Using high-throughput SNP technologies to study cancer

Increased hsa-miR-100-5p Expression Improves Hepatocellular Carcinoma Prognosis in the Asian Population with PLK1 Variant rs27770A>G

Hepatocellular carcinoma (HCC) has the highest incidence and mortality in the Asian population, and race is an independent risk factor affecting survival time in liver cancer. Micro RNAs (miRNAs) are remarkably dysregulated in HCC and closely associated with HCC prognosis. Recent studies show that genetic variability between ethnic groups may result in differences in the specificity of HCC miRNA biomarkers. Here, we reveal a high expression level of hsa-miR-100-5p, an HCC prognosis-related miRNA, which improves HCC prognosis in the Asian Population with Polo-like kinase 1 (PLK1) variant rs27770A>G. In this study, we discovered that hsa-miR-100-5p was downregulated in various HCC cell lines. While mimics transient transfection and mouse liver cancer model confirmed the interaction between hsa-miR-100-5p and PLK1, a stratified analysis based on the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) data suggest both low hsa-miR-100-5p expression level and high PLK1 expression level associated with poor HCC prognosis, especially in the Asian population. According to the 1000 Genomes Project database, the SNP rs27770 located in 3'UTR of PLK1 had a significantly higher G allele frequency in the East Asian population. Bioinformatics analysis suggested that rs27770 A>G affects PLK1 mRNA secondary structure and alters the hsa-miR-100-5p/PLK1 interaction by forming an additional seedless binding site. This racial variation caused PLK1 to be more vulnerable to hsa-miR-100-5p inhibition, resulting in hsa-miR-100-5p being more favorable for HCC prognosis in the Asian population.

High-Fidelity Identification of Single Nucleotide Polymorphism by Type V CRISPR Systems

Accurate and sensitive detection of single nucleotide polymorphism (SNP) holds significant clinical implications, especially in the field of cancer diagnosis. Leveraging its high accuracy and programmability, the CRISPR system emerges as a promising platform for advancing the identification of SNPs. In this study, we compared two type V CRISPR/Cas systems (Cas12a and Cas14a) for the identification of cancer-related SNP. Their identification performances were evaluated by characterizing their mismatch tolerance to the BRAF gene. We found that the CRISPR/Cas14a system exhibited superior accuracy and robustness over the CRISPR/Cas12a system for SNP detection. Furthermore, blocker displacement amplification (BDA) was combined with the CRISPR/Cas14a system to eliminate the interference of the wild type (WT) and increase the detection accuracy. In this strategy, we were able to detect BRAF V600E as low as 103 copies with a sensitivity of 0.1% variant allele frequency. Moreover, the BDA-assisted CRISPR/Cas14a system has been applied to identify the BRAF mutation from human colorectal carcinoma cells, achieving a high sensitivity of 0.5% variant allele frequency, which is comparable to or even superior to those of most commercially available products. This work has broadened the scope of the CRISPR system and provided a promising method for precision medicine.

Associations between non-coding RNAs genetic polymorphisms with ovarian cancer risk: A systematic review and meta-analysis update with trial sequential analysis

BACKGROUND

This systemic review and meta-analysis seeks to systematically analyze and summarize the association between non-coding RNA polymorphisms and ovarian cancer risk.

METHODS

We searched PubMed, Web of Science and CNKI for available articles on non-coding RNA polymorphisms in patients with ovarian cancer from inception to March 1, 2023. The quality of each study included in the meta-analysis was rated according to the Newcastle-Ottawa Scale.Odds ratios (ORs) with their 95% confidence intervals (95% CI) were used to assess associations. Chi-square Q-test combined with inconsistency index (I2) was used to test for heterogeneity among studies. Lastly, trial sequential analysis (TSA) software was used to verify the reliability of meta-analysis results, and in-silico miRNA expression were also performed. The meta-analysis was registered with PROSPERO (No. CRD42023422091).

RESULTS

A total of 17 case-control studies with 18 SNPs were selected, including 2 studies with H19 rs2107425 and HOTAIR rs4759314, and 5 studies with miR-146a rs2910164 and miR-196a rs11614913. Significant associations were found between H19 rs2107425, miR-146a rs2910164, and miR-196a rs11614913 and ovarian cancer risk. Three genetic models of H19 rs2107425 (CT vs TT (heterozygote model): OR = 1.36, 95% CI = 1.22-1.52, P < .00001; CC + CT vs TT (dominant model): OR = 1.12, 95% CI = 1.02-1.24, P = .02; and CC vs CT + TT (recessive model): OR = 1.23, 95% CI = 1.16-1.31, P < .00001), 2 genetic models of miR-146a rs2910164 (allele model: OR = 1.75, 95% CI = 1.05-2.91, P = .03; and heterozygote model: OR = 0.33, 95% CI = 0.11-0.98, P = .05), 3 genetic models of miR-196a rs11614913 (allele model: OR = 0.70, 95% CI = 0.59-0.82, P < .0001; dominant model: OR = 1.62, 95% CI = 1.18-2.24, P = .0001; and recessive model: OR = 0.70, 95% CI = 0.57-0.87, P = .03) were statistically linked to ovarian cancer risk. Subgroup analysis for miR-146a rs2910164 was performed according to ethnicity. No association was found in any genetic model. The outcomes of TSA also validated the findings of this meta-analysis.

CONCLUSION

This study summarizes that H19 rs2107425, miR-146a rs2910164, and miR-196a rs11614913 polymorphisms are significantly linked with the risk of ovarian cancer, and moreover, large-scale and well-designed studies are needed to validate our result.

Chemical Sensors using Single-Molecule Electrical Measurements

Driven by the digitization and informatization of contemporary society, electrical sensors are developing toward minimal structure, intelligent function, and high detection resolution. Single-molecule electrical measurement techniques have been proven to be capable of label-free molecular recognition and detection, which opens a new strategy for the design of efficient single-molecule detection sensors. In this review, we outline the main advances and potentials of single-molecule electronics for qualitative identification and recognition assays at the single-molecule level. Strategies for single-molecule electro-sensing and its main applications are reviewed, mainly in the detection of ions, small molecules, oligomers, genetic materials, and proteins. This review summarizes the remaining challenges in the current development of single-molecule electrical sensing and presents some potential perspectives for this field.

