Multi-omics identifies OSM-OSMR as a key receptor-ligand in the tumor environment of endometrial adenocarcinoma.

Journal: International immunopharmacology
Published Date:

Abstract

Endometrial adenocarcinoma carries a bleak prognosis, and the molecular markers that evaluate the progression of endometrial adenocarcinoma to advanced stages remain uncertain. Cell-cell communication plays a crucial role in the tumor microenvironment. We aimed to explore the ligand-receptor relationship between tumor cells and other cells and construct a prognostic model. To make further investigation, we downloaded and analyzed datasets of single-cell RNA-seq, spatial transcriptome sequencing for EC from GEO, bulk RNA sequencing and clinical data of TCGA-EC project from TCGA. Compared to the adjacent normal tissue, there is a significantly elevated Oncostatin M (OSM) signaling in the cell communication intensity and quantity of endometrial cancer tissues through analyzing the scRNA-seq dataset. Endometrial adenocarcinoma can be divided into four subtypes based on the OSM gene set. By comparing multiple machine learning methods, we have identified the random survival forest method as having the highest C-index. Based on this method, we constructed a seven-gene signature model to predict the survival prognosis of endometrial adenocarcinoma. The exogenous cytokine OSM induced Ishikawa cell proliferation and abnormal lipids metabolism, while the transcriptome sequencing results reveal that the pathways enriched with differentially expressed genes include AKT signaling pathways. The OSMR-knockout inhibited the tumorigenicity of Ishikawa Cells in the subcutaneous xenotransplanted tumor model of endometrial cancer. Our analysis revealed that OSM promotes the proliferation of Ishikawa cells via the AKT signaling pathway, abnormal lipids metabolism highlighting its significance in the regulation of TME. The prognostic model can provide valuable insights into guiding treatment strategies and suggesting further clinical management of endometrial adenocarcinoma patients.

Authors

  • Qiuao Zhou
    The First School of Clinical Medicine, Nanjing Medical University, 211166 Nanjing, Jiangsu, China.
  • Zhijun Wu
    Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Jianing Gu
    Department of Bioinformatics, Nanjing Medical University, 211166 Nanjing, Jiangsu, China.
  • Xiaoyu Tang
    School of Data Science and Engineering, Xingzhi College, South China Normal University, Shanwei 516600, China.
  • Ning Li
    Department of Respiratory and Critical Care Medicine, Center for Respiratory Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
  • Minmin Yu
    Department of Pathology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
  • Changsong Lin
    Department of Bioinformatics, Nanjing Medical University, 211166 Nanjing, Jiangsu, China. Electronic address: lcs04bio@njmu.edu.cn.