ORCID Profile
0000-0002-4357-0439
Current Organisations
The Chinese University of Hong Kong
,
The Chinese University of Hong Kong Faculty of Medicine
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Publisher: IEEE
Date: 06-2015
Publisher: American Association for Cancer Research (AACR)
Date: 15-02-2015
DOI: 10.1158/0008-5472.CAN-14-1301
Abstract: Chromatin remodeling has emerged as a hallmark of gastric cancer, but the regulation of chromatin regulators other than genetic change is unknown. Helicobacter pylori causes epigenetic dysregulation to promote gastric carcinogenesis, but the roles and functions of microRNAs (miRNA) in this multistage cascade are not fully explored. In this study, miRNA expression in preneoplastic and neoplastic lesions in murine stomachs induced by H. pylori and N-methyl-N-nitrosourea (MNU) was profiled by miRNA expression array. miR-490-3p exhibited progressive downregulation in gastritis, intestinal metaplasia, and adenocarcinoma during H. pylori and MNU-induced gastric carcinogenesis. Significant downregulation of miR-490-3p was confirmed in human gastric cancer tissues in which its regulatory region was found to be hypermethylated. miR-490-3p exerted growth- and metastasis-suppressive effects on gastric cancer cells through directly targeting SMARCD1, a SWItch/Sucrose NonFermentable (SWI/SNF) chromatin remodeling complex subunit. Knockdown of SMARCD1 significantly attenuated the protumorigenic effects of miR-490-3p inhibitor, whereas enforced expression of SMARCD1 promoted in vitro and in vivo oncogenic phenotypes of gastric cancer cells. SMARCD1 was markedly upregulated in gastric cancer in which its high expression was associated with shortened patients' survival independent of TNM staging. In conclusion, hypermethylation-mediated silencing of miR-490-3p reactivates SMARCD1 to confer malignant phenotypes, mechanistically linking H. pylori, chromatin remodeling, and gastric carcinogenesis. Cancer Res 75(4) 754–65. ©2014 AACR.
Publisher: Elsevier BV
Date: 11-2018
Abstract: Cancer-related genes are under intense evolutionary pressure. We conjectured that gene size is an important determinant of lification propensity for oncogenes and thus cancer susceptibility and therefore could be subject to natural selection. Gene information, including size and genomic locations, of all protein-coding genes were downloaded from Ensembl (release 87). Quantification of gene lification was based on Genomic Identification of Significant Targets in Cancer scores obtained from available The Cancer Genome Atlas studies. Oncogenes are larger in size as compared with non-cancer genes (mean size: 92.1 kb versus 61.4 kb P < 0.0001) in the human genome, which is contributed by both increased total exon size (mean size: 4.6 kb versus 3.4 kb P < 0.0001) and higher intronic content (mean %: 84.8 versus 78.0 P < 0.01). Such non-random size distribution and intronic composition are conserved in mouse and Drosophila (all P < 0.0001). Stratification by gene age indicated that young oncogenes have been subject to a stronger evolutionary pressure for gene expansion than their non-cancer counterparts. Pan-cancer analysis demonstrated that larger oncogenes were lified to a lesser extent. Tumor-suppressor genes also moved toward small oncogenes in the course of evolution. Oncogenes expand in size whereas tumor-suppressor genes move closer to small oncogenes in the course of evolution to withstand oncogenic somatic lification. Our findings have shed new light on the previously unappreciated influence of gene size on oncogene lification and elucidated how cancers have shaped our genome to its present configuration.
