Caveolin-1 is a scaffolding protein of caveolae, flask-shaped membrane microdomains involved in diverse cellular processes. Caveolae are primarily localized to the plasma membrane, the trans-Golgi network, and mitochondria-associated endoplasmic reticulum (ER) membranes (MAMs). Most enzymes involved in cholesterol biosynthesis reside in the ER, and although caveolin-1 avidly binds cholesterol, its role in cholesterol trafficking remains unclear. Acyl-coenzyme A:cholesterol acyltransferases (ACAT1 and ACAT2) convert free cholesterol into cholesteryl esters for storage, with ACAT1 serving as the predominant isoenzyme in most cell types. ACAT1 is an ER-resident protein, with a fraction associated with specialized ER subdomains, including the MAM. Here, we report that a subset of caveolin-1 molecules appears to be associated with a fraction of ACAT1 in ER subdomains. Using immunoprecipitation under detergent conditions, immunoadsorption of MAM-enriched membranes under detergent-free conditions, and electron microscopy, we provide evidence consistent with an association between a subset of caveolin-1 molecules and ACAT1. Functionally, in mouse embryonic fibroblasts, we show that genetic ablation of caveolin-1 significantly increases the esterification of low-density lipoprotein-derived cholesterol, suggesting that caveolin-1 may attenuate ACAT1 activity. Collectively, these findings indicate that caveolin-1 may modulate cholesterol esterification and contribute to the regulation of cholesterol distribution among cellular membranes.

AbstractBackground: Cure fraction—the proportion of persons considered cured of cancer after long-term follow-up—reflects the total impact of cancer control strategies, including screening, without lead-time bias. Previous studies have not reported stage-stratified cure fraction across the spectrum of cancer types. Methods: Using a mixture cure model, we estimated cure fraction across stages for 21 cancer types and additional subtypes. Cause-specific survival for 2.4 million incident cancers came from 17 US Surveillance, Epidemiology, and End Results registries for adults 40 to 84 years at diagnosis in 2006 to 2015, followed through 2020. Results: Across cancer types, a substantial cure fraction was evident at early stages, followed by either a sharp drop from stages III to IV or a steady decline from stages I to IV. For example, estimated cure fractions for colorectal cancer at stages I, II, III, and IV were 62% (95% confidence interval: 59%–66%), 61% (58%–65%), 58% (57%–59%), and 7% (7%–7%), respectively. Corresponding estimates for gallbladder cancer were 50% (46%–54%), 24% (22%–27%), 22% (19%–25%), and 2% (2%–3%). Differences in 5-year cause-specific survival between early-stage and stage IV cancers were highly correlated with between-stage differences in cure fraction, indicating that survival gaps by stage are persistent and not due to lead-time bias. Conclusions: A considerable fraction of cancer is amenable to cure at early stages, but not after metastasis. Impact: These results emphasize the potential for early detection of numerous cancers, including those with no current screening modalities, to reduce cancer death.

Cholesterol homeostasis is pivotal for cellular function. Acyl-coenzyme A:cholesterol acyltransferase 1 (ACAT1), also abbreviated as SOAT1, is an enzyme responsible for catalyzing the storage of excess cholesterol to cholesteryl esters. ACAT1 is an emerging target to treat diverse diseases including atherosclerosis, cancer, and neurodegenerative diseases. F12511 is a high-affinity ACAT1 inhibitor. Previously, we developed a stealth liposome-based nanoparticle to encapsulate F12511 to enhance its delivery to the brain and showed its efficacy in treating a mouse model for Alzheimer’s disease (AD). In this study, we introduce F26, a close derivative of F12511 metabolite in rats. F26 was encapsulated in the same DSPE-PEG2000/phosphatidylcholine (PC) liposome-based nanoparticle system. We employed various in vitro and in vivo methodologies to assess F26’s efficacy and toxicity compared to F12511. The results demonstrate that F26 is more effective and durable than F12511 in inhibiting ACAT1, in both mouse embryonic fibroblasts (MEFs), and in multiple mouse tissues including the brain tissues, without exhibiting any overt systemic or neurotoxic effects. This study demonstrates the superior pharmacokinetic and safety profile of F26 in wild-type mice, and suggests its therapeutic potential against various neurodegenerative diseases including AD.

Aging and apolipoprotein E4 (APOE4) are the two most significant risk factors for late-onset Alzheimer’s disease (LOAD). Compared to APOE3, APOE4 disrupts cholesterol homeostasis, increases cholesteryl esters (CEs), and exacerbates neuroinflammation in brain cells, including microglia. Targeting CEs and neuroinflammation could be a novel strategy to ameliorate APOE4-dependent phenotypes. Toll-like receptor 4 (TLR4) is a key macromolecule in inflammation, and its regulation is associated with the cholesterol content of lipid rafts in cell membranes. We previously demonstrated that in normal microglia expressing APOE3, inhibiting the cholesterol storage enzyme acyl-CoA:cholesterol acyltransferase 1 (ACAT1/SOAT1) reduces CEs, dampened neuroinflammation via modulating the fate of TLR4. We also showed that treating myelin debris-loaded normal microglia with ACAT inhibitor F12511 reduced cellular CEs and activated ABC transporter 1 (ABCA1) for cholesterol efflux. This study found that treating primary microglia expressing APOE4 with F12511 also reduces CEs, activates ABCA1, and dampens LPS-dependent NFκB activation. In vivo, two-week injections of nanoparticle F12511, which consists of DSPE-PEG2000, phosphatidylcholine, and F12511, to aged female APOE4 mice reduced TLR4 protein content and decreased proinflammatory cytokines, including IL-1β in mice brains. Overall, our work suggests nanoparticle F12511 is a novel agent to ameliorate LOAD.

