TreeAndLeaf: an R/Bioconductor package for graphs and trees with focus on the leaves.

MOTIVATION: Dendrogram is a classical diagram for visualizing binary trees. Although efficient to represent hierarchical relations, it provides limited space for displaying information on the leaf elements, especially for large trees. RESULTS: Here, we present TreeAndLeaf, an R/Bioconductor package that implements a hybrid layout strategy to represent tree diagrams with focus on the leaves. The TreeAndLeaf package combines force-directed graph and tree layout algorithms using a single visualization system, allowing projection of multiple layers of information onto a graph-tree diagram. The Supplementary Information provides two case studies that use breast cancer data from epidemiological and experimental studies. AVAILABILITY AND IMPLEMENTATION: TreeAndLeaf is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/TreeAndLeaf/ (version≥1.4.2). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A prospective study of tea drinking temperature and risk of esophageal squamous cell carcinoma.

Previous studies have reported an association between hot tea drinking and risk of esophageal cancer, but no study has examined this association using prospectively and objectively measured tea drinking temperature. We examined the association of tea drinking temperature, measured both objectively and subjectively at study baseline, with future risk of esophageal squamous cell carcinoma (ESCC) in a prospective study. We measured tea drinking temperature using validated methods and collected data on several other tea drinking habits and potential confounders of interest at baseline in the Golestan Cohort Study, a population-based prospective study of 50,045 individuals aged 40-75 years, established in 2004-2008 in northeastern Iran. Study participants were followed-up for a median duration of 10.1 years (505,865 person-years). During 2004-2017, 317 new cases of ESCC were identified. The objectively measured tea temperature (HR 1.41, 95% CI 1.10-1.81; for ≥60°C vs. <60°C), reported preference for very hot tea drinking (HR 2.41, 95% CI 1.27-4.56; for "very hot" vs. "cold/lukewarm"), and reported shorter time from pouring tea to drinking (HR 1.51, 95% CI 1.01-2.26; for <2 vs. ≥6 min) were all associated with ESCC risk. In analysis of the combined effects of measured temperature and amount, compared to those who drank less than 700 ml of tea/day at <60°C, drinking 700 mL/day or more at a higher-temperature (≥60°C) was consistently associated with an about 90% increase in ESCC risk. Our results substantially strengthen the existing evidence supporting an association between hot beverage drinking and ESCC.

RTNsurvival: an R/Bioconductor package for regulatory network survival analysis.

MOTIVATION: Transcriptional networks are models that allow the biological state of cells or tumours to be described. Such networks consist of connected regulatory units known as regulons, each comprised of a regulator and its targets. Inferring a transcriptional network can be a helpful initial step in characterizing the different phenotypes within a cohort. While the network itself provides no information on molecular differences between samples, the per-sample state of each regulon, i.e. the regulon activity, can be used for describing subtypes in a cohort. Integrating regulon activities with clinical data and outcomes would extend this characterization of differences between subtypes. RESULTS: We describe RTNsurvival, an R/Bioconductor package that calculates regulon activity profiles using transcriptional networks reconstructed by the RTN package, gene expression data, and a two-tailed Gene Set Enrichment Analysis. Given regulon activity profiles across a cohort, RTNsurvival can perform Kaplan-Meier analyses and Cox Proportional Hazards regressions, while also considering confounding variables. The Supplementary Information provides two case studies that use data from breast and liver cancer cohorts and features uni- and multivariate regulon survival analysis. AVAILABILITY AND IMPLEMENTATION: RTNsurvival is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/RTNsurvival/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

RTNduals: an R/Bioconductor package for analysis of co-regulation and inference of dual regulons.

MOTIVATION: Transcription factors (TFs) are key regulators of gene expression, and can activate or repress multiple target genes, forming regulatory units, or regulons. Understanding downstream effects of these regulators includes evaluating how TFs cooperate or compete within regulatory networks. Here we present RTNduals, an R/Bioconductor package that implements a general method for analyzing pairs of regulons. RESULTS: RTNduals identifies a dual regulon when the number of targets shared between a pair of regulators is statistically significant. The package extends the RTN (Reconstruction of Transcriptional Networks) package, and uses RTN transcriptional networks to identify significant co-regulatory associations between regulons. The Supplementary Information reports two case studies for TFs using the METABRIC and TCGA breast cancer cohorts. AVAILABILITY AND IMPLEMENTATION: RTNduals is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/RTNduals/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

Personalized genomic information: preparing for the future of genetic medicine.

The falling cost of sequencing means that we are rapidly approaching an era in which access to personalized genomic information is likely to be widespread. Here, four experts with different insights into the field of genomic medicine answer questions about the prospects for using this type of information. Their responses highlight the diverse range of issues that must be addressed - ranging from scientific to ethical and logistical - to ensure that the potential benefits of personal genomic information outweigh the costs to both individuals and societies.

