Mapping spatial organization and genetic cell state regulators to target immune evasion in ovarian cancer

This collection of data accompanies the study: Yeh, Aguirre, Laveroni et al. Mapping spatial organization and genetic cell-state regulators to target immune evasion in ovarian cancer. (2024). Nature Immunology.  Files are provided in the form of RObjects (extension .rds) or tabulated data (extension .csv) to reproduce the results and figures provided in the paper via the the R programming environment using Code provided here. 

Data collected and processed and published as a part of this study of tubo-ovarian high grade serous carcinoma (HGSC) includes: 

~2.5 million single cell spatial transcriptomics profiles from 130 HGSC tumors of 94 patients

Matching de-identified clinical annotations and clinical outcomes.

Matching targeted genomic data from the bulk tumor tissues.

Perturb-seq CRISPR knockout data in ovarian cancer cells in monoculture and co-culture with Natural Killer (NK) cells.

The spatial transcriptomics, Perturb-Seq, and matched H&E (Hematoxylin & Eosin, where available) are also provided via the Single Cell Portal with an interactive interface (SCP2640, SCP2641, SCP2650, SCP2644, SCP2646, SCP2707).

The collection also includes previously published data that was analyzed and used in this study to examine the generalizability of the findings, evaluate immunotherapy predictors, and for data-driven experimental design.

The SeuratObj.zip contains six SeuratObjects matching the five spatial transcriptomcs datasets (Discovery, Validation 1, Validation 2, Test 1 and Test 2) and Perturb-Seq data.

The Yeh2024.zip file includes the study's data and additional datasets/results to reproduce the study's figures. A detailed description of the files included in the repository is provided in `README.txt` and `README.xlsx`