., Snapper C.M. Epstein Barr Virus: Development of Vaccines and Immune Cell Therapy for EBV-Associated Diseases. Front. Immunol. 2021;12:734471. doi: 10.3389/fimmu.2021.734471. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Damania B., Kenney S.C., Raab-Traub N. Epstein-Barr virus: Biology and clinical disease. Cell. 2022;185:3652–3670. doi: 10.1016/j.cell.2022.08.026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Malhi H., Homad L.J., Wan Y.H., Poudel B., Fiala B., Borst A.J., Wang J.Y., Walkey C., Price J., Wall A., et al. Immunization with a self-assembling nanoparticle vaccine displaying EBV gH/gL protects humanized mice against lethal viral challenge. Cell Rep. Med. 2022;3:100658. doi: 10.1016/j.xcrm.2022.100658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Cao Y., Xie L., Shi F., Tang M., Li Y., Hu J., Zhao L., Zhao L., Yu X., Luo X., et al. Targeting the signaling in Epstein-Barr virus-associated diseases: Mechanism, regulation, and clinical study. Signal Transduct. Target. Ther. 2021;6:15. doi: 10.1038/s41392-020-00376-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Tsao S.W., Tramoutanis G., Dawson C.W., Lo A.K., Huang D.P. The significance of LMP1 expression in nasopharyngeal carcinoma. Semin. Cancer Biol. 2002;12:473–487. doi: 10.1016/S1044579X02000901. [DOI] [PubMed] [Google Scholar]
- 20.Chan K.C.A., Lo Y.M.D. Circulating EBV DNA as a tumor marker for nasopharyngeal carcinoma. Semin. Cancer Biol. 2002;12:489–496. doi: 10.1016/S1044579X02000913. [DOI] [PubMed] [Google Scholar]
- 21.Fu T., Voo K.S., Wang R.F. Critical role of EBNA1-specific CD4+ T cells in the control of mouse Burkitt lymphoma in vivo. J. Clin. Investig. 2004;114:542–550. doi: 10.1172/JCI22053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Richardo T., Prattapong P., Ngernsombat C., Wisetyaningsih N., Iizasa H., Yoshiyama H., Janvilisri T. Epstein-Barr Virus Mediated Signaling in Nasopharyngeal Carcinoma Carcinogenesis. Cancers. 2020;12:2441. doi: 10.3390/cancers12092441. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Xu X., Zhu N., Zheng J., Peng Y., Zeng M.S., Deng K., Duan C., Yuan Y. EBV abortive lytic cycle promotes nasopharyngeal carcinoma progression through recruiting monocytes and regulating their directed differentiation. PLoS Pathog. 2024;20:e1011934. doi: 10.1371/journal.ppat.1011934. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Munz C. Latency and lytic replication in Epstein-Barr virus-associated oncogenesis. Nat. Rev. Microbiol. 2019;17:691–700. doi: 10.1038/s41579-019-0249-7. [DOI] [PubMed] [Google Scholar]
- 25.Dorothea M., Xie J., Yiu S.P.T., Chiang A.K.S. Contribution of Epstein-Barr Virus Lytic Proteins to Cancer Hallmarks and Implications from Other Oncoviruses. Cancers. 2023;15:2120. doi: 10.3390/cancers15072120. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Cai Y.L., Li J., Lu A.Y., Zheng Y.M., Zhong W.M., Wang W., Gao J.Q., Zeng H., Cheng J.R., Tang M.Z. Diagnostic significance of combined detection of Epstein-Barr virus antibodies, VCA/IgA, EA/IgA, Rta/IgG and EBNA1/IgA for nasopharyngeal carcinoma. Asian Pac. J. Cancer Prev. 2014;15:2001–2006. doi: 10.7314/apjcp.2014.15.5.2001. [DOI] [PubMed] [Google Scholar]
- 27.Liu H., Lei L., Song S., Geng X., Lin K., Li N., Chen W., Peng J., Ren J. The serological diagnostic value of EBV-related IgA antibody panels for nasopharyngeal carcinoma: A diagnostic test accuracy meta-analysis. BMC Cancer. 2024;24:1115. doi: 10.1186/s12885-024-12878-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Bossi P., Chan A.T., Licitra L., Trama A., Orlandi E., Hui E.P., Halamkova J., Mattheis S., Baujat B., Hardillo J., et al. Nasopharyngeal carcinoma: ESMO-EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2021;32:452–465. doi: 10.1016/j.annonc.2020.12.007. [DOI] [PubMed] [Google Scholar]
- 29.Shayah A., Wickstone L., Kershaw E., Agada F. The role of cross-sectional imaging in suspected nasopharyngeal carcinoma. Ann. R. Coll. Surg. Engl. 2019;101:325–327. doi: 10.1308/rcsann.2019.0025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Sun C., Zhang Y., Han X., Du X. Diagnostic Performance of Narrow Band Imaging for Nasopharyngeal Cancer: A Systematic Review and Meta-analysis. Otolaryngol. Head Neck Surg. 2018;159:17–24. doi: 10.1177/0194599818758302. [DOI] [PubMed] [Google Scholar]
