Integrated Analysis of TME and Hypoxia Identifies a Classifier to Predict Prognosis and Therapeutic Biomarkers in Soft Tissue Sarcomas

SIMPLE SUMMARY: Soft tissue sarcomas are uncommon and diverse solid tumors with high risks that have a poor prognosis. Tumor microenvironment (TME) and hypoxia play critical roles in tumor development. Therefore, we aimed to determine whether linking hypoxia-related parameters to TME cells could improve prognosis and treatment outcomes. The Hypoxia-TME classifier was first proposed by us using TCGA-SARC court (n = 258) and fusion data from GSE63157 and GSE30929 (n = 225). This classifier is capable of correctly classifying patients based on their prognosis and immune type. In addition, immunotherapy and chemotherapy programs were provided in a more specific manner. Several key genes were identified for future research as a result of the classification results. ABSTRACT: Soft tissue sarcoma (STS) is one of the rarest but most aggressive cancer. It is important to note that intratumoral hypoxia and tumor microenvironment (TME) infiltration play a significant role in the growth and therapeutic resistance of STS. The goal of this study was therefore to determine whether linking hypoxia-related parameters to TME cells could provide a more accurate prediction of prognosis and therapeutic response. An analysis of 109 hypoxia-related genes and 64 TME cells was conducted in STS. Hypoxia-TME classifier was constructed based on 6 hypoxia prognostic genes and 8 TME cells. As a result, we evaluated the prognosis, tumor, and immune characteristics, as well as the effectiveness of therapies in Hypoxia-TME-defined subgroups. The Lowplus group showed a better prognosis and therapeutic response than any other subgroup. It is possible to unravel these differences based on immune-related molecules and somatic mutations in tumors. Further validation of Hypoxia-TME was done in an additional cohort of 225 STS patients. Additionally, we identified five key genes through differential analysis and RT-qPCR, namely, ACSM5, WNT7B, CA9, MMP13, and RAC3, which could be targeted for therapy. As a whole, the Hypoxia-TME classifier demonstrated a pretreatment predictive value for prognosis and therapeutic outcome, providing new approaches to therapy strategizing for patients.