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. 2020 May 6;15:45. doi: 10.1186/s13000-020-00964-6

An economical Nanopore sequencing assay for human papillomavirus (HPV) genotyping

Wai Sing Chan 1, Tsun Leung Chan 1, Chun Hang Au 1, Chin Pang Leung 1, Man Yan To 1, Man Kin Ng 1, Sau Man Leung 1, May Kwok Mei Chan 1, Edmond Shiu Kwan Ma 1, Bone Siu Fai Tang 1,✉
PMCID: PMC7203875  PMID: 32375813

Abstract

Background

Human papillomavirus (HPV) testing has been employed by several European countries to augment cytology-based cervical screening programs. A number of research groups have demonstrated potential utility of next-generation sequencing (NGS) for HPV genotyping, with comparable performance and broader detection spectrum than current gold standards. Nevertheless, most of these NGS platforms may not be the best choice for medium sample throughput and laboratories with less resources and space. In light of this, we developed a Nanopore sequencing assay for HPV genotyping and compared its performance with cobas HPV Test and Roche Linear Array HPV Genotyping Test (LA).

Methods

Two hundred and one cervicovaginal swabs were routinely tested for Papanicolaou smear, cobas HPV Test and LA. Residual DNA was used for Nanopore protocol after routine testing. Briefly, HPV L1 region was amplified using PGMY and MGP primers, and PCR-positive specimens were sequenced on MinION flow cells (R9.4.1). Data generated in first 2 h were aligned with reference sequences from Papillomavirus Episteme database for genotyping.

Results

Nanopore detected 96 HPV-positive (47.76%) and 95 HPV-negative (47.26%) specimens, with 10 lacking β-globin band and not further analyzed (4.98%). Substantial agreement was achieved with cobas HPV Test and LA (κ: 0.83–0.93). In particular, Nanopore appeared to be more sensitive than cobas HPV Test for HPV 52 (n = 7). For LA, Nanopore revealed higher concordance for high-risk (κ: 0.93) than non-high risk types (κ: 0.83), and with similar high-risk positivity in each cytology grading. Nanopore also provided better resolution for HPV 52 in 3 specimens co-infected with HPV 33 or 58, and for HPV 87 which was identified as HPV 84 by LA. Interestingly, Nanopore identified 5 additional HPV types, with an unexpected high incidence of HPV 90 (n = 12) which was reported in North America and Belgium but not in Hong Kong.

Conclusions

We developed a Nanopore workflow for HPV genotyping which was economical (about USD 50.77 per patient specimen for 24-plex runs), and with comparable or better performance than 2 reference methods in the market. Future prospective study with larger sample size is warranted to further evaluate test performance and streamline the protocol.

Keywords: Cervical cancer, HPV, Nanopore, NGS

Introduction

Human papillomavirus (HPV) is generally accepted as the causative agent of cervical cancer (CC) [1], which was first unmasked by the landmark studies of Meisels and Fortin [2] and Purola and Savia [3]. Currently, there are 198 reference HPV types listed on Papillomavirus Episteme (PaVE) database, and at least 12 were classified as high-risk by World Health Organization (WHO) International Agency for Research on Cancer (IARC) Monographs Working Group [4–6]. HPV testing has been adopted by several European countries for primary CC screening, to augment cytology-based screening programs [7, 8]. A number of HPV assays are available commercially, which are mainly based on direct HPV genome detection, HPV DNA amplification and E6/ E7 mRNA detection [9]. Recent advent of next-generation sequencing (NGS) technologies has facilitated high throughput tools for infectious disease diagnostics and epidemiological research. Several research groups have explored utility of Illumina MiSeq and Ion Torrent platforms for HPV genotyping, with comparable sensitivity to well-established line blot assays and broader detection spectrum [10–12]. While the reagent cost is comparable to existing commercial assays for large sample batches, these NGS platforms may not be the best choice for medium sample throughput and laboratories with less resources and space. In this regard, portable Nanopore sequencers may allow more flexibility with shorter sequencing time and lower reagent cost. In light of this, we developed a Nanopore HPV genotyping protocol using 2 published primer sets, and compared its performance with 2 commercial HPV assays: cobas HPV Test and Roche Linear Array HPV Genotyping Test (LA).

Methods

Specimens

Two hundred and one cervicovaginal swabs were collected from March to July, 2019 in Hong Kong Sanatorium & Hospital. The swabs were preserved in SurePath preservative fluid (Becton, Dickson and Company, Sparks, MD, USA) and routinely tested for Papanicolaou smear (Pap smear, following The Bethesda System for reporting), cobas HPV Test and LA (Roche Diagnostics, Mannheim, Germany). Routine test results are shown in Table 1.

Table 1.

Results of Pap smear, cobas HPV Test, Roche Linear Array HPV Genotyping Test, and Nanopore sequencing