- 31.King A.D., Wong L.Y.S., Law B.K.H., Bhatia K.S., Woo J.K.S., Ai Q.Y., Tan T.Y., Goh J., Chuah K.L., Mo F.K.F., et al. MR Imaging Criteria for the Detection of Nasopharyngeal Carcinoma: Discrimination of Early-Stage Primary Tumors from Benign Hyperplasia. AJNR Am. J. Neuroradiol. 2018;39:515–523. doi: 10.3174/ajnr.A5493. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.King A.D., Woo J.K.S., Ai Q.Y., Chan J.S.M., Lam W.K.J., Tse I.O.L., Bhatia K.S., Zee B.C.Y., Hui E.P., Ma B.B.Y., et al. Complementary roles of MRI and endoscopic examination in the early detection of nasopharyngeal carcinoma. Ann. Oncol. 2019;30:977–982. doi: 10.1093/annonc/mdz106. [DOI] [PubMed] [Google Scholar]
- 33.Xu X., Tang X., Wu W., Liu M., Zeng J. Radiopharmaceuticals in Nasopharyngeal Cancer. Bioorg Chem. 2025;157:108281. doi: 10.1016/j.bioorg.2025.108281. [DOI] [PubMed] [Google Scholar]
- 34.Xu J.W., Wang J., Bian X.Z., Zhu J.Q., Tie C.W., Liu X.Q., Zhou Z.Y., Ni X.G., Qian D.H. Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow-Band Imaging Endoscopy. Laryngoscope. 2022;132:999–1007. doi: 10.1002/lary.29894. [DOI] [PubMed] [Google Scholar]
- 35.Chuang W.Y., Chang S.H., Yu W.H., Yang C.K., Yeh C.J., Ueng S.H., Liu Y.J., Chen T.D., Chen K.H., Hsieh Y.Y., et al. Successful Identification of Nasopharyngeal Carcinoma in Nasopharyngeal Biopsies Using Deep Learning. Cancers. 2020;12:507. doi: 10.3390/cancers12020507. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Hu Z.W., Wang J.C., Gao Q.Q., Wu Z.D., Xu H.C., Guo Z.C., Quan J.W., Zhong L.H., Du M., Tong T., et al. Weakly Supervised Classification for Nasopharyngeal Carcinoma with Transformer in Whole Slide Images. IEEE J. Biomed. Health. 2024;28:7251–7262. doi: 10.1109/JBHI.2024.3422874. [DOI] [PubMed] [Google Scholar]
- 37.Lin Y.B., Yang Z.N., Chen J.C., Li M., Cai Z.M., Wang X., Zhai T.T., Lin Z.X. A contrast-enhanced CT radiomics-based model to identify candidates for deintensified chemoradiotherapy in locoregionally advanced nasopharyngeal carcinoma patients. Eur. Radiol. 2024;34:1302–1313. doi: 10.1007/s00330-023-09987-1. [DOI] [PubMed] [Google Scholar]
- 38.Ouyang P.Y., He Y., Guo J.G., Liu J.N., Wang Z.L., Li A.W., Li J.J., Yang S.S., Zhang X., Fan W., et al. Artificial intelligence aided precise detection of local recurrence on MRI for nasopharyngeal carcinoma: A multicenter cohort study. eClinicalMedicine. 2023;63:102202. doi: 10.1016/j.eclinm.2023.102202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Expert Committee of Nasopharyngeal Cancer Biomarker. Tumor Biomarker Committee of China Anti-Cancer Association Expert consensus on the clinical application of nasopharyngeal carcinoma biomarkers. Chin. J. Oncol. Prev. Treat. 2019;11:183–193. doi: 10.3969/j.issn.1674-5671.2019.03.01. [DOI] [Google Scholar]
- 40.Yao J.J., Lin L., Jin Y.N., Wang S.Y., Zhang W.J., Zhang F., Zhou G.Q., Cheng Z.B., Qi Z.Y., Sun Y. Prognostic value of serum Epstein-Barr virus antibodies in patients with nasopharyngeal carcinoma and undetectable pretreatment Epstein-Barr virus DNA. Cancer Sci. 2017;108:1640–1647. doi: 10.1111/cas.13296. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Chen Y., Zhao W., Lin L., Xiao X., Zhou X., Ming H., Huang T., Liao J., Li Y., Zeng X., et al. Nasopharyngeal Epstein-Barr Virus Load: An Efficient Supplementary Method for Population-Based Nasopharyngeal Carcinoma Screening. PLoS ONE. 2015;10:e0132669. doi: 10.1371/journal.pone.0132669. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Alanazi A.E., Alhumaidy A.A., Almutairi H., Awadalla M.E., Alkathiri A., Alarjani M., Aldawsari M.A., Maniah K., Alahmadi R.M., Alanazi B.S., et al. Evolutionary analysis of LMP-1 genetic diversity in EBV-associated nasopharyngeal carcinoma: Bioinformatic insights into oncogenic potential. Infect. Genet. Evol. 2024;120:105586. doi: 10.1016/j.meegid.2024.105586. [DOI] [PubMed] [Google Scholar]
- 43.Tang L.L., Chen Y.P., Chen C.B., Chen M.Y., Chen N.Y., Chen X.Z., Du X.J., Fang W.F., Feng M., Gao J., et al. The Chinese Society of Clinical Oncology (CSCO) clinical guidelines for the diagnosis and treatment of nasopharyngeal carcinoma. Cancer Commun. 2021;41:1195–1227. doi: 10.1002/cac2.12218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Ji M.F., Sheng W., Cheng W.M., Ng M.H., Wu B.H., Yu X., Wei K.R., Li F.G., Lian S.F., Wang P.P., et al. Incidence and mortality of nasopharyngeal carcinoma: Interim analysis of a cluster randomized controlled screening trial (PRO-NPC-001) in southern China. Ann. Oncol. 2019;30:1630–1637. doi: 10.1093/annonc/mdz231. [DOI] [PubMed] [Google Scholar]
