Displaying publications 61 - 64 of 64 in total

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  1. Shi W, Louzada S, Grigorova M, Massaia A, Arciero E, Kibena L, et al.
    Hum Mol Genet, 2019 Aug 15;28(16):2785-2798.
    PMID: 31108506 DOI: 10.1093/hmg/ddz101
    Human RBMY1 genes are located in four variable-sized clusters on the Y chromosome, expressed in male germ cells and possibly associated with sperm motility. We have re-investigated the mutational background and evolutionary history of the RBMY1 copy number distribution in worldwide samples and its relevance to sperm parameters in an Estonian cohort of idiopathic male factor infertility subjects. We estimated approximate RBMY1 copy numbers in 1218 1000 Genomes Project phase 3 males from sequencing read-depth, then chose 14 for valid ation by multicolour fibre-FISH. These fibre-FISH samples provided accurate calibration standards for the entire panel and led to detailed insights into population variation and mutational mechanisms. RBMY1 copy number worldwide ranged from 3 to 13 with a mode of 8. The two larger proximal clusters were the most variable, and additional duplications, deletions and inversions were detected. Placing the copy number estimates onto the published Y-SNP-based phylogeny of the same samples suggested a minimum of 562 mutational changes, translating to a mutation rate of 2.20 × 10-3 (95% CI 1.94 × 10-3 to 2.48 × 10-3) per father-to-son Y-transmission, higher than many short tandem repeat (Y-STRs), and showed no evidence for selection for increased or decreased copy number, but possible copy number stabilizing selection. An analysis of RBMY1 copy numbers among 376 infertility subjects failed to replicate a previously reported association with sperm motility and showed no significant effect on sperm count and concentration, serum follicle stimulating hormone (FSH), luteinizing hormone (LH) and testosterone levels or testicular and semen volume. These results provide the first in-depth insights into the structural rearrangements underlying RBMY1 copy number variation across diverse human lineages.
    Matched MeSH terms: Genome, Human
  2. Vui-Kee K, Mohd Dali AZ, Mohamed Rose I, Ghazali R, Jamal R, Mokhtar NM
    Kaohsiung J. Med. Sci., 2012 May;28(5):243-50.
    PMID: 22531302 DOI: 10.1016/j.kjms.2011.11.007
    Nonepithelial ovarian cancer (NEOC) is a rare cancer that is often misdiagnosed as other malignant tumors. Research on this cancer using fresh tissues is nearly impossible because of its limited number of samples within a limited time provided. The study is to identify potential genes and their molecular pathways related to NEOC using formalin-fixed paraffin embedded samples. Total RNA was extracted from eight archived NEOCs and seven normal ovaries. The RNA samples with RNA integrity number >2.0, purity >1.7 and cycle count value <28 cycles were hybridized to the Illumina Whole-Genome DASL assay (cDNA-mediated annealing, selection, extension, and ligation). We analyzed the results using the GeneSpring GX11.0 and FlexArray software to determine the differentially expressed genes. Microarray results were validated using an immunohistochemistry method. Statistical analysis identified 804 differentially expressed genes with 443 and 361 genes as overexpressed and underexpressed in cancer, respectively. Consistent findings were documented for the overexpression of eukaryotic translation elongation factor 1 alpha 1, E2F transcription factor 2, and fibroblast growth factor receptor 3, except for the down-regulated gene, early growth response 1 (EGR1). The immunopositivity staining for EGR1 was found in the majority of cancer tissues. This finding suggested that the mRNA level of a transcript did not always match with the protein expression in tissues. The current gene profile can be the platform for further exploration of the molecular mechanism of NEOC.
    Matched MeSH terms: Genome, Human
  3. Pan JW, Zabidi MMA, Ng PS, Meng MY, Hasan SN, Sandey B, et al.
    Nat Commun, 2020 Dec 22;11(1):6433.
    PMID: 33353943 DOI: 10.1038/s41467-020-20173-5
    Molecular profiling of breast cancer has enabled the development of more robust molecular prognostic signatures and therapeutic options for breast cancer patients. However, non-Caucasian populations remain understudied. Here, we present the mutational, transcriptional, and copy number profiles of 560 Malaysian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to breast tumours in Caucasian women, we show an increased prevalence of HER2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. We also observe elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst HER2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.
    Matched MeSH terms: Genome, Human
  4. Darawi MN, Ai-Vyrn C, Ramasamy K, Hua PP, Pin TM, Kamaruzzaman SB, et al.
    BMC Med Genet, 2013;14:27.
    PMID: 23419238 DOI: 10.1186/1471-2350-14-27
    The incidence of Alzheimer's disease, particularly in developing countries, is expected to increase exponentially as the population ages. Continuing research in this area is essential in order to better understand this disease and develop strategies for treatment and prevention. Genome-wide association studies have identified several loci as genetic risk factors of AD aside from apolipoprotein E such as bridging integrator (BIN1), clusterin (CLU), ATP-binding cassette sub-family A member 7 (ABCA7), complement receptor 1 (CR1) and phosphatidylinositol binding clathrin assembly protein (PICALM). However genetic research in developing countries is often limited by lack of funding and expertise. This study therefore developed and validated a simple, cost effective polymerase chain reaction based technique to determine these single nucleotide polymorphisms.
    Matched MeSH terms: Genome, Human
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