The construction and analysis of ceRNA and tumor-infiltrating immune cell networks in the distant metastasis of lung adenocarcinoma

Abstract

Abstract Lung adenocarcinoma (LUAD) is the most common lung cancer with a high rate of distant metastasis. The potential mechanism of competitive endogenous RNA (ceRNA) and tumor-infiltrating immune cells in LUAD distant metastasis is still unclear. RNA profiles of LUAD were downloaded from the cancer genome atlas (TCGA) including primary LUADs without or with distant metastasis. The miRNA-mRNA and lncRNA-miRNA interaction information were downloaded to establish the distant metastasis-specific ceRNA network. The algorithm “cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)” was used to estimate their immune cells. The Pearson correlation analysis was utilized to compare the prognostic biomarker in the ceRNA network and immune cell proportion. We established the two nomograms of metastasis-related ceRNA networks and immune cells. The Receiver Operating Characteristic (ROC) and the calibration curves indicated acceptable accuracy and discrimination of the nomogram. Based on the correction analysis between metastasis-related ceRNA and immune cells, along with external validation, NR3C2, PIK3R1, PTPN13, SPRY2 and mast cells resting were found to be associated with each other and constitute the potential regulation networks. Our data identify prognostic ceRNAs and immune cells and provide two prediction nomograms. Besides, the potential regulatory networks among NR3C2, PIK3R1, PTPN13, SPRY2 and mast cells resting are also uncovered, which may take part in the distant metastasis of LUAD.