BIOM-40. THERABIOME-GBM: THERAPEUTIC OUTCOMES RELATED TO GUT MICROBIOME IN GLIOBLASTOMA (GBM) PATIENTS RECEIVING CHEMO-RADIATION: A PROSPECTIVE OBSERVATIONAL STUDY
Bibliographic record
Abstract
Abstract PURPOSE A major barrier to improving outcomes in glioblastoma multiforme (GBM) is overcoming a heavily immunosuppressed tumor and systemic environment, as demonstrated by several negative phase III randomized studies of nivolumab in both newly diagnosed and recurrent GBM. In several mouse avatar and human studies across several tumor cohorts including in a humanized microbiome GBM model, re-establishing a new gut microbiome (GM) via fecal transplantation led to tumor responses to PD-1/PD-L1 inhibition. A recent scoping review confirmed a paucity of GM clinical data of a uniform GBM cohort with adequate longitudinal GM sample collection. We are conducting a single-center prospective observational study to establish the feasibility of collecting stool samples throughout the time course of GBM treatment and upon recurrence, and to understand the gut microbiome dynamics of newly diagnosed IDH-wild type (WT) GBM patients. METHODS Patients with newly diagnosed unifocal IDH-1 R132H WT WHO grade 4 GBM, ECOG 0-2, at least 70% tumor resected with plan to receive temozolomide-radiation (TMZ-RT) and adjuvant TMZ +/- Tumor Treating Fields are eligible. Stool samples will be collected prior to TMZ-RT, 4 weeks after TMZ-RT, after adjuvant TMZ, and upon recurrence. The primary endpoint is feasibility, defined as stool sample obtained pre-RT, post-RT (pre-adjuvant TMZ), and at time of recurrence in ≥ 70% of enrolled participants, 75% of target sample size enrolled within 2 years, and stool sample volume and quality sufficient for analysis in ≥ 75% of collected samples. Secondary endpoints include progression-free survival (PFS) in pre-defined GM subgroups, GM taxonomy and diversity in late vs. early progressors, and GM differences in patients with and without post-RT necrosis. Age, sex, race, concurrent medication, corticosteroid use, and diet will be carefully accounted for. Patient reported outcomes using EORTC-QLQ-BN20 and QLQ-C30 will be collected at baseline, 3-, 6-, 9-, and 12-months.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".