A plasma-based analysis and genomic landscape of patients with high tumor mutational burden (TMB-H), microsatellite stable (MSS) colorectal cancer (CRC).
Bibliographic record
Abstract
249 Background: An estimated 85% of CRC are microsatellite stable (MSS) and this population has limited response to immune checkpoint inhibitors (ICIs). Biomarkers are needed to identify responders. Although pembrolizumab received FDA universal approval for chemorefractory cancers with tissue TMB-H > 10 mut/Mb, it is not effective across all TMB-H cancers. We aim to identify TMB-H/MSS CRC patients that derive benefit from ICIs through analysis of circulating tumor DNA (ctDNA). Methods: We retrospectively queried Guardant Health database (2020-2022) for patients with advanced CRC who had ctDNA NGS (Guardant360, Redwood City, CA) as part of routine clinical care. The assay covers a 1Mb panel for TMB that counts synonymous and non-synonymous somatic SNVs and indels to calculate a TMB score. Co-mutations were evaluated for MSS cancers with plasma TMB-H; ≥20mut/Mb vs those with low TMB (TMB-L; < 20mut/Mb). RAS- mutated signature was defined as those harboring an activating somatic alteration in KRAS, NRAS, or BRAF. Statistical significance was calculated using Fisher’s exact test. Results: We identified 6412 CRC patients: 11% (711) TMB-H/MSS (median age 64), 69% (4426) TMB-L/MSS (median age 62), 3% MSI-H, and 17% unevaluable. When compared to TMB-L/MSS, patients with TMB-H/MSS had a significantly higher frequency of select genetic mutations, including TP53, APC, KRAS, EGFR, and PIK3CA (p < 0.001). Treatment-naïve TMB-H/MSS cancers had a higher frequency of ARID1A (p = 0.05) and TERT (p = 0.02) alterations, while those post therapy progression had higher frequency of KRAS (p = 0.02), EGFR (p < 0.001), and MAP2K1 (p = 0.002) alterations. A total of 556 (78%) CRC patients in the TMB-H/MSS cohort harbored a RAS-mutated genetic signature. Of those, 432 (78%) belonged to the post therapy progression group, likely representing adaptive clones post anti-EGFR therapy. While RAS-mutated tumors had a higher prevalence of PIK3CA (p = 0.001) and SMAD4 (p = 0.007) co-alterations, RAS-wildtype ones carried a higher frequency of ERBB2 (p = 0.068) alterations. Conclusions: We describe the genomic landscape of patients with plasma TMB-H/MSS CRC. A clinical cohort of TMB-H/MSS CRC patients identified by ctDNA and treated with ICIs will be presented.
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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 | 0.001 | 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) | 0.002 | 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".