Gierman, Hinco J.

Summary Functional ex vivo assays using live tumor tissues have demonstrated strong predictive accuracy for response to immune checkpoint inhibitors (ICIs) but are not scalable, requiring manual processing of large resections collected at academic centers. Here, an ex vivo live tumor fragment (LTF) platform was developed using standard-of-care biopsies from 228 patients with suspected malignancy collected across prospective, multicenter observational trials and biobanks. Hierarchical clustering of ICI-mediated changes in cytokine production identified two groups: responders and nonresponders. A binary classifier (elive index) using 8 cytokines achieved an AUC of 0.99 for cluster prediction. elive index correctly predicted clinical benefit in 93% (26/28) of patients ( P = 3.2x10 -5 ) and accurately identified 83% (10/12) of objective responders. Critically, elive responders were identified among biomarker-negative patients, highlighting the platform as a scalable approach that complements existing companion diagnostics and expands the population of patients identified to benefit from ICI therapy.

2646 Background: Immune checkpoint inhibitors (ICIs) have transformed the management of many advanced cancers but identifying patients who are likely or unlikely to benefit from ICI treatment remains a critical challenge. Biomarkers, such as PD-L1, mismatch repair deficiency, and tumor mutational burden, capture only static, unidimensional features of the complex tumor microenvironment, and therefore inadequately predict response to immunotherapy in patients. In contrast, live tumor fragments (LTFs) preserve the full complexity of the tumor microenvironment and enable functional ex vivo assessments of ICI activity. Previous efforts have had limited clinical applicability because they required larger resection specimens often collected at a single academic center. Here, the predictive capability of an ex vivo platform using core needle and forceps biopsies from multiple clinical sites was assessed and compared to approved biomarkers. Methods: Patients with eligible solid tumors (where ICI has an indication, including renal, non-small cell lung, bladder, colorectal, and triple-negative breast cancer, and others) were enrolled in ongoing, prospective observational trials (NCT05478538, NCT05520099, NCT06349642). Biopsies were cut into LTFs, encapsulated in hydrogel, and treated sequentially with IgG antibody followed by ICI (αPD-[L]1 with or without αCTLA-4). Cytokine production was assessed by a multiplexed bead-based immunoassay at multiple time points during ex vivo treatment. Using receiver operating characteristic and precision recall analyses, we identified 9 predictive cytokines (including IFN-γ, granzyme B, and CXCL9/10), which were used to develop the Elephas score (ELP-score) to assess cytokine response to ex vivo ICI treatment. Results: Of 167 eligible patient specimens, 85% (n = 142) passed quality control metrics and 130 were used for model development. Hierarchical clustering of cytokine production revealed that 27% (n = 35) of patient specimens exhibited a cytokine response to ICI. In a validation set of 20 tumors, collected from patients who were subsequently treated with ICI, ELP-score positivity correctly identified 9 of 11 patients (82%) who had an objective response (PR/CR) to ICI, including 2 patients who were negative for FDA-approved standard-of-care ICI biomarkers. Furthermore, 5 of 5 patients (100%) with clinical progressive disease were correctly characterized as ELP-score negative. Conclusions: Using routine biopsy specimens, the ex vivo live tumor platform accurately identifies patients with clinical response to ICI therapy, including those incorrectly identified by conventional biomarkers. Ongoing efforts will test these findings in an additional validation set. If confirmed, the ex vivo LTF platform could enable the identification of patients likely to benefit from ICI therapy. Clinical trial information: NCT05478538 , NCT05520099 , NCT06349642 .

