The role of single nucleotide polymorphisms in predicting prostate cancer risk and therapeutic decision making

Advancing antibiotic discovery with bacterial cytological profiling: a high-throughput solution to antimicrobial resistance

Developing new antibiotics poses a significant challenge in the fight against antimicrobial resistance (AMR), a critical global health threat responsible for approximately 5 million deaths annually. Finding new classes of antibiotics that are safe, have acceptable pharmacokinetic properties, and are appropriately active against pathogens is a lengthy and expensive process. Therefore, high-throughput platforms are needed to screen large libraries of synthetic and natural compounds. In this review, we present bacterial cytological profiling (BCP) as a rapid, scalable, and cost-effective method for identifying antibiotic mechanisms of action. Notably, BCP has proven its potential in drug discovery, demonstrated by the identification of the cellular target of spirohexenolide A against methicillin-resistant Staphylococcus aureus. We present the application of BCP for different bacterial organisms and different classes of antibiotics and discuss BCP's advantages, limitations, and potential improvements. Furthermore, we highlight the studies that have utilized BCP to investigate pathogens listed in the Bacterial Priority Pathogens List 2024 and we identify the pathogens whose cytological profiles are missing. We also explore the most recent artificial intelligence and deep learning techniques that could enhance the analysis of data generated by BCP, potentially advancing our understanding of antibiotic resistance mechanisms and the discovery of novel druggable pathways.

Prediction of deleterious non-synonymous SNPs of human MDC1 gene: an in silico approach

MDC1 (Mediator of DNA damage Checkpoint protein 1) functions to facilitate the localization of numerous DNA damage response (DDR) components to DNA double-strand break sites. MDC1 is an integral component in preserving genomic stability and appropriate DDR regulation. There haven't been systematic investigations of MDC1 mutations that induce cancer and genomic instability. Variations in nsSNPs have the potential to modify the protein chemistry and their function. Describing functional SNPs in disease-associated genes presents a significant conundrum for investigators, it is possible to assess potential functional SNPs before conducting larger population examinations. Multiple sequences and structure-based bioinformatics strategies were implemented in the current in-silico investigation to discern potential nsSNPs of the MDC1 genes. The nsSNPs were identified with SIFT, SNAP2, Align GVGD, PolyPhen-2, and PANTHER, and their stability was determined with MUpro. The conservation, solvent accessibility, and structural effects of the mutations were identified with ConSurf, NetSurfP-2.0, and SAAFEC-SEQ respectively. Cancer-related analysis of the nsSNPs was conducted using cBioPortal and TCGA web servers. The present study appraised five nsSNPs (P1426T, P69S, P194R, P203L, and H131Y) as probably mutilating due to their existence in highly conserved regions and propensity to deplete protein stability. The nsSNPs P194R, P203L, and H131Y were concluded as deleterious and possibly damaging from the 5 prediction tools. The functional nsSNP P194R mutation is associated with skin cutaneous melanoma while no significant records were found for other nsSNPs. The present study concludes that the highly deleterious P194R mutations can potentially induce genomic instability and contribute to various cancers' pathogenesis. Developing drugs targeting these mutations can undoubtedly be advantageous in large population-based studies, particularly in the development of precision medicine.

Functional characterization of the SDR42E1 reveals its role in vitamin D biosynthesis

Vitamin D deficiency poses a widespread health challenge, shaped by environmental and genetic determinants. A recent discovery identified a genetic regulator, rs11542462, in the SDR42E1 gene, though its biological implications remain largely unexplored. Our bioinformatic assessments revealed pronounced SDR42E1 expression in skin keratinocytes and the analogous HaCaT human keratinocyte cell lines, prompting us to select the latter as an experimental model. Employing CRISPR/Cas9 gene-editing technology and multi-omics approach, we discovered that depleting SDR42E1 showed a 1.6-fold disruption in steroid biosynthesis pathway (P-value = 0.03), considerably affecting crucial vitamin D biosynthesis regulators. Notably, SERPINB2 (P-value = 2.17 × 10-103), EBP (P-value = 2.46 × 10-13), and DHCR7 (P-value = 8.03 × 10-09) elevated by ∼2-3 fold, while ALPP (P-value <2.2 × 10-308), SLC7A5 (P-value = 1.96 × 10-215), and CYP26A1 (P-value = 1.06 × 10-08) downregulated by ∼1.5-3 fold. These alterations resulted in accumulation of 7-dehydrocholesterol precursor and reduction of vitamin D3 production, as evidenced by the drug enrichment (P-value = 4.39 × 10-06) and total vitamin D quantification (R2 = 0.935, P-value = 0.0016) analyses. Our investigation unveils SDR42E1's significance in vitamin D homeostasis, emphasizing the potential of precision medicine in addressing vitamin D deficiency through understanding its genetic basis.

