Abstract
Nasopharyngeal carcinoma (NPC) is originated from the epithelial cells of nasopharynx, Epstein–Barr virus (EBV)‐associated and has the highest incidence and mortality rates in Southeast Asia. Late presentation is a common issue and early detection could be the key to reduce the disease burden. Sensitivity of plasma EBV DNA, an established NPC biomarker, for Stage I NPC is controversial. Most newly reported NPC biomarkers have neither been externally validated nor compared to the established ones. This causes difficulty in planning for cost‐effective early detection strategies. Our study systematically evaluated six established and four new biomarkers in NPC cases, population controls and hospital controls. We showed that BamHI‐W 76 bp remains the most sensitive plasma biomarker, with 96.7% (29/30), 96.7% (58/60) and 97.4% (226/232) sensitivity to detect Stage I, early stage and all NPC, respectively. Its specificity was 94.2% (113/120) against population controls and 90.4% (113/125) against hospital controls. Diagnostic accuracy of BamHI‐W 121 bp and ebv‐miR‐BART7‐3p were validated. Hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p were not, possibly due to lower number of advanced stage NPC cases included in this subset. Decision tree modeling suggested that combination of BamHI‐W 76 bp and VCA IgA or EA IgG may increase the specificity or sensitivity to detect NPC. EBNA1 99 bp could identify NPC patients with poor prognosis in early and advanced stage NPC. Our findings provided evidence for improvement in NPC screening strategies, covering considerations of opportunistic screening, combining biomarkers to increase sensitivity or specificity and testing biomarkers from single sampled specimen to avoid logistic problems of resampling.
Keywords: systematic comparison, biomarkers, early detection, prognosis, Epstein–Barr virus, nasopharyngeal carcinoma
Short abstract
What's new?
Plasma Epstein–Barr virus (EBV) DNA is an established nasopharyngeal carcinoma (NPC) biomarker, but not all cases are associated with EBV and its sensitivity for stage I NPC remains controversial. Meanwhile, most newly‐reported NPC biomarkers have neither been externally validated nor compared to established biomarkers. This study systematically evaluates six established and four new biomarkers in NPC cases, population controls, and hospital controls. The findings provide evidence to policymakers for improvement in NPC screening and monitoring strategies, covering considerations of opportunistic screening, combining biomarkers to increase sensitivity/specificity, and testing multiple biomarkers on single specimens to avoid the logistic problems of resampling.
Abbreviations
- AJCC
American Joint Committee on Cancer
- ASR
age standardized rate
- AUC
area under curve
- EA
early antigen
- EBNA‐1
EBV nuclear antigen 1
- EBV
Epstein–Barr virus
- ICC
intraclass correlation coefficient
- LMICs
low‐ and middle‐income countries
- NPC
nasopharyngeal carcinoma
- qPCR
quantitative polymerase chain reaction
- ROC
receiver operating characteristic
- RT
reverse transcription
- VCA
viral capsid antigen
Background
Nasopharyngeal carcinoma (NPC) is an epithelial malignancy originating from the fossa of Rosenmüller of the nasopharynx. Its distribution is geographically distinct, with natives of Borneo Island, people in Southeast Asia and the Southern part of China having high age standardized rate (ASR) but is uncommon in most part of the world.1, 2 Among the top 20 countries with highest incidence and mortality rates of NPC,3 17 are low‐ and middle‐income countries (LMICs), 10 of which are located in Southeast Asia. It is known that the family members of NPC patients have two to nine folds higher risk in developing NPC.4, 5, 6, 7 The lowest social class group had 4.1 odds ratio in developing NPC.8 NPC is radiosensitive when treated early, with 5‐year overall survival rate ranging from 78% to 100% (early stage) to as low as 26% (late stage and recurrent cases).9, 10, 11 Recently, a study revealed that over 75% of cancer patients in Southeast Asia experienced death or financial catastrophe within 1 year of cancer diagnosis, mainly due to the lack of early detection and affordable cancer care.12 As the majority of NPC patients present at late stage,13 early detection could be the key to reduce the disease burden caused by NPC in LMICs.
