Establishment of a prognostic model to predict chemotherapy response and identification of RAC3 as a chemotherapeutic target in bladder cancer.

Cisplatin-based chemotherapy is considered the primary treatment option for patients with advanced bladder cancer (BCa). However, the objective response rate to chemotherapy is often unsatisfactory, leading to a poor 5-year survival rate. Furthermore, current strategies for evaluating chemotherapy response and prognosis are limited and inefficient. In this study, we aimed to address these challenges by establishing a chemotherapy response type gene (CRTG) signature consisting of 9 genes and verified the prognostic value of this signature using TCGA and GEO BCa cohorts. The risk scores based on the CRTG signature were found to be associated with advanced clinicopathological status and demonstrated favorable predictive power for chemotherapy response in the TCGA cohort. Meanwhile, tumors with high risk scores exhibited a tendency toward a "cold tumor" phenotype. These tumors showed a low abundance of T cells, CD8+ T cells and cytotoxic lymphocytes, along with a high abundance of cancer-associated fibroblasts. Moreover, they displayed higher mRNA levels of these immune checkpoints: CD200, CD276, CD44, NRP1, PDCD1LG2 (PD-L2), and TNFSF9. Furthermore, we developed a nomogram that integrated the CRTG signature with clinicopathologic risk factors. This nomogram proved to be a more effective tool for predicting the prognosis of BCa patients. Additionally, we identified Rac family small GTPase 3 (RAC3) as a biomarker in our model. RAC3 was found to be overexpressed in chemoresistant BCa tissues and enhance the chemotherapeutic resistance of BCa cells in vitro and in vivo by regulating the PAK1-ERK1/2 pathway. In conclusion, our study presents a novel CRTG model for predicting chemotherapy response and prognosis in BCa. We also highlight the potential of combining chemotherapy with immunotherapy as a promising strategy for chemoresistant BCa and that RAC3 might be a latent target for therapeutic intervention.

A clinically practical model for the preoperative prediction of lymph node metastasis in bladder cancer: a multicohort study.

BACKGROUND: The aim of this study was to construct a clinically practical model to precisely predict lymph node (LN) metastasis in bladder cancer patients. METHODS: Four independent cohorts were included. The least absolute shrinkage and selection operator regression with multivariate logistic regression were applied. The diagnostic efficacy of LN score and CT/MRI was compared by accuracy, sensitivity, specificity, and area under curve (AUC). RESULTS: A total of 606 patients were included to develop a basic prediction model. After multistep gene selection, the LN metastasis prediction model was constructed with 5 genes. The model can accurately predict LN metastasis with an AUC of 0.781. For clinically practical use, we transformed the model into a Fast LN Scoring System using the SYSMH cohort (n = 105). High LN score patients exhibited a 72.2% LN metastasis rate, while low LN score patients showed a 3.4% LN metastasis rate. The LN score achieved a superior accuracy than CT/MRI (0.882 vs. 0.727). Application of LN score can correct the diagnosis of 88% (22/25) patients who were misdiagnosed by CT/MRI. DISCUSSION: The clinically practical LN score can precisely, rapidly, and conveniently predict LN status, which will assist preoperative diagnosis for LN metastasis and guide precise therapy.

LAFITE Reveals the Complexity of Transcript Isoforms in Subcellular Fractions.

Characterization of the subcellular distribution of RNA is essential for understanding the molecular basis of biological processes. Here, the subcellular nanopore direct RNA-sequencing (DRS) of four lung cancer cell lines (A549, H1975, H358, and HCC4006) is performed, coupled with a computational pipeline, Low-abundance Aware Full-length Isoform clusTEr (LAFITE), to comprehensively analyze the full-length cytoplasmic and nuclear transcriptome. Using additional DRS and orthogonal data sets, it is shown that LAFITE outperforms current methods for detecting full-length transcripts, particularly for low-abundance isoforms that are usually overlooked due to poor read coverage. Experimental validation of six novel isoforms exclusively identified by LAFITE further confirms the reliability of this pipeline. By applying LAFITE to subcellular DRS data, the complexity of the nuclear transcriptome is revealed in terms of isoform diversity, 3'-UTR usage, m6A modification patterns, and intron retention. Overall, LAFITE provides enhanced full-length isoform identification and enables a high-resolution view of the RNA landscape at the isoform level.