Abstract Background While immune checkpoint inhibitors (ICIs) provide durable clinical benefit in a subset of patients, current biomarkers to predict response lack accuracy. Ex vivo cytokine profiling has shown promise for improved accuracy but has been mostly limited to ICIs targeting PD-1 [Voabil et al, 2021]. This poses the question of whether ICIs beyond αPD-1 – such as CTLA4 blockade, which has been reported to act within the draining lymph node – would be amenable to similar approaches. The Elephas platform characterizes response to ICIs in live tumor fragments (LTFs) from core needle biopsies (CNBs) and resections using longitudinal cytokine profiling. Using a panel of 7 clinically relevant ICI regimens, we demonstrate cytokine responses across diverse tumor types, characterize similarities and differences in cytokine response profiles across different ICIs, and explore specimen variability in responses across ICI treatments. Methods CNBs were collected through 3 observational clinical trials (NCT05478538, NCT05520099, NCT0634962) and a biobank collection study, while resections were procured from NCI CHTN. LTFs were generated using an automated cutting device and encapsulated in hydrogel. LTFs were treated with mono (αPD-1, αPD-L1, αCTLA4, αLAG-3) or combination therapy (αPD-1/αCTLA4, αPD-1/αLAG-3, αPD-L1/αCTLA4) using a sequential treatment strategy in which isotype control followed by ICI were added to the same tissue in a single well. This approach enabled the comparison of control and treatment conditions while mitigating the effects of tumor heterogeneity. Production rates for 46 cytokines were measured using a multiplex assay. Remaining T-cell reactivity was also evaluated at the end of the assay to better understand the presence of functional T cells in LTFs. Results Unsupervised hierarchical clustering of cytokine profiling data from CNB LTFs across 129 patients identified defined responder and non-responder clusters. Within the response cluster, 4 subclusters with distinct immune phenotypes were identified. While tight clustering of samples treated with the same ICI was not observed, some enrichment of samples treated with combination ICIs was observed within individual subclusters. Further, cytokine responses to αCTLA4 monotherapy were observed, suggesting that CTLA4 blockade may act beyond the draining lymph node. LTFs from resections enabled the characterization of cytokine response profiles across treatment conditions within individual specimens, including the magnitude of cytokine response and variability in cytokine response profiles. Evaluation of T-cell reactivity provided further insight into the presence of functional T-cells in LTFs and the extent of T-cell activation achieved by ICI treatment. Conclusions This study demonstrates the platform’s ability to recapitulate diverse mechanisms of immune activation ex vivo, enabling the characterization of cytokine responses to clinically relevant ICI mono or combination therapy in live tumor tissue and supporting future efforts to improve ICI response prediction beyond αPD-1. Citation Format: Pichet Adstamongkonkul, Pierre Cunin, Santanu Bhattacharya, Tanmay Kulkarni, Amreen Nasreen, Nathan Marhefke, Nina Chen, T S. Ramasubramanian, Laura Hrycyniak, Julie Zweng, Erika von Euw, Christina Vivelo, Sean Caenepeel, Debabrata Mukhopadhyay, Hinco Gierman, Hilario Ramos. Characterization of αPD1, αPD-L1, αCTLA4, and αLAG3 as mono and combination therapy in live tumor fragments using an ex vivo cytokine profiling platform [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr B032.

Abstract Background: Immune checkpoint inhibition (ICI) in combination with chemotherapy is associated with improved outcomes in a subset of patients with triple negative breast cancer (TNBC). However, biomarkers for predicting patient response, such as PD-L1 expression, have limited predictive efficiency. Voabil et al. has shown that ex vivo cytokine profiling of live tumor tissue resections treated with αPD-1 can predict patient response to ICI (Voabil et al., Nat Med. 2021). However, this method requires large amounts of tissue to address intra-specimen tumor heterogeneity, which is not feasible with standard of care (SOC) diagnostic core needle biopsies (CNBs) for breast cancer, where tissue is scarce. We show for the first time that ex vivo cytokine profiling is possible in live tumor fragments (LTFs) generated from CNBs in breast tissue. Methods: We present a cytokine profiling platform to assess response to ICI treatment in LTFs generated from CNBs. CNBs were collected from patients who were identified as potential candidates for SOC ICI (by treating physician) and enrolled in one of two prospective observational clinical trials (NCT05520099 and NCT06349642). CNBs were cut by an automated, proprietary cutting instrument to generate LTFs ofapproximately 300 µm in thickness. To address tissue heterogeneity and mitigate tissue scarcity in CNBs, we used a sequential treatment strategy in which control and ICI treatment were applied to LTFs in the same well, in a phased approach. This strategy provides a solution for the variability observed in cross-well comparisons. LTFs were encapsulated in hydrogel and treated with IgG control followed by αPD-1 (BioXCell). Cytokine production rates were measured longitudinally using multiplex assays assessing>45 cytokines, including 15 cytokines assayed by Voabil et al., and the fold changes of cytokine production rates in response to ICI over IgG control were calculated. Results: Using non-breast tumor tissue, we validated that our platform can measure changes in cytokine production in LTFs following sequential treatment, and that these measurements are comparable to those observed in a cross-well setting. In a small cohort of TNBC specimens, we show changes in cytokine production rates in response to ex vivo sequential control and ICI treatment. Ten cytokines, including IFN-γ and CXCL10, shown to be predictive of patient response to ICI in Voabil et al. were found upregulated in response to αPD-1 in TNBC specimens. Future determination of correlation with clinical response data (pathological complete response for early stage and RECIST 1.1 for metastatic patients) gathered from NCT05520099 and NCT06349642 will be used to validate platform responders and non-responders. To date, 11 patients with confirmed TNBC diagnoses have enrolled in these clinical studies. Conclusion: We report, for the first time to our knowledge, the ability to detect immune checkpoint inhibitor responses in live TNBC tissue obtained via CNBs. This proof-of-concept lays the groundwork for integrating functional tissue responses with clinical correlation data, with important implications for guiding current ICI therapies and advancing this platform for use in next-generation immuno-oncology treatments for TNBC. Citation Format: P. P. Advani, J. Harvey, J. Polley, M. Weidner, A. Arnold, D. Haley, R. Bollam, R. Rao, S. Chumsri, K. Hugghins, M. Acampora, C. Vivelo, H. Hernan, L. Hrycyniak, J. Zweng, H. Gierman, S. Bhattacharya, D. Mukhopadhyay. Ex vivo cytokine profiling of live triple negative breast cancer patient specimens from core needle biopsies illustrates proof of concept to assess tumor response to immune checkpoint inhibition [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-01-08.