Identification of single nucleotide polymorphisms by a peptide nucleic acid-based sandwich hybridization assay coupled with toehold-mediated strand displacement reactions

In this work, we developed a simple and accurate peptide nucleic acid (PNA)-based sandwich hybridization assay for single nucleotide polymorphisms (SNPs) in the p53 gene. Our approach combines the enzyme-free toehold-mediated strand displacement reaction (SDR) with real-time enzyme-linked immunosorbent assay (ELISA) to detect SNPs with high sensitivity and specificity. A PNA-DNA heteroduplex with an external toehold is designed and fixed on well surface of a 96-well plate. The strand displacement from PNA-DNA heteroduplexes is initiated by the hybridization of target sequence with the toehold domain and ends with the fully displacing of the incumbent DNA. Finally, the as formed PNA-target DNA duplex with overhang at its 5'-end hybridizes with a biotin-labeled reporter PNA to form a sandwich structure on surface for signal amplification. The proposed PNA-based sandwich biosensor displays high sensitivity and greatly enhanced discriminability to target p53 gene segments against single-base mutant sequences compared to its all-DNA counterpart. Furthermore, the probe design is elegantly simple and the sensing procedure is easy to operate. We believe that this strategy may provide a simple and universal strategy for SNPs detection through easily altering the sequences of probes according to the sequences around target SNPs.

Cytokine-polymorphisms associated with Preeclampsia: A review

BACKGROUND

Preeclampsia (PE) is a syndromic disorder that affects 2% to 8% of pregnancies and is diagnosed principally when hypertension appears in the second-d half of pregnancy. WHO estimates the incidence of PE to be seven times higher in developing countries than in developed countries. Severe preeclampsia/eclampsia is one of the most important causes of maternal mortality, associated with 50,000 to 100,000 annual deaths globally as well as serious fetal and neonatal morbidity and mortality, especially in developing countries. Even though evidence from family-based studies suggest PE has a heritable component, its etiology, and specific genetic contributions remain unclear. Many studies examining the genetic factors contributing to PE have been conducted, most of them are focused on single nucleotide polymorphisms (SNPs). Given that PE has a very important inflammatory component, is mandatory to examine cytokine-SNPs for elucidating all mechanisms involved in this pathology. In this review, we describe the most important cytokine-polymorphisms associated with the onset and development of PE. We aim to provide current and relevant evidence in this regard.

METHODS

We searched English databases such as PubMed and the National Center for Biotechnology Information. The publication time of the papers was set from the establishment of the databases to February 2022. All studies about Th1/Th2/Th17 cytokines polymorphisms were included in our study.

RESULTS

SNPs in IFN-γ, TNF-α, IL-4, IL-6, IL-10, IL-17A, and IL-22 are associated with the development, early-onset and severity of PE, being the Th1/Th2/Th17 responses affected by the presence of these SNPs.

CONCLUSIONS

The changes in Th1/Th2/Th17 response modify processes such as placentation, control of inflammation, and vascular function. Nonetheless, association studies have shown different results depending on sample size, diagnostic, and population.

Association between long non‑coding RNA HOTAIR polymorphism and lung cancer risk: A systematic review and meta‑analysis

Single nucleotide polymorphism (SNP) of long noncoding RNA (lnc)RNA has been reported to be an important factor in cancer development. Recently, lncRNA homeobox transcript antisense intergenic RNA (HOTAIR) was indicated to induce tumorigenesis of several cancer types, but the association between the SNP of lncRNA HOTAIR and lung cancer susceptibility has remained undetermined. The present meta-analysis aimed to investigate the effect of HOTAIR polymorphism on susceptibility to lung cancer. The PubMed, Ovid Medline, Embase and Cochrane Library databases were thoroughly searched. Studies containing data on the incidence of lung cancer in patients with different HOTAIR SNPs were included. The Hardy-Weinberg equilibrium was analyzed to determine genotype distribution and allele frequencies. The odds ratio (OR) was pooled to evaluate the association of different SNPs with the susceptibility to lung cancer. A total of six studies comprising 1,715 patients with lung cancer and 2,745 healthy controls were finally included. A total of 4 SNPs (rs12826786, rs1899663, rs920778 and rs4759314) were reported. Analyses for all of these SNPs individually indicated that the lncRNA HOTAIR rs1899663 C>A polymorphism was a risk factor for lung cancer (dominant mode, AA+CA vs. CC: OR=0.816, 95% CI=0.707-0.942, P=0.005). The present study was the first meta-analysis investigating the association between lncRNA HOTAIR and lung cancer susceptibility. The results indicated that the lncRNA HOTAIR rs1899663 C>A polymorphism is a risk factor for lung cancer. LncRNA HOTAIR may be of value in lung cancer screening, particularly for populations with high-risk factors, as well as prognosis prediction. Future investigations are required to further clarify the intrinsic mechanism of the role of HOTAIR in the oncogenesis of lung cancer.

PLCE1 Polymorphisms Are Associated With Gastric Cancer Risk: The Changes in Protein Spatial Structure May Play a Potential Role

Background

Gastric cancer (GC) is one of the most significant health problems worldwide. Some studies have reported associations between Phospholipase C epsilon 1 (PLCE1) single-nucleotide polymorphisms (SNPs) and GC susceptibility, but its relationship with GC prognosis lacked exploration, and the specific mechanisms were not elaborated fully yet. This study aimed to further explore the possible mechanism of the association between PLCE1 polymorphisms and GC.

Materials and Methods

A case-control study, including 588 GC patients and 703 healthy controls among the Chinese Han population, was performed to investigate the association between SNPs of PLCE1 and GC risk by logistic regression in multiple genetic models. The prognostic value of PLCE1 in GC was evaluated by the Kaplan-Meier plotter. To explored the potential functions of PLCE1, various bioinformatics analyses were conducted. Furthermore, we also constructed the spatial structure of PLCE1 protein using the homology modeling method to analyze its mutations.

