University of Groningen Epstein-Barr virus-associated malignancies Tan, Geok Wee

Epstein-Barr virus-associated malignancies

Tan, Geok Wee

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10.33612/diss.173425402

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Tan, G. W. (2021). Epstein-Barr virus-associated malignancies: Susceptibility factors and molecular detection in liquid biopsies. University of Groningen. https://doi.org/10.33612/diss.173425402

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A novel and non‐invasive approach 

utilizing nasal washings 

for the detection of 

nasopharyngeal carcinoma

CHAPTER

 6

Abstract

Nasopharyngeal carcinoma (NPC) is an epithelial cancer of the nasopharynx which is highly associated with Epstein–Barr virus (EBV). Worldwide, most of the top 20 countries with the highest incidence and mortality rates of NPC are low‐ and middle‐income countries. Many studies had demonstrated that EBV could be detected in the tissue, serum and plasma of NPC patients. In this study, we explored the potential of assays based on non‐invasive nasal washings (NW) as a diagnostic and prognostic tool for NPC. A total of 128 patients were evaluated for NW EBV DNA loads and a subset of these samples were also tested for 27 EBV and human miRNAs shortlisted from literature. EBV DNA and seven miRNAs showed area under the receiver operating characteristic curve (AUC) values of more than 0.7, suggestive of their potential utility to detect NPC. Logistic regression analyses suggested that combination of two NW assays that test for EBNA‐1 and

hsa‐miR‐21 had the best performance in detecting NPC. The trend of NW EBV DNA load matched with clinical outcome of 71.4% (10 out of 14) NPC patients being followed‐up. In summary, the non‐invasive NW testing panel may be particularly useful for NPC screening in remote areas where healthcare facilities and otolaryngologists are lacking and may encourage frequent testing of individuals in the high-risk groups who are reluctant to have their blood tested. However, further validation in an independent cohort is required to strengthen the utility of this testing panel as a non‐invasive detection tool for NPC.

What’s new?

Nasopharyngeal carcinoma (NPC) is highly associated with Epstein–Barr virus (EBV) and is mostly prevalent in Southeast Asia. While EBV serology and EBV DNA load from nasopharyngeal swab or plasma are valuable early detection tests, a lack of resources has limited their implementation. This study found that the performance of nasal washings EBV DNA testing for the detection of NPC is superior to urine EBV DNA testing but inferior to EBV DNA testing from nasopharyngeal swab and blood. Nonetheless, nasal washings testing may be valuable in remote areas lacking healthcare facilities and lower invasiveness may encourage frequent testing for high-risk groups.

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1. Introduction

Nasopharyngeal carcinoma (NPC) is an epithelial cancer of the nasopharynx. It is highly prevalent in Southeast Asia and the Southern part of China but very rare in most part of the world. Family members of NPC patients have four‐ to eight‐fold higher risk than the general population in developing NPC1_{. According to GLOBOCAN's estimates, 17 of the 20} countries with highest NPC incidence and mortality rates worldwide are low‐ and middle‐income countries (LMICs)2_{. In Malaysia, the group with lowest social class were} reported to have a four‐fold higher risk of disease3_{and some of the high incidence regions} are in remote areas where access to healthcare is limited. Majority of NPC cases frequently presented late4_{leading to poor survival rate}5_.

The etiology of NPC is a complicated interaction between genetic, dietary and viral (Epstein Barr Virus [EBV]) factors6_{. Reports showed that EBV could be detected in NPC} cells most of the time, while traces of EBV could also be found in the blood, urine and saliva of NPC patients7–9_{. Early detection tests such as EBV serology, EBV DNA load from} nasopharyngeal swab/brush and plasma are valuable for NPC screening and patient management. Recent large cohort NPC screening studies in Southern China had demonstrated the utilities of these tests as early detection tool for NPC10,11_{. However,} these NPC screening tests have yet to be adopted in LMICs with high NPC incidence rates due to many reasons. Lack of resources to store and process biospecimen for screening tests as well as access to endoscopic examination by otolaryngologists are among some of the reasons. In LMICs and remote areas, a useful non‐invasive test may encourage frequent testing of individuals from the high-risk groups for early detection and aids in the monitoring of disease recurrence.

MiRNAs are a group of small non‐coding RNAs which alter gene expression post‐transcriptionally12_{and its dysregulation has been identified in many cancers including} NPC13,14_{. Over the course of about a decade, miRNA signatures unique to NPC had been} reported based on studies in tissue, serum and plasma. As discordance between tissue miRNAs and circulating miRNAs is a known issue15_{and it is assumed that miRNAs in NW} samples may be more similar to cellular miRNAs than circulating miRNAs, five published Gene Expression Omnibus (GEO) datasets were compared to identify miRNAs which were consistently dysregulated between NPC and control tissues. Together with EBV DNA loads, levels of selected EBV and human miRNAs were examined in nasal washings (NW) of NPC patients and non‐NPC patients. The aims of this study were (i) to evaluate the diagnostic value of NW EBV DNA and NW miRNAs for NPC and, (ii) to determine if NW EBV DNA could be utilized as a monitoring tool for post‐treatment NPC patients.

2. Materials and Methods

2.1. Patients and samples

Patients were recruited from the Department of Otorhinolaryngology in Selayang Hospital and the Department of Oncology and Radiotherapy in Kuala Lumpur Hospital with informed consent and ethics approval from the Medical Research and Ethics Committee, Ministry of Health Malaysia. All NPC patients were histologically diagnosed as NPC while controls were non‐NPC patients from the otorhinolaryngology clinic. Details of the non‐NPC group are depicted in Figure 1. Collection of NW sample was carried out by the patient himself/herself. Five milliliters of saline was pushed through the left nostril to the right nostril from a syringe and nasal washings was collected in a kidney dish. The same procedure was repeated for the right nostril to the left nostril. The combined nasal washings were then poured into a plastic bottle and stored at −20 °C.