Aging is the major risk factor for Alzheimer’s disease (AD). In the aged brain, myelin debris accumulates and is cleared by microglia. Phagocytosed myelin debris increases neutral lipid droplet content in microglia. Neutral lipids include cholesteryl esters (CE) and triacylglycerol (TAG). To examine the effects of myelin debris on neutral lipid content in microglia, we added myelin debris to human HMC3 and mouse N9 cells. The results obtained when using 3H-oleate as a precursor in intact cells reveal that myelin debris significantly increases the biosynthesis of CE but not TAG. Mass analyses have shown that myelin debris increases both CE and TAG. The increase in CE biosynthesis was abolished using inhibitors of the cholesterol storage enzyme acyl-CoA:cholesterol acyltransferase 1 (ACAT1/SOAT1). ACAT1 inhibitors are promising drug candidates for AD treatment. In myelin debris-loaded microglia, treatment with two different ACAT1 inhibitors, K604 and F12511, increased the mRNA and protein content of ATP-binding cassette subfamily A1 (ABCA1), a protein that is located at the plasma membrane and which controls cellular cholesterol disposal. The effect of the ACAT1 inhibitor on ABCA1 was abolished by preincubating cells with the liver X receptor (LXR) antagonist GSK2033. We conclude that ACAT1 inhibitors prevent the accumulation of cholesterol and CE in myelin debris-treated microglia by activating ABCA1 gene expression via the LXR pathway.

Cholesterol is essential for cellular function and is stored as cholesteryl esters (CEs). CEs biosynthesis is catalyzed by the enzymes acyl-CoA:cholesterol acyltransferase 1 and 2 (ACAT1 and ACAT2), with ACAT1 being the primary isoenzyme in most cells in humans. In Alzheimer's Disease, CEs accumulate in vulnerable brain regions. Therefore, ACATs may be promising targets for treating AD. F12511 is a high-affinity ACAT1 inhibitor that has passed phase 1 safety tests for antiatherosclerosis. Previously, we developed a nanoparticle system to encapsulate a large concentration of F12511 into a stealth liposome (DSPE-PEG2000 with phosphatidylcholine). Here, we injected the nanoparticle encapsulated F12511 (nanoparticle F) intravenously (IV) in wild-type mice and performed an HPLC/MS/MS analysis and ACAT enzyme activity measurement. The results demonstrated that F12511 was present within the mouse brain after a single IV but did not overaccumulate in the brain or other tissues after repeated IVs. A histological examination showed that F12511 did not cause overt neurological or systemic toxicity. We then showed that a 2-week IV delivery of nanoparticle F to aging 3xTg AD mice ameliorated amyloidopathy, reduced hyperphosphorylated tau and nonphosphorylated tau, and reduced neuroinflammation. This work lays the foundation for nanoparticle F to be used as a possible therapy for AD and other neurodegenerative diseases.

Cholesterol is stored as cholesteryl esters by the enzymes acyl-CoA:cholesterol acyltransferases/sterol O:acyltransferases (ACATs/SOATs). ACAT1 blockade (A1B) ameliorates the pro-inflammatory responses of macrophages to lipopolysaccharides (LPS) and cholesterol loading. However, the mediators involved in transmitting the effects of A1B in immune cells is unknown. Microglial Acat1/Soat1 expression is elevated in many neurodegenerative diseases and in acute neuroinflammation. We evaluated LPS-induced neuroinflammation experiments in control vs. myeloid-specific Acat1/Soat1 knockout mice. We also evaluated LPS-induced neuroinflammation in microglial N9 cells with and without pre-treatment with K-604, a selective ACAT1 inhibitor. Biochemical and microscopy assays were used to monitor the fate of Toll-Like Receptor 4 (TLR4), the receptor at the plasma membrane and the endosomal membrane that mediates pro-inflammatory signaling cascades. In the hippocampus and cortex, results revealed that Acat1/Soat1 inactivation in myeloid cell lineage markedly attenuated LPS-induced activation of pro-inflammatory response genes. Studies in microglial N9 cells showed that pre-incubation with K-604 significantly reduced the LPS-induced pro-inflammatory responses. Further studies showed that K-604 decreased the total TLR4 protein content by increasing TLR4 endocytosis, thus enhancing the trafficking of TLR4 to the lysosomes for degradation. We concluded that A1B alters the intracellular fate of TLR4 and suppresses its pro-inflammatory signaling cascade in response to LPS.

Cholesterol is a key component of all mammalian cell membranes. Disruptions in cholesterol metabolism have been observed in the context of various diseases, including neurodegenerative disorders such as Alzheimer's disease (AD). The genetic and pharmacological blockade of acyl-CoA:cholesterol acyltransferase 1/sterol O-acyltransferase 1 (ACAT1/SOAT1), a cholesterol storage enzyme found on the endoplasmic reticulum (ER) and enriched at the mitochondria-associated ER membrane (MAM), has been shown to reduce amyloid pathology and rescue cognitive deficits in mouse models of AD. Additionally, blocking ACAT1/SOAT1 activity stimulates autophagy and lysosomal biogenesis; however, the exact molecular connection between the ACAT1/SOAT1 blockade and these observed benefits remain unknown. Here, using biochemical fractionation techniques, we observe cholesterol accumulation at the MAM which leads to ACAT1/SOAT1 enrichment in this domain. MAM proteomics data suggests that ACAT1/SOAT1 inhibition strengthens the ER-mitochondria connection. Confocal and electron microscopy confirms that ACAT1/SOAT1 inhibition increases the number of ER-mitochondria contact sites and strengthens this connection by shortening the distance between these two organelles. This work demonstrates how directly manipulating local cholesterol levels at the MAM can alter inter-organellar contact sites and suggests that cholesterol buildup at the MAM is the impetus behind the therapeutic benefits of ACAT1/SOAT1 inhibition.

