Assessment of <i>SLX4</i> Mutations in Hereditary Breast Cancers

<div><p>Background</p><p><i>SLX4</i> encodes a DNA repair protein that regulates three structure-specific endonucleases and is necessary for resistance to DNA crosslinking agents, topoisomerase I and poly (ADP-ribose) polymerase (PARP) inhibitors. Recent studies have reported mutations in <i>SLX4</i> in a new subtype of Fanconi anemia (FA), FA-P. Monoallelic defects in several FA genes are known to confer susceptibility to breast and ovarian cancers.</p><p>Methods and Results</p><p>To determine if <i>SLX4</i> is involved in breast cancer susceptibility, we sequenced the entire <i>SLX4</i> coding region in 738 (270 Jewish and 468 non-Jewish) breast cancer patients with 2 or more family members affected by breast cancer and no known <i>BRCA1</i> or <i>BRCA2</i> mutations. We found a novel nonsense (c.2469G>A, p.W823*) mutation in one patient. In addition, we also found 51 missense variants [13 novel, 23 rare (MAF<0.1%), and 15 common (MAF>1%)], of which 22 (5 novel and 17 rare) were predicted to be damaging by Polyphen2 (score = 0.65–1). We performed functional complementation studies using p.W823* and 5 <i>SLX4</i> variants (4 novel and 1 rare) cDNAs in a human <i>SLX4</i>-null fibroblast cell line, RA3331. While wild type <i>SLX4</i> and all the other variants fully rescued the sensitivity to mitomycin C (MMC), campthothecin (CPT), and PARP inhibitor (Olaparib) the p.W823* <i>SLX4</i> mutant failed to do so.</p><p>Conclusion</p><p>Loss-of-function mutations in <i>SLX4</i> may contribute to the development of breast cancer in very rare cases.</p></div

Identification of the nonsense<i>SLX4</i> variant and evaluation of pathogenicity of the <i>SLX4</i> variants by complementation assay.

<p>(A) Sanger sequence traces for DNA extracted from whole blood and breast tumor of the patient with the c.2469G>A (p.W823*) <i>SLX4</i> mutation (NCBI Refseq NM_032444.2). (B) Anti-HA immunoblot showing expression of HA-tagged SLX4 variants in RA3331/E6E7/hTERT cells. Alpha-tubulin serves as loading control. (C)∼(E) Cell survival assays of the RA3331/E6E7/hTERT cell lines expressing indicated SLX4 variants in response to MMC (C), CPT (D) and the PARP inhibitor, Olaparib (E). RA3331/E6E7/hTERT fibroblast cell lines expressing empty vector, wild type SLX4 and indicated SLX4 variants were treated in triplicate with increasing concentrations of MMC (0–100 nM), CPT (0–16 nM) and Olaparib (0–50 µM). After 8 days in culture, the cell number was determined using a Coulter counter. The number of cells at each drug concentration was divided by the number of cells in the untreated sample to calculate the percentage of cell survival. The error bars indicate standard deviations based on three replicates.</p

Susceptibility Loci Associated with Specific and Shared Subtypes of Lymphoid Malignancies

