Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352

Identification of 19 new risk loci and potential regulatory mechanisms influencing susceptibility to testicular germ cell tumor

Genome-wide association studies (GWAS) have transformed understanding of susceptibility to testicular germ cell tumors (TGCTs), but much of the heritability remains unexplained. Here we report a new GWAS, a meta-analysis with previous GWAS and a replication series, totaling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, roughly doubling the number of known TGCT risk loci to 44. By performing in situ Hi-C in TGCT cells, we provide evidence for a network of physical interactions among all 44 TGCT risk SNPs and candidate causal genes. Our findings implicate widespread disruption of developmental transcriptional regulators as a basis of TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis. Defective microtubule assembly and dysregulation of KIT-MAPK signaling also feature as recurrently disrupted pathways. Our findings support a polygenic model of risk and provide insight into the biological basis of TGCT.We acknowledge National Health Service funding to the National Institute for Health Research Biomedical Research Centre. Genotyping of the OncoArray was funded by the US National Institutes of Health (NIH) (U19 CA 148537 for Elucidating Loci Involved in Prostate cancer Susceptibility (ELLIPSE) project and X01HG007492 to the Center for Inherited Disease Research (CIDR) under contract number HHSN268201200008I). Additional analytical support was provided by NIH NCI U01 CA188392. The PRACTICAL consortium was supported by Cancer Research UK Grants C5047/A7357, C1287/A10118, C1287/A16563, C5047/A3354, C5047/A10692 and C16913/A6135; the European Commission’s Seventh Framework Programme grant agreement 223175 (HEALTH-F2-2009-223175) (D.F.E., R.E. and Z.K.-J.); and the NIH Cancer Post-Cancer GWAS initiative grant 1 U19 CA 148537-01 (the GAME-ON initiative). We thank the following for funding support: the Institute of Cancer Research and the Everyman Campaign, the Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), the Orchid Cancer Appeal, the National Cancer Research Network UK and the National Cancer Research Institute (NCRI) UK. We are grateful for NIHR funding to the Biomedical Research Centre at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust. We acknowledge funding from the Swedish Cancer Society (CAN2011/484 and CAN2012/823), the Norwegian Cancer Society (grants 418975-71081-PR-2006-0387 and PK01-2007- 0375) and the Nordic Cancer Union (grant S-12/07). This study was supported by the Movember Foundation and the Institute of Cancer Research. K.L. is supported by a PhD fellowship from Cancer Research UK. R.S.H. and P.B. are supported by Cancer Research UK (C1298/A8362 Bobby Moore Fund for Cancer Research UK)

Convergence of dispersed regulatory mutations reveals candidate driver genes in prostate cancer

Non UBCUnreviewedAuthor affiliation: MITResearche

MicroRNAs and Regeneration: Let-7 Members as Potential Regulators of Dedifferentiation in Lens and Inner Ear Hair Cell Regeneration of the Adult Newt

MicroRNAs are known to regulate the expression of many mRNAs by binding to complementary target sequences at the 3′UTRs. Because of such properties, miRNAs may regulate tissue-specific mRNAs as a cell undergoes transdifferentiation during regeneration. We have tested this hypothesis during lens and hair cell regeneration in newts using microarray analysis. We found that distinct sets of miRNAs are associated with lens and hair cell regeneration. Members of the let-7 family are expressed in both events and they are regulated in a similar fashion. All the let-7 members are down regulated during the initiation of regeneration, which is characterized by dedifferentiation of terminally differentiated cells. This is the first report to correlate expression of miRNAs as novel regulators of vertebrate regeneration, alluding to a novel mechanism whereby transdifferentiation occurs

MicroRNAs and Regeneration: Let-7 Members as Potential Regulators of Dedifferentiation in Lens and Inner Ear Hair Cell Regeneration of the Adult Newt

MicroRNAs are known to regulate the expression of many mRNAs by binding to complementary target sequences at the 3′UTRs. Because of such properties, miRNAs may regulate tissue-specific mRNAs as a cell undergoes transdifferentiation during regeneration. We have tested this hypothesis during lens and hair cell regeneration in newts using microarray analysis. We found that distinct sets of miRNAs are associated with lens and hair cell regeneration. Members of the let-7 family are expressed in both events and they are regulated in a similar fashion. All the let-7 members are down regulated during the initiation of regeneration, which is characterized by dedifferentiation of terminally differentiated cells. This is the first report to correlate expression of miRNAs as novel regulators of vertebrate regeneration, alluding to a novel mechanism whereby transdifferentiation occurs

Variant Set Enrichment: an R package to identify disease-associated functional genomic regions

BACKGROUND: Genetic predispositions to diseases populate the noncoding regions of the human genome. Delineating their functional basis can inform on the mechanisms contributing to disease development. However, this remains a challenge due to the poor characterization of the noncoding genome. Here, we propose an R package that can pinpoint which genomic features are etiologically important based on the genetic predispositions. RESULTS: Variant Set Enrichment (VSE) is an R package to calculate the enrichment of a set of disease-associated variants across functionally annotated genomic regions, consequently highlighting the mechanisms important in the etiology of the disease studied. CONCLUSIONS: VSE is implemented as an R package and can easily be implemented in any system with R. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13040-017-0129-5) contains supplementary material, which is available to authorized users