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Transcriptomic-Based Classification Identifies Prognostic Subtypes and Therapeutic Strategies in Soft Tissue
Miguel Esperança-Martins1,2,3, Hugo Vasques3,4, Manuel Sokolov Ravasqueira5,6
1Medical Oncology Department, Unidade Local de Saúde de Santa Maria, 1649-028 Lisboa, Portugal.
Cancers
|September 13, 2025
Summary
A new transcriptomic subtype classification for soft tissue sarcomas (STSs) improves prognosis prediction and identifies novel molecular targets for precision treatment, outperforming current methods.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Current soft tissue sarcoma (STS) classification and prognostication tools have limitations.
- Molecular profiling offers potential for improved accuracy and personalized treatment.
Purpose of the Study:
- To develop a novel molecular-based classification for high-grade STS.
- To identify new molecular targets for precision medicine in STS.
Main Methods:
- DNA sequencing (DNA-seq) and RNA sequencing (RNA-seq) on 102 high-grade STS samples.
- Unsupervised machine learning for transcriptomic subtype identification.
- External validation using independent patient cohorts.
Main Results:
- Identified four transcriptomic subtypes (TCs) with significant prognostic value for overall survival (OS) and disease-free survival (DFS).
- TC-based classification demonstrated superior prognostic accuracy compared to SARCULATOR and CINSARC.
- Discovered novel molecular targets for precision treatment across TCs.
Conclusions:
- The novel TC-based classification provides superior prognostication for STS.
- This classification aids in identifying precision treatment targets.
- Represents a significant advancement in STS prognostication and treatment guidance.
