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
Complement C3 and C4 play key roles in the main physiological activities of complement system, and their deficiencies or over-expression are associated with many clinical infectious or immunity diseases. A two-stage genome-wide association study (GWAS) was performed for serum levels of C3 and C4. The first stage was conducted in 1,999 healthy Chinese men, and the second stage was performed in an additional 1,496 subjects. We identified two SNPs, rs3753394 in CFH gene and rs3745567 in C3 gene, that are significantly associated with serum C3 levels at a genome-wide significance level (P = 7.33×10−11 and P = 1.83×10−9, respectively). For C4, one large genomic region on chromosome 6p21.3 is significantly associated with serum C4 levels. Two SNPs (rs1052693 and rs11575839) were located in the MHC class I area that include HLA-A, HLA-C, and HLA-B genes. Two SNPs (rs2075799 and rs2857009) were located 5′ and 3′ of C4 gene. The other four SNPs, rs2071278, rs3763317, rs9276606, and rs241428, were located in the MHC class II region that includes HLA-DRA, HLA-DRB, and HLA-DQB genes. The combined P-values for those eight SNPs ranged from 3.19×10−22 to 5.62×10−97. HBsAg-positive subjects have significantly lower C3 and C4 protein concentrations compared with HBsAg-negative subjects (P<0.05). Our study is the first GWAS report which shows genetic components influence the levels of complement C3 and C4. Our significant findings provide novel insights of their related autoimmune, infectious diseases, and molecular mechanisms.
The complement system plays important roles in the innate and adaptive immune functions. C3 and C4 participate in almost all physiological activities and activated pathways as key complement members and host defense proteins. Identifying the genes that influence serum levels of C3 and C4 may help to elucidate the factors and mechanisms underlying the complement system. The genome-wide association studies (GWAS) have shown great success in revealing robust associations in both quantitative and qualitative traits. In this study, we performed a two-stage GWAS in a large cohort from the Chinese male population to examine the roles of common genetic variants on serum C3 and C4 levels. Our research identified genetic determinants associated with the quantitative levels of C3 and C4. Overall, our study highlights an intricate regulation of complement levels and potentially reveals novel mechanisms that may be followed up with additional functional studies.
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.
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
CHK2 kinase is a key mediator in many cellular responses to genotoxic stresses including ionizing radiation and topoisomerase inhibitors. Upon ionizing radiation, CHK2 is activated by ATM kinase and regulates the S-phase and G1-S checkpoints, apoptosis, and DNA repair by phosphorylating downstream target proteins such as p53 and Brca1. In addition, CHK2 is thought to be a multi-organ cancer susceptibility gene. In this study, we used a tandem affinity purification strategy to identify proteins that interact with CHK2 kinase. CDK11p110 kinase, implicated in pre-mRNA splicing and transcription, was identified as a CHK2-interacting protein. CHK2 kinase phosphorylated CDK11p110 on serine 737 in vitro. Unexpectedly, CHK2 kinase constitutively phosphorylated CDK11p110 in a DNA damage-independent manner. At a molecular level, CDK11p110 phosphorylation was required for homodimerization without affecting its kinase activity. Overexpression of CHK2 promoted pre-mRNA splicing. Conversely, CHK2 depletion decreased endogenous splicing activity. Mutation of the phosphorylation site in CDK11p110 to alanine abrogated its splicing activating activity. These results provide the first evidence that CHK2 kinase promotes pre-mRNA splicing via phosphorylating CDK11p110.
CHK2; pre-mRNA splicing; CDK11; DNA damage response pathway
Transforming growth factor β (TGF-β)-activated kinase 1 (TAK1) is a key regulator in the signals transduced by proinflammatory cytokines and Toll-like receptors (TLRs). The regulatory mechanism of TAK1 in response to various tissue types and stimuli remains incompletely understood. Here, we show that ribosomal S6 kinase 1 (S6K1) negatively regulates TLR-mediated signals by inhibiting TAK1 activity. S6K1 overexpression causes a marked reduction in NF-κB and AP-1 activity induced by stimulation of TLR2 or TLR4. In contrast, S6K1−/− and S6K1 knockdown cells display enhanced production of inflammatory cytokines. Moreover, S6K1−/− mice exhibit decreased survival in response to challenge with lipopolysaccharide (LPS). We found that S6K1 inhibits TAK1 kinase activity by interfering with the interaction between TAK1 and TAB1, which is a key regulator protein for TAK1 catalytic function. Upon stimulation with TLR ligands, S6K1 deficiency causes a marked increase in TAK1 kinase activity that in turn induces a substantial enhancement of NF-κB-dependent gene expression, indicating that S6K1 is negatively involved in the TLR signaling pathway by the inhibition of TAK1 activity. Our findings contribute to understanding the molecular pathogenesis of the impaired immune responses seen in type 2 diabetes, where S6K1 plays a key role both in driving insulin resistance and modulating TLR signaling.
