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@ARTICLE{Deutelmoser:164288,
author = {H. Deutelmoser$^*$ and J. Lorenzo Bermejo and A. Benner$^*$
and K. Weigl$^*$ and H. A. Park$^*$ and M. Haffa$^*$ and E.
Herpel and M. Schneider and C. M. Ulrich$^*$ and M.
Hoffmeister$^*$ and J. Chang-Claude$^*$ and H. Brenner$^*$
and D. Scherer$^*$},
title = {{G}enotype-{B}ased {G}ene {E}xpression in {C}olon
{T}issue-{P}rediction {A}ccuracy and {R}elationship with the
{P}rognosis of {C}olorectal {C}ancer {P}atients.},
journal = {International journal of molecular sciences},
volume = {21},
number = {21},
issn = {1422-0067},
address = {Basel},
publisher = {Molecular Diversity Preservation International},
reportid = {DKFZ-2020-02371},
pages = {8150},
year = {2020},
note = {#EA:C120#LA:C120#},
abstract = {Colorectal cancer (CRC) survival has environmental and
inherited components. The expression of specific genes can
be inferred based on individual genotypes-so called
expression quantitative trait loci. In this study, we used
the PrediXcan method to predict gene expression in normal
colon tissue using individual genotype data from 91 CRC
patients and examined the correlation ρ between predicted
and measured gene expression levels. Out of 5434 predicted
genes, $58\%$ showed a negative ρ value and only $16\%$
presented a ρ higher than 0.10. We subsequently
investigated the association between genotype-based gene
expression in colon tissue for genes with ρ > 0.10 and
survival of 4436 CRC patients. We identified an inverse
association between the predicted expression of ARID3B and
CRC-specific survival for patients with a body mass index
greater than or equal to 30 kg/m2 (HR (hazard ratio) = 0.66
for an expression higher vs. lower than the median, p =
0.005). This association was validated using genotype and
clinical data from the UK Biobank (HR = 0.74, p = 0.04). In
addition to the identification of ARID3B expression in
normal colon tissue as a candidate prognostic biomarker for
obese CRC patients, our study illustrates the challenges of
genotype-based prediction of gene expression, and the
advantage of reassessing the prediction accuracy in a subset
of the study population using measured gene expression
data.},
cin = {C120 / C060 / C070 / C020 / B280 / HD01},
ddc = {540},
cid = {I:(DE-He78)C120-20160331 / I:(DE-He78)C060-20160331 /
I:(DE-He78)C070-20160331 / I:(DE-He78)C020-20160331 /
I:(DE-He78)B280-20160331 / I:(DE-He78)HD01-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:33142733},
doi = {10.3390/ijms21218150},
url = {https://inrepo02.dkfz.de/record/164288},
}