Patients included in the study n = 128 Non-NPC patients

(ear, nose and throat symptoms) n = 73 NPC patients n = 55 Others n = 17 Lymphoid hyperplasia n = 3

Rhinitis, sinusitis, rhinosinusitis n = 32

Nasal polyps n = 8 Tinnitus, otiti s, hearing loss

n = 8 Lymphadenopathy

n = 5 Pre-treatment_{n = 41} Pre-treatment and_{post-treatment}

n = 5 Post-treatment n = 9 Evaluation of markers for NPC detection n = 119 Evaluation of markers for NPC monitoring n = 14

Figure 1. Overview of experimental design. EBV DNA and microRNAs from the nasal washings (NW) of non-NPC and pre-treatment NPC were evaluated to develop detection tool for NPC (indicated by solid line). Multiple time points NW samples from NPC patients were included in the evaluation of EBV DNA as a monitoring tool for NPC (indicated by dashed line).

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2.2. DNA and RNA extractions

Frozen NW samples were thawed and centrifuged at 4000 RPM, 4 °C for 20 min. Cell pellets were resuspended with 400 μl of phosphate buffered saline and separated into two 200 μl aliquots for separate extraction of DNA and RNA. DNA and RNA extractions were performed using QIAamp DNA Mini kit and miRNeasy Micro Kit (Qiagen, Germany), respectively, according to manufacturer's instructions. Synthetic miRNAs (cel‐miR‐39 and cel‐miR‐54) were spiked in during RNA extraction after the addition of lysis buffer.

2.3. Quantification of EBV DNA

EBV DNA loads were evaluated by quantifying PCR products amplified from the BamHI‐W region and EBNA‐1 of EBV. Sequences of primers and probes used for the detection of EBV

DNA were according to previous publications7,16_{with FAM and MGB as fluorochrome and} quencher, respectively for probes. Quantitative Polymerase Chain Reaction (qPCR) was carried out in triplicates for each sample. No‐template‐control and a series of standard points from serial dilution of Namalwa cells DNA were run in each qPCR plate. EBV DNA copy number was interpolated from the standard curve and results were calculated using the following formula:

EBV DNA load = [(average Cq– c)/m] x (elution volume/volume used for qPCR) (Cq= quantitation cycle, c = intercept, m = slope of the standard curve)

All EBV DNA positive NW samples with Cqvalue in only one qPCR wells and/or out of the interpolation range were arbitrarily set as one copy EBV DNA.

2.4. Evaluation of miRNA expression

Twenty‐seven miRNAs were shortlisted from GEO DataSets for further validation in RT‐qPCR (Supplementary Table S1). Selection criteria is described in Supplementary Methods.

RNA samples were subjected to reverse transcription (RT), preamplification and qPCR carried out in triplicates according to the optimized protocol that had demonstrated high

consistency of miRNA detection in high‐throughput microfluidic

platform17,18_{. No‐template‐control and a series of standard points from serial dilution of} pooled human cell/xenograft RNA were run in the same dynamic array. Assays that did not exhibit linear amplification and data points that were beyond the reliable detection limit (Cq> 25) were excluded from analysis. Average Cqvalues for NW were normalized to spiked‐in synthetic oligonucleotides to remove technical bias17_{. For comparison of miRNA} levels between NW samples, fold change over the detection limit was calculated using the following formula:

2.5. Statistical analysis

Mann Whitney test was applied to compare the differences between two groups of samples. Area under the curve (AUC) of receiver operating characteristic (ROC) were calculated to evaluate the performance of markers as classifier for NPC. Optimal cut‐off values were obtained by calculating Youden's index. Logistic regression was used to determine if combination of markers could lead to improved classifier performance for NPC.

3. Results and Discussions

3.1. Characteristics of study population

A total of 128 patients comprising of 55 NPC and 73 non‐NPC were assessed for their NW EBV DNA loads and miRNA levels. Samples collected at multiple time points from 14 NPC patients and their follow‐up information were available for analysis. Overview of the experimental details is shown in Figure 1. Between the non‐NPC patient samples and pre‐treatment NPC samples, there were no significant differences in the distribution of age, ethnicity and gender (Supplementary Table S2).

3.2. NW EBV DNA load as biomarker for NPC detection and monitoring

In our study, we showed that even though NW sampling was carried out by different operators (the test subject himself/herself), NW EBV DNA test results were consistent and reproducible (Supplementary Figure S1). Pre‐treatment NPC samples were shown to have significantly higher NW EBV DNA load than the non‐NPC samples (Figures 2A and 2B). ROC analysis suggested that NW EBV DNA is good at classifying non‐NPC from pre‐treatment NPC patients (Figure 2J and Supplementary Table S3). Patients with larger tumor size (T3 and T4) appeared to have higher median of NW EBV DNA load as compared to those with smaller tumor size (T1 and T2) (Supplementary Figure S2). When remission samples were compared to residual NPC samples, higher median NW EBV DNA load was seen in the residual NPC samples (Supplementary Figure S3).

