TR&D 1

Overview: Imaging and theranostics to detect and promote an immune reactive tumor microenvironment

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Treatment with immune checkpoints inhibitors has had unprecedented responses in turning some deadly cancers into chronic diseases. Despite these successes, 80% of cancers have complex tumor microenvironments (TMEs) that are resistant to immune checkpoint inhibitors. Although we have begun to uncover complex signals that provide a formidable barrier to immune cell infiltration and cancer cell killing, this requires sequential and multiple tumor biopsies from multiple tumor sites to delineate this signaling network and to assess heterogeneity between tumors in the same patient before and after treatment with different therapies. Non-invasive translatable imaging methods that provide spatio-temporal information on mechanisms that create barriers to immune cell infiltration, provide novel theranostic strategies to improve the outcome of cancer immunotherapy (CIT), and detect response to treatment are urgently needed to accelerate progress in this field.
The overall goals of TR&D1 are to develop and validate non-invasive imaging probes that can be used by the CPs and SPs to identify a TME hostile to CIT, to provide novel theranostic approaches to overcome such an environment to facilitate CIT, and to identify the response of tumors to CIT using artificial intelligence (AI) integrated with spectroscopy of plasma samples. We intend to accomplish these goals in the following three aims by building upon advances made during the previous funding period, and by combining our expertise in
multimodal imaging of the TME, PET/MR imaging including spectroscopy and chemical exchange saturation transfer (CEST), and theranostics. We will integrate, for the first time, artificial intelligence (AI) into CEST and metabolomic analysis of human plasma samples to predict and detect the response of clear cell renal cell carcinomas (ccRCC) to CIT.

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Aim 1: To develop novel PET and CEST MRI probes based on decorin to expand understanding of the spatio-temporal dynamics between collagen 1, decorin, hypoxia, extracellular pH (pHe), and immune checkpoint expression in syngeneic  models of pancreatic and breast cancer using multimodal imaging.

Aim 2: To develop and validate multi-modality imaging/multiplexed siRNA theranostics of myeloid derived suppressor cells (MDSCs) in the spleen and tumor to create an immune reactive TME in syngeneic models of pancreatic and breast cancer.

Aim 3: To integrate AI with 1H MR and CEST spectra of human plasma from patients with ccRCC to predict and detect response to CIT.