Single-cell and spatial transcriptomics reveal P4HA2-mediated radiotherapy resistance mechanisms in breast cancer

Huimin Li1,2, Junzhi Liu2, Yuheng Jiao3

  • 1The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310009, China.

Theranostics
|December 22, 2025
PubMed

Insights

This study identifies a radiotherapy resistance (RR) gene panel and Prolyl 4-Hydroxylase Subunit Alpha 2 (P4HA2) as key drivers of treatment failure in breast cancer, offering new therapeutic targets and prognostic tools.

Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Radiotherapy resistance is a significant challenge in breast cancer treatment.
  • The molecular drivers and cellular mechanisms of this resistance are not fully elucidated.

Purpose of the Study:

  • To identify key genes and cellular populations associated with radiotherapy resistance in breast cancer.
  • To develop a prognostic model for stratifying patients based on radiotherapy resistance.
  • To investigate the role of Prolyl 4-Hydroxylase Subunit Alpha 2 (P4HA2) in breast cancer radiotherapy resistance.

Main Methods:

  • Utilized TCGA-BRCA and GSE120798 cohorts to identify a radiotherapy resistance (RR) gene panel.
  • Employed single-cell and spatial transcriptomics to characterize RR-high epithelial cells (RRhighepi).
  • Developed a prognostic model (SSRR) using machine learning and Mendelian randomization; validated P4HA2 function in vitro.

Main Results:

  • The RR gene panel and RRhighepi cells showed enrichment in cell cycle pathways, elevated stemness, and enhanced DNA repair.
  • The SSRR model effectively stratified patients into high-risk groups with poor survival.
  • P4HA2 knockdown inhibited cancer cell proliferation and invasion, and synergized with radiotherapy to reduce stemness and DNA damage.

Conclusions:

  • Multi-omics analysis revealed a mechanistic model for radiotherapy resistance in breast cancer.
  • P4HA2 is a potential therapeutic target to sensitize breast cancer to radiotherapy.
  • The RR gene panel and SSRR model offer insights into resistance mechanisms and patient stratification.