Patient Pap smear Roche Linear Array Cobas HPV Nanopore (PGMY) Nanopore (MGP) Total HPV reads
HR Non-HR HR Non-HR HR Non-HR
1 AGUS Neg Neg Neg Neg Neg Neg Neg ND
2 ASCH 52, 59 62 Other HR 59 Neg 59 90 4956
3 ASCUS 52 55 Neg 52 55 Neg Neg 4262
4 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
5 ASCUS 31, 33 54 Other HR 31, 33, 52 Neg Neg 90 8973
6 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
7 ASCUS 31 Neg Other HR Neg Neg 31 Neg 1430
8 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
9 ASCUS Neg 81 Neg Neg 81 Neg 81 48,477
10 ASCUS 18 Neg 18 18 Neg 18 Neg 16,206
11 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
12 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
13 ASCUS 52 53, 54 Other HR 52 44, 53, 74 52 74, 90 15,419
14 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
15 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
16 ASCUS 52 81 Neg 52 81 Neg 81 8873
17 ASCUS 52 54 Other HR 52 54 52 54 36,258
18 ASCUS 52, 59 11 Other HR 52, 59 11 52, 59 11 44,702
19 ASCUS Neg Neg Neg PCR inhibition
20 ASCUS Neg Neg Neg Neg Neg Neg Neg 7
21 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
22 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
23 ASCUS 39 61, 72 Other HR 39 61, 72 39 87 1624
24 ASCUS 66 Neg Other HR 66 Neg 66 Neg 10,383
25 ASCUS 68 61 Other HR Neg 61 Neg 61 10,644
26 ASCUS Neg Neg Neg Neg Neg Neg 90 541
27 ASCUS 52 Neg Neg 52 Neg Neg 87 3614
28 ASCUS Neg 62 Neg Neg 62 Neg 62 45
29 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
30 ASCUS 35 Neg Other HR 35 Neg 35 Neg 1641
31 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
32 ASCUS 52 Neg Other HR 52 Neg 52 Neg 399
33 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
34 ASCUS 51 84 Other HR 51 Neg Neg Neg 1853
35 ASCUS Neg Neg Neg Neg 74 Neg 74 11,499
36 ASCUS Neg Neg Neg Neg Neg Neg Neg 93
37 ASCUS 51 Neg Other HR 51 Neg 51 Neg 2897
38 ASCUS Neg 40, 55, 83 Neg Neg 40, 55, 83 Neg 40, 55, 83 47,736
39 ASCUS Neg Neg Neg Neg Neg Neg Neg ND
40 ASCUS 58 53, 55, 62 Other HR 52, 58 53, 55, 62, 74 52 53, 62, 74 42,106
41 ASCUS 52 42, 73 Other HR 52 42, 73 52 42, 73 15,778
42 ASCUS Neg Neg Neg Neg Neg Neg Neg 116
43 HSIL 16 Neg 16 16 Neg 16 Neg 15,918
44 HSIL 16 Neg 16 16 Neg 16 Neg 34,654
45 HSIL 59 Neg Other HR 59 Neg 59 Neg 15,381
46 HSIL 31, 58 Neg Other HR 31, 58 Neg 31, 58 Neg 3367
47 LSIL 52, 68 84 Other HR 52, 68 84 52, 68 84, 90 24,366
48 LSIL 66 84 Other HR 66 44, 84 66 44 57,206
49 LSIL 52 Neg Neg 52 Neg 52 Neg 14,516
50 LSIL Neg 40, 53 Neg Neg 40, 53 Neg 40, 53 9265
51 LSIL 52 11, 81 Other HR 52 11, 81 52 11, 43, 81 29,748
52 LSIL 66 Neg Other HR 66 Neg 66 Neg 40,328
53 LSIL 51 Neg Other HR 51 Neg 51 43, 90 4454
54 LSIL 16, 51, 56 54, 62, 81 16, other HR 16, 51, 56 54, 62, 81 16, 51 40, 62, 81 20,455
55 LSIL 56 53 Other HR 56 53 56 53 28,377
56 LSIL Neg Neg Neg Neg Neg Neg Neg ND
57 LSIL 66 54, 55, 81 Other HR 66 54, 55, 81 66 55, 81, 90 25,606
58 LSIL 52 Neg Neg 52 42 52 90 15,103
59 LSIL 59 Neg Other HR 59 Neg Neg Neg 11,235
60 LSIL 59 89 Neg 59 89 Neg 89 67,220
61 LSIL 56 82 Other HR 56 82 56 43, 82 42,160
62 LSIL 52 Neg Other HR 52 Neg 52 Neg 39,323
63 LSIL 33, 51 Neg Other HR 33, 51 44 51 44 19,704
64 LSIL+ ASCH 51 Neg Other HR 51 Neg 51 Neg 4621
65 NIL 16 Neg 16 16 Neg 16 Neg 1958
66 NIL Neg Neg Neg Neg Neg Neg Neg ND
67 NIL Neg Neg Neg Neg Neg Neg Neg ND
68 NIL Neg Neg Neg 59 Neg 59 Neg 2455
69 NIL Neg Neg Neg Neg 87 Neg 87 8775
70 NIL Neg Neg Neg Neg Neg Neg Neg ND
71 NIL Neg Neg Neg Neg Neg Neg Neg ND
72 NIL Neg Neg Neg Neg Neg Neg Neg ND
73 NIL Neg Neg Neg Neg Neg Neg Neg ND
74 NIL 58 Neg Other HR 58 Neg 52, 58 62 8619
75 NIL 58 Neg Other HR 58 Neg 58 Neg 13,149
76 NIL Neg Neg Neg Neg Neg Neg Neg ND
77 NIL Neg Neg Neg Neg Neg Neg Neg ND
78 NIL Neg Neg Neg Neg Neg Neg 90 2289
79 NIL 56 70 Other HR Neg 44, 70 56 44, 70 7855
80 NIL Neg Neg Neg PCR inhibition
81 NIL Neg Neg Neg Neg Neg Neg Neg 74
82 NIL Neg 42 Neg Neg Neg Neg 42 1406
83 NIL Neg Neg Neg Neg 74 Neg 74 7441
84 NIL Neg Neg Neg Neg Neg Neg Neg ND
85 NIL Neg 82 Neg Neg 82 Neg 82 1162
86 NIL Neg 62 Neg Neg 62 Neg 62 65,368
87 NIL Neg Neg Neg Neg Neg Neg Neg ND
88 NIL Neg Neg Neg Neg Neg Neg Neg ND
89 NIL Neg Neg Neg Neg Neg Neg Neg ND
90 NIL Neg Neg Neg Neg Neg Neg Neg 142
91 NIL 39, 52 Neg Other HR 52 Neg 52 90 15,703
92 NIL 68 Neg Other HR 68 42 68 Neg 19,777
93 NIL Neg Neg Neg Neg Neg Neg Neg ND
94 NIL Neg Neg Neg Neg Neg Neg Neg ND
95 NIL Neg Neg Neg Neg Neg Neg Neg ND
96 NIL 52 Neg Neg 52 Neg 52 Neg 5242
97 NIL Neg Neg Neg Neg Neg Neg Neg ND
98 NIL Neg Neg Neg Neg Neg Neg Neg ND
99 NIL Neg Neg Neg Neg Neg Neg Neg 41
100 NIL 52 Neg Other HR 52 Neg 52 Neg 24,478
101 NIL Neg 61 Neg PCR inhibition
102 NIL Neg Neg Neg Neg Neg Neg Neg 72
103 NIL 39 Neg Neg Neg Neg Neg Neg ND
104 NIL Neg 62, 84 Neg Neg 62 Neg 62 3589
105 NIL Neg 71 Neg Neg Neg Neg Neg ND
106 NIL Neg Neg Neg Neg Neg Neg Neg ND
107 NIL 52 62 Other HR 52 44, 53, 62 52 44 18,086
108 NIL Neg Neg Neg Neg Neg Neg Neg ND
109 NIL Neg Neg Neg Neg Neg Neg Neg ND
110 NIL Neg Neg Neg Neg Neg Neg Neg ND
111 NIL Neg 84 Neg Neg Neg Neg Neg ND
112 NIL 16, 52 Neg 16 16, 52 Neg 16 Neg 72,357
113 NIL Neg Neg Neg Neg Neg Neg Neg ND
114 NIL Neg 55, 89 Neg Neg 26, 55, 89 59 26, 55, 62, 89 8926
115 NIL Neg Neg Neg Neg Neg Neg 74 1586
116 NIL Neg 81 Neg Neg Neg Neg Neg ND
117 NIL Neg Neg Neg Neg Neg Neg Neg ND
118 NIL Neg 6, 62 Neg Neg 6, 62 Neg 6, 62 9414
119 NIL Neg Neg Neg Neg Neg Neg Neg ND
120 NIL Neg 54 Neg Neg Neg Neg Neg ND
121 NIL Neg Neg Neg PCR inhibition
122 NIL Neg Neg Neg Neg Neg Neg Neg 8
123 NIL 68 Neg Other HR Neg Neg Neg Neg ND
124 NIL Neg 81 Neg Neg 81 Neg 81 8735
125 NIL Neg 84 Neg Neg Neg Neg 87 1025
126 NIL Neg Neg Neg Neg Neg Neg 90 1719
127 NIL Neg Neg Neg Neg Neg Neg Neg ND
128 NIL Neg Neg Neg Neg Neg Neg Neg ND
129 NIL Neg Neg Neg Neg Neg Neg Neg 10
130 NIL Neg Neg Neg Neg Neg Neg Neg ND
131 NIL Neg 84 Neg Neg Neg Neg Neg ND
132 NIL Neg Neg Neg Neg Neg Neg Neg ND
133 NIL 59 62, 71 Other HR Neg Neg Neg Neg 30
134 NIL Neg Neg Neg Neg Neg Neg Neg ND
135 NIL Neg Neg Neg Neg Neg Neg Neg 522
136 NIL Neg Neg Neg Neg Neg Neg Neg ND
137 NIL 51 84 Other HR PCR inhibition
138 NIL 39 Neg Other HR 39 Neg 39 Neg 19,305
139 NIL Neg Neg Neg Neg Neg Neg Neg 195
140 NIL Neg Neg Neg Neg Neg Neg Neg ND
141 NIL Neg Neg Neg Neg Neg Neg Neg 23
142 NIL Neg Neg Neg Neg Neg Neg Neg ND
143 NIL Neg 42, 81 Neg Neg 40, 74, 81 Neg 40, 74, 81, 87 19,118
144 NIL Neg Neg Neg Neg Neg Neg Neg ND
145 NIL Neg Neg Neg Neg Neg Neg Neg ND
146 NIL Neg Neg Neg Neg Neg Neg Neg ND
147 NIL Neg Neg Neg Neg Neg Neg Neg 40
148 NIL 59 Neg Neg 59 Neg Neg Neg 12,681
149 NIL Neg Neg Neg Neg Neg Neg Neg 14
150 NIL Neg Neg Neg PCR inhibition
151 NIL Neg Neg Neg Neg Neg Neg Neg 79
152 NIL Neg 62 Neg Neg 62 Neg 62 14,353
153 NIL Neg Neg Neg Neg Neg Neg Neg ND
154 NIL Neg Neg Neg Neg Neg Neg Neg ND
155 NIL Neg Neg Neg Neg Neg Neg Neg ND
156 NIL 52 54 Neg 52 54 52 54 18,397
157 NIL 39, 52 53, 61 Other HR 39 53, 61 39 53, 61 20,332
158 NIL Neg Neg Neg Neg Neg Neg Neg ND
159 NIL Neg Neg Neg Neg Neg Neg Neg 60
160 NIL Neg Neg Neg PCR inhibition
161 NIL Neg 62 Neg Neg 62 Neg 62 13,545
162 NIL Neg Neg Neg Neg 74 Neg 74 4514
163 NIL Neg 62 Neg Neg 62 Neg 62 11,894
164 NIL Neg Neg Neg Neg Neg Neg Neg ND
165 NIL 59 Neg Neg PCR inhibition
166 NIL Neg Neg Neg Neg Neg Neg Neg ND
167 NIL 39 Neg Other HR 39 Neg 39 Neg 52,831
168 NIL Neg Neg Neg Neg Neg Neg Neg ND
169 NIL Neg Neg Neg Neg Neg Neg Neg ND
170 NIL 66 Neg Other HR 66 Neg 66 Neg 54,943
171 NIL Neg Neg Neg Neg Neg Neg Neg ND
172 NIL Neg Neg Neg Neg Neg Neg Neg ND
173 NIL Neg Neg Neg Neg Neg Neg Neg ND
174 NIL 66 Neg Other HR 66 Neg 66 Neg 57,791
175 NIL Neg 54 Neg Neg 54 Neg 54 23,583
176 NIL Neg Neg Neg PCR inhibition
177 NIL 16 62 16 Neg 53, 62 16 62 28,181
178 NIL Neg Neg Neg Neg Neg Neg Neg 206
179 NIL Neg Neg Neg Neg Neg Neg Neg ND
180 NIL Neg Neg Neg Neg Neg Neg Neg ND
181 NIL 51, 66 Neg Other HR 51, 66, 68 Neg 51, 66, 68 Neg 6952
182 NIL 16, 51, 58 61 Other HR 58 61 Neg 61 5737
183 NIL Neg Neg Neg Neg Neg Neg Neg ND
184 NIL 58 Neg Other HR 58 Neg 58 Neg 43,034
185 NIL 58 70, 89 Other HR 58 70, 89 58 89 33,842
186 ND Neg Neg Neg Neg Neg Neg Neg 414
187 ND Neg Neg Neg Neg Neg Neg Neg ND
188 ND 16 Neg 16 16 Neg 16 Neg 96,549
189 ND Neg Neg Neg Neg Neg Neg Neg ND
190 ND Neg Neg Neg Neg Neg Neg Neg ND
191 ND 56 Neg Other HR 56 Neg 56 Neg 18,782
192 ND 51 Neg Other HR 51 Neg 51 Neg 6020
193 ND Neg 62 Neg Neg 62 Neg 62 20,373
194 ND Neg Neg Neg Neg Neg Neg Neg ND
195 ND 52, 59 Neg Other HR 52, 59 Neg 59 Neg 11,926
196 ND 59 Neg Other HR 59 Neg 59 Neg 24,045
197 ND 52, 59 54, 70 Other HR 52, 59 70 52, 59 70, 90 46,523
198 ND 56, 66 53, 61, 84 Other HR 66 32, 53, 61, 84 56 32, 53, 61, 84 62,600
199 ND Neg 62 Neg Neg Neg Neg Neg ND
200 ND Neg 53, 54, 81, 83 Neg Neg 53, 54, 83 Neg 53, 81, 83 32,868
201 ND Neg Neg Neg PCR inhibition
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AGUS Atypical glandular cells of undetermined significance, ASCH Atypical squamous cells – cannot exclude HSIL, ASCUS Atypical squamous cells of undetermined significance, HR High-risk, HSIL High-grade squamous intraepithelial lesion, LSIL Low-grade squamous intraepithelial lesion, ND Pap smear/ MinION sequencing not done, Neg Negative, NIL normal cytology

