RESUMEN
BACKGROUND@#Single-nucleotide polymorphisms (SNPs)-associated genes and long non-coding RNAs (lncRNAs) can contribute to human disease. To comprehensively investigate the contribution of lncRNAs to breast cancer, we performed the first genome-wide lncRNA association study on Han Chinese women.@*METHODS@#We designed an lncRNA array containing >800,000 SNPs, which was incorporated into a 96-array plate by Affymetrix (CapitalBio Technology, China). Subsequently, we performed a two-stage genome-wide lncRNA association study on Han Chinese women covering 11,942 individuals (5634 breast cancer patients and 6308 healthy controls). Additionally, in vitro gain or loss of function strategies were performed to clarify the function of a novel SNP-associated gene.@*RESULTS@#We identified a novel breast cancer-associated susceptibility SNP, rs11066150 (Pmeta = 2.34 × 10-8), and a previously reported SNP, rs9397435 (Pmeta = 4.32 × 10-38), in Han Chinese women. rs11066150 is located in NONHSAT164009.1 (lncHSAT164), which is highly expressed in breast cancer tissues and cell lines. lncHSAT164 overexpression promoted colony formation, whereas lncHSAT164 knockdown promoted cell apoptosis and reduced colony formation by regulating the cell cycle.@*CONCLUSIONS@#Based on our lncRNA array, we identified a novel breast cancer-associated lncRNA and found that lncHSAT164 may contribute to breast cancer by regulating the cell cycle. These findings suggest a potential therapeutic target in breast cancer.
Asunto(s)
Femenino , Humanos , Pueblo Asiatico/genética , Neoplasias de la Mama/genética , Estudios de Casos y Controles , China , Predisposición Genética a la Enfermedad/genética , Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple/genética , ARN Largo no Codificante/genéticaRESUMEN
To identify the genetic factors influencing complex diseases is a challenging problem. With the development of several technologies, such as large-scale genome sequencing, gene chips and mass spectrometry, and the successful completion of the first phase of International HapMap Project, it is feasible to explore the associations between hundreds of polymorphisms in the human genome, even the whole genome, and complex diseases in populations with large number of samples. The present paper briefly describes the results of the International HapMap Project, the merging whole-genome association study, and some new methods applicable to data including multiple loci.