The role of longevity-related genetic variant interactions as predictors of survival after 85 years of age

Genome-wide association studies and candidate gene studies have identified several genetic variants that might play a role in achieving longevity. This study investigates interactions between pairs of those single nucleotide polymorphisms (SNPs) and their effect on survival above the age of 85 in a sample of 327 Croatian individuals. Although none of the SNPs individually showed a significant effect on survival in this sample, 14 of the 359 interactions tested (between SNPs not in LD) reached the level of nominal significance (p<0.05), showing a potential effect on late-life survival. Notably, SH2B3 rs3184504 interacted with different SNPs near TERC, TP53 rs1042522 with different SNPs located near the CDKN2B gene, and CDKN2B rs1333049 with different SNPs in FOXO3, as well as with LINC02227 rs2149954. The other interaction pairs with a possible effect on survival were FOXO3 rs2802292 and ERCC2 rs50871, IL6 rs1800795 and GHRHR rs2267723, LINC02227 rs2149954 and PARK7 rs225119, as well as PARK7 rs225119 and PTPN1 rs6067484. These interactions remained significant when tested together with a set of health-related variables that also had a significant effect on survival above 85 years. In conclusion, our results confirm the central role of genetic regulation of insulin signalling and cell cycle control in longevity.

Analysis of prognostic germline polymorphisms in patients with advanced hepatocellular carcinoma

Background

The prognosis of hepatocellular carcinoma (HCC) is influenced by both tumor and patient specific factors. Current therapies of advanced HCC target angiogenesis and immune evasion, however there are no clinically useful biomarkers to guide clinicians.

Methods

Our aim in this retrospective cohort study was to validate single nucleotide polymorphisms (SNPs) prognostic of outcome in advanced HCC from the literature, and to analyze exploratory SNPs chosen from evaluation of the HCC tumor immune microenvironment. Using a database of patients with HCC treated with sorafenib, blood samples were genotyped, clinical variables were retrospectively collected, and SNPs were analyzed for association with progression-free survival (PFS) and overall survival (OS). A subsequent analysis was conducted to determine if identified SNPs were prognostic in trans arterial chemoembolization (TACE) treated patients.

Results

Literature review identified 7 SNPs in vascular endothelial growth factor (VEGF), eNOS, angiopoietin 2 (ANGPT2) and vascular endothelial growth factor receptor 2 (VEGFR2), however none were externally validated in our dataset. Of the 35 exploratory immunomodulatory SNPs, the following were associated with PFS or OS: CCL2 C-C motif ligand 2 (CCL2) (rs1024611), interleukin-10 (IL-10) (rs1800896), cytotoxic T-lymphocyte antigen-4 (CTLA-4) (rs231775) and NFKB1 (rs28362491).

Conclusions

SNPs identified by literature review to be prognostic in sorafenib treated patients with advanced HCC were not validated in our dataset. Our findings suggest potentially important prognostic implications of SNPs in VEGFR2, CCL2, IL-10, CTLA-4 and NFKB1 that deserve further study.

No association between MTHFR gene C677T/A1298C polymorphisms, serum folate, vitamin B12, homocysteine levels, and prostate cancer in an Algerian population

BACKGROUND

Methylenetetrahydrofolate reductase (MTHFR) is an important enzyme involved in folate and homocysteine metabolism, which are necessary for DNA methylation and nucleotide synthesis. Genetic polymorphisms that reduce MTHFR activity have been linked to several diseases, including prostate cancer. In this study, we aimed to investigate whether MTHFR polymorphisms, along with serum levels of folate, vitamin B12, and homocysteine, are associated with prostate cancer risk in the Algerian population.

METHODS

A total of 106 Algerian men with newly diagnosed prostate cancer and 125 healthy controls were included in this case-control study. The MTHFR C677T and A1298C polymorphisms were analyzed using PCR/RFLP and Real-Time PCR TaqMan® assays, respectively. Serum levels of folate, total homocysteine, and vitamin B12 were measured using an automatic biochemistry analyzer.

RESULTS

We found no significant differences in the genotype frequency of A1298C and C677T between prostate cancer patients and controls. Moreover, serum levels of folate, total homocysteine, and vitamin B12 were not significantly associated with prostate cancer risk (p > 0.05). However, age and family history were identified as significant risk factors (OR = 1.178, p = 0.00 and OR = 10.03, p = 0.007, respectively).

CONCLUSION

Our study suggests that MTHFR C677T and A1298C, as well as serum levels of folate, total homocysteine, and vitamin B12, are not associated with prostate cancer risk in the Algerian population. However, age and family history are significant risk factors. Further studies with a larger sample size are required to confirm these findings.

An overview of remote monitoring methods in biodiversity conservation

Conservation of biodiversity is critical for the coexistence of humans and the sustenance of other living organisms within the ecosystem. Identification and prioritization of specific regions to be conserved are impossible without proper information about the sites. Advanced monitoring agencies like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) had accredited that the sum total of species that are now threatened with extinction is higher than ever before in the past and are progressing toward extinct at an alarming rate. Besides this, the conceptualized global responses to these crises are still inadequate and entail drastic changes. Therefore, more sophisticated monitoring and conservation techniques are required which can simultaneously cover a larger surface area within a stipulated time frame and gather a large pool of data. Hence, this study is an overview of remote monitoring methods in biodiversity conservation via a survey of evidence-based reviews and related studies, wherein the description of the application of some technology for biodiversity conservation and monitoring is highlighted. Finally, the paper also describes various transformative smart technologies like artificial intelligence (AI) and/or machine learning algorithms for enhanced working efficiency of currently available techniques that will aid remote monitoring methods in biodiversity conservation.