Interaction among genes, environmental exposure and the Epstein–Barr virus (EBV) are the key events leading to NPC pathogenesis. Majority of NPC cases (>95%, except for the WHO keratinizing NPC subtype) are associated with EBV.14 EBV is commonly detected in the tumor cells, blood and urine of NPC patients.15 Over decades of research, EBV serology and plasma EBV DNA tests have become the established circulating biomarkers known to have high diagnostic performance in distinguishing NPC from controls.15 Recent evidences showed that combination of serum viral capsid antigen (VCA) IgA and EBV nuclear antigen 1 (EBNA‐1) IgA tests by ELISA could outperform single serology marker test in a case–control study16 as well as in a cluster randomized screening trial17 among the southern Chinese populations. The percentage of early stage NPC cases (Stages I and II) detected by the combination of these two serology markers during screening were higher (68.3%) as compared to unscreened populations in the screening towns (36.0%) and control towns (25.7%).17 However, the seropositive rate of about 3% in a screening setting may still lead to a considerable burden on the resource low health care system in LMICs to conduct close follow‐up for individuals with positive screening results. Meanwhile, plasma EBV DNA test is long known to have high sensitivity and specificity to distinguish NPC from controls when optimal experimental protocols were carried out, but there were concerns about its utility in detecting early stage NPC and recurrent NPC.15, 18 Of note, these EBV DNA case–control studies analyzed small sample size of Stage I NPC cases.15, 19 Recently, a large NPC screening study conducted in Hong Kong demonstrated that plasma EBV DNA test (BamHI‐W 76 bp) could identify a significantly higher proportion of participants with early stage NPC as compared to the unscreened historical cohort (70.6% vs. 19.2%).20 The same study group subsequently reported that EBV DNA fragment size profiles of NPC patients are different from the small subset of general population who was transiently positive for plasma EBV DNA.21
According to the US National Cancer Institute's Early Detection Research Network, there are five phases for developing and validating biomarkers.22 Despite the established EBV DNA tests and EBV serology tests which had already reach Phase 5 (Cancer Control), the pursuit of new NPC biomarkers continues for two main reasons: (i) keratinizing NPC subtype and recurrent NPC have reduced or absence of biomarkers originating from EBV,15 and (ii) EBV is also associated with many other diseases23 and biomarkers of non‐EBV origin may help to reduce the false positive rate. Among the newly reported circulating biomarkers for NPC, serum ebv‐BART2‐5p, plasma ebv‐miR‐BART7‐3p, ebv‐miR‐BART13‐3p, hsa‐miR‐29a‐3p, hsa‐miR‐103a‐3p, hsa‐miR‐483‐5p and hsa‐let‐7c had moderately good diagnostic accuracy (area under curve [AUC] > 0.7) in detecting NPC against controls.24, 25, 26 Meanwhile, other newly reported circulating biomarkers had AUC < 0.7,27, 28, 29 were identified from studies with normalization methods which are suboptimal for circulating biomarkers30, 31 and/or required additional processing or enrichment steps.19, 32 The reliability and diagnostic accuracy of these new biomarkers for early detection of NPC await validation by external independent studies (Phase 2, Clinical Assay and Validation) and should be evaluated together with the established EBV DNA and serology tests.
Malaysia is a country inhabited by multiethnic groups with different ASRs of NPC. Highest ASR of NPC (30 per 100,000) was observed in Bidayuh males, followed by Bidayuh females, Chinese males, Iban males and Kadazan males (10–20 per 100,000). Malay males, Chinese females, Iban females and Kadazan females have intermediate ASR of NPC (3.3–5.9 per 100,000), while lowest ASR of NPC (0.6–1.3 per 100,000) was observed in Malay females, Indian males and females.33, 34, 35 According to the Malaysian National Cancer Registry Report 2007–2011, NPC was the cancer with the highest ASR among Malaysian men between 26 and 45 years old.35 Despite the progress of NPC screening studies in southern China, NPC screening is yet to be adopted in Malaysia, due to less characterized population baseline values and uncertainty in the application of single or combination of biomarkers for screening. In Malaysia, histological examination of nasoendoscopic biopsy samples remains the gold standard to diagnose NPC. Computerized tomography is limited to major centers while magnetic resonance imaging and positron emission tomography are not routinely available to most NPC patients. Due to the confusing and nonspecific nature of early stage NPC symptoms,13 as well as the invasive and difficult accessibility of nasoendoscopic biopsy tests mandatory to confirm the presence of tumor (nasoendoscopy is only performed by trained otorhinolaryngologists in major centers), late presentation is a common issue.13
Our study aimed to evaluate the diagnostic performance of six established NPC biomarkers, consisting of two EBV DNA (BamHI‐W 76 bp and EBNA1 99 bp) and four anti‐EBV antibodies (early antigen [EA] IgA, EA IgG, EBNA‐1 IgA and VCA IgA), in local NPC cases, population controls and hospital controls. In addition, the performance of four newly reported NPC biomarkers, including one EBV DNA (BamHI‐W 121 bp) and three miRNAs (ebv‐miR‐BART7‐3p, hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p) were evaluated in a subset of our study. It is hoped that single or combination of tests optimal for early detection and prognosis of NPC can be identified to improve strategies for NPC screening and monitoring.
Materials and Methods
Participants and blood samples collection
Participants were recruited from hospitals and National Blood Bank from year 2008 to 2017. Ethics approval was obtained from the Medical Research and Ethics Committee, Ministry of Health Malaysia. Signed informed consent was obtained from histologically confirmed NPC patients, population controls (apparently healthy asymptomatic individuals) and hospital controls (patients without any cancer, EBV related diseases or ear‐nose‐throat diseases). Blood samples were collected in EDTA tubes and processed within 4 hr. Blood tubes were centrifuged at room temperature for 10 min at 2,500 RPM, and plasma aliquoted into separate cryogenic tubes and stored at −80°C. The numbers of samples analyzed for each test are stated in Table 1. Staging for NPC was based on the American Joint Committee on Cancer (AJCC) 7th edition and completion of radical treatment was defined as receiving a minimum of 66 Gy of radiotherapy. Survival information was retrieved from National Registration Department, Ministry of Home Affairs.
Table 1.
