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Tumour budding in pretreatment cervical biopsies: a prognosticator for personalised therapy in the era of precision

Young Sub Lee1, Kwangil Yim2, Chan Joo Kim3

  • 1Department of Hospital Pathology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

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|December 25, 2025
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Summary

Tumour budding (TB) and cell nest size (CNS) in pretreatment cervical cancer biopsies are reliable prognostic indicators. These routine H&E staining features can predict survival and guide precision oncology, especially in resource-limited settings.

Keywords:
biopsycervical cancerprognosistumour buddingtumour microenvironment

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Area of Science:

  • Oncology
  • Pathology
  • Cancer Research

Background:

  • Tumour budding (TB) is a recognized indicator of the tumour microenvironment (TME).
  • Its prognostic value is established in many cancers but not yet in pretreatment cervical cancer biopsies.
  • Routine H&E staining allows for TB detection, alongside other TME features like cell nest size (CNS).

Purpose of the Study:

  • To investigate the prognostic value of TB in pretreatment cervical cancer biopsy specimens.
  • To evaluate additional H&E-identifiable TME features, such as CNS.
  • To assess the combined prognostic performance of TB and CNS.

Main Methods:

  • Retrospective review of 182 patients with FIGO stage IIVA cervical cancer treated in 2018.
  • Multivariate analysis to assess independent prediction of overall survival by TB and CNS.
  • Time-dependent receiver operating characteristic (ROC) analysis to compare prognostic performance.

Main Results:

  • Both TB (HR, 2.06) and CNS (HR, 2.16) independently predicted overall survival in multivariate analysis.
  • TB (AUC, 0.7065) showed slightly better discrimination than CNS (AUC, 0.6975) for overall survival.
  • The combination of TB and CNS achieved the highest prognostic performance (AUC, 0.7192).

Conclusions:

  • TB in pretreatment cervical cancer biopsies is a reliable morphologic prognosticator.
  • TME features like TB and CNS can enhance precision oncology by revealing tumour biology.
  • These H&E-based features are valuable, particularly in low-resource settings, potentially reducing the need for further testing.