DNA extraction

DNA extraction and cobas HPV Test were performed using cobas 4800 system (Roche Diagnostics, Rotkreuz, Switzerland). Briefly, 500 μL of cervicovaginal specimen was added to 500 μL of sample preparation buffer and heated at 120 °C for 20 min. The mixture was brought to ambient temperature for 10 min and processed on cobas × 480 using ‘high-risk HPV DNA PCR’ protocol. Real-time polymerase chain reaction (PCR) was performed on cobas z 480. Fifty microliter of DNA extract was used for LA according to manufacturer’s recommendations. Residual DNA was used for Nanopore protocol after routine testing.

HPV PCR

For each specimen, L1 region of HPV genome was amplified in 2 separate PCRs using PGMY and MGP primer sets [13, 14]. Primer sequences and cycling conditions are shown in Tables 2 and 3. Human β-globin gene was used as inhibition control and contamination was monitored by negative extraction control. Five microliter of each PCR amplicon was electrophoresized in 2% agarose gel (Invitrogen, Carlsbad, CA, USA) and analyzed. PCR-positive specimens were sequenced using Nanopore MinION.

Table 2.

Primer sequences

Primer 5′ to 3′ sequence References
PGMY PCR
 PGMY11-A GCA CAG GGA CAT AAC AAT GG [13]
 PGMY11-B GCG CAG GGC CAC AAT AAT GG
 PGMY11-C GCA CAG GGA CAT AAT AAT GG
 PGMY11-D GCC CAG GGC CAC AAC AAT GG
 PGMY11-E GCT CAG GGT TTA AAC AAT GG
 PGMY09-F CGT CCC AAA GGA AAC TGA TC
 PGMY09-G CGA CCT AAA GGA AAC TGA TC
 PGMY09-H CGT CCA AAA GGA AAC TGA TC
 PGMY09-I G CCA AGG GGA AAC TGA TC
 PGMY09-J CGT CCC AAA GGA TAC TGA TC
 PGMY09-K CGT CCA AGG GGA TAC TGA TC
 PGMY09-L CGA CCT AAA GGG AAT TGA TC
 PGMY09-M CGA CCT AGT GGA AAT TGA TC
 PGMY09-N CGA CCA AGG GGA TAT TGA TC
 PGMY09-P G CCC AAC GGA AAC TGA TC
 PGMY09-Q CGA CCC AAG GGA AAC TGG TC
 PGMY09-R CGT CCT AAA GGA AAC TGG TC
 HMB01 GCG ACC CAA TGC AAA TTG GT
 Human β-globin forward GAAGAGCCAAGGACAGGTAC [15]
 Human β-globin reverse GGAAAATAGACCAATAGGCAG
MGP PCR
 MGPA ACGTTGGATGTTTGTTACTGTGGTGGATACTAC [16]
 MGPB ACGTTGGATGTTTGTTACCGTTGTTGATACTAC
 MGPC ACGTTGGATGTTTGTTACTAAGGTAGATACCACTC
 MGPD ACGTTGGATGTTTGTTACTGTTGTGGATACAAC
 MGP31 ACGTTGGATGTTTGTTACTATGGTAGATACCACAC
 MGPG ACGTTGGATGGAAAAATAAACTGTAAATCATATTCCT
 MGPH ACGTTGGATGGAAAAATAAATTGTAAATCATACTC
 MGPI ACGTTGGATGGAAATATAAATTGTAAATCAAATTC
 MGPJ ACGTTGGATGGAAAAATAAACTGTAAATCATATTC
 MGP18 ACGTTGGATGGAAAAATAAACTGCAAATCATATTC
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Table 3.

Master mix constituents and PCR conditions

PGMY PCR
Master mix constituents (for single reaction)
Reagent Volume/μL
10X PCR buffer II (Applied Biosystems) 5
25 mM MgCl2 (Applied Biosystems) 3
PGMY primer mix (10 μM) 1
Human β-globin primer mix (5 μM) 1
10 mM dNTPs (Roche) 1
5 M betaine (Sigma) 10
AmpliTaq Gold DNA Polymerase (Applied Biosystems) 0.25
Molecular grade water (Sigma) 23.75
DNA 5
PCR conditions
Temperature/oC Time No. of cycles
95 9 min 1
95 1 min 40 (50% ramp)
55 1 min
72 1 min
72 5 min 1
15 Hold /
MGP PCR
Master mix constituents (for single reaction)
Reagent Volume/μL
10X PCR buffer II (Applied Biosystems) 2.5
25 mM MgCl2 (Applied Biosystems) 1.5
MGP primer mix (10 μM) 0.5
10 mM dNTPs (Roche) 0.5
AmpliTaq Gold DNA Polymerase (Applied Biosystems) 0.1
Molecular grade water (Sigma) 14.9
DNA 5
PCR conditions
Temperature/oC Time No. of cycles
95 10 min 1
95 30 s 5
42 30 s
72 30 s
95 30 s 45
64 30 s
72 30 s
72 5 min 1
15 Hold /
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Nanopore sequencing library preparation

PGMY and MGP PCR amplicons of each positive specimen were pooled and purified using AMPure XP beads (Beckman-Coulter, Brea, CA, USA). Nanopore sequencing libraries were prepared from purified amplicons using Ligation Sequencing Kit 1D (SQK-LSK109) and PCR-free Native Barcoding Expansion Kit (EXP-NBD104/114) (Oxford Nanopore Technologies, Oxford, England). The barcoded libraries were loaded and sequenced on MinION flow cells (FLO-MIN106D R9.4.1, Oxford Nanopore Technologies, Oxford, England) after quality control runs.

Data analysis

Data from first 2 h of sequencing runs was analyzed. FASTQ files generated by live basecalling (MinKNOW version 2.0) were demultiplexed using ‘FASTQ Barcoding’ workflow on EPI2ME (Oxford Nanopore Technologies, Oxford, England) with default minimum qscore of 7, ‘auto’ and ‘split by barcode’ options. FASTQ files of each specimen were concatenated into a single file and analyzed using a 2-step custom workflow on Galaxy bioinformatics platform. Briefly, FASTQ files were converted into FASTA format, followed by aligning sequences against HPV reference genomes from PaVE database using NCBI BLAST+ blastn (Galaxy version 1.1.1). PGMY and MGP reads were sorted based on sequence length and analyzed individually. Threshold of each run was derived from average number of background reads plus 10 standard deviations, which were calculated using interquartile rule, excluding first and last quartiles. A positive HPV call was based on either (1) the number of reads for a particular HPV type was above threshold, or (2) the specimen had the highest number of reads for a particular HPV type. All positive calls were further assessed by aligning FASTQ sequences against HPV reference genomes using minimap2 (Galaxy version 2.17 + galaxy0), and consensus sequences were built from BAM files using Unipro UGENE (version 1.29.0) for determining their percentage of identity to reference genomes.

Results

As HPV 66 is categorized as ‘other high-risk’ by cobas HPV Test, all calculations were based on this grouping, albeit HPV 66 was found as a single infection in cancers with extreme rarity and re-classified as possible carcinogen (Group 2B) by IARC Monographs Working Group [6].

The results are summarized in Table 1. PCR was successful for 191 specimens (191/201, 95.02%), with 10 specimens (10/201, 4.98%) lacking β-globin band and therefore regarded as inappropriate for further analysis. Seventy-six specimens (76/201, 37.81%) were negative for both PGMY and MGP PCRs, and 115 (115/201, 57.21%) were positive for either of the two. PCR-positive specimens were sequenced on 10 MinION flow cells with 145–890 active pores, generating 31,748–525,880 HPV reads in first 2 h (Table 4). For the 115 specimens sequenced, 19 were negative (7–522 reads, 113 in average) and 96 were positive (45–96,549 reads, 20,158 in average) for HPV. Taken together, there were 95 HPV-negative (95/201, 47.26%) and 96 HPV-positive (96/201, 47.76%) specimens by Nanopore workflow.

Table 4.