Results

Rs3765524 C > T, rs2274223 A > G and rs3781264 T > C in PLCE1 were associated with the increased risk of GC. The overall survival and progression-free survival of patients with high expression of PLCE1 were significantly lower than those with low expression [HR (95% CI) = 1.38 (1.1–1.63), P < 0.01; HR (95% CI) = 1.4 (1.07–1.84), P = 0.01]. Bioinformatic analysis revealed that PLCE1 was associated with protein phosphorylation and played a crucial role in the calcium signal pathway. Two important functional domains, catalytic binding pocket and calcium ion binding pocket, were found by homology modeling of PLCE1 protein; rs3765524 polymorphism could change the efficiency of the former, and rs2274223 polymorphism affected the activity of the latter, which may together play a potentially significant role in the tumorigenesis and prognosis of GC.

Conclusion

Patients with high expression of PLCE1 had a poor prognosis in GC, and SNPs in PLCE1 were associated with GC risk, which might be related to the changes in spatial structure of the protein, especially the variation of the efficiency of PLCE1 in the calcium signal pathway.

PLCE1 Polymorphisms and Risk of Esophageal and Gastric Cancer in a Northwestern Chinese Population

The reported risk susceptibility between phospholipase C epsilon 1 (PLCE1) polymorphisms and esophageal cancer (EC) and gastric cancer (GC) remained inconsistent and controversial, especially on variants other than rs2274223. The relationship between PLCE1 polymorphisms and gene expression is also unclear. Here we conducted a case-control study from northwest China, genotyped seven tag single nucleotide polymorphisms (SNPs) in PLCE1 with multiplexed SNP MassARRAY assay. Stratified analysis was carried out and PLCE1 expression was evaluated in specified groups with the method of qRT-PCR and immunohistochemistry. Results showed that the minor alleles of rs3765524, rs2274223, and rs10509670 were associated with increased risk of EC and GC. Linkage disequilibrium analysis revealed protective haplotypes of CCAAGTC and CCAA. By stratification, a more significant association was found in subgroups of male, age ≥ 54, tumor stages of I-II and tumor size ≤ 5 cm, EC and cardia cancer (CC) of stomach, and moderate to well differentiated squamous carcinoma. In addition, a significant association for rs3765524 with noncardia cancer (NCC) and adenocarcinoma which is predominant in China was also observed. Further expression analysis identified that PLCE1 was downregulated in NCC tissues comparing to their adjacent noncancerous tissues, and its protein expression was higher in genotype rs3765524 CT/TT than in rs3765524 CC. In summary, our study suggests that PLCE1 polymorphisms may affect its gene expression and are associated with not only EC and CC, but also, to some extent, NCC risk in this study population.

Label/quencher-free detection of single-nucleotide changes in DNA using isothermal amplification and G-quadruplexes

We report an analytical method that exploits the interaction between G-quadruplexes and thioflavin T (ThT), for detecting mutant DNA species containing single-base changes. This system is a label/quencher-free fluorescence enhancement system based on rolling circle amplification (RCA)-responsive G-quadruplex formation, which enables a highly selective detection of T790M SNPs in the gene encoding the epidermal growth factor receptor, EGFR.

Specific Gene Capture Combined with Restriction-Fragment Release for Directly Fluorescent Genotyping of Single-Nucleotide Polymorphisms in Diagnosing Spinal Muscular Atrophy

In this study, a fast and simple fluorescent genotyping strategy, streptavidin magnetic beads combined with biotin-coupled PCR and restriction-fragment release, was developed for determination of nucleotide variants. This method was further applied for analyzing SMN1 gene in diagnosis of spinal muscular atrophy (SMA). After biotin-coupled PCR, the streptavidin magnetic beads would capture the biotin-labeled SMN genetic fragments, and then the restriction enzyme of HPY188I could only digest and release the fluorescent end of SMN1 genetic fragment into the supernatant. Therefore, the SMN1 gene could be easily fluorescently quantified, and SMN2 would not, for diagnosis of SMA. The copy number of the SMN1 gene could be regressed using the relative fluorescent unit versus the known copy number, and the coefficient of correlation is equal to 0.9617 ( r = 0.9617). In this research, a total of 16 blind DNA samples were analyzed, including 6 wild types, 5 carriers, and 5 SMA patients. Importantly, this fast, simple, and highly efficient method is universal for detection of all nucleotides variants by replacing the specific restriction enzyme. This technique has the potency to be served as a tool for fast and accurate diagnosis of genotypes in clinical medicine.

Hyperbranched rolling circle amplification (HRCA)-based fluorescence biosensor for ultrasensitive and specific detection of single-nucleotide polymorphism genotyping associated with the therapy of chronic hepatitis B virus infection

Detection of specific genes related to drug action can provide scientific guidance for personalized medicine. Taking the detection of a single-nucleotide polymorphism (SNP) genotyping related to the chronic hepatitis B virus (HBV) therapy as an example, a novel biosensor with high sensitivity and selectivity was developed based on the hyperbranched rolling circle amplification (HRCA) in this work. The single-base mutant DNA (mutDNA) sequence can perfectly hybridize with the specially designed discrimination padlock probe and initiate the HRCA reaction. Subsequently, a great abundant of double-strand DNA sequences were released and a strong fluorescence signal can be detected after adding SYBR Green I. In particular, the enhanced fluorescence intensity exhibits a linear relationship with the logarithm of mutDNA concentration ranging from 0.1 nM to 40 nM with a low detection limit of 0.05 nM. However, when there was even a single base mismatch in the target DNA, the HRCA was suppressed and fluorescence response process could not occur, resulting in a high selectivity of this biosensor. Moreover, this detection strategy also performs well in human serums, demonstrating its potential application in detecting SNPs in real biological samples.

