Tumour budding is associated with the mesenchymal colon cancer subtype and RAS/RAF mutations: a study of 1320 colorectal cancers with Consensus Molecular Subgroup (CMS) data
Bibliographic record
Abstract
BACKGROUND: Tumour budding is an important prognostic factor in colorectal cancer (CRC). Molecular profiling of tumour buds suggests (partial) epithelial-mesenchymal transition and cancer stem-cell phenotype, similarly described in the "mesenchymal" Consensus Molecular Subtype 4 (CMS4), which identifies a particularly poor prognostic subgroup. Here, we determine the association of tumour budding with CMS classification, prognosis, and response to therapy. METHODS: AMC-AJCCII-90 cohort (n = 76, stage II) was evaluated for peritumoural budding on H&E slides. LUMC (n = 270, stage I-IV), CAIRO (n = 504, metastatic CRC) and CAIRO2 (n = 472, metastatic CRC) cohorts were investigated for intratumoural budding using pan-cytokeratin-stained tissue microarrays. Budding was scored as count/area, then classified as <5 or ≥5 buds. For all cohorts, CMS classifications were available (gene-expression/immunohistochemistry-based classifiers). RESULTS: High (≥5) budding predicted a worse outcome in multivariate analysis in AMC-AJCCII-90 (p = 0.018), LUMC (p < 0.0001), and CAIRO (p = 0.03), and in CAIRO2 (continuous variable, p = 0.02). Tumour budding counts were higher in CMS4 compared to epithelial CMS2/3 cancers (p < 0.01, all), and associated with KRAS/BRAF mutations (p < 0.01, AMC-AJCCII-90, CAIRO, CAIRO2). CONCLUSION: Tumour budding is an adverse prognostic factor across all CRC stages and is associated with the mesenchymal CMS4 phenotype. KRAS/BRAF mutations are strongly correlated with tumour budding suggesting their involvement in the regulation of this process.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".