Abstract 680: HPV serology and circulating viral DNA for detection, genotyping, and measurement of disease burden in oropharyngeal cancer
Bibliographic record
Abstract
Abstract Introduction: The incidence of human papillomavirus-positive (HPV+) oropharyngeal cancer (OPC) has increased rapidly, and HPV early antigen serology has been proposed as a scalable and cost-effective early detection test. HPV seropositivity can precede clinical presentation of OPC by several years, so additional surveillance procedures may be necessary to optimize early cancer detection. The potential for HPV circulating tumor DNA (ctDNA) to confirm a diagnosis of OPC in seropositive individuals is poorly understood. Here, we assess the relationship between HPV serology and HPV ctDNA with disease burden in a large cohort of HPV+ OPC. Methods: We analyzed pre-treatment peripheral blood plasma from 262 patients with non-metastatic p16+ OPC treated with definitive (chemo)radiotherapy. A multiplex ELISA was used for serologic evidence of HPV proteins from 10 HPV genotypes, quantified by mean fluorescence intensity (MFI). Plasma HPV ctDNA was quantified by whole viral genome sequencing utilizing a custom HPV-targeted capture panel for 38 HPV genotypes. Gross tumor volume (GTV) was obtained from the sum of all target contours on computed tomography scans. Results: Both assays identified HPV16 as the most prevalent genotype (84%), with results indicating a total of 4 and 6 HPV genotypes for serology and HPV ctDNA, respectively. HPV ctDNA results demonstrated higher sensitivity and lower cross-reactivity between HPV types compared with HPV serology results. Furthermore, HPV ctDNA but not HPV16 E6 antibody levels were positively associated with disease burden as determined by N-category (Table 1) and tumor volume (ctDNA vs GTV, r=0.48 p=6.4e-13; E6 vs GTV, r= -0.079 p=0.26). Conclusion: This is the largest cohort to compare HPV serology and ctDNA results in OPC. These findings highlight the potential for ctDNA to augment future strategies for blood-based early detection of HPV+ OPC. Citation Format: Lucas Penny, Eric Y. Stutheit-Zhao, Birgitta E. Michels, Fabian Rosing, Jinfeng Zou, Zhen Zhao, Yangqiao Zheng, Shao Hui Huang, Johnny Carlton, Andrew McPartlin, John R. de Almeida, David Goldstein, Andrew Hope, Ali Hosni, John Kim, Fei-Fei Liu, C Jillian Tsai, John N. Waldron, Anna Spreafico, Enrique Sanz Garcia, Lillian L. Siu, Tim Waterboer, Geoffrey Liu, Scott V. Bratmn. HPV serology and circulating viral DNA for detection, genotyping, and measurement of disease burden in oropharyngeal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 680.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".