CEACAM7 Is an Effective Target for CAR T-cell Therapy of Pancreatic Ductal Adenocarcinoma
Bibliographic record
Abstract
Abstract Purpose: To investigate whether CEACAM7 represents a novel therapeutic target for treating pancreatic ductal adenocarcinoma (PDAC) and to generate CEACAM7-targeting CAR T cells to test this hypothesis. Experimental Design: We identified CEACAM7 (CGM2), a member of the CEA family of proteins with expression restricted to the colon and pancreas, as a potential CAR T-cell target for PDAC. We probed a panel of PDAC tumor sections as well as patient-derived PDAC cell cultures for CEACAM7 expression. We generated CAR-targeting CEACAM7, and assessed antitumor efficacy of CEACAM7 CAR T cells using in vitro and in vivo models. Results: We show here that CEACAM7 is expressed in a large subset of PDAC tumors, with low to undetectable expression in all normal tissues tested. CEACAM7 is also expressed in primary PDAC cultures isolated from patient-derived tumors, with high expression within the cancer stem cell-enriched subset. CAR T cells targeting CEACAM7 are capable of targeting antigen-expressing tumor cells, and mediate remission in patient-derived xenograft tumors. Conclusions: We identify CEACAM7 as a potential therapeutic target in PDAC and describe the development of CEACAM7-targeted CAR T cells with efficacy against PDAC.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".