Tumor cell-intrinsic PD-1 regulates chemotherapy resistance in colorectal cancer cells by activating downstream MAPK signaling
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) remains a significant clinical challenge. Immunotherapy against programmed cell death 1 protein (PD-1) in CRC has limited success. Intriguingly, CRC cells express PD-1 (ciPD-1) intrinsically, and we report here its function with respect to chemotherapy. METHODS: We evaluated the associations between ciPD-1 expression and disease progression, overall survival, and upregulation of survival pathways in human CRC tumors. Expression levels of ciPD-1 in CRC cells were modulated to evaluate its biological role in vitro. RESULTS: High expression levels of PD-1 in CRC tumors are associated with inferior outcomes; these tumors are also more aggressive and drug-resistant. Expression levels of ciPD-1 in CRC cells increase during 5-FU or CPT-11 treatment and are accompanied by upregulation of cell survival pathways. When ciPD-1 is inhibited, the cell-killing effects of 5-FU or CPT-11 were significantly increased. Our data show that ciPD-1 signaling occurs via MAPK signaling in CRC cells to support survival under stress conditions. CONCLUSIONS: CRC tumors with high levels of ciPD-1 are more aggressive and associated with inferior outcomes. Reducing ciPD-1 levels in CRC cells make them more sensitive to chemotherapy. The aggregate results suggest that using a PD-1 inhibitor with first-line treatments in CRC could improve therapeutic efficacy. Proposed biological role of ciPD-1 in CRC cells. After exposure to chemotherapy, radiotherapy, or nutrient deprivation, ciPD-1 expression is elevated in CRC cells. Subsequently, ciPD-1 activates MAPK and AKT signaling pathways to increase proliferation and differentiation, resulting in drug resistance and tumor growth in CRC cells. The administration of anti-PD-1 immunotherapy with chemotherapy in CRC cells could abrogate ciPD-1 activity and enhance the efficacy of chemotherapy to overcome resistance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".