Comparison | BamHI‐W 76 bp | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >0 copy/ml | 29 | 1 | 113 | 7 | 94.7% | 96.7% | 94.2% | 0.9726 |
Stages I and II NPC vs. PC | >0 copy/ml | 58 | 2 | 113 | 7 | 95.0% | 96.7% | 94.2% | 0.9756 |
All NPC vs. PC | >0 copy/ml | 226 | 6 | 113 | 7 | 96.3% | 97.4% | 94.2% | 0.9832 |
Stage I NPC vs. HC | >0 copy/ml | 29 | 1 | 113 | 12 | 91.6% | 96.7% | 90.4% | 0.9615 |
Stages I and II NPC vs. HC | >0 copy/ml | 58 | 2 | 113 | 12 | 92.4% | 96.7% | 90.4% | 0.9679 |
All NPC vs. HC | >0 copy/ml | 226 | 6 | 113 | 12 | 95.0% | 97.4% | 90.4% | 0.9796 |
Comparison | EBNA1 99 bp | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >0 copy/ml | 22 | 8 | 119 | 1 | 94.0% | 73.3% | 99.2% | 0.8650 |
Stages I and II NPC vs. PC | >0 copy/ml | 48 | 12 | 119 | 1 | 92.8% | 80.0% | 99.2% | 0.8988 |
All NPC vs. PC | >0 copy/ml | 200 | 32 | 119 | 1 | 90.6% | 86.2% | 99.2% | 0.9303 |
Stage I NPC vs. HC | >0 copy/ml | 22 | 8 | 124 | 1 | 94.2% | 73.3% | 99.2% | 0.8608 |
Stages I and II NPC vs. HC | >0 copy/ml | 48 | 12 | 124 | 1 | 93.0% | 80.0% | 99.2% | 0.8941 |
All NPC vs. HC | >0 copy/ml | 200 | 32 | 124 | 1 | 90.8% | 86.2% | 99.2% | 0.9281 |
Comparison | EA IgA | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | <1,006 U/ml1 | 4 | 4 | 83 | 29 | 72.5% | 50.0% | 74.1% | 0.5368 |
Stages I and II NPC vs. PC | >1,852 U/ml | 17 | 13 | 81 | 31 | 69.0% | 56.7% | 72.3% | 0.6226 |
All NPC vs. PC | >1,510 U/ml | 136 | 53 | 71 | 41 | 68.8% | 72.0% | 63.4% | 0.6835 |
Stage I NPC vs. HC | >823.0 U/ml | 7 | 1 | 44 | 9 | 83.6% | 87.5% | 83.0% | 0.8514 |
Stages I and II NPC vs. HC | > 815.0 U/ml | 27 | 3 | 44 | 9 | 85.5% | 90.0% | 83.0% | 0.9094 |
All NPC vs. HC | >1,002 U/ml | 172 | 17 | 48 | 5 | 90.9% | 91.0% | 90.6% | 0.9567 |
Comparison | EBNA‐1 IgA | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >6,147 U/ml | 4 | 4 | 107 | 6 | 91.7% | 50.0% | 94.7% | 0.6565 |
Stages I and II NPC vs. PC | >4,409 U/ml | 10 | 19 | 100 | 13 | 77.5% | 34.5% | 88.5% | 0.6196 |
All NPC vs. PC | >5,217 U/ml | 58 | 130 | 104 | 9 | 53.8% | 30.9% | 92.0% | 0.6476 |
Stage I NPC vs. HC | >5,080 U/ml | 4 | 4 | 50 | 3 | 88.5% | 50.0% | 94.3% | 0.7476 |
Stages I and II NPC vs. HC | >2,988 U/ml | 15 | 14 | 48 | 5 | 76.8% | 51.7% | 90.6% | 0.7586 |
All NPC vs. HC | >1,791 U/ml | 117 | 71 | 43 | 10 | 66.4% | 62.2% | 81.1% | 0.7886 |
Comparison | EA IgG | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >1,605 U/ml | 8 | 0 | 60 | 52 | 56.7% | 100.0% | 53.6% | 0.7031 |
Stages I and II NPC vs. PC | >1,575 U/ml | 28 | 2 | 60 | 52 | 62.0% | 93.3% | 53.6% | 0.7991 |
All NPC vs. PC | >5,322 U/ml | 156 | 34 | 84 | 28 | 79.5% | 82.1% | 75.0% | 0.8612 |
Stage I NPC vs. HC | >1,642 U/ml | 8 | 0 | 50 | 3 | 95.1% | 100.0% | 94.3% | 0.9670 |
Stages I and II NPC vs. HC | >1,481 U/ml | 28 | 2 | 49 | 4 | 92.8% | 93.3% | 92.5% | 0.9415 |
All NPC vs. HC | >1,642 U/ml | 185 | 5 | 50 | 3 | 96.7% | 97.4% | 94.3% | 0.9765 |
Comparison | VCA IgA | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >731.5 U/ml | 8 | 0 | 71 | 42 | 65.3% | 100.0% | 62.8% | 0.7378 |
Staged I and II NPC vs. PC | >731.5 U/ml | 27 | 2 | 71 | 42 | 69.0% | 93.1% | 62.8% | 0.7667 |
All NPC vs. PC | >731.5 U/ml | 180 | 8 | 71 | 42 | 83.4% | 95.7% | 62.8% | 0.7979 |
Stage I NPC vs. HC | >1,055 U/ml | 6 | 2 | 51 | 2 | 93.4% | 75.0% | 96.2% | 0.9033 |
Stages I and II NPC vs. HC | >964.5 U/ml | 25 | 4 | 50 | 3 | 91.5% | 86.2% | 94.3% | 0.9115 |
All NPC vs. HC | >1,022 U/ml | 170 | 18 | 51 | 2 | 91.7% | 90.4% | 96.2% | 0.9498 |
Comparison | BamHI‐W 121 bp | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >0 copy/ml | 14 | 6 | 48 | 1 | 89.9% | 70.0% | 98.0% | 0.8459 |
Stages I and II NPC vs. PC | >0 copy/ml | 28 | 8 | 48 | 1 | 89.4% | 77.8% | 98.0% | 0.8861 |
All NPC vs. PC | >0 copy/ml | 48 | 14 | 48 | 1 | 86.5% | 77.4% | 98.0% | 0.8845 |
Stage I NPC vs. HC | >0 copy/ml | 14 | 6 | 8 | 4 | 68.8% | 70.0% | 66.7% | 0.6333 |
Stages I and II NPC vs. HC | >0 copy/ml | 28 | 8 | 8 | 4 | 75.0% | 77.8% | 66.7% | 0.6736 |
All NPC vs. HC | >0 copy/ml | 48 | 14 | 8 | 4 | 75.7% | 77.4% | 66.7% | 0.7218 |
Comparison | ebv‐miR‐BART7‐3p | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >5.565 FCOD | 15 | 4 | 38 | 5 | 85.5% | 78.9% | 88.4% | 0.8550 |
