Abstract IA23: ctDNA as predictive biomarkers for response and toxicity with immunotherapy
Bibliographic record
Abstract
Abstract Immune checkpoint blockade (ICB) with anti-PD1/PD-L1 antibodies provides clinical benefit to a subset of cancer patients. However, existing biomarkers do not reliably predict treatment response across diverse cancer types. Limited data exist to show how serial circulating tumor (ct)DNA testing may perform as a predictive biomarker in patients receiving immune checkpoint blockade. In an investigator-initiated phase II study of the anti-PD1 antibody pembrolizumab in patients with advanced solid tumors (INSPIRE; NCT02644369), we collected plasma samples at baseline and prior to every third cycle. These samples were retrospectively analyzed using a validated patient-specific, amplicon-based sequencing assay to detect and quantify ctDNA levels at each plasma time point. In total, 94 patients with serial ctDNA collections in five cohorts of solid tumors received single-agent pembrolizumab 200 mg IV ever 3 weeks. Levels of ctDNA at serial time points and the change from baseline were correlated with overall survival (OS), progression-free survival (PFS), objective response rate (ORR by RECIST v1.1), and clinical benefit rate (CBR, CR + PR + SD > 6 cycles). Response was measured by RECIST v1.1. Across the five cancer cohorts, median number of pembrolizumab cycles received was 3 and median follow-up was 13.8 months. Baseline ctDNA concentration correlated with multiple efficacy measures. This association became stronger across the cohorts when considering ctDNA kinetics after treatment initiation. An early reduction in ctDNA levels (at about 6-7 weeks) was strongly correlated with OS, PFS, ORR, and CBR. Sustained ctDNA clearance during treatment preceded durable clinical response. Strikingly, all 14 patients with ctDNA clearance during treatment were alive with a median of 27.5 months follow-up. These results demonstrate the potential for broad clinical utility of ctDNA-based surveillance in patients treated with ICB for advanced solid tumors of diverse histologies. Limited by the number of patients with grade 2 or higher immune-related adverse events (irAEs, 23/94 patients, 24%), no correlation was seen between irAE and cell-free DNA levels in the INSPIRE cohort. Currently we are planning interventional ICB studies using early ctDNA dynamics as predictive biomarkers. Citation Format: Lillian L. Siu. ctDNA as predictive biomarkers for response and toxicity with immunotherapy [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr IA23.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".