In patients with previously treated metastatic uveal melanoma, the historical 1 year overall survival rate is 37% with a median overall survival of 7.8 months. We conducted a multicenter, single-arm, open-label phase 2 study of tebentafusp, a soluble T cell receptor bispecific (gp100×CD3), in 127 patients with treatment-refractory metastatic uveal melanoma (NCT02570308). The primary endpoint was the estimation of objective response rate based on RECIST (Response Evaluation Criteria in Solid Tumours) v1.1. Secondary objectives included safety, overall survival, progression-free survival and disease control rate. All patients had at least one treatment-related adverse event, with rash (87%), pyrexia (80%) and pruritus (67%) being the most common. Toxicity was mostly mild to moderate in severity but was greatly reduced in incidence and intensity after the initial three doses. Despite a low overall response rate of 5% (95% CI: 2–10%), the 1 year overall survival rate was 62% (95% CI: 53–70%) with a median overall survival of 16.8 months (95% CI: 12.9–21.3), suggesting benefit beyond traditional radiographic-based response criteria. In an exploratory analysis, early on-treatment reduction in circulating tumour DNA was strongly associated with overall survival, even in patients with radiographic progression. Our findings indicate that tebentafusp has promising clinical activity with an acceptable safety profile in patients with previously treated metastatic uveal melanoma, and data suggesting ctDNA as an early indicator of clinical benefit from tebentafusp need confirmation in a randomized trial.

9515 Background: Investigational unengineered TIL cell therapy has shown promising activity in ICI-resistant metastatic melanoma but requires systemic high-dose IL2, which has well-described high-grade toxicity frequently requiring specialized management and limiting pt eligibility. OBX-115 autologous engineered TIL cell therapy does not require co-administration of IL2 due to its regulatable expression of membrane-bound IL15 (mbIL15) using the FDA-approved small-molecule drug acetazolamide (ACZ) to provide cytokine support for TIL expansion and persistence. Methods: This Phase 1 study (NCT05470283) assesses the OBX-115 regimen in pts with ICI-resistant unresectable/metastatic melanoma. OBX-115 is manufactured from the pt’s tumor tissue (surgical excision or core needle biopsy [CNB]). After lymphodepletion (cyclophosphamide, fludarabine), pts receive OBX-115 followed by ACZ once daily for up to 7 days; ACZ redosing (up to 7 days) is permitted at Wk 6 for non-responders. No systemic IL2 is administered. Peripheral blood and tumor tissue is collected for longitudinal immune profiling. Results: As of 02 Jan 2024, 9 pts (median age, 50 y) with ICI-resistant metastatic melanoma were infused with OBX-115 (median study follow up, 17 wks; range, 2–58 wks). Median lines of prior therapy was 3 (range, 1–6). OBX-115 was successfully manufactured for all pts, including from CNB tumor tissue (n = 5). The infusion product had a high proportion of CD8+ cells (≥96%) and stem-like cells (CD8+CD39-CD69-; median 76%) with very low PD-1 expression in the CD8+ population ( < 1%). Post-infusion safety included no DLTs, 3 Gr 3 nonhematologic TEAEs in 2 pts (abdominal pain, ALT elevation, syncope), and no Gr 4 nonhematologic TEAEs. ACZ was redosed and well-tolerated in 4 of 5 eligible pts. Among patients with minimum 12-wk follow-up (n = 6), ORR per RECIST v1.1 was 50% (2 CR, 1 PR, 3 SD); all responses occurred between Wk 6–18 and were ongoing, with longest response sustained > 12 mo. One pt developed new metastatic disease (liver) and progressed at Wk 24, despite continued target lesion reduction; no pt developed brain metastasis. Post-infusion ctDNA was not detectable in any of the responders at Day 14 or 42. Though OBX-115 had minimal NK cells ( < 1%), post-infusion peripheral blood and tumor biopsies showed NK cell expansion, consistent with trans-presentation of mbIL15 to circulating NK cells. Updated efficacy data on all infused pts will be presented. Conclusions: OBX-115regulatableengineeredTIL cell therapy was well-tolerated and produced consistently deepening and durable responses, indicating that OBX-115 may mediate CRs and durable clinical benefit in ICI-resistant metastatic melanoma without high-dose IL2. OBX-115 investigation continues in this and an ongoing Phase 1/2 multicenter study (NCT06060613). Clinical trial information: NCT05470283 .

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and its potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICI). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA sequencing (RNA-seq) was conducted on the formalin-fixed, paraffin-embedded and fresh frozen tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The age of the 71 patients with metastatic melanoma ranged from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy-responsive versus nonresponsive tumors. Responders showed significant enrichment of bacteriophages in the phylum Uroviricota, and nonresponders showed enrichment of several bacteria, including Campylobacter jejuni. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs. Significance: We analyzed the tumor microbiome and interactions with genes and pathways in metastatic melanoma treated with immunotherapy and identified several microbes associated with immunotherapy response and immune-related gene expression signatures. Machine learning models that combined microbe abundances and gene expression outperformed models using either dataset alone in predicting immunotherapy responses.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10%–20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, microbial graph attention (MEGA), to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of nine cancer centers in the Oncology Research Information Exchange Network. This package has three unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2,704 tumor RNA sequencing samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors.Significance: Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.