Improving the response to oxaliplatin by targeting chemotherapy-induced CLDN1 in resistant metastatic colorectal cancer cells
Bibliographic record
Abstract
BACKGROUND: Tumor resistance is a frequent cause of therapy failure and remains a major challenge for the long-term management of colorectal cancer (CRC). The aim of this study was to determine the implication of the tight junctional protein claudin 1 (CLDN1) in the acquired resistance to chemotherapy. METHODS: Immunohistochemistry was used to determine CLDN1 expression in post-chemotherapy liver metastases from 58 CRC patients. The effects of oxaliplatin on membrane CLDN1 expression were evaluated by flow cytometry, immunofluorescence and western blotting experiments in vitro and in vivo. Phosphoproteome analyses, proximity ligation and luciferase reporter assays were used to unravel the mechanism of CLDN1 induction. RNAseq experiments were performed on oxaliplatin-resistant cell lines to investigate the role of CLDN1 in chemoresistance. The "one-two punch" sequential combination of oxaliplatin followed by an anti-CLDN1 antibody-drug conjugate (ADC) was tested in both CRC cell lines and murine models. RESULTS: We found a significant correlation between CLDN1 expression level and histologic response to chemotherapy, CLDN1 expression being the highest in resistant metastatic residual cells of patients showing minor responses. Moreover, in both murine xenograft model and CRC cell lines, CLDN1 expression was upregulated after exposure to conventional chemotherapies used in CRC treatment. CLDN1 overexpression was, at least in part, functionally related to the activation of the MAPKp38/GSK3β/Wnt/β-catenin pathway. Overexpression of CLDN1 was also observed in oxaliplatin-resistant CRC cell lines and was associated with resistance to apoptosis, suggesting an anti-apoptotic role for CLDN1. Finally, we demonstrated that the sequential treatment with oxaliplatin followed by an anti-CLDN1 ADC displayed a synergistic effect in vitro and in in vivo. CONCLUSION: Our study identifies CLDN1 as a new biomarker of acquired resistance to chemotherapy in CRC patients and suggests that a "one-two punch" approach targeting chemotherapy-induced CLDN1 expression may represent a therapeutic opportunity to circumvent resistance and to improve the outcome of patients with advanced CRC.
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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 | 0.000 |
| 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".