Kokabi, Nima

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 Minimally invasive image-guided tumor ablation techniques have been established as safe, effective methods to treat a variety of unresectable soft tissue tumors. Standard thermal ablation methods include radiofrequency ablation, microwave ablation, and cryoablation. However, newer non-thermal and/or non-invasive ablation techniques are now available as alternative options to treat soft tissue tumors, particularly those that are near critical structures or otherwise susceptible to thermal energy sink effects. The 4 types of emerging ablation techniques discussed in this review are as follows: irreversible electroporation, pulsed electric field, high-intensity focused ultrasound, and histotripsy. While the clinical trials evaluating the safety and efficacy of these ablation techniques are in their early stages, initial results are promising in the treatment of various cancers at different stages. These include potential synergistic effects when combined with chemotherapy and immunotherapy.

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