Different NW EBV DNA trends were observed in NW samples collected at multiple time points from 14 NPC patients (Figure 3). Among these cases, 71.4% (10/14, Figures 3A – 3J) had NW EBV DNA trends that corresponded to their clinical outcomes. Consistently undetectable or decreasing NW EBV DNA load was observed in eight of the remission cases (Figures 3A – 3H), while increasing NW EBV DNA load was observed in a recurrent NPC (Figure 3I) and a residual NPC (Figure 3J). For the case depicted in Figure 3I, follow‐up clinical examination and cytology test of nasal swab reported no malignancy but increasing NW EBV DNA load was detected. This case was not clinically diagnosed as recurrence until 10 months later. For the case shown in Figure 3J, consistent high levels of

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clinical diagnosis of residual NPC. Among the four cases which NW EBV DNA load did not correspond to the clinical outcome, possible reasons include: (i) false positive, as the increment was from undetected to one copy (Figure 3K), (ii) no tumor in the nasopharynx leading to negative NW EBV DNA test results even though patients had distant metastasis (Figures 3L and 3M) and (iii) possible true EBV negative for recurrent NPC (Figure 3N). Limitation of NW EBV DNA test to detect EBV negative NPC cases suggested the importance to include non‐EBV markers in the detection panel.

3.3. NW miRNA as biomarker for NPC detection

GEO2R analysis on five NPC tissue miRNA profiling data sets obtained from NCBI GEO database (GSE70790, GSE43039, GSE32960, GSE36682 and GSE32906) was performed to identify dysregulated miRNAs in NPC. Thirteen consistently dysregulated miRNAs in at least three of the five studies, together with an additional 14 miRNAs dysregulated in at least one of the five studies were selected for further validation (Supplementary Table S1). Due to insufficient material, only 35 NPC and 64 non‐NPC samples were evaluated for NW miRNAs. One out of 27 miRNA assays failed and was excluded from further analysis (Supplementary Table S1). Among the miRNAs analyzed, 69.3% (18/26) were detected in NW samples. Low and inconsistent levels of RNU6B, RNU44 and RNU48 in NW samples (data not shown) suggested that there were limited cellular RNA and a mixture of cell‐free miRNAs from biofluid within the nasal cavity. As a result, these endogenous small RNA were not applicable as reference gene for NW data normalization. Based on data normalized to cel‐miR‐39 spike‐in controls, RT‐qPCR results indicated that 38.9% (7/18) of the miRNAs detected in NW, namely hsa‐miR‐21, hsa‐miR‐26a, hsa‐miR‐29c, hsa‐miR‐93, hsa‐miR‐205, hsa‐miR‐375 and hsa‐miR‐421 were significantly upregulated in pre‐treatment NPC compared to non‐NPC NW samples (Figures 2C ‐ 2I). In ROC analysis, the AUC of these miRNAs were all above 0.7 in classifying non‐NPC from pre‐treatment NPC (Figure 2J and Supplementary Table S3). Levels of hsa‐miR‐21, hsa‐miR‐26a, hsa‐miR‐29c and hsa‐miR‐93 appeared to be associated with larger tumor size (Supplementary Figure S2).

Pre-treatment NPC non-NPC 0 4 8 12 16 hsa-miR-21 Fo ld ch an ge **** Pre-treatment NPC non-NPC 0 4 8 12 16 hsa-miR-29c **** Pre-treatment NPC non-NPC 0 4 8 12 16 hsa-miR-26a *** Pre-treatment NPC non-NPC 0 4 8 12 16 hsa-miR-93 *** Pre-treatment NPC non-NPC 0 4 8 12 16 hsa-miR-205 Fo ld ch an ge **** Pre-treatment NPC non-NPC 0 4 8 12 16 hsa-miR-375 **** Pre-treatment NPC non-NPC 0 4 8 12 16 hsa-miR-421 *** EBNA-1 Pre-treatment NPC non-NPC 10-2 100 102 104 106 EB V D N A lo ad **** BamHI-W Pre-treatment NPC non-NPC 10-2 100 102 104 106 EB V D N A lo ad **** Fo ld ch an ge Fo ld ch an ge Fo ld ch an ge Fo ld ch an ge Fo ld ch an ge A B C D E F G H I J 1 - Specificity0.4 0.6 0.8 1.0 0.2 0.0 Se ns iti vi ty 1.0 0.8 0.6 0.4 0.2 0.0 hsa-miR-421 hsa-miR-375 hsa-miR-205 hsa-miR-93 hsa-miR-29c hsa-miR-26a hsa-miR-21 EBNA-1 BamHI-W Regression model

Figure 2. EBV DNA load and differentially expressed miRNAs in nasal washings. EBV DNA load measured by (A) BamHI‐W and (B) EBNA‐1 were significantly different between pre‐treatment NPC

samples (n = 46) and non‐NPC samples (n = 73) (Mann–Whitney test, **** p  ≤ 0.0001). EBV DNA load was set as 0.1 (arbitrary value) for samples below detection limit (Cq > 40) and 1 to indicate

samples that were weak positive. (C) hsa‐miR‐21, (D) hsa‐miR‐26b, (E) hsa‐miR‐29c, (F) hsa‐miR‐93, (G) hsa‐miR‐205, (H) hsa‐miR‐375 and (I) hsa‐miR‐421 in nasal washings of pre‐treatment NPC (n = 35) and non‐NPC (n = 64) samples were significantly different (Mann Whitney test, *** p  ≤ 0.001; **** p  ≤ 0.0001). (J) Receiver operating characteristics curve discriminating pre‐treatment NPC from non‐NPC. Area under curve for all markers are above 0.7 as shown in Supplementary Table S4.

