Comparing the Diagnostic Performance of Quantitative PCR, Digital Droplet PCR, and Next-Generation Sequencing Liquid Biopsies for Human Papillomavirus–Associated Cancers

Saskia Naegele; Daniel A Ruiz-Torres; Yan Zhao; Deborah Goss; Daniel L Faden

doi:10.1016/j.jmoldx.2023.11.007

. 2024 Mar;26(3):179–190. doi: 10.1016/j.jmoldx.2023.11.007

Comparing the Diagnostic Performance of Quantitative PCR, Digital Droplet PCR, and Next-Generation Sequencing Liquid Biopsies for Human Papillomavirus–Associated Cancers

Saskia Naegele ^∗, Daniel A Ruiz-Torres ^∗, Yan Zhao ^∗, Deborah Goss ^∗, Daniel L Faden ^∗,^†,^‡,^∗

PMCID: PMC10918646 PMID: 38103593

Abstract

Human papillomavirus (HPV)-associated cancers, including oropharyngeal squamous cell carcinoma (HPV + OPSCC), cervical cancer, and squamous cell carcinoma of the anus (HPV + SCCA), release circulating tumor HPV DNA (ctHPVDNA) into the blood. The diagnostic performance of ctHPVDNA detection depends on the approaches used and the individual assay metrics. A comparison of these approaches has not been systematically performed to inform expected performance, which in turn affects clinical interpretation. A meta-analysis was performed using Ovid MEDLINE, Embase, and Web of Science Core Collection databases to assess the diagnostic accuracy of ctHPVDNA detection across cancer anatomic sites, detection platforms, and blood components. The population included patients with HPV + OPSCC, HPV-associated cervical cancer, and HPV + SCCA with pretreatment samples analyzed by quantitative PCR (qPCR), digital droplet PCR (ddPCR), or next-generation sequencing (NGS). Thirty-six studies involving 2986 patients met the inclusion criteria. The sensitivity, specificity, and quality of each study were assessed and pooled for each analysis. The sensitivity of ctHPVDNA detection was greatest with NGS, followed by ddPCR and then qPCR when pooling all studies, whereas specificity was similar (sensitivity: ddPCR > qPCR, P < 0.001; NGS > ddPCR, P = 0.014). ctHPVDNA from OPSCC was more easily detected compared with cervical cancer and SCCA, overall (P = 0.044). In conclusion, detection platform, anatomic site of the cancer, and blood component used affects ctHPVDNA detection and must be considered when interpreting results. Plasma NGS-based testing may be the most sensitive approach for ctHPVDNA overall.

Human papillomaviruses (HPVs) are a family of DNA oncoviruses that cause benign and malignant lesions of the genital mucosa, upper respiratory tract, and skin. More than 200 distinct types of HPV have been identified, and at least 14 of them are classified as high risk, or capable of tumorigenesis, in specific anatomic sites.1, 2, 3 HPV accounts for 5% of cancers worldwide and causes almost all cases of cervical cancer, as well as a significant proportion of vaginal, vulvar, penile, anal, rectal, and oropharyngeal cancers.4, 5, 6, 7, 8 Routine screening strategies for HPV-associated cervical cancer (HPV + CC), including pelvic examinations and Papanicolaou smears, enable early detection and have contributed to a substantial reduction in the incidence of early-stage cervical cancer.⁹^,¹⁰ Unlike with cervical cancer, effective screening strategies for HPV-associated oropharyngeal squamous cell carcinoma (HPV + OPSCC) and HPV-associated squamous cell carcinoma of the anus (HPV + SCCA) are lacking, and the incidence of these cancers has steadily increased in the past few decades.¹¹ In the United States and the United Kingdom, the incidence of HPV + OPSCC in men has surpassed rates of cervical cancer in women and continues to rise, despite HPV vaccination efforts.12, 13, 14, 15, 16 Existing approaches to diagnose and monitor these cancers are invasive, costly, and have variable accuracy, indicating a need to improve the current standard of care.

Circulating tumor DNA (ctDNA) is released or secreted from cancer cells into the blood and other body fluids.17, 18, 19, 20, 21, 22 Results of liquid biopsies detecting ctDNA have shown broad applicability, from cancer screening to molecular profiling, adaptive treatment monitoring during therapy, detection of minimal residual disease, and recurrence detection.23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33 HPV-associated cancers release circulating tumor HPV DNA (ctHPVDNA), which has distinct advantages over somatic ctDNA due to the smaller size of the viral genome and its specificity to cancer cells, making HPV-associated cancers an optimal target for the application of liquid biopsies.³⁴ Numerous studies have shown that ctHPVDNA is detectable in the plasma or serum of patients with HPV-associated cancers at the time of diagnosis. It can be used as a real-time biomarker to monitor treatment response and can detect recurrence earlier than standard of care imaging.35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45 ctHPVDNA-based diagnostics may have improved accuracy, reduced cost, and a shorter time to diagnosis compared with existing tissue-based clinical diagnostics.⁴⁶ In the past, conventional real-time quantitative PCR (qPCR) was the most common method used for the detection of ctDNA, but newer (and more costly) techniques, including droplet-digital PCR (ddPCR) and next-generation sequencing (NGS), have emerged.⁴⁷ The diagnostic performance of ctHPVDNA detection depends on the approaches used and the individual assay metrics. A comparison of these approaches has not been systematically performed in the literature to inform expected performance, which in turn influences clinical interpretation. We tested the hypothesis that the sensitivity of NGS-based liquid biopsy is superior to that of qPCR and ddPCR at the time of diagnosis across HPV-associated cancers.

