Journal article

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Joel Saltz, Rajarsi Gupta, Le Hou, Tahsin Kurc, Pankaj Singh, Nguyen Vu, Dimitris Samaras, Kenneth R Shroyer, Tianhao Zhao, Rebecca Batiste, John Van Arnam, Ilya Shmulevich, Arvind UK Rao, Alexander J Lazar, Ashish Sharma, Vesteinn Thorsson

Cell Reports | CELL PRESS | Published : 2018


Awarded by National Cancer Institute (NCI)

Awarded by NCI

Awarded by Leidos Biomedical

Awarded by CCSG Bioinformatics Shared Resource

Awarded by ITCR U24 Supplement

Awarded by CPRIT

Awarded by American Cancer Society

Awarded by National Science Foundation XSEDEScience Gateways program

Awarded by National Science Foundation

Funding Acknowledgements

We are grateful to all the patients and families who contributed to this study. Funding from the Cancer Research Institute is gratefully acknowledged, as is support from National Cancer Institute (NCI) through U54 HG003273, U54 HG003067, U54 HG003079, U24 CA143799, U24 CA143835, U24 CA143840, U24 CA143843, U24 CA143845, U24 CA143848, U24 CA143858, U24 CA143866, U24 CA143867, U24 CA143882, U24 CA143883, U24 CA144025, P30 CA016672, U24CA180924, U24CA210950, U24CA215109, NCI Contract HHSN261201400007C, and Leidos Biomedical Contract 14X138. A.U.K.R. and P.S were supported by CCSG Bioinformatics Shared Resource P30 CA01667, ITCR U24 Supplement 1U24CA199461-01, a gift from Agilent technologies, CPRIT RP150578, and a Research Scholar Grant from the American Cancer Society (RSG-16-005-01). This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation XSEDEScience Gateways program under grant ACI-1548562 allocation TG-ASC130023. The authors would like to thank Stony Brook Research Computing and Cyberinfrastructure and the Institute for Advanced Computational Science at Stony Brook University for access to the high-performance LIred and SeaWulf computing systems, the latter of which was supported by National Science Foundation grant (#1531492).