BACKGROUND:When solid tumors are amenable to definitive resection, clinical outcomes are generally superior to when those tumors are inoperable. However, the population-level cancer survival benefit of eligibility for surgery by cancer stage has not yet been quantified.METHODS:Using Surveillance, Epidemiology and End Results data allowing us to identify patients who were deemed eligible for and received surgical resection, we examined the stage-specific association of surgical resection with 12-year cancer-specific survival. The 12-year endpoint was selected to maximize follow-up time and thereby minimize the influence of lead time bias.RESULTS:Across a variety of solid tumor types, earlier stage at diagnosis allowed for surgical intervention at a much higher rate than later-stage diagnosis. At every stage, surgical intervention was associated with a substantially higher rate of 12-year cancer-specific survival, with absolute differences of up to 51% for stage I, 51% for stage II, and 44% for stage III cancer, and stage-specific mortality relative risks of 3.6, 2.4, and 1.7, respectively.CONCLUSIONS:Diagnosis of solid cancers in early stages often enables surgical resection, which reduces the risk of death from cancer. Receipt of surgical resection is an informative endpoint that is strongly associated with long-term cancer-specific survival at every stage.

The current paradigm of carcinogenesis as a cellular evolutionary process driven by mutations of a few critical driver genes has immediate logical implications for the epidemiology of cancer. These include the impact of age on cancer risk, the role played by inherited tumor predisposition syndromes, and the interaction of genetics and environmental exposures on cancer risk. In this paper, we explore the following logical epidemiological consequences of carcinogenesis as a clonal process of mutation accumulation, with special emphasis on asbestos-related cancers, specifically malignant mesothelioma:1 All cancers, including mesothelioma, can and do occur spontaneously, i.e., in the absence of exposure to any environmental carcinogens. 2. Age is an important determinant of cancer risk, with or without exposure to environmental carcinogens. 3. Genetic tumor predisposition syndromes, such as the BAP1 syndrome, increase enormously the risk of cancer even in the absence of exposure to environmental carcinogens. We illustrate these concepts by applying a multistage clonal expansion model to U.S. Surveillance, Epidemiology, and End Results cancer registry data for pleural and peritoneal malignant mesotheliomas in 1975-2018.

Polygenic risk scores (PRS) have the potential to identify individuals at risk of diseases, optimizing treatment, and predicting survival outcomes. Here, we construct and validate a genome-wide association study (GWAS) derived PRS for nasopharyngeal carcinoma (NPC), using a multi-center study of six populations (6 059 NPC cases and 7 582 controls), and evaluate its utility in a nested case-control study. We show that the PRS enables effective identification of NPC high-risk individuals (AUC = 0.65) and improves the risk prediction with the PRS incremental deciles in each population ( P trend ranging from 2.79 × 10 −7 to 4.79 × 10 −44 ). By incorporating the PRS into EBV-serology-based NPC screening, the test’s positive predictive value (PPV) is increased from an average of 4.84% to 8.38% and 11.91% in the top 10% and 5% PRS, respectively. In summary, the GWAS-derived PRS, together with the EBV test, significantly improves NPC risk stratification and informs personalized screening.

Multiple membrane organelles require cholesterol for proper function within cells. The Niemann-Pick type C (NPC) proteins export cholesterol from endosomes to other membrane compartments, including the endoplasmic reticulum (ER), plasma membrane (PM), trans-Golgi network (TGN), and mitochondria, to meet their cholesterol requirements. Defects in NPC cause malfunctions in multiple membrane organelles and lead to an incurable neurological disorder. Acyl-coenzyme A:cholesterol acyltransferase 1 (ACAT1), a resident enzyme in the ER, converts cholesterol to cholesteryl esters for storage. In mutant NPC cells, cholesterol storage still occurs in an NPC-independent manner. Here we report the interesting finding that in a mutant Npc1 mouse (Npc1nmf), Acat1 gene (Soat1) knockout delayed the onset of weight loss, motor impairment, and Purkinje neuron death. It also improved hepatosplenic pathology and prolonged lifespan by 34%. In mutant NPC1 fibroblasts, ACAT1 blockade (A1B) increased cholesterol content associated with TGN-rich membranes and mitochondria, while decreased cholesterol content associated with late endosomes. A1B also restored proper localization of syntaxin 6 and golgin 97 (key proteins in membrane trafficking at TGN) and improved the levels of cathepsin D (a key protease in lysosome and requires Golgi/endosome transport for maturation) and ABCA1 (a key protein controlling cholesterol release at PM). This work supports the hypothesis that diverting cholesterol from storage can benefit multiple diseases that involve cholesterol deficiencies in cell membranes.

Abstract Background Epstein-Barr virus (EBV) reactivation from latent to lytic infection has been considered as a key step in nasopharyngeal carcinoma oncogenesis. However, epidemiological evidence regarding environmental risk factors for EBV reactivation on a population level remains largely lacking. Methods We enrolled 1916 randomly selected adults from the general population of Guangdong and Guangxi, China, from 2010 to 2014. Information on environmental factors was collected via a structured interview. Serum immunoglobulin A antibodies against EBV viral capsid antigen and nuclear antigen 1 were measured by enzyme-linked immunosorbent assay to evaluate EBV reactivation status. We used logistic regression to calculate odds ratios (ORs) with 95% confidence intervals (CIs) for the associations of EBV reactivation with various environmental factors. Results No associations were observed between EBV reactivation and extensive environmental factors, including alcohol or tea drinking, a history of chronic ear/nose/throat diseases, use of medications or herbs, consumption of salted fish or preserved foods, oral hygiene, sibship structure, and various residential and occupational exposures. Only cigarette smoking was associated with EBV reactivation (current smokers vs never smokers; OR = 1.37; 95% CI = 1.02–1.83), with positive exposure-response trends with increasing intensity, duration, and pack-years of smoking. Conclusions Consistent with previous studies, we found an association between cigarette smoking and EBV reactivation. Other examined exposures were not associated with EBV reactivation. These null results could suggest either more complex interactions between exposures and EBV reactivation or a predominant role of host and/or viral genetic variation.