Materials and Methods

A systematic review was performed by a medical librarian (D.G.) following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses.⁴⁸

Literature Search

A search of published studies in Ovid MEDLINE (Wolters-Kluwer, 1946–February 2022), Embase (Elsevier, 1947–February 2022), and Web of Science Core Collections (Clarivate, 1900–February 2022) was designed and conducted by a reference librarian (D.G.) on February 18 and February 23, 2022. (Registration may be required to access these databases.)

Search strategies were customized for each database. Each search used a combination of controlled vocabulary and key word terms relating to the diagnosis of HPV-associated cancer (head and neck, anal, vulvar, cervical, vaginal, and penile) using qPCR, ddPCR, or NGS testing. The search was constructed to exclude non-human studies. No filters for language, study design, date of publication, or country of origin were used in the search, which produced 251 articles (Figure 1). All references were exported into EndNote X7.8 (Clarivate, Philadelphia, PA). Duplicates were removed first by the automated process in EndNote and then manually by the librarian; this left 153 articles, which were exported into Covidence (Melbourne, VIC, Australia) for study screening, selection, and data extraction. Nine subsequent articles were found through searching the references of included articles, thus yielding a total of 162 articles for screening.

Study Selection

Studies that examined ctDNA in any HPV-associated cancer with qPCR, ddPCR, or NGS were considered eligible for inclusion. Extracted data comprised the following: anatomic subsite; HPV status; HPV assay detection method; number of patients tested on each assay; number of true-positive, false-positive, false-negative, and true-negative findings; source of ctHPVDNA (plasma or serum); probe target gene (if ddPCR was used); and amplicon or hybrid capture (if NGS was used). Only studies written in English were included. Titles and abstracts were screened independently by two authors (S.N. and D.A.R.-T.) for full-text review. The same two authors independently conducted the full-text review. Any disagreements in the screening process were settled by discussion and consensus between the two authors. All eligible studies were screened for duplicate data by comparing authors, timeframe of data collection, and outcomes. After full text screening, 36 studies remained for the quantitative synthesis.

R 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria; https://cran.r-project.org) was used to conduct the statistical analysis and the R packages “meta” and “metafor” were used for the meta-analysis. The studies missing one of the two values [true positive, false negative (TP, FN) or true negative, false positive (TN, FP)] were excluded. Using the random effects model, sensitivity, including 95% confidence intervals (CIs), was computed from TP and TP + FN, and specificity including 95% CI was computed from TN and TN + FP. Subgroups were defined differently for each model, and the pooled means were calculated respectively. Subsequently, separate meta-regressions were performed to test the association of each study characteristic with HPV sensitivities and specificities. Interstudy variability and between-study variance were assessed by using Cochran’s Q statistic. The percentage of variation explained by true heterogeneity opposed to sampling error was calculated with the I² statistic. A two-sided P < 0.05 was considered to be significant.

Potential publication bias was evaluated by using the Quality Assessment of Diagnostic Accuracy Studies-2 tool (https://www.bristol.ac.uk/population-health-sciences/projects/quadas/quadas-2). The risk of bias was judged as high or low when the answers to all signaling questions in the four domains were yes or no, respectively. If the information was not sufficient, an unclear bias was used. Most studies were at unclear or low risk of bias for flow and timing and index test domains (Figure 2). Notably, for reference standard, three studies were at unclear risk of bias and for patient selection, four studies were at high risk of bias. Regarding applicability, 33 studies were at low risk of bias for reference standard and index test, but five studies were at high risk of bias for patient selection.

Quality evaluation of the included studies. The domains rated were flow and timing, patient selection, reference standard, and index test. Patient selection determined whether the selection of patients may have introduced bias. Index test assessed what the index test was and how it was conducted and interpreted. Reference standard assessed whether the gold standard was likely to correctly classify the target condition and if those results were interpreted without knowledge of the index test results. Flow and timing assessed whether there was an appropriate interval between the index test and the reference standard. Red color indicates high risk of bias, green indicates low risk of bias, and yellow indicates unclear risk of bias. QUADAS-2, Quality Assessment of Diagnostic Accuracy Studies-2.