- 45.Prayongrat A., Chakkabat C., Kannarunimit D., Hansasuta P., Lertbutsayanukul C. Prevalence and significance of plasma Epstein-Barr Virus DNA level in nasopharyngeal carcinoma. J. Radiat. Res. 2017;58:509–516. doi: 10.1093/jrr/rrw128. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Zheng X.H., Li X.Z., Zhou T., Jiang C.T., Tang C.L., Deng C.M., Liao Y., He Y.Q., Wang T.M., Jia W.H. Quantitative detection of Epstein-Barr virus DNA methylation in the diagnosis of nasopharyngeal carcinoma by blind brush sampling. Int. J. Cancer. 2023;152:2629–2638. doi: 10.1002/ijc.34491. [DOI] [PubMed] [Google Scholar]
- 47.Leung S.F., Chan K.C., Ma B.B., Hui E.P., Mo F., Chow K.C., Leung L., Chu K.W., Zee B., Lo Y.M., et al. Plasma Epstein-Barr viral DNA load at midpoint of radiotherapy course predicts outcome in advanced-stage nasopharyngeal carcinoma. Ann. Oncol. 2014;25:1204–1208. doi: 10.1093/annonc/mdu117. [DOI] [PubMed] [Google Scholar]
- 48.Wang W.Y., Twu C.W., Chen H.H., Jiang R.S., Wu C.T., Liang K.L., Shih Y.T., Chen C.C., Lin P.J., Liu Y.C., et al. Long-term survival analysis of nasopharyngeal carcinoma by plasma Epstein-Barr virus DNA levels. Cancer. 2013;119:963–970. doi: 10.1002/cncr.27853. [DOI] [PubMed] [Google Scholar]
- 49.Huang C.L., Sun Z.Q., Guo R., Liu X., Mao Y.P., Peng H., Tian L., Lin A.H., Li L., Shao J.Y., et al. Plasma Epstein-Barr Virus DNA Load After Induction Chemotherapy Predicts Outcome in Locoregionally Advanced Nasopharyngeal Carcinoma. Int. J. Radiat. Oncol. Biol. Phys. 2019;104:355–361. doi: 10.1016/j.ijrobp.2019.01.007. [DOI] [PubMed] [Google Scholar]
- 50.Chen F.P., Huang X.D., Lv J.W., Wen D.W., Zhou G.Q., Lin L., Kou J., Wu C.F., Chen Y., Zheng Z.Q., et al. Prognostic potential of liquid biopsy tracking in the posttreatment surveillance of patients with nonmetastatic nasopharyngeal carcinoma. Cancer. 2020;126:2163–2173. doi: 10.1002/cncr.32770. [DOI] [PubMed] [Google Scholar]
- 51.Liang T., Liu W., Xie J., Wang Y., Chen G., Liao W., Song L., Zhang X. Serum EA-IgA and D-dimer, but not VCA-IgA, are associated with prognosis in patients with nasopharyngeal carcinoma: A meta-analysis. Cancer Cell Int. 2021;21:329. doi: 10.1186/s12935-021-02035-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Kanakry J.A., Hegde A.M., Durand C.M., Massie A.B., Greer A.E., Ambinder R.F., Valsamakis A. The clinical significance of EBV DNA in the plasma and peripheral blood mononuclear cells of patients with or without EBV diseases. Blood. 2016;127:2007–2017. doi: 10.1182/blood-2015-09-672030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Zhou Z., Li P., Zhang X., Xu J., Xu J., Yu S., Wang D., Dong W., Cao X., Yan H., et al. Mutational landscape of nasopharyngeal carcinoma based on targeted next-generation sequencing: Implications for predicting clinical outcomes. Mol. Med. 2022;28:55. doi: 10.1186/s10020-022-00479-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Claudio P.P., Howard C.M., Fu Y., Cinti C., Califano L., Micheli P., Mercer E.W., Caputi M., Giordano A. Mutations in the retinoblastoma-related gene RB2/p130 in primary nasopharyngeal carcinoma. Cancer Res. 2000;60:8–12. [PubMed] [Google Scholar]
- 55.Tao Q., Chan A.T. Nasopharyngeal carcinoma: Molecular pathogenesis and therapeutic developments. Expert. Rev. Mol. Med. 2007;9:1–24. doi: 10.1017/S1462399407000312. [DOI] [PubMed] [Google Scholar]
- 56.Huang Z., Desper R., Schaffer A.A., Yin Z., Li X., Yao K. Construction of tree models for pathogenesis of nasopharyngeal carcinoma. Genes Chromosomes Cancer. 2004;40:307–315. doi: 10.1002/gcc.20036. [DOI] [PubMed] [Google Scholar]
- 57.Wang F.H., Wei X.L., Feng J.F., Li Q., Xu N., Hu X.C., Liao W.J., Jiang Y., Lin X.Y., Zhang Q.Y., et al. Efficacy, Safety, and Correlative Biomarkers of Toripalimab in Previously Treated Recurrent or Metastatic Nasopharyngeal Carcinoma: A Phase II Clinical Trial (POLARIS-02) J. Clin. Oncol. 2021;39:704–712. doi: 10.1200/JCO.20.02712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Fan C.S., Wong N., Leung S.F., To K.F., Lo K.W., Lee S.W., Mok T.S., Johnson P.J., Huang D.P. Frequent c-myc and Int-2 overrepresentations in nasopharyngeal carcinoma. Hum. Pathol. 2000;31:169–178. doi: 10.1016/S0046-8177(00)80216-6. [DOI] [PubMed] [Google Scholar]
- 59.Dai W., Zheng H., Cheung A.K., Lung M.L. Genetic and epigenetic landscape of nasopharyngeal carcinoma. Chin. Clin. Oncol. 2016;5:16. doi: 10.21037/cco.2016.03.06. [DOI] [PubMed] [Google Scholar]
- 60.Hui A.B.Y., Or Y.Y.Y., Takano H., Tsang R.K.Y., To K.F., Guan X.Y., Sham J.S.T., Hung K.W.K., Lam C.N.Y., van Hasselt C.A., et al. Array-based comparative genomic hybridization analysis identified cyclin D1 as a target oncogene at 11q13.3 in nasopharyngeal carcinoma. Cancer Res. 2005;65:8125–8133. doi: 10.1158/0008-5472.CAN-05-0648. [DOI] [PubMed] [Google Scholar]
