A genetic risk score to personalize prostate cancer screening, applied to population data.

Background: A polygenic hazard score (PHS)—the weighted sum of 54 SNP genotypes—was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening. Methods: UK population incidence data (Cancer Research UK) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using hazard ratios estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age—when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-years-standard risk)—was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups. Results: The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-years-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age. Conclusions: PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man’s PHS. Impact: Personalized genetic risk assessments could inform prostate cancer screening decisions

Nanomaterials in drug delivery system

In this article, nanomaterials that are currently being investigated for their potentials in biomedical field and have established to be drug carriers are elaborated. Liposome for example, has already been utilised in biomedical applications for a long time ago but extensive studies are still conducted in order to optimize its properties for better results. Each nanomaterials discussed in this article exhibits unique physiochemical and biological characteristics which give them flexibility to be used in many applications. Some exist as natural nanomaterials such as liposome, while some can be synthesized from certain compounds. Some nanomaterials can be functionalized to enhance their efficiency as drug carriers. However, not all synthetic nanomaterials are safe to be consumed by human. Therefore, further investigations and evaluations of each nanomaterial in term of long term effect in vivo must be carried out

Novel Mutations In Genes Causing Hereditary Spastic Paraplegia And Charcot-Marie-Tooth Neuropathy Identified By An Optimized Protocol For Homozygosity Mapping Based On Whole-Exome Sequencing

Purpose: Homozygosity mapping is an effective approach for detecting molecular defects in consanguineous families by delineating stretches of genomic DNA that are identical by descent. Constant developments in next-generation sequencing created possibilities to combine whole-exome sequencing (WES) and homozygosity Mapping in a single step. Methods: Basic optimization of homozygosity mapping parameters was performed in a group of families with autosomal-recessive (AR) mutations for which both single-nucleotide polymorphism (SNP) array and WES data were available. We varied the criteria for SNP extraction and PLINK thresholds to estimate their effect on the accuracy of homozygosity mapping based on WES. Results: Our protocol showed high specificity and sensitivity for homozygosity detection and facilitated the identification of novel mutations in GAN, GBA2, and ZFYVE26 in four families affected by hereditary spastic paraplegia or Charcot-Marie-Tooth disease. Filtering and mapping with optimized parameters was integrated into the HOMWES (homozygosity mapping based on WES analysis) tool in the GenomeComb package for genomic data analysis. Conclusion: We present recommendations for detection of homozygous regions based on WES data and a bioinformatics tool for their identification, which can be widely applied for studying AR disorders.WoSScopu

A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data.

BackgroundA polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.MethodsUnited Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.ResultsThe expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.ConclusionsPHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.ImpactPersonalized genetic risk assessments could inform prostate cancer screening decisions

Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array.

Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10(-8)). More than 70 prostate cancer susceptibility loci, explaining ∼30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies

Modulation of hormonal signaling in the brain by steroid receptor coactivators.

Nuclear receptors, such as estrogen, glucocorticoid or thyroid hormone receptors, have been shown to play a critical role in brain development and physiology. The activity of these receptors is modulated by the interaction with several proteins and, in particular, coactivators are required to enhance their transcriptional activity. The steroid receptor coactivators (SRC-1, -2 and -3) are currently the best characterized coactivators and we review here the current knowledge on the distribution and function of these proteins in the brain. Knock-out models and antisense techniques have demonstrated the requirement for SRC-1 and -2 in the brain, focusing mainly on steroid and thyroid hormone-dependent development and behavior. The precise function of SRC-3 in the brain is currently unknown but its presence throughout the brain suggests an important function. Although the molecular biology of SRCs is relatively well known, the in vivo control of their expression, post-translational modifications and time- and cell-specific interactions with the different nuclear receptors remain elusive. A complete understanding of hormone action on brain and behavior will not be attained until a better knowledge of coactivator physiology is achieved