Wen Jin, Jianli Liu, Tingyu Yang, Zongqi Feng, Jie Yang, Lei Cao, Chengyan Wu, Yongchun Zuo, Lan Yu
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引用次数: 0
Abstract
MicroRNAs (miRNAs) are crucial factors in gene regulation, and their dysregulation plays important roles in the immunity of gastric cancer (GC). However, finding specific and effective miRNA markers is still a great challenge for GC immunotherapy. In this study, we computed and analysed miRNA-seq, RNA-seq and clinical data of GC patients from the TCGA database. With the comparison of tumour and normal tissues in GC, we identified 2056 upregulated and 2311 downregulated protein-coding genes. Based on the miRNet database, more than 2600 miRNAs interact with these genes. Several key miRNAs, including hsa-mir-34a, hsa-mir-182 and hsa-mir-23b, were identified to potentially play important regulatory roles in the expression of most upregulated and downregulated genes in GC. Based on bioinformation approaches, the expressions of hsa-mir-34a and hsa-mir-182 were closely linked to the tumour stage, and high expression of hsa-mir-23b was correlated with poor survival in GC. Moreover, these three miRNAs are involved in immune cell infiltration (such as activated memory CD4 T cells and resting mast cells), particularly hsa-mir-182 and hsa-mir-23b. GSEA suggested that the changes in their expression may possibly activate/inhibit immune-related signal pathways, such as chemokine signalling pathway and CXCR4 pathway. These results will provide possible miRNA markers or targets for combined immunotherapy of GC.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.