Results

Sensitivity and Specificity of ctHPVDNA Detection by Test at the Time of Diagnosis

A total of 36 studies were included in the meta-analysis containing a total of 2986 patients (Table 1 35, 36, 37^,⁴⁰^,42, 43, 44, 46^,49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76). There were 11 qPCR studies, 19 ddPCR studies, and 7 NGS studies. The pooled sensitivity of ctHPVDNA detection was first examined across all tests (Figure 3). A pooled sensitivity of 0.81 (95% CI, 0.73–0.87) from 19 studies (n = 1056) was compared using ddPCR versus 11 studies (n = 597) using qPCR (0.51; 95% CI, 0.37–0.64; P < 0.001) and 7 studies (n = 179) using NGS (0.94; 95% CI, 0.88–0.97; P = 0.014)) (Figure 4). Ten qPCR studies (n = 638), 12 ddPCR studies (n = 449), and 7 NGS studies (n = 244) were used to calculate specificity. A pooled specificity of 0.98 (95% CI, 0.96–0.99) for ddPCR was compared with qPCR (0.93; 95% CI, 0.83–0.97; P = 0.05) and NGS (0.95; 95% CI, 0.90–0.97; P = 0.507) (Figure 4).

Table 1.

Overview of Study Characteristics

Studies included in statistical analysis
Authors	Year	Anatomic subsite	Total no. of patients evaluated	Assay technique	Source of ctHPVDNA	Target gene (if ddPCR)	Amplicon or hybrid capture (if NGS)
Bernard-Tessier et al⁴⁴	2019	Anus	57	ddPCR	Serum	E7	–
Cabel et al⁴⁹	2021	Cervix	55	ddPCR	Plasma; serum	E7	–
Cabel et al⁵⁰	2018	Anus	33	ddPCR	Plasma; serum	E7	–
Chera et al³⁷	2019	Oropharynx	218	ddPCR	Plasma	E7	–
Cheung et al⁵¹	2019	Cervix	138	ddPCR	Plasma	E7, L1	–
Damerla et al⁴⁰	2019	Anus, oropharynx	159	ddPCR	Plasma	E6, E7	–
Han et al⁵²	2018	Cervix	19	ddPCR	Plasma	E6, E7	–
Haring et al⁵³	2021	Oropharynx	16	ddPCR	Plasma	E6	–
Hilke et al⁵⁴	2020	Oropharynx	20	NGS	Plasma	–	Hybrid capture
Holmes et al⁵⁵	2016	Cervix	5	NGS	Plasma; serum	–	Hybrid capture
Jeannot et al⁴²	2016	Anus, cervix, oropharynx	86	ddPCR	Serum	E7	–
Jeannot et al⁴³	2021	Cervix	94	ddPCR	Serum	E7	–
Kang et al⁵⁶	2017	Cervix	64	ddPCR	Serum	E7	–
Lee et al⁵⁷	2020	Anus	41	NGS	Plasma	–	Amplicon
Lee et al⁵⁸	2017	Oropharynx	41	NGS	Plasma	–	Amplicon
Lefèvre et al⁵⁹	2021	Anus	61	ddPCR	Plasma	E6, E7	–
Leung et al⁶⁰	2021	Anus, oropharynx	26	ddPCR	Plasma	E6, E7	–
Leung et al⁶⁰	2021	Anus, oropharynx	18	NGS	Plasma	–	Hybrid capture
Mes et al⁶¹	2020	Oropharynx	59	NGS	Plasma	–	Hybrid capture
Nguyen et al⁶²	2020	Oropharynx	28	ddPCR	Plasma	E7	–
Rungkamoltip et al⁶³	2020	Cervix	73	ddPCR	Serum	E7	–
Sastre-Garau et al⁶⁴	2021	Anus, cervix, oropharynx	134	NGS	Plasma	–	Hybrid capture
Siravegna et al⁴⁶	2021	Oropharynx	131	ddPCR	Plasma	E7	–
Tanaka et al⁶⁵	2022	Oropharynx	80	ddPCR	Plasma	E6, E7	–
Veyer et al⁶⁶	2020	Oropharynx	66	ddPCR	Plasma	E6	–
Ahn et al³⁶	2014	Oropharynx	61	qPCR	Plasma	–	–
Akashi et al⁶⁷	2022	Oropharynx	29	ddPCR	Plasma	E6, E7	–
Cao et al³⁵	2012	Oropharynx	74	qPCR	Plasma	–	–
Cocuzza et al⁶⁸	2017	Cervix	140	qPCR	Plasma	–	–
Capone et al⁶⁹	2000	Oropharynx	70	qPCR	Serum	–	–
Ho et al⁷⁰	2005	Cervix	135	qPCR	Plasma	–	–
Hsu et al⁷¹	2003	Cervix	152	qPCR	Serum	–	–
Mazurek et al⁷²	2019	Oropharynx	29	qPCR	Plasma	–	–
Pornthanakasem et al⁷³	2001	Cervix	83	qPCR	Plasma	–	–
Dahlstrom et al⁷⁴	2015	Oropharynx	262	qPCR	Serum	–	–
Reder et al⁷⁵	2020	Oropharynx	50	qPCR	Plasma	–	–
Yang et al⁷⁶	2004	Cervix	179	qPCR	Plasma	–	–

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Study characteristics are presented for all 36 studies eligible for the statistical analysis, including anatomic subsite, assay technique, source of ctHPVDNA, target gene (if ddPCR), and amplicon or hybrid capture (if NGS).

