The promise and translation of cell-free human papillomavirus DNA testing for cervical cancer surveillance

Clinical tests to monitor disease responses provide critical tools for optimizing treatment for individual patients. Blood is an ideal specimen type for this endeavor because it can be easily and repeatedly collected and processed to monitor the disease. Cell-free DNA (cfDNA) circulating in the blood is becoming an increasingly promising biomarker for the measurement of small amounts of specific DNA sequences. cfDNA is released from cells into the bloodstream through a variety of mechanisms, including cell death processes and the release of extracellular vesicles (1). Although serum has higher levels of cfDNA, plasma is the preferred specimen type because cfDNA in plasma is less diluted by cfDNA arising from leukocyte lysis during serum processing (2). Inclusion of a cocktail of ingredients to stabilize cells and inhibit nucleases in the cfDNA blood collection tubes (BCTs) has been shown to maintain stable cfDNA levels for 3 to 14 days at room temperature prior to processing (3). Because circulating cfDNA originates from multiple cell types, the accuracy of cfDNA measurement in cancer patients must include a method to differentiate circulating tumor DNA (ctDNA) within the cfDNA pool. Distinguishing ctDNA from the remaining cfDNA pool is accomplished by identifying DNA mutations in the tumor and detecting the same mutation in ctDNA (2). This important step is not required for the detection of high-risk human papillomavirus (HR-HPV) DNA because viral DNA can be readily distinguished from human DNA.

Cervical cancer is an HR-HPV-related cancer that recurs after primary treatment (surgery or radiotherapy with or without chemotherapy) at a rate of 10% for early-stage cancers and 40% for local regionally advanced cancer and up to 70% for stage IVB (4,5). A meta-analysis of studies evaluating cell-free HR-HPV (cfHR-HPV) DNA in patients with cervical cancer indicated a significant association between the detection of cfHR-HPV DNA at the end of treatment and worse progression-free survival (6). One conclusion of this study is that prospective studies with larger numbers of specimens are needed to validate and translate cfHR-HPV DNA for clinical use. A recent study by Sivars et al. (7) evaluated a total of 418 blood samples from 66 patients with cervical cancer, representing the largest number of follow-up samples in a single study to-date. Their method and results provide a framework for translating cfHR-HPV DNA detection into clinical trials and patient care.

In the past few decades, several methods have been developed for detecting cfHR-HPV DNA (8). In all cases, the methods detect the HPV early 6 (E6) or early 7 (E7) genes, which are known to drive carcinogenesis and maintain cancer cell viability (9). Initial studies used polymerase chain reaction (PCR) and quantitative PCR (qPCR) to detect either HPV16 or HPV18 DNA in serum and saliva samples (8,10). Although these methods can detect cfHR-HPV DNA, the detection rates among studies are highly variable, ranging from 20% to 30% of cfHR-HPV DNA within patient cohorts (11,12). Droplet digital PCR (ddPCR) is a sensitive method that has also been used to determine the cfHR-HPV DNA status. This approach had a higher level of specificity, with studies ranging from 60% to 90% rates of detection for cfHR-HPV DNA in patients with HPV-positive tumors (13). Recently, next-generation sequencing (NGS) has been used to detect cfHR-HPV DNA. This is the most sensitive method available and can detect up to 100% cfHR-HPV DNA in the plasma of patients with International Federation of Gynecology and Obstetrics (FIGO) stage IVB cervical cancer (14). NGS, like ddPCR, can simultaneously detect a variety of HR-HPV subtypes with high specificity. The drawback of this method, at least clinically, is the cost and training associated with the NGS technique. Among the methods discussed, ddPCR has a high level of sensitivity and cost comparable to that of standard qPCR.

