19MO Desaminotyrosine is a key driver of the success of immunotherapy with fecal microbial transplantation in cancer
Bibliographic record
Abstract
Background: LB has become a practical, non-invasive tool for genomic profiling.However, its interpretation often requires a MTB.We present results from the PRECISO program evaluating the integration of blood-based NGS into a real-world MTB for TM. Methods:We conducted a prospective analysis of patients (pts) with TM enrolled in the PRECISO program in Hospital 12 de Octubre (Feb 2024-Apr 2025).All underwent LB using FoundationOne ® Liquid CDx (Roche).We collected clinical variables, genomic findings, and MTB recommendations.Results: A total of 346 pts were included (45.1% female; 85.9% metastatic disease, median age 65).Most had ECOG 0-1 (86.7%) and NSCLC (98.3%: 20.5% squamous (sq), 77.8% non-sq); 1.6% mesothelioma and 0.1% thymic tumors.Samples were obtained at diagnosis (31.3%), progression (PD) (59.6%), or other settings (9.1%).Median turnaround time for NGS results was 15 days.ESCAT I/II alterations were detected in 33.2%/21.7% of pts.Excluding diagnostic samples, actionable ESCAT I alterations were identified in 10.1% of sq-NSCLC and 25.8% of non-sq NSCLC without prior molecular findings.At diagnosis, 78.8% of LBs were informative.Non-informative results were more likely in pts with non-progressive disease (OR 2.25; χ 2 p = 0.10), radiological response (OR 10.8; χ 2 p = 0.008) and non-metastatic status (OR 9.1; χ 2 p < 0.001).The MTB recommended targeted therapy in 26% of pts (13.9% trials, 7.8% standard, 4.3% compassionate use); 7.2% had suspected germline variants.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".