Stages I and II NPC vs. PC | >4.145 FCOD | 30 | 5 | 31 | 12 | 78.2% | 85.7% | 72.1% | 0.8399 |
All NPC vs. PC | >4.085 FCOD | 52 | 19 | 31 | 12 | 72.8% | 73.2% | 72.1% | 0.7737 |
Stage I NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
Stages I and II NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
All NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
Comparison | hsa‐miR‐29a‐3p | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >9.760 FCOD1 | 6 | 12 | 23 | 0 | 70.7% | 33.3% | 100.0% | 0.6763 |
Stages I and II NPC vs. PC | >9.760 FCOD1 | 9 | 23 | 23 | 0 | 58.2% | 28.1% | 100.0% | 0.5639 |
All NPC vs. PC | <8.200 FCOD | 25 | 21 | 15 | 8 | 58.0% | 54.3% | 65.2% | 0.5071 |
Stage I NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
Stages I and II NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
All NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
Stages II to IVC NPC vs. PC | <8.300 FCOD | 22 | 6 | 14 | 9 | 70.6% | 78.6% | 60.9% | 0.6250 |
Comparison | hsa‐miR‐103a‐3p | ||||||||
---|---|---|---|---|---|---|---|---|---|
Cutoff | TP | FN | TN | FP | Accuracy | Sensitivity | Specificity | AUC | |
Stage I NPC vs. PC | >10.89 FCOD1 | 5 | 13 | 20 | 3 | 61.0% | 27.8% | 87.0% | 0.5060 |
Stages I and II NPC vs. PC | <9.270 FCOD | 19 | 13 | 15 | 8 | 61.8% | 59.4% | 65.2% | 0.5618 |
All NPC vs. PC | <9.390 FCOD | 31 | 15 | 15 | 8 | 66.7% | 67.4% | 65.2% | 0.6144 |
Stage I NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
Stages I and II NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
All NPC vs. HC | ND | ND | ND | ND | ND | ND | ND | ND | ND |
Stages II to IVC NPC vs. PC | <9.390 FCOD | 22 | 6 | 15 | 8 | 72.5% | 78.6% | 65.2% | 0.6918 |
All cutoff values were calculated based on Youden index from ROC analysis except BamHI‐W 76 bp, EBNA‐1 99 bp and BamHI‐W 121 bp which had cutoff set as >0 copy/ml.
Cutoff is not practical due to biomarker not suitable for detection of early stage NPC.
Abbreviations: FCOD, fold change over detection limit; HC, hospital controls; PC, population controls; ND, not determined.
Measurement of plasma anti‐EBV antibodies using ELISA
Plasma VCA IgA, EBNA‐1 IgA, EA IgA and EA IgG were measured according to manufacturer's instructions (IBL International, Hamburg, Germany). The microtiter strips of VCA IgA (RE57341), EBNA‐1 IgA (RE57321), EA IgA (RE56211) and EA IgG (RE57311) ELISA kits were precoated with VCA gp 125 affinity purified from P3HR1 cells, recombinant EBNA‐1 p72 antigen expressed in Sf9‐cells, an immunodominant region of EA‐D which was affinity purified from RAJI cells, and recombinant EA p54 expressed in Escherichia coli, respectively. First, plasma samples were diluted in diluent buffer (1:401). Standard, control or diluted samples were aliquoted (100 μl each) into duplicate wells of microtiter plates, followed by 60 min incubation at 25°C or 37°C and three times washing (each time with 350 μl wash buffer per well). Then, 30 min or 1 hr incubation with 100 μl of enzyme conjugate was carried out at 25°C or 37°C, followed by another washing step as described previously. Twenty or 30 min incubation with 100 μl of 3,3′,5,5′‐tetramethylbenzidine substrate solution was subsequently carried out in the dark and the reaction was stopped by addition of 100 μl stop solution. Optical density was measured at 450 nm and average results from duplicate wells were calculated. Levels of anti‐EBV antibodies in Unit/ml were interpolated from standard curve.
Plasma DNA and RNA extractions
Frozen plasma samples were thawed and centrifuged at room temperature for 10 min at 3,000 RPM to remove any cell debris prior to DNA or RNA extractions. DNA extraction from 200 to 400 μl plasma per sample was performed using QIAamp DNA Mini kit, while automated extraction of RNA from 400 μl plasma per sample was carried out using miRNeasy Micro Kit with QIAcube according to manufacturer's protocols (Qiagen, Hilden, Germany). In order to account for possible plasma RNA extraction bias, 500 attomole of synthetic miRNA cel‐miR‐39 (Integrated DNA Technologies, Coralville, IA) was spiked into all plasma samples after mixing with QIAzol from the miRNeasy Micro Kit (Qiagen). All DNA and RNA samples were eluted in 50 and 25 μl of nuclease free water (Qiagen), respectively.
