Intertrochanteric fractures of the femur are the most common type of fracture, and are an increasing occurrence due to the aging of the population. The objectives of our study are to predict the fate of intertrochanteric fractures treated with intramedullary hip nails by assessing the postoperative fracture stability utilizing the newly developed scoring system, and to help rehabilitate these patients.
Eighty-two patients with intertrochanteric fractures that were treated with intramedullary hip nails between December, 2004 and January, 2011 were subjected to this study. The patients who could be followed for a minimum of one year postoperatively were enrolled. The immediate postoperative conditions were determined by radiograms: reduction status (3 parameters/4 points: contact accuracy of posteromedial cortex, severity of angulation, and distraction), fixation status (3 parameters/3 points: tip-apex distance, location of tip of the lag screw, entry point of the intramedullary nail), and fracture type (1 parameter/1 point: stable or unstable type by the Kyle's classification). Postoperative reduction loss and fixation failure were checked by radiograms taken at a minimum 3 months postoperative.
Reduction loss and fixation failure were observed in 14 consecutive patients (17%). The fixation failure rate was 100% (2 patients) in score 1, 60% (3 out of the 5 patients) in score 2, 39% (3 out of the 8 patients) in score 3, and 50% (4 out of the 8 patients) in score 4 groups. There were fixation failures only in 1 out of 13 patients with score 5, and in 1 out of 18 patients with score 6. There was no fixation failure in 17 patients with score 7 and 11 patients with score 8.
Maintenance of the fracture reduction by the stable fixation in the patient scores over 5 could be predicted by the postoperative radiograms.
Intertrochanteric; Fracture; Intramedullary hip nail; Fixation stability score
Pyogenic spondylitis involving only the posterior element of a vertebra is rare. To the best of our knowledge, there have been no reports of osteomyelitis of the transverse process. We report here on a 45-year-old male with a one month history of swelling associated with lower back pain. The magnetic resonance imaging showed a paraspinal soft tissue mass, and computed tomography revealed a fine osteolytic lesion in the right transverse process of the 5th lumbar spine, and this was all consistent with chronic osteomyelitis. A mixed staphylococcal infection was identified. Open drainage, resection of the transverse process and intravenous injection of anti-staphylococcal antibiotics resolved the back pain and reduced the erythrocyte sedimentation rate to normal. Pyogenic osteomyelitis of the transverse process is extremely rare, which can cause a misdiagnosis or a delayed diagnosis. Careful consideration of this disease is needed when evaluating patients who complain of back pain.
Osteomyelitis; Transverse process; Lumbar spine
Bilateral psoas abscesses extending to the gluteal muscle and intrapelvic area are uncommon. We present our experience with computed tomography (CT)-guided percutaneous catheter drainage for the treatment of multiple aggressive abscesses in a diabetic patient. The abscesses completely resolved after the procedures. Psoas abscess should be considered in the differential diagnosis of older diabetic patients with fever, flank or back pain, and flexion contracture of the hip joint. CT scanning is a useful method in diagnosing abscesses, and CT-guided percutaneous catheter drainage is an effective treatment method in selected patients.
Psoas abscess extending into the gluteal muscle and intrapelvic area; Diabetic patient; CT-guided percutaneous drainage
Circulating androgen levels are often used as indicators of physiological or pathological conditions. More than half of the variance for circulating androgen levels is thought to be genetically influenced. A genome-wide association study (GWAS) has identified two loci, SHBG at 17p13 and FAM9B at Xp22, for serum testosterone (T) levels; however, these explain only a small fraction of inter-individual variability. To identify additional genetic determinants of androgen levels, a GWAS of baseline serum T and dihydrotestosterone (DHT) levels was conducted in 3225 men of European ancestry from the REduction by DUtasteride of Prostate Cancer Events (REDUCE) study. Cross-validation was used to confirm the observed associations between the drug (n = 1581) and placebo (n = 1644) groups of REDUCE. In addition to confirming the associations of two known loci with serum T levels (rs727428 in SHBG: P = 1.26 × 10−12; rs5934505 in FAM9B: P = 1.61 × 10−8), we identified a new locus, JMJD1C at 10q21 that was associated with serum T levels at a genome-wide significance level (rs10822184: P = 1.12 × 10−8). We also observed that the SHBG locus was associated with serum DHT levels (rs727428: P = 1.47 × 10−11). Moreover, two additional variants in SHBG [rs72829446, in strong linkage equilibrium with the missense variant D356N (rs6259), and rs1799941] were also independently associated with circulating androgen levels in a statistical scale. These three loci (JMJD1C, SHBG and FAM9B) were estimated to account for ∼5.3 and 4.1% of the variance of serum T and DHT levels. Our findings may provide new insights into the regulation of circulating androgens and potential targets for androgen-based therapy.
Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk.
To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa.
Design, setting, and participants
Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated.
Outcome measurements and statistical analysis
Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers.
Results and limitations
Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10−8). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p < 0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p = 0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥7) PCa. A major limitation of this study was its focus on white patients only.
Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.
Prostate cancer; Genetics; AUC; Detection rate; Reclassification; SNPs; Prospective study; Clinical trial
We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates – one via a weighted PCa ‘risk’ score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.
prostate cancer; genetic clinical risk prediction; genetic scores; Bayesian logistic regression; predictive assessment
PPP2R2A, mapped to 8p21.2, encodes for the α isoform of the regulatory B55 subfamily of the protein phosphatase 2 (PP2A). PP2A is one of the four major Ser/Thr phosphatases and is implicated in the negative control of cell growth and division. Because of its known functions and location within a chromosomal region where evidence for linkage and somatic loss of heterozygosity was found, we hypothesized that either somatic copy number changes or germline sequence variants in PPP2R2A may increase prostate cancer (PCa) risk. We examined PPP2R2A deletion status in 141 PCa samples using Affymetrix SNP arrays. It was found that PPP2R2A was commonly (67.1%) deleted in tumor samples including a homozygous deletion in 3 tumors (2.1%). We performed a mutation screen for PPP2R2A in 96 probands of hereditary prostate cancer (HPC) families. No high risk mutations were identified. Additionally, we reanalyzed 10 SNPs of PPP2R2A in sporadic PCa cases and controls. No significant differences in the allele and genotype frequencies were observed among either PCa cases and controls or PCa aggressive and non-aggressive cases. Taken together, these results suggest that a somatic deletion rather than germline sequence variants of PPP2R2A may play a more important role in PCa susceptibility.
PPP2R2A; homozygous deletion; prostate cancer
Prostate cancer gene 3 (PCA3) is a non-coding gene specifically overexpressed in prostate cancer (PCa) that has great potential as a clinical biomarker for predicting prostate biopsy outcome. However, genetic determinants of PCA3 expression level remain unknown. To investigate the association between genetic variants and PCA3 mRNA level, a genome-wide association study was conducted in 1371 men of European descent in the REduction by DUtasteride of prostate Cancer Events trial. First-voided urine specimens containing prostate cells were obtained after digital rectal examination. The PROGENSA PCA3 assay was used to determine PCA3 score in the urinary samples. A linear regression model was used to detect the associations between (single nucleotide polymorphisms) SNPs and PCA3 score under an additive genetic model, adjusting for age and population stratification. Two SNPs, rs10993994 in β-microseminoprotein at 10q11.23 and rs10424878 in kallikrein-related peptidase 2 at 19q13.33, were associated with PCA3 score at genome-wide significance level (P = 1.22 x 10-9 and 1.06 x 10-8, respectively). Men carrying the rs10993994 “T” allele or rs10424878 “A” allele had higher PCA3 score compared with men carrying rs10993994 “C” allele or rs10424878 “G” allele (β = 1.25 and 1.24, respectively). This is the first comprehensive search for genetic determinants of PCA3 score. The novel loci identified may provide insight into the molecular mechanisms of PCA3 expression as a potential marker of PCa.