–, characteristic was not applicable to the particular study; ctHPVDNA, circulating tumor human papillomavirus DNA; ddPCR, digital droplet PCR; NGS, next-generation sequencing; qPCR, quantitative PCR.

Sensitivity from 36 studies used in the meta-analysis. CI, confidence interval; ddPCR, digital droplet PCR; HPV, human papillomavirus; NGS, next-generation sequencing; qPCR, quantitative PCR.

Pooled sensitivity and specificity of quantitative PCR (qPCR) versus digital droplet PCR (ddPCR) versus next-generation sequencing (NGS) across all human papillomavirus–associated cancers.

Sensitivity and Specificity of ctHPVDNA Detection Test According to Anatomic Subsite

Because ctHPVDNA detection may differ according to cancer anatomic site, sensitivity and specificity was evaluated next across each anatomic site by ctHPVDNA test. For HPV + OPSCC, 21 studies including a total of 1436 patients were evaluated (Supplemental Figure S1). A pooled sensitivity of 0.89 (95% CI, 0.78–0.94) was compared from 10 studies (n = 460) using ddPCR versus 6 studies (n = 278) using qPCR (0.66; 95% CI, 0.58–0.74; P = 0.005), and 5 studies (n = 74) using NGS (0.91; 95% CI, 0.81–0.96; P = 0.357) (Figure 5). Five qPCR studies (n = 268), six ddPCR studies (n = 253), and three NGS studies (n = 103) were used to calculate specificity. A pooled specificity of 0.97 (95% CI, 0.94–0.99) for ddPCR was compared versus qPCR (0.94; 95% CI, 0.59–0.99; P = 0.449) and NGS (0.97; 95% CI, 0.90–0.99; P = 0.922) (Figure 5).

Pooled sensitivity and specificity of quantitative PCR (qPCR) versus digital droplet PCR (ddPCR) versus next-generation sequencing (NGS) in studies of human papillomavirus–associated oropharyngeal, cervical, and anal cancer.

For HPV + CC, 16 studies including a total of 1285 patients were evaluated (Supplemental Figure S2). A pooled sensitivity of 0.69 (95% CI, 0.55–0.80) from eight studies (n = 416) was compared using ddPCR versus five studies (n = 319) using qPCR (0.32; 95% CI, 0.19–0.48; P < 0.001) and three studies (n = 72) using NGS (0.96; 95% CI, 0.87–0.99; P = 0.008) (Figure 6). Five qPCR studies (n = 370), three ddPCR studies (n = 97), and one NGS study (n = 11) were used to calculate specificity. A pooled specificity of 0.98 (95% CI, 0.92–1.00) for ddPCR was compared versus qPCR (0.91; 95% CI, 0.80–0.96; P = 0.057) and NGS (1.00; 95% CI, 0.72–1.00; P = 0.589) (Figure 5).

Pooled quantitative PCR, digital droplet PCR, and next-generation sequencing sensitivity and specificity in studies of human papillomavirus–associated oropharyngeal cancer compared with cervical and anal cancer. ∗P < 0.05. ctHPVDNA, circulating tumor human papillomavirus DNA; ns, not significant.

For HPV + SCCA, seven studies including a total of 252 patients were evaluated (Supplemental Figure S3). A pooled sensitivity of 0.86 (95% CI, 0.75–0.92) from five studies (n = 172) was compared using ddPCR versus 0.91 (95% CI, 0.59–0.99) from two studies (n = 32) using NGS (P = 0.652) (Figure 5). Specificity regression was unavailable for HPV + SCCA studies because of the small sample size.

Finally, the pooled sensitivities and specificities of these assays were compared in the most common HPV-associated cancer, HPV + OPSCC (which has distinct histopathologic features), versus HPV-associated cervical and anal cancer (Supplemental Figures S4–S7). A pooled sensitivity of 0.66 (95% CI, 0.58–0.74) from six HPV + OPSCC qPCR studies (n = 278) was compared versus 0.32 (95% CI, 0.19–0.48) from five HPV-associated cervical and anal cancer qPCR studies (n = 319) (P < 0.001); a pooled sensitivity of 0.89 (95% CI, 0.78–0.94) from 10 HPV + OPSCC ddPCR studies (n = 460) was compared versus 0.77 (95% CI, 0.67–0.85) from 13 HPV-associated cervical and anal cancer ddPCR studies (n = 588) (P = 0.096); and a pooled sensitivity of 0.91 (95% CI, 0.81–0.96) from five HPV + OPSCC NGS studies (n = 74) was compared versus 0.93 (95% CI, 0.86–0.97) from five HPV-associated cervical and anal cancer studies (n = 104) (P = 0.645). Finally, a pooled sensitivity of 0.83 (95% CI, 0.75–0.89) from 21 HPV + OPSCC studies (n = 812) using qPCR, ddPCR, and NGS was compared versus a pooled sensitivity of 0.72 (95% CI, 0.60–0.81) from 23 HPV-associated anal and cervical cancer studies (n = 1011) using all three assays (P = 0.044) (Figure 6).