Genetic variants of SDCCAG8 and MAGI2 in mitosis-related pathway genes are independent predictors of cutaneous melanoma-specific survival

Mitosis is a prognostic factor for cutaneous melanoma (CM), but accurate mitosis detection in CM tissues is difficult. Therefore, the 8th Edition of the American Joint Committee on Cancer staging system has removed the mitotic rate as a category criterion of the tumor T-category, based on the evidence that the mitotic rate was not an independent prognostic factor for melanoma survival. As single-nucleotide polymorphisms (SNPs) have been shown to be potential predictors for cutaneous melanoma-specific survival (CMSS), we investigated the potential prognostic value of SNPs in mitosis-related pathway genes in CMSS by analyzing their associations with outcomes of 850 CM patients from The University of Texas MD Anderson Cancer Center in a discovery dataset and validated the findings in another dataset of 409 CM patients from the Harvard University Nurses' Health Study and Health Professionals Follow-up Study. In both datasets, we identified two SNPs (SDCCAG8 rs10803138 G>A and MAGI2 rs3807694 C>T) as independent prognostic factors for CMSS, with adjusted allelic hazards ratios of 1.49 (95% confidence interval = 1.17-1.90, P = .001) and 1.45 (1.13-1.86, P = .003), respectively. Furthermore, their combined unfavorable alleles also predicted a poor survival in both discovery and validation datasets in a dose-response manner (Ptrend  = .0006 and .0001, respectively). Additional functional analysis revealed that both SDCCAG8 rs10803138 A and MAGI2 rs3807694 T alleles were associated with elevated mRNA expression levels in normal tissues. Therefore, these findings suggest that SDCCAG8 rs10803138 G>A and MAGI2 rs3807694 C>T are independent prognostic biomarkers for CMSS, possibly by regulating the mRNA expression of the corresponding genes involved in mitosis.

ZNF507 affects TGF-β signaling via TGFBR1 and MAP3K8 activation in the progression of prostate cancer to an aggressive state

Background

The progression of prostate cancer (PC) to the highly aggressive metastatic castration-resistant prostate cancer (mCRPC) or neuroendocrine prostate cancer (NEPC) is a fatal condition and the underlying molecular mechanisms are poorly understood. Here, we identified the novel transcriptional factor ZNF507 as a key mediator in the progression of PC to an aggressive state.

Methods

We analyzed ZNF507 expression in the data from various human PC database and high-grade PC patient samples. By establishment of ZNF507 knockdown and overexpression human PC cell lines, we assessed in vitro PC phenotype changes including cell proliferation, survival, migration and invasion. By performing microarray with ZNF507 knockdown PC cells, we profiled the gene clusters affected by ZNF507 knockdown. Moreover, ZNF507 regulated key signal was evaluated by dual-luciferase reporter and chromatin immunoprecipitation (ChIP) assays. Finally, we performed xenograft and in vivo metastasis assay to confirm the effect of ZNF507 knockdown in PC cells.

Results

We found that ZNF507 expression was increased, particularly in the highly graded PC. ZNF507 was also found to be associated with metastatic PC of a high grade. Loss- or gain-of-function–based analysis revealed that ZNF507 promotes the growth, survival, proliferation, and metastatic properties of PC (e.g., epithelial-mesenchymal transition) by upregulating TGF-β signaling. Profiling of gene clusters affected by ZNF507 knockdown revealed that ZNF507 positively regulated the transcription of TGFBR1, MAP3K8, and FURIN, which in turn promoted the progression of PC to highly metastatic and aggressive state.

Conclusions

Our findings suggest that ZNF507 is a novel key regulator of TGF-β signaling in the progression of malignant PC and could be a promising target for studying the development of advanced metastatic PCs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-02094-3.

Genetic variants of EML1 and HIST1H4E in myeloid cell-related pathway genes independently predict cutaneous melanoma-specific survival

Both in vivo and in vitro evidence has supported a key role of myeloid cells in immune suppression in melanoma and in promoting melanocytic metastases. Some single-nucleotide polymorphisms (SNPs) have been shown to predict cutaneous melanoma-specific survival (CMSS), but the association between genetic variation in myeloid cell-related genes and cutaneous melanoma (CM) patient survival remains unknown.

METHODS

we investigated associations between SNPs in myeloid cell-related pathway genes and CMSS in a discovery dataset of 850 CM patients and replicated the findings in another dataset of 409 CM patients.

RESULTS

we identified two SNPs (EML1 rs10151787 A>G and HIST1H4E rs2069018 T>C) as independent prognostic factors for CMSS, with adjusted allelic hazards ratios of 1.56 (95% confidence interval =1.19-2.05, P=0.001) and 1.66 (1.22-2.26, P=0.001), respectively; so were their combined unfavorable alleles in a dose-response manner in both discovery and replication datasets (P trend<0.001 and 0.002, respectively). Additional functional analysis revealed that both EML1 rs10151787 G and HIST1H4E rs2069018 C alleles were associated with elevated mRNA expression levels in normal tissues.