Genome-wide association studies (GWAS) have identified ∼30 single-nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. To test the hypothesis that other sequence variants in the genome may interact with those 32 known PCa risk-associated SNPs identified from GWAS to affect PCa risk, we performed a systematic evaluation among three existing PCa GWAS populations: CAncer of the Prostate in Sweden population, a Johns Hopkins Hospital population, and the Cancer Genetic Markers of Susceptibility population, with a total sample size of 4723 PCa cases and 4792 control subjects. Meta-analysis of the interaction term between each of those 32 SNPs and SNPs in the genome was performed in three PCa GWAS populations. The most significant interaction detected was between rs12418451 in MYEOV and rs784411 in CEP152, with a Pinteraction of 1.15 × 10−7 in the meta-analysis. In addition, we emphasized two pairs of interactions with potential biological implication, including an interaction between rs7127900 near insulin-like growth factor-2 (IGF2)/IGF2AS and rs12628051 in TNRC6B, with a Pinteraction of 3.39 × 10−6 and an interaction between rs7679763 near TET2 and rs290258 in SYK, with a Pinteraction of 1.49 × 10−6. Those results show statistical evidence for novel loci interacting with known risk-associated SNPs to modify PCa risk. The interacting loci identified provide hints on the underlying molecular mechanism of the associations with PCa risk for the known risk-associated SNPs. Additional studies are warranted to further confirm the interaction effects detected in this study.
Genome-wide association studies (GWAS) have identified approximately three dozen single nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. Despite the reproducibility of these associations, the molecular mechanism for most of these SNPs has not been well elaborated as most lie within non-coding regions of the genome. Androgens play a key role in prostate carcinogenesis. Recently, using ChIP-on-chip technology, 22,447 androgen receptor (AR) binding sites have been mapped throughout the genome, greatly expanding the genomic regions potentially involved in androgen-mediated activity.
To test the hypothesis that sequence variants in AR binding sites are associated with PCa risk, we performed a systematic evaluation among two existing PCa GWAS cohorts; the Johns Hopkins Hospital and the Cancer Genetic Markers of Susceptibility (CGEMS) study population. We demonstrate that regions containing AR binding sites are significantly enriched for PCa risk-associated SNPs, i.e. more than expected by chance alone. In addition, compared with the entire genome, these newly observed risk-associated SNPs in these regions are significantly more likely to overlap with established PCa risk-associated SNPs from previous GWAS. These results are consistent with our previous finding from a bioinformatics analysis that one-third of the 33 known PCa risk-associated SNPs discovered by GWAS are located in regions of the genome containing AR binding sites.
The results to date provide novel statistical evidence suggesting an androgen-mediated mechanism by which some PCa associated SNPs act to influence PCa risk. However, these results are hypothesis generating and ultimately warrant testing through in-depth molecular analyses.
AR; prostate cancer; GWAS; pathway association study
CABIN1 acts as a negative regulator of p53 by keeping p53 in an inactive state on chromatin. Genotoxic stress causes rapid dissociation of CABIN1 and activation of p53. However, its molecular mechanism is still unknown. Here, we reveal the phosphorylation- and ubiquitination-dependent degradation of CABIN1 upon DNA damage, releasing p53 for transcriptional activation. The DNA-damage-signaling kinases, ATM and CHK2, phosphorylate CABIN1 and increase the degradation of CABIN1 protein. Knockdown or overexpression of these kinases influences the stability of CABIN1 protein showing that their activity is critical for degradation of CABIN1. Additionally, CABIN1 was found to undergo ubiquitin-dependent proteasomal degradation mediated by the CRL4DDB2 ubiquitin ligase complex. Both phosphorylation and ubiquitination of CABIN1 appear to be relevant for controlling the level of CABIN1 protein upon genotoxic stress.
Percentage of free-to-total prostate-specific antigen (%fPSA) is an independent predictor of risk for prostate cancer among men with modestly elevated level of total PSA (tPSA) in blood. Physiological and pathological factors have been shown to influence the %fPSA value and diagnostic accuracy.