A pooled specificity of 0.94 (95% CI, 0.59–0.99) from five HPV + OPSCC qPCR studies (n = 268) was compared versus 0.91 (95% CI, 0.80–0.96) from five HPV-associated cervical and anal cancer qPCR studies (n = 370) (P = 0.710). A pooled specificity of 0.97 (95% CI, 0.94–0.99) from six HPV + OPSCC ddPCR studies (n = 253) was compared versus 0.98 (95% CI, 0.94–1.00) from four HPV-associated cervical and anal cancer ddPCR studies (n = 124) (P = 0.489). A pooled specificity of 0.97 (95% CI, 0.90–0.99) from three HPV + OPSCC NGS studies (n = 103) was compared versus 0.97 (95% CI, 0.81–1.00) from two HPV-associated cervical and anal cancer NGS studies (n = 32). Finally, a pooled specificity of 0.96 (95% CI, 0.86–0.99) from 14 HPV + OPSCC studies (n = 624) using qPCR, ddPCR, and NGS was compared versus a pooled specificity of 0.95 (95% CI, 0.90–0.98) from 11 HPV-associated anal and cervical cancer studies (n = 526) using all three assays (P = 0.738) (Figure 6).

Sensitivity and Specificity of Test According to Blood Compartment

The pooled sensitivities and specificities were assessed next based on whether the studies used plasma or serum samples (Supplemental Figures S8–S11) to evaluate the impact of the blood compartment on test performance. A pooled sensitivity of 0.65 (95% CI, 0.45–0.81) from eight serum qPCR, ddPCR, and NGS studies combined (n = 510) was compared versus 0.79 (95% CI, 0.70–0.86) from 27 plasma studies (n = 1240) using all three assays (P = 0.125). A pooled specificity of 0.97 (95% CI, 0.70–1.00) from six serum qPCR, ddPCR, and NGS studies combined (n = 348) was compared versus 0.95 (95% CI, 0.91–0.97) from 18 plasma studies (n = 861) using all three assays (P = 0.840).

Sensitivity and Specificity of Test According to Target

The pooled sensitivities and specificities were evaluated based on the targets of the three assays (Supplemental Figure S12). First, ddPCR studies, which had probes designed for a single E7 target gene, were analyzed and compared versus ddPCR studies with probes for both the E6 and E7 genes. A pooled sensitivity of 0.81 (95% CI, 0.69–0.89) from 11 studies (n = 690) was compared using E7 ddPCR probes versus 0.84 (95% CI, 0.67–0.93) from six studies (n = 284) that used both E6 and E7 ddPCR probes (P = 0.727). A pooled specificity of 0.98 (95% CI, 0.95–0.99) from six studies (n = 287) whose ddPCR assays targeted E7 was compared versus 0.97 (95% CI, 0.89–0.99) from three studies (n = 90) that used both E6 and E7 ddPCR probes (P = 0.732).

Next, NGS studies were evaluated based on whether they used an amplicon-based approach or hybrid capture (Supplemental Figure S13). A pooled sensitivity of 0.93 (95% CI, 0.86–0.96) from five NGS hybrid capture studies (n = 132) was compared versus 0.98 (95% CI, 0.87–1.00) from two NGS amplicon studies (n = 47) (P = 0.224). A pooled specificity of 0.96 (95% CI, 0.83–0.99) from three NGS hybrid capture studies (n = 159) was then compared versus 0.95 (95% CI, 0.79–0.99) from two NGS amplicon studies (n = 35) (P = 0.955). Of the seven NGS studies, five used assays that covered the full genome. One of the studies (by Hilke et al⁵⁴) only covered E7, and another study (Lee et al⁵⁸) only covered 40% of the genome, focusing on sublineage defining regions. It is notable that in the two amplicon-based studies, whole genome versus partial genome coverage did not have a difference in sensitivity, whereas in the hybrid capture studies, the one study that only covered the E7 region had a noticeably lower sensitivity (0.85) compared with the overall pooled sensitivity (0.93).

Discussion

Despite advances in early detection for HPV + CC, including Papanicolaou smears and direct HPV PCR testing, cervical cancer remains the fourth-leading cause of cancer death in women worldwide and is the leading cause of cancer death in women in low Human Development Index countries.77, 78, 79 For HPV + SCCA, there has been a dramatic increase in the incidence and mortality rates (nearly 3% per year), with roughly 10,000 new cases and >1600 deaths expected to be attributed to it in the United States in 2022.80, 81, 82 Globally, high- and middle-income countries have detected a 2% to 6% annual increase in the HPV + SCCA incidence over the last few decades.⁸³^,⁸⁴ Similarly concerning, and even more striking, the incidence of HPV + OPSCC has risen >200% over the past decades in the United States and is projected to continue climbing, despite HPV vaccination efforts.¹²^,¹⁵^,¹⁶^,⁸⁵^,⁸⁶

Blood-based biomarkers function as ideal, noninvasive modalities with strong diagnostic and monitoring potential for HPV-associated cancers. Accurate detection of ctHPVDNA can optimize many aspects of cancer management, from the prediagnostic setting to minimal residual disease detection after surgery and detection of recurrence. Because HPV-associated cancers remain a global health concern, and as the field of ctHPVDNA detection continues to evolve, it is critical to have a better understanding of the available ctHPVDNA detection approaches and how they perform both against each other and among differing anatomic subsites.

