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Kellinger, Caroline

Mayo Clinic

Actuate Therapeutics, Inc. (United States)

Citations 3

Machine learning and statistical prediction of overall survival (OS) from pre-dose plasma biomarkers in a randomized phase 2 trial (1801 Part 3B) of the GSK-3 inhibitor elraglusib in metastatic pancreatic ductal adenocarcinoma (mPDAC): Application toward p
Weiskittel, Taylor M. , Koukol, Austin , Kellinger, Caroline, Seifarth, Christopher, Zhang, Leiqing , Carneiro, Benedito A. , El‐Deiry, Wafik S. , Mazar, Andrew P. , Ugolkov, Andrey , Seifarth, Christopher, Li, Hu , Mahalingam, Devalingam

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: 4185-4185

10.1200/jco.2025.43.16_suppl.4185 Get It

4185 Background: Elraglusib is a first-in-class inhibitor of GSK-3ß, a well-credentialed target in cancer implicated in intrinsic oncologic processes and tumor immune response. Preliminary results of the 1801 Part 3B trial (NCT03678883) showed statistically significant benefits for elraglusib+GnP versus GnP for 1-year survival and mOS in mPDAC (companion abstract: Mahalingam et al.). We investigated plasma levels of cytokines/chemokines/soluble cell receptors/growth factors (CCSG) as potential biomarkers of favorable outcomes on elraglusib. Methods: Forty CCSGs were evaluated in pre-dose plasma from patients with previously untreated mPDAC enrolled in 1801 Part 3B treated with GnP (n = 78) or elraglusib+GnP (n = 155) using a Luminex immunoassay. Using Kaplan-Meier statistics and cutpoint determination, CCSGs were assessed for OS predictive ability in the elraglusib+GnP arm. Multivariate models were constructed to predict binarized survival at 12 months using machine learning (ML). Fivefold cross-validation was used in both analyses, and all methods were applied to the GnP arm to identify elraglusib+GnP specific predictors. Results: Data shown as of November 15, 2024. Multiple CCSGs significantly stratified elraglusib+GnP patients. The most extreme prognosticators were IFN-ß (average HR = 2.34), and PD-L1 (average HR = 0.52) (HR shown as high CCSG vs low CCSG). Screening of different ML approaches ranked logistic regression at the top, and hyperparameter grid search identified stochastic gradient solver with ridge regularization as the optimal method. The model had an accuracy of 88% (SD: 3.9%) and a balanced accuracy of 80% (SD: 8.5%). IFN-beta had the most substantial effect size (odds ratio (OR) = 72.28), followed by IL-18 (OR = 23.38) and PD-L1 (OR = 15.32). All other CCSGs had an OR between 0.03 and 6.71. When this model was applied to patients in the GnP arm, accuracy was 68.4%, and balanced accuracy was 43.1%. Conclusions: Many CCSG biomarkers were identified as promising predictors of survival benefit in mPDAC patients treated with elraglusib+GnP. Both univariate statistical and multivariate ML approaches show predictive significance with high interpretability. The initial ML model is specific to elraglusib treatment, not GnP alone. These results indicate that patients’ initial immune state plays a role in response to elraglusib+GnP. However, single CCSGs for enrichment currently exclude too many patients ( > 75%), and thus, panels of biomarkers are being investigated with ML to overcome this limitation. The 1801 Part 3B clinical trial recruitment has been completed, and updated biomarker models reflective of topline OS data, available by April 2025, will be presented.
Identification of immune biomarkers in treatment-naive patients with metastatic pancreatic cancer treated with the GSK-3 inhibitor elraglusib (9-ING-41) in combination with gemcitabine/nab-paclitaxel in the 1801 phase 2 study.
Weiskittel, Taylor M. , Koukol, Austin , Kellinger, Caroline, Zhang, Leiqing , Carneiro, Benedito A. , El‐Deiry, Wafik S. , Mazar, Andrew P. , Li, Hu , Ugolkov, Andrey

Journal of Clinical Oncology | July 8, 2024 | Volume: 42 | Issue: 16_suppl | Pages: e16331-e16331

