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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Inflammation

This article is part of the Research TopicSpatial Approaches to Understanding Lung Health and Disease Across LifespanView all articles

SCPEP1⁺ basal cells are associated with the remodeling of oxidative stress signaling networks in idiopathic pulmonary fibrosis

Provisionally accepted
Xiang  ZhouXiang Zhou1Tong  LuTong Lu2Xu  RanXu Ran1Cheng-hao  WangCheng-hao Wang1Simiao  ChenSimiao Chen1Jing  ChenJing Chen3Xiaoyan  ChangXiaoyan Chang1Meifeng  LiMeifeng Li1Jiaxin  ShiJiaxin Shi1Chengyu  XuChengyu Xu1Yupeng  ZhaoYupeng Zhao1Bo  PengBo Peng1Jiaying  ZhaoJiaying Zhao1Linyou  ZhangLinyou Zhang1*
  • 1Department of Thoracic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, China
  • 2Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
  • 3Department of Nephrology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China

The final, formatted version of the article will be published soon.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal interstitial lung disease marked by progressive extracellular matrix accumulation and irreversible lung architecture remodeling. Oxidative stress (OS) plays a crucial role in IPF pathogenesis, yet its role across distinct cellular compartments and tissue microenvironments remains incompletely characterized. Methods: We integrated single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (stRNA-seq), and bulk RNA-seq datasets to comprehensively characterize oxidative stress activity across cellular and tissue scales in IPF lungs. Oxidative stress scores were calculated using multiple enrichment algorithms, and machine learning models (LASSO, Random Forest, Boruta, Bayesian, LVQ, Treebag) were applied to identify robust OS-related diagnostic biomarkers. Expression patterns were validated in public datasets and a bleomycin-induced C57BL/6 mouse model. Cell-cell communication and gene regulatory pathways were further explored using CellChat and pseudotime trajectory analysis. Results: Oxidative stress activity was significantly elevated in IPF lung tissue and specifically enriched in basal cells. Among 71 candidate OS-related genes, SCPEP1 emerged as the most robust biomarker, consistently upregulated across multiple datasets and experimental validation, with an AUC of 0.857 in the training cohort. SCPEP1 expression was spatially confined to airway-adjacent regions and highly specific to basal cells. SCPEP1⁺ basal cells exhibited transcriptional reprogramming enriched in Wnt signaling and developmental pathways, dynamic expression during early pseudotime progression, and engaged in multifaceted interactions with immune and stromal cells through pro-fibrotic and inflammatory signaling axes such as MIF-CD74, MDK-NCL, and ICAM1-ITGAL. Translationally, these findings may help prioritize redox-sensitive pathways and ligand–receptor interactions for further investigation. While SCPEP1 appears to be a promising candidate, its potential for patient stratification or therapeutic intervention remains to be confirmed through functional studies. Keywords Idiopathic Pulmonary Fibrosis; Oxidative Stress; Single-Cell RNA Sequencing; Spatial Transcriptomics; Machine Learning; SCPEP1 Conclusion: Our multi-omics integration revealed SCPEP1⁺ basal cells as central oxidative stress responders and communication hubs in IPF. These findings provide insights into ROS-driven epithelial remodeling and highlight SCPEP1 as a potential contributor to disease-associated pathways that warrants further exploration for its diagnostic or therapeutic relevance.

Keywords: Idiopathic Pulmonary Fibrosis, Oxidative Stress, single-cell RNA sequencing, spatialtranscriptomics, machine learning, SCPEP1

Received: 30 Jul 2025; Accepted: 24 Nov 2025.

Copyright: © 2025 Zhou, Lu, Ran, Wang, Chen, Chen, Chang, Li, Shi, Xu, Zhao, Peng, Zhao and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Linyou Zhang

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