- 61.Fendri A., Khabir A., Mnejja W., Sellami-Boudawara T., Daoud J., Frikha M., Ghorbel A., Gargouri A., Mokdad-Gargouri R. PIK3CA amplification is predictive of poor prognosis in Tunisian patients with nasopharyngeal carcinoma. Cancer Sci. 2009;100:2034–2039. doi: 10.1111/j.1349-7006.2009.01292.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Bruce J.P., To K.F., Lui V.W.Y., Chung G.T.Y., Chan Y.Y., Tsang C.M., Yip K.Y., Ma B.B.Y., Woo J.K.S., Hui E.P., et al. Whole-genome profiling of nasopharyngeal carcinoma reveals viral-host co-operation in inflammatory NF-kappaB activation and immune escape. Nat. Commun. 2021;12:4193. doi: 10.1038/s41467-021-24348-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Chen J., Jiang C., Fu L., Zhu C.L., Xiang Y.Q., Jiang L.X., Chen Q., Liu W.M., Chen J.N., Zhang L.Y., et al. CHL1 suppresses tumor growth and metastasis in nasopharyngeal carcinoma by repressing PI3K/AKT signaling pathway via interaction with Integrin beta1 and Merlin. Int. J. Biol. Sci. 2019;15:1802–1815. doi: 10.7150/ijbs.34785. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Zhao Y., Li J., Dian M., Bie Y., Peng Z., Zhou Y., Zhou B., Hao W., Wang X. Role of N6-methyladenosine methylation in nasopharyngeal carcinoma: Current insights and future prospective. Cell Death Discov. 2024;10:490. doi: 10.1038/s41420-024-02266-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Moore L.D., Le T., Fan G. DNA methylation and its basic function. Neuropsychopharmacology. 2013;38:23–38. doi: 10.1038/npp.2012.112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Zhang J., Zheng Z.Q., Yuan Y.W., Zhang P.P., Li Y.Q., Wang Y.Q., Tang X.R., Wen X., Hong X.H., Lei Y., et al. NFAT1 Hypermethylation Promotes Epithelial-Mesenchymal Transition and Metastasis in Nasopharyngeal Carcinoma by Activating ITGA6 Transcription. Neoplasia. 2019;21:311–321. doi: 10.1016/j.neo.2019.01.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Lu Y., Zhou X., Zhao W., Liao Z., Li B., Han P., Yang Y., Zhong X., Mo Y., Li P., et al. Epigenetic Inactivation of Acetyl-CoA Acetyltransferase 1 Promotes the Proliferation and Metastasis in Nasopharyngeal Carcinoma by Blocking Ketogenesis. Front. Oncol. 2021;11:667673. doi: 10.3389/fonc.2021.667673. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Chen Y., Zhao Y., Yang X., Ren X., Huang S., Gong S., Tan X., Li J., He S., Li Y., et al. USP44 regulates irradiation-induced DNA double-strand break repair and suppresses tumorigenesis in nasopharyngeal carcinoma. Nat. Commun. 2022;13:501. doi: 10.1038/s41467-022-28158-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Long Z.Q., Ding R., Quan T.Q., Xu R., Huang Z.H., Wei D., Zheng W.H., Sun Y. Multi-Omics Characterization of Genome-Wide Abnormal DNA Methylation Reveals FGF5 as a Diagnosis of Nasopharyngeal Carcinoma Recurrence After Radiotherapy. Biomolecules. 2025;15:283. doi: 10.3390/biom15020283. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Liu Y., Zhou H., Yu Q., Wang Q. Hypomethylation-associated ELF3 helps nasopharyngeal carcinoma to escape immune surveillance via MUC16-mediated glycolytic metabolic reprogramming. Am. J. Physiol. Cell Physiol. 2024;327:C1125–C1142. doi: 10.1152/ajpcell.00438.2024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Lin Z., Deng L., Ji J., Cheng C., Wan X., Jiang R., Tang J., Zhuo H., Sun B., Chen Y. S100A4 hypomethylation affects epithelial-mesenchymal transition partially induced by LMP2A in nasopharyngeal carcinoma. Mol. Carcinog. 2016;55:1467–1476. doi: 10.1002/mc.22389. [DOI] [PubMed] [Google Scholar]
- 72.Loyo M., Brait M., Kim M.S., Ostrow K.L., Jie C.C., Chuang A.Y., Califano J.A., Liegeois N.J., Begum S., Westra W.H., et al. A survey of methylated candidate tumor suppressor genes in nasopharyngeal carcinoma. Int. J. Cancer. 2011;128:1393–1403. doi: 10.1002/ijc.25443. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Xu Y., Zhao W., Mo Y., Ma N., Midorikawa K., Kobayashi H., Hiraku Y., Oikawa S., Zhang Z., Huang G., et al. Combination of RERG and ZNF671 methylation rates in circulating cell-free DNA: A novel biomarker for screening of nasopharyngeal carcinoma. Cancer Sci. 2020;111:2536–2545. doi: 10.1111/cas.14431. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 74.Yang X., Dai W., Kwong D.L., Szeto C.Y., Wong E.H., Ng W.T., Lee A.W., Ngan R.K., Yau C.C., Tung S.Y., et al. Epigenetic markers for noninvasive early detection of nasopharyngeal carcinoma by methylation-sensitive high resolution melting. Int. J. Cancer. 2015;136:E127–E135. doi: 10.1002/ijc.29192. [DOI] [PubMed] [Google Scholar]