The Ratio of IL-6 to IL-4 in Synovial Fluid of Knee or Hip Performances a Noteworthy Diagnostic Value in Prosthetic Joint Infection.

The diagnosis of prosthetic joint infection (PJI) is still a challenge, the ratio of interleukin-6 (IL-6) to IL-4 in the joint fluid of knee or hip was used to analyze whether the diagnostic accuracy of PJI can be improved. Between January 2017 and May 2022, 180 patients who developed pain after revision total hip or knee arthroplasty were enrolled retrospectively. 92 patients of PJI and 88 of aseptic failure were included. PJI was as defined by the Musculoskeletal Infection Society (MSIS). The content of IL-6 and IL-4 in synovial fluid of knee or hip were measured, and the areas under the receiver operating characteristic curve (ROC) and IL-6/IL-4 curve were analyzed to obtain a better diagnostic effect. The area under the curve of IL-6/IL-4 in synovial fluid of knee or hip was 0.9623, which was more accurate than ESR 0.5994 and C-reactive protein 0.6720. The optimal threshold of IL-6/IL-4 ratio was 382.10. Its sensitivity and specificity were 81.32% and 98.86%, respectively. The positive predictive value for the diagnosis of PJI was 98.91%. This study showed that the level of IL-6/IL-4 in synovial fluid of knee or hip could further improve the diagnostic accuracy for PJI.

Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis.

Single-cell RNA-sequencing has become a powerful tool to study biologically significant characteristics at explicitly high resolution. However, its application on emerging data is currently limited by its intrinsic techniques. Here, we introduce Tissue-AdaPtive autoEncoder (TAPE), a deep learning method connecting bulk RNA-seq and single-cell RNA-seq to achieve precise deconvolution in a short time. By constructing an interpretable decoder and training under a unique scheme, TAPE can predict cell-type fractions and cell-type-specific gene expression tissue-adaptively. Compared with popular methods on several datasets, TAPE has a better overall performance and comparable accuracy at cell type level. Additionally, it is more robust among different cell types, faster, and sensitive to provide biologically meaningful predictions. Moreover, through the analysis of clinical data, TAPE shows its ability to predict cell-type-specific gene expression profiles with biological significance. We believe that TAPE will enable and accelerate the precise analysis of high-throughput clinical data in a wide range.

Changes in Thromboelastography to Predict Ecchymosis After Knee Arthroplasty: A Promising Guide for the Use of Anticoagulants.

Background: Ecchymosis is one of the worrisome complications after total knee arthroplasty (TKA) and interferes with functional rehabilitation. Current clinical guidelines do not provide individualized approaches for patients with ecchymoses. Methods: In this study, we used thromboelastography (TEG) to determine the coagulation state after TKA and to then explore markers that predict the occurrence of ecchymosis events after TKA. In our cohort, patients were divided into ecchymosis (n = 55) and non-ecchymosis (n = 137) groups according to whether ecchymosis events occurred after TKA. Rivaroxaban 10 mg/d was taken orally for thromboprophylaxis after surgery. All patients completed TEG testing. Correlation analysis was used to determine the risk factors for ecchymosis after TKA, and receiver operating characteristic (ROC) curves for variables with significant correlation were plotted. Results: In all, 55 of the 192 patients (28.65%) developed ecchymosis surrounding the surgical site. Multivariate analysis showed that hidden blood loss (OR = 1.003 and p = 0.005) and changes in the coagulation index (ΔCI) values (OR = 0.351 and p = 0.001) were risk factors for ecchymosis after TKA. Using the Youden index, 0.1805 was determined as the optimal threshold value of ΔCI for predicting the occurrence of ecchymosis, with a sensitivity of 74.55% and specificity of 72.99%. ΔCI is a promising marker as an alarm for the occurrence of ecchymosis after TKA. Trial Registration: The study was registered in the Chinese Clinical Trial Registry (ChiCTR1800017245). Registered name: The role of thrombelastography in monitoring the changes of coagulation function during perioperative period of arthroplasty. Registered 19 July 2018. http://www.chictr.org.cn/showproj.aspx?proj=29220.

HSF1 facilitates the multistep process of lymphatic metastasis in bladder cancer via a novel PRMT5-WDR5-dependent transcriptional program.

