Transcriptomics

Dataset Information

0

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


ABSTRACT: 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.

ORGANISM(S): Mus musculus

PROVIDER: GSE193460 | GEO | 2022/01/15

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2023-08-16 | E-MTAB-12767 | biostudies-arrayexpress
2023-04-19 | GSE224411 | GEO
2019-11-01 | GSE139265 | GEO
2024-05-23 | GSE246011 | GEO
2024-04-16 | GSE243022 | GEO
2022-08-03 | GSE169659 | GEO
2009-03-07 | E-GEOD-11994 | biostudies-arrayexpress
2021-04-20 | GSE98138 | GEO
2023-06-16 | MSV000092193 | MassIVE
2016-02-26 | E-GEOD-66717 | biostudies-arrayexpress