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Transcriptome Analysis of CircMRPS35 mediated mRNA expression profiles

ABSTRACT: Purpose: To explore the mechanism of circMRPS35-mediated suppression of proliferation and invasion in gastric cancer. Methods: MGC-803 cells were transfected with control and SiRNA-circMRPS35, in triplicate. Total RNA was extracted using Trizol reagent.

ORGANISM(S): Homo sapiens

PROVIDER: GSE121382 | GEO | 2019/11/01

REPOSITORIES: GEO

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Project description:We performed RNA-seq to investigate the differences in the gene expression profiles between primary gastric cancer (PGC) and paired metastatic gastric cancer (MGC). RNA-sequencing was performed on 7 paired PGC and MGC FFPE tissues. The transcriptome profiling of the two groups (MGC vs PGC) including immune response gene signature was analyzed. Total RNA was isolated using Trizol reagent. Extracted RNA samples were processed using the QuantSeq 3’mRNA-Seq Library Prep Kit and sequenced on an Illumina NextSeq 500. QuantSeq 3’mRNA-Seq reads were aligned using Bowtie2. The alignment file was used to assemble transcripts and the Read Count data was processed based on quantile normalization method using EdgeR within R. We identified 519 differentially regulated genes between the two sets, 76 of which were significantly up-regulated and 443 significantly down-regulated in MGCs. Among DEGs, 33 immune response genes were selected using QuickGO database (https://www.ebi.ac.uk/QuickGO/), with majority (27/33) of them exhibiting downregulation in the MGC samples. In summary, RNA sequencing data revealed that immune-related gene expression were down-regulated in MGC compared to PGC. We performed RNA-seq to investigate the differences in the gene expression profiles between primary gastric cancer (PGC) and paired metastatic gastric cancer (MGC). RNA-sequencing was performed on 7 paired PGC and MGC FFPE tissues. The transcriptome profiling of the two groups (MGC vs PGC) including immune response gene signature was analyzed. Total RNA was isolated using Trizol reagent. Extracted RNA samples were processed using the QuantSeq 3’mRNA-Seq Library Prep Kit and sequenced on an Illumina NextSeq 500. QuantSeq 3’mRNA-Seq reads were aligned using Bowtie2. The alignment file was used to assemble transcripts and the Read Count data was processed based on quantile normalization method using EdgeR within R. We identified 519 differentially regulated genes between the two sets, 76 of which were significantly up-regulated and 443 significantly down-regulated in MGCs. Among DEGs, 33 immune response genes were selected using QuickGO database (https://www.ebi.ac.uk/QuickGO/), with majority (27/33) of them exhibiting downregulation in the MGC samples. In summary, RNA sequencing data revealed that immune-related gene expression were down-regulated in MGC compared to PGC.

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Transcriptome Analysis of CircMRPS35 mediated mRNA expression profiles

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