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2016 ; 8
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): ä Nephropedia Template TP
gab.com Text
Twit Text FOAVip
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English Wikipedia
Comprehensive Assessments of RNA-seq by the SEQC Consortium: FDA-Led Efforts
Advance Precision Medicine
#MMPMID26999190
Xu J
; Gong B
; Wu L
; Thakkar S
; Hong H
; Tong W
Pharmaceutics
2016[Mar]; 8
(1
): ä PMID26999190
show ga
Studies on gene expression in response to therapy have led to the discovery of
pharmacogenomics biomarkers and advances in precision medicine. Whole
transcriptome sequencing (RNA-seq) is an emerging tool for profiling gene
expression and has received wide adoption in the biomedical research community.
However, its value in regulatory decision making requires rigorous assessment and
consensus between various stakeholders, including the research community,
regulatory agencies, and industry. The FDA-led SEquencing Quality Control (SEQC)
consortium has made considerable progress in this direction, and is the subject
of this review. Specifically, three RNA-seq platforms (Illumina HiSeq, Life
Technologies SOLiD, and Roche 454) were extensively evaluated at multiple sites
to assess cross-site and cross-platform reproducibility. The results demonstrated
that relative gene expression measurements were consistently comparable across
labs and platforms, but not so for the measurement of absolute expression levels.
As part of the quality evaluation several studies were included to evaluate the
utility of RNA-seq in clinical settings and safety assessment. The neuroblastoma
study profiled tumor samples from 498 pediatric neuroblastoma patients by both
microarray and RNA-seq. RNA-seq offers more utilities than microarray in
determining the transcriptomic characteristics of cancer. However, RNA-seq and
microarray-based models were comparable in clinical endpoint prediction, even
when including additional features unique to RNA-seq beyond gene expression. The
toxicogenomics study compared microarray and RNA-seq profiles of the liver
samples from rats exposed to 27 different chemicals representing multiple
toxicity modes of action. Cross-platform concordance was dependent on chemical
treatment and transcript abundance. Though both RNA-seq and microarray are
suitable for developing gene expression based predictive models with comparable
prediction performance, RNA-seq offers advantages over microarray in profiling
genes with low expression. The rat BodyMap study provided a comprehensive rat
transcriptomic body map by performing RNA-Seq on 320 samples from 11 organs in
either sex of juvenile, adolescent, adult and aged Fischer 344 rats. Lastly, the
transferability study demonstrated that signature genes of predictive models are
reciprocally transferable between microarray and RNA-seq data for model
development using a comprehensive approach with two large clinical data sets.
This result suggests continued usefulness of legacy microarray data in the coming
RNA-seq era. In conclusion, the SEQC project enhances our understanding of
RNA-seq and provides valuable guidelines for RNA-seq based clinical application
and safety evaluation to advance precision medicine.