Identification of mC-related molecular subtypes and prediction models in the prognosis and tumor microenvironment infiltration of soft tissue sarcoma.

BACKGROUND

The epigenetic regulator in cancer progression and immune response has been demonstrated recently. However, the potential implications of 5-methylcytosine (mC) in soft tissue sarcoma (STS) are unclear.

METHODS

The RNA sequence profile of 911 normal and 259 primary STS tissues were obtained from GTEx and TCGA databases, respectively. We systematically analyzed the mC modification patterns of STS samples based on 11 mC regulators, and comprehensively correlated these modification patterns with clinical characteristics, prognosis, and tumor microenvironment (TME) cell-infiltrating. Furthermore, an mC-related signature was generated using Cox proportional hazard model and validated by the GSE17118 cohort.

RESULTS

Two distinct mC modification patterns (cluster1/2) were discovered. The cluster1 had favorable overall survival, higher immune score, higher expression of most immune checkpoints, and active immune cell infiltration. The GSVA analysis of the P53 pathway, Wnt signaling pathway, G2M checkpoint, mTORC1 signaling, Wnt/β catenin signaling, and PI3K/AKT/mTOR signaling were significantly enriched in the cluster2. Moreover, 1220 genes were differentially expressed between two clusters, and a mC prognostic signature was constructed with five mC-related genes. The signature represented an independent prognostic factor and showed the favorable performance in the GSE17118 cohort. Patients in the low-risk group showed higher immunoscore and higher expression of most immune checkpoints. Further GSVA analysis indicated that the levels of P53 pathway, Wnt signaling pathway, and TGF-β signaling pathway were different between low- and high-risk groups. Moreover, a nomogram incorporating mC signature and clinical variables was established and showed well performance.

CONCLUSION

This work showed that the mC modification plays a significant role in the progression of STS and the formation of TME diversity. Evaluating the mC modification pattern of tumor will enhance our cognition of TME infiltration characterization to guide more effective immunotherapy strategies.