<div><p>The genetics of lymphoma susceptibility reflect the marked heterogeneity of diseases that comprise this broad phenotype. However, multiple subtypes of lymphoma are observed in some families, suggesting shared pathways of genetic predisposition to these pathologically distinct entities. Using a two-stage GWAS, we tested 530,583 SNPs in 944 cases of lymphoma, including 282 familial cases, and 4,044 public shared controls, followed by genotyping of 50 SNPs in 1,245 cases and 2,596 controls. A novel region on 11q12.1 showed association with combined lymphoma (LYM) subtypes. SNPs in this region included rs12289961 near <em>LPXN</em>, (P_LYM = 3.89×10⁻⁸, OR = 1.29) and rs948562 (P_LYM = 5.85×10⁻⁷, OR = 1.29). A SNP in a novel non-HLA region on 6p23 (rs707824, P_NHL = 5.72×10⁻⁷) was suggestive of an association conferring susceptibility to lymphoma. Four SNPs, all in a previously reported HLA region, 6p21.32, showed genome-wide significant associations with follicular lymphoma. The most significant association with follicular lymphoma was for rs4530903 (P_FL = 2.69×10⁻¹², OR = 1.93). Three novel SNPs near the HLA locus, rs9268853, rs2647046, and rs2621416, demonstrated additional variation contributing toward genetic susceptibility to FL associated with this region. Genes implicated by GWAS were also found to be cis-eQTLs in lymphoblastoid cell lines; candidate genes in these regions have been implicated in hematopoiesis and immune function. These results, showing novel susceptibility regions and allelic heterogeneity, point to the existence of pathways of susceptibility to both shared as well as specific subtypes of lymphoid malignancy.</p> </div

Quantile–quantile plots.

<p>Quantile–quantile (QQ) plots for (A) LYM, (B) NHL, (C) FL, (D) DLBCL. The X-axis represents expected −log₁₀(P) and the Y-axis represents −log₁₀(P) from logistic regression. Genomic inflation factor λ for LYM, NHL, FL and DLBCL was 1.09, 1.07, 1.04 and 1.04 respectively.</p

Summary statistics for the analyses in all three stages.

<p>Association with all lymphoma subtypes (LYM), all non-Hodgkin's lymphomas (NHL), and subtypes of follicular lymphoma (FL) and diffuse large B cell lymphoma (DLBCL) and all non-follicular or non-diffuse subtypes (NFD), RA = Risk allele.</p

Heterogeneity test.

<p>(P) BD is the asymptotic p-value of Breslow-Day statistic for the heterogeneity test.</p

p-values of association (−log10 scale) with breast cancer risk in <i>BRCA2</i> carriers for genotyped and imputed SNPs in the <i>NEIL2</i> gene.

<p>SNP rs1466785 is indicated with a purple arrow and the best causal imputed SNPs, rs804276 and rs804271 are indicated with a red arrow. Colors represent the pariwise r². Plot generated with LocusZoom <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004256#pgen.1004256-Pruim1" target="_blank">[42]</a> (<a href="http://csg.sph.umich.edu/locuszoom/" target="_blank">http://csg.sph.umich.edu/locuszoom/</a>).</p

Associations with breast and ovarian cancer risk for SNPs observed at p-trend<0.05 in stage II of the experiment.

a<p>Hazard Ratio per allele (1 df) estimated from the retrospective likelihood analysis.</p>b<p>Hazard Ratio under the genotype specific models (2df) estimated from the retrospective likelihood analysis.</p>c<p>p-values were based on the score test.</p>d<p>HR per allele of 1.69 and p-trend of 1×10⁻⁴ for <i>BRCA2</i> mutation carriers in stage I of the study.</p>e<p>HR per allele of 1.43 and p-trend of 0.01 for <i>BRCA1</i> mutation carriers in stage I of the study.</p>f<p>HR per allele of 1.30 and p-trend of 0.03 for <i>BRCA1</i> mutation carriers in stage I of the study.</p>g<p>HR per allele of 0.64 and p-trend of 0.057 for <i>BRCA2</i> mutation carriers in stage I of the study.</p>h<p>HR per allele of 1.25 and p-trend of 0.04 for <i>BRCA1</i> mutation carriers in stage I of the study.</p>i<p>HR per allele of 1.25 and p-trend of 0.058 for <i>BRCA2</i> mutation carriers in stage I of the study.</p>j<p>rs3093926 did not yield results under the genotype specific model due to the low minor allele frequency.</p><p>Complete description of results from stage I are included in Supplementary <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004256#pgen.1004256.s002" target="_blank">Table S1</a>.</p><p>Highlighted in bold are those SNPs showing strongest associations with breast or ovarian cancer risk (p<0.01).</p