# The recurrence or metastasis related gene predicts the prognosis of extremity and trunk soft tissue sarcoma

## TL;DR

This study identifies genes linked to recurrence in soft tissue sarcomas and develops a model to predict patient outcomes.

## Contribution

A novel risk score model (RRSM) is developed to predict relapse and prognosis in soft tissue sarcomas.

## Key findings

- Relapsed STS showed distinct multi-omic profiles compared to primary tumors.
- The RRSM model accurately predicted relapse-free survival and was validated in multiple datasets.
- Genes FZD7, ITPKA, and PRKAG1 were confirmed to be involved in recurrence and may guide treatment.

## Abstract

Relapsed soft tissue sarcomas (STS) have poor prognosis and limited treatment options. However, the molecular mechanism underlying recurrence and the prognostic predictor for STS are unclear.

We enrolled 35 extremity and trunk STS patients. Tumor specimens of 20 relapsed and 15 primary STS underwent sequencing to detect DNA mutation, RNA expression, and DNA methylation. Moreover, 206 STS cases from The Cancer Genome Atlas (TCGA) were utilized to construct the relapse-associated risk score model (RRSM), validated using three Gene Expression Omnibus datasets. Key model genes, COL6A3, FZD7, ITPKA, and PRKAG1, were validated in formalin-fixed paraffin-embedded tissue sections from primary and relapsed STS patients, confirming their potential involvement in STS recurrence.

The primary STS exhibited an immune-enriched tumor microenvironment, whereas the tumor microenvironment of relapsed STS had features that promote tumor recurrence or metastasis. The RRSM could predict relapse-free survival in TCGA STS and performed well in the validation cohort. Multivariate analysis revealed that RRSM was an independent prognostic factor. Moreover, the nomogram developed had excellent predictive ability.

This study revealed different multi-omic profiles between relapsed and primary STS. RRSM is a potential prognostic predictor for STS and lays a foundation for early intervention of high-risk STS patients. The expression of genes FZD7, ITPKA, and PRKAG1 may guide STS treatment decisions.