BACKGROUND: Lymphatic metastasis has been associated with poor prognosis in bladder cancer patients with limited therapeutic options. Emerging evidence shows that heat shock factor 1 (HSF1) drives diversified transcriptome to promote tumor growth and serves as a promising therapeutic target. However, the roles of HSF1 in lymphatic metastasis remain largely unknown. Herein, we aimed to illustrate the clinical roles and mechanisms of HSF1 in the lymphatic metastasis of bladder cancer and explore its therapeutic potential. METHODS: We screened the most relevant gene to lymphatic metastasis among overexpressed heat shock factors (HSFs) and heat shock proteins (HSPs), and analyzed its clinical relevance in three cohorts. Functional in vitro and in vivo assays were performed in HSF1-silenced and -regained models. We also used Co-immunoprecipitation to identify the binding proteins of HSF1 and chromatin immunoprecipitation and dual-luciferase reporter assays to investigate the transcriptional program directed by HSF1. The pharmacological inhibitor of HSF1, KRIBB11, was evaluated in popliteal lymph node metastasis models and patient-derived xenograft models of bladder cancer. RESULTS: HSF1 expression was positively associated with lymphatic metastasis status, tumor stage, advanced grade, and poor prognosis of bladder cancer. Importantly, HSF1 enhanced the epithelial-mesenchymal transition (EMT) of cancer cells in primary tumor to initiate metastasis, proliferation of cancer cells in lymph nodes, and macrophages infiltration to facilitate multistep lymphatic metastasis. Mechanistically, HSF1 interacted with protein arginine methyltransferase 5 (PRMT5) and jointly induced the monomethylation of histone H3 at arginine 2 (H3R2me1) and symmetric dimethylation of histone H3 at arginine 2 (H3R2me2s). This recruited the WD repeat domain 5 (WDR5)/mixed-lineage leukemia (MLL) complex to increase the trimethylation of histone H3 at lysine 4 (H3K4me3); resulting in upregulation of lymphoid enhancer-binding factor 1 (LEF1), matrix metallopeptidase 9 (MMP9), C-C motif chemokine ligand 20 (CCL20), and E2F transcription factor 2 (E2F2). Application of KRIBB11 significantly inhibited the lymphatic metastasis of bladder cancer with no significant toxicity. CONCLUSION: Our findings reveal a novel transcriptional program directed by the HSF1-PRMT5-WDR5 axis during the multistep process of lymphatic metastasis in bladder cancer. Targeting HSF1 could be a multipotent and promising therapeutic strategy for bladder cancer patients with lymphatic metastasis.

Targeting WD repeat domain 5 enhances chemosensitivity and inhibits proliferation and programmed death-ligand 1 expression in bladder cancer.

BACKGROUND: Chemotherapy and/or immunotherapy are first-line treatments for advanced muscle-invasive bladder cancer (BCa), but the unsatisfactory objective response rate to these treatments yields poor 5-year patient survival. Discovery of therapeutic targets essential for BCa maintenance is critical to improve therapy response in clinic. This study evaluated the role of targeting WD repeat domain 5 (WDR5) with the small molecule compound OICR-9429 and whether it could be used to treat bladder cancer. METHODS: We analysed the expression and clinical prognosis of WDR5 in a TCGA cohort. The pharmacological role of OICR-9429 was further investigated in vitro and in vivo. RNA sequencing, western blot, and chromatin immunoprecipitation (ChIP) were utilized to explored the mechanism underlying OICR-9429-induced WDR5 inhibition. RESULTS: First, we found that WDR5 expression was upregulated in BCa and was associated with histologic grade, metastasis status, histologic subtype, and molecular subtype. High WDR5 expression level was also correlated with shorter overall survival (OS) in BCa. The WDR5 inhibitor OICR-9429 reduced cell viability by decreasing H3K4me3 levels but not WDR5 levels in T24, UM-UC-3, and TCCSUP BCa cells. OICR-9429 suppressed the proliferation of BCa cells by blocking the G1/S phase transition. Next, OICR-9429 enhanced apoptosis and chemosensitivity to cisplatin in BCa cells. In addition, OICR-9429 independently inhibited the motility and metastatic behaviour of BCa cells. In vivo experiments further revealed that OICR-9429 suppressed tumour growth, enhanced chemosensitivity, and reduced the toxicity of cisplatin in BCa. Notably, WDR5 was positively correlated with programmed death-ligand 1 (PD-L1) expression, and OICR-9429 suppressed immune evasion by blocking PD-L1 induced by IFN-γ. Mechanistically, some cell cycle-, antiapoptosis-, DNA repair-, metastasis-, and immune evasion-related genes, including BIRC5, XRCC2, CCNB1, CCNE2, PLK1, AURKA, FOXM1, and PD-L1 were identified to be directly regulated by OICR-9429 in a H3K4me3-dependent manner. CONCLUSIONS: Our novel finding is that the WDR5 inhibitor, OICR-9429, suppressed proliferation, metastasis and PD-L1-based immune evasion while enhancing apoptosis and chemosensitivity to cisplatin in BCa by blocking the WDR5-MLL complex mediating H3K4me3 in target genes. Hence, our findings offer insight into a multipotential anticancer compound, OICR-9429, which enhances the antitumour effect of cisplatin or immunotherapy in BCa.

