Myelomodulatory treatments augment the therapeutic benefit of oncolytic viroimmunotherapy in murine models of malignant peripheral nerve sheath tumors.

Introduction: Malignant peripheral nerve sheath tumors (MPNST) pose a significant therapeutic challenge due to high recurrence rates after surgical resection and a largely ineffective response to traditional chemotherapy. An alternative treatment strategy is oncolytic viroimmunotherapy, which can elicit a durable and systemic antitumor immune response and is Food and Drug Administration (FDA)-approved for the treatment of melanoma. Unfortunately, only a subset of patients responds completely, underscoring the need to address barriers hindering viroimmunotherapy effectiveness. Methods: Here we investigated the therapeutic utility of targeting key components of the MPNST immunosuppressive microenvironment to enhance viroimmunotherapy's antitumor efficacy in three murine models, one of which showed more immunogenic characteristics than the others. Results: Myelomodulatory therapy with pexidartinib, a small molecule inhibitor of CSF1R tyrosine kinase, and the oncolytic herpes simplex virus T-VEC exhibited the most significant increase in median survival time in the highly immunogenic model. Additionally, targeting myeloid cells with the myelomodulatory therapy trabectedin, a small molecule activator of caspase-8 dependent apoptosis, augmented the survival benefit of T-VEC in a less immunogenic MPNST model. However, tumor regressions or shrinkages were not observed. Depletion experiments confirmed that the enhanced survival benefit relied on a T cell response. Furthermore, flow cytometry analysis following combination viroimmunotherapy revealed decreased M2 macrophages and myeloid-derived suppressor cells and increased tumor-specific gp70+ CD8 T cells within the tumor microenvironment. Discussion: In summary, our findings provide compelling evidence for the potential to leverage viroimmunotherapy with myeloid cell targeting against MPNST and warrant further investigation.

The Tumor Microbiome as a Predictor of Outcomes in Patients with Metastatic Melanoma Treated with Immune Checkpoint Inhibitors.

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.

Corrigendum: Myelomodulatory treatments augment the therapeutic benefit of oncolytic viroimmunotherapy in murine models of malignant peripheral nerve sheath tumors.

[This corrects the article DOI: 10.3389/fimmu.2024.1384623.].

NF1+/ex42del miniswine model the cellular disruptions and behavioral presentations of NF1-associated cognitive and motor impairment.

Cognitive or motor impairment is common among individuals with neurofibromatosis type 1 (NF1), an autosomal dominant tumor-predisposition disorder. As many as 70% of children with NF1 report difficulties with spatial/working memory, attention, executive function, and fine motor movements. In contrast to the utilization of various Nf1 mouse models, here we employ an NF1+/ex42del miniswine model to evaluate the mechanisms and characteristics of these presentations, taking advantage of a large animal species more like human anatomy and physiology. The prefrontal lobe, anterior cingulate, and hippocampus from NF1+/ex42del and wild-type miniswine were examined longitudinally, revealing abnormalities in mature oligodendrocytes and astrocytes, and microglial activation over time. Imbalances in GABA: Glutamate ratios and GAD67 expression were observed in the hippocampus and motor cortex, supporting the role of disruption in inhibitory neurotransmission in NF1 cognitive impairment and motor dysfunction. Moreover, NF1+/ex42del miniswine demonstrated slower and shorter steps, indicative of a balance-preserving response commonly observed in NF1 patients, and progressive memory and learning impairments. Collectively, our findings affirm the effectiveness of NF1+/ex42del miniswine as a valuable resource for assessing cognitive and motor impairments associated with NF1, investigating the involvement of specific neural circuits and glia in these processes, and evaluating potential therapeutic interventions.

The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer.