A common coding variant in CASP8 is associated with breast cancer risk.

The Breast Cancer Association Consortium (BCAC) has been established to conduct combined case-control analyses with augmented statistical power to try to confirm putative genetic associations with breast cancer. We genotyped nine SNPs for which there was some prior evidence of an association with breast cancer: CASP8 D302H (rs1045485), IGFBP3 -202 C --> A (rs2854744), SOD2 V16A (rs1799725), TGFB1 L10P (rs1982073), ATM S49C (rs1800054), ADH1B 3' UTR A --> G (rs1042026), CDKN1A S31R (rs1801270), ICAM5 V301I (rs1056538) and NUMA1 A794G (rs3750913). We included data from 9-15 studies, comprising 11,391-18,290 cases and 14,753-22,670 controls. We found evidence of an association with breast cancer for CASP8 D302H (with odds ratios (OR) of 0.89 (95% confidence interval (c.i.): 0.85-0.94) and 0.74 (95% c.i.: 0.62-0.87) for heterozygotes and rare homozygotes, respectively, compared with common homozygotes; P(trend) = 1.1 x 10(-7)) and weaker evidence for TGFB1 L10P (OR = 1.07 (95% c.i.: 1.02-1.13) and 1.16 (95% c.i.: 1.08-1.25), respectively; P(trend) = 2.8 x 10(-5)). These results demonstrate that common breast cancer susceptibility alleles with small effects on risk can be identified, given sufficiently powerful studies.

A functional variant at a prostate cancer predisposition locus at 8q24 is associated with PVT1 expression.

Genetic mapping studies have identified multiple cancer susceptibility regions at chromosome 8q24, upstream of the MYC oncogene. MYC has been widely presumed as the regulated target gene, but definitive evidence functionally linking these cancer regions with MYC has been difficult to obtain. Here we examined candidate functional variants of a haplotype block at 8q24 encompassing the two independent risk alleles for prostate and breast cancer, rs620861 and rs13281615. We used the mapping of DNase I hypersensitive sites as a tool to prioritise regions for further functional analysis. This approach identified rs378854, which is in complete linkage disequilibrium (LD) with rs620861, as a novel functional prostate cancer-specific genetic variant. We demonstrate that the risk allele (G) of rs378854 reduces binding of the transcription factor YY1 in vitro. This factor is known to repress global transcription in prostate cancer and is a candidate tumour suppressor. Additional experiments showed that the YY1 binding site is occupied in vivo in prostate cancer, but not breast cancer cells, consistent with the observed cancer-specific effects of this single nucleotide polymorphism (SNP). Using chromatin conformation capture (3C) experiments, we found that the region surrounding rs378854 interacts with the MYC and PVT1 promoters. Moreover, expression of the PVT1 oncogene in normal prostate tissue increased with the presence of the risk allele of rs378854, while expression of MYC was not affected. In conclusion, we identified a new functional prostate cancer risk variant at the 8q24 locus, rs378854 allele G, that reduces binding of the YY1 protein and is associated with increased expression of PVT1 located 0.5 Mb downstream.

The histone methyltransferase Wolf-Hirschhorn syndrome candidate 1-like 1 (WHSC1L1) is involved in human carcinogenesis.

Histone lysine methylation plays a fundamental role in chromatin organization. Although a set of histone methyltransferases have been identified and biochemically characterized, the pathological roles of their dysfunction in human cancers are still not well understood. In this study, we demonstrate important roles of WHSC1L1 in human carcinogenesis. Expression levels of WHSC1L1 transcript were significantly elevated in various human cancers including bladder carcinoma. Immunohistochemical analysis of bladder, lung, and liver cancers confirmed overexpression of WHSC1L1. WHSC1L1-specific small interfering RNAs significantly knocked down its expression and resulted in suppression of proliferation of bladder and lung cancer cell lines. WHSC1L1 knockdown induced cell cycle arrest at the G(2)/M phase followed by multinucleation of cancer cells. Expression profile analysis using Affymetrix GeneChip(®) showed that WHSC1L1 affected the expression of a number of genes including CCNG1 and NEK7, which are known to play crucial roles in the cell cycle progression at mitosis. As WHSC1L1 expression is significantly low in various normal tissues including vital organs, WHSC1L1 could be a good candidate molecule for development of novel treatment for various types of cancer.

Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis.

Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease's tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies.

Smoking-associated gene expression alterations in nasal epithelium reveal immune impairment linked to lung cancer risk.