NONO Inhibits Lymphatic Metastasis of Bladder Cancer via Alternative Splicing of SETMAR.

Bladder cancer patients with lymph node (LN) metastasis have an extremely poor prognosis and no effective treatment. The alternative splicing of precursor (pre-)mRNA participates in the progression of various tumors. However, the precise mechanisms of splicing factors and cancer-related variants in LN metastasis of bladder cancer remain largely unknown. The present study identified a splicing factor, non-POU domain-containing octamer-binding protein (NONO), that was significantly downregulated in bladder cancer tissues and correlated with LN metastasis status, tumor stage, and prognosis. Functionally, NONO markedly inhibited bladder cancer cell migration and invasion in vitro and LN metastasis in vivo. Mechanistically, NONO regulated the exon skipping of SETMAR by binding to its motif, mainly through the RRM2 domain. NONO directly interacted with splicing factor proline/glutamine rich (SFPQ) to regulate the splicing of SETMAR, and it induced metastasis suppression of bladder cancer cells. SETMAR-L overexpression significantly reversed the metastasis of NONO-knockdown bladder cancer cells, both in vitro and in vivo. The further analysis revealed that NONO-mediated SETMAR-L can induce H3K27me3 at the promotor of metastatic oncogenes and inhibit their transcription, ultimately resulting in metastasis suppression. Therefore, the present findings uncover the molecular mechanism of lymphatic metastasis in bladder cancer, which may provide novel clinical markers and therapeutic strategies for LN-metastatic bladder cancer.

Evaluation of synovial fluid neutrophil CD64 index as a screening biomarker of prosthetic joint infection.

AIMS: Prosthetic joint infection (PJI) remains a major clinical challenge. Neutrophil CD64 index, Fc-gamma receptor 1 (FcγR1), plays an important role in mediating inflammation of bacterial infections and therefore could be a valuable biomarker for PJI. The aim of this study is to compare the neutrophil CD64 index in synovial and blood diagnostic ability with the standard clinical tests for discrimination PJI and aseptic implant failure. METHODS: A total of 50 patients undergoing revision hip and knee arthroplasty were enrolled into a prospective study. According to Musculoskeletal Infection Society (MSIS) criteria, 25 patients were classified as infected and 25 as not infected. In all patients, neutrophil CD64 index and percentage of polymorphonuclear neutrophils (PMN%) in synovial fluid, serum CRP, ESR, and serum CD64 index levels were measured preoperatively. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were analyzed for each biomarker. RESULTS: Serum CD64 index showed no significant difference between the two groups (p = 0.091). Synovial fluid CD64 index and PMN% discriminated good differentiation between groups of PJI and aseptic failure with AUC of 0.946 (95% confidence interval (CI) 0.842 to 0.990) and 0.938 (95% CI 0.832 to 0.987) separately. The optimal threshold value of synovial CD64 index for the diagnosis of PJI was 0.85, with a sensitivity of 92.00%, a specificity of 96.00%, and diagnostic odds ratio (DOR) of 227.11. CONCLUSION: The present study demonstrates that CD64 index in synovial fluid could be a promising laboratory marker for screening PJI. The cut-off values of 0.85 for synovial CD64 index has the potential to distinguish aseptic failure from PJI. Cite this article: Bone Joint J 2020;102-B(4):463-469.

