Concordance of tissue- and plasma-derived genomic profiling in CheckMate 9LA, using the FoundationOne CDx and GuardantOMNI assays.
Bibliographic record
Abstract
9010 Background: Blood-based profiling of genomic features including tumor mutational burden (TMB) has generally demonstrated positive correlations with tissue-derived assessments from paired tumor samples. However, both technical and biological factors contributing to discordance between these measurements and underlying sequence alterations need further investigation for the successful adoption of noninvasive tumor profiling. We explored the genomic landscape, including the association between tissue TMB (tTMB) and blood TMB (bTMB), in samples from patients with stage IV non-small cell lung cancer (NSCLC) enrolled in CheckMate 9LA (NCT03215706), a phase 3, randomized clinical trial of nivolumab + ipilimumab in combination with 2 cycles of chemotherapy (chemo) vs 4 cycles of chemo as first-line treatment for NSCLC. Methods: Tissue- (FoundationOne CDx [F1CDx]) and blood-based (GuardantOMNI [OMNI]) genomic data obtained from both treatment arms were utilized for our retrospective analysis of genomic variants and complex biomarkers, including tTMB and bTMB. In total, 692 tissue and 646 plasma samples were analyzed. Results: Following the established criteria for the validated F1CDx and OMNI platforms, 464 tissue and 537 plasma samples passed quality control, resulting in ascertainment levels of 67% for tTMB and 83% for bTMB. Across 344 paired tissue and plasma samples, tTMB and bTMB scores were found to be moderately correlated (Spearman’s r = 0.56; P < 0.001); median tTMB score was 7.7 mutations per megabase (mut/Mb) and median bTMB score was 13.5 mut/Mb. For the prespecified cutoffs of 10 mut/Mb for tTMB and 16 mut/Mb for bTMB, the positive, negative, and overall percentage agreements between assays were 65%, 79%, and 73%, respectively. Interestingly, 2 discordant sample pairs had considerably higher bTMB than tTMB (76.1 vs 3.8 and 172.6 vs 5.0 mut/Mb for bTMB and tTMB, respectively) and both had high microsatellite instability from blood-based assessments. OMNI and F1CDx data from 477 patients were evaluable for the analysis of short sequence variants (single nucleotide variations and indels). OMNI detected 4557 variants, F1CDx detected 4620, and 2903 (46% of total reported variants) were detected by both assays. Conclusions: In CheckMate 9LA, data from paired samples revealed the complementary nature of TMB assessments from tissue and blood and suggest that both approaches may have the potential to identify genomic alterations that may be useful in the management of patients with NSCLC. Further interrogation of the biological and analytical factors affecting tumor- and blood-derived genomic profiling is warranted to support their implementation in clinical settings. Clinical trial information: NCT03215706.
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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 | 0.003 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".