Mutational Analysis of Oncogenic AKT1 Gene Associated with Breast Cancer Risk in the High Altitude Ecuadorian Mestizo Population

Breast cancer is the leading cause of cancer-related death among women worldwide. AKT1 encodes the kinase B alpha protein. The rs121434592, rs12881616, rs11555432, rs11555431, rs2494732, and rs3803304 single nucleotide polymorphisms have been identified in the AKT1 kinase gene. Activated AKT1 phosphorylates downstream substrates regulating cell growth, metabolism, apoptosis, angiogenesis, and drug responses. It is essential to know how breast cancer risk is associated with histopathological and immunohistochemical characteristics and genotype polymorphisms in a high altitude Ecuadorian mestizo population. This is a retrospective case-control study. DNA was extracted from 185 healthy and 91 affected women who live 2,800 meters above sea level. Genotypes were determined by genomic sequencing. We found a possible association between the noncoding intronic variant rs3803304 and breast cancer risk development: GG (odds ratio [OR] = 5.2; 95% confidence interval [CI] = 1.3-20.9; P ≤ 0.05; Q > 0.05). Regarding pathologic characteristics, we found significant risk between estrogen receptor, progesterone receptor, and HER2 status and molecular subtypes (P ≤ 0.001; Q ≤ 0.05). On the other hand, we did not find risk between variants and histopathological characteristics. Despite the small sample size, we found that the intronic variant, AKT1 rs3803304, may act as a predictive biomarker in the risk of developing breast cancer in the high altitude Ecuadorian mestizo population.

DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine

In the era of personalized medicine, high-throughput technologies have allowed the investigation of genetic variations underlying the inter-individual variability in drug pharmacokinetics/pharmacodynamics. Several studies have recently moved from a candidate gene-based pharmacogenetic approach to genome-wide pharmacogenomic analyses to identify biomarkers for selection of patient-tailored therapies. In this aim, the identification of genetic variants affecting the individual drug metabolism is relevant for the definition of more active and less toxic treatments. This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.

Integrated analysis of SNP, CNV and gene expression data in genetic association studies

Integrative approaches that combine multiple forms of data can more accurately capture pathway associations and so provide a comprehensive understanding of the molecular mechanisms that cause complex diseases. Association analyses based on single nucleotide polymorphism (SNP) genotypes, copy number variant (CNV) genotypes, and gene expression profiles are the 3 most common paradigms used for gene set/pathway enrichment analyses. Many work has been done to leverage information from 2 types of data from these 3 paradigms. However, to the best of our knowledge, there is no work done before to integrate the 3 paradigms all together. In this article, we present an integrated analysis that combine SNP, CNV, and gene expression data to generate a single gene list. We present different methods to compare this gene list with the other 3 possible lists that result from the combinations of the following pairs of data: SNP genotype with gene expression, CNV genotype with gene expression, and SNP genotype with CNV genotype. The comparison is done using 3 different cancer datasets and 2 different methods of comparison. Our results show that integrating SNP, CNV, and gene expression data give better association results than integrating any pair of 3 data.

Single Nucleotide Polymorphism Genotyping in Single-Molecule Electronic Circuits

Establishing low-cost, high-throughput, simple, and accurate single nucleotide polymorphism (SNP) genotyping techniques is beneficial for understanding the intrinsic relationship between individual genetic variations and their biological functions on a genomic scale. Here, a straightforward and reliable single-molecule approach is demonstrated for precise SNP authentication by directly measuring the fluctuations in electrical signals in an electronic circuit, which is fabricated from a high-gain field-effect silicon nanowire decorated with a single hairpin DNA, in the presence of different target DNAs. By simply comparing the proportion difference of a probe-target duplex structure throughout the process, this study implements allele-specific and accurate SNP detection. These results are supported by the statistical analyses of different dynamic parameters such as the mean lifetime and the unwinding probability of the duplex conformation. In comparison with conventional polymerase chain reaction and optical methods, this convenient and label-free method is complementary to existing optical methods and also shows several advantages, such as simple operation and no requirement for fluorescent labeling, thus promising a futuristic route toward the next-generation genotyping technique.

Breast Cancer Risk Associated with Genotype Polymorphisms of the Aurora Kinase a Gene (AURKA): a Case-Control Study in a High Altitude Ecuadorian Mestizo Population

Breast cancer (BC) is the leading cause of cancer related death among women in 2014. The AURKA gene that encodes the protein called Aurora kinase A plays an important role in the progression of the cell cycle, by controlling and promoting the entry into the phase of mitosis. The single nucleotide polymorphism AURKA T91A (rs2273535) (Phe21Ile) has been identified as functional alternator of this kinase, the Ile allele is associated with the occurrence of chromosome segregation errors and tumor progression. Therefore, it is essential to know how BC risk is associated with histopathological characteristics, immunohistochemical characteristics, and genotype polymorphism in a high altitude Ecuadorian mestizo population. In this retrospective case-control study 200 individuals were analyzed. DNA was extracted from 100 healthy and 100 affected women. Genotypes were determined by genomic sequencing. We found significant association between the AURKA T91A (rs2273535) (Phe21Ile) genotype and an increased risk of BC development: Phe/Ile (odds ratio [OR] = 2.6; 95% confidence interval [CI] = 1.4-4.9; P = 0.004), Ile/Ile (OR = 3.8; 95% CI = 1.6-9.0; P = 0.002), and Phe/Ile + Ile/Ile (OR = 2.9; 95% CI = 1.6-5.2; P = 0.001). Additionally, the rs2273535 variant was associated with the tumor grade SBR III (OR = 9.6; 95% CI = 1.0-91.9; P = 0.048) and the Ki-67 ≥ 20 (OR = 16.5; 95% CI = 2.7-101.3; P = 0.002). In brief, this study provides the first evidence where the Ile allele of the AURKA gene could act as potentially predictive biomarker of BC in the high altitude Ecuadorian mestizo population that lives at 2800 m above sea level (masl).

Genetic Association of Hematopoietic Stem Cell Transplantation Outcome beyond Histocompatibility Genes

The outcome of hematopoietic stem cell transplantation (HSCT) is controlled by genetic factors among which the leukocyte antigen human leukocyte antigen (HLA) matching is most important. In addition, minor histocompatibility antigens and non-HLA gene polymorphisms in genes controlling immune responses are known to contribute to the risks associated with HSCT. Besides single-nucleotide polymorphisms (SNPs) in protein coding genes, SNPs in regulatory elements such as microRNAs (miRNAs) contribute to these genetic risks. However, genetic risks require for their realization the expression of the respective gene or miRNA. Thus, gene and miRNA expression studies may help to identify genes and SNPs that indeed affect the outcome of HSCT. In this review, we summarize gene expression profiling studies that were performed in recent years in both patients and animal models to identify genes regulated during HSCT. We discuss SNP–mRNA–miRNA regulatory networks and their contribution to the risks associated with HSCT in specific examples, including forkheadbox protein 3 and regulatory T cells, the role of the miR-155 and miR-146a regulatory network for graft-versus-host disease, and the function of MICA and its receptor NKG2D for the outcome of HSCT. These examples demonstrate how SNPs affect expression or function of proteins that modulate the alloimmune response and influence the outcome of HSCT. Specific miRNAs targeting these genes and directly affecting expression of mRNAs are identified. It might be valuable in the future to determine SNPs and to analyze miRNA and mRNA expression in parallel in cohorts of HSCT patients to further elucidate genetic risks of HSCT.

