Role of circulating tumor DNA and cell-free DNA biomarkers in diagnosis and prognosis of oral cancer - a systematic review
Bibliographic record
Abstract
BACKGROUND: Oral squamous cell carcinoma is the most common malignant neoplasm of the oral cavity, contributing significantly to cancer-related mortality worldwide. Circulating tumor DNA could be a promising biomarker for the early diagnosis and prognosis of oral cancer. OBJECTIVE: The aim of this systematic review was to consolidate the existing literature on the role of circulating tumor DNA (ctDNA) and cell-free DNA (cfDNA) in the diagnosis and prognosis of oral cancer. METHODOLOGY: The review protocol followed PRISMA guidelines. A systematic search was conducted across PubMed, Web of Science, Google Scholar and SCOPUS. Only English-language studies were included, while narrative reviews, HPV-positive OSCC, systematic reviews, meta-analyses, abstracts, and letters to the editor were excluded. Data were extracted on study design, country, sample size, participant characteristics, assessment methods, type of oral cancer and measured outcomes. Risk of bias was evaluated using Newcastle-Ottawa Scale (NOS). RESULTS: A total of 3,155 records were identified, out of which 17 studies met the inclusion criteria. These comprised eleven cohort studies, one was a case series, two were descriptive studies, and three were case-control studies. The studies primarily addressed oral squamous cell carcinoma (OSCC) and head and neck squamous cell carcinoma (HNSCC). Findings revealed that elevated cfDNA levels are associated with poor prognosis, lymph node metastasis, larger tumor size and advanced disease stages. ctDNA acts as a predictive tool for monitoring cancer progression, treatment response, recurrence risk, and overall survival. Among 12 studies evaluated using NOS, 8 were of good quality, while 4 were fair quality. CONCLUSION: ctDNA and cfDNA exhibit promising prognostic and diagnostic potential for OSCC and HNSCC. Elevated cfDNA levels correlate with poor prognosis, while ctDNA shows potential for monitoring cancer progression and treatment response.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".