It is becoming increasingly apparent that discovering new therapeutics for the treatment of cancer must involve a consideration of: (A) The interplay between the host immune system and tumors. Cancer cells often have adapted the ability to evade immune surveillance, either by muted antigenicity or via actively disarming immune activation via immune checkpoint blockade. (B) The connection between chemotherapeutic interventions and immunogenicity. It has become apparent that the efficacy of many traditional chemotherapies is dependent upon enhancing the immunogenicity of cancer cells. Without a functional immune system, cytotoxic small molecules demonstrate decrease selectivity for cancer cells versus healthy ones. (C) The highly heterogeneous nature of tumors in their native environments. Tumors are comprised of a complex mixture of multiple tumor lineages embedded host tissue microenvironments. The structure and complexity of the tumor microenvironment has a direct bearing on the efficacy of therapeutic interventions. This proposal develops a new methodology for natural product discovery using biopsied human tumors and tumor infiltrating immune cells. Multiplexed activity metabolomics (MAM) merges flow cytometric microtiter well and bioassay multiplexing with metabolomics and cheminformatics software to radically accelerate bioactive compound discovery, and specifically addresses the above considerations in the context of the discovery of acute myeloid leukemia anticancer lead discovery. Additionally, experimental designs will provide new insights into the effect and mechanism of a reference set of known synthetic and natural small molecules, providing a basis set of cellular responses to cytotoxic small molecules for the evaluation of lead compounds generated during discovery efforts.
Specific aims of this proposal are organized independently to develop a multiplexing system for bioeffector discovery, a multiplexing system for analysis of heterogeneous cell mixtures, and a deep cell response profiling via multiplexed immunoassay of markers of cell status.
Aims circumscribe this plan for our cross-disciplinary team employing metabolomics, natural product chemical biology, and discovery (Bachmann), cytometry and cancer biology (Irish), and clinical cancer biology (Ferrell).
We aim to: (1) Identify microbial metabolites that specifically target human cancer cells from primary tumor tissue samples to modulate anti-tumor immunity. (2) Discover metabolites that remodel immune cell population fates to enhance anti-tumor immunity, (3) Determine deep single cell metabolite responses of malignant and tumor-associated immune cells using known, clinically active molecules as reference points Relevance: This successful completion of the proposed research is highly relevant to human health because it will provide methods to accelerate the identification of potential anticancer natural products, which have had and continue to have a large impact on human health. Furthermore, the discovery of the multi-cell targeting immuno-oncological activity of known compound families, and newly discovered compounds may provide new targeted therapeutics, with greater efficiency and reduced clinical toxicity.

Public Health Relevance

. Cancer is a complex disease to treat in part because individual tumors are comprised of mixtures of non-malignant immune and stromal cells, and often distinct subsets of cancerous cells. Here we propose to apply a method to rapidly discovery and deeply characterize natural products sourced from cave ecosystems that effect changes in the diverse cells that make up human tumor microenvironments. We will use this method to better understand how existing anticancer drugs work and to discover new natural molecules that kill cancer cells in the context of the complex tumor environment.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Synthetic and Biological Chemistry B Study Section (SBCB)
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Knowlton, John R
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Vanderbilt University Medical Center
Schools of Arts and Sciences
United States
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