MDM2 promoter del1518 polymorphism and cancer risk: evidence from 22,931 subjects

Studies have shown that single-nucleotide polymorphisms in MDM2 gene may play important roles in the development of malignant tumor. The association of del1518 polymorphism (rs3730485) in the MDM2 promoter with cancer susceptibility has been extensively studied; however, the results are contradictory. To quantify the association between this polymorphism and overall cancer risk, we conducted a meta-analysis with 12,905 cases and 10,026 controls from 16 eligible studies retrieved from PubMed, Embase, and Chinese Biomedical (CBM) databases. We assessed the strength of the connection using odds ratios (ORs) and 95% confidence intervals (CIs). In summary, no significant associations were discovered between the del1518 polymorphism and overall cancer risk (Del/Del vs Ins/Ins: OR =1.01, 95% CI =0.90-1.14; Ins/Del vs Ins/Ins: OR =1.03, 95% CI =0.96-1.12; recessive model: OR =0.98, 95% CI =0.90-1.07; dominant model: OR =1.03, 95% CI =0.94-1.12; and Del vs Ins: OR =1.01, 95% CI =0.94-1.07). In the stratified analysis by source of control, quality score, cancer type, and ethnicity, no significant associations were found. Despite some limitations, the current meta-analysis provides solid statistical evidence of lacking association between the MDM2 del1518 polymorphism and cancer risk.

Associations between three polymorphisms in the interleukin-4 receptor gene and risk of cancer: a meta-analysis

Interleukin-4 receptor (IL-4R) gene single nucleotide polymorphisms (SNPs) are implicated in cancer development. However, results from the published reports have remained inconclusive. The objective of this study was to conduct a meta-analysis investigating the association between polymorphisms in IL-4R gene and cancer risk. Pubmed, EMBASE and China National Knowledge Infrastructure (CNKI) were searched for case- control studies published up to October 30, 2012 that investigated IL-4R polymorphisms and cancer risk. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the strength of any associations. Three IL-4R polymorphisms (Q576R, rs1801275; I75V, rs1805010; S503P, rs1805015) in 21 case-control studies were analyzed. Our meta-analysis indicated that these three polymorphisms are not associated with cancer risk when all studies were pooled together. In the subgroup analysis by tumor site, the results showed that Q576R G allele carriers were associated with a significantly decreased cervical cancer risk (recessive model: OR = 0.77, 95%CI = 0.60-0.98; homozygote comparison: OR = 0.76, 95%CI = 0.58-0.98). I75V G allele carriers were associated with a decreased risk of renal cancer (dominant model = 0.71, 95%CI = 0.57-0.89, heterozygote comparison: OR = 0.69, 95%CI = 0.55-0.87). When stratified by ethnicity, Q576R G allele carriers were associated with a decreased cancer risk in Caucasians (dominant model: OR = 0.90, 95%CI = 0.83-0.98; heterozygote comparison: OR = 0.89, 95%CI = 0.82-0.98). I75V G allele carriers were associated with a decreased cancer risk in Asians (heterozygote comparison: OR = 0.76, 95%CI = 0.62-0.94). S503P C allele carriers were also associated with a decreased cancer risk in Asians (CC VS TT: OR = 0.29, 95%CI = 0.08-0.99). Our results suggest that Q576R, I75V and S503P may be associated with a decreased cancer risk for certain types of cancers and in some specific ethnic groups. Future case-control studies with large sample size are needed to evaluate these associations in detail.

A turn-on dual emissive nucleobase sensitive to mismatches and duplex conformational changes

Herein, we demonstrate the on–off dual emissive behaviour of a fluorescent nucleoside sensitive towards DNA hybridization and conformational changes as well as detection of single nucleotide polymorphisms.

A Novel Teaching-Learning-Based Optimization for Improved Mutagenic Primer Design in Mismatch PCR-RFLP SNP Genotyping

Many single nucleotide polymorphisms (SNPs) for complex genetic diseases are genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in small-scale basic research studies. It is an essential work to design feasible PCR-RFLP primer pair and find out available restriction enzymes to recognize the target SNP for PCR experiments. However, many SNPs are incapable of performing PCR-RFLP makes SNP genotyping become unpractical. A genetic algorithm (GA) had been proposed for designing mutagenic primer and get available restriction enzymes, but it gives an unrefined solution in mutagenic primers. In order to improve the mutagenic primer design, we propose TLBOMPD (TLBO-based Mutagenic Primer Design) a novel computational intelligence-based method that uses the notion of "teaching and learning" to search for more feasible mutagenic primers and provide the latest available restriction enzymes. The original Wallace's formula for the calculation of melting temperature is maintained, and more accurate calculation formulas of GC-based melting temperature and thermodynamic melting temperature are introduced into the proposed method. Mutagenic matrix is also reserved to increase the efficiency of judging a hypothetical mutagenic primer if involve available restriction enzymes for recognizing the target SNP. Furthermore, the core of SNP-RFLPing version 2 is used to enhance the mining work for restriction enzymes based on the latest REBASE. Twenty-five SNPs with mismatch PCR-RFLP screened from 288 SNPs in human SLC6A4 gene are used to appraise the TLBOMPD. Also, the computational results are compared with those of the GAMPD. In the future, the usage of the mutagenic primers in the wet lab needs to been validated carefully to increase the reliability of the method. The TLBOMPD is implemented in JAVA and it is freely available at http://tlbompd.googlecode.com/.