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last seen well completion

of RT completion_{of RT last seen well} completion_{of RT last seen well}

completion of NAC completion of CCRT completion of AC

last seen well no evidence

of tumour

completion

of RT _{last seen well}

completion

of RT _{last seen well}

completion

of RT last seen well

completion

of RT last seen well

completion of RT recurrence defaulted CCRT for traditional treatment residual completion of palliative RT completion of palliative CT NPC with local and intracranial extension completion of palliative CT completion of RT recurrence completion of NAC completion of CCRT no lesion within

nasopharynx lung metastasis_palliative CTno evidence

of local recurrence

completion

of RT lung metastasis last seen well

months since first diagnosis

EB V D N A lo ad 0 5 10 15 20 25 10-2 10-1 100 101 102 103 104 105 55 60

months since first diagnosis

EB V D N A lo ad 0 5 10 15 10-2 10-1 100 101 102 103 104 105 52 10 0 10 -2 10-1 100 101 102 103 104 105 16 18 20 76

months since first diagnosis

EB V D N A lo ad 0 5 10 15 20 25 10-2 10-1 100 101 102 103 104 105 45 months since first diagnosis

EB V D N A lo ad

months since first diagnosis

EB V D N A lo ad 0 5 10 10-2 10-1 100 101 102 103 104 105 75 100 110

months since first diagnosis

EB V D N A lo ad 0 10 10-2 10-1 100 101 102 103 104 105 120 125 130 162

months since first diagnosis

EB V D N A lo ad 0 5 10 15 20 25 10-2 10-1 100 101 102 103 104 105 40 0 5 10 15 20 25 30 10-2 10-1 100 101 102 103 104 105

months since first diagnosis

EB V D N A lo ad 0 5 10 15 20 25 30 10-2 10-1 100 101 102 103 104 105

months since first diagnosis

EB V D N A lo ad 0 5 10-2 10-1 100 101 102 103 104 105 35 4045 50 5560 65 70 months since first diagnosis

EB V D N A lo ad

months since first diagnosis

EB V D N A lo ad 0 5 10 10-2 10-1 100 101 102 103 104 105 23 25 27 50 55 0 5 10 15 20 25 30 10-2 10-1 100 101 102 103 104 105

months since first diagnosis

EB V D N A lo ad 5 10 15 20 10-2 10-1 100 101 102 103 104 105

months since first diagnosis

EB V D N A lo ad 5 10 15 20 25 30 10-2 10-1 100 101 102 103 104 105

months since first diagnosis

EB V D N A lo ad 0 0 A B C D E F G H I J K L M N

Figure 3. EBV DNA load in nasal washings of NPC patients collected at multiple time points. Each graph represents the trend of NW EBV DNA load (measured by EBNA‐1 assay) for one patient. Each

dot represents NW EBV DNA load at the indicated time point. (A) – (H) Patients were last known to be well and had decreasing or undetectable NW EBV DNA load after treatment. (I) and (J) Increasing NW EBV DNA load in patients with recurrence/residual NPC. (K) Undetectable and weak positive NW EBV DNA load in complete remission patient. (L) – (N) Undetectable or decreasing NW EBV DNA load in patients with lung metastasis or recurrence. RT, radiotherapy; NAC, neoadjuvant chemotherapy;

Two of the upregulated NW miRNAs, hsa‐miR‐93 and hsa‐miR‐205 concurred with the findings of other studies19,20_{. Both hsa‐miR‐93 and hsa‐miR‐205 were shown to be} upregulated in NPC tissue samples21,22_{and could lead to enhance cell growth, migration} and invasion in NPC cell lines21,23_{. Meanwhile, hsa‐miR‐21 and hsa‐miR‐421 that were} shown to be upregulated in NW were consistent with the trend reported by one to two NPC tissue profiling studies (Supplementary Table S1). Three of the upregulated NW miRNAs, namely hsa‐miR‐26a, hsa‐miR‐29c and hsa‐miR‐375, were previously reported to be downregulated in NPC tissues as compared to control tissues20,24,25_{. Discordance of} circulating miRNA profiles with tissue miRNA profiles is a common issue15_{. Studies of NPC} tissues compare cellular miRNAs between tumor and normal epithelial cells while our study using NW analyzed a mixture of cellular and cell‐free miRNAs from tumor, as well as from other cell types and biofluid within the nasal cavity. Hence differences in levels may also not be directly comparable. Nonetheless, we postulate that, just like EBV DNA, the significantly upregulated NW miRNAs which were associated with tumor size are highly enriched in tumor cells.

3.4. Performance of combined markers for NPC detection

NW EBV DNA and seven microRNAs that were shown to have significant differences between the pre‐treatment NPC and non‐NPC, as well as AUC > 0.7 were included in the logistic regression analyses. Simple logistic regression demonstrated that all nine markers (BamHI‐W, EBNA‐1, hsa‐miR‐21, hsa‐miR‐26a, hsa‐miR‐29c, hsa‐miR‐93, hsa‐miR‐205,

hsa‐miR‐375 and hsa‐miR‐421) were able to predict NPC with p < 0.05 (Supplementary Table S4). In multiple logistic regression analyses using forward and backward methods to evaluate all markers shortlisted from simple logistic regression analyses, only EBNA‐1 and

hsa‐miR‐21 remained as the significant variables in the model. Multicollinearity was detected and moderate correlation was observed between BamHI‐W and EBNA‐1, as well

as among few miRNAs, namely hsa‐miR‐21, hsa‐miR‐26a, hsa‐miR‐29c, hsa‐miR‐93 and hsa‐miR‐205. This could have led to the exclusion of these markers in the model for the prediction of NPC. Multiple logistic regression model with EBNA‐1 and hsa‐miR‐21 showed

the best AUC (0.860) compared to any marker alone as a prediction model (Supplementary Table S3). The utility of this model needs to be evaluated further by performing validation in an independent cohort in the future which should also include samples from non‐NPC patients with other EBV related diseases and EBV negative NPC patients.

