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A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.
Bao, Xuanwen; Li, Qiong; Chen, Dong; Dai, Xiaomeng; Liu, Chuan; Tian, Weihong; Zhang, Hangyu; Jin, Yuzhi; Wang, Yin; Cheng, Jinlin; Lai, Chunyu; Ye, Chanqi; Xin, Shan; Li, Xin; Su, Ge; Ding, Yongfeng; Xiong, Yangyang; Xie, Jindong; Tano, Vincent; Wang, Yanfang; Fu, Wenguang; Deng, Shuiguang; Fang, Weijia; Sheng, Jianpeng; Ruan, Jian; Zhao, Peng.
Afiliación
  • Bao X; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China. Electronic address: xuanwen.bao@zju.edu.cn.
  • Li Q; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Chen D; Department of Colorectal Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Dai X; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Liu C; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Tian W; Department of Immunology, School of Medicine, Jiangsu University, Zhenjiang, Jiangsu 212013, China.
  • Zhang H; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Jin Y; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Wang Y; College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Cheng J; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Lai C; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Ye C; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Xin S; Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA.
  • Li X; Department of Chronic Inflammation and Cancer, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
  • Su G; College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Ding Y; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Xiong Y; Department of Gastroenterology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Xie J; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China.
  • Tano V; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 637551, Republic of Singapore.
  • Wang Y; Ludwig-Maximilians-Universität München (LMU), 80539 Munich, Germany.
  • Fu W; Department of Hepatobiliary Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province 646000, China.
  • Deng S; College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Fang W; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China.
  • Sheng J; Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China. Electronic address: shengjp@zju.edu.cn.
  • Ruan J; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China; Department of Hepatobiliary Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province 646000, China. Electronic address:
  • Zhao P; Department of Medical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, China. Electronic address: zhaop@zju.edu.cn.
Cell Rep Med ; 5(2): 101399, 2024 Feb 20.
Article en En | MEDLINE | ID: mdl-38307032
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Receptor 2 de Folato / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cell Rep Med Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Receptor 2 de Folato / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cell Rep Med Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos