A novel immune-related gene signature predicting survival in sarcoma patients

Jiang Zhu,Sven Jacob,Elise Pretzsch,Martin K Angele,Haochen Yu,Lars H Lindner,Markus Albertsmeier,Florian Bösch,Jens Werner,Haoyu Ren,Thomas Knösel,Alexandr V Bazhin

doi:10.1016/j.omto.2021.12.007

Abstract

Sarcomas are a heterogeneous group of rare mesenchymal tumors. The migration of immune cells into these tumors and the prognostic impact of tumor-specific factors determining their interaction with these tumors remain poorly understood. The current risk stratification system is insufficient to provide a precise survival prediction and treatment response. Thus, valid prognostic models are needed to guide treatment. This study analyzed the gene expression and outcome of 980 sarcoma patients from seven public datasets. The abundance of immune cells and the response to immunotherapy was calculated. Immune-related genes (IRGs) were screened through a weighted gene co-expression network analysis (WGCNA). A least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish a powerful IRG signature predicting prognosis. The identified IRG signature incorporated 14 genes and identified high-risk patients in sarcoma cohorts. The 14-IRG signature was identified as an independent risk factor for overall and disease-free survival. Moreover, the IRG signature acted as a potential indicator for immunotherapy. The nomogram based on the risk score was built to provide a more accurate survival prediction. The decision tree with IRG risk score discriminated risk subgroups powerfully. This proposed IRG signature is a robust biomarker to predict outcomes and treatment responses in sarcoma patients.

Highlights

Sarcomas arise from the skeleton and the soft tissue subdividing in various histologic subtypes and have an increasing incidence of 7.7 cases/100,000 individuals per year.[1,2] In the European Union, about 27,908 new cases per year are registered.[3,4] The therapeutic approaches differ between the subgroups, but surgery offers the only chance of cure.[5,6] in large series, recurrence rates are as high as up to 45%, which underlines the importance of a precise diagnostic and therapeutic workup.[7,8] In this respect, the anatomic heterogeneity complicates the standardization of diagnosis and therapy
A weighted gene co-expression network analysis (WGCNA) was performed to Prognostic relevance of T cell subtypes and natural killer (NK) cells The univariate Cox regression analysis demonstrated that the abundance scores of eleven immune cells and the infiltration score were significantly associated with overall survival (OS) in the training set
The 256 patients of the TCGA-SARC cohort were divided into high-score and low-score groups based on the optimal immune-score-cutoff value, and the high-score group exhibited a better prognosis than the low-score group (Figures 2B–2J)

Summary

Introduction

Sarcomas arise from the skeleton and the soft tissue subdividing in various histologic subtypes and have an increasing incidence of 7.7 cases/100,000 individuals per year.[1,2] In the European Union, about 27,908 new cases per year are registered.[3,4] The therapeutic approaches differ between the subgroups, but surgery offers the only chance of cure.[5,6] in large series, recurrence rates are as high as up to 45%, which underlines the importance of a precise diagnostic and therapeutic workup.[7,8] In this respect, the anatomic heterogeneity complicates the standardization of diagnosis and therapy. The main prognostic criteria for sarcomas are tumor grade, size, histological subtype, and resection margin status,[9] which makes it challenging to precisely assess the

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Conclusion