The methodological approach developed in Sivars et al. involves a series of HPV-type-specific ddPCR assays to detect cfHR-HPV DNA in plasma samples collected in cfDNA BCTs. The E7 gene was targeted to HPV16, HPV18, HPV45, HPV31, HPV33, HPV35, HPV39, HPV51, HPV52, HPV56, HPV58, HPV59, and HPV66. As a control, total cell-free albumin DNA (cfALB) was used to determine the total cfDNA load and to normalize the expression between samples. The plasmids and reference genomes for each HPV subtype were obtained from the International HPV Reference Center, an international repository of novel HPV subtypes. When tested, all HPV subtypes were determined to be within the range of detection of serum samples using the ddPCR QX Manager analysis system. All samples were run in triplicate, and only the HPV type detected in the patient’s tumor was analyzed in the same patient’s serum. Plasma from blood donors was processed simultaneously with the HPV patient cohort to act as a negative control and to determine the effectiveness of the assay. Non-template controls and nuclease-free water were used as blank controls. For all samples, a minimum of three molecules per sample were required to determine HPV positivity, except for HPV 31 and HPV58 where 5.4 and 6.0 molecules were required, respectively. cfHR-HPV DNA was detected in 49 of 54 (92.4%) blood specimens from patients who had an HR-HPV-positive tumor biopsy. This is the highest detection rate of any other ddPCR study, and is also higher than that of a similar study using NGS (14). NGS analysis detected the same 13 HPV subtypes. However, the study by Sivars et al. is the first to develop a method using ddPCR, which could potentially be deployed more easily in a clinical setting.

Although the detection of cfHR-HPV DNA to determine patient outcomes has been studied for decades, the development of techniques to determine patient outcomes stratified according to HPV subtype is relatively nascent. There are two primary HR-HPV subtypes that lead to the development of nearly 70–80% of all cervical cancers: HPV16 and HPV18 (15,16). Most studies have primarily focused on these two HR-HPV subtypes because of their abundance. The third most common subtype, HPV45, accounts for ~12% of HR-HPV-positive cases, meaning that the remaining ~10% is shared between HPV31, HPV33, HPV35, HPV39, HPV51, HPV52, HPV56, HPV58, HPV59, and HPV66 (15). Studies that develop techniques for these rare HPV subtypes will provide a framework for determining the differences in patient outcomes and tumor characteristics between patients. Future studies will require coordination between multiple institutions to study the thousands of patients needed to have sufficient samples harboring the rare HR-HPV subtypes. Ultimately, such a study may lead to a more personalized approach to the treatment of patients with cervical cancer.

To be clinically useful, an assay’s predictive value should meet standards that justify altering a patient’s treatment based on the test results. A benefit of the Sivars et al. study is that it reports the negative- and positive-predictive values (NPVs and PPVs, respectively) for early detection of relapse for the 6 collection time points before, during, and after treatment of the patients with individualized care. The NPVs and PPVs were similar for specimens collected throughout the treatment and increased for specimens collected at the end of treatment and during follow-up. The PPVs were 57% at the end of treatment, 86% during early follow-up, and 88% at tumor evaluation. A subsequent study by Seo et al. reported that lack of detection of cfHR-HPV DNA using a similar ddPCR method predicted recurrence-free survival with a concordance index (CI) score of 0.83, which increased to 0.88 when combined with magnetic resonance imaging (17).

The interpretation of PPV or CI of cfHR-HPV DNA assays depends on the intended use, which could include use as a biomarker for detecting residual disease, monitoring response to therapy, and predicting recurrence. If the future is to use cfHR-HPV DNA at the conclusion of therapy to direct additional adjuvant chemotherapy or declare a treatment failure, high PPV or CI is critical. A positive result should accurately indicate the presence of remaining tumor cells. If cfHR-HPV DNA is used for surveillance to predict recurrence, its clinical utility may allow a lower PPV or CI, even with high sensitivity and specificity, due to the low prevalence of recurrence in treated patients. For instance, based on the positive results of the KEYNOTE-826 trial (18), the anti-programmed death-1 (PD-1) monoclonal antibody pembrolizumab was approved by the US Food and Drug Administration for second-line treatment of patients with metastatic cervical cancer after progression on platinum-based chemotherapy. To be eligible, the patient’s tumor needs to express programmed death-ligand 1 (PD-L1). However, there is a need for new knowledge and guidance to optimize how long the patients should be treated with adjuvant pembrolizumab (19).

The cfHR-HPV DNA assays reported by Sivars et al. (7) and Seo et al. (17) represent candidate assays for optimizing pembrolizumab scheduling in this patient population. cfHR-HPV DNA could be evaluated by ddPCR in plasma specimens prospectively collected in cfDNA BCTs and compared or combined with standard of care PET scanning for predicting tumor recurrence. The potential risks to keep in mind include avoiding false positives from the presence of benign HPV or concurrent HPV infections, which might lower specificity and consequently, PPV.