3.5. Comparison of NW test to other less/minimally invasive test

Besides NW samples, EBV DNA test can be carried out using blood and other less/minimally invasive sample types, including urine and nasopharyngeal swab/brushings (Supplementary Table S5). Among these sample types, otolaryngologist is required to collect nasopharyngeal swab/brushings samples, medical support staff would be needed

6

individual with guidance from the medical support personnel. The cost for NW sampling is lower compared to blood and nasopharyngeal swab/brushings samples that require additional laboratory resources like centrifuge, preservation buffer and/or storage in ultra‐low temperature (−80 °C). In terms of test performance as evaluated by sensitivity, specificity, positive predictive value and negative predictive value, NW EBV DNA test (EBNA‐1) is slightly inferior to nasopharyngeal swab/brushings EBV DNA test but

outperformed the urine EBV DNA test7_{(Supplementary Table S5), probably due to the} proximity of sampling at the nasopharyngeal area.

4. Conclusion

In summary, the performance of NW EBV DNA test for the detection of NPC is superior to urine EBV DNA test but inferior to EBV DNA test from nasopharyngeal swab/brushings and blood. In remote areas of LMICs with high prevalence of NPC, access to healthcare facilities and routine monitoring by otolaryngologists are limited. The advantage of NW EBV DNA test compared to nasopharyngeal swab/brushings is that sampling can be easily achieved without the presence of otolaryngologist. In addition, high risks groups and post‐treatment NPC patients may feel more inclined to be tested frequently as compared to blood test because sampling of NW is non‐invasive. In fact, nasal washing is a procedure routinely taught by the otolaryngologists to the post‐treatment NPC patients for maintenance of nasopharynx. NW test may have potential as a post‐treatment surveillance system where patients with positive NW results can be closely monitored for any sign of recurrence. Lastly, our preliminary findings suggest that NW EBV DNA, hsa‐miR‐21, hsa‐miR‐26a, hsa‐miR‐29c, hsa‐miR‐93, hsa‐miR‐205, hsa‐miR‐375 and hsa‐miR‐421 are potential markers for NPC detection. External validation is required to confirm their applicability as detection tool for NPC.

Acknowledgements

We thank the Director General of Health Malaysia for his approval of the publication of this manuscript. We also thank the Director of Institute for Medical Research Malaysia for her support of this study. We are grateful to all staff from the Department of Otorhinolaryngology in Selayang Hospital, Department of Oncology and Radiotherapy in Kuala Lumpur Hospital, Molecular Pathology unit and Biospecimen Bank at the Institute for Medical Research for their assistance in sample and data collection. This study was funded by Ministry of Health Malaysia (NMRR-11-597-9667).

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Supplementary Methods

Quantification of EBV DNA

TaqMan Fast Advanced Master mix were used (Applied Biosystems, USA). In each well, 5 µl of DNA was used in a total reaction volume of 20 µl. qPCR was performed with the following conditions: 50 °C for 2 min, 95 °C for 20 s, and 40 cycle of 95 °C for 3 s and 56 °C for 30 s.

Evaluation of miRNA expression

MiRNA expression profiling data were obtained from National Center for Biotechnology

Information (NCBI) Gene Expression Omnibus (GEO) DataSets

(http://www.ncbi.nlm.nih.gov/gds) by using the search terms “(microRNA) AND Nasopharyngeal Carcinoma) AND RNA[Sample Type]”. Only datasets which studied tissue samples with a sample size of at least 20 and published prior to August 2015 were considered. Five GEO datasets (GSE70970, GSE43039, GSE32960, GSE36682 and GSE32906) which fulfilled these criteria were analyzed using the web tool GEO2R at the NCBI website (http://www.ncbi.nlm.nih.gov/geo/geo2r/). Differentially expressed miRNAs with significance (adjusted p value with false discovery rate correction, p < 0.05) were obtained by using limma R package as the default analysis. A total of 27 miRNAs were shortlisted based on this analysis for further validation in RT-qPCR (Supplementary Table 1). RNA samples of NW were subjected to reverse transcription (RT) using MicroRNA Reverse Transcription Kit (Applied Biosystems, USA) according to previous study1_{. Briefly, RT} primer pool was prepared by mixing equal volume of 32 stem-loop specific 5X RT primers. Primer pool consists of 27 miRNAs of interest, three small nucleolar RNAs (U6, U44 and U48) which are potential reference miRNAs and two C. elegans miRNA (cel-miR-39 and cel-miR-54) which are spike in controls for data normalization. Each RT reaction consists of 4.65 µl of RNA sample, 0.2 µl 100 mM dNTPs, 0.15 µl RNase inhibitor (20 U/µl), 1 µl 10X Reverse Transcription Buffer, 1µl MultiScribe Reverse Transcriptase (50 U/µl) and 3 µl of RT primers pool. RT was performed with thermal condition as follows: 16 °C for 30 min, 42 °C for 30 min, 85 °C for 5 min and 4 °C until the reaction is removed from incubation. Preamplification primer pool was prepared by mixing 32 TaqMan primers to a final concentration of 0.02X each. Preamplification reaction consisted of 2.5 µl diluted RT products (1:4 dilution), 5 µl TaqMan PreAmp Master Mix (2X) and 2.5 µl TaqMan preamplification primer pool. Preamplification was carried out with the following conditions: denaturation at 95 °C for 10 min, followed by 16 cycles of preamplification at 95 °C for 15 s and 60 °C for 4 min. Preamplified product was further diluted 1:5 before qPCR was carried out using a 96.96 dynamic array in BioMark (Fluidigm, USA). No-template-control and a series of standard points from pooled RNA of human cell/xenograft were run in the same dynamic array as control samples. qPCR for all

samples were carried out in triplicate wells and average Cqwere obtained from at least duplicate wells.

Pre-analysis quality control (QC) was performed to exclude any miRNA assays that do not exhibit linear amplification. Average Cq for NW were normalized according to normalization factor calculated from the Cq of spiked-in synthetic oligonucleotides to remove technical bias2,3_.

