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  1. Hassn Mesrati M, Behrooz AB, Y Abuhamad A, Syahir A
    Cells, 2020 05 16;9(5).
    PMID: 32429463 DOI: 10.3390/cells9051236
    Gliomas are the most frequent and deadly form of human primary brain tumors. Among them, the most common and aggressive type is the high-grade glioblastoma multiforme (GBM), which rapidly grows and renders patients a very poor prognosis. Meanwhile, cancer stem cells (CSCs) have been determined in gliomas and play vital roles in driving tumor growth due to their competency in self-renewal and proliferation. Studies of gliomas have recognized CSCs via specific markers. This review comprehensively examines the current knowledge of the most significant CSCs markers in gliomas in general and in glioblastoma in particular and specifically focuses on their outlook and importance in gliomas CSCs research. We suggest that CSCs should be the superior therapeutic approach by directly targeting the markers. In addition, we highlight the association of these markers with each other in relation to their cascading pathways, and interactions with functional miRNAs, providing the role of the networks axes in glioblastoma signaling pathways.
  2. Husam IS, Abuhamad, Azuraliza Abu Bakar, Suhaila Zainudin, Mazrura Sahani, Zainudin Mohd Ali
    Sains Malaysiana, 2017;46:255-265.
    Dengue fever is considered as one of the most common mosquito borne diseases worldwide. Dengue outbreak detection can be very useful in terms of practical efforts to overcome the rapid spread of the disease by providing the knowledge to predict the next outbreak occurrence. Many studies have been conducted to model and predict dengue outbreak using different data mining techniques. This research aimed to identify the best features that lead to better predictive accuracy of dengue outbreaks using three different feature selection algorithms; particle swarm optimization (PSO), genetic algorithm (GA) and rank search (RS). Based on the selected features, three predictive modeling techniques (J48, DTNB and Naive Bayes) were applied for dengue outbreak detection. The dataset used in this research was obtained from the Public Health Department, Seremban, Negeri Sembilan, Malaysia. The experimental results showed that the predictive accuracy was improved by applying feature selection process before the predictive modeling process. The study also showed the set of features to represent dengue outbreak detection for Malaysian health agencies.
  3. Abuhamad AY, Mohamad Zamberi NN, Vanharanta S, Mohd Yusuf SNH, Mohtar MA, Syafruddin SE
    Int J Mol Sci, 2023 Mar 29;24(7).
    PMID: 37047421 DOI: 10.3390/ijms24076447
    Clear cell renal cell carcinoma (ccRCC) is a hypervascular tumor that is characterized by bi-allelic inactivation of the VHL tumor suppressor gene and mTOR signalling pathway hyperactivation. The pro-angiogenic factor PDGFB, a transcriptional target of super enhancer-driven KLF6, can activate the mTORC1 signalling pathway in ccRCC. However, the detailed mechanisms of PDGFB-mediated mTORC1 activation in ccRCC have remained elusive. Here, we investigated whether ccRCC cells are able to secrete PDGFB into the extracellular milieu and stimulate mTORC1 signalling activity. We found that ccRCC cells secreted PDGFB extracellularly, and by utilizing KLF6- and PDGFB-engineered ccRCC cells, we showed that the level of PDGFB secretion was positively correlated with the expression of intracellular KLF6 and PDGFB. Moreover, the reintroduction of either KLF6 or PDGFB was able to sustain mTORC1 signalling activity in KLF6-targeted ccRCC cells. We further demonstrated that conditioned media of PDGFB-overexpressing ccRCC cells was able to re-activate mTORC1 activity in KLF6-targeted cells. In conclusion, cancer cell-derived PDGFB can mediate mTORC1 signalling pathway activation in ccRCC, further consolidating the link between the KLF6-PDGFB axis and the mTORC1 signalling pathway activity in ccRCC.
  4. Mohamad Zamberi NN, Abuhamad AY, Low TY, Mohtar MA, Syafruddin SE
    CRISPR J, 2024 Apr;7(2):73-87.
    PMID: 38635328 DOI: 10.1089/crispr.2023.0078
    Clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing is evolving into an essential tool in the field of biological and medical research. Notably, the development of catalytically deactivated Cas9 (dCas9) enzyme has substantially broadened its traditional boundaries in gene editing or perturbation. The conjugation of dCas9 with various molecular effectors allows precise control over transcriptional processes, epigenetic modifications, visualization of chromosomal dynamics, and several other applications. This expanded repertoire of CRISPR-Cas9 applications has emerged as an invaluable molecular tool kit that empowers researchers to comprehensively interrogate and gain insights into health and diseases. This review delves into the advancements in Cas9 protein engineering, specifically on the generation of various dCas9 tools that have significantly enhanced the CRISPR-based technology capability and versatility. We subsequently discuss the multifaceted applications of dCas9, especially in interrogating the regulation and function of genes that involve in supporting cancer pathogenesis. In addition, we also delineate the designing and utilization of dCas9-based tools as well as highlighting its current constraints and transformative potentials in cancer research.
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