CONCLUSIONS

Our findings suggest that EML1 rs10151787 A>G and HIST1H4E rs2069018 T>C are independent prognostic biomarkers for CMSS.

Single nucleotide polymorphisms (SNPs) in prostate cancer: its implications in diagnostics and therapeutics

Prostate cancer is one of the most frequently diagnosed malignancies in developed countries and approximately 248,530 new cases of prostate cancer are likely to be diagnosed in the United States in 2021. During the late 1990s and 2000s, the prostate cancer-related death rate has decreased by 4% per year on average because of advancements in prostate-specific antigen (PSA) testing. However, the non-specificity of PSA to distinguish between benign and malignant forms of cancer is a major concern in the management of prostate cancer. Despite other risk factors in the pathogenesis of prostate cancer, recent advancement in molecular genetics suggests that genetic heredity plays a crucial role in prostate carcinogenesis. Approximately, 60% of heritability and more than 100 well-recognized single-nucleotide-polymorphisms (SNPs) have been found to be associated with prostate cancer and constitute a major risk factor in the development of prostate cancer. Recent findings revealed that a low to moderate effect on the progression of prostate cancer of individual SNPs was observed compared to a strong progressive effect when SNPs were in combination. Here, in this review, we made an attempt to critically analyze the role of SNPs and associated genes in the development of prostate cancer and their implications in diagnostics and therapeutics. A better understanding of the role of SNPs in prostate cancer susceptibility may improve risk prediction, enhance fine-mapping, and furnish new insights into the underlying pathophysiology of prostate cancer.

Functional association of a CD40 gene single-nucleotide polymorphism with the pathogenesis of coronary heart disease

AIMS

Endothelial dysfunction is a major contributor to the pathogenesis of atherosclerosis. CD40-CD40 ligand interactions confer a pro-inflammatory phenotype to endothelial cells (ECs). Recently, a thymine to cytosine transition (-1T>C) in the Kozak sequence of the CD40 gene (rs1883832) has been associated with coronary heart disease (CHD) in an Asian population. As there are no reports yet regarding its role in other ethnic groups, this study determines if the -1T>C single-nucleotide polymorphism (SNP) could be a risk factor for CHD in Caucasians by performing an association study and elucidates its functional consequence in cultured ECs.

METHODS AND RESULTS

Molecular and biochemical techniques, cell adhesion assays were used for genotype-stratified human EC characterization. SNP distribution in Caucasians was examined in a hospital-based case-control CHD study and serum levels of soluble CD40 (sCD40) were quantified by ELISA. The SNP in the CD40 gene affected baseline CD40 protein abundance on ECs. There was a genotype-dependent difference in CD40-mediated expression of pro-inflammatory genes. Monocyte adhesion was highest on the surface of cells homozygous for the C allele. Homozygosity for the C allele was associated with significant 2.32-fold higher odds of developing CHD as compared to TT genotype carriers. sCD40 plasma levels were genotype-dependently elevated in CHD patients, indicating a possible prognostic value.

CONCLUSION

The C allele of the CD40 SNP provokes a pro-inflammatory EC phenotype, compensated by an enhanced CD40 shedding to neutralize excess CD40 ligand. Homozygosity for the C allele is the cause for a genetic susceptibility to atherosclerosis and its sequelae.

Alcohol Intake and Alcohol-SNP Interactions Associated with Prostate Cancer Aggressiveness

Excessive alcohol intake is a well-known modifiable risk factor for many cancers. It is still unclear whether genetic variants or single nucleotide polymorphisms (SNPs) can modify alcohol intake's impact on prostate cancer (PCa) aggressiveness. The objective is to test the alcohol-SNP interactions of the 7501 SNPs in the four pathways (angiogenesis, mitochondria, miRNA, and androgen metabolism-related pathways) associated with PCa aggressiveness. We evaluated the impacts of three excessive alcohol intake behaviors in 3306 PCa patients with European ancestry from the PCa Consortium. We tested the alcohol-SNP interactions using logistic models with the discovery-validation study design. All three excessive alcohol intake behaviors were not significantly associated with PCa aggressiveness. However, the interactions of excessive alcohol intake and three SNPs (rs13107662 [CAMK2D, p = 6.2 × 10-6], rs9907521 [PRKCA, p = 7.1 × 10-5], and rs11925452 [ROBO1, p = 8.2 × 10-4]) were significantly associated with PCa aggressiveness. These alcohol-SNP interactions revealed contrasting effects of excessive alcohol intake on PCa aggressiveness according to the genotypes in the identified SNPs. We identified PCa patients with the rs13107662 (CAMK2D) AA genotype, the rs11925452 (ROBO1) AA genotype, and the rs9907521 (PRKCA) AG genotype were more vulnerable to excessive alcohol intake for developing aggressive PCa. Our findings support that the impact of excessive alcohol intake on PCa aggressiveness was varied by the selected genetic profiles.

