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Microbes are extensively present among various cancer tissues and play critical roles in carcinogenesis and treatment responses. However, the underlying relationships between intratumoral microbes and tumors remain poorly understood. Here, a MIcrobial Cancer-association Analysis using a Heterogeneous graph transformer (MICAH) to identify intratumoral cancer-associated microbial communities is presented. MICAH integrates metabolic and phylogenetic relationships among microbes into a heterogeneous graph representation. It uses a graph transformer to holistically capture relationships between intratumoral microbes and cancer tissues, which improves the explainability of the associations between identified microbial communities and cancers. MICAH is applied to intratumoral bacterial data across 5 cancer types and 5 fungi datasets, and its generalizability and reproducibility are demonstrated. After experimentally testing a representative observation using a mouse model of tumor-microbe-immune interactions, a result consistent with MICAH's identified relationship is observed. Source tracking analysis reveals that the primary known contributor to a cancer-associated microbial community is the organs affected by the type of cancer. Overall, this graph neural network framework refines the number of microbes that can be used for follow-up experimental validation from thousands to tens, thereby helping to accelerate the understanding of the relationship between tumors and intratumoral microbiomes., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

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., (©2024 The Authors; Published by the American Association for Cancer Research.)

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., (©2024 The Authors; Published by the American Association for Cancer Research.)

Background: Depression is a leading cause of disability worldwide yet its underlying factors, particularly microbial associations, are poorly understood., Methods: We examined the longitudinal interplay between the microbiome and immune system in the context of depression during an immersive psychosocial intervention. 142 multi-omics samples were collected from 52 well-characterized participants before, during, and three months after a nine-day inquiry-based stress reduction program., Results: We found that depression was associated with both an increased presence of putatively pathogenic bacteria and reduced microbial beta-diversity. Following the intervention, we observed reductions in neuroinflammatory cytokines and improvements in several mental health indicators. Interestingly, participants with a Prevotella -dominant microbiome showed milder symptoms when depressed, along with a more resilient microbiome and more favorable inflammatory cytokine profile, including reduced levels of CXCL-1., Conclusions: Our findings reveal a protective link between the Prevotella-dominant microbiome and depression, associated with a less inflammatory environment and moderated symptoms. These insights, coupled with observed improvements in neuroinflammatory markers and mental health from the intervention, highlight potential avenues for microbiome-targeted therapies in depression management., Competing Interests: CONFLICT OF INTEREST M.P.S. is a co-founder and the scientific advisory board member of Personalis, Qbio, January, SensOmics, Filtricine, Akna, Protos, Mirvie, NiMo, Onza, Oralome, Marble Therapeutics, and Iollo. He is also on the scientific advisory board of Danaher, Genapsys, and Jupiter. A. B. G. is a founding partner at Arben Ventures and Xthena Partners. The fund she manages through Arben Ventures is an advisor to Elemind Technologies, Northstar Care, and Bloch Quantum Imaging. These organizations had no role in planning, writing, editing, or reviewing this article, or in deciding to submit this article for publication. All other authors report no biomedical financial interests or potential conflicts of interest.

The microbiome affects cancer, from carcinogenesis to response to treatments. New evidence suggests that microbes are also present in many tumors, though the scope of how they affect tumor biology and clinical outcomes is in its early stages. A broad survey of tumor microbiome samples across several independent datasets is needed to identify robust correlations for follow-up testing. We created a tool called {exotic} for "exogenous sequences in tumors and immune cells" to carefully identify the tumor microbiome within RNA sequencing (RNA-seq) datasets. We applied it to samples collected through the Oncology Research Information Exchange Network (ORIEN) and The Cancer Genome Atlas. We showed how the processing removes contaminants and batch effects to yield microbe abundances consistent with non-high-throughput sequencing-based approaches and DNA-amplicon-based measurements of a subset of the same tumors. We sought to establish clinical relevance by correlating the microbe abundances with various clinical and tumor measurements, such as age and tumor hypoxia. This process leveraged the two datasets and raised up only the concordant (significant and in the same direction) associations. We observed associations with survival and clinical variables that are cancer specific and relatively few associations with immune composition. Finally, we explored potential mechanisms by which microbes and tumors may interact using a network-based approach. Alistipes, a common gut commensal, showed the highest network degree centrality and was associated with genes related to metabolism and inflammation. The {exotic} tool can support the discovery of microbes in tumors in a way that leverages the many existing and growing RNA-seq datasets., Significance: The intrinsic tumor microbiome holds great potential for its ability to predict various aspects of cancer biology and as a target for rational manipulation. Here, we describe a tool to quantify microbes from within tumor RNA-seq and apply it to two independent datasets. We show new associations with clinical variables that justify biomarker uses and more experimentation into the mechanisms by which tumor microbiomes affect cancer outcomes., (© 2023 The Authors; Published by the American Association for Cancer Research.)

Background: We investigated the role of A2B-adenosine receptor in regulating immunosuppressive metabolic stress in the tumor microenvironment. Novel A2B-adenosine receptor antagonist PBF-1129 was tested for antitumor activity in mice and evaluated for safety and immunologic efficacy in a phase I clinical trial of patients with non-small cell lung cancer., Methods: The antitumor efficacy of A2B-adenosine receptor antagonists and their impact on the metabolic and immune tumor microenvironment were evaluated in lung, melanoma, colon, breast, and epidermal growth factor receptor-inducible transgenic cancer models. Employing electron paramagnetic resonance, we assessed changes in tumor microenvironment metabolic parameters, including pO2, pH, and inorganic phosphate, during tumor growth and evaluated the immunologic effects of PBF-1129, including its pharmacokinetics, safety, and toxicity, in patients with non-small cell lung cancer., Results: Levels of metabolic stress correlated with tumor growth, metastasis, and immunosuppression. Tumor interstitial inorganic phosphate emerged as a correlative and cumulative measure of tumor microenvironment stress and immunosuppression. A2B-adenosine receptor inhibition alleviated metabolic stress, downregulated expression of adenosine-generating ectonucleotidases, increased expression of adenosine deaminase, decreased tumor growth and metastasis, increased interferon γ production, and enhanced the efficacy of antitumor therapies following combination regimens in animal models (anti-programmed cell death 1 protein vs anti-programmed cell death 1 protein plus PBF-1129 treatment hazard ratio = 11.74 [95% confidence interval = 3.35 to 41.13], n = 10, P < .001, 2-sided F test). In patients with non-small cell lung cancer, PBF-1129 was well tolerated, with no dose-limiting toxicities; demonstrated pharmacologic efficacy; modulated the adenosine generation system; and improved antitumor immunity., Conclusions: Data identify A2B-adenosine receptor as a valuable therapeutic target to modify metabolic and immune tumor microenvironment to reduce immunosuppression, enhance the efficacy of immunotherapies, and support clinical application of PBF-1129 in combination therapies., (© The Author(s) 2023. Published by Oxford University Press.)