Trisomy 8 Defines a Distinct Subtype of Myeloproliferative Neoplasms Driven by the MYC-Alarmin Axis.

Despite advances in understanding the genetic abnormalities in myeloproliferative neoplasms (MPNs) and the development of JAK2 inhibitors, there is an urgent need to devise new treatment strategies, particularly for triple negative myelofibrosis (MF) patients who lack mutations in the JAK2 kinase pathway and have very poor clinical outcomes. Here we report that MYC copy number gain and increased MYC expression frequently occur in triple negative MF, and that MYC-directed activation of S100A9, an alarmin protein that plays pivotal roles in inflammation and innate immunity, is necessary and sufficient to drive development and progression of MF. Notably, the MYC-S100A9 circuit provokes a complex network of inflammatory signaling that involves numerous hematopoietic cell types in the bone marrow microenvironment. Accordingly, genetic ablation of S100A9 or treatment with small molecules targeting the MYC-S100A9 pathway effectively ameliorates MF phenotypes, highlighting the MYC-alarmin axis as a novel therapeutic vulnerability for this subgroup of MPNs.

Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy.

Osteosarcoma is the most common bone sarcoma in children and young adults. While universally delivered, chemotherapy only benefits roughly half of patients with localized disease. Increasingly, intratumoral heterogeneity is recognized as a source of therapeutic resistance. In this study, we develop and evaluate an in vitro model of osteosarcoma heterogeneity based on phenotype and genotype. Cancer cell populations vary in their environment-specific growth rates and in their sensitivity to chemotherapy. We present the genotypic and phenotypic characterization of an osteosarcoma cell line panel with a focus on co-cultures of the most phenotypically divergent cell lines, 143B and SAOS2. Modest environmental (pH, glutamine) or chemical perturbations dramatically shift the success and composition of cell lines. We demonstrate that in nutrient rich culture conditions 143B outcompetes SAOS2. But, under nutrient deprivation or conventional chemotherapy, SAOS2 growth can be favored in spheroids. Importantly, when the simplest heterogeneity state is evaluated, a two-cell line coculture, perturbations that affect the faster growing cell line have only a modest effect on final spheroid size. Thus the only evaluated therapies to eliminate the spheroids were by switching therapies from a first strike to a second strike. This extensively characterized, widely available system, can be modeled and scaled to allow for improved strategies to anticipate resistance in osteosarcoma due to heterogeneity.

Correlating Immune Cell Infiltration Patterns with Recurrent Somatic Mutations in Advanced Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) tumors have low frequencies of genetic alterations compared with other malignancies, but very high levels of immune cell infiltration and favorable response rates to immunotherapy. Currently, the interplay between specific ccRCC somatic mutations and immune infiltration pattern is unclear. OBJECTIVE: To analyze the associations between common ccRCC somatic mutations and immune cell infiltration patterns within the tumor immune microenvironment (TIME). DESIGN, SETTING, AND PARTICIPANTS: The study included tumor samples (24 primary and 24 metastatic) from 48 patients with stage IV ccRCC. Targeted sequencing was performed for well-characterized recurrent somatic mutations in ccRCC, with the analysis focusing on the six most common ones: VHL, BAP1, PBRM1, SETD2, TP53, and KDM5C. For each sample, multiplex immunofluorescence (IF) was performed in lymphoid and myeloid panels, for seven regions of interest in three zones (tumor core, stroma, and tumor-stroma interface). IF-derived cellular densities were compared across patients, stratified by their somatic mutation status, using a linear mixed-model analysis. External validation was pursued using RNA-seq enrichment scoring from three large external data sources. RESULTS AND LIMITATIONS: Tumors with SETD2 mutations demonstrated significantly decreased levels of FOXP3+ T cells in the tumor core, stroma, and tumor-stroma interface. PBRM1 mutations were associated with decreased FOXP3+ T cells in the tumor core. Primary KDM5C mutations were associated with significantly increased CD206+ macrophage tumor infiltration in the tumor core. A computational method estimating immune cell types in the TIME using bulk RNA-seq data, xCell scoring, failed to validate associations from the IF analysis in large external data sets. A major limitation of the study is the relatively small patient population studied. CONCLUSIONS: This study provides evidence that common somatic mutations in ccRCC, such as SETD2, PBRM1, and KDM5C, are associated with distinct immune infiltration patterns within the TIME. PATIENT SUMMARY: In this study, we analyzed tumor samples from patients with metastatic kidney cancer to determine whether common genetic mutations that arise from the cancer cells are associated with the density of immune cells found within those tumors. We found several distinct immune cell patterns that were associated with specific genetic mutations. These findings provide insight into the interaction between cancer genetics and the immune system in kidney cancer.