Publisher: Wiley
Date: 28-02-2018
DOI: 10.1002/PATH.5033
Abstract: Evasion of autophagy is key for intracellular survival of bacteria in host cells, but its involvement in persistent infection by Helicobacter pylori, a bacterium identified to invade gastric epithelial cells, remains obscure. The aim of this study was to functionally characterize the role of autophagy in H. pylori infection. Autophagy was assayed in H. pylori-infected human gastric epithelium and the functional role of autophagy was determined via genetic or pharmacological ablation of autophagy in mouse and cell line models of H. pylori infection. Here, we showed that H. pylori inhibited lysosomal function and thereby promoted the accumulation of autophagosomes in gastric epithelial cells. Importantly, inhibiting autophagosome formation by pharmacological inhibitors or genetic ablation of BECN1 or ATG5 reduced H. pylori intracellular survival, whereas inhibition of lysosomal functions exerted an opposite effect. Further experiments demonstrated that H. pylori inhibited lysosomal acidification and the retrograde trafficking of mannose-6-phosphate receptors, both of which are known to positively regulate lysosomal function. We conclude that H. pylori subverts autophagy into a pro-survival mechanism through inhibition of lysosomal clearance of autophagosomes. Disruption of autophagosome formation offers a novel strategy to reduce H. pylori colonization in human stomachs. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Publisher: Oxford University Press (OUP)
Date: 12-01-2017
Publisher: Springer Science and Business Media LLC
Date: 16-06-2022
DOI: 10.1038/S41591-022-01877-1
Abstract: Timely evaluation of the protective effects of Coronavirus Disease 2019 (COVID-19) vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is urgently needed to inform pandemic control planning. Based on 78 vaccine efficacy or effectiveness (VE) data from 49 studies and 1,984,241 SARS-CoV-2 sequences collected from 31 regions, we analyzed the relationship between genetic distance (GD) of circulating viruses against the vaccine strain and VE against symptomatic infection. We found that the GD of the receptor-binding domain of the SARS-CoV-2 spike protein is highly predictive of vaccine protection and accounted for 86.3% ( P = 0.038) of the VE change in a vaccine platform-based mixed-effects model and 87.9% ( P = 0.006) in a manufacturer-based model. We applied the VE-GD model to predict protection mediated by existing vaccines against new genetic variants and validated the results by published real-world and clinical trial data, finding high concordance of predicted VE with observed VE. We estimated the VE against the Delta variant to be 82.8% (95% prediction interval: 68.7–96.0) using the mRNA vaccine platform, closely matching the reported VE of 83.0% from an observational study. Among the four sublineages of Omicron, the predicted VE varied between 11.9% and 33.3%, with the highest VE predicted against BA.1 and the lowest against BA.2, using the mRNA vaccine platform. The VE-GD framework enables predictions of vaccine protection in real time and offers a rapid evaluation method against novel variants that may inform vaccine deployment and public health responses.
Publisher: Wiley
Date: 03-2023
DOI: 10.1111/PAI.13854
Abstract: Since the discovery of immunoglobulin E (IgE) as a mediator of allergic diseases in 1967, our knowledge about the immunological mechanisms of IgE‐mediated allergies has remarkably increased. In addition to understanding the immune response and clinical symptoms, allergy diagnosis and management depend strongly on the precise identification of the elicitors of the IgE‐mediated allergic reaction. In the past four decades, innovations in bioscience and technology have facilitated the identification and production of well‐defined, highly pure molecules for component‐resolved diagnosis (CRD), allowing a personalized diagnosis and management of the allergic disease for in idual patients. The first edition of the “EAACI Molecular Allergology User's Guide” (MAUG) in 2016 rapidly became a key reference for clinicians, scientists, and interested readers with a background in allergology, immunology, biology, and medicine. Nevertheless, the field of molecular allergology is moving fast, and after 6 years, a new EAACI Taskforce was established to provide an updated document. The Molecular Allergology User's Guide 2.0 summarizes state‐of‐the‐art information on allergen molecules, their clinical relevance, and their application in diagnostic algorithms for clinical practice. It is designed for both, clinicians and scientists, guiding health care professionals through the overwhelming list of different allergen molecules available for testing. Further, it provides diagnostic algorithms on the clinical relevance of allergenic molecules and gives an overview of their biology, the basic mechanisms of test formats, and the application of tests to measure allergen exposure.
Publisher: Centers for Disease Control and Prevention (CDC)
Date: 10-2018
Publisher: Elsevier BV
Date: 03-2020
Publisher: American Chemical Society (ACS)
Date: 19-06-1999
DOI: 10.1021/JP990926X
Publisher: The Royal Society
Date: 09-2021
DOI: 10.1098/RSOS.201867
Abstract: The novel coronavirus disease 2019 (COVID-19) has spread worldwide and threatened human life. Diagnosis is crucial to contain the spread of SARS-CoV-2 infections and save lives. Diagnostic tests for COVID-19 have varying sensitivity and specificity, and the false-negative results would have substantial consequences to patient treatment and pandemic control. To detect all suspected infections, multiple testing is widely used. However, it may be challenging to build an assertion when the testing results are inconsistent. Considering the situation where there is more than one diagnostic outcome for each subject, we proposed a Bayesian probabilistic framework based on the sensitivity and specificity of each diagnostic method to synthesize a posterior probability of being infected by SARS-CoV-2. We demonstrated that the synthesized posterior outcome outperformed each in idual testing outcome. A user-friendly web application was developed to implement our analytic framework with free access via www2.ccrb.cuhk.edu.hk/statgene/COVID_19/ . The web application enables the real-time display of the integrated outcome incorporating two or more tests and calculated based on Bayesian posterior probability. A simulation-based assessment demonstrated higher accuracy and precision of the Bayesian probabilistic model compared with a single-test outcome. The online tool developed in this study can assist physicians in making clinical evaluations by effectively integrating multiple COVID-19 tests.
Location: No location found
Location: Hong Kong
No related grants have been discovered for Kati Palosuo.