2. Academic Validation
  3. Neutrophil-centric analysis of gastric cancer: prognostic modeling and molecular insights

Neutrophil-centric analysis of gastric cancer: prognostic modeling and molecular insights

  • Cell Mol Life Sci. 2024 Nov 14;81(1):452. doi: 10.1007/s00018-024-05484-w.
Guangbo Tang # 1,  Qiong Song # 2,  Jianhua Dou # 3,  Zhangqian Chen 4,  Xi Hu 1,  Zihang Li 5 6,  Xiujuan Li 7,  Tingjie Wang 8,  Shanshan Dong 9,  Huqin Zhang 10
Affiliations

Affiliations

  • 1 Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi Province, People's Republic of China.
  • 2 Department of Nephrology, Shaanxi Second People's Hospital, Xi'an, 710004, Shaanxi Province, People's Republic of China.
  • 3 State Key Laboratory of Cancer Biology, Xijing Hospital of Digestive Diseases, Xi'an, 710032, Shaanxi Province, People's Republic of China.
  • 4 State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, 710049, Shaanxi Province, People's Republic of China.
  • 5 Department of Hematology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi Province, People's Republic of China.
  • 6 Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710004, Shaanxi Province, People's Republic of China.
  • 7 School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710032, Shaanxi Province, People's Republic of China.
  • 8 Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450003, Henan Province, People's Republic of China. wtj505531480@163.com.
  • 9 Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi Province, People's Republic of China. dongss@xjtu.edu.cn.
  • 10 Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi Province, People's Republic of China. huqzhang@xjtu.edu.cn.
  • # Contributed equally.
PMID: 39540948 DOI: 10.1007/s00018-024-05484-w
Abstract

Gastric Cancer remains a significant global health concern with poor prognosis. This study investigates the role of neutrophils in gastric Cancer progression and their potential as prognostic indicators. Using multi-omics approaches, including Weighted Gene Co-expression Network Analysis (WGCNA), machine learning, and single-cell analysis, we identified neutrophil-associated gene signatures and developed a robust prognostic model. Our findings reveal distinct gastric Cancer subtypes based on neutrophil-associated genes, with one subtype showing increased neutrophil infiltration and poorer prognosis. Single-cell analysis uncovered neutrophil-associated alterations in cell composition, gene expression profiles, and intercellular communication within the tumor microenvironment. Additionally, we explored the relationship between neutrophil-associated genes, microbiota composition, and alternative splicing events in gastric Cancer. Furthermore, we identified QKI as a key regulator of alternative splicing and demonstrated its role in promoting malignant phenotypes and enhancing TGF-beta signaling and epithelial-mesenchymal transition in gastric Cancer cells by wet experiment. Lastly, the role of QKI in the association with drug resistance and the identification of specific agents for treating QKI-associated drug resistance were also explored. This comprehensive study provides novel insights into the complex interplay between neutrophils, the tumor microenvironment, microbiota, alternative splicing and gastric Cancer progression, offering potential new targets for therapeutic intervention.

Keywords

Alternative splicing; Drug resistance; Epithelial-mesenchymal transition (EMT); Gastric cancer; Machine learning; Microbiota; Neutrophils; Prognosis model; QKI; Single-cell analysis; TGF-beta signaling; Tumor microenvironment.

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