Anti-Claudin-2 Antibody–Drug Conjugates for the Treatment of Colorectal Cancer Liver Metastasis
Bibliographic record
Abstract
We have previously demonstrated that Claudin-2 is required for colorectal cancer (CRC) liver metastasis. The expression of Claudin-2 in primary CRC is associated with poor survival and highly expressed in liver metastases. Claudin-2 also promotes breast cancer liver metastasis by enabling seeding and cancer cell survival. These observations support Claudin-2 as a potential therapeutic target for managing patients with liver metastases. Antibody-drug conjugates (ADC) are promising antitumor therapeutics, which combine the specific targeting ability of monoclonal antibodies with the potent cell killing activity of cytotoxic drugs. Herein, we report the generation of 28 anti-Claudin-2 antibodies for which the binding specificities, cross-reactivity with claudin family members, and cross-species reactivity were assessed by flow cytometry analysis. Multiple drug conjugates were tested, and PNU was selected for conjugation with anti-Claudin-2 antibodies binding either extracellular loop 1 or 2. Anti-Claudin-2 ADCs were efficiently internalized and were effective at killing Claudin-2-expressing CRC cancer cells in vitro. Importantly, PNU-conjugated-anti-Claudin-2 ADCs impaired the development of replacement-type CRC liver metastases in vivo, using established CRC cell lines and patient-derived xenograft (PDX) models of CRC liver metastases. Results suggest that the development of ADCs targeting Claudin-2 is a promising therapeutic strategy for managing patients with CRC liver-metastatic disease who present replacement-type liver metastases.
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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) | 0.001 | 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) | 0.000 | 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".