To evaluate genetic determinants of %fPSA, we conducted a genome-wide association study of serum %fPSA by genotyping 642,584 single nucleotide polymorphisms (SNPs) in 3192 men of European ancestry, each with a tPSA level of 2.5 to 10 ng/ml, that were recruited in the REduction by DUtasteride of Prostate Cancer Events study. Single nucleotide polymorphisms (SNPs) with P < 10-5 were further evaluated among the controls of a population-based case-control study in Sweden (2899 prostate cancer cases and 1722 male controls), including 464 controls having tPSA levels of 2.5 to 10 ng/ml.
We identified two loci that were associated with %fPSA at a genome-wide significance level (P <5 x 10-8). The first associated SNP was rs3213764 (P = 6.45 x 10-10), a nonsynonymous variant (K530R) in the ATF7IP gene at 12p13. This variant was also nominally associated with tPSA (P = .015). The second locus was rs1354774 (P = 1.25 x 10-12), near KLK2 at 19q13, which was not associated with tPSA levels, and is separate from the rs17632542 locus at KLK3 that was previously associated with tPSA levels and prostate cancer risk. Neither rs3213764 nor rs1354774 was associated with prostate cancer risk or aggressiveness.
These findings demonstrate that genetic variants at ATF7IP and KLK2 contribute to the variance of %fPSA.
Prostate-specific antigen (PSA) screening is growing in popularity in China, but its impact on biopsy characteristics and outcomes are poorly understood.
Our objective was to characterize prostate biopsy outcomes and trends in Chinese men over a 10-year period, since the increasing use of PSA tests.
All men (n = 1,650) who underwent prostate biopsy for PCa at Huashan Hospital, Shanghai, China from 2003–2011 were evaluated. Demographic and clinical information was collected for each patient, including age, digital rectal examination (DRE), transrectal ultrasound (prostate volume and nodule), total prostate-specific antigen (tPSA) levels and free PSA ratio (fPSA/tPSA) prior to biopsy. Prostate biopsy was performed using six cores before October 2007 or ten cores thereafter. Logistic regression and multivariate analysis were used to evaluate our data.
The overall positive rate of prostate biopsy for PCa was 47% and the rate decreased significantly over the years from 74% in 2003 to 33% in 2011 (P-trend = 0.004) . Age at diagnosis was slightly increased (P-trend = 0.04) while fPSA/tPSA was significantly decreased (P-trend = 1.11×10-5). A statistically significant trend was not observed for tPSA levels, prostate volume, or proportion of positive nodule. The model including multiple demographic and clinical variables (i.e., age, DRE, tPSA, fPSA/tPSA and transrectal ultrasound results) (AUC = 0.93) statistically outperformed models that included only PSA (AUC = 0.85) or fPSA/tPSA (AUC = 0.66) to predict PCa risks (P<0.05). Similar results were observed in a subgroup of men whose tPSA levels were lower than 20 ng/mL (AUC = 0.87, vs. AUC of tPSA = 0.62, P<0.05).
Detection rates of PCa and high-grade PCa among men that underwent prostate biopsy at the institution has decreased significantly in the past 10 years, likely due to increasing use of PSA tests. Predictive performance of demographic and clinical variables of PCa was excellent. These variables should be used in clinics to determine the need for prostate biopsy.
Long non-coding RNAs (lncRNAs), representing a large proportion of non-coding transcripts across the human genome, are evolutionally conserved and biologically functional. At least one-third of the phenotype-related loci identified by genome-wide association studies (GWAS) are mapped to non-coding intervals. However, the relationships between phenotype-related loci and lncRNAs are largely unknown. Utilizing the 1000 Genomes data, we compared single-nucleotide polymorphisms (SNPs) within the sequences of lncRNA and protein-coding genes as defined in the Ensembl database. We further annotated the phenotype-related SNPs reported by GWAS at lncRNA intervals. Because prostate cancer (PCa) risk-related loci were enriched in lncRNAs, we then performed meta-analysis of two existing GWAS for discovery and an additional sample set for replication, revealing PCa risk-related loci at lncRNA regions. The SNP density in regions of lncRNA was similar to that in protein-coding regions, but they were less polymorphic than surrounding regions. Among the 1998 phenotype-related SNPs identified by GWAS, 52 loci were located directly in lncRNA intervals with a 1.5-fold enrichment compared with the entire genome. More than a 5-fold enrichment was observed for eight PCa risk-related loci in lncRNA genes. We also identified a new PCa risk-related SNP rs3787016 in an lncRNA region at 19q13 (per allele odds ratio = 1.19; 95% confidence interval: 1.11–1.27) with P value of 7.22 × 10−7. lncRNAs may be important for interpreting and mining GWAS data. However, the catalog of lncRNAs needs to be better characterized in order to fully evaluate the relationship of phenotype-related loci with lncRNAs.