References

1. Heegaard NHH, Schetter AJ, Welsh JA, Yoneda M, Bowman ED, Harris CC. Circulating micro-RNA expression profiles in early stage nonsmall cell lung cancer. Int J Cancer 2012;130:1378–86.

2. Tan GW, Khoo ASB, Tan LP. Evaluation of extraction kits and RT-qPCR systems adapted to high-throughput platform for circulating miRNAs. Sci Rep 2015;5:9430.

3. Kroh EM, Parkin RK, Mitchell PS, Tewari M. Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR). Methods 2010;50:298–301.

10-2 ₁₀-1 ₁₀0 ₁₀1 ₁₀2 ₁₀3 ₁₀4 10-2 10-1 100 101 102 103

EBV DNA load

Time point #1 Ti m e po in t# 2 1c 1L 1R 2c 2L 2R 3c 3L 3R 4c 4L 4R 5c 5L 5R 6c 6L 6R r = 0.9916 10-2 ₁₀-1 ₁₀0 ₁₀1 ₁₀2 ₁₀3 ₁₀4 10-2 10-1 100 101 102 103 104

EBV DNA load

Left to right R ig ht to le ft 1 2 3 4 5 6 7 8 9 10 11 r = 0.7655 A B

Supplementary Figure S1. Comparison of EBV DNA load in nasal washings collected differently. (A) NW collected from the right nostril by introducing saline into the left nostril and vice versa. Patients with EBV DNA showed high EBV DNA load regardless of the side of NW samples being collected while patients that were negative for EBV DNA consistently had no EBV DNA on both sides. Each number indicates one patient with some patients having two samples collected at different time points. (B) NW collected from patients at two different time points during the course of treatment. All data points that were negative were given arbitrary values of 0.07 to 0.13 EBV DNA copy while samples with low EBV DNA load were given arbitrary values of 0.7 to 1.3. c, combined lysate of left

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Supplementary Figure S2. EBV DNA load and miRNA expression level in nasal washings of NPC patients with different T stages in comparison to non-NPC patients. Patients with T3 and T4 tumours had higher median EBV DNA loads compared to T1 and T2 tumours, as measured by (A) BamHI-W and (B) EBNA-1 assay. NPC cases with higher T stages showed higher expression of (C) hsa-miR-21, (D) hsa-miR-26b, (E) hsa-miR-29c, and (F) hsa-miR-93, while no obvious trend is observed for (G) hsa-miR-205, (H) hsa-miR-375 and (I) hsa-miR-421.

BamHI-W EB V D N A lo ad Complete remission Residual 10-2 1010-1 0 101 102 103 104 105 EBNA-1 Complete remission Residual 10-2 1010-1 0 101 102 103 104 105 EB V D N A lo ad A B

Supplementary Figure S3. EBV DNA load in nasal washings. Higher median NW EBV DNA load is seen in residual samples compared to remission samples as measured by (A) BamHI-W assay and (B)

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miRNA GSE70970 GSE43039 GSE32960 GSE36682 GSE32906 this study

ebv-miR-BART4 UP* UP UP* UP* NT NE

ebv-miR-BART6-3p UP* UP UP* UP* NT NE

ebv-miR-BART6-5p UP* UP UP* UP* NT NE

ebv-miR-BART7 UP* UP* UP* UP* NT NA

ebv-miR-BART8 UP* UP* ND UP* NT NE

ebv-miR-BART9 UP* UP* UP* UP* NT ND

ebv-miR-BART10 UP* UP* UP* UP* NT NE

ebv-miR-BART17-5p UP* UP ND UP* NT NE

ebv-miR-BART19-3p UP* ND UP* UP* NT NE

hsa-miR-142-3p UP ND DOWN* ND ND UP

hsa-miR-143 ND DOWN DOWN* DOWN* ND ND

hsa-miR-145 DOWN* DOWN DOWN* DOWN* ND UP

hsa-miR-155 UP* ND ND ND ND UP

hsa-miR-196b UP* ND ND ND ND NE

hsa-miR-205 UP UP* UP* UP* ND UP*

hsa-miR-21 UP* ND DOWN* UP* ND UP*

hsa-miR-26a ND ND DOWN* DOWN* ND UP*

hsa-miR-26b ND DOWN* DOWN* DOWN* ND UP

hsa-miR-29b UP* DOWN* DOWN* DOWN ND ND

hsa-miR-29c ND DOWN* DOWN* DOWN* ND UP*

hsa-miR-34c-5p DOWN* DOWN* DOWN* DOWN* DOWN ND

hsa-miR-375 DOWN* ND ND DOWN* ND UP*

hsa-miR-421 UP* ND DOWN* DOWN* ND UP*

hsa-miR-451 ND ND DOWN* DOWN* ND ND

hsa-mir-9 UP ND ND ND UP ND

hsa-miR-93 UP* ND UP* ND ND UP*

hsa-miR-99b DOWN ND ND DOWN* UP UP

*statistically significant

Abbreviations: UP, >2-fold upregulation; DOWN, >2-fold downregulation; NT, not tested; NE, no expression in >80% of samples; NA, not analysed due to assay failing pre-analysis quality control; ND, no difference in expression between NPC and control.