TPS2689 Background: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, existing FDA approved companion diagnostic biomarkers like PD-L1, dMMR/MSI-H and TMB have low accuracy in predicting response. Ex vivo cytokine profiling of live tumor samples has shown promise as an improved means of predicting response to PD-1 blockade (Voabil, et al. Nat Med. 2021), but this approach has been limited to tumor resections given the need for large amounts of tissue. Here we present three clinical trials that leverage a novel approach using limited tissue from a single core needle biopsy (CNB) (20 gauge or larger). A sequential ex vivo treatment strategy is used, eliminating the need for a separate control arm and addressing challenges with tumor heterogeneity, particularly in CNBs where tissue is limiting. Using a specialized instrument, CNBs are cut into live tumor fragments (LTFs) which are viable in culture and retain the native tumor microenvironment, enabling cytokine profiling in response to ICI treatment ex vivo. Methods: ELEPHAS-01 (NCT05478538), ELEPHAS-02 (NCT05520099) and ELEPHAS-04 (NCT06349642) are observational prospective clinical trials initiated to characterize the accuracy of this approach for predicting ICI response. Over 750 patients that are being considered for standard of care (SOC) ICI therapy in the metastatic/relapse or neoadjuvant setting will be enrolled (Table). Fresh live CNBs are collected prior to treatment start and processed within 24 hrs enabling prediction of results within 72 hrs of receipt. LTFs are treated using a strategy where control (IgG) and SOC ICI treatments are performed sequentially on the same tissue in a single well. Changes in the cytokine secretion rates are then compared between ICI and control to characterize immunotherapy response. Additionally, tissue viability and tumor content measurements are used to assess tissue quality. Clinical response is measured using pathologic response in patients receiving neoadjuvant ICI therapy, while RECIST v1.1 is used in all other patients. The primary objective of these trials is to determine the platform’s ex vivo accuracy (e.g., sensitivity, specificity) for predicting clinical response to ICIs and comparing it to the accuracy of PD-L1, dMMR/MSI-H and TMB. Clinical trial information: NCT06349642 , NCT05478538 , NCT05520099 . ELEPHAS-01 (Lung) ELEPHAS-02 (Hoosier) ELEPHAS-04 (Mayo) Setting Metastatic & recurrent Metastatic & recurrent Metastatic, recurrent & neoadjuvant Tumor type Lung Bladder, kidney, colorectal, head and neck, lung, melanoma, endometrial Metastatic/recurrent: lung, skin, esophageal, cervical, endometrial, colon, liver, kidney, bladder Neoadjuvant: breast–TNBC, lung Enrollment as of 1/27/2025 26 44 20 Est. total enrollment 216 216 324 Clinical endpoints RECIST v1.1 RECIST v1.1 RECIST v1.1 & Pathologic response at surgery