A Complement-Related Gene Signature for Predicting Overall Survival and Immunotherapy Efficacy in Sarcoma Patients

Abstract

The prognoses of sarcomas are poor and the responses of them to systemic therapies are limited and controversial. Thus, there is an urgent need to stratify the risk factors and identify the patients who may benefit from systemic therapies. Here, we developed a reliable, complement-based gene signature to predict the prognosis of sarcoma patients. Survival-related complement genes were identified by univariate Cox analyses and were used to build a gene signature, which was further selected using the least absolute shrinkage and selection operator model, and determined using a stepwise Cox proportional hazards regression model. The whole sarcoma cohort of TCGA was randomly divided into a training set and a test set. The signature was constructed using the training set and validated subsequently in the test set, the whole TCGA sarcoma cohort, and another two independent cohorts from the TARGET and GEO databases, respectively. Furthermore, the prognostic value of the signature was also validated in an independent cohort from our center. This model effectively predicted prognoses across the training set, different validation cohorts, and different clinical subgroups. Next, immune cell infiltration analysis, GO and KEGG analysis, and gene set enrichment analysis were performed to explore possible underlying mechanisms of this signature. Moreover, this signature may predict the response to immunotherapy. Collectively, the current complement-related gene signature can predict overall survival and possible immunotherapy response of sarcoma patients; it may serve as a powerful prognostic tool to further optimize clinical treatment and prognosis management for sarcoma patients.

The Immune Contexture of Liposarcoma and Its Clinical Implications

“…Dancsok et al observed that a high CD56 + score was linked to significantly worse OS in mutation- and/or copy number-driven sarcomas (including WDLPS and DDLPS) while the overall CD56 expression in this cohort was remarkably low [ 86 ]. In contrast, a high NK cell-related gene signature was associated with a significantly prolonged OS in the TCGA-SARC cohort (including DDLPS) as confirmed by two independent studies [ 101 , 105 ]. However, a separate analysis of the histological subtypes within the TCGA-SARC cohort revealed that a NK cell signature was not significantly correlated with DSS in DDLPS [ 90 ].…”

“…Zhu and Hou showed that CD8 + T cell and Treg gene signatures were significantly associated with prolonged OS [ 104 ]. A third study reported no significant correlation between both CD8 + T cells and Tregs and OS [ 105 ]. Regarding publicly available transcriptome databases, the composition of the patient cohort and, most importantly, the applied gene signatures may vary among the studies and thereby cause conflicting results that are based on the same initial dataset.…”