Biomarker detection in urinary proteome of prostate cancer by nanoflow LC-MS/MS

INTRODUCTION: Urinary proteomics provides a wealth of information in the identification of protein markers associated with various diseases such as in carcinoma. With the increasing incidence of prostate cancer and the lack of sensitivity and specificity of prostate specific antigen, the simultaneous identification of an alternative protein biomarker through urinary proteomics is encouraging. Urine, which has similar proteins with serum, makes it an ideal alternative biofluid wherein the collection is easy and non-invasive.METHODS: Urinary proteins were separated by gradient SDS-PAGE followed by in-gel digestion and organic/buffer peptide extraction. The protein biomarkers in prostate cancer patients and control subjects were identified via LC-MS/MS and submitted to Protein Prospector where the peptide fragmentation of sequence was analyzed and compared with the SwissProt database.RESULTS: A panel of three protein biomarkers for the early detection of prostate cancer were identified: transthyretin, hemoglobin subunit alpha and hemoglobin sububit beta. The presence of these three biomarkers is associated with high Gleason scores and TNM stages but not with PSA level. Uromodulin and mannan binding lectin serine protease cancer from BPH. The study also revealed the divergence of the urinary proteome of the cancer patients from the urinary proteome of the control with BPH suggesting the fundamental differences in benign and malignant growth of the prostate epithelial cells. Another highlight of the study was the identification of oxidation of pro63 of transthyretin in patient 3. The proposed role of the post translational modification in pro63 of transthyretinin in the mechanism of prostate carcinogenesis remains to be defined and warrants further study.CONCLUSION: Our study was able to establish the homology of urine proteome among the controls and its divergence from the patients afflicted with prostate cancer by simultaneously comparing their urine proteomes leading to the identification of a distinct panel of biomarkers, namely, transthyretin, hemoglobin subunit alpha and hemoglobin subunit beta. Uromodulin and mannan binding lectin serine protease 2 are the additional biomarkers that can distinguish prostate cancer from BPH. Due to limitations in the number of controls and patients, only preliminary findings and their significance were shown. These findings need to be confirmed in future investigations using larger sample size for both the controls and the patients.

Association of cholesteryl ester transfer protein (CETP) Taq1B polymorphism with response to simvastatin treatment in hypercholesterolemic Filipino patients

Although statins reduced cardiovascular mortality, these drugs did not prevent myocardial infarction in some patients. Previous studies showed that genetic variation in cholesteryl ester transfer protein (CETP) gene was linked to this response. The identified gene is characterized by two different variants: B1 and B2 alleles identified by the presence and absence, respectively, of a restriction site for the enzyme Taq1 in intron 1. The present study identified the variation in Taq1B of the gene using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) in 130 patients. An association study of Taq1B with the response of 24 middle-aged dyslipidemic patients to simvastatin treatment for 8 weeks was also done. The overall allele frequencies of B1 and B2 alleles were 0.548 and 0.462, respectively. The genotype frequencies were in Hardy-Weinberg equilibrium. The distinguishing feature of individuals with B1B1 genotype when treated with simvastatin was their rapid increase in high density lipoprotein (HDL) observed after 2 weeks which continued till the 8th week treatment. The expected HDL elevation among individuals with B1B2 genotype was observed only after the 8th week simvastatin treatment.

Allelic frequencies of single nucleotide polymorphisms (SNPs) in the N-acetyltransferase 2 (NAT2) gene of Filipinos

OBJECTIVES:The present study aims to determine the frequency of occurrence of NAT2*4, NAT2*5A, NAT2*6B, NAT2*7A and NAT2*14A alleles by PCR-RFLP among Filipino volunteers. These alleles correspond to substitutions in the following sites: C341T, G590A, G857A and G191A, respectively, of the NAT2 gene. The presence of specific SNP combination was also used to deduce acetylation status and estimate genotype frequency and describe them in comparison with other populations based on literature. METHODS: Genomic DNA from peripheral blood lymphocytes from 129 healthy Filipino volunteers was used to amplify the NAT2 gene segment. The RFLP analysis was done by restricting the expected PCR product with Kpn1, Taq1, BamH1 and Msp1/Al1, respectively, to detect the 4 alleles: NAT2*4, NAT2*5A, NAT2*6B, NAT2*7A and NAT2*14A. RESULTS:The calculated allelic frequencies in Hardy-Weinberg equilibrium of NAT2*5A (C481T), NAT2*6B (G590A), NAT2*7A (G857A) and NAT2*14A (G191A) were 0.058, 0.097, 0.182 and 0.046, respectively. NAT2*4 had an allele frequency of 0.617. Nine genotypes were determined: NAT2*4/*4, NAT2*4/*5A, NAT2*4/*6B, NAT2*4/*7A, NAT2*4/*14A, NAT2*5A/*7A, NAT2*6B/*7A, NAT2*6B/*14A and NAT2*7A/*14A. From these genotypes, acetylator phenotypes were deduced. A trimodal pattern of distribution was established: rapid, intermediate and slow acetylators with the following percentages, 47.3%, 41.1 % and 11.6%. Among the slow acetylator SNPs determined, NAT2*7A was found as the most frequent allele and NAT2*14A was found as the least frequent allele. CONCLUSION:The study showed the mutation profile and observed genotypic similarities and differences of Filipinos with other Asian populations and Americans and other Caucasians based on literature. The results also suggest a trimodal pattern of distribution of acetylators and lesser number of slow acetylators among Filipino populations, a characteristic similar to other Asian populations but significantly different from Americans and other Caucasians. The occurrence of NAT2*7A and NAT2*14A can be further sequenced to verify the observed genotype.