The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Mesothelioma with Bone Metastasis

Abstract

Mesothelioma is a rare and aggressive tumor. Bone metastasis often occurs at the late-stage of this disease with poor quality of life. Thus, it is important to explore the tumorigenesis and bone metastasis mechanism of invasive mesothelioma. For this purpose, we downloaded the expression profiles of mRNAs, lncRNAs and miRNAs of 87 primary mesotheliomas were obtained from the TCGA database, including 4 patients with bone metastasis and 83 patients without it. Differential analysis revealed that 20 lncRNAs, 15 miRNAs and 230 mRNAs were significantly different in mesothelioma samples versus bone metastasis samples. We constructed the ceRNA network including 10 protein-coding mRNAs, 8 lncRNAs and 10 miRNAs. CIBERSORT was used to distinguish 22 immune cell types from the tumor transcriptomes. We established two nomograms based on tumor-infiltrating immune cells and ceRNA networks. Nine of 28 ceRNAs were found to be significant in Kaplan-Meier analysis. Out of the 22 cell types, the fraction of dendritic cells resting (P = 0.018) was significantly different between bone metastasis group and non-bone metastasis group. The ROC and the calibration curves based on ceRNA networks and tumor-infiltrating immune cells suggested acceptable accuracy respectively (AUC of 3-year survival: 0.827, AUC of 5-year survival: 0.840; AUC of 3-year survival: 0.730; AUC of 5-year survival: 0.753). Notably, based on the co-expression patterns between ceRNAs and Immune cells, we found that the hsa-miR-582-5p, CASP9, dendritic cells resting, ANIX2, T cells CD8 and T cells CD4 memory resting might associated with the mesothelioma bone metastasis. Funding: This work was supported by grants from the Natural Science Foundation of China (Grant No. 81702659; 81772856; 81501203), Youth Fund of Shanghai Municipal Health Planning Commission (No.2017YQ054) and Henan medical science and technology research project (Grant No. 201602031). Declaration of Interest: The authors declare no conflicts of interest in this work. Ethical Approval:The relevant data provided by TCGA are publicly available and do not require the approval of the local ethics committee.