BACKGROUND: Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to modifiable lifestyle risk in the form of tobacco smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, 40% of which occur more than 15 years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk remain unclear. We thus set out to examine whether risk stratification in the clinic and in the general population can be improved upon by the addition of genetic data and to explore the mechanisms of the persisting risk in former smokers. METHODS: We analysed transcriptomic data from accessible airway tissues of 487 subjects, including healthy volunteers and clinic patients of different smoking statuses. We developed a computational model to assess smoking-associated gene expression changes and their reversibility after smoking is stopped, comparing healthy subjects to clinic patients with and without lung cancer. RESULTS: We find persistent smoking-associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune- and interferon-related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. CONCLUSIONS: Our results provide initial evidence for germline-mediated personalized smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

Allele-specific expression analysis methods for high-density SNP microarray data.

MOTIVATION: In the past decade, a number of technologies to quantify allele-specific expression (ASE) in a genome-wide manner have become available to researchers. We investigate the application of single-nucleotide polymorphism (SNP) microarrays to this task, exploring data obtained from both cell lines and primary tissue for which both RNA and DNA profiles are available. RESULTS: We analyze data from two experiments that make use of high-density Illumina Infinium II genotyping arrays to measure ASE. We first preprocess each data set, which involves removal of outlier samples, careful normalization and a two-step filtering procedure to remove SNPs that show no evidence of expression in the samples being analyzed and calls that are clear genotyping errors. We then compare three different tests for detecting ASE, one of which has been previously published and two novel approaches. These tests vary at the level at which they operate (per SNP per individual or per SNP) and in the input data they require. Using SNPs from imprinted genes as true positives for ASE, we observe varying sensitivity for the different testing procedures that improves with increasing sample size. Methods that rely on RNA signal alone were found to perform best across a range of metrics. The top ranked SNPs recovered by all methods appear to be reasonable candidates for ASE. AVAILABILITY AND IMPLEMENTATION: Analysis was carried out in R (http://www.R-project.org/) using existing functions.

Association studies for finding cancer-susceptibility genetic variants.

Cancer is the result of complex interactions between inherited and environmental factors. Known genes account for a small proportion of the heritability of cancer, and it is likely that many genes with modest effects are yet to be found. Genetic-association studies have been widely used in the search for such genes, but success has been limited so far. Increased knowledge of the function of genes and the architecture of human genetic variation combined with new genotyping technologies herald a new era of gene mapping by association.

The genetics and genomics of cancer.

The past decade has seen great strides in our understanding of the genetic basis of human disease. Arguably, the most profound impact has been in the area of cancer genetics, where the explosion of genomic sequence and molecular profiling data has illustrated the complexity of human malignancies. In a tumor cell, dozens of different genes may be aberrant in structure or copy number, and hundreds or thousands of genes may be differentially expressed. A number of familial cancer genes with high-penetrance mutations have been identified, but the contribution of low-penetrance genetic variants or polymorphisms to the risk of sporadic cancer development remains unclear. Studies of the complex somatic genetic events that take place in the emerging cancer cell may aid the search for the more elusive germline variants that confer increased susceptibility. Insights into the molecular pathogenesis of cancer have provided new strategies for treatment, but a deeper understanding of this disease will require new statistical and computational approaches for analysis of the genetic and signaling networks that orchestrate individual cancer susceptibility and tumor behavior.

Polygenic susceptibility to breast cancer and implications for prevention.

The knowledge of human genetic variation that will come from the human genome sequence makes feasible a polygenic approach to disease prevention, in which it will be possible to identify individuals as susceptible by their genotype profile and to prevent disease by targeting interventions to those at risk. There is doubt, however, regarding the magnitude of these genetic effects and thus the potential to apply them to either individuals or populations. We have therefore examined the potential for prediction of risk based on common genetic variation using data from a population-based series of individuals with breast cancer. The data are compatible with a log-normal distribution of genetic risk in the population that is sufficiently wide to provide useful discrimination of high- and low-risk groups. Assuming all of the susceptibility genes could be identified, the half of the population at highest risk would account for 88% of all affected individuals. By contrast, if currently identified risk factors for breast cancer were used to stratify the population, the half of the population at highest risk would account for only 62% of all cases. These results suggest that the construction and use of genetic-risk profiles may provide significant improvements in the efficacy of population-based programs of intervention for cancers and other diseases.

Identification of Stk6/STK15 as a candidate low-penetrance tumor-susceptibility gene in mouse and human.

