Content » Vol 99, Issue 13

Short communication

rs34567942 a Novel Susceptibility Single Nucleotide Polymorphism for Cutaneous Squamous Cell Carcinoma in Organ Transplant Recipients

Aleksandar Kuzmanov1, Weihong Qi2, Nadja Stenz3, Pierre-Yves Bochud4, Zoltan Kutalik5,6, Agnieszka Wójtowicz7, Gunther Hofbauer1 and the Swiss Transplant Cohort Study

1Department of Dermatology, University Hospital Zurich, Wagistrasse 14, CH-8952 Schlieren, 2Functional Genomics Centre Zurich, University of Zürich, 3Medical Faculty, University of Zürich, Zürich, 4Service of Infectious Diseases, University Hospital and University of Lausanne, 5Institute of Social and Preventive Medicine, University Hospital Lausanne (CHUV), 6Swiss Institute of Bioinformatics, and 7Service of Infectious Diseases, University Hospital and University of Lausanne, Lausanne, Switzerland. E-mail: Aleksandar.Kuzmanov@usz.ch

Accepted Sep 25, 2019; E-published Sep 25, 2019

INTRODUCTION

Cutaneous squamous cell carcinoma (cSCC) is the second most common type of solid human tumour and a main cause of cancer-related death in the general population (1, 2). Typically, it emerges on ultraviolet (UV)-exposed sun-damaged skin from benign intraepithelial lesions called actinic keratosis (AK) (3, 4). High-risk patient groups, such as organ transplant recipients (OTR), display a 65–250-fold increase in cSCC, making cSCC the most frequent cancer in this group (5). However, not all OTR develop cSCC, while some develop a multi-plicity of sSCC (1). This discrepancy is the major focus of the current study.

Specific genetic factors, such as single nucleotide polymorphisms (SNPs) determining cSCC susceptibility in OTRs, have been little-studied. Only a few papers have addressed this topic (6–8). Moreover, only one group has performed genome-wide association studies (GWAS), replicating 10 candidate SNPs previously associated with skin cancer in the general population; however, they did not show SNP-significant genome-wide association with cSCC in the OTRs (7). Our GWAS revealed novel OTR-specific SNP associated with cSCC susceptibility in OTR.

METHODS AND RESULTS

Patient data and material were collected prospectively from the Swiss Transplant Cohort Study (STCS), from adult solid-organ transplant recipients who received either kidney, liver, lung, heart, pancreas, small bowel or mixed organ transplant between 2008 and 2011. Skin cancer episodes after or during transplantation were reviewed by an independent clinician. All patients had provided written informed consent for participation in the STCS (including genetic analyses). The protocol was approved by the independent ethics committees of each Swiss participating centre (University Hospital of Lausanne; University Hospitals of Geneva; University Hospital Zürich; Cantonal Hospital St Gallen; Inselspital, Bern University Hospital; ClinicaLuganese, Lugano; and University Hospital of Basel and registered at ClinicalTrials.gov Identifier NCT01204944). To identify susceptibility SNPs for cSCC, GWAS were performed on 61 OTR patients with cSCC and 908 skin cancer negative-OTR patients. Genome-wide genotyping was performed on DNA samples extracted from EDTA blood using the Illumina® Human Omni Express chip Genome Studio software and default parameters were used to call genotypes. GWAS were conducted using frequentist association tests in SNPtest. Associations meeting the genome-wide threshold p-values of 5 × 10–8 were considered statistically significant.

The raw genotype data-set included 719,665 variants. After exclusion, 627,443 remained. The total number of imputed SNPs was 42,400,475. Exclusion criteria were: violation of Hardy-Weinberg-principle (p<1E-6), call rate < 0.95, minor allele frequency (MAF) < 0.01, and minor allele count (MAC) < 3. Untyped variants were imputed using a combined reference panel of the 1,000 Genomes Project phase 3 (9) and Genome of the Netherlands v5 (10) totalling more than 90 million genetic variants across the genome. The software package SHAPEIT (11) was used for phasing and IMPUTE2 (12) for imputation. The info statistic was computed to establish imputation accuracy and markers with info < 0.7 were excluded from further analysis.