Supplementary Table S2. Clinical and demographics features of study subjects. All NPCa _non-NPC p value n = 119 n = 46 n = 73 Sex Male 88 (73.9%) 37 (80.4%) 51 (69.9%) > 0.05b Female 31 (26.1%) 9 (19.6%) 22 (30.1%) Age

mean years (range) 48.9 (15 - 85) 51.5 (15 - 85) 44.8 (19 - 78) > 0.05c

Ethnicity Chinese 68 (57.1%) 30 (65.2%) 38 (52.1%) > 0.05b Malay 44 (37.0%) 15 (32.6%) 29 (39.7%) Others 7 (5.9%) 1 (2.2%) 6 (8.2%) AJCC Staging I 1 (2.2%) II 2 (4.3%) III 10 (21.7%) IVA 7 (15.2%) IVB 7 (15.2%) IVC 6 (13%) Incomplete staging 12 (26.1%) Unknown 1 (2.2%) Nasopharynx (T) T1 10 (21.7%) T2 11 (23.9%) T3 8 (17.4%) T4 16 (34.8%) Unknown 1 (2.2%) Regional node (N) N0 6 (13.0%) N1 5 (10.9%) N2 20 (43.5%) N3 4 (8.7%) N3a 4 (8.7%) N3b 5 (10.9%) Unknown 2 (4.3%) Metastasis (M) M0 27 (58.7%) M1 6 (13.0%) Mx 12 (26.1%) Unknown 1 (2.2%)

a_{Only NPC patients that contributed to pre-treatment samples (n = 46) are included here for statistical analyses}

of differences in sex, age and ethnicity.

b_{Statistical significance as determined by Chi-square test.} c_{Statistical significance as determined by Mann-Whitney U test}

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Area under ROC curve

Sensitivity Specificity Positive predictive value Negative predictive value

Area 95% C.I. p value

Lower Upper BamHI-Wa _{0.774 0.684 0.864 <0.001 54.3% 90.4% 78.1% 75.9%} BamHI-Wb _{0.786 0.689 0.883 <0.001 48.6% 95.3% 85.0% 77.2%} EBNA-1a _{0.805 0.718 0.893 <0.001 71.7% 83.6% 73.3% 82.4%} EBNA-1b _{0.810 0.712 0.908 <0.001 74.3% 81.3% 68.4% 85.2%} hsa-miR-21b _{0.736 0.633 0.839 <0.001 77.1% 62.5% 52.9% 83.3%} hsa-miR-26ab _{0.708 0.600 0.817 0.001 74.3% 60.9% 51.0% 81.3%} hsa-miR-29cb _{0.762 0.661 0.862 <0.001 80.0% 70.3% 59.6% 86.5%} hsa-miR-93b _{0.716 0.609 0.823 <0.001 71.4% 70.3% 56.8% 81.8%} hsa-miR-205b _{0.736 0.630 0.842 <0.001 65.7% 78.1% 62.2% 80.6%} hsa-miR-375b _{0.733 0.630 0.835 <0.001 82.9% 57.8% 51.8% 86.0%} hsa-miR-421b _{0.705 0.592 0.819 0.001 60.0% 84.4% 67.7% 79.4%} Regression modelb,c _{0.860 0.783 0.936 <0.001 80.0% 78.1% 66.7% 87.7%}

a_{Calculation was done for all samples evaluated (n = 119).}

b_{Calculation was done for a subset of samples (n = 99) that were available for miRNA analyses.} c_{This model includes EBV DNA measured by the EBNA-1 assay and hsa-miR-21.}

Abbreviations: C.I., confidence interval.

Supplementary Table S4. Markers in NPC analyzed by simple and multiple logistic regression. Simple logistic regression Multiple logistic regresionb Ba _{p value} Crude odd ratio 95% C.I. Ba _{p value} Adjusted odd ratio 95% C.I.

Lower Upper Lower Upper

BamHI-Wc _{0.287 <0.001 1.333 1.170 1.518} EBNA-1c _{0.363 <0.001 1.438 1.205 1.716 0.370 0.000 1.447 1.192 1.757} hsa-miR-21 0.262 <0.001 1.300 1.124 1.504 0.220 0.009 1.246 1.056 1.471 hsa-miR-26a 0.236 0.001 1.266 1.096 1.463 hsa-miR-29c 0.345 <0.001 1.412 1.182 1.686 hsa-miR-93 0.208 0.001 1.231 1.085 1.397 hsa-miR-205 0.197 <0.001 1.218 1.098 1.350 hsa-miR-375 0.262 <0.001 1.300 1.123 1.503 has-miR-421 0.406 <0.001 1.500 1.201 1.874 a_{Regression coefficient}

b_{Multiple logistic regression with forward and backward methods. All methods yielded the same results.} c_{Calculation for EBV DNA was done based on subset (n = 99) for comparison with miRNA.}

