Antibody-mediated targeting of Claudins in cancer
Bibliographic record
Abstract
Tight junctions (TJs) are large intercellular adhesion complexes that maintain cell polarity in normal epithelia and endothelia. Claudins are critical components of TJs, forming homo- and heteromeric interaction between adjacent cells, which have emerged as key functional modulators of carcinogenesis and metastasis. Numerous epithelial-derived cancers display altered claudin expression patterns, and these aberrantly expressed claudins have been shown to regulate cancer cell proliferation/growth, metabolism, metastasis and cell stemness. Certain claudins can now be used as biomarkers to predict patient prognosis in a variety of solid cancers. Our understanding of the distinct roles played by claudins during the cancer progression has progressed significantly over the last decade and claudins are now being investigated as possible diagnostic markers and therapeutic targets. In this review, we will summarize recent progress in the use of antibody-based or related strategies for targeting claudins in cancer treatment. We first describe pre-clinical studies that have facilitated the development of neutralizing antibodies and antibody-drug-conjugates targeting Claudins (Claudins-1, -3, -4, -6 and 18.2). Next, we summarize clinical trials assessing the efficacy of antibodies targeting Claudin-6 or Claudin-18.2. Finally, emerging strategies for targeting Claudins, including Chimeric Antigen Receptor (CAR)-T cell therapy and Bi-specific T cell engagers (BiTEs), are also discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".