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Series GSE127934 Query DataSets for GSE127934
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
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.
 
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.
 
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
Phone 9177762533
Organization name 1st Hospital of Jilin University
Lab Yongjun Liu Lab
Street address 519 Dongminzhu Ave
City Changchun
State/province Jilin
ZIP/Postal code 130061
Country China
 
Platforms (1)
GPL20795 HiSeq X Ten (Homo sapiens)
Samples (14)
GSM3656784 N_ILC3_1
GSM3656785 N_ILC3_2
GSM3656786 N_ILC3_3
Relations
BioProject PRJNA525832
SRA SRP187734

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE127934_RAW.tar 57.3 Mb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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