Details of Nanopore sequencing runs

Run No. of active pores Elapsed sequencing time No. of HPV reads
1 611 2 h 11 min 60,976
2 458 1 h 59 min 246,521
3 690 2 h 1 min 279,520
4 467 2 h 5 min 111,885
5 462 2 h 5 min 31,748
6 247 2 h 3 min 113,521
7 330 2 h 5 min 111,702
8 753 2 h 1 min 478,711
9 145 1 h 59 min 207,094
10 890 1 h 59 min 525,880
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Table 5 shows concordance of Nanopore workflow with cobas HPV Test and LA, which was based on the 37 HPV types detectable by LA. For cobas HPV Test, our workflow achieved 93.19, 93.19 and 81.94% for perfect, total and positive agreement, respectively, with Cohen’s kappa of 0.85. For LA, Nanopore achieved a perfect agreement of 83.77% for both high-risk and non-high risk HPVs. For high-risk types, total and positive agreement were 96.86 and 91.78%, respectively, with Cohen’s kappa of 0.93. For non-high risk types, total and positive agreement were 93.19 and 77.59%, respectively, with Cohen’s kappa of 0.83.

Table 5.

Agreement between cobas HPV Test, Roche Linear Array HPV Genotyping Test (LA) and Nanopore

Nanopore Perfect agreement Total agreement Positive agreement Cohen’s κ
+ –
cobas HPV Test + 59 2 93.19% 93.19% 81.94% 0.85
– 11 119
LA HR + 67 4 83.77% 96.86% 91.78% 0.93
– 2 118
Non-HR + 45 10 93.19% 77.59% 0.83
– 3 133
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Table 6 shows per-type concordance of Nanopore and LA. A total of 13 high-risk and 19 non-high risk HPV types were evaluated. Positive agreement for HPV 16 (n = 8) and 18 (n = 1) were 87.5 and 100%, respectively. Positive agreement was 75–100% for high-risk HPV 31, 33, 35, 39, 51, 52, 56, 58, 59 and 66, and 20% for HPV 68 (n = 5). For non-high risk HPVs, positive agreement was 37.5–100% for HPV 6, 11, 40, 42, 53, 54, 55, 61, 62, 70, 72, 73, 81, 82, 83, 84 and 89. There were 2 non-high risk types with 0% positive agreement (HPV 26 and 71). HPV 26 (n = 1) was only detected by Nanopore workflow, whereas HPV 71 (n = 2) was only detected by LA.

Table 6.

Per HPV type positive agreement between Roche Linear Array Genotyping Test (LA) and Nanopore

HPV Genotypes Number of specimens Positive agreement
Nanopore−/LA−/LA- Nanopore +/LA- Nanopore−/LA+ Nanopore+/LA+ Total
High-risk 16 183 0 1 7 191 87.5%
18 190 0 0 1 191 100%
31 188 0 0 3 191 100%
33 189 0 0 2 191 100%
35 190 0 0 1 191 100%
39 185 0 1 5 191 83.33%
51 182 0 1 8 191 88.89%
52 165 3 2 21 191 80.77%
56 185 0 0 6 191 100%
58 184 0 0 7 191 100%
59 179 2 1 9 191 75%
66 182 1 0 8 191 88.89%
68 186 2 2 1 191 20%
Non-high risk 6 190 0 0 1 191 100%
11 189 0 0 2 191 100%
26 190 1 0 0 191 0%
40 187 2 0 2 191 50%
42 186 2 1 2 191 40%
53 181 3 0 7 191 70%
54 181 0 4 6 191 60%
55 186 0 0 5 191 100%
61 186 0 0 5 191 100%
62 174 2 2 13 191 76.47%
70 188 0 0 3 191 100%
71 189 0 2 0 191 0%
72 190 0 0 1 191 100%
73 190 0 0 1 191 100%
81 182 0 1 8 191 88.89%
82 189 0 0 2 191 100%
83 189 0 0 2 191 100%
84 183 0 5 3 191 37.5%
89 188 0 0 3 191 100%
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Table 7 reveals the percentage of identity of Nanopore consensus sequences to HPV reference genomes. In general, Nanopore consensus sequences showed an average identity of 98% to the best matches, with an average difference of 15% from second BLAST hits.

Table 7.

