Blood and saliva‐derived <scp>ctDNA</scp> is a marker of residual disease after treatment and correlates with recurrence in human papillomavirus‐associated head and neck cancer
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: There is an alarming increase in human papillomavirus-associated head and neck cancer (HNC), reaching epidemic levels. While patient prognosis is generally good, off-target treatment effects are associated with decreased quality of life. Thus, non-invasive strategies to predict treatment response and risk of recurrence could help de-escalate treatment. In this study, we tested circulating tumor (ct)DNA in liquid biopsies (blood/saliva) of HPV-positive HNC patients to assess treatment response and disease progression. METHODS: A total of 235 blood and saliva samples were collected from 60 HPV-positive and 17 HPV-negative HNC patients (control group) before and/or after treatment. Samples were analyzed using ddPCR for HPV16/18/31/33/35/45 and correlated with imaging and pathological examination. RESULTS: p < 0.00001), with high concordance between saliva and blood (93%). In matched samples, all patients positive for ctDNA before treatment showed significant reductions in ctDNA levels post treatment (p < 0.0001). All but one patient with persistent ctDNA after treatment showed residual tumor and subsequent recurrence. Finally, fragmentomic analysis revealed shifts in cell-free DNA fragment size after treatment, suggesting a complementary biomarker for treatment response. CONCLUSIONS: Blood and saliva were found to be good sources of HPV-ctDNA. The presence of ctDNA strongly correlated with treatment response, demonstrating clinical utility as a non-invasive biomarker to monitor tumor progression in HPV-positive HNC. Liquid biopsy based ctDNA testing could be an effective approach to predict recurrence and stratify patients for de-escalation of treatment, thereby improving quality of life.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it