Deconvoluting complex tissues for expression quantitative trait locus-based analyses

Functional annotation of breast cancer risk loci: current progress and future directions

Genome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal "at risk" breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman's risk of breast cancer.

Overview of human 20 alpha-hydroxysteroid dehydrogenase (AKR1C1): Functions, regulation, and structural insights of inhibitors

Human aldo-keto reductase family 1C1 (AKR1C1) is an important enzyme involved in human hormone metabolism, which is mainly responsible for the metabolism of progesterone in the human body. AKR1C1 is highly expressed and has an important relationship with the occurrence and development of various diseases, especially some cancers related to hormone metabolism. Nowadays, many inhibitors against AKR1C1 have been discovered, including some synthetic compounds and natural products, which have certain inhibitory activity against AKR1C1 at the target level. Here we briefly reviewed the physiological and pathological functions of AKR1C1 and the relationship with the disease, and then summarized the development of AKR1C1 inhibitors, elucidated the interaction between inhibitors and AKR1C1 through molecular docking results and existing co-crystal structures. Finally, we discussed the design ideals of selective AKR1C1 inhibitors from the perspective of AKR1C1 structure, discussed the prospects of AKR1C1 in the treatment of human diseases in terms of biomarkers, pre-receptor regulation and single nucleotide polymorphisms, aiming to provide new ideas for drug research targeting AKR1C1.

Expression Quantitative Trait loci (QTL) in tumor adjacent normal breast tissue and breast tumor tissue

We investigate 71 single nucleotide polymorphisms (SNPs) identified in meta-analytic studies of genome-wide association studies (GWAS) of breast cancer, the majority of which are located in intergenic or intronic regions. To explore regulatory impacts of these variants we conducted expression quantitative loci (eQTL) analyses on tissue samples from 376 invasive postmenopausal breast cancer cases in the Nurses' Health Study (NHS) diagnosed from 1990-2004. Expression analysis was conducted on all formalin-fixed paraffin-embedded (FFPE) tissue samples (and on 264 adjacent normal samples) using the Affymetrix Human Transcriptome Array. Significance and ranking of associations between tumor receptor status and expression variation was preserved between NHS FFPE and TCGA fresh-frozen sample sets (Spearman r = 0.85, p<10^-10 for 17 of the 21 Oncotype DX recurrence signature genes). At an FDR threshold of 10%, we identified 27 trans-eQTLs associated with expression variation in 217 distinct genes. SNP-gene associations can be explored using an open-source interactive browser distributed in a Bioconductor package. Using a new a procedure for testing hypotheses relating SNP content to expression patterns in gene sets, defined as molecular function pathways, we find that loci on 6q14 and 6q25 affect various gene sets and molecular pathways (FDR < 10%). Although the ultimate biological interpretation of the GWAS-identified variants remains to be uncovered, this study validates the utility of expression analysis of this FFPE expression set for more detailed integrative analyses.

FGFR2 risk SNPs confer breast cancer risk by augmenting oestrogen responsiveness

The fibroblast growth factor receptor 2 (FGFR2) locus is consistently the top hit in genome-wide association studies for oestrogen receptor-positive (ER(+)) breast cancer. Yet, its mode of action continues to be controversial. Here, we employ a systems biology approach to demonstrate that signalling via FGFR2 counteracts cell activation by oestrogen. In the presence of oestrogen, the oestrogen receptor (ESR1) regulon (set of ESR1 target genes) is in an active state. However, signalling by FGFR2 is able to reverse the activity of the ESR1 regulon. This effect is seen in multiple distinct FGFR2 signalling model systems, across multiple cells lines and is dependent on the presence of FGFR2. Increased oestrogen exposure has long been associated with an increased risk of breast cancer. We therefore hypothesized that risk variants should reduce FGFR2 expression and subsequent signalling. Indeed, transient transfection experiments assaying the three independent variants of the FGFR2 risk locus (rs2981578, rs35054928 and rs45631563) in their normal chromosomal context show that these single-nucleotide polymorphisms (SNPs) map to transcriptional silencer elements and that, compared with wild type, the risk alleles augment silencer activity. The presence of risk variants results in lower FGFR2 expression and increased oestrogen responsiveness. We thus propose a molecular mechanism by which FGFR2 can confer increased breast cancer risk that is consistent with oestrogen exposure as a major driver of breast cancer risk. Our findings may have implications for the clinical use of FGFR2 inhibitors.

An assessment of computational methods for estimating purity and clonality using genomic data derived from heterogeneous tumor tissue samples

Solid tumor samples typically contain multiple distinct clonal populations of cancer cells, and also stromal and immune cell contamination. A majority of the cancer genomics and transcriptomics studies do not explicitly consider genetic heterogeneity and impurity, and draw inferences based on mixed populations of cells. Deconvolution of genomic data from heterogeneous samples provides a powerful tool to address this limitation. We discuss several computational tools, which enable deconvolution of genomic and transcriptomic data from heterogeneous samples. We also performed a systematic comparative assessment of these tools. If properly used, these tools have potentials to complement single-cell genomics and immunoFISH analyses, and provide novel insights into tumor heterogeneity.

Single nucleotide polymorphisms of caudal type homeobox 1 and 2 are associated with Barrett's esophagus

BACKGROUND

Barrett's esophagus (BE), the premalignant lesion of esophageal adenocarcinoma, is believed to develop as a result of chronic gastroesophageal reflux disease (GERD). Approximately 10 % of subjects with GERD progress to BE. Genetic, epigenetic and other risk factors may contribute to this inter-individual variability. Caudal type homeobox 1 (Cdx1) and Caudal type homeobox 2 (Cdx2) play important regulatory roles in the development of human BE.

AIMS

To determine associations between Cdx1 and Cdx2 single nucleotide polymorphisms (SNPs) and BE.

METHODS

Genomic DNA was extracted from blood samples collected from BE (n = 109) and GERD (n = 223) patients for genotyping of 5 SNPs each of Cdx1 and Cdx2 using TaqMan allelic discrimination assays. Odds ratios and 95 % confidence intervals of SNPs and haplotypes were calculated with a logistic regression model adjusted for factors including age, sex and hiatal hernia. Interactions between genetic variants and these three risk factors were also analyzed.

RESULTS

Older age (≥50 years), male sex and hiatal hernia were significantly associated with BE (P < 0.001). Five variants of Cdx1 SNPs (rs3776082, rs717746 and rs3776083), one Cdx1 haplotype, and three variants of Cdx2 SNPs (rs4769585 and rs3812863) were associated with BE (P < 0.05). Statistically significant interactions were detected between most of these SNPs and the three risk factors (P < 0.05).

CONCLUSION

Certain SNPs of Cdx1 and Cdx2 and their interactions with other risk factors are associated with BE, and may contribute to human susceptibility to BE.