TFEB links MYC signaling to epigenetic control of myeloid differentiation and acute myeloid leukemia.

MYC oncoproteins regulate transcription of genes directing cell proliferation, metabolism and tumorigenesis. A variety of alterations drive MYC expression in acute myeloid leukemia (AML) and enforced MYC expression in hematopoietic progenitors is sufficient to induce AML. Here we report that AML and myeloid progenitor cell growth and survival rely on MYC-directed suppression of Transcription Factor EB (TFEB), a master regulator of the autophagy-lysosome pathway. Notably, although originally identified as an oncogene, TFEB functions as a tumor suppressor in AML, where it provokes AML cell differentiation and death. These responses reflect TFEB control of myeloid epigenetic programs, by inducing expression of isocitrate dehydrogenase-1 (IDH1) and IDH2, resulting in global hydroxylation of 5-methycytosine. Finally, activating the TFEB-IDH1/IDH2-TET2 axis is revealed as a targetable vulnerability in AML. Thus, epigenetic control by a MYC-TFEB circuit dictates myeloid cell fate and is essential for maintenance of AML.

KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP-SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10-9) and 3145 (P < 1 × 10-5) SNP-SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene-gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP-SNP interactions were supported by gene expression and protein-protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.

Alcohol Intake and Alcohol-SNP Interactions Associated with Prostate Cancer Aggressiveness.

Excessive alcohol intake is a well-known modifiable risk factor for many cancers. It is still unclear whether genetic variants or single nucleotide polymorphisms (SNPs) can modify alcohol intake's impact on prostate cancer (PCa) aggressiveness. The objective is to test the alcohol-SNP interactions of the 7501 SNPs in the four pathways (angiogenesis, mitochondria, miRNA, and androgen metabolism-related pathways) associated with PCa aggressiveness. We evaluated the impacts of three excessive alcohol intake behaviors in 3306 PCa patients with European ancestry from the PCa Consortium. We tested the alcohol-SNP interactions using logistic models with the discovery-validation study design. All three excessive alcohol intake behaviors were not significantly associated with PCa aggressiveness. However, the interactions of excessive alcohol intake and three SNPs (rs13107662 [CAMK2D, p = 6.2 × 10-6], rs9907521 [PRKCA, p = 7.1 × 10-5], and rs11925452 [ROBO1, p = 8.2 × 10-4]) were significantly associated with PCa aggressiveness. These alcohol-SNP interactions revealed contrasting effects of excessive alcohol intake on PCa aggressiveness according to the genotypes in the identified SNPs. We identified PCa patients with the rs13107662 (CAMK2D) AA genotype, the rs11925452 (ROBO1) AA genotype, and the rs9907521 (PRKCA) AG genotype were more vulnerable to excessive alcohol intake for developing aggressive PCa. Our findings support that the impact of excessive alcohol intake on PCa aggressiveness was varied by the selected genetic profiles.

Noninvasive Assessment of Epidermal Genomic Markers of UV Exposure in Skin.

The measurement of UV-induced DNA damage as a dosimeter of exposure and predictor of skin cancer risk has been proposed by multiple groups. Although UV-induced mutations and adducts are present in normal-appearing UV-exposed epidermis, sampling normal nonlesional skin requires noninvasive methods to extract epidermal DNA for analysis. Here, we demonstrate the feasibility of such an approach, termed surfactant-based tissue acquisition for molecular profiling. Sampling in patients was performed using a felt-tip pen soaked in a mixture of surfactants (Brij-30/N-decyl-N,N-dimethyl-3-ammonio-1-propanesulfonate). In mice, we show that the epidermis can be selectively removed without scarring, with complete healing within 2 weeks. We exposed hairless mice to low-dose UV radiation over a period of 3 months and serially sampled them through up to 2 months following the cessation of UV exposure, observing a progressive increase in a UV signature mutational burden. To test whether surfactant-based tissue acquisition for molecular profiling could be applied to human patients, samples were collected from sun-exposed and sun-protected areas, which were then subjected to high-depth targeted exome sequencing. Extensive UV-driven mosaicism and substantially increased mutational loads in sun-exposed versus sun-protected areas were observed, suggesting that genomic measures, as an integrated readout of DNA damage, repair, and clonal expansion, may be informative markers of UV exposure.

Managing a Large-Scale Multiomics Project: A Team Science Case Study in Proteogenomics.

Highly collaborative scientists are often called on to extend their expertise to different types of projects and to expand the scope and scale of projects well beyond their previous experience. For a large-scale project involving "big data" to be successful, several different aspects of the research plan need to be developed and tested, which include but are not limited to the experimental design, sample collection, sample preparation, metadata recording, technical capability, data acquisition, approaches for data analysis, methods for integration of different data types, recruitment of additional expertise as needed to guide the project, and strategies for clear communication throughout the project. To capture this process, we describe an example project in proteogenomics that built on our collective expertise and experience. Key steps included definition of hypotheses, identification of an appropriate clinical cohort, pilot projects to assess feasibility, refinement of experimental designs, and extensive discussions involving the research team throughout the process. The goal of this chapter is to provide the reader with a set of guidelines to support development of other large-scale multiomics projects.

The genomic landscape of undifferentiated embryonal sarcoma of the liver is typified by C19MC structural rearrangement and overexpression combined with TP53 mutation or loss.

Undifferentiated embryonal sarcoma of the liver (UESL) is a rare and aggressive malignancy. Though the molecular underpinnings of this cancer have been largely unexplored, recurrent chromosomal breakpoints affecting a noncoding region on chr19q13, which includes the chromosome 19 microRNA cluster (C19MC), have been reported in several cases. We performed comprehensive molecular profiling on samples from 14 patients diagnosed with UESL. Congruent with prior reports, we identified structural variants in chr19q13 in 10 of 13 evaluable tumors. From whole transcriptome sequencing, we observed striking expressional activity of the entire C19MC region. Concordantly, in 7 of 7 samples undergoing miRNAseq, we observed hyperexpression of the miRNAs within this cluster to levels >100 fold compared to matched normal tissue or a non-C19MC amplified cancer cell line. Concurrent TP53 mutation or copy number loss was identified in all evaluable tumors with evidence of C19MC overexpression. We find that C19MC miRNAs exhibit significant negative correlation to TP53 regulatory miRNAs and K-Ras regulatory miRNAs. Using RNA-seq we identified that pathways relevant to cellular differentiation as well as mRNA translation machinery are transcriptionally enriched in UESL. In summary, utilizing a combination of next-generation sequencing and high-density arrays we identify the combination of C19MC hyperexpression via chromosomal structural event with TP53 mutation or loss as highly recurrent genomic features of UESL.

Non-del(5q) myelodysplastic syndromes-associated loci detected by SNP-array genome-wide association meta-analysis.

Myelodysplastic syndromes (MDS) are hematopoietic stem cell malignancies. Known predisposing factors to adult MDS include rare germline mutations, cytotoxic therapy, age-related clonal hematopoiesis, and autoimmune or chronic inflammatory disorders. To date, no published studies characterizing MDS-associated germline susceptibility polymorphisms exist. We performed a genome-wide association study of 2 sample sets (555 MDS cases vs 2964 control subjects; 352 MDS cases vs 2640 control subjects) in non-del(5q) MDS cases of European genomic ancestry. Meta-analysis identified 8 MDS-associated loci at 1q31.1 (PLA2G4A), 3p14.1 (FAM19A4), 5q21.3 (EFNA5), 6p21.33, 10q23.1 (GRID1), 12q24.32, 15q26.1, and 20q13.12 (EYA2) that approached genome-wide significance. Gene expression for 5 loci that mapped within or near genes was significantly upregulated in MDS bone marrow cells compared with those of control subjects (P < .01). Higher PLA2G4A expression and lower EYA2 expression were associated with poorer overall survival (P = .039 and P = .037, respectively). Higher PLA2G4A expression is associated with mutations in NRAS (P < .001), RUNX1 (P = .012), ASXL1 (P = .007), and EZH2 (P = .038), all of which are known to contribute to MDS development. EYA2 expression was an independently favorable risk factor irrespective of age, sex, and Revised International Scoring System score (relative risk, 0.67; P = .048). Notably, these genes have regulatory roles in innate immunity, a critical driver of MDS pathogenesis. EYA2 overexpression induced innate immune activation, whereas EYA2 inhibition restored colony-forming potential in primary MDS cells indicative of hematopoietic restoration and possible clinical relevance. In conclusion, among 8 suggestive MDS-associated loci, 5 map to genes upregulated in MDS with functional roles in innate immunity and potential biological relevance to MDS.

