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  1. Abu N, Othman N, W Hon K, Nazarie WF, Jamal R
    Biomark Med, 2020 05;14(7):525-537.
    PMID: 32462912 DOI: 10.2217/bmm-2019-0241
    Background: Finding a new target or a new drug to overcome chemoresistance is difficult due to the heterogenous nature of cancer. Meta-analysis was performed to combine the analysis of different microarray studies to get a robust discovery. Materials & methods: Herein, we analyzed three microarray datasets on combination of folinic acid, fluorouracil, and oxaliplatin drugs (FOLFOX) resistance that fit our inclusion/exclusion criteria and performed a meta-analysis using the OmiCC system. Results: We identified several deregulated genes and we discovered HNF4A as a hub gene. We performed functional validation and observed that by targeting HNF4A, HCT116 cells were more sensitive toward both oxaliplatin and 5-fluorouracil significantly. Conclusion: Our findings show that HNF4A could be a potential target in overcoming FOLFOX chemoresistance in colorectal cancer.
  2. Yap HY, Ghazali K, Wan Mohamad Nazarie WF, Mat Isa MN, Zakaria Z, Omar AR
    Genome Announc, 2013;1(5).
    PMID: 24136854 DOI: 10.1128/genomeA.00872-13
    Pasteurella multocida serotypes B:2 and E:2 are the main causative agents of ruminant hemorrhagic septicemia in Asia and Africa, respectively. Pasteurella multocida strain PMTB was isolated from a buffalo with hemorrhagic septicemia and has been determined to be serotype B:2. Here we report the draft genome sequence of strain PMTB.
  3. Syafruddin SE, Mohtar MA, Wan Mohamad Nazarie WF, Low TY
    Biomolecules, 2020 09 28;10(10).
    PMID: 32998281 DOI: 10.3390/biom10101378
    The Krüppel-like factors (KLFs) family of proteins control several key biological processes that include proliferation, differentiation, metabolism, apoptosis and inflammation. Dysregulation of KLF functions have been shown to disrupt cellular homeostasis and contribute to disease development. KLF6 is a relevant example; a range of functional and expression assays suggested that the dysregulation of KLF6 contributes to the onset of cancer, inflammation-associated diseases as well as cardiovascular diseases. KLF6 expression is either suppressed or elevated depending on the disease, and this is largely due to alternative splicing events producing KLF6 isoforms with specialised functions. Hence, the aim of this review is to discuss the known aspects of KLF6 biology that covers the gene and protein architecture, gene regulation, post-translational modifications and functions of KLF6 in health and diseases. We put special emphasis on the equivocal roles of its full-length and spliced variants. We also deliberate on the therapeutic strategies of KLF6 and its associated signalling pathways. Finally, we provide compelling basic and clinical questions to enhance the knowledge and research on elucidating the roles of KLF6 in physiological and pathophysiological processes.
  4. Ang MY, Low TY, Lee PY, Wan Mohamad Nazarie WF, Guryev V, Jamal R
    Clin Chim Acta, 2019 Nov;498:38-46.
    PMID: 31421119 DOI: 10.1016/j.cca.2019.08.010
    One of the best-established area within multi-omics is proteogenomics, whereby the underpinning technologies are next-generation sequencing (NGS) and mass spectrometry (MS). Proteogenomics has contributed significantly to genome (re)-annotation, whereby novel coding sequences (CDS) are identified and confirmed. By incorporating in-silico translated genome variants in protein database, single amino acid variants (SAAV) and splice proteoforms can be identified and quantified at peptide level. The application of proteogenomics in cancer research potentially enables the identification of patient-specific proteoforms, as well as the association of the efficacy or resistance of cancer therapy to different mutations. Here, we discuss how NGS/TGS data are analyzed and incorporated into the proteogenomic framework. These sequence data mainly originate from whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. We explain two major strategies for sequence analysis i.e., de novo assembly and reads mapping, followed by construction of customized protein databases using such data. Besides, we also elaborate on the procedures of spectrum to peptide sequence matching in proteogenomics, and the relationship between database size on the false discovery rate (FDR). Finally, we discuss the latest development in proteogenomics-assisted precision oncology and also challenges and opportunities in proteogenomics research.
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