Implications of mutational spectrum in myelodysplastic syndromes based on targeted next-generation sequencing.

Myelodysplastic syndromes (MDS) are a group of myeloid hematological malignancies, with a high risk of progression to acute myeloid leukemia (AML). To explore the role of acquired mutations in MDS, 111 MDS-associated genes were screened using next-generation sequencing (NGS), in 125 patients. One or more mutations were detected in 84% of the patients. Some gene mutations are specific for MDS and were associated with disease subtypes, and the patterns of mutational pathways could be associated with progressive MDS. The patterns, frequencies and functional pathways of gene mutations are different, but somehow related, between MDS and AML. Multivariate analysis suggested that patients with ≥ 2 mutations had poor progression-free survival, while GATA1/GATA2, DNMT3A and KRAS/NRAS mutations were associated with poor overall survival. Based on a novel system combining IPSS-R and molecular markers, these MDS patients were further divided into 3 more accurate prognostic subgroups. A panel of 11 target genes was proposed for genetic profiling of MDS. The study offers new insights into the molecular signatures of MDS and the genetic consistency between MDS and AML. Furthermore, results indicate that MDS could be classified by mutation combinations to guide the administration of individualized therapeutic interventions.

Identifying the causative proteins of similar side effect pairs to explore the common molecular basis of these side effects.

Drug side effects, or adverse drug reactions (ADRs), have become a major public health concern and often cause drug development failure and withdrawal. Some ADRs always occur concomitantly. Therefore, identifying these ADRs and their common molecular basis can better promote their prevention and treatment. In this paper we predicted the potential proteins for ADR pairs with similar mechanisms based on three layers of information: (i) the drug co-occurrence between a pair of ADRs; (ii) the correlation between a protein and an ADR pair based on the co-occurrence of drugs and (iii) the interaction between these proteins within the protein-protein interaction (PPI) network. The methods of randomization and functional annotation are used to investigate and analyze the relation between causative proteins and similar ADR pairs. The prediction accuracy of the relation between similar ADR pairs and related proteins reached 80%, and it increases with the number of drugs shared by the ADR pairs. From the ADR network made of single ADRs from predicted similar ADR pairs, we found that some ADRs are involved in multiple ADR pairs. The functional analysis of these ADR-related proteins suggests that a similar molecular basis is shared by multiple ADR pairs containing the same ADR, and these ADR pairs are almost caused by the same drug sets. The results of this study are reliable and provide a theoretical basis for the better prevention and treatment of ADRs that always occur concomitantly.

Drug repositioning by applying 'expression profiles' generated by integrating chemical structure similarity and gene semantic similarity.

Drug repositioning, also known as drug repurposing or reprofiling, is the process of finding new indications for established drugs. Because drug repositioning can reduce costs and enhance the efficiency of drug development, it is of paramount importance in medical research. Here, we present a systematic computational method to identify potential novel indications for a given drug. This method utilizes some prior knowledge such as 3D drug chemical structure information, drug-target interactions and gene semantic similarity information. Its prediction is based on another form of 'expression profile', which contains scores ranging from -1 to 1, reflecting the consensus response scores (CRSs) between each drug of 965 and 1560 proteins. The CRS integrates chemical structure similarity and gene semantic similarity information. We define the degree of similarity between two drugs as the absolute value of their correlation coefficients. Finally, we establish a drug similarity network (DSN) and obtain 33 modules of drugs with similar modes of action, determining their common indications. Using these modules, we predict new indications for 143 drugs and identify previously unknown indications for 42 drugs without ATC codes. This method overcomes the instability of gene expression profiling derived from experiments due to experimental conditions, and predicts indications for a new compound feasibly, requiring only the 3D structure of the compound. In addition, the high literature validation rate of 71.8% also suggests that our method has the potential to discover novel drug indications for existing drugs.

Network characteristic analysis of ADR-related proteins and identification of ADR-ADR associations.

Adverse drug reactions (ADRs) are caused by interactions between drugs or their metabolites and specific proteins. Knowledge of these proteins is important for facilitating mechanistic research of ADRs and new drug discovery. Here, we identified 41 network modules from an ADR-protein network; analysed the function of each module; revealed the potential accompanying actions of the ADRs and the new ADR-related proteins (ADRPs) to a unique ADR and studied the characteristics of composition, subcellular location and tissue distribution of these ADRPs by comparing them with drug-related proteins (DRPs). The results indicated that ADRs are mainly caused by risk drug-related proteins (RDRPs) and that drug off-target effects are a secondary cause. Biological processes that enzymes involve are the main reason for the occurrence of ADRs. However, drug-related transporters have a higher risk of inducing ADRs than drug-related enzymes do, and ADRPs locating in the cell membrane tend to induce multiple ADRs.