- 75.Tang C.L., Li X.Z., Zhang Y.M., Zhou T., Yang X.J., Liao Y., Wang T.M., He Y.Q., Xue W.Q., Jia W.H., et al. Blind Brush Biopsy: Quantification of Epstein-Barr Virus and Its Host DNA Methylation in the Detection of Nasopharyngeal Carcinoma. Research. 2024;7:0475. doi: 10.34133/research.0475. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 76.Lyu J.Y., Chen J.Y., Zhang X.J., Zhang M.W., Yu G.S., Zhang L., Wen Z. Septin 9 Methylation in Nasopharyngeal Swabs: A Potential Minimally Invasive Biomarker for the Early Detection of Nasopharyngeal Carcinoma. Dis. Markers. 2020;2020:7253531. doi: 10.1155/2020/7253531. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Jiang W., Liu N., Chen X.Z., Sun Y., Li B., Ren X.Y., Qin W.F., Jiang N., Xu Y.F., Li Y.Q., et al. Genome-Wide Identification of a Methylation Gene Panel as a Prognostic Biomarker in Nasopharyngeal Carcinoma. Mol. Cancer Ther. 2015;14:2864–2873. doi: 10.1158/1535-7163.MCT-15-0260. [DOI] [PubMed] [Google Scholar]
- 78.Ren X., Yang X., Cheng B., Chen X., Zhang T., He Q., Li B., Li Y., Tang X., Wen X., et al. HOPX hypermethylation promotes metastasis via activating SNAIL transcription in nasopharyngeal carcinoma. Nat. Commun. 2017;8:14053. doi: 10.1038/ncomms14053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 79.Hamidi A.A., Zangoue M., Kashani D., Zangouei A.S., Rahimi H.R., Abbaszadegan M.R., Moghbeli M. MicroRNA-217: A therapeutic and diagnostic tumor marker. Expert Rev. Mol. Diagn. 2022;22:61–76. doi: 10.1080/14737159.2022.2017284. [DOI] [PubMed] [Google Scholar]
- 80.Akhlaghipour I., Taghehchian N., Zangouei A.S., Maharati A., Mahmoudian R.A., Saburi E., Moghbeli M. MicroRNA-377: A therapeutic and diagnostic tumor marker. Int. J. Biol. Macromol. 2023;226:1226–1235. doi: 10.1016/j.ijbiomac.2022.11.236. [DOI] [PubMed] [Google Scholar]
- 81.Rahimi H.R., Abbaszadegan M.R., Moghbeli M. MicroRNA-96: A therapeutic and diagnostic tumor marker. Iran. J. Basic Med. Sci. 2022;25:3–13. doi: 10.22038/Ijbms.2021.59604.13226. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Wang J., Ge J., Wang Y., Xiong F., Guo J., Jiang X., Zhang L., Deng X., Gong Z., Zhang S., et al. EBV miRNAs BART11 and BART17-3p promote immune escape through the enhancer-mediated transcription of PD-L1. Nat. Commun. 2022;13:866. doi: 10.1038/s41467-022-28479-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Zhang T., Chen Z., Deng J., Xu K., Che D., Lin J., Jiang P., Gu X., Xu B. Epstein-Barr virus-encoded microRNA BART22 serves as novel biomarkers and drives malignant transformation of nasopharyngeal carcinoma. Cell Death Dis. 2022;13:664. doi: 10.1038/s41419-022-05107-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.Zhu Q., Zhang Q., Gu M., Zhang K., Xia T., Zhang S., Chen W., Yin H., Yao H., Fan Y., et al. MIR106A-5p upregulation suppresses autophagy and accelerates malignant phenotype in nasopharyngeal carcinoma. Autophagy. 2021;17:1667–1683. doi: 10.1080/15548627.2020.1781368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Zou X., Zhu D., Zhang H., Zhang S., Zhou X., He X., Zhu J., Zhu W. MicroRNA expression profiling analysis in serum for nasopharyngeal carcinoma diagnosis. Gene. 2020;727:144243. doi: 10.1016/j.gene.2019.144243. [DOI] [PubMed] [Google Scholar]
- 86.Liu N., Cui R.X., Sun Y., Guo R., Mao Y.P., Tang L.L., Jiang W., Liu X., Cheng Y.K., He Q.M., et al. A four-miRNA signature identified from genome-wide serum miRNA profiling predicts survival in patients with nasopharyngeal carcinoma. Int. J. Cancer. 2014;134:1359–1368. doi: 10.1002/ijc.28468. [DOI] [PubMed] [Google Scholar]
- 87.Lin C., Lin K., Zhang B., Su Y., Guo Q., Lu T., Xu Y., Lin S., Zong J., Pan J. Plasma Epstein-Barr Virus MicroRNA BART8-3p as a Diagnostic and Prognostic Biomarker in Nasopharyngeal Carcinoma. Oncologist. 2022;27:e340–e349. doi: 10.1093/oncolo/oyac024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Wang H., Wei X., Wu B., Su J., Tan W., Yang K. Tumor-educated platelet miR-34c-3p and miR-18a-5p as potential liquid biopsy biomarkers for nasopharyngeal carcinoma diagnosis. Cancer Manag. Res. 2019;11:3351–3360. doi: 10.2147/CMAR.S195654. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Wu L., Zheng K., Yan C., Pan X., Liu Y., Liu J., Wang F., Guo W., He X., Li J., et al. Genome-wide study of salivary microRNAs as potential noninvasive biomarkers for detection of nasopharyngeal carcinoma. BMC Cancer. 2019;19:843. doi: 10.1186/s12885-019-6037-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Huang G., Zhao N., Wu J., Zhou X., Liu W. Labeling and Diagnostic Value of miRNA-28-3p in Patients with Nasopharyngeal Carcinoma. Altern. Ther. Health Med. 2024;30:84–89. [PubMed] [Google Scholar]
