A genome-wide association study of IgM antibody against phosphorylcholine: shared genetics and phenotypic relationship to chronic lymphocytic leukemia

Phosphorylcholine (PC) is an epitope on oxidized low-density lipoprotein (oxLDL), apoptotic cells and several pathogens like Streptococcus pneumoniae. Immunoglobulin M against PC (IgM anti-PC) has the ability to inhibit uptake of oxLDL by macrophages and increase clearance of apoptotic cells. From our genome-wide association studies (GWASs) in four European-ancestry cohorts, six single nucleotide polymorphisms (SNPs) in 11q24.1 were discovered (in 3002 individuals) and replicated (in 646 individuals) to be associated with serum level of IgM anti-PC (the leading SNP rs35923643-G, combined β = 0.19, 95% confidence interval 0.13-0.24, P = 4.3 × 10-11). The haplotype tagged by rs35923643-G (or its proxy SNP rs735665-A) is also known as the top risk allele for chronic lymphocytic leukemia (CLL), and a main increasing allele for general IgM. By using summary GWAS results of IgM anti-PC and CLL in the polygenic risk score (PRS) analysis, PRS on the basis of IgM anti-PC risk alleles positively associated with CLL risk (explained 0.6% of CLL variance, P = 1.2 × 10-15). Functional prediction suggested that rs35923643-G might impede the binding of Runt-related transcription factor 3, a tumor suppressor playing a central role in the immune regulation of cancers. Contrary to the expectations from the shared genetics between IgM anti-PC and CLL, an inverse relationship at the phenotypic level was found in a nested case-control study (30 CLL cases with 90 age- and sex-matched controls), potentially reflecting reverse causation. The suggested function of the top variant as well as the phenotypic association between IgM anti-PC and CLL risk needs replication and motivates further studies.

Gene regulatory mechanisms underpinning prostate cancer susceptibility

Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.

Genome-wide association study of prostate cancer-specific survival

BACKGROUND

Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical.

METHODS

We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR).

RESULTS

We observed no significant association between genetic variants and prostate cancer survival.

CONCLUSIONS

Common genetic variants with large impact on prostate cancer survival were not observed in this study.

IMPACT

Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND

Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction.

METHODS

We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls.

RESULTS

The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk.

CONCLUSIONS

Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.

Abstract 842: Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor

Genome-wide association (GWA) studies have reported 19 distinct susceptibility loci for testicular germ cell tumor (TGCT). The aim of the present study was to identify additional loci and gene sets associated with susceptibility to TGCT. A GWA study for TGCT was performed by genotyping 610,240 single nucleotide polymorphisms (SNPs) in 1,326 cases and 6,687 controls from Sweden and Norway. We put forward 34 SNPs from 17 novel regions and 11 SNPs previously reported, for replication in 710 case-parent triads and 289 cases and 290 controls. Predefined biological pathways and processes, in addition to a custom-built sex determination gene set, were subject to enrichment analyses using Meta-Analysis Gene Set Enrichment of Variant Associations (M) and Improved Gene Set Enrichment Analysis for Genome-wide Association Study (I). In the combined meta-analysis, we observed genome-wide significant association for rs7501939 on chromosome 17q12 (OR = 1.29, 95% CI = 1.19-1.40, P = 1.1 × 10-9) and rs2195987 on chromosome 19p12 (OR = 1.31, 95% CI: 1.19-1.45, P = 3.2 × 10-8). The marker rs7501939 on chromosome 17q12 is located in an intron of the HNF1B gene, encoding a member of the homeodomain-containing superfamily of transcription factors. The sex determination gene set (FDRM < 0.001, FDRI < 0.001) and pathways related to NF-κB, glycerophospholipid and ether lipid metabolism, as well as cancer and apoptosis, was associated with TGCT (FDR < 0.1). In addition to revealing two new TGCT susceptibility loci, our results support the notion that genes governing normal germ cell development in utero are implicated in the development of TGCT.

Citation Format: Tom Grotmol, Wenche Kristiansen, Robert Karlsson, Trine B. Rounge, Thomas Whitington, Bettina K. Andreassen, Patrik KE Magnusson, Hans-Olov Adami, Clare Turnbull, Trine B. Haugen, Fredrik Wiklund. Two new loci and gene sets related to sex determination and cancer progression are associated with susceptibility to testicular germ cell tumor. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 842. doi:10.1158/1538-7445.AM2015-842

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites

During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M phase. These results suggest that cohesin-binding functions as a cellular memory that promotes re-establishment of TF clusters after DNA replication and chromatin condensation.

Lessons from functional analysis of genome-wide association studies

Most cancer-associated single-nucleotide polymorphisms (SNP) identified using genome-wide association studies are located outside of protein-coding regions, and their significance and mode of action have been a source of continuing debate. One proposed mechanism of action of the SNPs is that they would affect the activity of enhancer elements regulating critical target genes. In this review, we summarize recent results that substantiate this model. These studies have identified a cancer-specific enhancer element at the 8q24 gene desert that controls the expression of the MYC oncogene. We further discuss implications of the observed difference between normal growth control and cancer for drug development, and the inherent features of genome-wide association studies that may specifically lead to identification of disease-specific regulatory elements.

DNA-binding specificities of human transcription factors

Although the proteins that read the gene regulatory code, transcription factors (TFs), have been largely identified, it is not well known which sequences TFs can recognize. We have analyzed the sequence-specific binding of human TFs using high-throughput SELEX and ChIP sequencing. A total of 830 binding profiles were obtained, describing 239 distinctly different binding specificities. The models represent the majority of human TFs, approximately doubling the coverage compared to existing systematic studies. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

Beyond the balance of activator and repressor

Cell differentiation during development is controlled by extracellular morphogens, which induce responding cells to differentiate into distinct cell fates based on the dose of morphogen they receive. Genes that specify the distinct cell fates are differentially responsive to morphogens, and the extracellular morphogen gradient is converted in responding cells to graded activity of transcription factors. In the case of Hedgehog, the gradient is converted to opposing gradients of transcriptional activator and repressor forms of the transcription factor Cubitus interruptus (Ci). It has been generally assumed that the balance between activator and repressor determines target gene responses within this gradient. However, new evidence shows that enhancers can respond selectively to the activator and repressor forms of Ci, and that this selectivity is determined by the affinity of Ci sites within the enhancers.