Quantification of plasma EBV DNA level
Three EBV DNA tests with different primers and hydrolysis probes were conducted in our study (Supporting Information Table S1). Quantitative polymerase chain reaction (qPCR) was carried out using TaqMan Fast Advanced Master Mix in the ABI7500 Fast Real‐Time PCR system (Applied Biosystems, Foster City, CA) according to manufacturer's instructions. A total of 5 μl eluted DNA was used in 20 μl total reaction volume in each qPCR well, and each sample was analyzed in triplicate wells. Each qPCR plate contained no‐template‐control and serially diluted Namalwa cell DNA samples as standard points for the construction of EBV DNA copy number standard curve. Namalwa cells are known to have two integrated EBV genomes per cell.36 Accurate dilution of Namalwa cell DNA standard points and quantification of EBV copy numbers by EBNA1 99 bp test were validated by calibrating these Namalwa cell DNA standard points to the 1st WHO International Standard for EBV for Nucleic Acid Amplification Techniques37 (NIBSC code: 09/260, Supporting Information Table S2). Thermal cycling conditions include 50°C for 2 min, 95°C for 20 sec, and 40 cycles of 95°C for 3 sec and 56°C for 30 sec. EBV DNA copy number was interpolated from the Namalwa cell DNA standard curve and plasma EBV DNA level was calculated using the following formula:
where c = intercept, m = slope of the standard curve, V e = DNA elution volume, V f = final DNA volume used per qPCR well, a = ml of plasma used for DNA extraction.
RT‐qPCR validation of differential miRNA expression
Pooled reverse transcription (RT) of cel‐miR‐39, hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p was carried out using commercially available assays (Applied Biosystems) according to optimized protocol which showed high reliability and consistency.38, 39 RT protocol, primers and probe sequences of ebv‐miR‐BART7‐3p were according to Zhang et al.24 RT products of each sample, negative and positive controls were analyzed in duplicate wells using TaqMan 2X Universal PCR Master Mix, No AmpErase UNG in ABI7500 Fast Real‐Time PCR system (Applied Biosystems) according to manufacturer's instructions. Data were normalized to cel‐miR‐39 (spike‐in control) and fold change over detection limit was calculated.38, 39
Statistical analysis
In GraphPad Prism software, Mann–Whitney test was used to compare the mean rank differences between NPC and controls. AUC values were generated from receiver operating characteristic (ROC) curve analysis. In SPSS software, intraclass correlation coefficient (ICC) was obtained from average‐measurement, absolute‐agreement, two‐way mixed‐effects model. Decision tree models for NPC detection and prediction of overall survival were built with sample size, decision tree growing methods, criteria and validation parameters stated in Table 2.
Table 2.
Biomarker test | Diagnostic performance | Cutoff | |||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Decision tree algorithm | Growing method | BamHI‐W as first testing criteria | Validation | BamHI‐W 76 bp | EBNA1 99 bp | EA IgG | EA IgA | VCA IgA | EBNA‐1 IgA | Name | True negative | False negative | False positive | True positive | Accuracy | Sensitivity | Specificity | AUC | BamHI‐W 76 bp (copy/ml) | EBNA1 99 bp (copy/ml) | EA IgG (U/ml) | VCA IgA (U/ml) | |
Detection of NPC1 | Classification and Regression Trees with Gini impurity measure | PN ≥ 50, CN ≥ 2, TD ≤ 5 | No | 20‐fold CV | + | − | − | − | + | − | Model 1 | 106 | 7 | 0 | 180 | 97.6% | 96.3% | 100.0% | ND | >0.2459 | NA | NA | >512.6 |
Yes | 50% train | + | − | − | − | − | − | Model 2 | 45 | 2 | 0 | 102 | 98.7% | 98.1% | 100.0% | ND | >0.1810 | NA | NA | NA | |||
50% test | 58 | 2 | 3 | 81 | 96.5% | 97.6% | 95.1% | NA | NA | NA | |||||||||||||
Classification and Regression Trees with Twoing impurity measure | No | 20‐fold CV | + | − | − | − | + | − | Model 3 | 106 | 7 | 0 | 180 | 97.6% | 96.3% | 100.0% | ND | >0.2459 | NA | NA | >512.6 | ||
Yes | 50% train | + | − | − | − | + | − | Model 4 | 60 | 0 | 0 | 88 | 100.0% | 100.0% | 100.0% | ND | >0.6786 | NA | NA | >541.8 | |||
50% test | 46 | 10 | 0 | 89 | 93.1% | 89.9% | 100.0% | ||||||||||||||||
CHAID with likelihood ratio Chi‐square statistics | PN ≥ 50, CN ≥ 2, TD ≤ 3 | No | 20‐fold CV | + | − | − | − | − | − | Model 5 | 102 | 4 | 4 | 183 | 97.3% | 97.9% | 96.2% | ND | >0 | NA | NA | NA | |
+ | − | + | − | − | − | Model 6 | 94 | 1 | 12 | 186 | 95.6% | 99.5% | 88.7% | ND | >0 | NA | >97,619 | NA | |||||
Yes | 50% train | + | − | − | − | − | − | Model 7 | 44 | 1 | 1 | 91 | 98.5% | 98.9% | 97.8% | ND | >0 | NA | NA | NA | |||
50% test | 58 | 3 | 3 | 92 | 96.2% | 96.8% | 95.1% | ||||||||||||||||
BamHI‐W 76 bp | 102 | 4 | 4 | 183 | 97.3% | 97.9% | 96.2% | 0.987 | >0 | NA | NA | NA | |||||||||||