Naltrexone/Bupropion extended release (ER; Contrave) is an extended-release, fixed-dose combination medication of naltrexone (8 mg) and bupropion (90 mg) for patients with obesity or overweight with at least one weight-related comorbidity. Obese and overweight patients with or without comorbidities are at increased cardiovascular (CV) risk. Due to the increased CV risk profile in this patient population, this systematic literature review was conducted to assess human studies reporting major adverse CV events (MACE) and other CV events. A priori eligibility criteria included clinical studies (randomized and observational) published from January 1, 2012, to September 30, 2021, with data comparing users of naltrexone/bupropion ER, naltrexone with bupropion, bupropion without naltrexone, or naltrexone without bupropion versus comparator groups (placebo or other treatments), and with sufficient information to determine the frequency of MACE or other CV adverse events by treatment group. Among 2539 English-language articles identified, 70 articles met the eligibility criteria: seven studies of naltrexone/bupropion ER or naltrexone with bupropion, 32 studies of bupropion, and 31 studies of naltrexone. No studies reported an increased risk of MACE among users of naltrexone/bupropion ER, naltrexone with bupropion, or bupropion or naltrexone individually compared with nonusers. One-half of the available studies (n = 35) reported no (zero) CV events and the other half (n = 35) reported that a non-zero frequency of CV events occurred. Four studies reported data on MACE, including three studies of bupropion and one study of naltrexone/bupropion ER. For composite MACE and its components, the difference in proportions between naltrexone/bupropion ER-, bupropion-, or naltrexone-treated patients compared with active comparators or placebo-treated patients did not exceed 2.5%. In conclusion, the available human evidence does not indicate an increased risk of CV events or MACE following use of naltrexone/bupropion ER, naltrexone with bupropion, or the individual components.

Lymphoma risk is elevated for relatives with common non-Hodgkin lymphoma (NHL) subtypes, suggesting shared genetic susceptibility across subtypes. To evaluate the extent of mutual heritability among NHL subtypes and discover novel loci shared among subtypes, we analyzed data from eight genome-wide association studies within the InterLymph Consortium, including 10,629 cases and 9505 controls. We utilized Association analysis based on SubSETs (ASSET) to discover loci for subsets of NHL subtypes and evaluated shared heritability across the genome using Genome-wide Complex Trait Analysis (GCTA) and polygenic risk scores. We discovered 17 genome-wide significant loci (P < 5 × 10−8) for subsets of NHL subtypes, including a novel locus at 10q23.33 (HHEX) (P = 3.27 × 10−9). Most subset associations were driven primarily by only one subtype. Genome-wide genetic correlations between pairs of subtypes varied broadly from 0.20 to 0.86, suggesting substantial heterogeneity in the extent of shared heritability among subtypes. Polygenic risk score analyses of established loci for different lymphoid malignancies identified strong associations with some NHL subtypes (P < 5 × 10−8), but weak or null associations with others. Although our analyses suggest partially shared heritability and biological pathways, they reveal substantial heterogeneity among NHL subtypes with each having its own distinct germline genetic architecture.

Environmental epidemiology has proven critical to study various associations between environmental exposures and adverse human health effects. However, there is a perception that it often does not sufficiently inform quantitative risk assessment. To help address this concern, in 2017, the Health and Environmental Sciences Institute initiated a project engaging the epidemiology, exposure science, and risk assessment communities with tripartite representation from government agencies, industry, and academia, in a dialogue on the use of environmental epidemiology for quantitative risk assessment and public health decision making. As part of this project, four meetings attended by experts in epidemiology, exposure science, toxicology, statistics, and risk assessment, as well as one additional meeting engaging funding agencies, were organized to explore incentives and barriers to realizing the full potential of epidemiological data in quantitative risk assessment. A set of questions was shared with workshop participants prior to the meetings, and two case studies were used to support the discussion.Five key ideas emerged from these meetings as areas of desired improvement to ensure that human data can more consistently become an integral part of quantitative risk assessment: 1) reducing confirmation and publication bias, 2) increasing communication with funding agencies to raise awareness of research needs, 3) developing alternative funding channels targeted to support quantitative risk assessment, 4) making data available for reuse and analysis, and 5) developing cross-disciplinary and cross-sectoral interactions, collaborations, and training.We explored and integrated these themes into a roadmap illustrating the need for a multi-stakeholder effort to ensure that epidemiological data can fully contribute to the quantitative evaluation of human health risks, and to build confidence in a reliable decision-making process that leverages the totality of scientific evidence.

BACKGROUND:Acyl-CoA:cholesterol acyltransferase (ACAT) inhibitors have been considered as potential therapeutic agents to treat several diseases, including Alzheimer's disease, atherosclerosis, and cancer. While many ACAT inhibitors are readily available, methods to encapsulate them as nanoparticles have not been reported.NEW METHOD:We report a simple method to encapsulate ACAT inhibitors, using the potent hydrophobic ACAT inhibitor F12511 as an example. By mixing DSPE-PEG2000, egg phosphatidylcholine (PC), and F12511 in ethanol, followed by drying, resuspension and sonication in buffer, we show that F12511 can be encapsulated as stealth liposomes at high concentration.RESULTS:We successfully incorporated F12511 into nanoparticles and found that increasing PC in the nanoparticles markedly increased the amount of F12511 incorporated in stealth liposomes. The nanoparticles containing F12511 (Nanoparticle F) exhibit average size of approximately 200 nm and are stable at 4 ºC for at least 6 months. Nanoparticle F is very effective at inhibiting ACAT in human and mouse neuronal and microglial cell lines. Toxicity tests using mouse primary neuronal cells show that F12511 alone or Nanoparticle F added at concentrations from 2 to 10 µM for 24-, 48-, and 72-hours produces minimal, if any, toxicity.COMPARISON WITH EXISTING METHOD(S):Unlike existing methods, the current method is simple, cost effective, and can be expanded to produce tagged liposomes to increase specificity of delivery. This also offers opportunity to embrace water soluble agent(s) within the aqueous compartment of the nanoparticles for potential combinatorial therapy.CONCLUSIONS:This method shows promise for delivery of hydrophobic ACAT inhibitors at high concentration in vivo.