The current meta-analysis examined 36 studies to compare the sensitivities and specificities across qPCR, ddPCR, and NGS platforms in HPV + OPSCC, HPV + SCCA, and HPV + CC at the time of diagnosis. After pooling the sensitivities from 36 studies, NGS was the most sensitive platform across all cancer types, outperforming ddPCR, which similarly outperformed qPCR. Why NGS is the most sensitive approach for ctHPVDNA detection is likely multifaceted. First, current ddPCR and qPCR approaches are only able to detect a limited number of predefined targets. Considering that the HPV genome is approximately 8000 bp, targeting one or two approximately 160 bp fragments [the approximate size of cell-free DNA (cfDNA)] leaves about 99% of the genome untargeted. Thus, although NGS capture is less efficient than ddPCR, the significant increase in the number of targets overcomes this limitation while leading to improved sensitivity. Furthermore, although the majority of HPV + OPSCC, HPV + SCCA, and HPV + CC are caused by a limited number of high-risk HPV genotypes, approximately 5% of cases are caused by numerous other rare genotypes that are missed by ddPCR and qPCR approaches, further limiting sensitivity.87, 88, 89, 90 Lastly, ddPCR and qPCR approaches are subject to false-negative findings due to mutations in the single DNA fragment of interest, disrupting primer binding, a phenomenon we have seen in our laboratory in select cases.

Similarly, ddPCR was more sensitive than qPCR. The reason for the superiority of ddPCR over qPCR lies in its inherent technological design. ddPCR partitions each sample into thousands of individual oil/water emulsion droplets, each of which is then individually analyzed for the presence or absence of a fluorescent signal. A crucial element of ddPCR is its ability to quantify the absolute number of DNA copies in each sample, without relying on a standard curve.⁹¹ At low copy numbers, ddPCR affords greater sensitivity over qPCR because high-copy templates and background are diluted across the droplets, enhancing template concentration in HPV-positive partitions.

When comparing ctHPVDNA detection between anatomic sites, across all platforms, detection was improved in the oropharynx compared with the anus and cervix. There are a few reasons for the superiority of liquid biopsy in the oropharynx. First, and most critically, HPV specifically targets the palatine and lingual tonsils in the oropharynx, which contain branching tonsillar crypts. These crypts are lined by a highly specialized lymphoepithelium, known as the reticulated epithelium, which functions to transport foreign antigens from the surrounding environment of the oropharynx to the tonsillar lymphoid tissue. The porous nature of the basal cell layer of this epithelium permits the direct passage of lymphocytes and antigen-presenting cells. Although the disrupted reticular epithelium plays a large role in mucosal immune protection, these same gaps also enable direct exposure to viral particles such as HPV. In the cervix, HPV infection requires microtrauma, such as mechanical abrasion, of the epithelium with subsequent invasion of the virus through an exposed basement membrane; in the reticulated epithelium of the tonsil, however, the already porous epithelium exposes the basal cell layer and basement membrane to viral transgression without the need for mucosal disruption.⁸⁶^,92, 93, 94, 95 We hypothesize that just as the gaps in the basement membrane of the tonsil permit HPV infection and subsequent malignant transformation, they may provide a similar route for egress of ctHPVDNA from HPV + OPSCC, providing liquid biopsy assays with more ctDNA to detect compared with ctDNA from the cervix and anus.

Second, HPV + OPSCC is often detected with nodal metastases.⁸⁶ Part of the reason for the early nodal metastasis of HPV + OPSCC may also be a result of the microanatomy of the crypt epithelium, which enables the cancer to easily spread to regional lymph nodes. The discontinuous basement membrane permits both early transgression of the cancer as well as regional metastasis of occult cancers. The nodal disease seen at presentation in most HPV + OPSCC cases means there is more tumor burden at diagnosis, which in turn leads to more shedding of ctHPVDNA, enhancing the sensitivity of HPV + OPSCC liquid biopsy at presentation. Importantly, existing data have shown that lymph node burden correlates most strongly with ctDNA levels. In a study of 110 patients, Rettig et al⁹⁶ found that the few patients with undetectable ctHPVDNA predominantly had clinical stage N0 disease. This suggests that assays used at the time of diagnosis may have lower sensitivity among patients without regional lymph node metastasis. Because most patients with HPV + OPSCC initially present with cervical lymphadenopathy due to asymptomatic early disease, liquid biopsy assays will thus have increased sensitivity for these patients.