Su p p le me n tar y Tab le S 5. C o mp a ri so n o f E BV DN A te sts usi n g d if fe re n t mi n imal ly /n o n -i n vasi ve sa mp le ty p e s. N e gati ve p re d ic ti ve val u e 96.2% 91.0% 80.0% 99.7% 99.9% 96.0% 67.7% 82.4% 75.9% NM N PB , n as o p h ar yn gea l b ru sh in gs ; T O B , t ra n s-o ra l b ru sh in gs ; N PS , n as o p h ar yn gea l s w ab ; N W , n as al w as h in gs ; N A , n o t ap p lic ab le ( sa m p le t es ted d ir ec tl y af te r s am p lin g) ; N M , n o t m en ti o n ed . Po si ti ve p re d ic ti ve val u e 96.4% 97.0% 84.4% 96.9% 41.2% 97.0% 93.3% 73.3% 78.1% NM Sp e ci fi ci ty 96.2% 98.0% 90.0% 99.3% 98.9% 97.0% 95.7% 83.6% 90.4% 87 -100% Se n si ti vi ty 96.4% 91.0% 94.3% 98.9% 87.5% 96.0% 56.8% 71.7% 54.3% ₆₉-99% Q u an ti fi e d re gi o n / ge n e Ba mH I-W EBN A -1 EBN A -1 EBN A -1 Ba mH I-W Ba mH I-W Ba mH I-W EBN A -1 Ba mH I-W vari o u s Sto rag e c o n d it io n s Temper atu re NA -80 ° C -80 ° C R o o m te mp erat u re -80 ° C -80 ° C NA -20 ° C -80 ° C Bu ff e r NA N u cl iS en s L ys is Buffe r N u cl iS en s L ys is Buffe r Pro p ri etar y p re se rvati o n ag en t Sali n e R N A late r NA Sali n e p las ma p ro ce ss e d fro m EDT A b lo o d tu b e R e q u ir e me n t o f o to lar yn go lo gi st fo r sam p lin g Ye s Ye s Ye s Ye s Ye s Ye s No No No Samp le ty p e N PB N PB N PB TO B N PS N PB u ri n e NW _bloo d Po p u lat io n H o n g Ko n g In d o n es ia In d o n es ia H o n g Ko n g an d Can ad a Ch in a Ch in a H o n g Ko n g Mal ays ia vari o u s Stu d y To n g et a l, 2002 Ste ve n s et a l, 2006 A d h am et a l, 2013 N g et a l, 2014 Ch en et a l, 2015 Zh en g et a l, 2015 Ch an et a l, 2008 a Tan et a l. (th is stu d y) Yi p et a l. 2018 NP B , n aso p h ar yn gea l b ru sh in gs ; T O B , tra n s-o ral b ru sh in gs; NP S, n aso p h ar yn gea l sw ab ; NW , n asal w as h in gs ; NA , n o t ap p lica b le ( samp le t e st ed d ire ctl y af ter sam p lin g) ; NM, n o t me n ti o n ed . aSen si ti vi ty , sp ec if ici ty , p o si ti ve p re d icti ve v al u e an d n eg at iv e p re d icti ve v al u e w er e ca lc u late d b ase d o n re p o rte d re su lts f ro m th e st u d ies. To n g JH M , T sa n g R KY , L o KW, Wo o J KS , Kw o n g J, C h an M WY , C h an g A R , V an H assel t C A , H u an g D P , T o KF. Q u an ti tati ve Ep st ei n -B ar r vi ru s D NA an al ys is an d d etec ti o n o f gen e p ro m o ter h yp er meth yl at io n in n aso p h ar yn gea l ( NP ) b ru sh in g sa mp les fr o m p at ien ts w ith NP ca rc in o ma. C lin C an ce r R e s 2 0 0 2 ;8 :2 6 1 2 –9 . Stev en s SJ C , V er ku ijl en S A WM , H ar iw iy an to B , H ar ija d i, Pa ra mi ta D K , Fac h iro h J , A d h a m M , Ta n I B , H ar ya n a SM , M id d el d o rp J M . No n in vasi ve d iag n o si s o f n aso p h ar yn gea l ca rc in o m a: Na so p h ar yn gea l b ru sh in gs re vea l h ig h E p stei n -B ar r vi ru s D N A lo ad a n d ca rc in o ma -sp ec if ic vi ra l B A R F1 mR N A . I n t J C an ce r 2 0 0 6 ;1 1 9 :6 0 8 – 1 4 . A d h am M , Gre ije r A E, V er ku ijl e n S A WM , Ju w an a H , Fl ei g S, R ac h mad i L, M al ik O , K u rn iaw an A N, R o ez in A , G o n d h o w iar d jo S , A tm ak u su mah D , Ste ven s SJ C , et al . Ep st e in -b ar r vi ru s D NA lo ad i n n aso p h ar yn gea l b ru sh in gs an d w h o le b lo o d in n aso p h ar yn gea l ca rc in o ma p at ien ts b ef o re a n d af ter tre a tm en t. C lin C an ce r R e s 2 0 1 3 ;1 9 :2 1 7 5 – 8 6 . Ng R H W, Ng an R , Wei WI , G u lla n e PJ , Ph ill ip s J. T ra n s-o ra l b ru sh b io p si e s an d q u an ti tat iv e PC R f o r EB V D NA d etec ti o n a n d scr ee n in g o f n aso p h ar yn gea l ca rc in o ma. O to lar yn go l H ea d Ne ck S u rg 2 0 1 4 ;1 5 0 :6 0 2 –9 . C h en Y , Zh a o W, L in L , Xi ao X, Z h o u X, M in g H , H u an g T, L iao J , Li Y , Zen g X, H u an g G , Ye W, et al . Na so p h ar yn gea l Ep stei n -B ar r V ir u s Lo ad : A n E ff ici e n t Su p p leme n tar y M eth o d f o r Po p u lati o n -B ased Na so p h ar yn gea l C ar ci n o ma Scr ee n in g. PL o S O n e 2 0 1 5 ;1 0 :e 0 1 3 2 6 6 9 . Zh en g X -H , Lu L -X, L i X -Z , Ji a W -H . Q u an ti fi cati o n o f Ep st e in -B ar r vi ru s D NA l o ad i n n aso p h ar yn gea l b ru sh in g sam p les i n th e d iag n o si s o f n as o p h ar yn gea l ca rc in o ma in s o u th er n C h in a. C an ce r Sc i 2 0 1 5 ;1 0 6 :1 1 9 6 – 2 01 . C h an KCA , L eu n g SF , Y e u n g SW , C h an A TC , L o Y M D . Q u an ti tat iv e a n al ysi s o f th e t ra n sre n al e xcr eti o n o f ci rc u la ti n g EB V D N A in n aso p h ar yn gea l ca rc in o ma p at ien ts . C lin C an ce r R e s 2 0 0 8 ;1 4 :4 8 0 9 – 13. Yi p T TC , Ng an R KC, F o n g A H W , L aw S C K. A p p lica ti o n o f ci rc u lat in g p lasma/ seru m EB V D N A in th e cl in ica l man ag e men t o f n aso p h ar yn gea l ca rc in o ma. O ra l O n co l 2 0 1 4 ;5 0 :5 2 7 – 38.