Tumor hypoxia has been shown to predict poor patient outcomes in several cancer types, partially because it reduces radiation's ability to kill cells. We hypothesized that some of the clinical effects of hypoxia could also be due to its impact on the tumor microbiome. Therefore, we examined the RNA sequencing data from the Oncology Research Information Exchange Network database of patients with colorectal cancer treated with radiotherapy. We identified microbial RNAs for each tumor and related them to the hypoxic gene expression scores calculated from host mRNA. Our analysis showed that the hypoxia expression score predicted poor patient outcomes and identified tumors enriched with certain microbes such as Fusobacterium nucleatum. The presence of other microbes, such as Fusobacterium canifelinum, predicted poor patient outcomes, suggesting a potential interaction between hypoxia, the microbiome, and radiation response. To experimentally investigate this concept, we implanted CT26 colorectal cancer cells into immune-competent BALB/c and immune-deficient athymic nude mice. After growth, in which tumors passively acquired microbes from the gastrointestinal tract, we harvested tumors, extracted nucleic acids, and sequenced host and microbial RNAs. We stratified tumors based on their hypoxia score and performed a metatranscriptomic analysis of microbial gene expression. In addition to hypoxia-tropic and -phobic microbial populations, analysis of microbial gene expression at the strain level showed expression differences based on the hypoxia score. Thus, hypoxia gene expression scores seem to associate with different microbial populations and elicit an adaptive transcriptional response in intratumoral microbes, potentially influencing clinical outcomes. SIGNIFICANCE: Tumor hypoxia reduces radiotherapy efficacy. In this study, we explored whether some of the clinical effects of hypoxia could be due to interaction with the tumor microbiome. Hypoxic gene expression scores associated with certain microbes and elicited an adaptive transcriptional response in others that could contribute to poor clinical outcomes.

Superoxide Dismutase Mimetic Avasopasem Manganese Enhances Radiation Therapy Effectiveness in Soft Tissue Sarcomas and Accelerates Wound Healing.

Soft tissue sarcomas (STSs) are mesenchymal malignant lesions that develop in soft tissues. Despite current treatments, including radiation therapy (RT) and surgery, STSs can be associated with poor patient outcomes and metastatic recurrences. Neoadjuvant radiation therapy (nRT), while effective, is often accompanied by severe postoperative wound healing complications due to damage to the surrounding normal tissues. Thus, there is a need to develop therapeutic approaches to reduce nRT toxicities. Avasopasem manganese (AVA) is a selective superoxide dismutase mimetic that protects against IR-induced oral mucositis and lung fibrosis. We tested the efficacy of AVA in enhancing RT in STSs and in promoting wound healing. Using colony formation assays and alkaline comet assays, we report that AVA selectively enhanced the STS (liposarcoma, fibrosarcoma, leiomyosarcoma, and MPNST) cellular response to radiation compared to normal dermal fibroblasts (NDFs). AVA is believed to selectively enhance radiation therapy by targeting differential hydrogen peroxide clearance in tumor cells compared to non-malignant cells. STS cells demonstrated increased catalase protein levels and activity compared to normal fibroblasts. Additionally, NDFs showed significantly higher levels of GPx1 activity compared to STSs. The depletion of glutathione using buthionine sulfoximine (BSO) sensitized the NDF cells to AVA, suggesting that GPx1 may, in part, facilitate the selective toxicity of AVA. Finally, AVA significantly accelerated wound closure in a murine model of wound healing post RT. Our data suggest that AVA may be a promising combination strategy for nRT therapy in STSs.

Integrated Epigenetic and Transcriptomic Analysis Identifies Interleukin 17 DNA Methylation Signature of Malignant Peripheral Nerve Sheath Tumor Progression and Metastasis.

PURPOSE: Sarcomas are a complex group of highly aggressive and metastatic tumors with over 100 distinct subtypes. Because of their diversity and rarity, it is challenging to generate multisarcoma signatures that are predictive of patient outcomes. MATERIALS AND METHODS: Here, we identify a DNA methylation signature for progression and metastasis of numerous sarcoma subtypes using multiple epigenetic and genomic patient data sets. Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are highly metastatic sarcomas with frequent loss of the histone methyltransferase, PRC2. Loss of PRC2 is associated with MPNST metastasis and plays a critical noncanonical role in DNA methylation. RESULTS: We found that over 900 5'-C-phosphate-G-3' (CpGs) were hypermethylated in MPNSTs with PRC2 loss. Furthermore, we identified eight differentially methylated CpGs in the IL17D/RD family that correlate with the progression and metastasis of MPNSTs in two independent patient data sets. Similar trends were identified in other sarcoma subtypes, including osteosarcoma, rhabdomyosarcoma, and synovial sarcoma. Analysis of scRNAseq data sets determined that IL17D/RD expression occurs in both the tumor cells and the surrounding stromal populations. CONCLUSION: These results might have broad implications for the clinical management and surveillance of sarcoma.

A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset.

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.