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Status |
Public on Mar 16, 2021 |
Title |
Correlation between immune lymphoid cells and plasmacytoid DCs in colon cancer |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by high throughput sequencing
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Summary |
Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to use RNA-seq to compare ILC3s and pDCs gene expression in colon cancer. Results: Using an optimized data analysis workflow, More than >60 million clean reads were obtained from each sample group after elimination of low-quality reads. A total of 14,943 in ILC3s and 10,840 in pDCs DEGs were found up-regulated and 4,213 in ILC3s and 11,549 DEGs in pDC s down-regulated on comparison of ILC3s and pDCs from tumor samples and controls samples transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusion: These findings highlighting the important roles of ILC3s and pDCs in the processes of tumor progression and inhibition in colon cancer promote the development of new strategies for inducing antitumor immune responses in metastatic and recurrent colon cancer.
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Overall design |
Methods: ILC3s and pDCs mRNA profiles of tumor sample and those of control were generated by deep sequencing, using Hiseq Xten.The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks.
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Contributor(s) |
Chen J, Wu J |
Citation(s) |
33708200 |
Submission date |
Mar 06, 2019 |
Last update date |
Mar 16, 2021 |
Contact name |
Jing Wu |
E-mail(s) |
jeanwood2012@126.com
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Phone |
9177762533
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Organization name |
1st Hospital of Jilin University
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Lab |
Yongjun Liu Lab
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Street address |
519 Dongminzhu Ave
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City |
Changchun |
State/province |
Jilin |
ZIP/Postal code |
130061 |
Country |
China |
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Platforms (1) |
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Samples (14)
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Relations |
BioProject |
PRJNA525832 |
SRA |
SRP187734 |