Taube, Janis M

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 .

Multiplex immunofluorescence and immunohistochemistry (mIF/IHC) are increasingly employed antibody-based technologies that use tissue sparingly and facilitate the detection of co-localized or neighboring biomarkers. Specifically, these platforms enable spatial analyses of the tumor microenvironment as well as extended applications, for example, describing normal tissue anatomy, autoimmunity, infectious diseases, etc. mIF/IHC has greatly enhanced biomarker discovery efforts, and a growing number of studies suggest superiority to traditional IHC. Standardization of staining approaches, reporting of image analysis strategies and resultant data is critical for facilitating cross-study comparisons, validation, deployment, and generalization of findings. To address this challenge, The Society for Immunotherapy of Cancer (SITC) previously published two articles providing best practice guidelines for mIF/IHC staining, image analysis, and data sharing. Here, SITC convened stakeholders to develop the third article in the series, a consensus checklist for scientific reporting of mIF/IHC data to support and complement the best practice guidelines. The checklist includes critical components of mIF/IHC applications to be defined within publications such as detailed descriptions of analytical validation; image acquisition, selection, and registration methods; and cell clustering and spatial analysis strategies, amongst others. Such information will help with data reproducibility and comparison across studies towards future drug and assay development.

Since the first approval for immune checkpoint inhibitors (ICIs) for the treatment of cutaneous melanoma more than a decade ago, immunotherapy has completely transformed the treatment landscape of this chemotherapy-resistant disease. Combination regimens including ICIs directed against programmed cell death protein 1 (PD-1) with anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) agents or, more recently, anti-lymphocyte-activation gene 3 (LAG-3) agents, have gained regulatory approvals for the treatment of metastatic cutaneous melanoma, with long-term follow-up data suggesting the possibility of cure for some patients with advanced disease. In the resectable setting, adjuvant ICIs prolong recurrence-free survival and several are FDA-approved. Although not yet approved, neoadjuvant ICIs have also shown to improve event-free survival and remains an ongoing area of investigation. Other immunotherapy strategies, such as oncolytic virotherapy for injectable cutaneous melanoma, bispecific T-cell engager therapy for HLA-A*02:01 genotype-positive uveal melanoma, and lifileucel, an autologous tumor-infiltrating lymphocyte therapy, for unresectable or metastatic melanoma are also available to patients. Despite the remarkable efficacy of these regimens for many patients with cutaneous melanoma, traditional immunotherapy biomarkers (ie, programmed death-ligand 1 expression, tumor mutational burden, T-cell infiltrate and/or microsatellite stability) have failed to reliably predict response. Furthermore, ICIs are associated with unique toxicity profiles, particularly for the highly active combination of anti-PD-1 plus anti-CTLA-4 agents. The Society for Immunotherapy of Cancer (SITC) convened a panel of experts to develop this clinical practice guideline on immunotherapy for the treatment of melanoma, including rare subtypes of the disease (eg, uveal, mucosal), with the goal of improving patient care by providing guidance to the oncology community. Drawing from published data and clinical experience, the Expert Panel developed evidence- and consensus-based recommendations for healthcare professionals using immunotherapy to treat melanoma, with topics including therapy selection in the advanced and perioperative settings, intratumoral immunotherapy, when to use immunotherapy for patients with BRAF V600-mutated disease, management of patients with brain metastases, evaluation of treatment response, special patient populations, patient education, quality of life, and survivorship, among others.