For the complex MHC region, imputation of SNPs, multi-allelic markers, amino acids, and classical HLA alleles using validated SNP2HLA pipelines were performed. Preliminary results in a subset of samples with HLA serology data showed that accuracy is very high for HLA-A, -B, -DRB1, and DQB1 (> 95%), and high for HLA-C (90%) in Europeans.

Manhattan plots were generated using the R package qqman (http://biorxiv.org/content/biorxiv/early/2014/05/14/005165.full.pdf). SNPs were queried against dbSNP (https://www.ncbi.nlm.nih.gov/projects/SNP/) and the ensembl variation database (http://www.ensembl.org/info/genome/variation/index.html). The results were combined with annotation results obtained with snpEff (13).

GWAS identified 1 SNP, rs34567942, to be significantly associated with cSCC in OTRs at the p-value threshold of 5×10–8 (Fig. 1). Table I shows the characteristics of SNP rs345567942; namely the alternative nucleotide, imputation accuracy and imputation quality. rs34567942 is a non-protein-coding intergenic SNP, located in a non-repetitive DNA region (https://genome-euro.ucsc.edu) on chromosome 8.


Fig. 1. Manhattan plot visualizing genome-wide association of 61 cutaneous squamous cell carcinoma (cSCC)-organ transplant recipients (OTRs) and 908 skin cancer negative-OTRs, showing –log10 p-value of SNPtest along chromosomes. Horizontal red line represents the significant threshold p-value of 5×10–8. Arrow indicates single nucleotide polymorphism rs34567942 with the most prominent p-value.


Table I. Characteristics of single nucleotide polymorphism (SNP) rs345567942, namely the position of the SNP on the chromosome, reference and alternative allele (R/A), minor allele, minor allele frequency (MAF), imputation accuracy (Info) and whether a SNP is located in repetitive region of the DNA (RM-repetitive masker)

DISCUSSION

Studies dealing with the specific genetic factors determining cSCC susceptibility in OTR are scarce. Burger et al. performed allele-specific sequencing and revealed gene-specific SNPs in OTRs with cSCC (6). However, this study could not find significant associations between the SNPs and the risk of cSCC development in OTRs. Sanders et al. were the first to perform GWAS on OTRs with cSCC, even though this study replicates 10 candidate SNPs previously associated with skin cancer in the general population, it did not show SNP-significant genome-wide association with cSCC in the OTRs (7). In our GWAS, we have identified one novel non-coding SNP meeting the genome-wide significance and previously unrelated to cSCC susceptibility in OTR. In addition, the Variant Effect Predictor (http://grch37.ensembl.org/Homo_sapiens/Tools/VEP) incorporated LoFtool (Loss-of-Function tool) revealed possibly damaging effects of rs34567942 on the nearby FBXO25 gene (14). FBXO25 was shown to be expressed and mutated in head and neck SCC (http://www.cbioportal.org/), suggesting possible SNP involvement.

Despite the small sample size, the current study de-scribes a novel gene variation that could be functionally explored for development of safer individualized medication. Therefore, we will continue to expand the number of OTRs in this continuous project.

Bearing in mind that some GWAS hits are not replicated in subsequent populations, the results of this study should be considered preliminary until validated in a second set of cases and controls. In order to do this, we will continue expanding the number of OTRs in this continuous project. In conclusion, this study provides a novel gene variation that, once confirmed, could be functionally explored for development of safer individualized medication.

