The cDNA-mediated Annealing, extension, Selection and Ligation (DASL) assay has become a suitable gene expression profiling system for degraded RNA from paraffin-embedded tissue. We examined assay characteristics and the performance of the DASL 502-gene Cancer Panel v1 (1.5K) and 24,526-gene panel (24K) platforms at differentiating nine human epidermal growth factor receptor 2- positive (HER2+) and 11 HER2-negative (HER2-) paraffin-embedded breast tumors.

MicroRNAs (miRNAs) are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available.

Genome-wide association studies (GWASs) assess correlation between traits and DNA sequence variation using large numbers of genetic variants such as single nucleotide polymorphisms (SNPs) distributed across the genome. A GWAS produces many trait-SNP associations with low p-values, but few are replicated in subsequent studies. We sought to determine if characteristics of the genomic loci associated with a trait could be used to identify initial associations with a higher chance of replication in a second cohort. Data from the age-related eye disease study (AREDS) of 100,000 SNPs on 395 subjects with and 198 without age-related macular degeneration (AMD) were employed. Loci highly associated with AMD were characterized based on the distribution of genotypes, level of significance, and clustering of adjacent SNPs also associated with AMD suggesting linkage disequilibrium or multiple effects. Forty nine loci were highly associated with AMD, including 3 loci (CFH, C2/BF, LOC387715/HTRA1) already known to contain important genetic risks for AMD. One additional locus (C3) reported during the course of this study was identified and replicated in an additional study group. Tag-SNPs and haplotypes for each locus were evaluated for association with AMD in additional cohorts to account for population differences between discovery and replication subjects, but no additional clearly significant associations were identified. Relying on a significant genotype tests using a log-additive model would have excluded 57% of the non-replicated and none of the replicated loci, while use of other SNP features and clustering might have missed true associations.

Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-control dataset to compare the performance of four of these imputation methods: IMPUTE, MACH, PLINK, and fastPHASE. We compared the methods' imputation error rates and performance of association tests using the imputed data, in the context of imputing completely untyped markers as well as imputing missing genotypes to combine two datasets genotyped at different sets of markers. As expected, all methods performed better for single-nucleotide polymorphisms (SNPs) in high linkage disequilibrium with genotyped SNPs. However, MACH and IMPUTE generated lower imputation error rates than fastPHASE and PLINK. Association tests based on allele "dosage" from MACH and tests based on the posterior probabilities from IMPUTE provided results closest to those based on complete data. However, in both situations, none of the imputation-based tests provide the same level of evidence of association as the complete data at SNPs strongly associated with disease.

Age-related bone loss in humans is associated with a decrease in bone formation relative to bone resorption, although the mechanisms for this impairment in bone formation with aging are not well understood. It is known that the precursors for the bone-forming osteoblasts reside in the mesenchymal cell population in bone marrow. Thus, in an effort to identify relevant genetic pathways that are altered with aging, we examined the gene expression and DNA methylation patterns from a highly enriched bone marrow mesenchymal cell population from young (mean age, 28.7 years) versus old (mean age, 73.3 years) women. Bone marrow mononuclear cells from these women were depleted of hematopoietic lineage (lin) and endothelial cells using a combination of magnetic- and fluorescence-activated cell sorting, yielding a previously characterized mesenchymal cell population (lin-/CD34-/CD31- cells) that is capable of osteoblast differentiation. Whole transcriptome RNA sequencing (RNAseq) of freshly isolated cells (without in vitro culture) identified 279 differentially expressed genes (p < 0.05, false discovery rate [q]< 0.10) between the young and old subjects. Pathway analysis revealed statistically significant (all p < 0.05) alterations in protein synthesis and degradation pathways, as well as mTOR, gap junction, calcium, melatonin and NFAT signaling pathways. Further, Reduced Representational Bisulphite sequencing (RRBS DNA methylation sequencing) revealed significant differences in methylation between the young and old subjects surrounding the promoters of 1528 target genes that also exhibited significant differences in gene expression by RNAseq. In summary, these studies provide novel insights into potential pathways affected by aging in a highly enriched human mesenchymal cell population analyzed without the confounding effects of in vitro culture. Specifically, our finding of alterations in several genes and pathways leading to impaired protein synthesis and turnover with aging in bone marrow mesenchymal cells points to the need for further studies examining how these changes, as well as the other alterations with aging that we identified, may contribute to the age-related impairment in osteoblast formation and/or function.

Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3' UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370.

Paclitaxel is a mainstay of treatment for many solid tumors, and frequently, clinical outcome is influenced by paclitaxel sensitivity. Despite this, our understanding of the molecular basis of paclitaxel response is incomplete. Recently, it has been shown that microRNAs (miRNAs) influence messenger RNA (mRNA) transcriptional control and can contribute to human carcinogenesis. In the present study, our objective was to identify miRNAs associated with cancer cell line response to paclitaxel and to evaluate these miRNAs as therapeutic targets to increase paclitaxel sensitivity. We measured the expression of 335 unique miRNAs in 40 human cancer cell lines selected from the NCI panel. We then integrated miRNA expression data with publicly available paclitaxel-sensitivity (GI₅₀) data for each of the 40 cell lines to identify miRNAs associated with paclitaxel sensitivity. Ovarian cancer cell lines with differential miRNA expression and paclitaxel sensitivity were transiently transfected with miRNA precursors and inhibitors, and the effects on in vitro cell paclitaxel sensitivity were evaluated. Pearson's correlation identified 2 miRNAs (miR-367 and miR-30a-5p) associated with the NCI40 cell line in vitro paclitaxel response (P<0.0003). Ovarian cancer cells were selected based on the association between paclitaxel sensitivity and miR-367/miR-30a-5p expression. Overexpression of miR-367 in the paclitaxel-sensitive cells [PA1; IC₅₀, 1.69 nM, high miR-367 (2.997), low miR-30a-5p (-0.323)] further increased paclitaxel sensitivity, whereas miR-367 depletion decreased paclitaxel sensitivity. In contrast, overexpression and depletion of miR-30a-5p in the paclitaxel-resistant cells [OVCAR4; IC₅₀, 17.8 nM, low miR-367 (-0.640), high miR-30a-5p (3.270)] decreased and increased paclitaxel sensitivity, respectively. We identified and successfully targeted miRNAs associated with human cancer cell line response to paclitaxel. Our strategy of integrating in vitro miRNA expression and drug sensitivity data may not only aid in the characterization of determinants of drug response but also in the identification of novel therapeutic targets to increase activity of existing therapeutics.

Mammalian target of rapamycin (mTOR) represents a key downstream intermediate for a myriad of oncogenic receptor tyrosine kinases. In the case of the insulin-like growth factor (IGF) pathway, the mTOR complex (mTORC1) mediates IGF-1 receptor (IGF-1R)-induced estrogen receptor alpha (ERα) phosphorylation/activation and leads to increased proliferation and growth in breast cancer cells. As a result, the prevalence of mTOR inhibitors combined with hormonal therapy has increased in recent years. Conversely, activated mTORC1 provides negative feedback regulation of IGF signaling via insulin receptor substrate (IRS)-1/2 serine phosphorylation and subsequent proteasomal degradation. Thus, the IGF pathway may provide escape (e.g. de novo or acquired resistance) from mTORC1 inhibitors. It is therefore plausible that combined inhibition of mTORC1 and IGF-1R for select subsets of ER-positive breast cancer patients presents as a viable therapeutic option.

Ovarian cancer represents the most lethal tumor type among malignancies of the female reproductive system. Overall survival rates remain low. In this study, we identify the serine protease inhibitor Kazal type 1 (SPINK1) as a potential therapeutic target for a subset of ovarian cancers. We show that SPINK1 drives ovarian cancer cell proliferation through activation of epidermal growth factor receptor (EGFR) signaling, and that SPINK1 promotes resistance to anoikis through a distinct mechanism involving protease inhibition. In analyses of ovarian tumor specimens from a Mayo Clinic cohort of 490 patients, we further find that SPINK1 immunostaining represents an independent prognostic factor for poor survival, with the strongest association in patients with nonserous histological tumor subtypes (endometrioid, clear cell, and mucinous). This study provides novel insight into the fundamental processes underlying ovarian cancer progression, and also suggests new avenues for development of molecularly targeted therapies.

