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RNA-sequencing: HNSCC tissue and adjacent normal tissue

ABSTRACT: RNA-sequencing: HNSCC tissue and adjacent normal tissue

PROVIDER: PRJNA668735 | ENA |

REPOSITORIES: ENA

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Dataset's files

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			Action	DRS
	SRR12809360_1.fastq.gz	Fastqsanger.gz
	SRR12809360_2.fastq.gz	Fastqsanger.gz
	SRR12809361_1.fastq.gz	Fastqsanger.gz
	SRR12809361_2.fastq.gz	Fastqsanger.gz
	SRR12809362_1.fastq.gz	Fastqsanger.gz

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Project description:Purpose: Liver-specific MPC-knockout (Mpc1-/-, LivKO) mice develop less liver tumors than wild-type (Mpc1+/+) mice when given a DEN/CCl4 hepatocarcinogenesis protocol. The goals of this study are to compare transcriptome changes (RNA-seq) between liver tumor and normal-adjacent tissue in WT and Mpc1-/- mice. Methods: Total RNA was collected from tumor and paired normal-adjacent liver samples using the Qiagen miRNeasy kit. RNA from four samples each of wild-type tumor (WT-Tumor), paired wild-type normal-adjacent (WT normal adjacent), Mpc1-/- (MPC LivKO) tumor (MPC LivKO-Tumor), and paired MPC LivKO normal-adjacent (MPC LivKO normal adjacent) tissue was isolated. Each tumor and its paired normal-adjacent tissue were analyzed in a paired manner. Library preparation and sequencing were performed using the Illumina mRNA-Seq workflow. For data normalization, the raw number of reads for each transcript was converted to Fragments Per Kilobase of transcript per Million mapped reads (FPKM). FPKM values were log transformed, and unsupervised clustering was performed on samples based on normalized expression of genes with variation in Euclidean distance among samples of at least 2.5 standard deviations using Cluster 3 software. Results: Using an optimized data analysis workflow, we mapped about 50 million sequence reads per sample to the mouse genome (buildmm10) and identified 15,777 transcripts in the liver tissue samples of WT an Mpc1-/- (MPC LivKO) with Illumina workflow. FPKM values were log transformed, and unsupervised clustering was performed using Cluster 3 software. Unsupervised clustering analysis identified six gene expression groups: (1) increased gene expression in both WT and LivKO tumors, (2) increased gene expression in WT tumors, (3) increased gene expression in MPC LivKO tumors, (4) decreased gene expression down in both WT and LivKO tumors, (5) decreased gene expression in WT tumors, and (6) decreased gene expression in MPC LivKO tumors. Conclusions: Our study is the first on Mpc1-/- liver tumors. The HCC markers Alpha-fetoprotein (Afp) and Glypican-3 (Gpc3) were in the cluster of genes upregulated in both WT and MPC LivKO tumors. In the cluster of 14 genes up-regulated in only WT tumors were two GSTs: Gsta1 and Gstp2. In the cluster of 108 genes down-regulated in only MPC LivKO tumors were three GSTs: Gsta2, Gsta3, and Mgst1. That same cluster contained Gpx1, glutathione peroxidase (Gpx1). Thus, we concluded WT tumors increased but MPC LivKO tumors decreased expression of glutathione metabolizing genes.

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RNA-sequencing: HNSCC tissue and adjacent normal tissue

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