El‐Deiry, Wafik S.

e14555 Background: Natural killer (NK) cells are innate lymphocytes that engage in direct cytotoxic responses against malignant cells and promote pro-inflammatory tumor microenvironments. While studies have predominantly focused on conventional NK cell subsets, recent findings uncovered adaptive and tissue-resident (TR) subsets with unique functional properties. The influence of distinct NK cell subsets on tumor immunobiology and clinical outcomes remains unknown. Methods: Single-cell RNA-sequencing (scRNA-seq) of primary, therapy-naïve tumors from 276 patients across 14 cancer types, as well as 39 patients treated with immune checkpoint blockade (ICB), was accessed through publicly available datasets. We employed systematic computational analyses to phenotype and examine intra-tumoral NK cells. Gene signatures for NK cell subsets were applied to bulk RNA-sequencing from 212,105 tumor samples to delineate their associations with clinical outcomes using the Caris CODEai database. Results: Six main subsets of NK cells were identified in solid tumors, including conventional CD56 dim and CD56 bright NK cells, alongside adaptive, TR adaptive, TR CD56 bright , and TR CD56 bright /adaptive subsets. Across cancer, TR adaptive NK cells emerged as the most prognostic subset, with high infiltration conferring significantly longer overall survival (HR[95% CI] = 0.68[0.66-0.69], p < 0.001) than conventional CD56 dim and CD56 bright subsets. This was also observed in cohorts of head and neck, non-small cell lung, and esophageal cancers, particularly those treated with ICB. Notably, elevated TR adaptive NK cell infiltration was more prognostic than high tumor mutational burden in these settings. This was most apparent in ICB-treated head and neck cancers (HR = 0.48[0.41-0.57], p < 0.001 vs HR = 0.90[0.76-1.04], p = 0.16). Additionally, TR adaptive NK cells were strongly correlated to the infiltration of CD8 + T cells and B cells in tumors. Underlying these observations, our scRNA-seq analyses demonstrated that TR adaptive NK cells exhibit the highest immunomodulatory activity of all subsets, expressing high levels of pro-inflammatory cytokines ( CCL3 , CXCL13 , and IFNG ) and low levels of immunosuppressive cytokines ( TGFB1 ). Mechanistically, this activity was linked to the upregulation of transcription factors associated with NK cell activation, function, and persistence and downregulation of genes related to stress response and exhaustion. Interestingly, scRNA-seq from paired pre- and post-ICB-treated tumors revealed a unique expansion of cytotoxic GZMB + TR adaptive NK cells after treatment. Conclusions: TR adaptive NK cells represent a novel subset of NK cells that may drive anti-tumor immune responses, particularly in the context of ICB treatment. Features of this unique population may be harnessed to design more effective NK cell-based therapies against solid tumors.

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.

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 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.

e14555 Background: 9-ING-41 (elraglusib) is a novel inhibitor of GSK-3β that has shown early signs of clinical benefit in a phase 1/2 clinical trial (ACT1801; NCT03678883). Early data support a multi-modal mechanism of action for elraglusib that targets both the tumor and immune system. Thus, the discovery and validation of biomarkers of drug sensitivity to elraglusib is a high priority. Here, we take inspiration from the literature on checkpoint inhibitor therapy and explore the potential of cytokines to predict elraglusib clinical response. Methods: Peripheral plasma samples from 59 patients enrolled in the 1801 phase 1/2 trial of elraglusib were assayed for 40 circulating cytokine levels. Patients advanced solid tumors refractory to standard treatments and received either elraglusib (1.0-15.0 mg/kg) as a single agent or in combination with other chemotherapies. Samples were taken from time points prior to elraglusib administration (pre-dose), after cycle 1, or after cycle 2. Each cytokine time point combination was used to stratify patients into high and low categories using an optimal cut-point determined using maximally selected rank statistics. Kaplan Meier and Cox Proportional Hazards analysis was used to determine the efficacy of each cytokine as a biomarker. The change in cytokine values between pre-dose and cycle 1 or pre-dose and cycle 2 was evaluated in a similar manner. Results: A total of 142 samples spanning eight different tumor histologies were collected and analyzed. A total of 240 cytokine-timepoint combinations were evaluated, and 53 significantly stratified patients by overall survival (p-value < 0.05). Of those, 35 showed that higher levels of the given cytokine correlated with a survival benefit and 18 a survival decrease. Notable among the cytokines demonstrating survival benefits were Granzyme B at Cycle 1 Day 4 (HR: 9.54, p-value:0.015) and TGF β at Cycle 1 Day 4 (HR: 8.48, p-value:0.0063). Strong hazard ratios were also observed for cytokines that correlated with survival decreases including TRAIL-R2 at Cycle 1 Day 2 (HR: 9.56e-02, p-value:0.0001), and IL-10 at Cycle 1 Day 4 (HR: 8.77e-02, p-value:0.007). Delta between timepoints was also able to stratifying patients by overall survival. Conclusions: Plasma cytokine profiling is a promising approach for discovery and validation of biomarkers prognostic for elraglusib clinical benefit. Numerous cytokines measured pre-dose stratified patients into significant survival groups suggesting a potential strategy for patient enrichment in clinical trials of elraglusib. These initial findings are being expanded by 1) increasing the cohort to accommodate histology specific investigations; 2) examining which cytokines are elraglusib response-specific versus drug-agnostic; and 3) combining cytokines in multivariate and machine learning models for optimal predictive capacity. Clinical trial information: NCT03678883 .