An open-label phase 1 study to investigate SGNCEACAM5C/SAR445953 in adults with advanced solid tumors (SGNCEA5C-001).
Bibliographic record
Abstract
TPS3160 Background: Patients (pts) with recurrent or metastatic solid tumors, including non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), colorectal cancer (CRC), gastric adenocarcinoma (GC), and pancreatic ductal adenocarcinoma (PDAC), have limited treatment options with short PFS and OS despite recent advances (1-3). Carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) is highly expressed across multiple solid tumors, such as CRC, GC, PDAC, and NSCLC. Restricted normal tissue expression and efficient lysosomal trafficking of CEACAM5 highlight its potential as an anticancer target. SGN-CEACAM5C is a novel investigational antibody-drug conjugate (ADC) directed to CEACAM5 composed of the humanized immunoglobulin G (IgG1) anti-CEACAM5 monoclonal antibody tusamitamab chemically conjugated to 8 molecules of the topoisomerase 1 inhibitor 7-aminomethyl-10,11-methylenedioxycamptothecin (AMDCPT). SGN-CEACAM5C selectively binds to CEACAM5 present on the cell surface and is internalized via the endo-lysosomal pathway, with subsequent release of the payload through enzymatic cleavage. Release of the cytotoxic payload induces DNA damage, cell cycle arrest in S phase, and apoptosis in tumor cells. In vitro bystander activity was observed against tumor cells without CEACAM5 surface expression. SGN-CEACAM5C is highly active in multiple patient-derived xenograft models, including CRC, GC, and NSCLC, across various levels of CEACAM5 expression (4,5). These preclinical findings justify evaluation of SGN-CEACAM5C in a clinical trial setting. Methods: SGNCEA5C-001 (NCT06131840) is a phase 1, open-label, multicenter study designed to characterize the safety, tolerability, pharmacokinetics (PK), pharmacodynamics (PD), and preliminary antitumor activity of SGN-CEACAM5C in adults with select advanced solid tumors. This study consists of dose escalation (Part A), dose and schedule optimization (Part B), and dose expansion (Part C). Eligible pts are adults ≥18 years of age with confirmed metastatic or unresectable solid tumor malignancy, measurable disease per Response Evaluation Criteria in Solid Tumors (RECIST) v1.1, an ECOG PS of 0-1, and 1 of the following tumor types: CRC, GC/gastroesophageal junction adenocarcinoma (GEJ), PDAC, NSCLC (squamous/non-squamous), or SCLC. Primary endpoints include incidence of AEs, laboratory abnormalities, dose modifications due to AEs, dose-limiting toxicities, and cumulative safety. Secondary endpoints include estimates of PK parameters, incidence of antidrug antibodies, objective response rate and best response per RECIST v1.1 by investigator, duration of response, PFS, and OS. Safety and antitumor activity endpoints will be summarized using descriptive statistics. Recruitment is ongoing for Part A in North America. 1. Bordry 2021. 2. Chakrabarti 2022. 3. Merle 2022. 4. Baudat 2023. 5. Baudat 2024. Clinical trial information: NCT06131840 .
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".