Prognostic Value of BRAF, Programmed Cell Death 1 (PD1), and PD Ligand 1 (PDL1) Protein Expression in Colon Adenocarcinoma
Bibliographic record
Abstract
Patients with colorectal cancer in different stages show variable outcomes/therapeutic responses due to their distinct tumoral biomarkers and biological features. In this sense, this study aimed to explore the prognostic utility of BRAF, programmed death-1 (PD1), and its ligand (PDL1) protein signatures in colon adenocarcinoma. The selected protein markers were explored in 64 archived primary colon adenocarcinomas in relation to clinicopathological features. BRAF overexpression was found in 39% of the cases and was significantly associated with grade 3, N1, advanced Dukes stage, presence of relapse, and shorter overall survival (OS). PD1 expression in the infiltrating immune cells (IICs) exhibited significant association with T2/T3, N0/M0, early Dukes stage, and absence of relapse. PDL1 expression in IICs is significantly associated with advanced nodal stage/distant metastasis, advanced Dukes stage, and shorter OS. Meanwhile, PDL1 expression in neoplastic cells (NC) was associated with the advanced lymph node/Dukes stage. A positive combined expression pattern of PDL1 in NC/IICs was associated with poor prognostic indices. Tumor PDL1 expression can be an independent predictor of OS and DFS. The multivariate analyses revealed that short OS was independently associated with the RT side location of the tumor, PD1 expression in stromal IICs, and PDL1 expression in NC. In conclusion, overexpression of BRAF in colon adenocarcinoma is considered a poor prognostic pathological marker. In addition, PDL1 expression in NC is considered an independent prognostic factor for DFS/OS. Combined immunohistochemical assessment for BRAF and PD1/PDL1 protein expressions in colon adenocarcinoma might be beneficial for selecting patients for future targeted therapy.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".