Cancer CommunicationsEarly View LETTER TO THE EDITOROpen Access Transcriptome-wide association analysis identified candidate susceptibility genes for nasopharyngeal carcinoma Yong-Qiao He, Yong-Qiao He State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorWen-Qiong Xue, Wen-Qiong Xue State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorDan-Hua Li, Dan-Hua Li State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorTong-Min Wang, Tong-Min Wang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorZhi-Ming Mai, Zhi-Ming Mai School of Public Health, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Center for Nasopharyngeal Carcinoma Research, Research Grants Council Area of Excellence Scheme, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892 USASearch for more papers by this authorDa-Wei Yang, Da-Wei Yang School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorChang-Mi Deng, Chang-Mi Deng State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorYing Liao, Ying Liao State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorWen-Li Zhang, Wen-Li Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorRuo-Wen Xiao, Ruo-Wen Xiao State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorLuting Luo, Luting Luo School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorHua Diao, Hua Diao School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorXiating Tong, Xiating Tong School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorYanxia Wu, Yanxia Wu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorJiang-Bo Zhang, Jiang-Bo Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorTing Zhou, Ting Zhou orcid.org/0000-0003-4349-2036 State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorXi-Zhao Li, Xi-Zhao Li State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorPei-Fen Zhang, Pei-Fen Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorXiao-Hui Zheng, Xiao-Hui Zheng State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorShao-Dan Zhang, Shao-Dan Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorYe-Zhu Hu, Ye-Zhu Hu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorMinzhong Tang, Minzhong Tang Wuzhou Red Cross Hospital, Wuzhou, Guangxi, 543002 P. R. China Wuzhou Cancer Center, Wuzhou, Guangxi, 543002 P. R. ChinaSearch for more papers by this authorYuming Zheng, Yuming Zheng Wuzhou Red Cross Hospital, Wuzhou, Guangxi, 543002 P. R. China Wuzhou Cancer Center, Wuzhou, Guangxi, 543002 P. R. ChinaSearch for more papers by this authorYonglin Cai, Yonglin Cai Wuzhou Red Cross Hospital, Wuzhou, Guangxi, 543002 P. R. China Wuzhou Cancer Center, Wuzhou, Guangxi, 543002 P. R. ChinaSearch for more papers by this authorEllen T. Chang, Ellen T. Chang Center for Health Sciences, Exponent, Inc., Menlo Park, CA, 94025, Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 94143 USASearch for more papers by this authorZhe Zhang, Zhe Zhang Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530021 P. R. ChinaSearch for more papers by this authorGuangwu Huang, Guangwu Huang Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530021 P. R. ChinaSearch for more papers by this authorSu-Mei Cao, Su-Mei Cao State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorQing Liu, Qing Liu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorLin Feng, Lin Feng State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorYing Sun, Ying Sun orcid.org/0000-0002-5888-2929 Department of Radiation Oncology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorMaria Li Lung, Maria Li Lung Center for Nasopharyngeal Carcinoma Research, Research Grants Council Area of Excellence Scheme, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Department of Clinical Oncology, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. ChinaSearch for more papers by this authorHans-Olov Adami, Hans-Olov Adami Clinical Effectiveness Group, Institute of Health and Society, University of Oslo, Oslo, 0316 Norway Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 SwedenSearch for more papers by this authorWeimin Ye, Weimin Ye Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 Sweden Department of Epidemiology and Health Statistics & Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, Fujian, 350122 P. R. ChinaSearch for more papers by this authorTai-Hing Lam, Tai-Hing Lam School of Public Health, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Center for Nasopharyngeal Carcinoma Research, Research Grants Council Area of Excellence Scheme, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. ChinaSearch for more papers by this authorWei-Hua Jia, Corresponding Author Wei-Hua Jia jiawh@sysucc.org.cn orcid.org/0000-0002-0528-8715 State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. China School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. China Correspondence Wei-Hua Jia, M.D., Ph.D. Professor, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dong Feng East Road, Guangzhou 510060, Guangdong, P. R. China. Email: jiawh@sysucc.org.cnSearch for more papers by this author Yong-Qiao He, Yong-Qiao He State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorWen-Qiong Xue, Wen-Qiong Xue State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorDan-Hua Li, Dan-Hua Li State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorTong-Min Wang, Tong-Min Wang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorZhi-Ming Mai, Zhi-Ming Mai School of Public Health, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Center for Nasopharyngeal Carcinoma Research, Research Grants Council Area of Excellence Scheme, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892 USASearch for more papers by this authorDa-Wei Yang, Da-Wei Yang School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorChang-Mi Deng, Chang-Mi Deng State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorYing Liao, Ying Liao State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorWen-Li Zhang, Wen-Li Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorRuo-Wen Xiao, Ruo-Wen Xiao State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorLuting Luo, Luting Luo School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorHua Diao, Hua Diao School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorXiating Tong, Xiating Tong School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. ChinaSearch for more papers by this authorYanxia Wu, Yanxia Wu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorJiang-Bo Zhang, Jiang-Bo Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorTing Zhou, Ting Zhou orcid.org/0000-0003-4349-2036 State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorXi-Zhao Li, Xi-Zhao Li State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorPei-Fen Zhang, Pei-Fen Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorXiao-Hui Zheng, Xiao-Hui Zheng State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorShao-Dan Zhang, Shao-Dan Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorYe-Zhu Hu, Ye-Zhu Hu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorMinzhong Tang, Minzhong Tang Wuzhou Red Cross Hospital, Wuzhou, Guangxi, 543002 P. R. China Wuzhou Cancer Center, Wuzhou, Guangxi, 543002 P. R. ChinaSearch for more papers by this authorYuming Zheng, Yuming Zheng Wuzhou Red Cross Hospital, Wuzhou, Guangxi, 543002 P. R. China Wuzhou Cancer Center, Wuzhou, Guangxi, 543002 P. R. ChinaSearch for more papers by this authorYonglin Cai, Yonglin Cai Wuzhou Red Cross Hospital, Wuzhou, Guangxi, 543002 P. R. China Wuzhou Cancer Center, Wuzhou, Guangxi, 543002 P. R. ChinaSearch for more papers by this authorEllen T. Chang, Ellen T. Chang Center for Health Sciences, Exponent, Inc., Menlo Park, CA, 94025, Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 94143 USASearch for more papers by this authorZhe Zhang, Zhe Zhang Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530021 P. R. ChinaSearch for more papers by this authorGuangwu Huang, Guangwu Huang Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530021 P. R. ChinaSearch for more papers by this authorSu-Mei Cao, Su-Mei Cao State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorQing Liu, Qing Liu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorLin Feng, Lin Feng State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorYing Sun, Ying Sun orcid.org/0000-0002-5888-2929 Department of Radiation