Association of circulating tumor (ct)-DNA genomic alterations (GA) with outcomes in metastatic urothelial carcinoma (mUC).
Bibliographic record
Abstract
4540 Background: Cell-free ctDNA profiling enables noninvasive identification of GA in mUC. We hypothesized that ctDNA GA correlate with outcomes and signify therapy targets. Methods: 477 patients (pts) with UC who underwent ctDNA analysis for potentially actionable GA via Guardant360 were identified. A 73-gene ctDNA next generation sequencing (NGS) panel from CLIA-licensed, CAP-accredited laboratory (Guardant Health, Inc.) offers complete exon sequencing in 19 cancer genes, critical exons in 54 genes, amplifications (18 genes), fusions (6 genes) & indels (23 genes) from 10 mL of peripheral blood. KM method was used to estimate overall survival (OS) and failure-free-survival (FFS) since therapy initiation. Cox proportional hazards regression was used to assess the association of ctDNA GA present in > 10% of pts and clinical factors with OS and FFS in univariable analyses. All tests were 2-sided, p ≤0.05 was significant. We also evaluated GA in serial samples to assess genomic evolution. Results: 124 pts had available clinical data, of whom 65 had received prior platinum, 21 prior taxane and 10 prior PD1/PD-L1 inhibitor; ≥1 GA was detected in 112 pts. Median age at time of ctDNA collection was 72 and median (range) number of GA per sample was 4 (0-80); 110 pts had ≥1 SNV & 39 pts ≥1 CNV. Most commonly altered genes were TP53 (55%), PIK3CA (24%) and ARID1A (23%). 1-year OS and FFS were 69% and 35%, respectively. ARID1A (HR 0.49, p = 0.052) & BRAF (HR 0.24, p = 0.048) GA were associated with longer FFS, while BRCA1 (HR: 2.36, p = 0.016) GA with shorter FFS; no GA were significantly associated with OS. After ctDNA collection, 32 pts received platinum, 43 anti-PD1/PDL1, 24 other and 25 no therapy. There was no significant effect of post-ctDNA therapy on OS (p = 0.91) or FFS (p = 0.29); post-ctDNA therapy did not interact with clinical factors. Serial samples showed new and resolution of some GA. Conclusions: ctDNA GA were detected in most pts with mUC and appeared similar to those from prior tumor tissue NGS studies. BRAF & ARID1A GA correlated with longer and BRCA1 GA with shorter FFS suggesting that synthetic lethality with DNA damage repair inhibitors may be clinically useful. Serial sample analysis revealed genomic evolution.
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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 | 0.000 | 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) | 0.001 | 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".