The molecular mechanisms for the GWAS-identified prostate cancer (PCa) risk-associated SNPs remain largely unexplained. One recent finding that the PCa risk SNPs are enriched in genomic regions containing androgen receptor (AR) binding sites has suggested altered AR signaling as a potentially important mechanism.
To explore novel associations by leveraging this knowledge, we utilized a meta-analysis previously performed over SNPs harbored in ChIP-on-chip identified AR binding genomic regions using the GWAS data from the Johns Hopkins Hospital (JHH) and the Cancer Genetic Markers of Susceptibility (CGEMS) study, and subsequently evaluated the top associations in a third population from the CAncer of the Prostate in Sweden (CAPS) study.
One SNP (rs4919743: G>A), located at the KRT8 locus at 12q13.13 which encodes a keratin protein (K8) long used as a prostate epithelial malignancy marker and implicated in the tumorigenesis of several cancer types, was identified to be associated with PCa risk. The frequency of its minor “A” allele was consistently higher in PCa cases than in controls in all three study populations, with a combined odds ratio of 1.22 (95% CI: 1.13–1.32) and an overall P-value of 4.50 × 10−7 (Bonferroni-corrected P = 0.006).
We have identified a novel genetic locus that is associated with PCa risk.
This study illustrated the great potential of prior biological knowledge in facilitating the search for novel disease-associated genetic loci. This finding warrants further replication in other studies.
androgen receptor; GWAS; keratin 8; prostate cancer; SNPs
Many differentially methylated genes have been identified in prostate cancer (PCa), primarily using candidate gene-based assays. Recently, several global DNA methylation profiles have been reported in PCa, however, each of these has weaknesses in terms of ability to observe global DNA methylation alterations in PCa. We hypothesize that there remains unidentified aberrant DNA methylation in PCa, which may be identified using higher resolution assay methods. We used the newly developed Illumina HumanMethylation450 BeadChip in PCa (n = 19) and adjacent normal tissues (n = 4) and combined these with gene expression data for identifying new DNA methylation that may have functional consequences in PCa development and progression. We also confirmed our methylation results in an independent data set. Two aberrant DNA methylation genes were validated among an additional 56 PCa samples and 55 adjacent normal tissues. A total 28,735 CpG sites showed significant differences in DNA methylation (FDR adjusted P<0.05), defined as a mean methylation difference of at least 20% between PCa and normal samples. Furthermore, a total of 122 genes had more than one differentially methylated CpG site in their promoter region and a gene expression pattern that was inverse to the direction of change in DNA methylation (e.g. decreased expression with increased methylation, and vice-versa). Aberrant DNA methylation of two genes, AOX1 and SPON2, were confirmed via bisulfate sequencing, with most of the respective CpG sites showing significant differences between tumor samples and normal tissues. The AOX1 promoter region showed hypermethylation in 92.6% of 54 tested PCa samples in contrast to only three out of 53 tested normal tissues. This study used a new BeadChip combined with gene expression data in PCa to identify novel differentially methylated CpG sites located within genes. The newly identified differentially methylated genes may be used as biomarkers for PCa diagnosis.