Proteogenomic landscape of squamous cell lung cancer.

How genomic and transcriptomic alterations affect the functional proteome in lung cancer is not fully understood. Here, we integrate DNA copy number, somatic mutations, RNA-sequencing, and expression proteomics in a cohort of 108 squamous cell lung cancer (SCC) patients. We identify three proteomic subtypes, two of which (Inflamed, Redox) comprise 87% of tumors. The Inflamed subtype is enriched with neutrophils, B-cells, and monocytes and expresses more PD-1. Redox tumours are enriched for oxidation-reduction and glutathione pathways and harbor more NFE2L2/KEAP1 alterations and copy gain in the 3q2 locus. Proteomic subtypes are not associated with patient survival. However, B-cell-rich tertiary lymph node structures, more common in Inflamed, are associated with better survival. We identify metabolic vulnerabilities (TP63, PSAT1, and TFRC) in Redox. Our work provides a powerful resource for lung SCC biology and suggests therapeutic opportunities based on redox metabolism and immune cell infiltrates.

African American Specific Gene Panel Predictive of Poor Prostate Cancer Outcome.

PURPOSE: Most prostate cancer in African American men lacks the ETS (E26 transforming specific) family fusion event (ETS-). We aimed to establish clinically relevant biomarkers in African American men by studying ETS dependent gene expression patterns to identified race specific genes predictive of outcomes. MATERIALS AND METHODS: Two multicenter cohorts of a total of 1,427 men were used for the discovery and validation (635 and 792 men, respectively) of race specific predictive biomarkers. We used false discovery rate adjusted q values to identify race and ETS dependent genes which were differentially expressed in African American men who experienced biochemical recurrence within 5 years. Principal component modeling along with survival analysis was done to assess the accuracy of the gene panel in predicting recurrence. RESULTS: We identified 3,047 genes which were differentially expressed based on ETS status. Of these genes 362 were differentially expressed in a race specific manner (false discovery rate 0.025 or less). A total of 81 genes were race specific and over expressed in African American men who experienced biochemical recurrence. The final gene panel included APOD, BCL6, EMP1, MYADM, SRGN and TIMP3. These genes were associated with 5-year biochemical recurrence (HR 1.97, 95% CI 1.27-3.06, p = 0.002) and they improved the predictive accuracy of clinicopathological variables only in African American men (60-month time dependent AUC 0.72). CONCLUSIONS: In an effort to elucidate biological features associated with prostate cancer aggressiveness in African American men we identified ETS dependent biomarkers predicting early onset biochemical recurrence only in African American men. Thus, these ETS dependent biomarkers representing ideal candidates for biomarkers of aggressive disease in this patient population.

Distinct transcriptional repertoire of the androgen receptor in ETS fusion-negative prostate cancer.

BACKGROUND: Prostate cancer (PCa) tumors harboring translocations of ETS family genes with the androgen responsive TMPRSS2 gene (ETS+ tumors) provide a robust biomarker for detecting PCa in approximately 70% of patients. ETS+ PCa express high levels of the androgen receptor (AR), yet PCa tumors lacking ETS fusions (ETS-) also express AR and demonstrate androgen-regulated growth. In this study, we evaluate the differences in the AR-regulated transcriptomes between ETS+ and ETS- PCa tumors. METHODS: 10,608 patient tumors from three independent PCa datasets classified as ETS+ (samples overexpressing ERG or other ETS family members) or ETS- (all other PCa) were analyzed for differential gene expression using false-discovery-rate adjusted methods and gene-set enrichment analysis (GSEA). RESULTS: Based on the expression of AR-dependent genes and an unsupervised Principal Component Analysis (PCA) model, AR-regulated gene expression alone was able to separate PCa samples into groups based on ETS status in all PCa databases. ETS status distinguished several differentially expressed genes in both TCGA (6.9%) and GRID (6.6%) databases, with 413 genes overlapping in both databases. Importantly, GSEA showed enrichment of distinct androgen-responsive genes in both ETS- and ETS+ tumors, and AR ChIP-seq data identified 131 direct AR-target genes that are regulated in an ETS-specific fashion. Notably, dysregulation of ETS-dependent AR-target genes within the metabolic and non-canonical WNT pathways was associated with clinical outcomes. CONCLUSIONS: ETS status influences the transcriptional repertoire of the AR, and ETS- PCa tumors appear to rely on distinctly different AR-dependent transcriptional programs to drive and sustain tumorigenesis.

