PMID- 28759038
OWN - NLM
STAT- MEDLINE
DCOM- 20171201
LR  - 20180512
IS  - 1476-5594 (Electronic)
IS  - 0950-9232 (Linking)
VI  - 36
IP  - 46
DP  - 2017 Nov 16
TI  - High-depth, high-accuracy microsatellite genotyping enables precision lung cancer
      risk classification.
PG  - 6383-6390
LID - 10.1038/onc.2017.256 [doi]
AB  - There remains a large discrepancy between the known genetic contributions to
      cancer and that which can be explained by genomic variants, both inherited and
      somatic. Recently, understudied repetitive DNA regions called microsatellites
      have been identified as genetic risk markers for a number of diseases including
      various cancers (breast, ovarian and brain). In this study, we demonstrate an
      integrated process for identifying and further evaluating microsatellite-based
      risk markers for lung cancer using data from the cancer genome atlas and the 1000
      genomes project. Comparing whole-exome germline sequencing data from 488 TCGA
      lung cancer samples to germline exome data from 390 control samples from the 1000
      genomes project, we identified 119 potentially informative microsatellite loci.
      These loci were found to be able to distinguish between cancer and control
      samples with sensitivity and specificity ratios over 0.8. Then these loci,
      supplemented with additional loci from other cancers and controls, were evaluated
      using a target enrichment kit and sample-multiplexed nextgen sequencing. Thirteen
      of the 119 risk markers were found to be informative in a well powered study
      (>0.99 for a 0.95 confidence interval) using high-depth (579x+/-315) nextgen
      sequencing of 30 lung cancer and 89 control samples, resulting in sensitivity and
      specificity ratios of 0.90 and 0.94, respectively. When 8 loci harvested from the
      bioinformatic analysis of other cancers are added to the classifier, then the
      sensitivity and specificity rise to 0.93 and 0.97, respectively. Analysis of the 
      genes harboring these loci revealed two genes (ARID1B and REL) and two
      significantly enriched pathways (chromatin organization and cellular stress
      response) suggesting that the process of lung carcinogenesis is linked to
      chromatin remodeling, inflammation, and tumor microenvironment restructuring. We 
      illustrate that high-depth sequencing enables a high-precision
      microsatellite-based risk classifier analysis approach. This microsatellite-based
      platform confirms the potential to create clinically actionable diagnostics for
      lung cancer.
FAU - Velmurugan, K R
AU  - Velmurugan KR
AD  - Department of Biological Sciences, Center for Bioinformatics and Genetics and the
      Primary Care Research Network, Edward Via College of Osteopathic Medicine,
      Blacksburg, VA, USA.
AD  - Department of Biological Sciences, Gibbs Cancer Center and Research Institute,
      Spartanburg, SC, USA.
FAU - Varghese, R T
AU  - Varghese RT
AD  - Department of Biological Sciences, Center for Bioinformatics and Genetics and the
      Primary Care Research Network, Edward Via College of Osteopathic Medicine,
      Blacksburg, VA, USA.
AD  - Department of Biological Sciences, Gibbs Cancer Center and Research Institute,
      Spartanburg, SC, USA.
FAU - Fonville, N C
AU  - Fonville NC
AD  - Department of Biological Sciences, Riverside Law, LLP Glenhardie Corporate
      Center, Wayne, PA, USA.
FAU - Garner, H R
AU  - Garner HR
AD  - Department of Biological Sciences, Center for Bioinformatics and Genetics and the
      Primary Care Research Network, Edward Via College of Osteopathic Medicine,
      Blacksburg, VA, USA.
AD  - Department of Biological Sciences, Gibbs Cancer Center and Research Institute,
      Spartanburg, SC, USA.
LA  - eng
PT  - Journal Article
PT  - Research Support, U.S. Gov't, Non-P.H.S.
PT  - Research Support, Non-U.S. Gov't
DEP - 20170731
PL  - England
TA  - Oncogene
JT  - Oncogene
JID - 8711562
RN  - 0 (Biomarkers, Tumor)
SB  - IM
MH  - Biomarkers, Tumor/*genetics
MH  - Exome/genetics
MH  - Genetic Predisposition to Disease/*genetics
MH  - Genomics/methods
MH  - Genotype
MH  - Genotyping Techniques/*methods
MH  - High-Throughput Nucleotide Sequencing/methods
MH  - Humans
MH  - Lung Neoplasms/classification/*genetics
MH  - Microsatellite Repeats/*genetics
MH  - Reproducibility of Results
MH  - Risk Factors
PMC - PMC5701090
EDAT- 2017/08/02 06:00
MHDA- 2017/12/02 06:00
CRDT- 2017/08/01 06:00
PHST- 2016/11/08 00:00 [received]
PHST- 2017/06/01 00:00 [revised]
PHST- 2017/06/13 00:00 [accepted]
PHST- 2017/08/02 06:00 [pubmed]
PHST- 2017/12/02 06:00 [medline]
PHST- 2017/08/01 06:00 [entrez]
AID - onc2017256 [pii]
AID - 10.1038/onc.2017.256 [doi]
PST - ppublish
SO  - Oncogene. 2017 Nov 16;36(46):6383-6390. doi: 10.1038/onc.2017.256. Epub 2017 Jul 
      31.