The p53 tumor suppressor function can be compromised in many tumors by the cellular antagonist HDM2 and human papillomavirus oncogene E6 that induce p53 degradation. Restoration of p53 activity has strong therapeutic potential. Here, we identified TSC-22 as a novel p53-interacting protein and show its novel function as a positive regulator of p53. We found that TSC-22 level was significantly down-regulated in cervical cancer tissues. Moreover, over-expression of TSC-22 was sufficient to inhibit cell proliferation, promote cellular apoptosis in cervical cancer cells and suppress growth of xenograft tumors in mice. Expression of also TSC-22 enhanced the protein level of p53 by protecting it from poly-ubiquitination. When bound to the motif between amino acids 100 and 200 of p53, TSC-22 inhibited the HDM2- and E6-mediated p53 poly-ubiquitination and degradation. Consequently, ectopic over-expression of TSC-22 activated the function of p53, followed by increased expression of p21Waf1/Cip1 and PUMA in human cervical cancer cell lines. Interestingly, TSC-22 did not affect the interaction between p53 and HDM2. Knock-down of TSC-22 by small interfering RNA clearly enhanced the poly-ubiquitination of p53, leading to the degradation of p53. These results suggest that TSC-22 acts as a tumor suppressor by safeguarding p53 from poly-ubiquitination mediated-degradation.
The genetic determinants for aggressiveness of prostate cancer (PCa) are poorly understood. Copy-number variations (CNVs) are one of the major sources for genetic diversity and critically modulate cellular biology and human diseases. We hypothesized that CNVs may be associated with PCa aggressiveness. To test this hypothesis, we conducted a genome-wide common CNVs analysis in 448 aggressive and 500 nonaggressive PCa cases recruited from Johns Hopkins Hospital (JHH1) using Affymetrix 6.0 arrays. Suggestive associations were further confirmed using single-nucleotide polymorphisms (SNPs) that tagged the CNVs of interest in an additional 2895 aggressive and 3094 nonaggressive cases, including those from the remaining case subjects of the JHH study (JHH2), the NCI Cancer Genetic Markers of Susceptibility (CGEMS) Study, and the CAncer of the Prostate in Sweden (CAPS) Study. We found that CNP2454, a 32.3 kb deletion polymorphism at 20p13, was significantly associated with aggressiveness of PCa in JHH1 [odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.01–1.68; P = 0.045]. The best-tagging SNP for CNP2454, rs2209313, was used to confirm this finding in both JHH1 (P = 0.045) and all confirmation study populations combined (P = 1.77 × 10−3). Pooled analysis using all 3353 aggressive and 3584 nonaggressive cases showed the T allele of rs2209313 was significantly associated with an increased risk of aggressive PCa (OR = 1.17, 95% CI: 1.07–1.27; P = 2.75 × 10−4). Our results indicate that genetic variations at 20p13 may be responsible for the progression of PCa.
A functional link is identified between Cdo and Stim1 that leads to NFATc3 activation. Stim1 is required for muscle differentiation via activation of the calcineurin/NFAT pathway. The netrin-2–mediated activation of NFATc3 is coincident with an interaction between Cdo and Stim1 via ERK-mediated phosphorylation of Stim1 at Ser-575.
The promyogenic cell surface molecule Cdo is required for activation of extracellular signal-regulated kinase (ERK) and nuclear factor of activated T cells c3 (NFATc3) induced by netrin-2 in myogenic differentiation. However, the molecular mechanism leading to NFATc3 activation is unknown. Stromal interaction molecule 1 (Stim1), an internal calcium sensor of the endoplasmic reticulum store, promotes myogenesis via activation of NFATc3. In this study we investigated the functional interaction between Cdo and Stim1 in myogenic differentiation. Overexpression and depletion of Stim1 enhanced or decreased myotube formation, respectively. Of interest, Stim1 protein levels were decreased in Cdo-deficient perinatal hindlimb muscles or primary myoblasts; this correlates with defective NFATc3 activation in Cdo−/− myoblasts upon differentiation. Forced activation of NFATc3 by overexpression of calcineurin restored differentiation of Cdo-depleted C2C12 myoblasts. Furthermore, Cdo and Stim1 formed a complex in 293T cells or in differentiating C2C12 myoblasts. The netrin-2–mediated NFATc3 activation was coincident with robust interactions between Cdo and Stim1 in myoblasts and the ERK-mediated Stim1 phosphorylation at serine 575. The serine 575 phosphorylation was enhanced in C2C12 cells upon differentiation, and the alanine substitution of serine 575 failed to restore differentiation of Stim1-depleted myoblasts. Taken together, the results indicate that cell adhesion signaling triggered by netrin-2/Cdo induces Stim1 phosphorylation at serine 575 by ERK, which promotes myoblast differentiation.
