MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data.
Endometriosis is characterized by ectopic endometrial-like epithelium and stroma, of which molecular characteristics remain to be fully elucidated. We sequenced 107 ovarian endometriotic and 82 normal uterine endometrial epithelium samples isolated by laser microdissection. In both endometriotic and normal epithelium samples, numerous somatic mutations were identified within genes frequently mutated in endometriosis-associated ovarian cancers. KRAS is frequently mutated in endometriotic epithelium, with a higher mutant allele frequency (MAF) accompanied by arm-level allelic imbalances. Analyses of MAF, combined with multiregional sequencing, illuminated spatiotemporal evolution of the endometriosis and uterine endometrium genomes. We sequenced 109 single endometrial glands and found that each gland carried distinct cancer-associated mutations, demonstrating the heterogeneity of the genomic architecture of endometrial epithelium. Remarkable increases in MAF of mutations in cancer-associated genes in endometriotic epithelium suggest retrograde flow of endometrial cells already harboring cancer-associated mutations, with selective advantages at ectopic sites, leading to the development of endometriosis.
We conducted a genome-wide association (GWA) meta-analysis of 4,604 endometriosis cases and 9,393 controls of Japanese1 and European2 ancestry. We show that rs12700667 on chromosome 7p15.2, previously found in Europeans, replicates in Japanese (P = 3.6 × 10−3), and confirm association of rs7521902 on 1p36.12 near WNT4. In addition, we establish association of rs13394619 in GREB1 on 2p25.1 and identify a novel locus on 12q22 near VEZT (rs10859871). Excluding European cases with minimal or unknown severity, we identified additional novel loci on 2p14 (rs4141819), 6p22.3 (rs7739264) and 9p21.3 (rs1537377). All seven SNP effects were replicated in an independent cohort and produced P < 5 × 10−8 in a combined analysis. Finally, we found a significant overlap in polygenic risk for endometriosis between the European and Japanese GWA cohorts (P = 8.8 × 10−11), indicating that many weakly associated SNPs represent true endometriosis risk loci and risk prediction and future targeted disease therapy may be transferred across these populations.
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