Early transcriptional response of human ovarian and fallopian tube surface epithelial cells to norepinephrine.

Evidence from human and animal studies suggests that chronic behavioral stress and resulting activation of the sympathetic nervous system may influence initiation and progression of tumors. However, the underlying mechanisms for these observations are poorly understood. The purpose of this study is to explore the effects of adrenergic signaling on cell line models derived from normal cells presumed to originate epithelial ovarian cancers. Here we explored the effects of the stress-related hormone, norepinephrine, on the transcriptional program of normal immortalized ovarian (iOSE) and fallopian tube (iFTSEC) surface epithelial cells. Analysis of RNA-Seq data of treated and untreated cells revealed a significant overlap between the responses in iOSE and iFTSEC cells. Most genes modulated by norepinephrine in ovarian and fallopian tube epithelial cells are already expressed in normal ovarian and fallopian tissue and cells. For several genes, expression changes were reflected at the protein level. Genes in immune-related and developmental pathways were enriched in the set of genes modulated by norepinephrine. We identified HOXA5, SPIB, REL, SRF, SP1, NFKB1, MEF2A, E2F1, and EGR1 transcription factor binding sites to be highly enriched in our dataset. These data represent the early transcriptional response to norepinephrine in cells postulated to originate epithelial ovarian cancer.

Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes.

BACKGROUND: A unique 12-chemokine gene expression score (CS) accurately predicted the presence of tumor-localized, ectopic lymph node-like structures (TL-ELNs) and improved overall survival (OS) in primary colorectal cancer and metastatic melanoma. We analyzed the correlation between CS, clinicopathological variables, molecular data, and 366 survival in Moffitt Cancer Center's Total Cancer Care (TCC) patients with non-metastatic breast cancer. METHODS: Affymetrix gene expression profiles were used to interrogate the CS by the principal component method. Breast tumors were classified as high or low score based on median split, and correlations between clinicopathologic variables, PAM50 molecular subtype, and ELN formation were analyzed using the TCC dataset. Differences in overall survival (OS) and recurrence-free survival (RFS) in the larger KM Plot breast cancer public datasets were compared using Kaplan-Meier curves. RESULTS: We divided the Total Cancer Care (TCC) breast cancer patients into two groups of high or low CS. Mean CS was 0.24 (range, 2.2-2.1). Patients with higher CS were more likely to be white (172 vs. 159; p = 0.03), had poorly differentiated tumors (112 vs. 59; p <0.0001), ER/PR negative (41 vs. 26) and HER2 positive (36 vs. 19; p = 0.001), and contain TL-ELNs. Higher CS scores were also seen in the basal and HER2+ molecular subtypes. In the KM Plot breast cancer datasets higher CS patients demonstrated superior OS (HR = 0.73, p = 0.008) and RFS (HR 0.76, p = <0.0001), especially in basal and HER2+ patients. CONCLUSIONS: High CS breast tumors tend to be higher grade, basal or HER2+, and present more frequently in Caucasians. However, this group of patients also shows the presence of TL-ELNs within the tumor microenvironment and has better survival outcomes. The CS is a novel tool that can identify breast cancer patients with tumors of a unique intratumoral immune composition and better prognosis. Whether or not the CS is a predictive response marker in breast cancer patients undergoing immunotherapy remains to be determined.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns.

Motivation: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. Availability and Implementation: The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ . Contact: hlin1@lsuhsc.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

A combined reference panel from the 1000 Genomes and UK10K projects improved rare variant imputation in European and Chinese samples.

Imputation using the 1000 Genomes haplotype reference panel has been widely adapted to estimate genotypes in genome wide association studies. To evaluate imputation quality with a relatively larger reference panel and a reference panel composed of different ethnic populations, we conducted imputations in the Framingham Heart Study and the North Chinese Study using a combined reference panel from the 1000 Genomes (N = 1,092) and UK10K (N = 3,781) projects. For rare variants with 0.01% < MAF ≤ 0.5%, imputation in the Framingham Heart Study with the combined reference panel increased well-imputed genotypes (with imputation quality score ≥0.4) from 62.9% to 76.1% when compared to imputation with the 1000 Genomes. For the North Chinese samples, imputation of rare variants with 0.01% < MAF ≤ 0.5% with the combined reference panel increased well-imputed genotypes by from 49.8% to 61.8%. The predominant European ancestry of the UK10K and the combined reference panels may explain why there was less of an increase in imputation success in the North Chinese samples. Our results underscore the importance and potential of larger reference panels to impute rare variants, while recognizing that increasing ethnic specific variants in reference panels may result in better imputation for genotypes in some ethnic groups.