Verbal communication depends on a good function of voice and speech organs. Some of the voice characteristics of deaf people differ considerably from those of speakers with normal hearing. After cochlear implantation (CI), auditory control of voice production is possible and the quality of the voice is improved. CI improves quality of voice, speech and hearing with deafness. The aim of our study was to investigate the relationship between acoustic analysis before CI and the speech intelligibility before and after CI.
Twelve prelingually deafened children implanted unilaterally at the age of 3.4-9 years were included in the study. For all of the children an acoustic analysis of the Slovene vowel 'a' was performed before CI. The fundamental frequency (F0), jitter, shimmer and noise-to-harmonic ratio (NHR) were studied before the implantation. For all of the children the speech intelligibility was performed before and 12 months after CI. Preoperative hearing was divided on existing residual hearing. The results of the acoustic analyses and speech intelligibility before and after CI were compared for preoperative hearing. The results of the speech intelligibility were compared for the age of operation and preoperative acoustic analysis (F0, jitter, shimmer, NHR).
Preoperative hearing had no influence on preoperative voice analysis. The children with residual hearing had a high grade of speech intelligibility before and after CI. The preoperative shimmer had positive correlation with postoperative 12 month speech intelligibility (r=0.618, P=0.032). The preoperative jitter had positive correlation with postoperative 12 month speech intelligibility, but was not statistically significant (r=0.479, P=0.116).
Shimmer on preoperative voice analyses had influence on speech intelligibility after CI.
Cochlear implantation; Jitter; Shimmer; Noise-to-harmonic ratio; Speech intelligibility
Prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) are continuously being discovered. Their ability to identify men at high risk and the impact of increasing numbers of SNPs on predictive performance are not well understood.
Absolute risk for PCa was estimated in a population-based case-control study in Sweden (2,899 cases and 1,722 controls) using family history and three sets of sequentially discovered PCa risk-associated SNPs. Their performance in predicting PCa was assessed by positive predictive values (PPV) and sensitivity.
SNPs and family history were able to differentiate individual risk for PCa and identify men at higher risk; ~18% and ~8% of men in the study had 20-year (55–74 years) absolute risks that were two-fold (0.24) or three-fold (0.36) greater than the population median risk (0.12), respectively. When predictive performances were compared at absolute risk cutoffs of 0.12, 0.24 or 0.36, PPV increased considerably (~20%, ~30% and ~37%, respectively) while sensitivity decreased considerably (~55%, ~20% and ~10%, respectively). In contrast, when increasing numbers of SNPs (5, 11 and 28 SNPs) were used in risk prediction, PPV approached a constant value while sensitivity increased steadily.
SNPs discovered to date are suitable for risk prediction while additional SNPs discovered in the future may identify more subjects at higher risk. Men identified as high-risk by SNP-based testing may be targeted for PCa screening or chemoprevention. The clinical impact on improving the effectiveness of these interventions can be and should be assessed.
Absolute risk; SNPs; association; screening; chemoprevention
Genome-wide association studies (GWAS) have led to the discovery of multiple SNPs that are associated with prostate cancer (PCa) risk. These SNPs may potentially be used for risk prediction. To date, there is not a stable estimate of their effect on PCa risk and their contribution to the genetic variation both of which are important for future risk prediction.
A literature review was conducted to identify SNPs associated with PCa risk with the following criteria: (1) GWAS in the Caucasian population; (2) SNPs with p-value < 1.0×10−6; and (3) one SNP from each independent LD block. A meta-analysis was performed to estimate combined odds ratio (OR) and its 95% confidence interval (CI) for the identified SNPs. The proportion of total genetic variance that is attributable by each of these SNPs was also estimated.
