Multi-Omics and Radiomics Approaches Uncover a TMSB10-Influenced Cell State for Non-Invasive Evaluation and Precision Classification in Breast Cancer - Summary - MDSpire

Multi-Omics and Radiomics Approaches Uncover a TMSB10-Influenced Cell State for Non-Invasive Evaluation and Precision Classification in Breast Cancer

  • By

  • Gui-Xin Wang

  • Jun-Ming Cao

  • Cheng-Lu Lu

  • Yun-Lin Wang

  • Zi-Yi Chen

  • Chang-Qing Yang

  • Shuo Wang

  • Zhang-Yin Guo

  • Yue Yu

  • Shan Cheng

  • Xin Wang

  • April 20, 2026

  • 0 min

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Objective:

To delineate breast cancer tumor cell heterogeneity and identify a tumor cell cluster influenced by TMSB10, which is crucial for non-invasive evaluation and precision classification.

Key Findings:
  • Identification of a poor-prognosis tumor cell cluster (C1) associated with late evolutionary state and metabolic reprogramming, indicating potential therapeutic targets.
  • High abundance of C1 cluster linked to poor survival and specific somatic mutations, suggesting a need for tailored treatment strategies.
  • C1 cluster predicted superior response to immune checkpoint blockade but not to chemo/radiotherapy, highlighting its role in immunotherapy.
  • TMSB10 was confirmed as a core gene promoting proliferation, migration, and invasion, indicating its potential as a therapeutic target.
Interpretation:

The C1 cluster is a key driver of breast cancer progression, influencing treatment responses and providing a target for non-invasive diagnostic and prognostic tools, which could improve patient outcomes.

Limitations:
  • Limited cohort sizes in previous studies may affect the generalizability of findings, potentially limiting the applicability of results.
  • Insufficient clinical-translational validation in some aspects of the research, necessitating further studies to confirm findings.
Conclusion:

The study highlights the potential of TMSB10 and the C1 cluster in breast cancer for non-invasive detection and prognostic stratification, paving the way for improved individualized patient management.

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