Abstract B028: Claudin-18 expression (using the 43-14A antibody kit) in pancreatic ductal adenocarcinoma: Assessment of a potential clinical biomarker for immunotherapy with zolbetuximab
Bibliographic record
Abstract
Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy; despite efforts to improve outcomes, five-year survival remains below 15% and immunotherapies have largely been unsuccessful. Claudin-18.2 (CLDN18.2), overexpressed in some gastro-intestinal cancers, including PDAC, has emerged as a promising therapeutic target. Zolbetuximab, a monoclonal antibody targeting CLDN18.2, triggers antibody- and complement-dependent cytotoxicity. Zolbetuximab has demonstrated therapeutic benefit in locally advanced and metastatic gastric and gastroesophageal junction cancers in phase 3 clinical trials (SPOTLIGHT and GLOW). A phase 2 clinical trial of zolbetuximab for PDAC patients is underway, with patient eligibility dependent on the expression of CLDN18 in ≥75% of tumor cells. CLDN18 overexpression in PDAC has been reported in research studies using a variety of antibodies, methods, and positivity thresholds. However, minimal population-based expression data uses the 43-14A diagnostic kit from the zolbetuximab clinical trials. The 43-14A antibody will likely become the standard clinical companion diagnostic if PDAC therapeutic trials succeed; hence, understanding its utility for binding and clinical assessment is prescient. Herein, we report the expression of CLDN18 using the 43-14A antibody kit in a retrospective Atlantic Canadian cohort of patients with PDAC. Methods: Immunohistochemical staining of CLDN18 was performed using the 43-14A antibody on PDAC samples (n=121) collected from patients who underwent surgical resection between 2012 and 2024 in Nova Scotia. Formalin-fixed paraffin-embedded samples were stained by immunohistochemistry with the 43-14A clone, prediluted kit, according to the kit manufacturer’s recommended protocol on the recommended platform (Benchmark ULTRA), consistent with methods employed in clinical trials. A board- certified pathologist, blinded to clinical outcomes, assessed CLDN18 immunostaining. Tumor cell staining proportion and membranous intensity were evaluated, with positive cases defined as ≥ 75% of tumor cells exhibiting membranous staining with an intensity of ≥ 2. Results: Out of 121 PDAC tumors, 39 (32.2%) stained positive for CLDN18. Although no significant associations were identified between CLDN18 positivity and various clinical variables, there was a trend suggesting a potential correlation with lower tumor grade (p = 0.0738). The study was adequately powered to detect significant associations. Conclusions: Our findings indicate that 32.2% of PDAC tumors in this cohort are positive for CLDN18, suggesting that a significant proportion of patients in our population could benefit from zolbetuximab and other CLDN18.2 targeted immunotherapies. Citation Format: Riley J Arseneau, Emma Kempster, Carley Bekkers, Thomas Sampson, Boris L Gala-Lopez, Ravi Ramjeesingh, Jeanette E Boudreau, Thomas Arnason. Claudin-18 expression (using the 43-14A antibody kit) in pancreatic ductal adenocarcinoma: Assessment of a potential clinical biomarker for immunotherapy with zolbetuximab [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr B028.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".