TY  - JOUR
AU  - Bao, Xuanwen
AU  - Li, Qiong
AU  - Chen, Dong
AU  - Dai, Xiaomeng
AU  - Liu, Chuan
AU  - Tian, Weihong
AU  - Zhang, Hangyu
AU  - Jin, Yuzhi
AU  - Wang, Yin
AU  - Cheng, Jinlin
AU  - Lai, Chunyu
AU  - Ye, Chanqi
AU  - Xin, Shan
AU  - Li, Xin
AU  - Su, Ge
AU  - Ding, Yongfeng
AU  - Xiong, Yangyang
AU  - Xie, Jindong
AU  - Tano, Vincent
AU  - Wang, Yanfang
AU  - Fu, Wenguang
AU  - Deng, Shuiguang
AU  - Fang, Weijia
AU  - Sheng, Jianpeng
AU  - Ruan, Jian
AU  - Zhao, Peng
TI  - A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.
JO  - Cell reports / Medicine
VL  - 5
IS  - 2
SN  - 2666-3791
CY  - Maryland Heights, MO
PB  - Elsevier
M1  - DKFZ-2024-00270
SP  - 101399
PY  - 2024
N1  - 2024 Feb 20;5(2):101399
AB  - Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.
KW  - FOLR2(+) macrophages (Other)
KW  - artificial intelligence (Other)
KW  - colorectal cancer (Other)
KW  - immuno module (Other)
KW  - tumor microenvironment (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:38307032
DO  - DOI:10.1016/j.xcrm.2024.101399
UR  - https://inrepo02.dkfz.de/record/287616
ER  -