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2016 ; 7
(44
): 71514-71525
Nephropedia Template TP
gab.com Text
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Paired proteomics, transcriptomics and miRNomics in non-small cell lung cancers:
known and novel signaling cascades
#MMPMID27588394
Backes C
; Ludwig N
; Leidinger P
; Huwer H
; Tenzer S
; Fehlmann T
; Franke A
; Meese E
; Lenhof HP
; Keller A
Oncotarget
2016[Nov]; 7
(44
): 71514-71525
PMID27588394
show ga
High-throughput omics analyses are applied to elucidate molecular pathogenic
mechanisms in cancer. Given restricted cohort sizes and contrasting large feature
sets paired multi-omics analysis supports discovery of true positive deregulated
signaling cascades. For lung cancer patients we measured from the same tissue
biopsies proteomic- (6,183 proteins), transcriptomic- (34,687 genes) and miRNomic
data (2,549 miRNAs). To minimize inter-individual variations case and control
lung biopsies have been gathered from the same individuals.Considering single
omics entities, 15 of 2,549 miRNAs (0.6%), 752 of 34,687 genes (2.2%) and 141 of
6,183 proteins (2.3%) were significantly deregulated. Multivariate analysis also
revealed that effects in miRNA were smaller compared to genes and proteins
indicating that expression changes of miRNAs might also have limited impact of
pathogenicity. However, a new algorithm for modeling the complex mutual
interactions of miRNAs and their target genes facilitated precise prediction of
deregulation in cancer genes (92.3% accuracy, p=0.007). Lastly, deregulation of
genes in cancer matched deregulation of proteins coded by the genes in 80% of
cases.The resulting interaction network, which is based on quantitative analysis
of the abundance of miRNAs, mRNAs and proteins each taken from the same lung
cancer tissue and from the same autologous normal lung tissue confirms molecular
pathological changes and further contributes to the discovery of altered
signaling cascades in lung cancer.
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