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Coding variants in NOD-like receptors: An association study on risk and survival of colorectal cancer

Overview of attention for article published in PLOS ONE, June 2018
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Article details
Title
Coding variants in NOD-like receptors: An association study on risk and survival of colorectal cancer
Published in
PLOS ONE, June 2018
DOI 10.1371/journal.pone.0199350
Pubmed ID
Authors
Abstract

Nod-like receptors (NLRs) are important innate pattern recognition receptors and regulators of inflammation or play a role during development. We systematically analysed 41 non-synonymous single nucleotide polymorphisms (SNPs) in 21 NLR genes in a Czech discovery cohort of sporadic colorectal cancer (CRC) (1237 cases, 787 controls) for their association with CRC risk and survival. Five SNPs were found to be associated with CRC risk and eight with survival at 5% significance level. In a replication analysis using data of two large genome-wide association studies (GWASs) from Germany (DACHS: 1798 cases and 1810 controls) and Scotland (2210 cases and 9350 controls) the associations found in the Czech discovery set were not confirmed. However, expression analysis in human gut-related tissues and immune cells revealed that the NLRs associated with CRC risk or survival in the discovery set were expressed in primary human colon or rectum cells, CRC tissue and/or cell lines, providing preliminary evidence for a potential involvement of NLRs in general in CRC development and/or progression. Most interesting was the finding that the enigmatic development-related NLRP5 (also known as MATER) was not expressed in normal colon tissue but in colon cancer tissue and cell lines. Future studies may show whether regulatory variants instead of coding variants might affect the expression of NLRs and contribute to CRC risk and survival.

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The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 7 24%
Student > Ph. D. Student 5 17%
Researcher 3 10%
Student > Doctoral Student 2 7%
Student > Master 2 7%
Other 2 7%
Unknown 8 28%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 17%
Agricultural and Biological Sciences 5 17%
Medicine and Dentistry 4 14%
Nursing and Health Professions 3 10%
Materials Science 1 3%
Other 0 0%
Unknown 11 38%