Disruption in circadian gene expression, whether due to genetic variation or environmental factors (e.g., light at night, shiftwork), is associated with increased incidence of breast, prostate, gastrointestinal and hematologic cancers and gliomas. Circadian genes are highly expressed in the ovaries where they regulate ovulation; circadian disruption is associated with several ovarian cancer risk factors (e.g., endometriosis). However, no studies have examined variation in germline circadian genes as predictors of ovarian cancer risk and invasiveness. The goal of the current study was to examine single nucleotide polymorphisms (SNPs) in circadian genes BMAL1, CRY2, CSNK1E, NPAS2, PER3, REV1 and TIMELESS and downstream transcription factors KLF10 and SENP3 as predictors of risk of epithelial ovarian cancer (EOC) and histopathologic subtypes. The study included a test set of 3,761 EOC cases and 2,722 controls and a validation set of 44,308 samples including 18,174 (10,316 serous) cases and 26,134 controls from 43 studies participating in the Ovarian Cancer Association Consortium (OCAC). Analysis of genotype data from 36 genotyped SNPs and 4600 imputed SNPs indicated that the most significant association was rs117104877 in BMAL1 (OR = 0.79, 95% CI = 0.68-0.90, p = 5.59 × 10-4]. Functional analysis revealed a significant down regulation of BMAL1 expression following cMYC overexpression and increasing transformation in ovarian surface epithelial (OSE) cells as well as alternative splicing of BMAL1 exons in ovarian and granulosa cells. These results suggest that variation in circadian genes, and specifically BMAL1, may be associated with risk of ovarian cancer, likely through disruption of hormonal pathways.

Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression.

Immunosuppression plays a pivotal role in assisting tumors to evade immune destruction and promoting tumor development. We hypothesized that genetic variation in the immunosuppression pathway genes may be implicated in breast cancer tumorigenesis. We included 42,510 female breast cancer cases and 40,577 controls of European ancestry from 37 studies in the Breast Cancer Association Consortium (2015) with available genotype data for 3595 single nucleotide polymorphisms (SNPs) in 133 candidate genes. Associations between genotyped SNPs and overall breast cancer risk, and secondarily according to estrogen receptor (ER) status, were assessed using multiple logistic regression models. Gene-level associations were assessed based on principal component analysis. Gene expression analyses were conducted using RNA sequencing level 3 data from The Cancer Genome Atlas for 989 breast tumor samples and 113 matched normal tissue samples. SNP rs1905339 (A>G) in the STAT3 region was associated with an increased breast cancer risk (per allele odds ratio 1.05, 95 % confidence interval 1.03-1.08; p value = 1.4 × 10(-6)). The association did not differ significantly by ER status. On the gene level, in addition to TGFBR2 and CCND1, IL5 and GM-CSF showed the strongest associations with overall breast cancer risk (p value = 1.0 × 10(-3) and 7.0 × 10(-3), respectively). Furthermore, STAT3 and IL5 but not GM-CSF were differentially expressed between breast tumor tissue and normal tissue (p value = 2.5 × 10(-3), 4.5 × 10(-4) and 0.63, respectively). Our data provide evidence that the immunosuppression pathway genes STAT3, IL5, and GM-CSF may be novel susceptibility loci for breast cancer in women of European ancestry.

Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.

