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MAPK1/ERK2 as novel target genes for pain in head and neck cancer patients.

Authors :
Reyes-Gibby, Cielito C.
Jian Wang
Silvas, Mary Rose T.
Yu, Robert
Yeung, Sai-Ching J.
Shete, Sanjay
Source :
BMC Genetics. 2/13/2016, Vol. 17, p1-13. 13p.
Publication Year :
2016

Abstract

Background: Genetic susceptibility plays an important role in the risk of developing pain in individuals with cancer. As a complex trait, multiple genes underlie this susceptibility. We used gene network analyses to identify novel target genes associated with pain in patients newly diagnosed with squamous cell carcinoma of the head and neck (HNSCC). Results: We first identified 36 cancer pain-related genes (i.e., focus genes) from 36 publications based on a literature search. The Ingenuity Pathway Analysis (IPA) analysis identified additional genes that are functionally related to the 36 focus genes through pathway relationships yielding a total of 82 genes. Subsequently, 800 SNPs within the 82 IPA-selected genes on the Illumina HumanOmniExpress-12v1 platform were selected from a large-scale genotyping effort. Association analyses between the 800 candidate SNPs (covering 82 genes) and pain in a patient cohort of 1368 patients with HNSCC (206 patients with severe pain vs. 1162 with non-severe pain) showed the highest significance for MAPK1/ERK2, a gene belonging to the MAP kinase family (rs8136867, p value = 8.92 × 10-4; odds ratio [OR] = 1.33, 95 % confidence interval [CI]: 1.13-1.58). Other top genes were PIK3C2G (a member of PI3K [complex], rs10770367, p value = 1.10 × 10-3; OR = 1.46, 95 % CI: 1.16-1.82), TCRA (the alpha chain of T-cell receptor, rs6572493, p value = 2.84 × 10-3; OR = 0.70, 95 % CI: 0.55-0.88), PDGFC (platelet-derived growth factor C, rs6845322, p value = 4.88 × 10-3; OR = 1.32, 95 % CI: 1.09-1.60), and CD247 (a member of CD3, rs2995082, p value = 7.79 × 10-3; OR = 0.76, 95 % CI: 0.62-0.93). Conclusions: Our findings provide novel candidate genes and biological pathways underlying pain in cancer patients. Further study of the variations of these candidate genes could inform clinical decision making when treating cancer pain. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712156
Volume :
17
Database :
Academic Search Index
Journal :
BMC Genetics
Publication Type :
Academic Journal
Accession number :
112956981
Full Text :
https://doi.org/10.1186/s12863-016-0348-7