Bioinformatics prioritization of SNPs perturbing microRNA regulation of hematological malignancy-implicated genes

The contribution of microRNAs (miRNAs) to cancer has been extensively investigated and it became obvious that a strict regulation of miRNA-mRNA regulatory network is crucial for safeguarding cell health. Apart from the direct impact of miRNA dysregulation in cancer pathogenesis, genetic variations in miRNAs are likely to disrupt miRNA-target interaction. Indeed, many evidences suggested that SNPs within miRNA regulome are associated with the development of different hematological malignancies. However, a full catalog of SNPs within miRNAs target sites of genes relevant to hematopoiesis and hematological malignancies is still lacking. Accordingly, we aimed to systematically identify and characterize such SNPs and provide a prioritized list of most potentially disrupting SNPs. Although in the present study we did not address the functional significance of these potential disturbing variants, we believe that our compiled results will be valuable for researchers interested in determining the role of target-SNPs in the development of hematological malignancies.

Application of nanomaterials in the bioanalytical detection of disease-related genes

In the diagnosis of genetic diseases and disorders, nanomaterials-based gene detection systems have significant advantages over conventional diagnostic systems in terms of simplicity, sensitivity, specificity, and portability. In this review, we describe the application of nanomaterials for disease-related genes detection in different methods excluding PCR-related method, such as colorimetry, fluorescence-based methods, electrochemistry, microarray methods, surface-enhanced Raman spectroscopy (SERS), quartz crystal microbalance (QCM) methods, and dynamic light scattering (DLS). The most commonly used nanomaterials are gold, silver, carbon and semiconducting nanoparticles. Various nanomaterials-based gene detection methods are introduced, their respective advantages are discussed, and selected examples are provided to illustrate the properties of these nanomaterials and their emerging applications for the detection of specific nucleic acid sequences.

Breast cancer risk associated with gene expression and genotype polymorphisms of the folate-metabolizing MTHFR gene: a case-control study in a high altitude Ecuadorian mestizo population

Breast cancer (BC) is the leading cause of cancer-related death among women in 2014. Methylenetetrahydrofolate reductase (MTHFR), methionine synthase (MTR), and MTR reductase (MTRR) are enzymes that play an important role in folate metabolism. The single nucleotide polymorphisms, MTHFR C677T, A1298C, MTR A2756G, and MTRR A66G, alter plasmatic folate and homocysteine concentrations, causing problems during the repairment, synthesis, and methylation of the genetic material. Therefore, it is essential to know how BC risk is associated with histopathological and immunohistochemical characteristics, genotype polymorphisms, and gene expression in a high altitude Ecuadorian mestizo population. DNA was extracted from 195 healthy and 114 affected women. Genotypes were determined by restriction enzymes and genomic sequencing. mRNA was extracted from 26 glandular breast tissue samples, both from cancerous tissue and healthy tissue adjacent to the tumor. Relative gene expression was determined with the comparative Livak method (2(-ΔΔCT)). We found significant association between the rs1801133 (A222V) genotypes and an increased risk of BC development: C/T (odds ratio [OR] = 1.8; 95 % confidence interval [CI] = 1.1-3.2; P = 0.039), T/T (OR = 2.9; 95 % CI = 1.2-7.2; P = 0.025), and C/T + T/T (OR = 1.9; 95 % CI = 1.1-3.3; P = 0.019). Regarding relative gene expression, we found significant mRNA subexpression between the combined genotypes C/T + T/T (rs1801133) and triple negative breast cancer (TNBC) (P = 0.034). In brief, the MTHFR gene and its protein could act as potential predictive biomarkers of BC, especially TNBC among the high altitude Ecuadorian mestizo population.

Universal probe amplification: multiplex screening technologies for genetic variations

In order to achieve multiplex screening of genetic variations, multiplex amplification of target genomic DNA is necessary. Universal amplification technology meets this requirement by simultaneously amplifying a number of different regions within the target genomic DNA using a single pair of universal primers and thus eliminating the limitations associated with the use of multiple pairs of primers. We comprehensively review universal probe amplification and its use with multiplex technologies for the identification of the most representative genetic variation, i. e. single nucleotide polymorphisms. The progress and key issues relating to universal probe amplification are discussed and the representative technologies are summarized with an emphasis on their application for the identification of susceptibility to human diseases.

Integrative approach detected association between genetic variants of microRNA binding sites of TLRs pathway genes and OSCC susceptibility in Chinese Han population

Oral squamous cell carcinoma (OSCC) is a leading malignancy worldwide; the overall 5-year survival rate is approximately 50%. A variety of proteins in Toll-like receptors (TLRs) pathway have been related with the risk of OSCC. However, the influence of genetic variations in TLRs pathway genes on OSCC susceptibility is unclear. Previous studies mainly focused on the coding region of genes, while the UTR region remains unstudied. In the current study, a bioinformatics approach was performed to select candidate single nucleotide polymorphisms (SNPs) on microRNA binding sites of TLRs pathway genes related with OSCC. After screening 90 OSCC related TLRs pathway genes, 16 SNPs were selected for genotyping. We found that rs5030486, the polymorphisms on 3′ UTR of TRAF6, was significantly associated with OSCC risk. AG genotype of TRAF6 was strongly associated with a decreased risk of OSCC (OR = 0.252; 95% CI = 0.106, 0.598; p = 0.001). In addition, AG genotype was also related with a reduced risk of OSCC progression both in univariable analysis (HR = 0.303, 95% CI = 0.092, 0.995) and multivariable analysis (HR = 0.272, 95% CI = 0.082, 0.903). Furthermore, after detecting the mRNA expression level of TRAF6 in 24 OSCC patients, we found that TRAF6 expression level was significantly different between patients carrying different genotypes at locus rs5030486 (p = 0.013), indicating that rs5030486 of TRAF6 might contribute to OSCC risk by altering TRAF6 expression level. In general, these data indicated that SNP rs5030486 could be a potential bio-marker for OSCC risk and our results might provide new insights into the association of polymorphisms within the non-coding area of genes with cancers.