10.1200/jco.2024.42.16_suppl.e16331 Get It

e16331 Background: Elraglusib (9-ING-41), a potent and selective GSK-3 inhibitor, is a targeted anticancer agent with clinical activity in phase 1 trial and undergoing clinical development for the treatment of metastatic pancreatic ductal adenocarcinoma (mPDAC). Elraglusib (9-ING-41) displayed immune-modulatory activity in preclinical models and modulation of serum cytokine profile in clinical specimens. Here, we investigated the correlation between plasma levels of cytokines/chemokines/soluble cell receptors/growth factors (CCSG) and clinical outcomes of patients with mPDAC treated with elraglusib and gemcitabine/nab-paclitaxel (GnP) in an exploratory study. Methods: CCSGs were evaluated in the pre-dose plasma samples of patients with newly diagnosed mPDAC enrolled in the 1801 phase 2 study (NCT03678883) treated with GnP (n = 13) or elraglusib/GnP (n = 32). Using a Luminex immunoassay, 40 CCSGs were screened as predictive biomarkers of median overall survival (mOS) in the elraglusib/GnP arm using 5-fold cross-validation and maximally selected rank statistic cutpoint determination. A subset of CCSGs (n = 10) was remeasured using an MSD immunoassay with greater sensitivity. Maximally selected rank statistic cutpoint determinations were conducted using MSD results for elraglusib/GnP samples with mOS and median progression free survival (mPFS). P values < 0.05 were considered statistically significant. Results: Luminex screening revealed several CCSGs significantly stratified elraglusib/GnP patients by mOS. IL-6 and IL-8 were identified as top candidates with stable and significant results on cross-validation. Using the MSD assay, both were confirmed to stratify elraglusib/GnP patients by OS and extended to analyze PFS. Low level of IL-8 conferred a better OS prognosis (HR: 0.0919, 95%, CI: 0.0205-0.411, P < 0.001) than low IL-6 (HR: 0.205, 95%, CI: 0.063-0.665, P = 0.005) in the elraglusib/GnP treated patients. Correlations with mPFS were similar in the elraglusib/GnP patients for IL-6 (HR: 0.248, 95% CI: 0.072-0.848, P = 0.02) and IL-8 (HR: 0.297, 95%, CI: 0.111-0.743, P = 0.01). Conclusions: Preliminary results of our exploratory study identified low plasma levels of IL-6 and IL-8 prior to elraglusib/GnP treatment as potential predictive biomarkers associated with improved outcomes in previously untreated patients with mPDAC. The 1801 Part 3 Arm B clinical trial recruitment has been completed. We plan to analyze additional pre-dose plasma samples obtained from approximately 200 patients by April 2024. These will be analyzed using interim OS data available by April 2024 and included in the final presentation. Clinical trial information: NCT03678883 .
Mutational analysis of cfDNA to identify predictive biomarkers in previously untreated patients with metastatic pancreatic cancer receiving the GSK-3 inhibitor elraglusib (9-ING-41) in combination with gemcitabine/nab-paclitaxel in the 1801 phase 2 study.
Weiskittel, Taylor M. , Koukol, Austin , Kellinger, Caroline, Mazar, Andrew P. , Ugolkov, Andrey , Li, Hu

Journal of Clinical Oncology | July 3, 2024 | Volume: 42 | Issue: 16_suppl | Pages: e16306-e16306

10.1200/jco.2024.42.16_suppl.e16306 Get It

e16306 Background: Glycogen Synthase Kinase-3beta has been well-credentialed as a therapeutic target in patients with advanced cancer including pancreatic cancer. Elraglusib (9-ING-41), a novel best-in-class GSK-3 inhibitor, is being developed in combination with gemcitabine/nab-paclitaxel (GnP) as first-line therapy for patients with metastatic pancreatic cancer (mPDAC). Using liquid biopsy samples from an ongoing randomized phase 2 trial (1801 Part 3B; NCT03678883), we examined whether gene mutations in cfDNA correlated with clinical outcomes in mPDAC patients treated with GnP or elraglusib/GnP. Methods: Pre-dose plasma samples were obtained from 37 (GnP arm) and 89 (elraglusib/GnP arm) mPDAC patients previously untreated for advanced disease. Mutational analysis of cfDNA extracted from plasma samples was performed by Tempus (Chicago, IL) using the xF+ platform. The Tempus xF+ assay is an NGS cfDNA liquid biopsy tumor profiling assay for identifying genomic alterations in 523 genes. Tempus xF+ reports were used for analysis of gene mutations. Results: In 126 pancreatic cancer patients, frequently mutated genes ( > 10%) consisted of KRAS (93/126, 74%), TP53 (79/126, 63%), CDKN2A (26/126, 21%), DNMT3A (25/126, 20%), NOTCH1/2 (25/126, 20%), and MLL3 (23/126, 18%). Gain-of-function mutations in KRAS, and loss-of-function mutations of TP53, and CDKN2A genes were associated with worse overall survival (OS) in patients treated with elraglusib/GnP (P < 0.05) but not in GnP-treated patients. Multivariate analysis of frequently mutated genes showed that patients with double (KRAS+TP53) and triple (KRAS+TP53+CDKN2A) mutations had significantly worse OS only in the elraglusib/GnP arm. The presence of DNMT3A, NOTCH1/2 or MLL3 gene mutations did not correlate with any clinical outcomes. Conclusions: Our preliminary analysis of gene mutations in liquid biopsy samples obtained from patients in the ongoing 1801 Part 3B phase 2 trial identified potential predictive biomarkers of clinical outcome in mPDAC patients treated with combination of elraglusib/GnP. Clinical trial information: NCT03678883 .