Thirty PCa risk-associated SNPs were identified. These SNPs had OR estimates between 1.12 – 1.47 except for marker rs16901979 (OR = 1.80). Significant heterogeneity in OR estimates was found among different studies for 13 SNPs. The proportion of total genetic variance attributed by each SNP ranged between 0.2% – 0.9%. These 30 SNPs explained ~13 .5% of the total genetic variance of PCa risk in the Caucasian population.
This study provides more stable OR estimates for PCa risk-associated SNPs, which is an important baseline for the effect of these SNPs in risk prediction. These SNPs explain a considerable proportion of genetic variance, however, the majority of genetic variance has yet to be explained.
PCa; GWAS; meta-analysis; heterogeneity; genetic variation
A fine mapping study in the HNF1B gene at 17q12 among two study populations revealed a second prostate cancer locus, ~26 kb centromeric to the first known locus (rs4430796); these are separated by a recombination hotspot. A SNP in the second locus (rs11649743) was confirmed in five additional populations, and P=1.7×10−9 for an allelic test in the seven combined studies. The association at each SNP remains significant after adjusting for the other SNP.
Several genome-wide association studies (GWAS) in populations of European descent have identified more than a dozen common genetic variants that are associated with prostate cancer risk.
To determine whether these variants are also associated with prostate cancer risk in the Chinese population, we evaluated 17 prostate cancer susceptibility loci in a population-based case-control study from Shanghai, including 288 prostate cancer cases and 155 population controls.
After adjusting for age, two of the 17 loci were significantly associated with prostate cancer risk, while the other 15 loci were suggestively associated with prostate cancer risk in this population. The strongest associations were found for chromosome 8q24 Region 2 (rs1016343: OR=2.07, 95% CI: 1.35-3.20, P=9.4×10-4) and 8q24 Region 1 (rs10090154: OR=2.07, 95% CI: 1.31-3.28, P=0.002); additional single nucleotide polymorphisms (SNPs) assessed in these two 8q24 regions were also significant (ORRegion2=1.92-2.05, P=9.4×10-4-0.003, and ORRegion1=1.77-1.81, P=0.01 for all SNPs).
Our study shows that multiple prostate cancer risk loci identified in European populations using GWAS are also associated with prostate cancer risk in Chinese men, a low-risk population with mostly clinically relevant cancers. Larger studies in Chinese and Asian populations are needed to confirm these findings and the role of these risk loci in prostate cancer etiology in Asian men.
prostate cancer; association; Asian; Chinese; 8q24
Disease risk-associated single nucleotide polymorphisms (SNPs) identified from genome-wide association studies have the potential to be used for disease risk prediction. An important feature of these risk-associated SNPs is their weak individual effect but stronger cumulative effect on disease risk. Several approaches are commonly used to model the combined effect in risk prediction but their performance is unclear. We compared two methods to model the combined effect of 14 prostate cancer (PCa) risk-associated SNPs and family history for the estimation of absolute risk for PCa in a population-based case-control study in Sweden (2,899 cases and 1,722 controls). Method 1 weighs each risk allele equally using a simple method of counting the number of risk alleles while Method 2 weighs each risk SNP differently based on their respective Odds Ratios. We found considerable differences between the two methods. Absolute risk estimates from Method 1 were generally higher than that of Method 2, especially among men at higher risk. The difference in the overall discriminative performance, measured by area under the curve (AUC) of the receiver operating characteristic was small between Method 1 (0.614) and Method 2 (0.618), P = 0.20. However, the performance of these two methods in identifying high-risk individuals (two-fold or three-fold higher than average risk), measured by positive predictive values (PPV), was higher for Method 2 than Method 1. In conclusion, these results suggest that Method 2 is superior to Method 1 in estimating absolute risk if the purpose of risk prediction is to identify high-risk individuals.
Absolute risk; SNPs; association; prostate cancer; genomic medicine