한빛사논문
Joonha Kwon1,10, Junho Kang2,10, Areum Jo3,4, Kayoung Seo1, Dohyeon An1, Mert Yakup Baykan2, Jun Hyeong Lee1, Nayoung Kim 3,4, Hye Hyeon Eum3,4, Sohyun Hwang5,6, Ji Min Lee7, Woong-Yang Park8, Hee Jung An 5, Hae-Ock Lee 3,4 , Jong-Eun Park 2 & Jung Kyoon Choi 1,9
1Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea.
2Graduate School of Medical Science and Engineering, KAIST, Daejeon, Republic of Korea.
3Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
4Department of Biomedicine and Health Sciences, Graduate School, The Catholic University of Korea, Seoul, Republic of Korea.
5Department of Pathology, CHA Bundang Medical Center, CHA University, Seongnam-si, Republic of Korea.
6Department of Biomedical Science, CHA University, Pocheon-si, Republic of Korea.
7CHA Advanced Research Institute, CHA Bundang Medical Center, Seongnam-si, Republic of Korea.
8Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea.
9Penta Medix Co., Ltd., Seongnam-si, Republic of Korea.
10These authors contributed equally: Joonha Kwon, Junho Kang.
Corresponding authors
Correspondence to Hee Jung An, Hae-Ock Lee, Jong-Eun Park or Jung Kyoon Choi.
Abstract
Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.
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