ACKNOWLEDGEMENTS

The members of the Swiss Transplant Cohort Study: Rita Achermann, Patrizia Amico, Philippe Baumann, Guido Beldi, Christian Benden, Christoph Berger, Isabelle Binet, Pierre-Yves Bochud, Elsa Boely, Heiner Bucher, Leo Bühler, Thierry Carell, Emmanuelle Catana, Yves Chalandon, Sabina de Geest, Olivier de Rougemont, Michael Dickenmann, Michel Duchosal, Thomas Fehr, Sylvie Ferrari- Lacraz, Christian Garzoni, Paola Gasche Soccal, Emiliano Giostra, Déla Golshayan, Daniel Good, Karine Hadaya, Jörg Halter, Dominik Heim, Christoph Hess, Sven Hillinger, Hans H. Hirsch, Uyen Huynh-Do, Franz Immer, Richard Klaghofer, Michael Koller, Bettina Laesser, Roger Lehmann, Christian Lovis, Hans-Peter Marti, Pierre Yves Martin, Luca Martinolli, Pascal Meylan, Paul Mohacsi, Isabelle Morard, Philippe Morel, Ulrike Mueller, Nicolas J. Mueller, Helen Mueller-McKenna, Antonia Müller, Thomas Müller, Beat Müllhaupt, David Nadal, Manuel Pascual, Jakob Passweg, Chantal Piot Ziegler, Juliane Rick, Eddy Roosnek, Anne Rosselet, Silvia Rothlin, Frank Ruschitzka, Urs Schanz, Stefan Schaub, Christian Seiler, Susanne Stampf, Jürg Steiger, Guido Stirnimann, Christian Toso, Dimitri Tsinalis, Jean-Pierre Venetz, Jean Villard, Madeleine Wick, Markus Wilhelm, Patrick Yerly.

The authors have no conflicts of interest to declare.

REFERENCES
  1. Hofbauer GF, Bouwes Bavinck JN, Euvrard S. Organ transplantation and skin cancer: basic problems and new perspectives. Exp Dermatol 2010; 19: 473–482.
    View article    Google Scholar
  2. Housman TS, Feldman SR, Williford PM, Fleischer AB, Jr, Goldman ND, Acostamadiedo JM, et al. Skin cancer is among the most costly of all cancers to treat for the Medicare population. J Am Acad Dermatol 2003; 48: 425–429.
    View article    Google Scholar
  3. Ackerman AB, Mones JM. Solar (actinic) keratosis is squamous cell carcinoma. Br J Dermatol 2006; 155: 9–22.
    View article    Google Scholar
  4. Glogau RG. The risk of progression to invasive disease. J Am Acad Dermatol 2000; 42: 23–24.
    View article    Google Scholar
  5. Euvrard S, Kanitakis J, Claudy A. Skin cancers after organ transplantation. N Engl J Med 2003; 348: 1681–1691.
    View article    Google Scholar
  6. Burger B, Sporri I, Stegmann DA, De Mesmaker J, Schaub S, Itin PH, et al. Risk of cutaneous squamous cell carcinoma development in renal transplant recipients is independent of TMC/EVER alterations. Dermatology 2015; 231: 245–252.
    View article    Google Scholar
  7. Sanders ML, Karnes JH, Denny JC, Roden DM, Ikizler TA, Birdwell KA. Clinical and genetic factors associated with cutaneous squamous cell carcinoma in kidney and heart transplant recipients. Transplantation Direct 2015 May1(4). doi: 10.1097/TXD.0000000000000521.
    View article    Google Scholar
  8. Wei L, Allain DC, Bernhardt MN, Gillespie JL, Peters SB, Iwenofu OH, et al. Variants at the OCA2/HERC2 locus affect time to first cutaneous squamous cell carcinoma in solid organ transplant recipients collected using two different study designs. Br J Dermatol 2017; 177: 1066–1073.
    View article    Google Scholar
  9. Genomes Project C, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, et al. An integrated map of genetic variation from 1,092 human genomes. Nature 2012; 491: 56–65.
    View article    Google Scholar
  10. Genome of the Netherlands C. Whole-genome sequence variation, population structure and demographic history of the Dutch population. Nat Genet 2014; 46: 818–825.
    View article    Google Scholar
  11. Delaneau O, Zagury JF, Marchini J. Improved whole-chromosome phasing for disease and population genetic studies. Nat Methods 2013; 10: 5–6.
    View article    Google Scholar
  12. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 2009; 5: e1000529.
    View article    Google Scholar
  13. Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 2012; 6: 80–92.
    View article    Google Scholar
  14. Fadista J, Oskolkov N, Hansson O, Groop L. LoFtool: a gene intolerance score based on loss-of-function variants in 60 706 individuals. Bioinformatics 2017; 33: 471–474.
    View article    Google Scholar