The Contribution of Genetic Variants to the Risk of Papillary Thyroid Carcinoma in the Kazakh Population: Study of Common Single Nucleotide Polymorphisms and Their Clinicopathological Correlations

OBJECTIVE

Risk for developing papillary thyroid carcinoma (PTC), the most common endocrine malignancy, is thought to be mediated by lifestyle, environmental exposures and genetic factors. Recent progress in the genome-wide association studies of thyroid cancer leads to the identification of several genetic variants conferring risk to this malignancy across different ethnicities. We set out to elucidate the impact of selected single nucleotide polymorphisms (SNPs) on PTC risk and to evaluate clinicopathological correlations of these genetic variants in the Kazakh population for the first time.

METHODS

Eight SNPs were genotyped in 485 patients with PTC and 1,008 healthy control Kazakh subjects. The association analysis and multivariable modeling of PTC risk by the genetic factors, supplemented with rigorous statistical validation, were performed.

RESULT

Five of the eight SNPs: rs965513 (FOXE1/PTCSC2, P = 1.3E-16), rs1867277 (FOXE1 5'UTR, P = 7.5E-06), rs2439302 (NRG1 intron 1, P = 4.0E-05), rs944289 (PTCSC3/NKX2-1, P = 4.5E-06) and rs10136427 (BATF upstream, P = 9.8E-03) were significantly associated with PTC. rs966423 (DIRC3, P = 0.07) showed a suggestive association. rs7267944 (DHX35) was associated with PTC risk in males (P = 0.02), rs1867277 (FOXE1) conferred the higher risk in subjects older than 55 years (P = 7.0E-05), and rs6983267 (POU5F1B/CCAT2) was associated with pT3-T4 tumors (P = 0.01). The contribution of genetic component (unidirectional independent effects of rs965513, rs944289, rs2439302 and rs10136427 adjusted for age and sex) to PTC risk in the analyzed series was estimated to be 30-40%.

CONCLUSION

Genetic factors analyzed in the present work display significant association signals with PTC either on the whole group analysis or in particular clinicopathological groups and account for about one-third of the risk for PTC in the Kazakh population.

Whole genome sequencing identifies high-impact variants in well-known pharmacogenomic genes

More than 1100 genetic loci have been correlated with drug response outcomes but disproportionately few have been translated into clinical practice. One explanation for the low rate of clinical implementation is that the majority of associated variants may be in linkage disequilibrium (LD) with the causal variants, which are often elusive. This study aims to identify and characterize likely causal variants within well-established pharmacogenomic genes using next-generation sequencing data from the 1000 Genomes Project. We identified 69,319 genetic variations within 160 pharmacogenomic genes, of which 8207 variants are in strong LD (r2>0.8) with known pharmacogenomic variants. Of the latter, eight are coding or structural variants predicted to have high impact, with 19 additional missense variants that are predicted to have moderate impact. In conclusion, we identified putatively functional variants within known pharmacogenomics loci that could account for the association signals and represent the missing causative variants underlying drug response phenotypes.

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Prostate cancer (PCa) diagnosis with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment, highlighting the need for novel biomarkers. The aim of this review is to provide a summary of available metabolomics PCa biomarkers, particularly for clinically significant disease. A systematic search was conducted on PubMed for publications from July 2008 to July 2018 in accordance with PRISMA guidelines to report biomarkers with respect to their application in PCa diagnosis, progression, aggressiveness, recurrence, and treatment response. The vast majority of studies report biomarkers with the ability to distinguish malignant from benign prostate tissue with a few studies investigating biomarkers associated with disease progression, treatment response or tumour recurrence. In general, these studies report high dimensional datasets and the number of analysed metabolites often significantly exceeded the number of available samples. Hence, observed multivariate differences between case and control samples in the datasets might potentially also be associated with pre-analytical, technical, statistical and confounding factors. Giving the technical and methodological hurdles, there are nevertheless a number of metabolites and pathways repeatedly reported across various technical approaches, cohorts and sample types that appear to play a predominant role in PCa tumour biology, progression and recurrence.

PCA3 rs544190G>A and prostate cancer risk in an eastern Chinese population

Background:

The association of prostate cancer antigen 3 (PCA3) polymorphism (SNP, rs544190G>A) with metastatic prostate cancer in European descent has been reported. Our aim of the current study was to re-validate the effect of PCA3 polymorphism on prostate cancer risk in an Eastern Chinese population and then estimate possible genetic discrepancies among population.

Materials and Methods:

Taqman assay was employed to determine genotype of SNP rs544190 in 1015 ethnic Han Chinese patients with prostate cancer and 1032 cancer-free controls. Simultaneously, odds ratios (OR) and 95% confidence intervals (95%CI) for risk relationship were calculated by logistic regression models.

Results:

The statistically significant relationship between PCA3 rs544190G>A and higher prostate cancer risk was not found. Stratification analysis revealed that there was no remarkable association of rs544190 variant AG/AA genotype with prostate cancer risk in every subgroup, except for patients with Gleason score ≤7(3+4).