The fact that ctHPVDNA may be more easily detected in HPV + OPSCC than in HPV + CC or HPV + SCCA is further borne out when analyzing each HPV-associated cancer individually. For HPV + OPSCC, although ddPCR was more sensitive than qPCR, the difference between ddPCR and NGS was not statistically significant, indicating that marginal improvements in sensitivity from ddPCR to NGS may not be meaningful when ctHPVDNA is relatively plentiful. On the contrary, when examining HPV + CC, in which ctHPVDNA levels may be quantitatively lower at presentation due to both earlier cancer stage at presentation and less ctHPVDNA transgression into the circulation, NGS was more sensitive than ddPCR.97, 98, 99, 100 The power of a more sensitive diagnostic test is more important in HPV + CC because of this, whereas in HPV + OPSCC, the most sensitive technique is less critical, rendering the difference in sensitivity between NGS and ddPCR negligible.

The current study has a number of limitations that relate to the status of the existing literature as well as the inherent methodologic variation within the included studies. First, sample sizes of the available studies were small, with 13 of the 36 studies included in the analysis having a sample size of <50 patients. Second, there is significant heterogeneity of the molecular characteristics of each of these liquid biopsy assays, such as probe design, cfDNA input, and the thresholds for positive detection. Specifically for NGS, assays also differ markedly in their library design, preparation steps, depth of sequencing, and variation in downstream sequencing analysis. More broadly, variation of the cfDNA extraction process, volume of plasma extracted from, extraction kits and procedure, and the volume and concentration of cfDNA added to the assay are factors that all affect assay performance. Controlling for all of these variables in a meta-analysis would not be possible. Reassuringly, variation in cfDNA extraction is likely negligible compared with other factors, both biological and technical. An additional limitation of this meta-analysis is that the data output (HPV reads) is not normalized between studies, and how this value is calculated varies from assay to assay. The sensitivity and specificities were not evaluated across the different assays and anatomic sites by stage, which could affect our hypothesis that liquid biopsies targeting ctHPVDNA from the oropharynx have higher sensitivity due to late-stage disease presentation with increased N-stage and associated tumor burden. Lastly, because of the more recent emergence of NGS, there were fewer NGS studies for evaluation.

In summary, using a systematic review and meta-analysis, we found that detection platform, anatomic site of the cancer, and blood component used for cfDNA extraction affect ctHPVDNA detection and must be considered when interpreting ctHPVDNA test results. Currently, plasma NGS-based testing should be considered the most sensitive approach for ctHPVDNA detection overall, whereas specificity is excellent regardless of platform used.

Disclosure Statement

D.L.F. has received research funding from Bristol Myers Squibb and Calico, and in-kind funding from BostonGene; holds equity in Illumina; and receives consulting fees from Merck, Noetic, Chrysalis Biomedical Advisors, and Focus.

Footnotes

Supported by the NIH (R21 1R21CA267152, R03DE030550, and K23DE029811) and Calico (salary support to D.L.F.).

Supplemental material for this article can be found at http://doi.org/10.1016/j.jmoldx.2023.11.007.

Supplemental Data

Supplemental Figure S1

Sensitivity (A) and specificity (B) from studies used in the meta-analysis comparing the three assays in human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma. CI, confidence interval; ddPCR, digital droplet PCR; NGS, next-generation sequencing; qPCR, quantitative PCR.

mmc1.pdf^{(142.6KB, pdf)}

Supplemental Figure S2

Sensitivity (A) and specificity (B) from studies used in the meta-analysis comparing the three assays in human papillomavirus (HPV)-associated cervical cancer. CI, confidence interval; ddPCR, digital droplet PCR; NGS, next-generation sequencing; qPCR, quantitative PCR.

mmc2.pdf^{(118.2KB, pdf)}

Supplemental Figure S3

Sensitivity (A) and specificity (B) from studies used in the meta-analysis comparing the three assays in human papillomavirus (HPV)-associated squamous cell carcinoma of the anus. CI, confidence interval; ddPCR, digital droplet PCR; NGS, next-generation sequencing.

mmc3.pdf^{(69.1KB, pdf)}

Supplemental Figure S4

Sensitivity (A) and specificity (B) from human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma quantitative PCR (qPCR) studies compared with HPV-associated cervical cancer and HPV-associated squamous cell carcinoma of the anus qPCR studies. CI, confidence interval.

mmc4.pdf^{(110.2KB, pdf)}

Supplemental Figure S5

Sensitivity (A) and specificity (B) from human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma digital droplet PCR (ddPCR) studies compared with HPV-associated cervical cancer and HPV-associated squamous cell carcinoma of the anus ddPCR studies. CI, confidence interval.

mmc5.pdf^{(135KB, pdf)}

Supplemental Figure S6

Sensitivity (A) and specificity (B) from human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma next-generation sequencing (NGS) studies compared with HPV-associated cervical cancer and HPV-associated squamous cell carcinoma of the anus NGS studies. CI, confidence interval.

mmc6.pdf^{(92.8KB, pdf)}

Supplemental Figure S7

Sensitivity (A) and specificity (B) from human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma quantitative PCR, digital droplet PCR, and next-generation sequencing studies compared with HPV-associated cervical cancer and HPV-associated squamous cell carcinoma of the anus quantitative PCR, digital droplet PCR, and next-generation sequencing studies.

