Screening, Validation, and Machine Learning-Based Evaluation of Serum Protein Biomarkers for Esophageal Squamous Cell Carcinoma Based on Single-Cell Subtype-Specific Genes.

Journal: Journal of proteome research
Published Date: Aug 12, 2025

Abstract

Cellular heterogeneity of epithelial cells and fibroblasts is critical in esophageal squamous cell carcinoma development (ESCC). Identifying dysregulated subtype-specific genes in these cells is essential for early diagnosis and treatment. In this study, our pipeline integrated scRNA-seq, proteomics, and ELISA to screen biomarkers: scRNA-seq defined epithelial and fibroblast subtypes and their markers, while proteomics and secretory profiling identified dysregulated secretory proteins. Serum levels of five selected proteins were measured in 344 ESCC patients, 46 HGIN cases, and 390 normal controls. Machine learning was employed to construct diagnostic models. An interactive web tool was implemented in R Shiny. Six epithelial and four fibroblast subtypes, proportionally distinct between ESCC and normal tissues, were identified. Four validated dysregulated proteins were used to build diagnostic models; among 12 algorithms, the Support Vector Machine (SVM) achieved the best performance with AUCs of 0.829 and 0.767 in the training and validation sets, respectively ( > 0.05). The model effectively distinguished early- and late-stage ESCC and HGIN from normal controls. The web-based diagnostic tool is publicly available at https://zhangxz.shinyapps.io/P4_Pred/. The identified serum biomarkers may enhance early ESCC detection and diagnosis. Our pipeline, leveraging heterogeneity-related genes in fibroblasts and epithelial cells, is readily adaptable to other tumors.

Authors

  • Xiuzhi Zhang
    Department of Pathology, Henan Medical College, Zhengzhou, Henan Province, China 451191.
  • Zhefeng Xiao
    Department of Pathology, NHC Key Laboratory of Cancer Proteomics, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
  • Fengqi Chen
    Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan 450052, China.
  • Wenke Sun
    Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan 450052, China.
  • Tiandong Li
    College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan Provinc, China.
  • Hua Ye
    Department of Pulmonary and Critical Care Medicine, Affiliated Yueqing Hospital, Wenzhou Medical University, Yueqing 325600, China.
  • Peng Wang
    Neuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Liping Dai
    Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, 450052, Henan Province, China.
  • Xiaoli Liu
    Neurology Department, Zhejiang Hospital, Zhejiang 310013, China.

Keywords

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