- 91.Hao Y., Li J., Zhang H., Guan G., Guo Y. MicroRNA-205 targets HER3 and suppresses the growth, chemosensitivity and metastasis of human nasopharyngeal carcinoma cells. J. BUON. 2020;25:350–356. [PubMed] [Google Scholar]
- 92.Lv B., Li F., Liu X., Lin L. The tumor-suppressive role of microRNA-873 in nasopharyngeal carcinoma correlates with downregulation of ZIC2 and inhibition of AKT signaling pathway. Cancer Gene Ther. 2021;28:74–88. doi: 10.1038/s41417-020-0185-8. [DOI] [PubMed] [Google Scholar]
- 93.Nemeth K., Bayraktar R., Ferracin M., Calin G.A. Non-coding RNAs in disease: From mechanisms to therapeutics. Nat. Rev. Genet. 2024;25:211–232. doi: 10.1038/s41576-023-00662-1. [DOI] [PubMed] [Google Scholar]
- 94.St Laurent G., Wahlestedt C., Kapranov P. The Landscape of long noncoding RNA classification. Trends Genet. 2015;31:239–251. doi: 10.1016/j.tig.2015.03.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.Zheng Z.Q., Li Z.X., Zhou G.Q., Lin L., Zhang L.L., Lv J.W., Huang X.D., Liu R.Q., Chen F.P., He X.J., et al. Long Noncoding RNA FAM225A Promotes Nasopharyngeal Carcinoma Tumorigenesis and Metastasis by Acting as ceRNA to Sponge miR-590-3p/miR-1275 and Upregulate ITGB3. Cancer Res. 2019;79:4612–4626. doi: 10.1158/0008-5472.CAN-19-0799. [DOI] [PubMed] [Google Scholar]
- 96.Zhang S., Liu N., Cao P., Qin Q., Li J., Yang L., Xin Y., Jiang M., Zhang S., Yang J., et al. LncRNA BC200 promotes the development of EBV-associated nasopharyngeal carcinoma by competitively binding to miR-6834-5p to upregulate TYMS expression. Int. J. Biol. Macromol. 2024;278:134837. doi: 10.1016/j.ijbiomac.2024.134837. [DOI] [PubMed] [Google Scholar]
- 97.Xu Q., Wen X., Huang C., Lin Z., Xu Z., Sun C., Li L., Zhang S., Song S., Lou J., et al. RRFERV stabilizes TEAD1 expression to mediate nasopharyngeal cancer radiation resistance rendering tumor cells vulnerable to ferroptosis. Int. J. Surg. 2024;111:450–466. doi: 10.1097/JS9.0000000000002099. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.He Y., Jing Y., Wei F., Tang Y., Yang L., Luo J., Yang P., Ni Q., Pang J., Liao Q., et al. Long non-coding RNA PVT1 predicts poor prognosis and induces radioresistance by regulating DNA repair and cell apoptosis in nasopharyngeal carcinoma. Cell Death Dis. 2018;9:235. doi: 10.1038/s41419-018-0265-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Mi J., Wang Y., He S., Qin X., Li Z., Zhang T., Huang W., Wang R. LncRNA HOTAIRM1 promotes radioresistance in nasopharyngeal carcinoma by modulating FTO acetylation-dependent alternative splicing of CD44. Neoplasia. 2024;56:101034. doi: 10.1016/j.neo.2024.101034. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 100.Li W., Wu X., She W. LncRNA POU3F3 promotes cancer cell migration and invasion in nasopharyngeal carcinoma by up-regulating TGF-beta1. Biosci. Rep. 2019;39:BSR20181632. doi: 10.1042/BSR20181632. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101.He B., Zeng J., Chao W., Chen X., Huang Y., Deng K., Huang Z., Li J., Dai M., Chen S., et al. Serum long non-coding RNAs MALAT1, AFAP1-AS1 and AL359062 as diagnostic and prognostic biomarkers for nasopharyngeal carcinoma. Oncotarget. 2017;8:41166–41177. doi: 10.18632/oncotarget.17083. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 102.Lin S.J., Chang K.P., Hsu C.W., Chi L.M., Chien K.Y., Liang Y., Tsai M.H., Lin Y.T., Yu J.S. Low-molecular-mass secretome profiling identifies C-C motif chemokine 5 as a potential plasma biomarker and therapeutic target for nasopharyngeal carcinoma. J. Proteom. 2013;94:186–201. doi: 10.1016/j.jprot.2013.09.013. [DOI] [PubMed] [Google Scholar]
- 103.Liao Q., Zhao L., Chen X., Deng Y., Ding Y. Serum proteome analysis for profiling protein markers associated with carcinogenesis and lymph node metastasis in nasopharyngeal carcinoma. Clin. Exp. Metastasis. 2008;25:465–476. doi: 10.1007/s10585-008-9152-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104.Cheng A.L., Huang W.G., Chen Z.C., Peng F., Zhang P.F., Li M.Y., Li F., Li J.L., Li C., Yi H., et al. Identification of novel nasopharyngeal carcinoma biomarkers by laser capture microdissection and proteomic analysis. Clin. Cancer Res. 2008;14:435–445. doi: 10.1158/1078-0432.CCR-07-1215. [DOI] [PubMed] [Google Scholar]
- 105.Liu L., Zuo L., Yang J., Xin S., Zhang J., Zhou J., Li G., Tang J., Lu J. Exosomal cyclophilin A as a novel noninvasive biomarker for Epstein-Barr virus associated nasopharyngeal carcinoma. Cancer Med. 2019;8:3142–3151. doi: 10.1002/cam4.2185. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 106.Tang L.Q., Li C.F., Chen Q.Y., Zhang L., Lai X.P., He Y., Xu Y.X., Hu D.P., Wen S.H., Peng Y.T., et al. High-sensitivity C-reactive protein complements plasma Epstein-Barr virus deoxyribonucleic acid prognostication in nasopharyngeal carcinoma: A large-scale retrospective and prospective cohort study. Int. J. Radiat. Oncol. Biol. Phys. 2015;91:325–336. doi: 10.1016/j.ijrobp.2014.10.005. [DOI] [PubMed] [Google Scholar]
- 107.Feng X., Zhang J., Chen W.N., Ching C.B. Proteome profiling of Epstein-Barr virus infected nasopharyngeal carcinoma cell line: Identification of potential biomarkers by comparative iTRAQ-coupled 2D LC/MS-MS analysis. J. Proteom. 2011;74:567–576. doi: 10.1016/j.jprot.2011.01.017. [DOI] [PubMed] [Google Scholar]
- 108.Huang H., Yao Y., Deng X., Huang Z., Chen Y., Wang Z., Hong H., Huang H., Lin T. Immunotherapy for nasopharyngeal carcinoma: Current status and prospects (Review) Int. J. Oncol. 2023;63:97. doi: 10.3892/ijo.2023.5545. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Liu X., Zhang Y., Yang K.Y., Zhang N., Jin F., Zou G.R., Zhu X.D., Xie F.Y., Liang X.Y., Li W.F., et al. Induction-concurrent chemoradiotherapy with or without sintilimab in patients with locoregionally advanced nasopharyngeal carcinoma in China (CONTINUUM): A multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial. Lancet. 2024;403:2720–2731. doi: 10.1016/S0140-6736(24)00594-4. [DOI] [PubMed] [Google Scholar]
- 110.Van D.N., Viet S.N., Phu G.H. Gemcitabine and cisplatin induction chemotherapy followed by concurrent chemoradiotherapy for stage III–IVA nasopharyngeal carcinoma: A real-world study. Sci. Prog. 2025;108:368504241312582. doi: 10.1177/00368504241312582. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 111.Comoli P., Pedrazzoli P., Maccario R., Basso S., Carminati O., Labirio M., Schiavo R., Secondino S., Frasson C., Perotti C., et al. Cell therapy of stage IV nasopharyngeal carcinoma with autologous Epstein-Barr virus-targeted cytotoxic T lymphocytes. J. Clin. Oncol. 2005;23:8942–8949. doi: 10.1200/JCO.2005.02.6195. [DOI] [PubMed] [Google Scholar]
- 112.Louis C.U., Straathof K., Bollard C.M., Ennamuri S., Gerken C., Lopez T.T., Huls M.H., Sheehan A., Wu M.F., Liu H., et al. Adoptive transfer of EBV-specific T cells results in sustained clinical responses in patients with locoregional nasopharyngeal carcinoma. J. Immunother. 2010;33:983–990. doi: 10.1097/CJI.0b013e3181f3cbf4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 113.Chia W.K., Teo M., Wang W.W., Lee B., Ang S.F., Tai W.M., Chee C.L., Ng J., Kan R., Lim W.T., et al. Adoptive T-cell transfer and chemotherapy in the first-line treatment of metastatic and/or locally recurrent nasopharyngeal carcinoma. Mol. Ther. 2014;22:132–139. doi: 10.1038/mt.2013.242. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 114.Mai H.Q., Chen Q.Y., Chen D., Hu C., Yang K., Wen J., Li J., Shi Y., Jin F., Xu R., et al. Toripalimab Plus Chemotherapy for Recurrent or Metastatic Nasopharyngeal Carcinoma: The JUPITER-02 Randomized Clinical Trial. JAMA. 2023;330:1961–1970. doi: 10.1001/jama.2023.20181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115.Liao C., Li M., Chen X., Tang C., Quan J., Bode A.M., Cao Y., Luo X. Anoikis resistance and immune escape mediated by Epstein-Barr virus-encoded latent membrane protein 1-induced stabilization of PGC-1alpha promotes invasion and metastasis of nasopharyngeal carcinoma. J. Exp. Clin. Cancer Res. 2023;42:261. doi: 10.1186/s13046-023-02835-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 116.Yang Y., Qu S., Li J., Hu C., Xu M., Li W., Zhou T., Shen L., Wu H., Lang J., et al. Camrelizumab versus placebo in combination with gemcitabine and cisplatin as first-line treatment for recurrent or metastatic nasopharyngeal carcinoma (CAPTAIN-1st): A multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol. 2021;22:1162–1174. doi: 10.1016/S1470-2045(21)00302-8. [DOI] [PubMed] [Google Scholar]
- 117.Yang Y., Pan J., Wang H., Zhao Y., Qu S., Chen N., Chen X., Sun Y., He X., Hu C., et al. Tislelizumab plus chemotherapy as first-line treatment for recurrent or metastatic nasopharyngeal cancer: A multicenter phase 3 trial (RATIONALE-309) Cancer Cell. 2023;41:1061–1072.e4. doi: 10.1016/j.ccell.2023.04.014. [DOI] [PubMed] [Google Scholar]