mmc7.pdf^{(213.2KB, pdf)}

Supplemental Figure S8

Sensitivity (A) and specificity (B) from quantitative PCR (qPCR) studies using serum compared with qPCR studies using plasma. A pooled sensitivity of 0.43 [95% confidence interval (CI), 0.20–0.70] from three serum qPCR studies (n = 233) was compared versus 0.54 (95% CI, 0.37–0.70) from eight plasma qPCR studies (n = 364) (P = 0.540). A pooled specificity of 0.95 (95% CI, 0.27–1.00) from three qPCR studies (n = 251) using serum was compared versus 0.91 (95% CI, 0.83–0.96) from seven qPCR studies (n = 387) using plasma (P = 0.493). HPV, human papillomavirus.

mmc8.pdf^{(111.6KB, pdf)}

Supplemental Figure S9

Sensitivity (A) and specificity (B) from digital droplet PCR (ddPCR) studies using serum compared with ddPCR studies using plasma and serum or plasma alone. A pooled sensitivity of 0.77 [95% confidence interval (CI), 0.51–0.92] from five serum ddPCR studies (n = 277) was compared versus 0.79 (95% CI, 0.54–0.92) from two ddPCR studies (n = 88) that used both plasma and serum samples (P = 0.845). A pooled sensitivity of 0.84 (95% CI, 0.75–0.90) from 13 ddPCR studies (n = 702) using plasma was then compared versus the ddPCR studies using both plasma and serum (P = 0.674). A pooled specificity of 0.98 (95% CI, 0.92–1.00) from three ddPCR studies using serum (n = 97) was compared versus 0.97 (95% CI, 0.94–0.99) from six ddPCR studies (n = 280) using plasma (P = 0.555). HPV, human papillomavirus.

mmc9.pdf^{(131.6KB, pdf)}

Supplemental Figure S10

Sensitivity (A) and specificity (B) from next-generation sequencing (NGS) studies using serum compared with NGS studies using plasma and serum. A pooled sensitivity of 0.94 [95% confidence interval (CI), 0.88–0.97) from six NGS studies (n = 174) using plasma was compared versus 1.00 (95% CI, 0.48–1.00) from one NGS study (n = 5) using both plasma and serum (P = 0.832). Specificity regression was unavailable for the NGS studies because of small sample size. HPV, human papillomavirus.

mmc10.pdf^{(73.7KB, pdf)}

Supplemental Figure S11

Sensitivity (A) and specificity (B) from quantitative PCR, digital droplet PCR, and next-generation sequencing studies overall using serum compared versus quantitative PCR, digital droplet PCR, and next-generation sequencing studies overall using plasma and serum or plasma alone. CI, confidence interval; HPV, human papillomavirus.

mmc11.pdf^{(200.2KB, pdf)}

Supplemental Figure S12

Sensitivity (A) and specificity (B) from digital droplet PCR (ddPCR) studies using probes for E7 target gene compared with ddPCR studies using probes for both E6 and E7 genes. CI, confidence interval; HPV, human papillomavirus.

mmc12.pdf^{(119KB, pdf)}

Supplemental Figure S13

Sensitivity (A) and specificity (B) from next-generation sequencing (NGS) studies using an amplicon-based approach compared with NGS studies using a hybrid capture-based approach. CI, confidence interval; HPV, human papillomavirus.

mmc13.pdf^{(85KB, pdf)}

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Supplementary Materials

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PERMALINK

Comparing the Diagnostic Performance of Quantitative PCR, Digital Droplet PCR, and Next-Generation Sequencing Liquid Biopsies for Human Papillomavirus–Associated Cancers

Saskia Naegele

Daniel A Ruiz-Torres

Yan Zhao

Deborah Goss

Daniel L Faden

Abstract

Materials and Methods

Literature Search

Figure 1.

Study Selection

Figure 2.

Results

Sensitivity and Specificity of ctHPVDNA Detection by Test at the Time of Diagnosis

Table 1.

Figure 3.

Figure 4.

Sensitivity and Specificity of ctHPVDNA Detection Test According to Anatomic Subsite

Figure 5.

Figure 6.

Sensitivity and Specificity of Test According to Blood Compartment

Sensitivity and Specificity of Test According to Target

Discussion

Disclosure Statement

Footnotes

Supplemental Data

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Cite

Add to Collections

PERMALINK

Comparing the Diagnostic Performance of Quantitative PCR, Digital Droplet PCR, and Next-Generation Sequencing Liquid Biopsies for Human Papillomavirus–Associated Cancers

Saskia Naegele

Daniel A Ruiz-Torres

Yan Zhao

Deborah Goss

Daniel L Faden

Abstract

Materials and Methods

Literature Search

Figure 1.

Study Selection

Figure 2.

Results

Sensitivity and Specificity of ctHPVDNA Detection by Test at the Time of Diagnosis

Table 1.

Figure 3.

Figure 4.

Sensitivity and Specificity of ctHPVDNA Detection Test According to Anatomic Subsite

Figure 5.

Figure 6.

Sensitivity and Specificity of Test According to Blood Compartment

Sensitivity and Specificity of Test According to Target

Discussion

Disclosure Statement

Footnotes

Supplemental Data

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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