Early circulating tumor DNA (ctDNA) kinetics using a tumor-naïve assay as a predictive biomarker in early-phase immunotherapy (IO) clinical trials.
Bibliographic record
Abstract
2546 Background: ctDNA kinetics with tumor-informed assays can predict treatment outcome in patients (pts) treated with anti-PD1 IO ( Bratman et al, Nature Cancer 2020). We evaluated whether early ctDNA kinetics with a tumor-naïve assay were associated with clinical outcomes in advanced solid tumor patients treated on early phase IO trials. Methods: Advanced solid tumor pts treated with investigational IO agents at the Princess Margaret Phase I program were enrolled. Baseline (B) and pre-cycle 2 (C2) (3-4 weeks after first dose) plasma samples were prospectively collected via an institutional liquid biopsy program (LIBERATE, NCT03702309). ctDNA was assessed using the tumor-naïve 425-gene Geneseeq Prime panel in a clinical laboratory. Mutations in each gene detected in ctDNA were measured as Variant Allele Fraction (VAF). Mean VAF from all mutations was calculated. Radiological response was measured per RECIST criteria and correlated using ROC curves. Hyperprogression (HPD) was defined using VHIO criteria ( Matos et al, CCR 2020). Survival outcomes were estimated using the Kaplan Meier method. Results: From 12/2017 to 3/2020, 162 plasma samples from 81 pts with 25 different tumor types were collected. Pts were treated within 25 different IO phase I/II trials, 72% of which involved a PD-1/PD-L1 inhibitor. Median age was 58y (range 21 – 79), 54% female, 76% ECOG1. Sarcoma and colorectal (11%, each) followed by breast (8%) and melanoma (7%) were the most frequent tumors. Median follow up was 10.3 months (m) (1.8-46.9). CR 4% (n = 3), PR 6% (n = 5), HPD 11% (n = 9). Clinical benefit (CB) rate (CR+PR+SD > 6 months) was 20% (n = 16). ctDNA was detected in 122/162 samples (75.3%) (60 at B, 62 at C2). The most frequent mutations were TP53 (32%), PI3KCA (12%), PKHD1 (11%), and KRAS (9%). Mean VAF at B below median was not associated with OS (HR = 0.68 95%CI 0.4-1.16; p = 0.16) or PFS (HR = 0.93 95%CI 0.56-1.54; p = 0.77). Mean VAF change (difference between mean VAF at B and at C2) was associated with response (AUC = 0.99) and CB (AUC = 0.86). A decrease in mean VAF from B to C2 was seen in 24 pts (37.5%) and was associated with longer PFS (median PFS 2.7 vs 1.8 m; HR: 0.43, 95%CI 0.24-0.77; p < 0.01) and OS (median OS 10.8 vs 9.1 m; HR: 0.54; 95%CI 0.3-0.96; p = 0.03) compared to an increase in mean VAF. These differences were more marked if there was > 50% decrease in mean VAF from B to C2 (n = 11, 17%) compared to decrease < 50% or increase: median PFS 3.6 vs 1.8 m (HR: 0.29, 95%CI 0.13-0.62; p < 0.01) and median OS not reached vs 9.6 m (HR: 0.23, 95%CI 0.09-0.6; p < 0.01). No differences in mean VAF change were seen between HPD and PD pts. Conclusions: In a pan-cancer solid tumor early phase trial IO cohort, a decrease in ctDNA within 4 weeks of treatment was associated with increased CB, OS and PFS. HPD pts did not show greater increases in ctDNA. Tumor-naïve ctDNA assays may be useful to identify early treatment benefit in phase I/II trials with IO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.009 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".