Percentage of identity of Nanopore consensus sequences to HPV reference genomes

Patient Nanopore results Best BLAST hit Second BLAST hit Difference
HPV type % identity HPV type % identity
2 59 59 99% 18 77% 22%
a90 90 97% 106 84% 15%
3 52 52 99% 58 80% 19%
55 55 100% 44 93% 7%
5 31 31 98% 35 80% 18%
33 33 99% 58 86% 13%
a52 52 99% 58 80% 19%
a90 90 97% 106 85% 12%
7 31 31 95% 35 79% 16%
9 81 81 99% 62 85% 14%
10 18 18 99% 45 85% 14%
13 a44 44 99% 55 92% 7%
52 52 99% 58 80% 19%
53 53 99% 30 85% 14%
a74 74 99% 55 83% 16%
a90 90 97% 106 85% 12%
16 52 52 99% 58 81% 18%
81 81 99% 62 85% 14%
17 52 52 99% 58 80% 19%
54 54 99% 45 74% 25%
18 11 11 99% 6 87% 12%
52 52 99% 58 80% 19%
59 59 99% 18 77% 22%
23 39 39 99% 70 81% 18%
61 61 99% mEV06c12b 83% 16%
72 72 92% mEV06c12b 89% 3%
a87 87 98% 86 85% 13%
24 66 66 98% 56 84% 14%
25 61 61 99% mEV06c12b 83% 16%
26 a90 90 97% 106 85% 12%
27 52 52 99% 58 80% 19%
a87 87 98% 86 84% 14%
28 62 62 99% 81 84% 15%
30 35 35 98% 31 80% 18%
32 52 52 99% 58 81% 18%
34 51 51 99% 82 85% 14%
35 a74 74 99% 55 84% 15%
37 51 51 99% 82 85% 14%
38 40 40 99% 7 88% 11%
55 55 99% 44 93% 6%
83 83 99% 102 84% 15%
40 a52 52 99% 58 80% 19%
53 53 98% 30 85% 13%
55 55 100% 44 93% 7%
58 58 99% 33 86% 13%
62 62 99% 81 85% 14%
a74 74 98% 55 84% 14%
41 42 42 98% 32 83% 15%
52 52 100% 58 81% 19%
73 73 99% 34 85% 14%
43 16 16 100% 35 78% 22%
44 16 16 99% 35 78% 21%
45 59 59 99% 18 76% 23%
46 31 31 98% 35 80% 18%
58 58 99% 33 86% 13%
47 52 52 98% 58 80% 18%
68 68 93% 39 81% 12%
84 84 98% 87 84% 14%
a90 90 97% 106 85% 12%
48 a44 44 99% 55 93% 6%
66 66 98% 56 84% 14%
84 84 99% 87 84% 15%
49 52 52 99% 58 80% 19%
50 40 40 98% 7 87% 11%
53 53 98% 30 85% 13%
51 11 11 100% 6 87% 13%
a43 43 95% 45 77% 18%
52 52 99% 58 80% 19%
81 81 99% 62 84% 15%
52 66 66 98% 56 83% 15%
53 a43 43 95% 45 78% 17%
51 51 99% 82 84% 15%
a90 90 97% 106 85% 12%
54 16 16 100% 35 78% 22%
a40 40 93% 7 85% 8%
51 51 99% 82 84% 15%
54 54 99% 45 73% 26%
56 56 90% 66 76% 14%
62 62 99% 81 84% 15%
81 81 99% 62 85% 14%
55 53 53 99% 56 79% 20%
56 56 99% 66 84% 15%
57 54 54 87% 31 74% 13%
55 55 100% 44 93% 7%
66 66 98% 56 84% 14%
81 81 99% 62 84% 15%
a90 90 97% 106 85% 12%
58 a42 42 99% 32 84% 15%
52 52 98% 58 80% 18%
a90 90 97% 106 85% 12%
59 59 59 99% 18 77% 22%
60 59 59 99% 18 76% 23%
89 89 99% 81 78% 21%
61 a43 43 96% 45 79% 17%
56 56 97% 66 83% 14%
82 82 99% 51 84% 15%
62 52 52 99% 58 80% 19%
63 33 33 99% 58 86% 13%
a44 44 99% 55 93% 6%
51 51 99% 82 83% 16%
64 51 51 99% 82 84% 15%
65 16 16 100% 35 78% 22%
68 a59 59 99% 18 77% 22%
69 a87 87 99% 86 86% 13%
74 a52 52 99% 58 81% 18%
58 58 99% 33 86% 13%
a62 62 99% 81 85% 14%
75 58 58 99% 33 85% 14%
78 a90 90 97% 106 85% 12%
79 a44 44 99% 55 92% 7%
56 56 96% 66 84% 12%
70 70 99% 39 81% 18%
81 a74 74 93% 55 81% 12%
82 42 42 95% 32 83% 12%
83 a74 74 97% 55 83% 14%
85 82 82 99% 51 84% 15%
86 62 62 99% 81 85% 14%
91 52 52 99% 58 80% 19%
a90 90 97% 106 84% 13%
92 a42 42 93% 32 78% 15%
68 68 92% 39 80% 12%
96 52 52 99% 58 80% 19%
100 52 52 99% 58 80% 19%
104 62 62 98% 81 85% 13%
107 a44 44 99% 55 93% 6%
52 52 99% 58 81% 18%
a53 53 100% 30 86% 14%
62 62 99% 81 85% 14%
112 16 16 98% 58 78% 20%
52 52 99% 58 81% 18%
114 a26 26 100% 69 83% 17%
55 55 100% 44 93% 7%
a59 59 99% 18 77% 22%
a62 62 99% 81 85% 14%
89 89 99% 81 77% 22%
115 a74 74 95% 55 83% 12%
118 6 6 99% 11 87% 12%
62 62 99% 81 84% 15%
124 81 81 99% 62 85% 14%
125 a87 87 98% 86 85% 13%
126 a90 90 97% 106 85% 12%
138 39 39 99% 68 81% 18%
143 a40 40 99% 7 88% 11%
a74 74 98% 55 84% 14%
81 81 99% 62 84% 15%
a87 87 97% 86 84% 13%
148 59 59 99% 18 77% 22%
152 62 62 98% 81 85% 13%
156 52 52 99% 58 81% 18%
54 54 95% 6 74% 21%
157 39 39 94% 70 81% 13%
53 53 96% 30 84% 12%
61 61 99% mEV06c12b 83% 16%
161 62 62 98% 81 83% 15%
162 a74 74 94% 55 85% 9%
163 62 62 99% 81 85% 14%
167 39 39 99% 70 81% 18%
170 66 66 98% 56 83% 15%
174 66 66 98% 56 83% 15%
175 54 54 99% 45 73% 26%
177 16 16 99% 35 80% 19%
a53 53 99% 30 84% 15%
62 62 99% 81 85% 14%
181 51 51 99% 82 85% 14%
66 66 98% 56 83% 15%
a68 68 98% 39 81% 17%
182 58 58 98% 33 87% 11%
61 61 100% mEV06c12b 83% 17%
184 58 58 99% 33 85% 14%
185 58 58 99% 33 85% 14%
70 70 99% 39 81% 18%
89 89 99% 81 78% 21%
188 16 16 100% 35 78% 22%
191 56 56 99% 66 83% 16%
192 51 51 98% 82 84% 14%
193 62 62 99% 81 85% 14%
195 52 52 99% 58 81% 18%
59 59 99% 18 76% 23%
196 59 59 99% 18 77% 22%
197 52 52 100% 58 81% 19%
59 59 99% 18 76% 23%
70 70 99% 39 81% 18%
a90 90 97% 106 85% 12%
198 a32 32 99% 42 84% 15%
53 53 99% 30 86% 13%
56 56 99% 66 84% 15%
61 61 100% mEV06c12b 83% 17%
66 66 98% 56 83% 15%
84 84 99% 87 84% 15%
200 53 53 98% 30 85% 13%
54 54 99% 45 74% 25%
81 81 99% 62 84% 15%
83 83 95% 102 82% 13%
Average % identity of the best hit 98% Average difference 15%
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a HPV types not detected by LA

Table 8 summarizes HPV status of each cytology grading. For high-grade and low-grade squamous intraepithelial lesion (HSIL and LSIL), nearly all specimens were positive for high-risk HPV (HSIL: 4/4, 100%; LSIL: 16/18, 88.89%). For atypical squamous/ glandular cells, about half of the specimens were positive for high-risk HPV (by LA: 19/41, 46.34%; by Nanopore: 18/41, 43.90%). For cases without observable abnormalities, 22.12% (25/113) and 21.24% (24/113) were positive for high-risk HPV by LA and Nanopore, respectively.

Table 8.

Results of Pap smear, LA and Nanopore workflow. The calculations were based 176 quality control-valid specimens with Pap smear results available

Pap smear interpretation HPV status No. of specimens
LA Nanopore
HSIL (n = 4) HR/ HR + non-HR 4 4
Non-HR only 0 0
Negative 0 0
LSIL/ LSIL + ASCH (n = 18) HR/ HR + non-HR 16 16
Non-HR only 1 1
Negative 1 1
AGUS/ ASCH/ ASCUS (n = 41) HR/ HR + non-HR 19 18
Non-HR only 3 6
Negative 19 17
NIL (n = 113) HR/ HR + non-HR 25 24
Non-HR only 18 18
Negative 70 71
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Discussion

Hong Kong has been one of the Asian regions with the lowest incidence and mortality rate of CC [16]. This might be attributable to the territory-wide cervical screening program implemented by Department of Health since 2004. The program is well-organized, which involves public education, regular cervical smear and follow-up service for eligible women, and a quality assurance mechanism on key components of the program [17]. Cytology is the mainstay of primary screening, and high-risk HPV testing may be performed for triage to colposcopy.

Cytology and HPV testing have their own value for CC screening. High quality cytology has high specificity for CC, but with lower sensitivity ranging from 50% suggested by cross-sectional studies to 75% estimated longitudinally [18]. For HPV testing, the sensitivity was reported to be about 10% higher than cytology, yet with lower specificity [18]. Complementary use of both tests could enhance the sensitivity approaching 100% with high specificity (92.5%) [19]. In fact, this combined approach has been adopted by several European countries and may become the future trend of primary CC screening in developed countries.

