Background: Human sarcomas (SARC) are a group of malignant tumors that originated from mesenchymal lineages with more than 60 subtypes. However, potential biomarkers for the diagnosis and prognosis of SARC remain to be investigated.
Methods: We obtained three GSE raw matrix files (GSE39262, GSE21122, GSE48418) that related to various subtypes of sarcoma from the public GEO database and explored the widely differential expression genes in three obtained GSE files. Then common differential expression genes (CDGEs) were identified. We analyzed the correlation between the expression of the top five interacted genes of CDEGs and genome-wide differences, prognosis, genetic mutation, functional enrichment, immune infiltration, immune checkpoint, and marker genes’ expression of N6-methyladenosine (m⁶A) modification in SARC patients. Besides, a prognostic nomogram was constructed to predict the survival of SARC patients.
Results: Among the three GSE files, 42 CDGEs were identified, and the top five interacted genes were ASPM, CCNB2, PRC1, AURKA, and SCM2. The expression levels of the five genes were higher in the SARC group than that in the normal group. The transcriptional level of CCNB2, PRC, and SCM2 was correlated to the worse survival of SARC. The constructed nomogram that combined CNB2, PRC1, and SCM2 showed a fairly good incredibility in predicting the survival of SARC (C-index: 0.711). Furthermore, the five genes were widely involved in immune infiltration, immune checkpoint, and m⁶A modification. In addition, we found a minor survival-related mutation rate (9%) of the five identified genes in SARC patients (p < 0.05).
Conclusion: The results suggested the five identified genes widely participated in the prognosis, immune infiltration, immune checkpoint, and m⁶A modification of SARC patients. This study provided a theoretical basis for the research about the correlation between the level of five identified genes and sarcoma, but the further mechanism needs to be verified by experiments.
Keywords: sarcoma, bioinformatics, prognostic values, differential expression gene, ASPM , CCNB2 , PRC1 , AURKA , SCM2