Precise delineation of the specific genes and pathways altered with aging and estrogen (E) therapy may lead to new skeletal biomarkers and the development of novel bone therapeutics. Previous human bone studies, however, have been limited by only examining pre-specified genes and pathways. High-throughput RNA sequencing (RNAseq), on the other hand, offers an unbiased approach to examine the entire transcriptome. Here we present an RNAseq analysis of human bone samples, obtained from iliac crest needle biopsies, to yield the first in vivo interrogation of all genes and pathways that may be altered in bone with aging and E therapy in humans. 58 healthy women were studied, including 19 young women (mean age ± SD, 30.3 ± 5.4 years), 19 old women (73.1 ± 6.6 years), and 20 old women treated with 3 weeks of E therapy (70.5 ± 5.2 years). Using generally accepted criteria (false discovery rate [q] < 0.10), aging altered a total of 678 genes and 12 pathways, including a subset known to regulate bone metabolism (e.g., Notch). Interestingly, the LEF1 transcription factor, which is a classical downstream target of the Wnt/β-catenin signaling pathway, was significantly downregulated in the bones from the old versus young women; consistent with this, LEF1 binding sites were significantly enriched in the promoter regions of the differentially expressed genes in the old versus young women, suggesting that aging was associated with alterations in Wnt signaling in bone. Further, of the 21 unique genes altered in bone by E therapy, the expression of INHBB (encoding for the inhibin, beta B polypeptide), which decreased with aging (by 0.6-fold), was restored to young adult levels in response to E therapy. In conclusion, our data demonstrate that aging alters a substantial portion of the skeletal transcriptome, whereas E therapy appears to have significant, albeit less wide-ranging effects. These data provide a valuable resource for the potential identification of novel biomarkers associated with age-related bone loss and also highlight potential pathways that could be targeted to treat osteoporosis.

We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer.

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P<2 × 10(-3)). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3'-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.

A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding the etiologic heterogeneity of breast cancer may ultimately result in improvements in prevention, early detection, and treatment.

The nuclear factor-kappaB (NF-kappaB) family of transcription factors regulates the expression of a variety of genes involved in apoptosis and immune response. We examined relationships between genotypes at five NF-kappaB subunits (NFKB1, NFKB2, REL, RELA, and RELB) and variable expression levels of 15 NF-kappaB regulated proteins with heritability greater than 0.40: BCL2A1, BIRC2, CD40, CD44, CD80, CFLAR, CR2, FAS, ICAM1, IL15, IRF1, JUNB, MYC, SLC2A5, and VCAM1. SNP genotypes and expression phenotypes from pedigrees of Utah residents with ancestry from northern and western Europe were provided by Genetic Analysis Workshop 15 and supplemented with additional genotype data from the International HapMap Consortium. We conducted association, linkage, and family-based association analyses between each candidate gene and the 15 heritable expression phenotypes. We observed consistent results in association and linkage analyses of the NFKB1 region (encoding p50) and levels of FAS and IRF1 expression. FAS is a cell surface protein that also belongs to the TNF-receptor family; signals through FAS are able to induce apoptosis. IRF1 is a member of the interferon regulatory transcription factor family, which has been shown to regulate apoptosis and tumor-suppression. Analyses in the REL region (encoding c-Rel) revealed linkage and association with CD40 phenotype. CD40 proteins belong to the tumor necrosis factor (TNF)-receptor family, which mediates a broad variety of immune and inflammatory responses. We conclude that variation in the genes encoding p50 and c-Rel may play a role in NF-kappaB-related transcription of FAS, IRF1, and CD40.

Several methods to identify tagging single-nucleotide polymorphisms (SNPs) are in common use for genetic epidemiologic studies; however, there may be loss of information when using only a subset of SNPs. We sought to compare the ability of commonly used pairwise, multimarker, and haplotype-based tagging SNP selection methods to detect known associations with quantitative expression phenotypes. Using data from HapMap release 21 on unrelated Utah residents with ancestors from northern and western Europe (CEPH-Utah, CEU), we selected tagging SNPs in five chromosomal regions using ldSelect, Tagger, and TagSNPs. We found that SNP subsets did not substantially overlap, and that the use of trio data did not greatly impact SNP selection. We then tested associations between HapMap genotypes and expression phenotypes on 28 CEU individuals as part of Genetic Analysis Workshop 15. Relative to the use of all SNPs (n = 210 SNPs across all regions), most subset methods were able to detect single-SNP and haplotype associations. Generally, pairwise selection approaches worked extremely well, relative to use of all SNPs, with marked reductions in the number of SNPs required. Haplotype-based approaches, which had identified smaller SNP subsets, missed associations in some regions. We conclude that the optimal tagging SNP method depends on the true model of the genetic association (i.e., whether a SNP or haplotype is responsible); unfortunately, this is often unknown at the time of SNP selection. Additional evaluations using empirical and simulated data are needed.