Conclusion:

Although the results demonstrated that SNP rs544190 was not involved in prostate cancer risk in Eastern Chinese descent, unlike in European population, these might have clinical implications on prostate cancer heterogeneity around the World. To validate these findings, well-designed studies with different ethnic populations are warranted.

Genomic and Bioinformatics Approaches for Analysis of Genes Associated With Cancer Risks Following Exposure to Tobacco Smoking

Cancer is a significant health problem in the Middle East and global population. It is well established that there is a direct link between tobacco smoking and cancer, which will continue to pose a significant threat to human health. The impact of long-term exposure to tobacco smoke on the risk of cancer encouraged the study of biomarkers for vulnerable individuals to tobacco smoking, especially children, who are more susceptible than adults to the action of environmental carcinogens. The carcinogens in tobacco smoke condensate induce DNA damage and play a significant role in determining the health and well-being of smokers, non-smoker, and primarily children. Cancer is a result of genomic and epigenomic malfunctions that lead to an initial premalignant condition. Although premalignancy genetic cascade is a much-delayed process, it will end with adverse health consequences. In addition to the DNA damage and mutations, tobacco smoke can cause changes in the DNA methylation and gene expression associated with cancer. The genetic events hint on the possible use of genomic–epigenomic changes in genes related to cancer, in predicting cancer risks associated with exposure to tobacco smoking. Bioinformatics provides indispensable tools to identify the cascade of expressed genes in active smokers and non-smokers and could assist the development of a framework to manage this cascade of events linked with the evolvement of disease including cancer. The aim of this mini review is to cognize the essential genomic processes and health risks associated with tobacco smoking and the implications of bioinformatics in cancer prediction, prevention, and intervention.

Identification and validation of regulatory SNPs that modulate transcription factor chromatin binding and gene expression in prostate cancer

Prostate cancer (PCa) is the second most common solid tumor for cancer related deaths in American men. Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with the increased risk of PCa. Because most of the susceptibility SNPs are located in noncoding regions, little is known about their functional mechanisms. We hypothesize that functional SNPs reside in cell type-specific regulatory elements that mediate the binding of critical transcription factors (TFs), which in turn result in changes in target gene expression. Using PCa-specific functional genomics data, here we identify 38 regulatory candidate SNPs and their target genes in PCa. Through risk analysis by incorporating gene expression and clinical data, we identify 6 target genes (ZG16B, ANKRD5, RERE, FAM96B, NAALADL2 and GTPBP10) as significant predictors of PCa biochemical recurrence. In addition, 5 SNPs (rs2659051, rs10936845, rs9925556, rs6057110 and rs2742624) are selected for experimental validation using Chromatin immunoprecipitation (ChIP), dual-luciferase reporter assay in LNCaP cells, showing allele-specific enhancer activity. Furthermore, we delete the rs2742624-containing region using CRISPR/Cas9 genome editing and observe the drastic downregulation of its target gene UPK3A. Taken together, our results illustrate that this new methodology can be applied to identify regulatory SNPs and their target genes that likely impact PCa risk. We suggest that similar studies can be performed to characterize regulatory variants in other diseases.

Association between polymorphisms in sex hormones synthesis and metabolism and prostate cancer aggressiveness

Novel biomarkers for prostate cancer (PCa) diagnosis and prognosis are necessary to improve the accuracy of current ones employed in clinic. We performed a retrospective study between the association of several polymorphisms in the main genes involved in the synthesis and metabolism of sex hormones and PCa risk and aggressiveness. A total of 311 Caucasian men (155 controls and 156 patients) were genotyped for 9 SNPs in AR, CYP17A1, LHCGR, ESR1 and ESR2 genes. Diagnostic PSA serum levels, Gleason score, tumor stage, D´Amico risk and data of clinical progression were obtained for patients at the moment of the diagnosis and after 54 months of follow-up. Chi-squared test were used for comparisons between clinical variables groups, logistic regression for clinical variables associations between SNPs; and Kaplan–Meier for the association between SNPs and time to biochemical progression. We found 5 variants (CYP17A1) rs743572, rs6162, rs6163; (LHCGR) rs2293275 and (ESR2) rs1256049 that were statistically significant according to clinical variables (PSA, D´Amico risk and T stage) on a case-case analysis. Moreover, the presence of A and G alleles in rs743572 and rs6162 respectively, increase the risk of higher PSA levels (>10 ng/μl). With respect to D´Amico risk rs743572 (AG-GG), rs6162 (AG-AA) and rs6163 (AC-AA) were associated with an increased risk; and last, AC and AA genotypes for rs6163 were associated with a shorter biochemical recurrence free survival (BRFS) in patients with radical prostatectomy. In multigene analysis, several variants in SNPs rs2293275, rs6152, rs1062577, rs6162, rs6163, rs1256049 and rs1004467 were described to be associated with a more aggressiveness in patients. However, none of the selected SNPs show significant values between patients and controls. In conclusion, this study identified inherited variants in genes CYP17A1, LHCGR and ESR2 related to more aggressiveness and/or a poor progression of the disease. According to this study, new promise PCa biomarkers for clinical management could be included in these previous SNPs.

