Multi-scale analysis of Bacillus Calmette-Guérin (BCG) resistant tumor micro-environment in non-muscle invasive bladder cancer to identify novel therapeutic axis

Rationale: Non–muscle invasive bladder cancer (NMIBC) accounts for 70-80% of newly diagnosed bladder cancer cases worldwide. Intravesical mycobacterium bovis Bacillus Calmette–Guérin (BCG) is the only US Food and Drug Administration (FDA)-approved first-line treatment option for high-risk NMIBC. Intravesical BCG targets the tumors by activating the mucosal anti-tumor immunity in the bladder tumor microenvironment (TME) and this involves intricate molecular interactions within and between distinct cell populations manifesting in different regions of the tissues. To this end, a comprehensive molecular atlas of NMIBC TME is needed to dissect the cellular and spatial features, and ultimately the crucial signaling cascades amongst these features that underlie the BCG resistance. Single-cell and spatially resolved sequencings hold promises to reveal the near-cellular resolution snapshots of the BCG resistant TME. Current studies on NMIBC TME, however, are often focused on the after-mass of BCG treatments, dominated by the muscle-invasive bladder cancers, are based on small numbers of samples (< 15), and mostly focus on each –omics data modality. Overall, a holistic, data-driven molecular model of NMIBC BCG resistance is lacking, which hinders the systematic search for the therapeutic axes. Method: In this study, we will generate tissues from BCG-treated NMIBC tumors from the responsive and unresponsive patients before BCG (pre-BCG) and after BCG (post-BCG) to explore these therapeutic axes. Specifically, we will elucidate the spatial and cellular landscapes of BCG-resistant NMIBC TME through i) matched single-nuclei RNA and ATAC sequencing, and near-cell resolution spatial sequencing across 36 samples, and ii) bulk RNA sequencing across 132 samples to validate single-nuclei and spatial findings and provide robust transcriptional readouts with the larger sample size. These data will be systematically utilized to construct cell type-resolved gene network models to survey de novo BCG resistance mechanisms and regulators, and repurpose pre-clinical or FDA-approved drugs to abolish multi-facetted BCG resistance. Expected Results: To our knowledge, this is the first effort to simultaneously study cellular genomic, epigenomic and spatial features of BCG-unresponsive NMIBCs. The altered cellular and spatial changes from each type of sequencing data will be integrated into the cell type-resolved multi-scale network model to elucidate their inter-wined signaling cascades as novel BCG resistance mechanisms and their regulators. Ultimately, these mechanistic insights will inform the identification of pre-clinical and FDA- approved drugs to target the BCG resistance regulators, and these will be validated in immune competent tumor explants model to observe their anti-tumor efficacies. Overall, this study will yield valuable resources of high resolution sequencing data to elucidate the NMIBC TME, and address the clinical unmet needs to tackle BCG resistances in NMIBC.