Analysis of metastasis‑related risk factors and clinical relevance in adult soft‑tissue sarcoma

  • 0Department of Orthopedics, Shanghai Pudong New Area People's Hospital, Shanghai 201299, P.R. China.

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Summary

This summary is machine-generated.

A new five-gene signature predicts survival in adult soft-tissue sarcoma (ASTS) by identifying metastatic risk. This model aids in personalized treatment strategies for ASTS patients.

Area Of Science

  • Oncology
  • Genomics
  • Biomarker Discovery

Background

  • Metastasis significantly impacts prognosis in adult soft-tissue sarcoma (ASTS), with a 2-year survival rate around 30%.
  • Accurate prognostic models are crucial for personalized therapeutic strategies in ASTS.
  • Identifying metastatic characteristics can improve survival predictions for ASTS patients.

Purpose Of The Study

  • To develop and validate a prognostic prediction model for ASTS based on gene expression differences between metastatic and non-metastatic patients.
  • To identify key genes associated with metastasis and survival in ASTS.
  • To explore the functional implications of identified gene signatures in sarcoma progression.

Main Methods

  • Differential gene expression analysis of Gene Expression Omnibus (GEO) and Cancer Genome Atlas (TCGA) datasets.
  • Development of a five-gene prognostic signature (ACTG2, apolipoprotein D, coatomer protein complex subunit γ2 imprinted transcript 1, collagen type VI α6 chain, osteomodulin).
  • Functional enrichment, pathway analysis (including PI3K-Akt), immune infiltration analysis, and in vitro assays (wound-healing, Transwell) to validate gene significance.

Main Results

  • A five-gene signature was developed and validated, categorizing ASTS patients into high- and low-risk groups.
  • High-risk patients showed activated stemness, extracellular matrix, cell adhesion, and PI3K-Akt pathways.
  • Inhibition of ACTG2 reduced cell migration and invasion in a sarcoma cell line, confirming its role in metastasis.

Conclusions

  • A validated metastasis-based prognostic model for ASTS has been successfully developed.
  • This model accurately predicts survival and offers insights into sarcoma metastasis mechanisms.
  • The findings support the design of tailored therapeutic regimens for ASTS patients.