Abstract 5629: TEQ103, a novel therapeutic for the treatment of estrogen receptor alpha positive (ERα+) breast cancer
Bibliographic record
Abstract
Abstract Background: Breast cancer is the most prevalent female cancer. Approximately 75% of them are ERα+ and are treated with ERα targeting agents. However, a good portion will ultimately relapse. TEQ103 (Sera2, ErSO-TFPy) is a first-in-class small molecule acting through the anticipatory unfolded protein response (aUPR) following dysregulation of calcium homeostasis in ERα+ tumor cells. The goal of this work is to further evaluate the efficacy, the influence of schedules of administration and the pharmacokinetics (PK) of TEQ103. Methods: TEQ103 was evaluated IV in advanced stage human breast adenocarcinoma MCF-7 implanted in athymic female mice. Mice with approximately 500mm3 tumors were randomized and 2 schedules evaluated, daily x 10, (0, 1, 2, 4, 15 & 30mg/kg/injection), and intermittent on day1 & 10, (1, 5, 20, 75 & 150mg/kg/injection), 9 mice/group. Tumors were measured with a caliper and efficacy endpoints included tumor growth delay (TGD), complete regressions (CR), and Tumor Free Survivors (TFS). PK evaluation was performed post one IV administrations at 5, 20 & 75mg/kg (6 mice/ dose) over 8 hours in plasma, at 4 and 8h post injection in tumors, and at a late 10 day sampling in both matrices. Plasma and tumor concentrations were measured using LC-MS/MS SCIEX QTRAP 6500+ and PK parameters in plasma were determined using noncompartmental methods (Kinetica Software v5.1). Results: TEQ 103 was found highly active in MCF-7 tumor bearing mice with a large therapeutic index. With the daily schedule, the lowest active dose was 2mg/kg/injection (i.e., 20mg/kg total dose (TD)) with 2/9 TFS and 44 days TGD for the 7 relapsing mice. With the intermittent schedule, the lowest active dose was 5mg/kg/injection (10mg/kg TD) with 4/9 TFS and 56 days TGD for the 5 relapsing mice. At total dosages equal and above 40mg/kg TD, both schedules lead to 100% TFS (CRs lasted 121 days post tumor induction). This indicates that TEQ103 is schedule independent. Overall TEQ103 was well tolerated and did not induce body weight loss in the dose ranges studied. PK profiles in plasma showed biphasic kinetics of TEQ103 in MCF-7 bearing mice. The Cmax and AUC0-8h increase was approximately dose-proportional over the dose range studied. The 4h concentrations in plasma and tumor at 5, 20 and 75 mg/kg were 7.25, 16.7 and 178 ng/mL and 582, 1796 and 5709 ng/g, respectively. There was a very good tumor retention with levels of TEQ 103 detectable 10 days post treatment with 75mg/kg dose. Conclusion: These results demonstrate the significant durable antitumor effect of TEQ103 driven by the total dose administered regardless of schedule of administration, the wide therapeutic index and the concentration in the tumor tissue at levels markedly above the nM IC50 reached in vitro. These studies form the basis for PKPD Tumor Growth Inhibition modeling that will be used for projection of an efficacious starting dose in a subsequent breast cancer patients’ phase 1 clinical trial. Citation Format: Marie-Christine Bissery, Eef Hoeben, Elisabeth Bertrand, Sylvie Maubant, Maëva Albanese, Olivier Duchamp, Isabelle St-Jean, Mads K. Dalsgaard. TEQ103, a novel therapeutic for the treatment of estrogen receptor alpha positive (ERα+) breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5629.
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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) | 0.003 | 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".