The phase III trial EMPOWER-Cervical-1/GOG-3061/ENGOT-cx9 compared the anti-PD-1 antibody cemiplimab against investigators’ choice in all cervical cancer patients regardless of the PD-L1 status of their tumors (20). The safety of cemiplimab and positive results regardless of tumoral PD-L1 status in this trial led to its approval for patients who are immune-naïve in Canada and Europe (21). The study by Seo et al., found that patients treated with a therapeutic HPV vaccine (PDS0101; IMMUNOCERV) had a higher rate of undetectable cfHR-HPV DNA than patients treated with standard-of-care chemoradiation (17). This result demonstrates the usefulness of cfHR-HPV DNA as a surrogate marker of response to treatment and sets the stage for its usefulness in clinical trials and in predicting patient survival. Clinical trials are needed to demonstrate whether this surrogate marker is reliable enough to change individual patient management, such as discontinuing chemotherapy or immune therapy. Altering treatment when the cfHR-HPV DNA level is increasing is also a foreseeable usefulness.

Another potential utility of cfHR-HPV DNA is that it could be used to allow patients with cervical cancer to be treated with surgery alone, to avoid adjuvant chemotherapy and radiation. Many patients with a 10% to 20% risk of recurrence may be given adjuvant radiation, because it is not known which of 100 patients are the most likely to have their cancer recur. Thus, 100 patients are treated to help 20. If cfHR-HPV DNA detection can distinguish high- and low-risk, treatment could be de-escalated for those with undetectable cfHR-HPV DNA. If a clinical trial documents that cfHR-HPV DNA measured preoperatively and 3 months post-treatment is sufficiently accurate, there is potential for withholding additional treatment in intermediate-risk patients. This would avoid toxicity, expenses and a reduced quality of life after surgery.

In summary, the ddPCR method-based detection of 13 HR-HPV subtypes in plasma specimens from patients with cervical cancer reported by Sivars et al. and Seo et al. supports utilization of this technology in clinical trials. The inclusion of multiple HR-HPV subtypes in the assay provides an opportunity to learn more about the clinical aspects of individual subtypes and to develop personalized treatment and monitoring strategies for individual patients. The 92.4% rate for detecting cfHR-HPV offers the most promise among all technologies reported to date. The 57% PPV at the end of treatment needs to be improved to use this assay for direct adjuvant therapy or to declare treatment failure. However, the 88% PPV and the 0.83 CI score for post-treatment cfHR-HPV DNA detection to diagnose recurrence offer promise for using this assay to monitor treatment and guide personalized care.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Translational Cancer Research. The article has undergone external peer review.

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-250/prf

Funding: Research reported in this publication was supported in part by the National Cancer Institute Cancer Center Support Grant P30CA225520 awarded to the University of Oklahoma Stephenson Cancer Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-250/coif). J.G. and D.M.B. report provisional patent P2024-016-001—5834.186 Methods for Inhibiting or Treating Human Papillomavirus (HPV)-Induced Dysplasias, Warts, and Cancer in HPV-Infected Subjects Filed 10-16-2023. K.N.M reports grants or contracts from PTC Therapeutics, Lilly, Clovis, Genentech, GSK and Verastem; consulting fees and service on data and safety monitoring boards or advisory boards from Astra Zeneca, Aravive, Aadi, Blueprint pharma, BioNTech, Caris, Duality, Eisai, GSK, Daiichi, Genentech/Roche, Immunogen, Iovance, Janssen, Lilly, Mersana, Merck, Myriad, Norvartis, Novocure, Pharma&, VBL Therapeutics, Verastem, Zentalis, Schrodinger, Regeneron and Takeda; honoraria from Astra Zeneca, GSK, Immunogen, PRIME, RTP, Medscape, Great Debates and Updates; support for attending meetings from Astra Zeneca, and BioNTech; and Leadership or fiduciary role as a Gynecologic Oncology Partners Associate Director. The other author has no conflicts of interest to declare.

