Perturb-map coupled with spatial transcriptomics identifies mutation associated gene signatures in a mouse model of lung adenocarcinoma

The cellular architecture of a tumor has a major impact on cancer outcome, and thus there is interest in identifying genes controlling the tumor microenvironment (TME). While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying gene functions operating extracellularly or within a tissue context. To address this, we developed an approach for spatial functional genomics called Perturb-map, which utilizes protein barcodes (Pro-Code) to enable spatial detection of barcoded cells within tissue. We applied Perturb-map to knockout dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Additionally, we paired Perturb-map and spatial transcriptomics for unbiased molecular analysis of Pro-Code/CRISPR lesions. Our studies found in Tgfbr2 knockout lesions, the TME was converted to a fibro-mucinous state and T-cells excluded, concomitant with upregulated TGFb and TGFb-mediated stroma activation, suggesting Tgfbr2 loss on lung cancer cells increased TGFb bioavailability and enhanced its suppressive effects on the TME. These studies establish Perturb-map for functional genomics within a tissue at single cell-resolution with spatial architecture preserved. Overall design: Male C57BL/6J mice were injected intravenously with KP (Kras G12D, p53 deleted) cells transduced with a Pro-Code/CRISPR library targeting 35 different genes associated with tumor-immune interaction. 10X Visium spatial transcriptomics profiling was performed on 4 separate sections of mouse lung from 3 different mice. Annotations for specific genes targeted in visium spots capturing tumor cells were generated by parallel hyperion imaging on a serial section to identify the linked protein barcode.