Circulating tumor (ct)-DNA alterations in advanced urothelial carcinoma: Association with outcomes and evolution with therapy.
Bibliographic record
Abstract
334 Background: Cell-free ctDNA may be potentially actionable, prognostic for outcomes and evolve after therapy. We conducted a retrospective study to evaluate these issues and shed light on UC biology. Methods: Patients (pts) with advanced UC who underwent ctDNA analysis for potentially actionable alterations using Guardant360 were identified. Data were requested for prognostic factors, current and prior therapies, TTF (time to treatment failure) and overall survival (OS). A 70-gene ctDNA next generation sequencing panel from a CLIA-licensed, CAP-accredited laboratory (Guardant Health, Inc.) offers complete exon sequencing for 29 cancer genes, critical exons in 39 genes and amplifications (16 genes), fusions (6 genes) and indels (3 genes) harvested from 10 mL of peripheral blood. Alterations were reported and association of non-synonymous potentially functional alterations with outcomes and prior therapy was examined. Results: There were 217 pts with 238 samples. ctDNA was detectable in 212 (89%) samples. Median age was 62 (range 39-91). The most common recurrent somatic mutations were in TP53 (n = 122, 57%) ARID1A (n = 47, 22%), NF1 (n = 35, 16%), FGFR2, FGFR3, and BRCA1 (n = 30, 14% each), MET (n = 27, 13%), ERBB2 (n = 25, 12%), PIK3CA (n = 24, 11%), and EGFR (n = 22, 10%). Most common genes with increased copy numbers were ERBB2 (n = 19, 9%) and RAF1 (n = 18, 8%). Clinical data were available for 64 pts, of whom 38 (59%) had prior chemotherapy. FGFR1 alterations noted in 3 of those pts (5%, 2 functional, 1 amplification) were associated with shorter OS (HR 2.95, p = 0.05). Pts with prior chemotherapy showed trend towards frequent alterations in DNA repair genes (45% vs. 23%, p = 0.11). Serial ctDNA profiling of 21 pts receiving therapy revealed the clonal evolution of mutations in BRCA2, NF1 and GATA3. Conclusions: ctDNA was very frequently detected in pts with advanced UC, and alterations were similar to those previously seen in muscle-invasive UC tumor tissue. FGFR1 alterations predicted for unfavorable outcome and DNA repair gene alterations evolved commonly after chemotherapy. Drugs exploiting these targets such as FGFR1 and PARP inhibitors may warrant exploration as salvage therapy in selected pts.
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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 | 0.002 |
| 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) | 0.001 | 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".