Oncology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060 P. R. ChinaSearch for more papers by this authorMaria Li Lung, Maria Li Lung Center for Nasopharyngeal Carcinoma Research, Research Grants Council Area of Excellence Scheme, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Department of Clinical Oncology, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. ChinaSearch for more papers by this authorHans-Olov Adami, Hans-Olov Adami Clinical Effectiveness Group, Institute of Health and Society, University of Oslo, Oslo, 0316 Norway Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 SwedenSearch for more papers by this authorWeimin Ye, Weimin Ye Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177 Sweden Department of Epidemiology and Health Statistics & Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, Fujian, 350122 P. R. ChinaSearch for more papers by this authorTai-Hing Lam, Tai-Hing Lam School of Public Health, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. China Center for Nasopharyngeal Carcinoma Research, Research Grants Council Area of Excellence Scheme, The University of Hong Kong, Hong Kong S.A.R., 999077 P. R. ChinaSearch for more papers by this authorWei-Hua Jia, Corresponding Author Wei-Hua Jia jiawh@sysucc.org.cn orcid.org/0000-0002-0528-8715 State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060 P. R. China School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080 P. R. China Correspondence Wei-Hua Jia, M.D., Ph.D. Professor, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dong Feng East Road, Guangzhou 510060, Guangdong, P. R. China. Email: jiawh@sysucc.org.cnSearch for more papers by this author First published: 01 June 2022 https://doi.org/10.1002/cac2.12317 Yong-Qiao He, Wen-Qiong Xue, Dan-Hua Li, and Tong-Min Wang have contributed equally to this work. AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abbreviations EBV Epstein-Barr virus GO gene ontology GWAS genome-wide association analysis HBV hepatitis B virus HCV hepatitis C virus HLA human leukocyte antigen KEGG Kyoto encyclopedia of genes and genomes LD linkage disequilibrium NPC nasopharyngeal carcinoma PIP posterior inclusion probability QC quality control TWAS transcriptome-wide association analysis ZEBRA BamHI Z EBV replication activator Dear Editor, Nasopharyngeal carcinoma (NPC) is a common malignancy in East and Southeast Asia, especially in South China. The etiology of NPC has been linked to genetic susceptibility, Epstein-Barr virus (EBV) infection, and environmental factors. Accumulated evidence including multiple genome-wide association studies (GWASs) has revealed robust genetic predisposition of NPC. However, GWAS-identified genetic variants collectively account for only 8.2% of NPC heritability [1]. The underlying inherited predisposition is largely undetermined. The strongest genetic signal for NPC consistently hits the human leukocyte antigen (HLA) region on 6p21 [2]. However, the highly polymorphic nature and complicated long-range linkage disequilibrium (LD) in the HLA region particularly obscure the causal variants driving the association. In addition, most genetic variants located in introns or intergenic regions. The causal genes mediating genetic effects on NPC risk have rarely been ascertained by GWAS alone. Recently, transcriptome-wide association study (TWAS) has been proposed as an attractive approach to identify novel gene-trait associations and prioritize causal genes for complex traits [3]. By integrating GWAS and gene expression data, TWAS can effectively and economically assess associations between genetically predicted gene expression levels and disease risks in large populations. Hence, using the cis-regulated expression in addition to genetic variants to explore NPC susceptibility genes could be promising and reasonable for mechanistic and functional inference. Nevertheless, neither public data of nasopharyngeal tissue were available, nor TWAS for NPC had been conducted. Herein, we integrated genome and transcriptome data of 89 nasopharyngeal tumor tissues and investigated the associations between predicted gene expression levels and NPC risk using multicenter GWAS data involving 4506 NPC cases and 5384 cancer-free subjects (defined as controls) from South China. Given the close relationship between EBV infection and NPC, a cis-regulated expression weight matrix from EBV-transformed lymphocytes (n = 117) in the GTEx project was used for further evaluation. Study populations and detailed methodology are described in the Supplementary file of methods. We predicted the expression levels of 2505 and 2411 genes in the GWAS population by constructing the models for the prediction of gene expression in nasopharyngeal tissues (NP models) and EBV-transformed lymphocytes (lymphocyte models), respectively (Supplementary Table S1), and 377 genes overlapped (Supplementary Figure S1). Thirty-three genes were associated with NPC at a Bonferroni-corrected threshold, and all were located in the HLA region (Figure 1A). Among them, 11 of 13 previously reported genes were replicated. Our results were consistent with the studies focusing on the HLA region in South China [4, 5], where most of the reported genes available in TWAS were replicated. The predicted expression levels of ZFP57 (NP models), MICA (both models), and HLA-C (lymphocyte models) were significantly higher in cases than in controls, while the expression levels of MOG, HCG27, HLA-DQB1, HLA-H, HLA-U (NP models), HLA-F (both models), HLA-A, and HLA-DRB1 (lymphocyte models) were lower in cases than in controls. The two overlapping genes showed similar associations with NPC (HLA-F: Z score = -10.28 and -8.95; MICA: Z score = 7.82 and 6.60, for NP and lymphocyte models, respectively) (Supplementary Table S2). Interestingly, half of the previously reported genes belonged to HLA class I. Most of them showed lower levels of predicted expression in cases than in controls, possibly because EBV transcripts in NPC tumors were involved in the inhibition of HLA class I gene expression [6]. It is rational to assume that the low expression levels of these genes may affect the anti-EBV immune response in presenting peptides to cytotoxic T cells, facilitating immune evasion of tumor cells or EBV-mediated oncogenic action. FIGURE 1Open in figure viewer TWAS-identified susceptibility genes and pathways for NPC. (A) Manhattan plot of TWAS in NP models and lymphocyte models. The blue lines represent the Bonferroni-corrected significance threshold. The red dots above or below the blue line represent the genes passed the Bonferroni threshold in the association analysis. The genes with green labels have been reported to be associated with NPC by previous genome-wide or candidate pathway association studies. The genes with black labels were newly identified as NPC susceptibility genes by our study. The genes in different chromosomes were exhibited in light and dark grey dots. (B) Expression quantitative trait locus analysis for the seven putative causal genes in the expression data of 89 nasopharyngeal tissue samples. The Kruskal-Wallis test was used to compare medians among three genotypes for most of the variants. In a certain homozygote group, the P values were recalculated using only the wild-type and heterozygous groups for the expression of MICD, HCG27 and HLA-DOB by excluding the groups with a sample size less than 5. (C) GO pathway enrichment analysis of NPC. (D) KEGG pathway enrichment analysis of NPC. “Gene Ratio” refers to the percentage of total significant genes in the given pathway. All 354 significant genes (P < 0.05) in TWAS were used in the enrichment analysis. Abbreviations: TWAS, Transcriptome-wide association analysis; NPC, Nasopharyngeal carcinoma; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes Although the significant signals consistently hit the HLA region, 22 additional genes not previously reported were identified in TWAS. Among them, the predicted expression levels of 9 genes were significantly higher in NPC cases than in controls, including HLA-DOB, HCG4B, RPL23AP1, HLA-J in NP models and HCG4, CCHCR1, STK19, C4B, IFITM4P in lymphocyte models, while 13 other genes showed significantly lower expression levels in cases than in controls, including HCP5, ZSCAN23, HCG4P11, HCG4P7, MICD, MICB-DT, SNHG32 in NP models and NOTCH4, C4A, HCG22, POU5F1, MICE, HLA-S in lymphocyte models (Figure 1A). We performed conditional analyses to determine whether the associations between predicted gene expression levels and NPC were influenced by the GWAS signals. After conditioning on the respective GWAS index SNP, the associations for HLA-DOB, NOTCH4, ZSCAN23, STK19, C4B, HLA-J, HLA-S, and MICB-DT remained significant. After conditioning on all previously reported SNPs, NOTCH4, HCG4, HCG22, POU5F1, HCG4B, HCG4P11, MICB-DT, STK19 and IFITM4P remained significant. It indicated that their associations were partially independent of the GWAS signals (Supplementary Table S3). Due to the complicated structure with high LD and co-expression networks in the HLA region, we conducted fine-mapping analyses to prioritize the causal genes. Using posterior inclusion probability (PIP) analysis, we prioritized 7 causal genes: MICA, HLA-DQB1, HLA-DOB, ZSCAN23, HCG27, MICD, and HLA-U. HLA-DOB, ZSCAN23, and MICD were newly identified as NPC susceptibility genes (Supplementary Table S4). Furthermore, we conducted expression quantitative trait locus (eQTL) analyses to identify whether the genetic variants could influence the expression levels of these genes. We found that individuals with relevant risk SNPs (the GWAS index SNPs) exhibited higher expression of HLA-DQB1, MICA, MICD and HLA-U, or lower expression levels of ZSCAN23, HCG27, and HLA-DOB. These results indicated that the risk alleles affected the expression levels of the causal genes (Figure 1B). Two HLA class II genes (HLA-DQB1 and HLA-DOB) were prioritized as causal genes. Both genes were associated with other virus-associated cancers, such as cervical cancer [7]. A comprehensive TWAS exploring genetic susceptibility for antiviral immune response using 7924 subjects from the UK Biobank cohort revealed that the genetic determinants for EBV infection were predominantly located on HLA class II genes. The most significant signals associated with the antibody level of BamHI Z EBV replication activator (ZEBRA) hit HLA-DQB1 [8]. HLA-DOB may impact viral clearance capacity and persistent infection of hepatitis B virus (HBV) and hepatitis C virus (HCV) [9]. Since EBV reactivation with elevated EBV DNA load or antibodies was observed at the preclinical phase of NPC, we hypothesized that HLA class II genes, especially HLA-DQB1and HLA-DOB, participate in the early stage of NPC tumorigenesis by influencing EBV infection. Besides, some identified pseudogenes, such as IFITM4P [10], may function by regulating their parental genes. However, their biological mechanisms remain unclear, and further researches are needed. Gene Ontology (GO) enrichment analysis confirmed that TWAS-identified genes (354 genes with P < 0.05) were enriched in the pathways of cell-mediated immune response, antigen processing and presentation (Figure 1C). Similarly, the top pathways annotated with the Kyoto Encyclopedia of Genes and Genomes (KEGG) database focused on infection of herpes simplex virus type 1, human T-cell leukemia virus type 1, EBV, and autoimmune disorders such as graft-versus-host disease (Figure 1D). In summary, using a TWAS approach, we corroborated the central role of HLA genes in NPC susceptibility. Apart from HLA class I genes, we propose critical roles of HLA class II genes and other nonclassical HLA genes. Seven genes, including HLA-DQB1 and HLA-DOB, were prioritized as causal genes. Recent evidence indicated that these genes are pivotal in the metastable equilibrium between host and virus. Our findings provide additional evidence for a better understanding of the genetic etiology of NPC and clues to further advance this field. DECLARATIONS ACKNOWLEDGEMENTS We thank the staffs from Sun Yat-sen University Cancer Center biorepository. We thank all the study participants and research staff who recruited participants and collected samples in this study. This study was funded by the National Key Research and Development Program of China (2021YFC2500400), the Basic and Applied Basic Research Foundation of Guangdong Province, China (2021B1515420007), Sino-Sweden Joint Research Programme (81861138006), the Science and Technology Planning Project of Guangzhou, China (201804020094), the Special Support Program for High-level Professionals on Scientific and Technological Innovation of Guangdong Province, China (2014TX01R201), National Natural Science Foundation of China (81973131, 81903395, 81803319, 82003520), National Science Fund for Distinguished Young Scholars of China (81325018). CONFLICT OF INTEREST The authors have no potential conflicts of interest to declare. ETHICS APPROVAL AND CONSENT TO PARTICIPATE The Institutional Review Board of Sun Yat-sen University Cancer Center approved this study. Informed consent was obtained from all study participants. AUTHOR CONTRIBUTIONS WHJ and YQH devised the project and the main conceptual ideas; YQH, WQX, DHL, and TMW wrote the original draft; DHL and TMW performed the computational analyses; TMW, DWY, CMD, and WLZ contributed to implementation of data processing and analyses; DWY, CMD, YL, WLZ, RWX, LL, HD, XT, YW, TZ, XZL, PFZ, XHZ, SDZ, YZH, MT, YZ, YC and JBZ contributed to the sample preparation; TMW and WLZ contributed to the RNA-seq quantification and quality control pipeline; ETC, ZZ, GH, SMC, QL, LF, YS, MLL, HOA, WY, and THL contributed to the interpretation of the results; YQH, WQX, and TMW revised and wrote the final version of the manuscript; verified the analytical methods; WHJ supervised the project. All authors read and approved the final manuscript. AVAILABILITY OF DATA AND MATERIALS Methods and materials are available in the supplementary file. The datasets generated and used during the current study are available at Research Data Deposit (RDD) public platform (www.researchdata.org.cn) with the approval RDD number of RDDB2021406340. Supporting Information Filename Description cac212317-sup-0001-SuppMat.docx136.9 KB Supporting information Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. REFERENCES 1Dai J, Shen W, Wen W, Chang J, Wang T, Chen H, et al. Estimation of heritability for nine common cancers using data from genome-wide association studies in Chinese population. Int J Cancer. 2017; 140(2): 329– 36. Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 2Bei JX, Li Y, Jia WH, Feng BJ, Zhou G, Chen LZ, et al. A genome-wide association study of nasopharyngeal carcinoma identifies three new susceptibility loci. 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Background The human microbiome has been reported to mediate the response to anticancer therapies. However, research about the influence of the oral microbiome on nasopharyngeal carcinoma (NPC) survival is lacking. We aimed to explore the effect of oral microbiota on NPC prognosis. Methods Four hundred eighty-two population-based NPC cases in southern China between 2010 and 2013 were followed for survival, and their saliva samples were profiled using 16s rRNA sequencing. We analyzed associations of the oral microbiome diversity with mortality from all causes and NPC. Results Within- and between-community diversities of saliva were associated with mortality with an average of 5.29 years follow-up. Lower Faith’s phylogenetic diversity was related to higher all-cause mortality [adjusted hazard ratio (aHR), 1.52 (95% confidence interval (CI), 1.06–2.17)] and NPC-specific mortality [aHR, 1.57 (95% CI, 1.07–2.29)], compared with medium diversity, but higher phylogenetic diversity was not protective. The third principal coordinate (PC3) identified from principal coordinates analysis (PCoA) on Bray–Curtis distance was marginally associated with reduced all-cause mortality [aHR, 0.85 (95% CI, 0.73–1.00)], as was the first principal coordinate (PC1) from PCoA on weighted UniFrac [aHR, 0.86 (95% CI, 0.74–1.00)], but neither was associated with NPC-specific mortality. PC3 from robust principal components analysis was associated with lower all-cause and NPC-specific mortalities, with HRs of 0.72 (95% CI, 0.61–0.85) and 0.71 (95% CI, 0.60–0.85), respectively. Conclusions Oral microbiome may be an explanatory factor for NPC prognosis. Lower within-community diversity was associated with higher mortality, and certain measures of between-community diversity were related to mortality. Specifically, candidate bacteria were not related to mortality, suggesting that observed associations may be due to global patterns rather than particular pathogens.