BIOM-34. GENOMIC ANALYSIS OF CSF CTDNA IN LUNG CANCER-RELATED LEPTOMENINGEAL METASTASES
Bibliographic record
Abstract
Abstract INTRODUCTION CSF-based ctDNA analysis holds potential in refining molecular diagnoses and staging in LMD, providing prognostic information, and optimizing CSF-directed therapy. Herein we retrospectively evaluate the potential clinical utility of analyzing CSF for SNV/MNV/indels, MGMT promoter methylation, and aneuploidy in optimizing LMD from lung cancer (LC). METHODS We examined 31 CSF samples from 8 LC patients with LMD (7 with longitudinal sampling, 2-6 samples per patient) collected under our institutional multi-agent intraventricular chemotherapy (MAIVC) protocol. The SummitTM assay was used to identify mutations and aneuploidy in CSF ctDNA, while the VantageTM assay evaluated MGMT methylation status via quantitative PCR. Molecular data were compared with primary tumor profiles, overall survival (OS) from LMD diagnosis, and clinical parameters (cytology, MRI, and treatment status). RESULTS The median OS was 358 days. In one patient, concordant EGFRG719F mutations (exon 19 deletion) were found in both primary tumor and CSF, with reductions in variant allele frequency (VAF) and aneuploidy following therapy (OS: 317 days). Another patient showed a late increase in EGFRQ791H and KRASQ61H variants and aneuploidy in the final CSF sample, with death occurring 44 days later (OS: 336 days). In a third patient, CSF-specific GNASR201H and HRASQ61L variants emerged shortly after therapy initiation, with an OS of 73 days. Two patients lacking significant variants or aneuploidy had extended OS (448 and 667 days). Persistent aneuploidy was observed in two patients: the MGMT-methylated patient survived 379 days, while the unmethylated patient survived 36 days. In one patient with a KRASG12A variant and aneuploidy, both resolved after one MAIVC cycle, with an OS of 635 days. CONCLUSIONS Unique driver mutations and dynamic changes in ctDNA were detected. The potential prognostic value of MGMT methylation warrants further investigation. Incorporating fusion detection and the addition of complementary CSF proteomic analysis could enhance insights. Larger prospective studies are ongoing.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.000 |
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".