Prognosis of NPC2 | Classification and Regression Trees with Gini impurity measure | PN ≥ 50, CN ≥ 2, TD ≤ 5 | No | 20‐fold CV | − | + | − | − | − | − | Model 8 | 31 | 8 | 16 | 25 | 70.0% | 75.8% | 66.0% | ND | NA | >14.0598 | NA | NA |
Yes | 50% train | − | + | − | − | − | − | Model 9 | 15 | 5 | 10 | 16 | 67.4% | 76.2% | 60.0% | ND | NA | >14.0451 | NA | NA | |||
50% test | 16 | 3 | 6 | 9 | 73.5% | 75.0% | 72.7% | ||||||||||||||||
Classification and Regression Trees with Twoing impurity measure | No | 20‐fold CV | − | + | − | − | − | − | Model 10 | 31 | 8 | 16 | 25 | 70.0% | 75.8% | 66.0% | ND | NA | >14.0598 | NA | NA | ||
Yes | 50% train | − | + | − | − | − | − | Model 11 | 19 | 3 | 7 | 14 | 76.7% | 82.4% | 73.1% | ND | NA | >14.0598 | NA | NA | |||
50% test | 12 | 5 | 9 | 11 | 62.2% | 68.8% | 57.1% | ||||||||||||||||
CHAID with likelihood ratio Chi‐square statistics | PN ≥ 50, CN ≥ 2, TD ≤ 3 | No | 20‐fold CV | − | + | − | − | − | − | Model 12 | 31 | 9 | 16 | 24 | 68.8% | 72.7% | 66.0% | ND | NA | >14.4270 | NA | NA | |
Yes | 50% train | − | + | − | − | − | − | Model 13 | 24 | 13 | 3 | 6 | 65.2% | 31.6% | 88.9% | ND | NA | >137.998 | NA | NA | |||
50% test | 16 | 7 | 4 | 7 | 67.6% | 50.0% | 80.0% | ||||||||||||||||
EBNA1 99 bp | 31 | 8 | 16 | 25 | 70.0% | 75.8% | 66.0% | 0.709 | NA | >14.0600 | NA | NA | |||||||||||
BamHI‐W 76 bp | ND | ND | ND | ND | ND | ND | ND | 0.680 | ND | NA | NA | NA | |||||||||||
EA IgA | ND | ND | ND | ND | ND | ND | ND | 0.518 | ND | NA | NA | NA | |||||||||||
EA IgG | ND | ND | ND | ND | ND | ND | ND | 0.545 | ND | NA | NA | NA | |||||||||||
EBNA‐1 IgA | ND | ND | ND | ND | ND | ND | ND | 0.525 | ND | NA | NA | NA | |||||||||||
VCA IgA | ND | ND | ND | ND | ND | ND | ND | 0.516 | ND | NA | NA | NA |
Data set included 187 NPC patients and 106 population controls who had test results of six established biomarkers. Positive = NPC; Negative = Population control.
Data set included 80 NPC patients who completed radical treatment, had overall survival information and test results of six established biomarkers. Positive = Dead; Negative = Alive.
Abbreviations: +, included in decision tree; −, not included in decision tree; AUC, area under curve; CHAID, Chi‐square Automatic Interaction Detector; CN, child node; CV, cross validation; NA, not applicable ND, not determined; PN, parental node; TD, tree depth.
Results
Plasma EBV DNA
Demographic and clinicopathological characteristics of NPC patients and controls are shown in Supporting Information Table S3. All 10 plasma biomarkers analyzed in our study did not correlate with age and were not significantly different between different sex and ethnic groups (Supporting Information Table S4). In our hands, results of EBV DNA test from DNA extraction replicates had excellent test–retest reliability (ICC > 0.95, Supporting Information Fig. S1 a). We also found that prior to plasma processing, plasma EBV DNA load was fairly stable up to 6 hr in EDTA blood tube kept on bench at room temperature (Supporting Information Fig. S1 b).
Comparison of plasma EBV DNA load as measured by two established EBV DNA tests (BamHI‐W 76 bp and EBNA1 99 bp, Figs. 1 a and 1 b) were carried out between NPC patients and controls. In general, plasma EBV DNA loads were significantly higher in NPC patients compared to controls, and only low levels of plasma EBV DNA load was observed in a small subset of controls (Figs. 1 a and 1 b). The level of plasma EBV DNA increases with more advanced stages (Figs. 1 a and 1 b). Similar to the large cohort NPC screening study in Hong Kong,20 plasma EBV DNA load of >0 copy/ml was set as positive for both plasma EBV DNA tests (Table 1). This resulted in 94.2% and 99.2% specificity, respectively for BamHI‐W 76 bp and EBNA1 99 bp to identify NPC against population controls. Specificity for BamHI‐W 76 bp and EBNA1 99 bp to identify NPC against hospital controls were 90.4% and 99.2%, respectively (Table 1). BamHI‐W 76 bp being the EBV DNA test with highest sensitivity to detect NPC had 96.7% (29/30) sensitivity to detect Stage I NPC, 96.7% (58/60) sensitivity to detect early stage (Stages I and II) NPC and 97.4% (226/232) sensitivity to detect all NPC (Table 1). Based on recent findings that NPC patients had significantly longer fragment lengths of plasma EBV DNA compared to non‐NPCs,21 the new BamHI‐W 121 bp test was evaluated in a subset of our study samples with more early stage NPC cases as well as cases with false positive results as determined by the two common EBV DNA tests (Fig. 2 a). When testing NPC against controls, improved specificity but decreased sensitivity was found with BamHI‐W 121 bp as compared to BamHI‐W 76 bp (Supporting Information Fig. S2).
