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Dataset Citation

Saltz, J., Gupta, R., Hou, L., Kurc, T., Singh, P., Nguyen, V., … Thorsson, V. (2018). Tumor-Infiltrating Lymphocytes Maps from TCGA H&E Whole Slide Pathology Images [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/k9/tcia.2018.y75f9w1

Description

Mappings of tumor-infiltrating lymphocytes (TILs), based on H&E images from 13 TCGA tumor types are available here. These TIL maps are derived through computational staining, using a convolutional neural network trained to classify patches of images. In addition to the TIL Maps, the analysis codes and the software used to extract TILs are also available. The accompanying paper contains detailed information about our methods and our findings.

TCGA Tumor Types Used in this Study

BLCA Bladder urothelial carcinoma
BRCA Breast invasive carcinoma
CESC Cervical squamous cell carcinoma and endocervical adenocarcinoma
COAD Colon adenocarcinoma
LUAD Lung adenocarcinoma
LUSC Lung squamous cell carcinoma
PAAD Pancreatic adenocarcinoma
PRAD Prostate adenocarcinoma
READ Rectum adenocarcinoma
SKCM Skin Cutaneous Melanoma
STAD Stomach adenocarcinoma
UCEC Uterine Corpus Endometrial Carcinoma
UVM Uveal Melanoma

Publication Citation

Saltz, J., Gupta, R., Hou, L., Kurc, T., Singh, P., Nguyen, V., . . . Thorsson, V. Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images. Cell Reports, 23(1), 181-193.e187. https://doi.org/10.1016/j.celrep.2018.03.086


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