Clinical and Molecular Profiling of Colorectal Cancer: A Comprehensive Cohort Study of BRAF-Mutated Cases from a Tertiary Centre
Bibliographic record
Abstract
Introduction: Increasingly, identification of BRAF mutation in colorectal cancer is used to guide management and predict cancer behaviour. There is, however, still significant diversity within this cohort of patients, both in terms of clinical phenotype and treatment outcomes. This may be explained, at least in part, by differences between classes of BRAF mutations and the presence of concomitant mutations. Methods: We present a retrospective cohort study of sequential patients diagnosed with BRAF-mutated (V600 and non-V600) colorectal cancer between 2014 and 2022. Information regarding presentation, treatment outcomes and molecular subtype was identified using the electronic medical record. Results: This study included 406 patients with BRAF-mutated colorectal cancer, 253 (228 V600BRAF) of whom had localised disease and 153 (137 V600BRAF) with metastatic disease at the time of diagnosis. In patients with localised disease at diagnosis, the V600BRAF mutation was associated with older median age (73 vs. 63 years, p = 0.04) and a higher prevalence of right-sided primary (73% vs. 40%, p < 0.01), mismatch repair deficiency (56% vs. 8%, p < 0.01), and faster time to disease relapse (p = 0.006). In the metastatic setting, non-V600BRAF mutation was associated with a higher prevalence of KRAS mutation (27% vs. 1%, p < 0.01), NRAS mutation (14% vs. 3%, p = 0.04) and PIK3CA mutation (33% vs. 8%, p = 0.02). Mismatch repair deficiency was more common in patients with V600BRAF mutations than in those with non-V600BRAF mutations (20% vs. 0%, p = 0.01). The median survival of patients with the V600BRAF mutation was 14 months, and 34 months in those with non-V600BRAF mutations. Concomitant RNF43 mutation in metastatic disease, was associated with a significantly higher incidence of disease control from combined BRAF and EGFR inhibition, when compared to those without an RNF43 mutation (100% vs. 54%, p = 0.02). Conclusions: Presentation and outcomes of BRAF-mutated colorectal cancer are heterogenous. The type of BRAF mutation, and the presence of concomitant RNF43 mutation, may explain some of the differences in cancer behaviour. Routine reporting of RNF43 mutations would assist clinicians to give more personalised treatment recommendations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".