Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma

Abstract

Abstract The present study aimed to improve the understanding of non-uterine leiomyosarcoma (NULMS) prognostic genes through system biology approaches. This cancer is heterogeneous and rare. Moreover, gene interaction networks have not been reported in NULMS yet. The datasets were obtained from the public gene expression databases. Seven co-expression modules were identified from 5000 most connected genes; using weighted gene co-expression network analysis. Using Cox regression, the modules showed favorable (HR = 0.6, 95% CI = 0.4–0.89, P = 0.0125), (HR = 0.65, 95% CI = 0.44–0.98, P = 0.04) and poor (HR = 1.55, 95% CI = 1.06–2.27, P = 0.025) prognosis to the overall survival (OS) (time = 3740 days). The first one was significant in multivariate HR estimates (HR = 0.4, 95% CI = 0.28–0.69, P = 0.0004). Enriched genes through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) revealed significant immune-related pathways; suggesting immune cell infiltration as a favorable prognostic factor. The most significant protective genes were ICAM3, NCR3, KLRB1, and IL18RAP, which were in one of the significant modules. Moreover, genes related to angiogenesis, cell–cell adhesion, protein glycosylation, and protein transport such as PYCR1, SRM, and MDFI negatively affected the OS and were found in the other related module. In conclusion, our analysis suggests that NULMS might be a good candidate for immunotherapy. Moreover, the genes found in this study might be potential candidates for targeted therapy.