Tissue-based biomarkers in prostate cancer

INTRODUCTION

Prostate cancer is a heterogeneous disease. Existing risk stratification tools based on standard clinlicopathologic variables (prostate specific antigen [PSA], Gleason score, and tumor stage) provide a modest degree of predictive ability. Advances in high-throughput sequencing has led to the development of several novel tissue-based biomarkers that can improve prognostication in prostate cancer management.

AREAS COVERED

The authors review commercially-available, tissue-based biomarker assays that improve upon existing risk-stratification tools in several areas of prostate cancer management, including the appropriateness of active surveillance and aiding in decision making regarding the use of adjuvant therapy. Additionally, some of the obstacles to the widespread adoption of these biomarkers and discuss several investigational sources of new biomarkers are discussed.

EXPERT COMMENTARY

Work is ongoing to answer pertinent clinical questions in prostate cancer management including which patients should undergo biopsy, active surveillance, receive adjuvant therapy, and what systemic therapy is best in the first-line. Incorporation into novel biomarkers may allow for the incorporation of a 'personalized' approach to management. Further validation will be required and questions of cost must be considered before wide scale adoption of these biomarkers. Tumor heterogeneity may impose a ceiling on the prognostic ability of biomarkers using currently available techniques.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns

Motivation

Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped.

Results

We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns.

Availability and Implementation

The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ .

Contact

hlin1@lsuhsc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

MicroRNA Theranostics in Prostate Cancer Precision Medicine

BACKGROUND

Prostate cancer is the second most frequently diagnosed cancer in men worldwide. Theranostics, a combination of diagnostics and therapeutics, is an emerging concept in the field of precision medicine, and microRNAs (miRNAs) are predictive pioneers in this area.

CONTENT

miRNAs are small endogenous noncoding RNA molecules that regulate gene expression posttranscriptionally by targeting messenger RNAs. More than 60% of all protein coding genes are controlled by miRNAs, which makes them powerful regulators of the different cellular processes involved in the pathogenesis of various types of cancer, including prostate cancer. Growing evidence indicates the differential expression of miRNAs in tumor tissues. In addition, miRNAs in body fluids, known as circulating miRNAs, are present in remarkably stable forms and their alteration in prostate cancer has been well documented. Circulating miRNAs are known to originate from tumor tissues, thereby enabling intercellular communication via carriers to promote tumorigenesis and malignancy. In addition, fueled by recent advances, the use of miRNA-based anticancer therapies has been proposed with the onset of early phase clinical trials to assess the therapeutic efficacy of miRNAs.

SUMMARY

In this review, we summarize the theranostic utility of miRNAs and outline their diagnostic and prognostic potential in prostate cancer. In addition, we discuss the current detection methodologies and emerging innovative strategies for the detection of miRNAs in body fluids and tumor tissues in the clinical setting. We also provide insight into the current and future therapeutic potential of miRNAs in prostate cancer.

Genetic Polymorphism of MMP2 Gene and Susceptibility to Prostate Cancer

BACKGROUND AND AIMS

The polymorphic genetic variants of matrix metalloproteinase (MMPs) can play critical roles in development and progression of cancer. The purpose of this study was to investigate if any association exists between MMP2 -1306/T and risk of prostate cancer (PCa).

METHODS

This case-control study comprised a total number of 241 subjects, including 102 patients with PCa and 139 controls with benign prostatic hyperplasia (BPH). MMP2 genotypes were detected by RFLP.

RESULTS

There is no significant difference between different genotypes of MMP2 polymorphism and risk of developing PCa (p = 0.08). Although these genotypes increased the risk of developing PCa 79% (CT vs. CC) and 54% (TT vs. CC), none had a significant effect (p = 0.09 and p = 1 respectively). There were no significant differences in genotype frequencies between patients with low and high degrees of PCa (p = 0.4). Therefore, this polymorphism cannot be considered as a protective factor for PCa metastasis. It seems that MMP2 polymorphism has no protective effect on the grading of the tumor (p = 0.8). Our results indicated that MMP2 polymorphism had no role in the vascular invasion of PCa.

CONCLUSION

We found no association between MMP2 polymorphism and cancer risk, overall or by grade, stage or age of diagnosis. Finally, there was no association between the different genotypes and PSA plasma levels among cases or controls. Further evaluations with larger samples from our population may illuminate the effects of polymorphisms on PCa risk and thus help early diagnosis, follow-up and prognostic determinations for PCa patients.

Synonymous Polymorphisms in HOXB13 as a Protective Factor for Prostate Cancer

BACKGROUND

Genomic association and linkage studies, as well as epidemiological data have implicated both the HOXB13 gene and single nucleotide polymorphisms (SNPs) in the development of prostate cancer (PCa). The recent association between the G84E polymorphism in the HOXB13 gene and PCa has been shown to result in a more aggressive cancer with an earlier onset of the disease. We examined the frequency of this mutation and other recurrent HOXB13 SNPs in patients with PCa and those with benign prostatic hyperplasia (BPH) or no cancer.