Compared with HPV assays in the market, HPV genotyping by NGS offers a broader detection spectrum which, despite minimal benefit of non-high risk HPV information for CC screening, may provide important etiologic clues for other HPV-associated infections and a more complete picture of HPV epidemiology. For the latter, Nanopore identified more HPV types per sample (Fig. 1) and 5 extra HPV types (HPV 43, 44, 74, 87 and 90, n = 34) not detectable by LA (Fig. 2), with an unexpected high incidence of HPV 90 (n = 12) which was reported in North America and Belgium but not in Hong Kong [20, 21]. Another advantage offered by NGS is its potential utility for simultaneous characterization of cervicovaginal microbiome, with its possible role in dysplasia and carcinogenesis revealed by accumulating research evidence [22–25]. These merits may facilitate a multifaceted approach for evaluation of woman health in near feature.

Fig. 1.

Fig. 1

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Number of HPV types detected per sample by Nanopore workflow and LA

Fig. 2.

Fig. 2

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Diversity of HPV types detected by Nanopore workflow and LA

In general, Nanopore had substantial agreement with cobas HPV Test and LA. Compared with cobas HPV Test, Nanopore appeared to be more sensitive for HPV 52 (n = 7) and 59 (n = 4), with 81.82% (9/11) of these discrepant results matched with LA. Compared with LA, concordance for high-risk HPV was higher than non-high risk types. Among the 37 discrepant results, 22 were false negatives by Nanopore and 15 were not detected by LA.

For the false negatives by Nanopore, more than half (12/22, 54.55%) were mixed infections, and similar finding was reported by other research groups using HPV consensus primers for NGS-based genotyping [10, 11]. Other possible causes of false negatives included (1) low viral load, as evident by Specimen 182, from which HPV 16 was missed by both Nanopore and cobas HPV Test; (2) substantial difference in DNA input (50 μL for LA versus 5 μL for PGMY/ MGP PCR), as well as (3) lower sensitivity due to reduced magnesium chloride concentration of PGMY PCR (from 4 mM to 1.5 mM), which was fine-tuned for minimal non-specific amplification.

For the 15 HPV types missed by LA, the average identity of Nanopore consensus sequences was 98.27% with an average difference of 16% from second BLAST hits (Table 7). As distinct HPV types generally have more than 10% difference in L1 sequence [26, 27], it appeared that the discrepant positive calls were less likely caused by high sequencing error rate of Nanopore. More specifically, 5 of these positive calls were identified solely by MGP PCR (5/15, 33.33%), 5 detected by PGMY PCR only (5/15, 33.33%), and 5 by both PCRs (5/15, 33.33%). These revealed differential sensitivities of PGMY and MGP PCR primers, which might complement with each other and enhance overall performance of the Nanopore assay. On the other hand, Nanopore sequencing might improve the resolution of genotyping, which might not be attained by line blot method due to cross-hybridization of certain probes. For instance, Nanopore identified HPV 52 in Specimen 5, 40 and 74, which could not be confirmed by LA due to cross-hybridization with HPV 33 and 58, respectively. Another example was Specimen 125, which was HPV 84-positive by LA and HPV 87-positive by Nanopore. From literature, Artaza-Irigaray and colleagues reported cross-hybridization between these 2 HPV types by LA, with 11.5% of HPV 84-positive cervical specimens by LA were actually HPV 87-positive by NGS [28].

The Nanopore method and LA revealed very similar high-risk HPV positivity in each cytology grading. The goal of combined cytology-HPV testing approach is to enhance cost effectiveness of CC screening. While minimizing unnecessary referral for colposcopy, HPV genotyping may identify high-risk individuals before observable cytological abnormalities, for instance, the 4 HPV 16-positive patients without abnormal cytology findings in this study. This may facilitate an early detection approach for cancer prevention.

Our study had several limitations. First, the sample size of certain HPV types, for example, HPV 18 (n = 1), was less satisfactory for evaluating type-specific performance. Second, as residual DNA was used after routine testing, DNA input for PGMY and MGP PCRs was constrained which might lower the sensitivity. In addition, as flow cells with suboptimal number of active pores were used, sequencing time and depth might be further improved if new flow cells were used.

Conclusions

We developed a Nanopore workflow for HPV genotyping, with performance comparable to or better than 2 reference methods in the market. Our method was economical, with a reagent cost of about USD 50.77 per patient specimen for 24-plex runs, which was competitive when compared to an average price of USD 106.14 (from 4 randomly-selected laboratories) for HPV genotyping referral service in our region (Table 9). The protocol was also straightforward with reasonable turnaround time of about 12 h from samples to answers. The small size and portability of MinION sequencers may well suit remote or resource-limited laboratories with constraints in space. Future prospective study with larger sample size is warranted to further evaluate test performance and streamline the protocol. As LA was discontinued in Hong Kong, the Nanopore workflow described here may provide an economical option for broad-range HPV genotyping.

Table 9.

Comparison of estimated reagent cost of Nanopore workflow (24-plex) and randomly-selected prices of HPV genotyping referral service in Hong Kong

This study
Procedure Number of specimens Cost
DNA extraction and PCRs 201 patients +20 controls = 221 USD 20.02 × 221 reactions = USD 4424.42
Nanopore sequencing

115 patients / 24 = at least 5 runs

N = 120 for 1 positive control per run

 USD 1155.94 × 5 runs = USD 5779.70
Cost per patient specimen (4424.42 + 5779.70) / 201 = USD 50.77
Referral service (transportation cost not included)
Lab A USD 77.19
Lab B USD 124.79
Lab C USD 101.63
Lab D USD 120.93
Average USD 106.14
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Acknowledgements

We thank the colleagues of Department of Pathology, Hong Kong Sanatorium & Hospital for their dedicated and professional work on routine laboratory diagnostics.

Abbreviations

CC

Cervical cancer

HPV

Human papillomavirus

HSIL

High-grade squamous intraepithelial lesion

IARC

International Agency for Research on Cancer (IARC)

LA

Roche Linear Array HPV Genotyping Test

LSIL

Low-grade squamous intraepithelial lesion

NGS

Next-generation sequencing

Pap smear

Papanicolaou smear

PCR

Polymerase chain reaction

WHO

World Health Organization

Authors’ contributions

BSFT, TLC and WSC conceived and designed the study. BSFT, ESKM, MKMC, TLC, CPL, CHA, MYT, MKN, SML and WSC were involved in data collection and analysis. WSC wrote the first draft. All authors critically reviewed and approved the manuscript.