Plasma anti‐EBV antibodies
Moderately good to excellent test–retest reliability (ICC of 0.837–0.998) was achieved by commercially available ELISA tests measuring plasma VCA IgA, EBNA‐1 IgA, EA IgA and EA IgG (Supporting Information Fig. S1 c).
Comparison of ELISA results between NPC patients and controls showed that plasma level of anti‐EBV antibodies was generally higher in NPC patients as compared to controls. No obvious trend was observed across different NPC stages and high levels of plasma anti‐EBV antibodies were observed in some controls (Figs. 1 c–1 f). Among these four anti‐EBV antibody tests evaluated in our study, VCA IgA and EA IgG consistently had higher AUC values to detect early stage NPC against all controls, while EBNA‐1 IgA consistently showed the lowest AUC values among the established biomarkers (Fig. 3 and Table 1).
Plasma miRNAs
Plasma ebv‐miR‐BART7‐3p, hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p were shortlisted for validation in a subset of our study samples enriched with more early stage NPC cases (Table 1). In general, plasma ebv‐miR‐BART7‐3p levels were higher in NPC compared to population controls and a portion of population controls also had detectable plasma ebv‐miR‐BART7‐3p (Fig. 2 b and Table 1). Similar median levels of plasma hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p were observed between population controls and Stage I NPC (Figs. 2 c and 2 d). It appeared that there was a decreasing trend in plasma hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p with the advancement of NPC stage (Figs. 2 c and 2 d).
Combination of plasma biomarkers for the detection of NPC
In order to evaluate if combination of plasma biomarkers may improve NPC detection, decision tree modeling was carried out on our data set comprising of 187 NPC cases and 106 population controls with available results of six plasma biomarkers (Table 2 and Supporting Information Table S3). BamHI‐W 76 bp test alone appeared to be sufficient for the detection of NPC, and appeared to be essential in all seven decision tree models (Table 2). Models 2, 5 and 7 suggested that BamHI‐W 76 bp test alone is sufficient (Table 2). Models 1, 3, and 4 suggested that combining VCA IgA with BamHI‐W 76 bp test can improve specificity at the expense of reduced sensitivity while Model 6 suggested that combining EA IgG with BamHI‐W 76 bp test can further increase sensitivity at the expense of decreased specificity (Table 2 and Supporting Information Fig. S3).
Plasma EBV DNA load as a prognosis marker for NPC overall survival
Survival information and test results of six plasma biomarkers were available for a subset of our NPC cases who had completed radical treatment (n = 80, Supporting Information Table S3). ROC analysis and decision tree modeling were carried out to evaluate if any of these six plasma biomarkers had prognostic value for the survival of these NPC patients (Table 2). According to ROC analysis, EBNA1 99 bp was the only biomarker with AUC > 0.7 (Table 2). With a cutoff at 14.06 copy/ml, EBNA1 99 bp could identify NPC patients with poor overall survival (Fig. 4 a) as well as poor progression‐free survival (Fig. 4 b) in both early stage and late stage NPC (Fig. 4). Decision tree modeling supported findings from this ROC analysis, revealing that EBNA1 99 bp with cutoff at about 14 copy/ml (Models 8–12) is sufficient for prognosis of survival while increasing EBNA1 99 bp cutoff to 138 copy/ml (Model 13) led to higher specificity but lower sensitivity in prognosis of survival (Table 2). Notably, EBNA1 99 bp with cutoff at about 14 copy/ml was still the only biomarker chosen by decision tree modeling even though additional information including age, sex, ethnicity, WHO type and AJCC staging were added into the analysis (data not shown).
Discussion
In our study, 10 plasma biomarkers (BamHI‐W 76 bp, BamHI‐W 121 bp, EBNA1 99 bp, EA IgA, EA IgG, EBNA‐1 IgA, VCA IgA, ebv‐miR‐BART7‐3p, hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p) were systematically analyzed for early detection and prognosis of NPC. These included established and newly reported NPC biomarkers of EBV and human origin.
