Microbiota-associated metabolic reprograming influenced clinical outcome in the randomized dendritic cell-based clinical trial in stage III melanoma
Bibliographic record
Abstract
Abstract Background: Melanoma is a malignancy where tumor immunosurveillance plays a major prognostic role, prompting the development of immunotherapy strategies, dominated earlier on by dendritic cell (DC)-based immunotherapy and recently, by immune checkpoint inhibitors (ICI). The taxonomic composition of the gut microbiome earned its credentials among predictors of survival in melanoma, by influencing the peripheral and tumoral immune tonus. Methods: In the MIND-DC phase III clinical trial (NCT02993315), 148 stage IIIB/IIIC cutaneous melanoma patients were randomized in a 2:1 ratio to adjuvant treatment with autologous conventional and plasmacytoid mature natural DC (nDC) versus placebo. Blood and stool samples were collected in 144 patients before and after 2 biweekly nDC injections to perform longitudinal metagenomics (MG) and metabolomics (MB), with the aim of finding predictors of 2-year recurrence-free survival (RFS). Results: Different microbial species were associated with prognosis of these patients with stage III melanoma, with the health-related Faecalibacterium prausnitzii standing out as the main beneficial taxon for no recurrence at 2 years (p=0.009). Therapy coincided with major perturbations of plasma acylcarnitines, as well as carboxylic and fatty acids (FA). Incidentally, despite randomization, patients in the nDC treatment arm exhibited a bias in their MG and MB baseline profiles, with a relative under-representation of F. prausnitzii, and perturbations of biliary salts and FA, compared to the control arm. Stool F. prausnitzii anticorrelated with plasma medium chain acylcarnitines and the combination of both of these MG and MB biomarkers markedly determined RFS. Conclusions: Altogether, the host-microbial interaction might be influenced by nDC-based immunotherapy in melanoma, a cancer highly dependent on lipid metabolism for its dissemination. We value the systematic MG profiling in randomized trials to avoid bias in baseline host-microbe metabolic and immune parameters.
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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 | 0.003 | 0.004 |
| 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 | 0.000 |
| 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".