Genotyping technologies for all

Three and a half million single nucleotide polymorphisms are now publicly available through the International HapMap project, enabling genetic and pharmacogenetic studies involving whole genome or comprehensive candidate gene association approaches. The cost/genotype for these studies has been driven down to levels unimagined only a few years ago albeit under particular conditions. Here, eight commonly used commercially available genotyping assays (TaqMan, SNPstream, SNPlex, hME/iPLEX, MIP, GenChip, Goldengate, Infinium I and II) are briefly presented and their particular strengths and weaknesses as well as their suitability for particular types of studies and the related costs are also discussed.:

Detection of single-nucleotide polymorphisms using an ON-OFF switching of regenerated biosensor based on a locked nucleic acid-integrated and toehold-mediated strand displacement reaction

Although various strategies have been reported for single-nucleotide polymorphisms (SNPs) detection, development of a time-saving, specific, and regenerated electrochemical sensing platform still remains a realistic goal. In this study, an ON-OFF switching of a regenerated biosensor based on a locked nucleic acid (LNA)-integrated and toehold-mediated strand displacement reaction technique is constructed for detection of SNPs. The LNA-integrated and methylene blue-labeled capture probe with an external toehold is designed to switch on the sensing system. The mutant-type DNA probe completes complementary with the capture probe to trigger the strand displacement reaction, which switches off the sensing system. However, when the single-base mismatched wild-type DNA probe is presented, the strand displacement reaction cannot be achieved; therefore, the sensing system still keeps the ON state. This DNA sensor is stable over five reuses. We further testify that the LNA-integrated sequence has better recognition ability for SNPs detection compared to the DNA-integrated sequence. Moreover, this DNA senor exhibits a remarkable discrimination capability of SNPs among abundant wild-type targets and 6000-fold (m/m) excess of genomic DNA. In addition, it is selective enough in complex and contaminant-ridden samples, such as human urine, soil, saliva, and beer. Overall, these results demonstrate that this reliable DNA sensor is easy to be fabricated, simple to operate, and stable enough to be readily regenerated.

The regulatory mechanism of the LY6K gene expression in human breast cancer cells

LY6K is a cancer biomarker and a therapeutic target that induces invasion and metastasis. However, the molecular mechanisms that determine human LY6K transcription are completely unknown. To elucidate the mechanisms involved in human LY6K gene regulation and expression, multiple cis-elements were predicted using TRANSFAC software, and the LY6K regulatory region was identified using the luciferase assay in the human LY6K gene promoter. We performed ChIP, EMSA, and supershift assays to investigate the transcription factor activity on the LY6K promoter, and the effect of a SNP and CpG site methylation on AP-1 transcription factor binding affinity. AP-1 and the CREB transcription factor bound to LY6K promoter within -550/-1, which was essential for LY6K expression, but only the AP-1 heterodimer, JunD, and Fra-1, modulates LY6K gene transcriptional level. A decrease in LY6K was associated with the SNP242 C allele, a polymorphic G/C-SNP at the 242 nucleotide in the LY6K promoter region (rs2585175), or methylation of the CpG site, which was closely located with the AP-1 site by interfering with binding of the AP-1 transcription factor to the LY6K promoter. Our findings reveal an important role for AP-1 activation in promoting LY6K gene expression that regulates cell mobility of breast cancer cells, whereas the SNP242 C allele or methylation of the CpG site may reduce the risk of invasion or metastasis by interfering AP-1 activation.

Mutagenic primer design for mismatch PCR-RFLP SNP genotyping using a genetic algorithm

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) is useful in small-scale basic research studies of complex genetic diseases that are associated with single nucleotide polymorphism (SNP). Designing a feasible primer pair is an important work before performing PCR-RFLP for SNP genotyping. However, in many cases, restriction enzymes to discriminate the target SNP resulting in the primer design is not applicable. A mutagenic primer is introduced to solve this problem. GA-based Mismatch PCR-RFLP Primers Design (GAMPD) provides a method that uses a genetic algorithm to search for optimal mutagenic primers and available restriction enzymes from REBASE. In order to improve the efficiency of the proposed method, a mutagenic matrix is employed to judge whether a hypothetical mutagenic primer can discriminate the target SNP by digestion with available restriction enzymes. The available restriction enzymes for the target SNP are mined by the updated core of SNP-RFLPing. GAMPD has been used to simulate the SNPs in the human SLC6A4 gene under different parameter settings and compared with SNP Cutter for mismatch PCR-RFLP primer design. The in silico simulation of the proposed GAMPD program showed that it designs mismatch PCR-RFLP primers. The GAMPD program is implemented in JAVA and is freely available at http://bio.kuas.edu.tw/gampd/.

Molecular Diagnostics of Soft Tissue Tumors

Context.—Soft tissue pathology encompasses a remarkably diverse assortment of benign and malignant soft tissue tumors. Rendering a definitive diagnosis is complicated not only by the large volume of existing histologic subtypes (&gt;100) but also frequently by the presence of overlapping clinical, histologic, immunohistochemical, and/or radiographic features. During the past 3 decades, mesenchymal tumor–specific, cytogenetic and molecular genetic abnormalities have demonstrated an increasingly important, ancillary role in mesenchymal tumor diagnostics.

Objectives.—To review molecular diagnostic tools available to the pathologist to further classify specific soft tissue tumor types and recurrent aberrations frequently examined. Advantages and limitations of individual approaches will also be highlighted.

Data Sources.—Previously published review articles, peer-reviewed research publications, and the extensive cytogenetic and molecular diagnostic experience of the authors to include case files of The University of Nebraska Medical Center.

Conclusions.—Cytogenetic and molecular genetic assays are used routinely for diagnostic purposes in soft tissue pathology and represent a powerful adjunct to complement conventional microscopy and clinicoradiographic evaluation in the formulation of an accurate diagnosis. Care should be taken, however, to recognize the limitations of these approaches. Ideally, more than one technical approach should be available to a diagnostic laboratory to compensate for the shortcomings of each approach in the assessment of individual specimens.