To identify novel effectors and markers of localized but potentially life-threatening prostate cancer (PCa), we evaluated chromosomal copy number alterations (CNAs) in tumors from patients who underwent prostatectomy and correlated these with clinicopathologic features and outcome.
CNAs in tumor DNAs from 125 prostatectomy patients in the discovery cohort were assayed with high resolution Affymetrix 6.0 SNP microarrays and then analyzed using the Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm.
The assays revealed twenty significant regions of CNAs, four of them novel, and identified the target genes of four of the alterations. By univariate analysis, seven CNAs were significantly associated with early PCa-specific mortality. These included gains of chromosomal regions that contain the genes MYC, ADAR, or TPD52 and losses of sequences that incorporate SERPINB5, USP10, PTEN, or TP53. On multivariate analysis, only the CNAs of PTEN and MYC contributed additional prognostic information independent of that provided by pathologic stage, Gleason score, and initial PSA level. Patients whose tumors had alterations of both genes had a markedly elevated risk of PCa-specific mortality (OR = 53; C.I.= 6.92–405, P = 1 × 10−4). Analyses of 333 tumors from three additional distinct patient cohorts confirmed the relationship between CNAs of PTEN and MYC and lethal PCa.
This study identified new CNAs and genes that likely contribute to the pathogenesis of localized PCa and suggests that patients whose tumors have acquired CNAs of PTEN, MYC, or both have an increased risk of early PCa-specific mortality.
prostate cancer death; PTEN; MYC; somatic DNA copy number
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
Myocyte enhancer factor 2 (MEF2) is a family of transcription factors that regulates many processes, including muscle differentiation. Due to its many target genes, MEF2D requires tight regulation of transcription activity over time and by location. Epigenetic modifiers have been suggested to regulate MEF2-dependent transcription via modifications to histones and MEF2. However, the modulation of MEF2 activity by lysine methylation, an important posttranslational modification that alters the activities of transcription factors, has not been studied. We report the reversible lysine methylation of MEF2D by G9a and LSD1 as a regulatory mechanism of MEF2D activity and skeletal muscle differentiation. G9a methylates lysine-267 of MEF2D and represses its transcriptional activity, but LSD1 counteracts it. This residue is highly conserved between MEF2 members in mammals. During myogenic differentiation of C2C12 mouse skeletal muscle cells, the methylation of MEF2D by G9a decreased, on which MEF2D-dependent myogenic genes were upregulated. We have also identified lysine-267 as a methylation/demethylation site and demonstrate that the lysine methylation state of MEF2D regulates its transcriptional activity and skeletal muscle cell differentiation.
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
Approximately 40 single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk have been identified through genome-wide association studies (GWAS). However, these GWAS-identified PCa risk-associated SNPs can explain only a small proportion of heritability (~13%) of PCa risk. Gene–gene interaction is speculated to be one of the major factors contributing to the so-called missing heritability. To evaluate the gene–gene interaction and PCa risk, we performed a two-stage genome-wide gene–gene interaction scan using a novel statistical approach named “Boolean Operation-based Screening and Testing”. In the first stage, we exhaustively evaluated all pairs of SNP–SNP interactions for ~500,000 SNPs in 1,176 PCa cases and 1,101 control subjects from the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study. No SNP–SNP interaction reached a genome-wide significant level of 4.4E–13. The second stage of the study involved evaluation of the top 1,325 pairs of SNP–SNP interactions (Pinteraction < 1.0E–08) implicated in CGEMS in another GWAS population of 1,964 PCa cases from the Johns Hopkins Hospital (JHH) and 3,172 control subjects from the Illumina iControl database. Sixteen pairs of SNP–SNP interactions were significant in the JHH population at a Pinteraction cutoff of 0.01. However, none of the 16 pairs of SNP–SNP interactions were significant after adjusting for multiple tests. The current study represents one of the first attempts to explore the high-dimensional etiology of PCa on a genome-wide scale. Our results suggested a list of SNP–SNP interactions that can be followed in other replication studies.
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.