Targeted sequencing of genome wide significant loci associated with bone mineral density (BMD) reveals significant novel and rare variants: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) targeted sequencing study.

Background: Bone mineral density (BMD) is a heritable phenotype that predicts fracture risk. We performed fine-mapping by targeted sequencing at WLS, MEF2C, ARHGAP1/F2 and JAG1 loci prioritized by eQTL and bioinformatic approaches among 56 BMD loci from our previous GWAS meta-analysis. Targeted sequencing was conducted in 1,291 Caucasians from the Framingham Heart Study ( n = 925) and Cardiovascular Health Study ( n = 366), including 206 women and men with extreme low femoral neck (FN) BMD. A total of 4,964 sequence variants (SNVs) were observed and 80% were rare with MAF <1%. The associations between previously identified SNPs in these loci and BMD, while nominally significant in sequenced participants, were no longer significant after multiple testing corrections. Conditional analyses did not find protein-coding variants that may be responsible for GWAS signals. On the other hand, in the sequenced subjects, we identified novel associations in WLS , ARHGAP1 , and 5' of MEF2C ( P- values < 8x10 - 5 ; false discovery rate (FDR) q-values < 0.01) that were much more strongly associated with BMD compared to the GWAS SNPs. These associated SNVs are less-common; independent from previous GWAS signals in the same loci; and located in gene regulatory elements. Our findings suggest that protein-coding variants in selected GWAS loci did not contribute to GWAS signals. By performing targeted sequencing in GWAS loci, we identified less-common and rare non-coding SNVs associated with BMD independently from GWAS common SNPs, suggesting both common and less-common variants may associate with disease risks and phenotypes in the same loci.

Coexpression and expression quantitative trait loci analyses of the angiogenesis gene-gene interaction network in prostate cancer.

BACKGROUND: Prostate cancer (PCa) shows a substantial clinical heterogeneity. The existing risk classification for PCa prognosis based on clinical factors is not sufficient. Although some biomarkers for PCa aggressiveness have been identified, their underlying functional mechanisms are still unclear. We previously reported a gene-gene interaction network associated with PCa aggressiveness based on single nucleotide polymorphism (SNP)-SNP interactions in the angiogenesis pathway. The goal of this study is to investigate potential functional evidence of the involvement of the genes in this gene-gene interaction network. METHODS: A total of 11 angiogenesis genes were evaluated. The crosstalks among genes were examined through coexpression and expression quantitative trait loci (eQTL) analyses. The study population is 352 Caucasian PCa patients in the Cancer Genome Atlas (TCGA) study. The pairwise coexpressions among the genes of interest were evaluated using the Spearman coefficient. The eQTL analyses were tested using the Kruskal-Wallis test. RESULTS: Among all within gene and 55 possible pairwise gene evaluations, 12 gene pairs and one gene (MMP16) showed strong coexpression or significant eQTL evidence. There are nine gene pairs with a strong correlation (Spearman correlation ≥0.6, P<1×10-13). The top coexpressed gene pairs are EGFR-SP1 (r=0.73), ITGB3-HSPG2 (r=0.71), ITGB3-CSF1 (r=0.70), MMP16-FBLN5 (r=0.68), ITGB3-MMP16 (r=0.65), ITGB3-ROBO1 (r=0.62), CSF1-HSPG2 (r=0.61), CSF1-FBLN5 (r=0.6), and CSF1-ROBO1 (r=0.60). One cis-eQTL in MMP16 and five trans-eQTLs (MMP16-ESR1, ESR1-ROBO1, CSF1-ROBO1, HSPG2-ROBO1, and FBLN5-CSF1) are significant with a false discovery rate q value less than 0.2. CONCLUSIONS: These findings provide potential biological evidence for the gene-gene interactions in this angiogenesis network. These identified interactions between the angiogenesis genes not only provide information for PCa etiology mechanism but also may serve as integrated biomarkers for building a risk prediction model for PCa aggressiveness.

Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture.

The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF ≤ 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 × 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 × 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1(cre/flox) mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 × 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.