1576P - Genome wide association study (GWAS) for identification of single nucleotide polymorphisms (SNPs) associated with individuals presenting extreme ph...

Date 28 September 2014
Event ESMO 2014
Session Poster Display session
Topics Cancer Aetiology, Epidemiology, Prevention
Lung and other Thoracic Tumours
Translational Research
Presenter Jose Luis Perez-Gracia
Citation Annals of Oncology (2014) 25 (suppl_4): iv546-iv563. 10.1093/annonc/mdu358
Authors J.L. Perez-Gracia1, M.J. Pajares2, M.P. Andueza1, G. Pita3, J.P. De Torres4, C. Casanova5, J. Zulueta4, A. Gurpide1, J.M. Lopez-Picazo1, R. Baz Davila5, R. Alonso3, N. Alvarez3, R. Pio2, I. Melero2, M.F. Sanmamed1, A. Agudo6, C. Gonzalez6, J. Benitez3, L. Montuenga2, A. Gonzalez-Neira3
  • 1Oncology, Clinica Universidad de Navarra, 31008 - Pamplona/ES
  • 2Oncology, Center for Applied Medical Research (CIMA), Pamplona/ES
  • 3Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Madrid/ES
  • 4Neumology, Clinica Universidad de Navarra, 31008 - Pamplona/ES
  • 5Pulmonary Department And Research Department, Hospital Universitario La Candelaria Santa Cruz de Tenerife, Santa Cruz de Tenerife/ES
  • 6Unit Of Nutrition, Environment And Cancer, Catalan Institute of Oncology-ICO, IDIBELL, Barcelona/ES

Abstract

Aim

We analyzed the genome of individuals presenting extreme phenotypes of sensitivity and resistance to develop tobacco induced NSCLC to identify SNPs associated with these phenotypes. For this purpose, we used one of the most powerful GWAS platforms available. We hypothesized that SNPs may modulate individual susceptibility to carcinogens and that selection of extreme phenotypes would enrich the frequencies of alleles that contribute to the trait, thus increasing the power to identify them.

Methods

From an identification cohort (n=3631) we selected caucasian heavy smokers that either developed NSCLC at an early age (cancer-cohort) or that did not present NSCLC at an advanced age (cancer-free cohort). We analyzed their genomic DNA using the array Illumina HumanOmni 2.5 Quad that includes over 2 million powerful markers selected from the 1000 Genomes Project, targeting genetic variation down to 1% minor allele frequency. Statistical significance of SNPs was calculated using logistic regression and Fisher´s test.

Results

96 patients (48 per cohort) were selected. Mean age for the cancer and cancer-free cohorts was 49 years (range 38-55) and 76 years (72-84). Mean tobacco consumption was 41 pack-years (range 18-99) and 68 pack-years (40-120). GWAS identified 8 SNPs differentially expressed by logistic regression and 54 SNP by Fisher´s test (p<10-5). Odds-ratio ranged between 0.08-0.29 for protective SNPs and 3.4-11.2 for SNPs that increased NSCLC risk. Candidate SNPs were located within or in adjacent regions of genes that have been previously related with cancer and that constitute potentially relevant targets (table 1):

Function

Gene

Oncogenes

MSX2

SOX11

Tumor supressors

CSMD1

FOXF1

Tobacco induced NSCLC

ABCB5

Regulators of transcription

DROSHA

HDAC9

KIAA0947

Regulators of inflammation

PellinoE3

TRIM9

Related with cancer

ABHD6

GRIK1

RAB40B

SCN1A

SLC24A2

SLC25A26

ZFYVE26

Conclusions

We identified candidate SNPs associated with the risk of developing tobacco-induced NSCLC in individuals with extreme phenotypes. Several identified SNPs were located within or near genes that constitute potentially relevant targets for modulation of cancer risk. Validation of the most significant SNPs in an independent set of individuals with similar phenotypes, selected from the EPIC-Spain project (www.epic-spain.com, n=40,000) is ongoing.

Disclosure

All authors have declared no conflicts of interest.