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Fulltext Two Genetically Distinct Plasmodium knowlesi Duffy Binding Protein Alpha Region II (PkDBPαII) Haplotypes Demonstrate Higher Binding Level to Fy(a+b+) Erythrocytes than Fy(a+b--) Erythrocytes

Liew CC, Lau YL, Fong MY, Cheong FW

Am J Trop Med Hyg, 2020 05;102(5):1068-1071.
PMID: 32189613 DOI: 10.4269/ajtmh.19-0836

Invasion of human erythrocytes by merozoites of Plasmodium knowlesi involves interaction between the P. knowlesi Duffy binding protein alpha region II (PkDBPαII) and Duffy antigen receptor for chemokines (DARCs) on the erythrocytes. Information is scarce on the binding level of PkDBPαII to different Duffy antigens, Fya and Fyb. This study aims to measure the binding level of two genetically distinct PkDBPαII haplotypes to Fy(a+b-) and Fy(a+b+) human erythrocytes using erythrocyte-binding assay. The binding level of PkDBPαII of Peninsular Malaysian and Malaysian Borneon haplotypes to erythrocytes was determined by counting the number of rosettes formed in the assay. Overall, the Peninsular Malaysian haplotype displayed higher binding activity than the Malaysian Borneon haplotype. Both haplotypes exhibit the same preference to Fy(a+b+) compared with Fy(a+b-), hence justifying the vital role of Fyb in the binding to PkDBPαII. Further studies are needed to investigate the P. knowlesi susceptibility on individuals with different Duffy blood groups.
Fulltext A case-controlled validation study of a blood-based seven-gene biomarker panel for colorectal cancer in Malaysia

Yip KT, Das PK, Suria D, Lim CR, Ng GH, Liew CC

J Exp Clin Cancer Res, 2010 Sep 16;29(1):128.
PMID: 20846378 DOI: 10.1186/1756-9966-29-128

BACKGROUND: Colorectal cancer (CRC) screening is key to CRC prevention and mortality reduction, but patient compliance with CRC screening is low. We previously reported a blood-based test for CRC that utilizes a seven-gene panel of biomarkers. The test is currently utilized clinically in North America for CRC risk stratification in the average-risk North American population in order to improve screening compliance and to enhance clinical decision making.
METHODS: In this study, conducted in Malaysia, we evaluated the seven-gene biomarker panel validated in a North American population using blood samples collected from local patients. The panel employs quantitative RT-PCR (qRT-PCR) to analyze gene expression of the seven biomarkers (ANXA3, CLEC4D, TNFAIP6, LMNB1, PRRG4, VNN1 and IL2RB) that are differentially expressed in CRC patients as compared with controls. Blood samples from 210 patients (99 CRC and 111 controls) were collected, and total blood RNA was isolated and subjected to quantitative RT-PCR and data analysis.
RESULTS: The logistic regression analysis of seven-gene panel has an area under the curve (AUC) of 0.76 (95% confidence interval: 0.70 to 0.82), 77% specificity, 61% sensitivity and 70% accuracy, comparable to the data obtained from the North American investigation of the same biomarker panel.
CONCLUSIONS: Our results independently confirm the results of the study conducted in North America and demonstrate the ability of the seven biomarker panel to discriminate CRC from controls in blood samples drawn from a Malaysian population.
Fulltext Whole blood transcriptome correlates with treatment response in nasopharyngeal carcinoma

Zaatar AM, Lim CR, Bong CW, Lee MM, Ooi JJ, Suria D, et al.

J Exp Clin Cancer Res, 2012 Sep 17;31:76.
PMID: 22986368 DOI: 10.1186/1756-9966-31-76

BACKGROUND: Treatment protocols for nasopharyngeal carcinoma (NPC) developed in the past decade have significantly improved patient survival. In most NPC patients, however, the disease is diagnosed at late stages, and for some patients treatment response is less than optimal. This investigation has two aims: to identify a blood-based gene-expression signature that differentiates NPC from other medical conditions and from controls and to identify a biomarker signature that correlates with NPC treatment response.
METHODS: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment.
RESULTS: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.
CONCLUSION: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.
Blood-based dynamic genomic signature for obsessive-compulsive disorder

Wang Y, Cheng C, Zhang Z, Wang J, Wang Y, Li X, et al.

Am J Med Genet B Neuropsychiatr Genet, 2018 12;177(8):709-716.
PMID: 30350918 DOI: 10.1002/ajmg.b.32675

No biologically based diagnostic criteria are in clinical use today for obsessive-compulsive disorder (OCD), schizophrenia, and major depressive disorder (MDD), which are defined with reference to Diagnostic and Statistical Manual clinical symptoms alone. However, these disorders cannot always be well distinguished on clinical grounds and may also be comorbid. A biological blood-based dynamic genomic signature that can differentiate among OCD, MDD, and schizophrenia would therefore be of great utility. This study enrolled 77 patients with OCD, 67 controls with no psychiatric illness, 39 patients with MDD, and 40 with schizophrenia. An OCD-specific gene signature was identified using blood gene expression analysis to construct a predictive model of OCD that can differentiate this disorder from healthy controls, MDD, and schizophrenia using a logistic regression algorithm. To verify that the genes selected were not derived as a result of chance, the algorithm was tested twice. First, the algorithm was used to predict the cohort with true disease/control status and second, the algorithm predicted the cohort with disease/control status randomly reassigned (null set). A six-gene panel (COPS7A, FKBP1A, FIBP, TP73-AS1, SDF4, and GOLGA8A) discriminated patients with OCD from healthy controls, MDD, and schizophrenia in the training set (with an area under the receiver-operating-characteristic curve of 0.938; accuracy, 86%; sensitivity, 88%; and specificity, 85%). Our findings indicate that a blood transcriptomic signature can distinguish OCD from healthy controls, MDD, and schizophrenia. This finding further confirms the feasibility of using dynamic blood-based genomic signatures in psychiatric disorders and may provide a useful tool for clinical staff engaged in OCD diagnosis and decision making.
Fulltext Blood-based biomarkers of aggressive prostate cancer

Liong ML, Lim CR, Yang H, Chao S, Bong CW, Leong WS, et al.

PLoS One, 2012;7(9):e45802.
PMID: 23071848 DOI: 10.1371/journal.pone.0045802

Prostate cancer is a bimodal disease with aggressive and indolent forms. Current prostate-specific-antigen testing and digital rectal examination screening provide ambiguous results leading to both under-and over-treatment. Accurate, consistent diagnosis is crucial to risk-stratify patients and facilitate clinical decision making as to treatment versus active surveillance. Diagnosis is currently achieved by needle biopsy, a painful procedure. Thus, there is a clinical need for a minimally-invasive test to determine prostate cancer aggressiveness. A blood sample to predict Gleason score, which is known to reflect aggressiveness of the cancer, could serve as such a test.
Blood gene signature for early hepatocellular carcinoma detection in patients with chronic hepatitis B

Omar H, Lim CR, Chao S, Lee MM, Bong CW, Ooi EJ, et al.

J Clin Gastroenterol, 2015 Feb;49(2):150-7.
PMID: 25569223 DOI: 10.1097/MCG.0000000000000112

Up to 25% of chronic hepatitis B (CHB) patients eventually develop hepatocellular carcinoma (HCC), a disease with poor prognosis unless detected early. This study identifies a blood-based RNA biomarker panel for early HCC detection in CHB.