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References

1. Grabuschnig S, Bronkhorst AJ, Holdenrieder S, et al. Putative Origins of Cell-Free DNA in Humans: A Review of Active and Passive Nucleic Acid Release Mechanisms. Int J Mol Sci 2020;21:8062. [Crossref] [PubMed]
2. Merker JD, Oxnard GR, Compton C, et al. Circulating Tumor DNA Analysis in Patients With Cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review. J Clin Oncol 2018;36:1631-41. [Crossref] [PubMed]
3. Diaz IM, Nocon A, Held SAE, et al. Pre-Analytical Evaluation of Streck Cell-Free DNA Blood Collection Tubes for Liquid Profiling in Oncology. Diagnostics (Basel) 2023;13:1288. [Crossref] [PubMed]
4. Quinn MA, Benedet JL, Odicino F, et al. Carcinoma of the Cervix Uteri. Int J Gynaecol Obstet 2006;95:S43-S103. [Crossref]
5. Friedlander M, Grogan M; US.. Guidelines for the treatment of recurrent and metastatic cervical cancer. Oncologist 2002;7:342-7. [Crossref] [PubMed]
6. Wang ZY, Li R, Li RZ, et al. Prognostic value of human papillomavirus cell-free DNA in cervical cancer patients: A systematic review and meta-analysis. Eur J Obstet Gynecol Reprod Biol 2024;300:211-8. [Crossref] [PubMed]
7. Sivars L, Jylhä C, Crona Guterstam Y, et al. Cell-Free Human Papillomavirus DNA Is a Sensitive Biomarker for Prognosis and for Early Detection of Relapse in Locally Advanced Cervical Cancer. Clin Cancer Res 2024;30:2764-71. [Crossref] [PubMed]
8. Liu VW, Tsang P, Yip A, et al. Low incidence of HPV DNA in sera of pretreatment cervical cancer patients. Gynecol Oncol 2001;82:269-72. [Crossref] [PubMed]
9. Vats A, Trejo-Cerro O, Thomas M, et al. Human papillomavirus E6 and E7: What remains? Tumour Virus Res 2021;11:200213. [Crossref] [PubMed]
10. Wang Y, Springer S, Mulvey CL, et al. Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas. Sci Transl Med 2015;7:293ra104. [Crossref] [PubMed]
11. Dong SM, Pai SI, Rha SH, et al. Detection and quantitation of human papillomavirus DNA in the plasma of patients with cervical carcinoma. Cancer Epidemiol Biomarkers Prev 2002;11:3-6. [PubMed]
12. Chatfield-Reed K, Roche VP, Pan Q. cfDNA detection for HPV+ squamous cell carcinomas. Oral Oncol 2021;115:104958. [Crossref] [PubMed]
13. Cheung TH, Yim SF, Yu MY, et al. Liquid biopsy of HPV DNA in cervical cancer. J Clin Virol 2019;114:32-6. [Crossref] [PubMed]
14. Mittelstadt S, Kelemen O, Admard J, et al. Detection of circulating cell-free HPV DNA of 13 HPV types for patients with cervical cancer as potential biomarker to monitor therapy response and to detect relapse. Br J Cancer 2023;128:2097-103. [Crossref] [PubMed]
15. Pirog EC, Lloveras B, Molijn A, et al. HPV prevalence and genotypes in different histological subtypes of cervical adenocarcinoma, a worldwide analysis of 760 cases. Mod Pathol 2014;27:1559-67. [Crossref] [PubMed]
16. Zampronha Rde A, Freitas-Junior R, Murta EF, et al. Human papillomavirus types 16 and 18 and the prognosis of patients with stage I cervical cancer. Clinics (Sao Paulo) 2013;68:809-14. [Crossref] [PubMed]
17. Seo A, Xiao W, Gjyshi O, et al. Human Papilloma Virus Circulating Cell-Free DNA Kinetics in Patients with Cervical Cancer Undergoing Definitive Chemoradiation. Clin Cancer Res 2025;31:697-706. [Crossref] [PubMed]
18. Colombo N, Dubot C, Lorusso D, et al. Pembrolizumab for Persistent, Recurrent, or Metastatic Cervical Cancer. N Engl J Med 2021;385:1856-67. [Crossref] [PubMed]
19. Wolf J, Xu Y. Immune checkpoint inhibitor therapy in advanced cervical cancer: Deepened response with prolonged treatment and repeat response to re-initiation of therapy. Gynecol Oncol Rep 2023;48:101244. [Crossref] [PubMed]
20. Tewari KS, Monk BJ, Vergote I, et al. Survival with Cemiplimab in Recurrent Cervical Cancer. N Engl J Med 2022;386:544-55. [Crossref] [PubMed]
21. Grau-Bejar JF, Garcia-Duran C, Garcia-Illescas D, et al. Advances in immunotherapy for cervical cancer. Ther Adv Med Oncol 2023;15:17588359231163836. [Crossref] [PubMed]