Current status of circulating tumor DNA and circulating cell alterations in HPV-associated head and neck cancer
Bibliographic record
Abstract
Head and neck cancer (HNC) is the sixth most prevalent cancer worldwide with a poor prognosis when diagnosed at advanced clinical stages. The main risk factors are tobacco consumption and alcohol abuse. However, the incidence of oropharyngeal cancer (OPC) is increasing due to human papillomavirus (HPV) infection. Current diagnostic techniques for both HPV-positive and HPV-negative HNC often involve invasive, costly, and time intensive procedures. Alternatively, liquid biopsies have emerged as a minimally invasive technique which may lessen the burden of cancer diagnoses on both patients and healthcare resources. This technique analyzes biological components released by tumors into the bloodstream, such as circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, tumor proteins, and methylation changes, allowing for specific cancer detection and surveillance. This article reviewed the status and clinical applications of ctDNA and CTCs in the diagnosis and treatment of HPV-positive HNC. In addition, a systematic review following PRISMA 2020 Checklist (PROSPERO ID: 560498) was conducted to investigate whether liquid biopsies could be leveraged to assess the role of the immune system on treatment outcomes and the overall survival of HNC patients. Two public databases (Medline and Embase) were searched using relevant MeSH (Medical Subject Headings) terms and keywords. After multiple rounds of screening, eight studies published between 2017 and 2024 involving 814 cancer patients from three different countries were retained for data extraction. The data demonstrated that the immune microenvironment of HNC patients could be characterized via liquid biopsy, however, future validation is required. Furthermore, through the detection of HPV ctDNA, liquid biopsy technology has shown promise in diagnostics, as a predictor of patient prognoses and treatment responses, and as a tool to monitor disease progression in HPV-positive HNC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".