Funding

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

This study was approved by Research Ethics Committee (REC) of Hong Kong Sanatorium & Hospital under the reference number RC-2019-18. No patient-identifying data was collected throughout the whole study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.zur Hausen H. Papillomaviruses in the causation of human cancers – a brief historical account. Virology. 2009;384:260–5. [DOI] [PubMed]
  • 2.Meisels A, Fortin R. Condylomatous lesions of the cervix and vagina. I Cytologic patterns Acta Cytol. 1976;20:505–509. [PubMed] [Google Scholar]
  • 3.Purola E, Savia E. Cytology of gynecologic condyloma acuminatum. Acta Cytol. 1977;21:26–31. [PubMed] [Google Scholar]
  • 4.Muñoz N, Bosch FX, de Sanjosé S, Herrero R, Castellsagué X, Shah KV, et al. Epidemiologic classification of human papillomavirus types associated with cervical cancer. N Engl J Med. 2003;348:518–527. doi: 10.1056/NEJMoa021641. [DOI] [PubMed] [Google Scholar]
  • 5.IARC Working Group on the Evaluation of Carcinogenic Risks to Humans Human papillomaviruses. IARC Monogr Eval Carinog Risks Hum. 2007;90:1–636. [PMC free article] [PubMed] [Google Scholar]
  • 6.Schiffman M, Clifford G, Buonaguro FM. Classification of weakly carcinogenic human papillomavirus types: addressing the limits of epidemiology at the borderline. Infect Agent Cancer. 2009;4:8. doi: 10.1186/1750-9378-4-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Chrysostomou AC, Stylianou DC, Constantinidou A, Kostrikis LG. Cervical cancer screening programs in Europe: the transition towards HPV vaccination and population-based HPV testing. Viruses. 2018;10:729. [DOI] [PMC free article] [PubMed]
  • 8.Petry KU, Barth C, Wasem J, Neumann A. A model to evaluate the costs and clinical effectiveness of human papilloma virus screening compared with annual Papanicolaou cytology in Germany. Eur J Obstet Gynecol Reprod Biol. 2017;212:132–139. doi: 10.1016/j.ejogrb.2017.03.029. [DOI] [PubMed] [Google Scholar]
  • 9.Pan American Health Organization. Section 2: Summary of commercially available HPV tests. https://www.paho.org/hq/dmdocuments/2016/manual-VPH-English-02.pdf (2016). Accessed 3 Jan 2020.
  • 10.Nilyanimit P, Chansaenroj J, Poomipak W, Praianantathavorn K, Payungporn S, Poovorawan Y. Comparison of four human papillomavirus genotyping methods: next-generation sequencing, INNO-LiPA, electrochemical DNA Chip, and nested-PCR. Ann Lab Med. 2018;38:139–146. doi: 10.3343/alm.2018.38.2.139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Nowak RG, Ambulos NP, Schumaker LM, Mathias TJ, White RA, Troyer J, et al. Genotyping of high-risk anal human papillomavirus (HPV): ion torrent-next generation sequencing vs. linear array. Virol J. 2017;14:112. doi: 10.1186/s12985-017-0771-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Wagner S, Roberson D, Boland J, Yeager M, Cullen M, Mirabello L, et al. Development of the TypeSeq assay for detection of 51 human papillomavirus genotypes by next-generation sequencing. J Clin Microbiol. 2019;57:e01794–18. [DOI] [PMC free article] [PubMed]
  • 13.Gravitt PE, Peyton CL, Alessi TQ, Wheeler CM, Coutlée F, Hildesheim A, et al. Improved amplification of genital human papillomaviruses. J Clin Microbiol. 2000;38:357–361. doi: 10.1128/jcm.38.1.357-361.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Söderlund-Strand A, Carlson J, Dillner J. Modified general primer PCR system for sensitive detection of multiple types of oncogenic human papillomavirus. J Clin Microbiol. 2009;47:541–546. doi: 10.1128/JCM.02007-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Marín M, Garcia-Lechuz JM, Alonso P, Villanueva M, Alcalá L, Gimeno M, et al. Role of universal 16S rRNA gene PCR and sequencing in diagnosis of prosthetic joint infection. J Clin Microbiol. 2012;50:583–589. doi: 10.1128/JCM.00170-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Department of Health, the Government of the Hong Kong Special Administrative Region. Evidence for organized screening programme. https://www.cervicalscreening.gov.hk/english/about/abt_evidence.html (2013). Accessed 15 Jan 2020.
  • 17.Department of Health, the Government of the Hong Kong Special Administrative Region. About Cervical Screening Programme. https://www.cervicalscreening.gov.hk/english/about/about.html (2013). Accessed 15 Jan 2020.
  • 18.World Health Organization: Cervical cancer screening in developing countries. Report of a WHO consultation. https://apps.who.int/iris/bitstream/handle/10665/42544/9241545720.pdf;jsessionid=2599A27FFB141B755D015B645FB889D9?sequence=1 (2002). Accessed 15 Jan 2020.
  • 19.Mayrand MH, Duarte-Franco E, Rodrigues I, Walter SD, Hanley J, Ferenczy A, et al. Human papillomavirus DNA versus Papanicolaou screening tests for cervical cancer. N Engl J Med. 2007;357:1579–1588. doi: 10.1056/NEJMoa071430. [DOI] [PubMed] [Google Scholar]
  • 20.Quiroga-Garza G, Zhou H, Mody DR, Schwartz MR, Ge Y. Unexpected high prevalence of HPV 90 infection in an underserved population: is it really a low-risk genotype? Arch Pathol Lab Med. 2013;137:1569–1573. doi: 10.5858/arpa.2012-0640-OA. [DOI] [PubMed] [Google Scholar]
  • 21.Schmitt M, Depuydt C, Benoy I, Bogers J, Antoine J, Arbyn M, et al. Prevalence and viral load of 51 genital human papillomavirus types and three subtypes. Int J Cancer. 2013;132:2395–2403. doi: 10.1002/ijc.27891. [DOI] [PubMed] [Google Scholar]
  • 22.Mitra A, Maclntyre DA, Lee YS, Smith A, Marchesi JR, Lehne B, et al. Cervical intraepithelial neoplasia disease progression is associated with increased vaginal microbiome diversity. Sci Rep. 2015;5:16865. doi: 10.1038/srep16865. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Oh HY, Kim BS, Seo SS, Kong JS, Lee JK, Park SY, et al. The association of uterine cervical microbiota with an increased risk for cervical intraepithelial neoplasia in Korea. Clin Microbiol Infect. 2015;21:674. doi: 10.1016/j.cmi.2015.02.026. [DOI] [PubMed] [Google Scholar]
  • 24.Klein C, Gonzalez D, Samwel K, Kahesa C, Mwaiselage J, Aluthge N, et al. Relationship between the cervical microbiome, HIV status, and precancerous lesions. MBio. 2019;10:e02785–e02718. doi: 10.1128/mBio.02785-18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Nené NR, Reisel D, Leimbach A, Franchi D, Jones A, Evans I, et al. Association between the cervicovaginal microbiome, BRCA1 mutation status, and risk of ovarian cancer: a case-control study. Lancet Oncol. 2019;20:1171–1182. doi: 10.1016/S1470-2045(19)30340-7. [DOI] [PubMed] [Google Scholar]
  • 26.King AJ, Sonsma JA, Vriend HJ, van der Sande MA, Feltkamp MC, Boot HJ, et al. Genetic diversity in the major capsid L1 protein of HPV-16 and HPV-18 in the Netherlands. PLoS One. 2016;11:e0152782. doi: 10.1371/journal.pone.0152782. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Burk RD, Harari A, Chen Z. Human papillomavirus genome variants. Virology. 2013;445:232–243. doi: 10.1016/j.virol.2013.07.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Artaza-Irigaray C, Flores-Miramontes MG, Olszewski D, Vallejo-Ruiz V, Limón-Toledo LP, Sánchez-Roque C, et al. Cross-hybridization between HPV genotypes in the linear Array genotyping test confirmed by next-generation sequencing. Diagn Pathol. 2019;14:31. doi: 10.1186/s13000-019-0808-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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