CanProVar: a human cancer proteome variation database

Identification and annotation of mutated genes or proteins involved in oncogenesis and tumor progression are crucial for both cancer biology and clinical applications. We have developed a human Cancer Proteome Variation Database (CanProVar) by integrating information on protein sequence variations from various public resources, with a focus on cancer-related variations (crVAR). We have also built a user-friendly interface for querying the database. The current version of CanProVar comprises 8,570 crVARs in 2,921 proteins derived from existing genome variation databases and recently published large-scale cancer genome resequencing studies. It also includes 41,541 non-cancer specific variations (ncsVARs) in 30,322 proteins derived from the dbSNP database. CanProVar provides quick access to known crVARs in protein sequences along with related cancer samples, relevant publications, data sources, and functional information such as Gene Ontology (GO) annotations for the proteins, protein domains in which the variation occurs, and protein interaction partners with crVARs. CanProVar also helps reveal functional characteristics of crVARs and proteins bearing these variations. Our analysis showed that crVARs were enriched in certain protein domains. We also showed that proteins bearing crVARs were more likely to interact with each other in the protein interaction network. CanProVar can be accessed from http://bioinfo.vanderbilt.edu/canprovar.

Rolling circle amplification combined with gold nanoparticle aggregates for highly sensitive identification of single-nucleotide polymorphisms

A highly sensitive and specific colorimetry-based rolling circle amplification (RCA) assay method for single-nucleotide polymorphism genotyping has been developed. A circular template is generated by ligation upon the recognition of a point mutation on DNA targets. An RCA amplification is then initiated using the circular template in the presence of Phi29 polymerase. The RCA product can be digested by a restricting endonuclease, and the cleaved DNA fragments can mediate the aggregation of gold nanoparticle-tagged DNA probes. This causes a colorimetric change of the solution as the indicator of the mutation occurrence, which can be detected using UV-vis spectroscopy or viewed by naked eyes. On the basis of the high amplification efficiency of Phi29 polymerase, a mutated target of approximately 70 fM can be detected in this assay. In addition, the protection of the circle template using phosphorothioated nucleotides allows the digestion reaction to be performed simultaneously in RCA. Moreover, DNA ligase offers high fidelity in distinguishing the mismatched bases at the ligation site, resulting in positive detection of mutant targets even when the ratio of the wild-type to the mutant is 10,000:1. The developed RCA-based colorimetric detection scheme was demonstrated for SNP typing of beta-thalassemia gene at position -28 in genomic DNA.

Streptavidin-enhanced assay for sensitive and specific detection of single nucleotide polymorphism in TP53

This paper reports an approach to detection of single nucleotide polymorphism based on special amplification assay and surface plasmon resonance biosensor technology. In this assay, a part of the target DNA is recognized by a probe (probe A) coupled with streptavidin-oligonucleotide (SON) complexes ex situ, and when the mixture is injected in the sensor, another part of the target DNA is recognized by a DNA probe (probe B) immobilized on the sensor surface. To achieve high sensitivity and specificity, the assay is optimized in terms of composition of SON complexes, probe design, and assay temperature. It is demonstrated that this approach provides high specificity (no response to targets containing single-mismatched bases) and sensitivity (improves sensor response to perfectly matched oligonucleotides by one order of magnitude compared to the direct detection method). The assay is applied to detection of a short synthetic analogue of TP53 containing a "hot spot"-single nucleotide mismatch frequently mutated in germ line cancer-at levels down to 40 pM.

A brief review of molecular techniques to assess plant diversity

Massive loss of valuable plant species in the past centuries and its adverse impact on environmental and socioeconomic values has triggered the conservation of plant resources. Appropriate identification and characterization of plant materials is essential for the successful conservation of plant resources and to ensure their sustainable use. Molecular tools developed in the past few years provide easy, less laborious means for assigning known and unknown plant taxa. These techniques answer many new evolutionary and taxonomic questions, which were not previously possible with only phenotypic methods. Molecular techniques such as DNA barcoding, random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), microsatellites and single nucleotide polymorphisms (SNP) have recently been used for plant diversity studies. Each technique has its own advantages and limitations. These techniques differ in their resolving power to detect genetic differences, type of data they generate and their applicability to particular taxonomic levels. This review presents a basic description of different molecular techniques that can be utilized for DNA fingerprinting and molecular diversity analysis of plant species.

Imaging mass spectrometry of gastric carcinoma in formalin-fixed paraffin-embedded tissue microarray

The popularity of imaging mass spectrometry (IMS) of tissue samples, which enables the direct scanning of tissue sections within a short time-period, has been considerably increasing in cancer proteomics. Most pathological specimens stored in medical institutes are formalin-fixed; thus, they had been regarded to be unsuitable for proteomic analyses, including IMS, until recently. Here, we report an easy-to-use screening method that enables the analysis of multiple samples in one experiment without extractions and purifications of proteins. We scanned, with an IMS technique, a tissue microarray (TMA) of formalin-fixed paraffin-embedded (FFPE) specimens. We detected a large amount of signals from trypsin-treated FFPE-TMA samples of gastric carcinoma tissues of different histological types. Of the signals detected, 54 were classified as signals specific to cancer with statistically significant differences between adenocarcinomas and normal tissues. We detected a total of 14 of the 54 signals as histological type-specific with the support of statistical analyses. Tandem MS revealed that a signal specific to poorly differentiated cancer tissue corresponded to histone H4. Finally, we verified the IMS-based finding by immunohistochemical analysis of more than 300 specimens spotted on TMAs; the immunoreactivity of histone H4 was remarkably strong in poorly differentiated cancer tissues. Thus, the application of IMS to FFPE-TMA can enable high-throughput analysis in cancer proteomics to aid in the understanding of molecular mechanisms underlying carcinogenesis, invasiveness, metastasis, and prognosis. Further, results obtained from the IMS of FFPE-TMA can be readily confirmed by commonly used immunohistochemical analyses.

Application of OMICS technologies in occupational and environmental health research; current status and projections

OMICS technologies are relatively new biomarker discovery tools that can be applied to study large sets of biological molecules. Their application in human observational studies (HOS) has become feasible in recent years due to a spectacular increase in the sensitivity, resolution and throughput of OMICS-based assays. Although, the number of OMICS techniques is ever expanding, the five most developed OMICS technologies are genotyping, transcriptomics, epigenomics, proteomics and metabolomics. These techniques have been applied in HOS to various extents. However, their application in occupational environmental health (OEH) research has been limited. Here, we will discuss the opportunities these new techniques provide for OEH research. In addition we will address difficulties and limitations to the interpretation of the data that is generated by OMICS technologies. To illustrate the current status of the application of OMICS in OEH research, we will provide examples of studies that used OMICS technologies to investigate human health effects of two well-known toxicants, benzene and arsenic.