Linkage analysis and haplotype mapping in interspecific mouse crosses (Mus musculus x Mus spretus) identified the gene encoding Aurora2 (Stk6 in mouse and STK15 in human) as a candidate skin tumor susceptibility gene. The Stk6 allele inherited from the susceptible M. musculus parent was overexpressed in normal cells and preferentially amplified in tumor cells from F(1) hybrid mice. We identified a common genetic variant in STK15 (resulting in the amino acid substitution F31I) that is preferentially amplified and associated with the degree of aneuploidy in human colon tumors. The Ile31 variant transforms rat1 cells more potently than the more common Phe31 variant. The E2 ubiquitin-conjugating enzyme UBE2N was a preferential binding partner of the 'weak' STK15 Phe31 variant form in yeast two-hybrid screens and in human cells. This interaction results in colocalization of UBE2N with STK15 at the centrosomes during mitosis. These results are consistent with an important role for the Ile31 variant of STK15 in human cancer susceptibility.

Effects of BRCA2 cis-regulation in normal breast and cancer risk amongst BRCA2 mutation carriers.

INTRODUCTION: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism. METHODS: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analyzed in vitro and in vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2,754 carriers. RESULTS: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterized three cis-regulatory SNPs located at the promoter and two intronic regulatory elements which affect the binding of the transcription factors C/EBPα, HMGA1, D-binding protein (DBP) and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele hazard ratio (HR) = 0.85, 95% confidence interval (CI) = 0.72 to 1.00, P-trend = 0.048). CONCLUSIONS: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2 which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele.

The JmjC domain-containing histone demethylase KDM3A is a positive regulator of the G1/S transition in cancer cells via transcriptional regulation of the HOXA1 gene.

A number of histone demethylases have been identified and biochemically characterized, yet their biological functions largely remain uncharacterized, particularly in the context of human diseases such as cancer. In this study, we describe important roles for the histone demethylase KDM3A, also known as JMJD1A, in human carcinogenesis. Expression levels of KDM3A were significantly elevated in human bladder carcinomas compared with nonneoplastic bladder tissues (p < 0.0001), when assessed by real-time PCR. We confirmed that some other cancers including lung cancer also overexpressed KDM3A, using cDNA microarray analysis. Treatment of cancer cell lines with small interfering RNA targeting KDM3A significantly knocked down its expression and resulted in the suppression of proliferation. Importantly, we found that KDM3A activates transcription of the HOXA1 gene through demethylating histone H3 at lysine 9 di-methylation by binding to its promoter region. Indeed, expression levels of KDM3A and HOXA1 in several types of cancer cell lines and bladder cancer samples were statistically correlated. We observed the down-regulation of HOXA1 as well as CCND1 after treatment with KDM3A siRNA, indicating G(1) arrest of cancer cells. Together, our results suggest that elevated expression of KDM3A plays a critical role in the growth of cancer cells, and further studies may reveal a cancer therapeutic potential in KDM3A inhibition.

Common variants associated with breast cancer in genome-wide association studies are modifiers of breast cancer risk in BRCA1 and BRCA2 mutation carriers.

Recent studies have identified single nucleotide polymorphisms (SNPs) that significantly modify breast cancer risk in BRCA1 and BRCA2 mutation carriers. Since these risk modifiers were originally identified as genetic risk factors for breast cancer in genome-wide association studies (GWASs), additional risk modifiers for BRCA1 and BRCA2 may be identified from promising signals discovered in breast cancer GWAS. A total of 350 SNPs identified as candidate breast cancer risk factors (P < 1 x 10(-3)) in two breast cancer GWAS studies were genotyped in 3451 BRCA1 and 2006 BRCA2 mutation carriers from nine centers. Associations with breast cancer risk were assessed using Cox models weighted for penetrance. Eight SNPs in BRCA1 carriers and 12 SNPs in BRCA2 carriers, representing an enrichment over the number expected, were significantly associated with breast cancer risk (P(trend) < 0.01). The minor alleles of rs6138178 in SNRPB and rs6602595 in CAMK1D displayed the strongest associations in BRCA1 carriers (HR = 0.78, 95% CI: 0.69-0.90, P(trend) = 3.6 x 10(-4) and HR = 1.25, 95% CI: 1.10-1.41, P(trend) = 4.2 x 10(-4)), whereas rs9393597 in LOC134997 and rs12652447 in FBXL7 showed the strongest associations in BRCA2 carriers (HR = 1.55, 95% CI: 1.25-1.92, P(trend) = 6 x 10(-5) and HR = 1.37, 95% CI: 1.16-1.62, P(trend) = 1.7 x 10(-4)). The magnitude and direction of the associations were consistent with the original GWAS. In subsequent risk assessment studies, the loci appeared to interact multiplicatively for breast cancer risk in BRCA1 and BRCA2 carriers. Promising candidate SNPs from GWAS were identified as modifiers of breast cancer risk in BRCA1 and BRCA2 carriers. Upon further validation, these SNPs together with other genetic and environmental factors may improve breast cancer risk assessment in these populations.