Association of plasma biomarkers with recurrence in glioblastoma.
Bibliographic record
Abstract
e14017 Background: Adult-type diffuse gliomas are common malignant tumors known for their high recurrence rates, regardless of grade. High recurrence is due to incomplete resection of the tumors and the infiltrative nature of the tumor cells. Unfortunately, prediction of recurrence relies solely on MRI, a method that is expensive and susceptible to errors, treatment and pseudo-progression effects. Capturing recurrence prior to MRI is an unmet clinical need and could allow for earlier intervention or enrolment of patients into clinical trials. Liquid biopsy has emerged as a promising approach. Methods: Previously collected patient plasma was retrieved from three sites: Northwestern University Tumor Biobank, Penn State Neuroscience Biorepository and University Health Network Biobank (Cross-sectional samples(all primary vs all recurrent) n = 264, patients with multiple samples (longitudinal) n = 44; Groups = Glioblastoma (GBM), astrocytoma, oligodendroglioma) and analyzed retrospectively for seven proteomic markers: GFAP, NEFL, FABP4, MMP1, MMP3, MMP9 and total tau (tTau) using research-use-only electrochemiluminescence assays available from Meso Scale Discovery. For the cross-sectional analysis (independent samples per patient), Wilcoxon rank sum test with post hoc Holm’s correction was used to compare biomarker values in samples from individuals with primary and recurrent tumors, after adjusting for sex differences. For the longitudinal analysis of paired primary and recurrence samples, Wilcoxon signed-rank test was used. Survival probability was tested through Kaplan-Meier survival curves. Results: In the cross-sectional analysis of the diffuse gliomas (GBM = 77+129 [Batch 1 + Batch 2], Oligodendroglioma = 23 +11, Astrocytoma = 26 + 25), we found that in the GBM group, the median values of MMP9 and GFAP were lower during recurrence. The median NEFL value was higher during GBM recurrence but did not achieve statistical significance, although the same effect was observed in the longitudinal analysis. In survival analyses, higher MMP3 and MMP9 in primary case samples across all diffuse gliomas were significantly associated with poorer survival, but this significance was lost during recurrence, indicating potentially important differences between a primary and a recurrent state. Conclusions: This cross-sectional and longitudinal retrospective pilot study evaluated seven plasma markers for the potential capability of predicting tumor recurrence in adult-type diffuse gliomas. While we found no significant differences across diffuse gliomas overall, subgroup analyses revealed recurrence-associated patterns. These findings suggest that certain markers could complement imaging for recurrence detection and perhaps prediction. Larger and more comprehensive studies are warranted.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".