PORTO-001 study: Changes in the oral microbiome and matrix metalloproteinases in patients with oropharyngeal squamous cell carcinoma undergoing definitive chemoradiotherapy.
Bibliographic record
Abstract
e18034 Background: Head and neck cancer patients treated with concurrent chemoradiotherapy (CRT) develop oral mucositis, with varying severity. However, knowledge about risk factors, biomarkers, treatment, and prognosis of oral mucositis is still limited. Methods: We designed an exploratory study to examine the changes in the oral microbiome and salivary and plasma levels of matrix metalloproteinases (MMP) in patients with locoregionally advanced oropharyngeal squamous cell carcinoma (OPSCC) undergoing definitive CRT. Patients were followed from screening to week 7 of treatment with CRT, which consisted of 70 Gy/35 fractions of radiation with cisplatin given at 100 mg/m2 q3weeks or weekly 40 mg/m2. Clinical and demographic data were collected at specified timepoints. Samples were collected at screening and on week 4 of treatment with CRT. A tumor swab was collected for microbiome analysis. Blood and saliva samples were collected for measurements of 7 MMPs and 26 other cytokines. The study population was summarized descriptively. The change in the cytokines and the α-diversity of microbiome data (week 4 vs screening) were examined using Wilcoxon signed rank test. Results: A total of 11 patients were included. Nine (82%) were male. 5 patients (45%) were stage III, and there were 2 patients (18%) for each of stages I, II, and IV. A history of smoking was present in 5 (45.4%) patients. p16 was positive in 9 (81.8%) patients. There was a median weight loss of 7.0% (5.1 kg) between screening and week 7 visits. Almost half (45%) of patients developed grade 2 oral mucositis. All patients developed radiation dermatitis, with most cases ranging between grades 2 and 3. There were no statistically significant changes in the salivary levels of cytokines. However, 1 patient developed clinical oral mucositis before all the other patients, at week 1, and this was associated with an upsurge in the salivary levels of IFN-γ, IL-6, TNF-α, MMP-1, MMP-2 and MMP-7. For all patients, there were statistically significant changes (median (95% confidence interval)) in the blood plasma levels of IP-10 (-0.1 fluorescence intensity (FI) (-0.3, -0.04), p = 0.01), MIP-1ß (0.2 FI (0.07, 0.5), p = 0.02), SDF-1α (1.4 pg/ml (0.07, 3.7), p = 0.02), MMP-1 (-0.4 pg/ml (-0.5, -0.09), p = 0.01), MMP-3 (0.4 pg/ml (0.03, 0.5), p = 0.02), and MMP-8 (-0.2 FI (-0.3, -0.02), p = 0.04). There was a 29.1% ((-3.0%, -32.8%), p = 0.005) reduction in α-diversity of microbiome at week 4 from screening. Conclusions: In this small series of patients diagnosed with OPSCC, there was a change in the plasma levels of IP-10, MIP-1ß, SDF-1α, MMP-1, MMP-3, and MMP-8, as well as a reduction in the α-diversity of the oral microbiome. Larger studies are needed to confirm these results. If confirmed, these changes might imply a potential role as predictive or pharmacodynamic biomarkers for oral mucositis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".