Soft tissue sarcomas (STS) are a heterogeneous group of malignancies arising from mesenchymal tissues, including muscle, fat, nerves, and blood vessels (Gamboa et al., 2020). In the United States, the overall incidence of soft tissue sarcomas is approximately 3.4 cases per 100,000 people per year. From 2002–2014, the incidence of all sarcomas increased from 6.8 to 7.7 per 100,000 individuals. Approximately 13,590 new cases are expected in 2024 (Siegel et al., 2024, Xia et al., 2022). The median age at diagnosis for STS is around 58 years, with a notable increase in incidence among individuals over 50 years old (Gamboa et al., 2024, Han et al., 2024). The disease is more common in men than women. Racial disparities exist, with higher incidence rates observed in Black individuals (5.1 per 100,000) compared to White individuals (4.5 per 100,000). At the genomic level, STS are generally classified into two main categories: those with complex karyotypes and those with specific genetic alterations like translocations and point mutations. Despite multidisciplinary approaches based on anatomical site, tumor grade, and histological subtype, clinical management of STS remains challenging, with recurrence rates as high as 50 % after surgery (Wt et al., 2012). Patients with locally advanced and metastatic STS face particularly poor outcomes due to limited systemic treatment options. The inherent molecular heterogeneity within STS subtypes poses a significant barrier to effective treatment strategies. There is a critical need to move towards personalized treatment approaches that account for this heterogeneity, utilizing molecular tools for better risk stratification and biomarker-matched therapies. While genomic and epigenomic studies have provided valuable insights into the molecular landscape of STS, proteomics and single-cell sequencing offer additional layers of biological understanding. Integrating data from genomics, transcriptomics, proteomics, and single-cell sequencing can lead to more precise molecular classification and identification of actionable targets.

Although large-scale genomic studies have been conducted in STS, translating these findings into clinical practice remains a challenge. Recent advances in proteomics and single-cell analysis have shown promise in overcoming translational gaps by providing a more comprehensive view of tumor biology. These complementary approaches can unveil the complex interplay between genetic alterations, gene expression, protein dynamics, and cellular heterogeneity, leading to a deeper understanding of STS pathogenesis and therapeutic vulnerabilities.

The present study aims to integrate multiomics and single cell sequencing data to decipher the biological heterogeneity of STS. By leveraging the power of these cutting-edge technologies, we seek to identify distinct molecular subgroups within STS that can inform clinical risk stratification and improve therapeutic selections for patients. Our comprehensive profiling approach encompasses genomic, transcriptomic, proteomic, and single-cell analyses of a diverse cohort of STS samples, spanning multiple histological subtypes and anatomical sites. Through this integrative analysis, we anticipate uncovering novel molecular signatures and pathways that drive STS progression and contribute to treatment resistance. By dissecting the complex interplay between genetic alterations, gene expression patterns, and cellular heterogeneity, we aim to provide a more granular understanding of STS biology and identify potential therapeutic targets. Moreover, by integrating clinical data with our multiomics findings, we seek to develop robust prognostic and predictive biomarkers that can guide personalized treatment strategies for STS patients.