Dynamic urinary proteomics integrates single-cell and spatial transcriptomics to reveal tumour microenvironment and predict immunotherapy response in biliary tract cancer - Report - MDSpire

Dynamic urinary proteomics integrates single-cell and spatial transcriptomics to reveal tumour microenvironment and predict immunotherapy response in biliary tract cancer

  • By

  • Shanshan Wang

  • Zhengguang Guo

  • Boyu Sun

  • Kai Liu

  • Jiashuo Chao

  • Ziyu Xun

  • Yunchao Wang

  • Zibo Xu

  • Ziyue Huang

  • Hao Wang

  • Yang Tan

  • Nan Zhang

  • Mingjian Piao

  • Longhao Zhang

  • Chengjie Li

  • Shuofeng Li

  • Jiongyuan Li

  • Haidan Sun

  • Feng Qi

  • Aiwei Wang

  • XiaoBo Yang

  • Chengpei Zhu

  • Hanping Wang

  • Wei Sun

  • Haitao Zhao

  • July 1, 2026

  • 0 min

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Clinical Report: Integrative Analysis of Urinary Proteomics in Biliary Tract Cancer

Overview

This study explores the use of urinary proteomics as a non-invasive method to predict responsiveness to immune checkpoint inhibitors (ICIs) in biliary tract cancer (BTC). The findings suggest that urinary biomarkers can capture tumor microenvironment dynamics and may guide therapeutic decisions in clinical practice.

Background

Biliary tract cancers are aggressive malignancies often diagnosed at advanced stages, where ICIs are the primary treatment. However, the lack of reliable biomarkers for predicting ICI efficacy poses a significant challenge. Current tissue-based biomarkers are limited by invasiveness and their inability to reflect the dynamic nature of tumor-immune interactions, highlighting the need for innovative non-invasive approaches.

Data Highlights

Sample SizeUrine Samples Analyzed
73187 (64 pretreatment, 123 post-treatment)

Key Findings

  • Urinary proteomics provides a novel, non-invasive approach to predict ICI responsiveness in BTC.
  • Protein tyrosine phosphatase non-receptor 13 is identified as a promising biomarker for enhancing ICI outcomes.
  • The study integrates single-cell and spatial transcriptomics to elucidate tumor microenvironment dynamics.
  • Urinary biomarkers can facilitate early prediction and longitudinal monitoring of ICI responsiveness.
  • This approach may enable timely therapeutic adjustments in clinical practice.

Clinical Implications

The findings support the potential of urinary proteomics as a valuable tool for non-invasive biomarker discovery in immuno-oncology. Clinicians may utilize these biomarkers for better patient stratification and to monitor treatment responses in real-time, enhancing personalized therapy approaches.

Conclusion

Urinary proteomics represents a promising frontier in the search for dynamic biomarkers in biliary tract cancer, with the potential to significantly improve patient management and outcomes in immunotherapy.

Related Resources & Content

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  2. npj Digital Medicine, Combining Single-Cell and Spatial Transcriptomics with Explainable AI Uncovers Critical Prognostic Factors in Prostate Cancer, 2025 -- Combining Single-Cell and Spatial Transcriptomics with Explainable AI Uncovers Critical Prognostic Factors in Prostate Cancer
  3. Frontiers in Immunology, Multi-omics analysis of kidney renal cell carcinoma in silico with preliminary in vivo validation, 2026 -- Multi-omics analysis of kidney renal cell carcinoma in silico with preliminary in vivo validation
  4. Frontiers in Oncology, Progress in the application of combined detection of urinary tumor DNA and exosomes in the classification, staging, and clinical management of bladder cancer: a review, 2026 -- Progress in the application of combined detection of urinary tumor DNA and exosomes in the classification, staging, and clinical management of bladder cancer: a review
  5. npj Digital Medicine — Comprehensive Molecular and Radiopathomic Analysis of AIRE-Influenced Immune Subtypes in Bladder Cancer
  6. Durvalumab Improves Survival in Bile Duct Cancers - NCI
  7. Frontiers | Immunohistochemistry in intrahepatic cholangiocarcinoma: histological subtyping and drug selection
  8. The current landscape of spatial biomarkers for prediction of response to immune checkpoint inhibition | npj Precision Oncology

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