Seligson, Nathan D.

Malignant glioma is considered invariably recalcitrant, thus necessitating development of new therapeutic approaches. Spontaneously arising canine glioma exhibits important molecular and pathological similarities to malignant pediatric glioma, making it an invaluable model for testing novel therapies. We evaluated safety and activity of RNA lipid particle aggregates (LPAs) designed to provoke cancer immunogenicity in 10 dogs with histologically confirmed glioma. Vaccine manufacturing was feasible in all subjects and generally well tolerated. Median survival time was 123 and 155 days in dogs receiving three (Group A) or four (Group B) vaccines, respectively; this was increased from historical reporting of subjects receiving palliative care. Responding animals had a robust cytokine response following infusions. In animals receiving non-specific RNA-LPAs, there was localization of messenger RNA (mRNA) payloads to the brain tumor microenvironment and a rapid shift in immunologic gene signatures consistent with a viral response. These data demonstrate the ability to induce rapid viremic response in the tumor microenvironment following a single peripherally administered mRNA vaccine. Since RNA-LPAs are amenable to repeat boosts, these formulations may overcome challenges of tumor immunosuppression and therapeutic access and are currently under evaluation in first-in-human trials ( NCT04573140 , NCT06389591 ).

Background In this open-label, randomized, non-comparative, multicenter phase II study (Alliance A091401) we report on three expansion cohorts treated with nivolumab (N) with and without ipilimumab (N+I) and provide a multi-omic correlative analysis of actionable biomarkers. Methods Patients were randomized (non-comparative) to receive either N or N+I. The primary endpoint was a 6-month confirmed response rate (CRR) defined by Response Evaluation Criteria in Solid Tumors version 1.1. Secondary endpoints included treatment-related adverse events (TRAEs), progression-free survival, and overall survival. Multi-omic correlative analyses were conducted using samples from both the primary and expansion cohorts. Results A total of 66 patients were evaluated for the primary endpoint with disease including gastrointestinal stromal tumor (GIST, n=18), undifferentiated pleomorphic sarcoma (UPS, n=24), and dedifferentiated liposarcoma (DDLPS, n=24). Neither N nor N+I achieved a complete or partial response in the GIST expansion cohort. In DDLPS and UPS, the primary response endpoint of CRR was met with N+I (both 16.6%, 2/12) but not with N alone (both 8.3%, 1/12). In the GIST cohort, TRAE was higher with N+I treatment, halting enrollment as required per protocol. In a correlative analysis of patients for the expansion cohort and the original cohort (n=86), traditional biomarkers of immunotherapy response were not correlated with response in any histological subtype. Markers of genomic instability including the presence of gene fusions and increased subclonal mutations correlated with improved clinical outcomes. Conclusions This expansion cohort reaffirms the outcomes of A091401. There remains a pressing need to determine the role of and predictive biomarkers for immunotherapy in sarcoma. Trial registration number NCT02500797.

Abstract Surgical resection of early stage soft-tissue sarcomas (STS) is a potentially curative treatment; however, many STS tumors will recur. Predicting recurrence and survival outcomes for patients with early stage STS remains a challenge. In this study, we identify prognostic biomarkers from clinical and transcriptomic data form a large set of early stage STS. Primary tumor samples from 69 subjects with STS were sequenced using the Tempus xT targeted DNA and whole transcriptome next-generation sequencing platforms. The most common histologies included were liposarcoma (n=22), gastrointestinal stromal tumor (n=19), and leiomyosarcoma (n=12). As expected, high-grade tumors were associated with decreased DFS and OS times while tumor histology was only correlated with OS. Single sample gene set enrichment analysis (ssGSEA) values for seven Hallmark genesets were correlated with both DFS and OS; including pro-tumor survival pathways (p53, Apoptosis, TNF-α via NF-κB), tumor proliferation pathways (MTORC1, MYC Targets, Mitotic Spindle), and UV Response signaling. These pathways are associated with tumor proliferation as well as an immunosuppressive tumor microenvironment (TME). To assess the TME of these tumors we estimated immune cell infiltration using CIBERSORTx. Of the 22 cell types accounted for by CIBERSORTx, only elevated infiltration of M2 Macrophages were associated with poor DFS and OS. To further determine TME activation we assessed the expression of 74 known immune response associated genes. Only PDCD1 (PD-1) was associated with reduced DFS and OS times. Clustering on the nine variables identified here to correlate with both DFS and OS revealed two distinct clusters demonstrating similar histologies. While histologies were similar across clusters, cluster 2 exclusively included high-grade tumors while cluster 1 was made up of 57.4% high-grade tumors. Sub-classifying cluster 1 into low and high-grade subgroups demonstrated a stepped biomarker expression pattern associated with both tumor grade and cluster membership. Using established TME genesets, high-grade tumors demonstrated higher tumor proliferative scores than low-grade tumors, while cluster 2 tumors demonstrated increased tumor associated macrophage signaling. In a multivariable model, cluster membership outperformed tumor grade and histology as the only significant predictor of DFS or OS. Taken together, while tumor grade is a strong predictor of clinical outcomes following surgical resection in STS, immunosuppressive signaling patters may help to identify patients at the highest risk. Citation Format: Nathan David Seligson, Yan W. Asmann, Tariq Almerey, Steven Attia, Sanjay P. Bagaria. Immune-suppressive tumor microenvironment leads to poor survival following curative intent surgical resection in soft-tissue sarcomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 990.

Abstract Defining patient-to-patient similarity is essential for the development of precision medicine in clinical care and research. Conceptually, the identification of similar patient cohorts appears straightforward; however, universally accepted definitions remain elusive. Simultaneously, an explosion of vendors and published algorithms have emerged and all provide varied levels of functionality in identifying patient similarity categories. To provide clarity and a common framework for patient similarity, a workshop at the American Medical Informatics Association 2019 Annual Meeting was convened. This workshop included invited discussants from academics, the biotechnology industry, the FDA, and private practice oncology groups. Drawing from a broad range of backgrounds, workshop participants were able to coalesce around 4 major patient similarity classes: (1) feature, (2) outcome, (3) exposure, and (4) mixed-class. This perspective expands into these 4 subtypes more critically and offers the medical informatics community a means of communicating their work on this important topic.