METHODS

Reverse transcriptase-polymerase chain reaction (RT-PCR) was performed on exons 1 and 2 of HOXB13 gene, followed by bidirectional Sanger Sequencing on peripheral blood from 232 PCa (age 46-92) and 110 BPH (age 45-84) patients. Statistical analysis was used to correlate between recurrent SNPs and PCa.

RESULTS

The G84E mutation was found at a low frequency in randomly selected PCa and BPH (both 0.9%). Two recurrent, synonymous SNPs, rs8556 and rs900627, were also detected. rs8556 was detected in 48 PCa (20.7%) and 26 BPH (23.6%) subjects; rs9900627was detected in 27 PCa (11.6%) and 19 BPH (17.3%) subjects. Having both rs8556 and rs9900627 or being homozygous for either one was associated with being 2.9 times less likely to develop PCa (p=0.05).

CONCLUSIONS

Although a larger study in order to confirm our findings, our data suggests a significant negative correlation between two SNPs, rs8556 and rs9900627, and the presence of PCa.

Copy number variation analysis by ligation-dependent PCR based on magnetic nanoparticles and chemiluminescence

A novel system for copy number variation (CNV) analysis was developed in the present study using a combination of magnetic separation and chemiluminescence (CL) detection technique. The amino-modified probes were firstly immobilized onto carboxylated magnetic nanoparticles (MNPs) and then hybridized with biotin-dUTP products, followed by amplification with ligation-dependent polymerase chain reaction (PCR). After streptavidin-modified alkaline phosphatase (STV-AP) bonding and magnetic separation, the CL signals were then detected. Results showed that the quantification of PCR products could be reflected by CL signal values. Under optimum conditions, the CL system was characterized for quantitative analysis and the CL intensity exhibited a linear correlation with logarithm of the target concentration. To validate the methodology, copy numbers of six genes from the human genome were detected. To compare the detection accuracy, multiplex ligation-dependent probe amplification (MLPA) and MNPs-CL detection were performed. Overall, there were two discrepancies by MLPA analysis, while only one by MNPs-CL detection. This research demonstrated that the novel MNPs-CL system is a useful analytical tool which shows simple, sensitive, and specific characters which are suitable for CNV analysis. Moreover, this system should be improved further and its application in the genome variation detection of various diseases is currently under further investigation.

Single nucleotide polymorphisms in DNA repair genes as risk factors associated to prostate cancer progression

Background

Besides serum levels of PSA, there is a lack of prostate cancer specific biomarkers. It is need to develop new biological markers associated with the tumor behavior which would be valuable to better individualize treatment. The aim of this study was to elucidate the relationship between single nucleotide polymorphisms (SNPs) in genes involved in DNA repair and prostate cancer progression.

Methods

A total of 494 prostate cancer patients from a Spanish multicenter study were genotyped for 10 SNPs in XRCC1, ERCC2, ERCC1, LIG4, ATM and TP53 genes. The SNP genotyping was made in a Biotrove OpenArray® NT Cycler. Clinical tumor stage, diagnostic PSA serum levels, and Gleason score at diagnosis were obtained for all participants. Genotypic and allelic frequencies were determined using the web-based environment SNPator.

Results

SNPs rs11615 (ERCC1) and rs17503908 (ATM) appeared as risk factors for prostate cancer aggressiveness. Patients wild homozygous for these SNPs (AA and TT, respectively) were at higher risk for developing cT2b – cT4 (OR = 2.21 (confidence interval (CI) 95% 1.47 – 3.31), p < 0.001) and Gleason scores ≥ 7 (OR = 2.22 (CI 95% 1.38 – 3.57), p < 0.001), respectively. Moreover, those patients wild homozygous for both SNPs had the greatest risk of presenting D’Amico high-risk tumors (OR = 2.57 (CI 95% 1.28 – 5.16)).

Conclusions

Genetic variants at DNA repair genes are associated with prostate cancer progression, and would be taken into account when assessing the malignancy of prostate cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-014-0143-0) contains supplementary material, which is available to authorized users.

Predictions for the future of kallikrein-related peptidases in molecular diagnostics

Kallikrein-related peptidases (KLKs) form a cancer-related ensemble of serine proteases. This multigene family hosts the most widely used cancer biomarker that is PSA-KLK3, with millions of tests performed annually worldwide. The present report provides an overview of the biomarker potential of the extended KLK family (KLK1-KLK15) in various disease settings and envisages approaches that could lead to additional KLK-driven applications in future molecular diagnostics. Particular focus is given on the inclusion of KLKs into multifaceted cancer biomarker panels that provide enhanced diagnostic, prognostic and/or predictive accuracy in several human malignancies. Such panels have been described so far for prostate, ovarian, lung and colorectal cancers. The role of KLKs as biomarkers in non-malignant disease settings, such as Alzheimer's disease and multiple sclerosis, is also commented upon. Predictions are given on the challenges and future directions regarding clinically oriented KLK research.