The Predictive Value of CD3+/CD8+ Lymphocyte Infiltration and PD-L1 Expression in Colorectal Cancer
Bibliographic record
Abstract
Aim: The immune system plays an important role in tumor development and treatment. In this study, we aimed to determine the relationships among the expressions of PD-L1, CD3, CD8, MMR proteins, clinicopathological features, and prognosis of CRC. Methods: Immunohistochemistry was used to determine the expression of PD-L1, CD3, and CD8 in 771 patients with CRC. Results: The expression of PD-L1 in TC was related to the right colon, adenocarcinoma, and dMMR, and in IC, it was related to younger CRC patients and the TNM stage. The expression of CD3 and CD8 in tumor-infiltrating lymphocytes was related to lymph node metastasis and the TNM stage. The expression of PD-L1 in TC and IC was correlated with the infiltration of CD3+ and CD8+ lymphocytes. Univariate survival analysis showed that the expression of PD-L1 in TC, IC, and dMMR was related to a better prognosis. Multivariate survival analysis showed that age, TNM stage, and dMMR were independent prognostic factors for CRC. The OS of the chemotherapy was significantly higher than that of the non-chemotherapy in III-IV TNM stage patients; CRC patients with positive PD-L1 expression in TC or IC and dMMR did not benefit from chemotherapy. Conclusions: PD-L1 expression in TC and IC was closely related to the density of CD3 and CD8 infiltration in tumor-infiltrating lymphocytes. The expression of CD3 and CD8 in tumor-infiltrating lymphocytes and the expression of PD-L1 in IC were linked to the TNM stage of CRC patients. PD-L1 expression in TC and IC and MMR status may act as an important biomarker for guiding the postoperative treatment of III-IV TNM stage CRC patients.
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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".