Purification and characterization of a naringinase from Aspergillus aculeatus JMUdb058.

A naringinase from Aspergillus aculeatus JMUdb058 was purified, identified, and characterized. This naringinase had a molecular mass (MW) of 348 kDa and contained four subunits with MWs of 100, 95, 84, and 69 kDa. Mass spectrometric analysis revealed that the three larger subunits were ß-D-glucosidases and that the smallest subunit was an α-L-rhamnosidase. The naringinase and its α-L-rhamnosidase and ß-D-glucosidase subunits all had optimal activities at approximately pH 4 and 50 °C, and they were stable between pH 3 and 6 and below 50 °C. This naringinase was able to hydrolyze naringin, aesculin, and some other glycosides. The enzyme complex had a K(m) value of 0.11 mM and a k(cat)/K(m) ratio of 14,034 s(-1) mM(-1) for total naringinase. Its α-L-rhamnosidase and ß-D-glucosidase subunits had K(m) values of 0.23 and 0.53 mM, respectively, and k(cat)/K(m) ratios of 14,146 and 7733 s(-1) mM(-1), respectively. These results provide in-depth insight into the structure of the naringinase complex and the hydrolyses of naringin and other glycosides.

New bibenzyl glycosides from leaves of Camellia oleifera Abel. with cytotoxic activities.

Studies on the chemical constituents of leaves of Camellia oleifera Abel. led to the isolation of 3 new bibenzyl glycosides. Their structures have been elucidated as 1-(3',5'-dihydroxy)phenyl-2-(4″-O-ß-D-glucopyranosyl)phenylethane (1), 1-(3',5'-dimethoxy)phenyl-2-(4″-O-ß-D-glucopyranosyl)phenylethane (2) and 1-(3',5'-dimethoxy)phenyl-2-[4″-O-ß-D-glucopyranosyl(6→1)-O-α-L-rhamnopyranosyl]phenylethane (3) through spectral studies including HR-ESI-MS, ((1))H NMR, ((13))C NMR and 2D NMR experiments. All the above 3 bibenzyl glycosides showed cytotoxic activities to Hela and hep2 cell lines.

Study on sero-diagnosis of nasopharyngeal carcinoma using a dual antibody test against recombinant Epstein-Barr virus antigens.

BACKGROUND & OBJECTIVE: The aim of this study was to optimize a dual-antibody assay for sero-diagnosis of nasopharyngeal carcinoma(NPC) by evaluating 4 Epstein-Barr virus(EBV) antigen-based enzyme-linked immunosorbent assays(ELISAs). METHODS: The serum samples of 57 pretreated NPC patients and 58 apparently healthy adults in Guangzhou were collected. The levels of anti-EBV antibody in the sera were tested by 4 ELISAs, which were developed using fusion proteins of glutathione transferase and EBV specific recombinant antigens, namely, EBNA1-IgA, EBNA1-IgG, Zta-IgA, and Zta-IgG. RESULTS: When evaluated individually, the sensitivity(0.9123) and negative predictive value(0.9074) of EBNA1-IgA were the highest among the 4 ELISAs tested. Zta-IgA test had the highest individual accuracy rate(pi, 0.8870) and Youden index(J, 0.7738). The dual positives for EBNA1-IgA and Zta-IgA were the highest among the 4 dual positives when paired ELISAs were evaluated. Five NPC patients with negative reaction to EBNA1-IgA showed positive reaction of Zta-IgA, and 7 NPC patients with negative reaction to Zta-IgA showed positive reaction of EBNA1-IgA. CONCLUSION: The EBNA1-IgA assay is more suitable than the other 3 ELISAs(EBNA1-IgG, Zta-IgA, and Zta-IgG) when used individually for serological diagnosis of NPC. When two assays are combined, EBNA1-IgA and Zta-IgA have complementary effect on serological diagnosis for NPC and is thus an optimal combination of serum antibody assays.