Abstract CT014: Initial results from the Phase I study of MSC-1, a humanized anti-LIF monoclonal antibody, in patients with advanced solid tumors
Bibliographic record
Abstract
Abstract Background: Leukemia Inhibitory Factor (LIF) is a pleiotropic cytokine involved in many physiological and pathological processes. LIF is highly expressed in a subset of tumors across multiple solid tumor types and has been shown to correlate with poor prognosis. LIF is hypothesized to contribute to tumor growth and progression by acting on multiple aspects of cancer biology, including immunosuppression of the tumor microenvironment (TME), and regulation of cancer initiating cells (CICs), which are thought to underpin tumor growth, metastasis, and resistance to therapy. MSC-1 is a first-in-class humanized IgG1 monoclonal antibody that potently and selectively inhibits LIF. Blocking LIF with MSC-1 decreased tumor growth in multiple mouse tumor models, drove reprogramming of the TME through effects on immunosuppressive macrophages, and generated durable regressions when combined with anti-PD1. These findings form the basis of a robust therapeutic hypothesis, that MSC-1 treatment may lead to clinical activity in multiple cancer indications. Methods: The Phase 1 study of MSC-1 is enrolling patients with advanced relapsed/refractory solid tumors. The study employs an accelerated 3+3 escalation design to explore safety, PK, LIF peripheral target engagement, immuno-regulatory activity, and preliminary anti-tumor activity of MSC-1. Patients receive treatment with MSC-1 intravenously once every three-weeks until confirmed disease progression or intolerable toxicity. At the top three dose levels, the cohorts will be expanded to further assess safety, PK/target engagement, and to preliminarily assess MOA biomarkers in paired pre- and on treatment tumor tissue from patients. The Dose and Expanded Escalation will enroll patients without regard to their pretreatment LIF tumor levels. Results: As of January 28, 2019, dosing has occurred in 14 patients in the 5 preplanned Dose Escalation cohorts (225mg-1500mg) as well as in 15 patients in the expanded cohorts at 750mg and 1125mg doses for additional safety, PK/PD and biomarker analysis, including analysis of pretreatment and on treatment tumor biopsies in a subset. There have been no DLTs observed at any dose, and analysis of data to select a RP2D for Dose Expansion is ongoing. Citation Format: Alison Schram, Anna Spreafico, Marc Oliva, Irene Brana, Elena Garralda, Nehal Lakhani, Daniel Von Hoff, Erkut Borazanci, Naimish Pandya, Kimberly Hoffman, Robin Hallett, Patricia Giblin, Judit Anido, Adrianne Kelly, Robert Wasserman, Joan Seoane, Lillian Siu, David M. Hyman, Josep Tabernero. Initial results from the Phase I study of MSC-1, a humanized anti-LIF monoclonal antibody, in patients with advanced solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT014.
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 | 0.001 | 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) | 0.001 | 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".