Data from Expanded Low Allele Frequency <i>RAS</i> and <i>BRAF</i> V600E Testing in Metastatic Colorectal Cancer as Predictive Biomarkers for Cetuximab in the Randomized CO.17 Trial
Bibliographic record
Abstract
AbstractPurpose: Expanded RAS/BRAF mutations have not been assessed as predictive for single-agent cetuximab in metastatic colorectal cancer (mCRC), and low mutant allele frequency (MAF) mutations are of unclear significance. We aimed to establish cetuximab efficacy in optimally selected patients using highly sensitive beads, emulsion, amplification, and magnetics (BEAMing) analysis, capable of detecting alterations below standard clinical assays. Patients and Methods: CO.17 trial compared cetuximab versus best supportive care (BSC) in RAS/BRAF-unselected mCRC. We performed RAS/BRAF analysis on microdissected tissue of 242 patients in CO.17 trial using BEAMing for KRAS/NRAS (codons 12/13/59/61/117/146) and BRAF V600E. Patients without BEAMing but with previous Sanger sequencing–detected mutations were included. Results: KRAS, NRAS, and BRAF mutations were present in 53%, 4%, and 3% of tumors, respectively. Cetuximab improved overall survival [OS; HR, 0.51; 95% confidence interval (CI), 0.32–0.81; P = 0.004] and progression-free survival (PFS; HR, 0.25; 95% CI, 0.15–0.41; P < 0.0001) compared with BSC in RAS/BRAF wild-type patients. Cetuximab did not improve OS/PFS for KRAS-, NRAS-, or BRAF-mutated tumors, and tests of interaction confirmed expanded KRAS (P = 0.0002) and NRAS (P = 0.006) as predictive, while BRAF mutations were not (P = 0.089). BEAMing identified 14% more tumors as RAS mutant than Sanger sequencing, and cetuximab lacked activity in these patients. Mutations at MAF < 5% were noted in 6 of 242 patients (2%). One patient with a KRAS A59T mutation (MAF = 2%) responded to cetuximab. More NRAS than KRAS mutations were low MAF (OR, 20.50; 95% CI, 3.88—96.85; P = 0.0038). Conclusions: We establish single-agent cetuximab efficacy in optimally selected patients and show that subclonal RAS/BRAF alterations are uncommon and remain of indeterminate significance.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".