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Zhang, Leiqing

https://orcid.org/0000-0002-9395-1862

Mayo Clinic

Brown University

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 .
Abstract 6426: Identification of potential immune biomarkers for GSK-3 inhibitor elraglusib (9-ING-41) in patients with relapsed/refractory metastatic cancer
Weiskittel, Taylor M. , Zhang, Leiqing , Koukol, Austin , Carneiro, Benedito A. , Ugolkov, Andrey , El‐Deiry, Wafik S. , Mazar, Andrew P. , Huntington, Kelsey E. , Li, Hu

Cancer Research | March 22, 2024 | Volume: 84 | Issue: 6_Supplement | Pages: 6426-6426

10.1158/1538-7445.am2024-6426 Get It

Abstract Cytokines mediate strong immunomodulatory effects in cancer. Elraglusib (9-ING-41), an inhibitor of GSK-3, is a potent antitumor and immune-modulatory agent in phase 2 clinical trials for the treatment of various cancers. Here, we examined the immune environment of elraglusib-treated cancer patients by measuring peripheral blood protein levels to explore whether the expression level of cytokines/chemokines/soluble cell receptors/growth factors (CCSG) is correlated with clinical outcome. Using a customized Luminex platform, the expression of forty CCSG hypothesized to be linked to GSK-3 activity was assessed in pre-dose plasma samples obtained from 45 cancer patients with relapsed/refractory metastatic disease (NCT03678883; the 1801 trial). All patients in the 1801 trial were treated with elraglusib (dose range: 1-15 mg/kg) either as a single agent (Part 1; n=21) or in combination with chemotherapy (Part 2; n=24). Pre-dose peripheral blood protein levels were examined as binary predictors of clinical outcome using optimal cutoff points determined by maximally selected rank statistics. In the aggregate Part 1 and 2 populations (n=45), we identified 13 CCSG that significantly stratified the cohort by overall survival (OS). High pre-dose levels of CD95 and TNFRSF10C were associated with better OS. CD95 was a better prognostic of OS than TNFRSF10C (HR: 2.27, 95% CI: 1.10-4.67, p-value: 0.023). Low pre-dose levels of 11 CCSG were also significantly associated with favorable OS, with IL-8 being the most predictive (HR: 0.137, 95% CI: 0.0545-0.346, p-value: &lt;0.0001). Part 1 and 2 predose samples were also analyzed separately, and many of the biomarkers identified in the aggregate analysis retained significance in the separated analysis. In Part 1, CXCL5, IFN-alpha, and IL-18 emerged as unique markers, and in Part 2, CCL22 was the single unique marker.The results of our exploratory study identified several putative biomarkers of elraglusib clinical benefit and demonstrated potential immunomodulatory mechanisms of elraglusib that will be used to inform the further clinical development of elraglusib for the treatment of metastatic cancer. Citation Format: Taylor Weiskittel, Kelsey Huntington, Leiqing Zhang, Austin Koukol, Benedito A. Carneiro, Hu Li, Andrey Ugolkov, Wafik El-Deiry, Andrew Mazar. Identification of potential immune biomarkers for GSK-3 inhibitor elraglusib (9-ING-41) in patients with relapsed/refractory metastatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6426.