- 118.Aggarwal V., Workman C.J., Vignali D.A.A. LAG-3 as the third checkpoint inhibitor. Nat. Immunol. 2023;24:1415–1422. doi: 10.1038/s41590-023-01569-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 119.Huang P.Y., Guo S.S., Zhang Y., Lu J.B., Chen Q.Y., Tang L.Q., Zhang L., Liu L.T., Zhang L., Mai H.Q. Tumor CTLA-4 overexpression predicts poor survival in patients with nasopharyngeal carcinoma. Oncotarget. 2016;7:13060–13068. doi: 10.18632/oncotarget.7421. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 120.Huang R.Y., Francois A., McGray A.R., Miliotto A., Odunsi K. Compensatory upregulation of PD-1, LAG-3, and CTLA-4 limits the efficacy of single-agent checkpoint blockade in metastatic ovarian cancer. Oncoimmunology. 2017;6:e1249561. doi: 10.1080/2162402X.2016.1249561. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 121.Lim D.W., Kao H.F., Suteja L., Li C.H., Quah H.S., Tan D.S., Tan S.H., Tan E.H., Tan W.L., Lee J.N., et al. Clinical efficacy and biomarker analysis of dual PD-1/CTLA-4 blockade in recurrent/metastatic EBV-associated nasopharyngeal carcinoma. Nat. Commun. 2023;14:2781. doi: 10.1038/s41467-023-38407-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 122.Jiang Y., Bei W., Wang L., Lu N., Xu C., Liang H., Ke L., Ye Y., He S., Dong S., et al. Efficacy and safety of cadonilimab (PD-1/CTLA-4 bispecific) in combination with chemotherapy in anti-PD-1-resistant recurrent or metastatic nasopharyngeal carcinoma: A single-arm, open-label, phase 2 trial. BMC Med. 2025;23:152. doi: 10.1186/s12916-025-03985-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 123.Zhao Y., Ma Y., Zang A., Cheng Y., Zhang Y., Wang X., Chen Z., Qu S., He J., Chen C., et al. First-in-human phase I/Ib study of QL1706 (PSB205), a bifunctional PD1/CTLA4 dual blocker, in patients with advanced solid tumors. J. Hematol. Oncol. 2023;16:50. doi: 10.1186/s13045-023-01445-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 124.Chen G., Sun D.C., Ba Y., Zhang Y.X., Zhou T., Zhao Y.Y., Zhao H.Y., Fang W.F., Huang Y., Wang Z., et al. Anti-LAG-3 antibody LBL-007 plus anti-PD-1 antibody toripalimab in advanced nasopharyngeal carcinoma and other solid tumors: An open-label, multicenter, phase Ib/II trial. J. Hematol. Oncol. 2025;18:15. doi: 10.1186/s13045-025-01666-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 125.Sun C., Kang Y.F., Fang X.Y., Liu Y.N., Bu G.L., Wang A.J., Li Y., Zhu Q.Y., Zhang H., Xie C., et al. A gB nanoparticle vaccine elicits a protective neutralizing antibody response against EBV. Cell Host Microbe. 2023;31:1882–1897.e10. doi: 10.1016/j.chom.2023.09.011. [DOI] [PubMed] [Google Scholar]
- 126.Lin C.L., Lo W.F., Lee T.H., Ren Y., Hwang S.L., Cheng Y.F., Chen C.L., Chang Y.S., Lee S.P., Rickinson A.B., et al. Immunization with Epstein-Barr Virus (EBV) peptide-pulsed dendritic cells induces functional CD8+ T-cell immunity and may lead to tumor regression in patients with EBV-positive nasopharyngeal carcinoma. Cancer Res. 2002;62:6952–6958. [PubMed] [Google Scholar]
- 127.Hui E.P., Taylor G.S., Jia H., Ma B.B., Chan S.L., Ho R., Wong W.L., Wilson S., Johnson B.F., Edwards C., et al. Phase I trial of recombinant modified vaccinia ankara encoding Epstein-Barr viral tumor antigens in nasopharyngeal carcinoma patients. Cancer Res. 2013;73:1676–1688. doi: 10.1158/0008-5472.CAN-12-2448. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 128.Taylor G.S., Jia H., Harrington K., Lee L.W., Turner J., Ladell K., Price D.A., Tanday M., Matthews J., Roberts C., et al. A recombinant modified vaccinia ankara vaccine encoding Epstein-Barr Virus (EBV) target antigens: A phase I trial in UK patients with EBV-positive cancer. Clin. Cancer Res. 2014;20:5009–5022. doi: 10.1158/1078-0432.CCR-14-1122-T. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 129.Shi Y., Li Z., Wang L., Wang H., Liu X., Gu D., Chen X., Liu X., Gong W., Jiang X., et al. Artificial intelligence-assisted detection of nasopharyngeal carcinoma on endoscopic images: A national, multicentre, model development and validation study. Lancet Digit Health. 2025;7:100869. doi: 10.1016/j.landig.2025.03.001. [DOI] [PubMed] [Google Scholar]
- 130.Wu B., Chen X., Cao C. Advances in Nasopharyngeal Carcinoma Staging: From the 7th to the 9th Edition of the TNM System and Future Outlook. Curr. Oncol. Rep. 2025;27:322–332. doi: 10.1007/s11912-025-01651-9. [DOI] [PubMed] [Google Scholar]
- 131.You R., Shen Q., Lin C., Dong K., Liu X., Xu H., Hu W., Xie Y., Xie R., Song X., et al. Single-cell and spatial transcriptomics reveal mechanisms of radioresistance and immune escape in recurrent nasopharyngeal carcinoma. Nat. Genet. 2025;57:1950–1965. doi: 10.1038/s41588-025-02253-8. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analyzed during the current study.