To our knowledge, published case–control studies which reported 50–86% sensitivity of plasma EBV DNA test for Stage I NPC had only analyzed two to 22 cases.15, 19 Our study which include larger sample size of Stage I NPC (n = 30) for plasma EBV DNA test revealed 96.7% (29/30) sensitivity to detect Stage I NPC. Besides larger sample size, our improved sensitivity findings may be due to lower qPCR platform detection limit (25 copy/ml) achieved with usage of more advanced qPCR master mix in our study as compared to other studies.15, 19 Our findings from comparison of BamHI‐W 121 bp test and BamHI‐W 76 bp test (Supporting Information Fig. S2) support the notion that the larger the qPCR amplicon size, the more specific but less sensitive is the EBV DNA qPCR test. This is consistent with the findings reported earlier which compared the performance of EBNA1 213 bp test and EBNA1 99 bp test.40 It is estimated that increase in input volume by eight times may compensate the sensitivity issue of BamHI‐W 121 bp test as compared to BamHI‐W 76 bp test, hypothetically from qPCR Cq 40 (undetected) to Cq 37, but will incur higher cost and larger effort in sample processing and DNA extraction. Interestingly, four hospital controls were positive in both plasma BamHI‐W 76 bp and BamHI‐W 121 bp tests (Supporting Information Fig. S2). It is possible that these tests were sensitive enough to detect NPC in cases which were too early to be detected clinically. A follow‐up on these individuals to check on event of NPC will be interesting.
In the EBV genome, there is only one copy of EBNA1 gene while BamHI‐W region may be reiterated by 7 to 11 repeats.41 Prevalent EBV in different populations may differ in the numbers of BamHI‐W region repeats, making prognostic cutoff value of pretreatment plasma BamHI‐W 76 bp level deduced from one cohort not optimal for another cohort.42, 43, 44 If plasma BamHI‐W 76 bp test results are intended to be used for prognosis, EBV DNA clearance rate calculated from pretreatment and posttreatment plasma EBV DNA load may be analyzed to rule out interindividual variability. Indeed, in a systematic review and meta‐analysis on the prognosis of NPC by plasma BamHI‐W 76 bp test, Zhang et al. showed that cutoff for EBV DNA clearance rate was comparable among studies cohort.42 In our study, pretreatment plasma EBNA1 99 bp and BamHI‐W 76 bp tests had similar prognostic values (AUC 0.709 and 0.680, respectively). Unlike BamHI‐W 76 bp test, pretreatment plasma EBNA1 99 bp test is not affected by interindividual variability and do not require multiple sampling to calculate EBV DNA clearance rate. It would be interesting to investigate if the cutoff value of pretreatment plasma EBNA1 99 bp level deduced in our study is applicable to future follow‐up studies.
Our study had served as an external independent study and validated the diagnostic performance of two newly reported biomarkers (BamHI‐W 121 bp and ebv‐miR‐BART7‐3p). Specificity of ebv‐miR‐BART7‐3p appeared to be less optimal as it was detected in about 28% (12/43) of population controls (Table 1), which is in line with recent findings from Ramayanti et al.32 but not Gao et al.29 The discrepancy may be due to the differences in PCR primers. Meanwhile the diagnostic performance of hsa‐miR‐29a‐3p and hsa‐miR103a‐3p reported elsewhere25 could not be reproduced in our study, possibly due to inclusion of more early stage NPC and less advanced stage NPC in our analysis. Consistent with findings from a previous report,25 differences in plasma hsa‐miR‐29a‐3p levels seemed to be more apparent only when comparing controls to advanced stage NPC (Fig. 2 c). It is possible that four other miRNAs (ebv‐BART2‐5p, ebv‐miR‐BART13‐3p, hsa‐miR‐483‐5p and hsa‐let‐7c) that are not included for validation in our study may perform well as early diagnosis markers for NPC. EBV DNA markers are already well established for NPC screening. From a clinical utility viewpoint, the additional value of including non‐EBV markers may be higher than the additional value of including another EBV marker in the NPC detection panel. Our study indicates that much effort is still needed to identify a combination panel of EBV markers and non‐EBV markers that will benefit the detection of not only the majority of NPC cases which are EBV positive but also the small subset of NPC cases which are EBV negative.
Conclusions
Our study provides important information to policy makers in LMICs who have limited health care resources to plan a more cost‐effective NPC screening and monitoring strategy for the apparently healthy asymptomatic controls. We showed that the diagnostic performance of established biomarkers to detect NPC in local general population were comparable to findings of studies from another NPC endemic area15 and plasma BamHI‐W 76 bp test is superior for early detection of NPC. Comparison of plasma biomarkers in NPC patients and local hospital controls suggests that plasma EBV DNA test could identify NPC cases among individuals who visit the hospital for other conditions in local setting, thus allowing for opportunistic screening. Combined biomarker tests from single sampled specimens can improve NPC detection specificity (with slight decrease in sensitivity) and avoid logistic problems of resampling. Plasma EBNA1 99 bp test may have important prognostic value and could be used to stratify NPC patients for different clinical management.
Supporting information
Acknowledgements
The authors thank the Director General of Health Malaysia for his approval of the publication of this article. The authors also thank the Director of Institute for Medical Research Malaysia for her support in this study. The authors are grateful to all staff from the Molecular Pathology unit, Biospecimen Bank at the Institute for Medical Research and hospitals involved in this study for their assistance in sample and data collection.
Conflict of interest: The authors declare no conflict of interest.
Author contributions: L.P.T., G.W.T., S.V.M., S.L.G., C.S.L., T.B.B.M.M., C.C.N. conducted experiments and acquired experimental data. W.R.K., X.J.N., N.S.M.D., C.S.H.O., C.Y.W., C.A.O., Y.Y.Y., F.H., K.C.P., C.E.K. and the M.N.C.S.G. recruited patients, acquired and interpreted clinical data. L.P.T. and G.W.T. analyzed and interpreted data. L.P.T. wrote the manuscript. A.S.B.K. and G.W.T. critically reviewed and improved the manuscript.
Data availability
The data that support the findings of our study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of our study are available from the corresponding author upon reasonable request.