Combined Effects Of Genetic Variants Research Articles

Association of Polygenic Risk Score of Alzheimer’s disease with A/T/N Biomarkers and Cognitive Decline

AbstractBackgroundPolygenic risk scores (PRS) quantify the combined effects of genetic variants to enable the prediction of an individual’s risk of developing the disease. Alzheimer’s disease (AD) is a complex disorder in which the relationship among PRS, neuropathological substrates, and related cognitive decline remain especially understudied in Asian populations. We investigated the associations of PRS with AD neuroimaging biomarkers and cognitive phenotypes in a Korean Cohort.MethodThe study included 501 older adults (264 cognitively normal [CN], 146 mild cognitive impairment [MCI], and 91 AD dementia) from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE). Comprehensive clinical and neuropsychological evaluations, as well as multi‐modal neuroimaging including 3T MRI and 11C‐PiB‐PET were administered. A subset of participants underwent 18F‐AV‐1451 PET (n = 167). Imaging phenotypes including beta‐amyloid (Aβ) positivity, global tau deposition, and adjusted hippocampal volume (HVa) were used for amyloid (A), tau (T), and neurodegeneration (N) biomarkers, respectively., which was imputed using the TOPMed reference panel. PRS was calculated using the summary statistics of a recent large‐scale GWAS study for AD by PRS‐CS. The Apolipoprotein E (APOE) region was excluded in the calculation. The associations between standardized PRS and imaging/cognitive phenotypes were examined using either multiple linear or logistic regression analysis with covariates (age and sex for neuroimaging biomarker phenotypes; age, sex and education for cognitive phenotypes).ResultPRS was significantly higher in the AD dementia group compared to the CN group. Higher PRS was associated with greater CDR‐sum‐of‐boxes (β[SE] = 0.233[0.083], t = 2.818, p = 0.005) and lower MMSE scores (β[SE] = ‐0.648[0.198], t = ‐3.271, p = 0.001). In terms of AD neuroimaging biomarkers (Figure 1), higher PRS was significantly associated with an increased likelihood of Aβ positivity (OR = 1.233, 95%CI = 1.024‐1.491), and lower HVa (β[SE] = ‐132.79[49.624], t = ‐2.676, p = 0.008), but not with global tau deposition (β[SE] = 0.075[0.048], t = 1.573, p = 0.118).ConclusionThese findings suggest that higher PRS predicts increased pathological Aβ deposition and accelerated neurodegeneration, as well as greater cognitive decline. Further investigation in larger and multiethnic samples are needed to determine generalizability to other ethnoracial populations.

The association between leptin and subclinical cardiovascular disease explained by body fat: Observational and Mendelian randomization analyses

Background and aimsLeptin has been associated with adverse effects on cardiovascular disease, but the effect of confounding by body fat in these associations remains unclear. To investigate associations between leptin and heart function and subclinical cardiovascular disease adjusted for total body fat, and to investigate the causal relation between leptin and cardiovascular disease using Mendelian randomisation. Methods and resultsLeptin concentrations, total body fat and diverse measures of subclinical cardiovascular disease were determined in participants of the Netherlands Epidemiology of Obesity study. Linear regression between leptin concentration and measures of heart function, ECG measures, and carotid intima media thickness as a measure of subclinical atherosclerosis was adjusted for potential confounding factors, and additionally including total body fat. We analysed the combined effects of genetic variants from a GWAS on leptin concentrations in publicly-available summary statistics of coronary heart disease GWAS (CARDIoGRAMplusC4D, n = 184,305). As many as 6107 men and women, mean (SD) age 56 (6) years, BMI 26 (4) kg/m2, and median leptin concentration 12.1 μg (IQR: 6.7–22.6) were included.In observational analyses, leptin was weakly associated with heart function and subclinical cardiovascular disease, but these associations attenuated when adjusting for total body fat. A doubling of genetically-determined leptin concentration was associated with an odds ratio of cardiovascular disease of 0.69 (0.37, 1.27). ConclusionObservational associations between leptin and subclinical measures of cardiovascular disease were largely explained by differences in total body fat. Results of analyses of genetically-determined leptin and coronary heart disease risk were inconclusive due to a large confidence interval.

New Trends in the Detection of Gynecological Precancerous Lesions and Early-Stage Cancers.

Simple SummaryThis review deals with the prospects of early diagnostics in cervical, endometrial, and ovarian cancers. Progress in cancer research has enabled the rapid development of cancer diagnostics, treatments, and preventions. Indeed, the current situation in genital tract tumors reflects the trend in contemporary oncology that emphasizes cancer prevention and early diagnostics. Cervical cancer screening using cytological examination has a long tradition, is highly effective, and is now being complemented with HPV triage, allowing early diagnostics even in precancerous stages due to the relative ease of accessibility of the uterine cervix. Moreover, vaccination against HPV, which is major cause of cervical cancer, is now recommended for both girls and boys at an early age. In contrast, endometrial and, particularly, ovarian cancers are poorly accessible by sampling, and neither prevention nor screening methods readily exist. Thus, other options leading to their early diagnostics are discussed, in which circulating biomarkers play key roles.The prevention and early diagnostics of precancerous stages are key aspects of contemporary oncology. In cervical cancer, well-organized screening and vaccination programs, especially in developed countries, are responsible for the dramatic decline of invasive cancer incidence and mortality. Cytological screening has a long and successful history, and the ongoing implementation of HPV triage with increased sensitivity can further decrease mortality. On the other hand, endometrial and ovarian cancers are characterized by a poor accessibility to specimen collection, which represents a major complication for early diagnostics. Therefore, despite relatively promising data from evaluating the combined effects of genetic variants, population screening does not exist, and the implementation of new biomarkers is, thus, necessary. The introduction of various circulating biomarkers is of potential interest due to the considerable heterogeneity of cancer, as highlighted in this review, which focuses exclusively on the most common tumors of the genital tract, namely, cervical, endometrial, and ovarian cancers. However, it is clearly shown that these malignancies represent different entities that evolve in different ways, and it is therefore necessary to use different methods for their diagnosis and treatment.

Association of HOTAIR (rs920778 and rs1899663) and NME1 (rs16949649 and rs2302254) gene polymorphisms with breast cancer risk in India

Until now, no study has reported the combined effect of genetic variants of HOTAIR and NME1 towards breast cancer (BC) pathogenesis. Hence, the aim of the present study is to determine the risk of breast cancer development with HOTAIR (rs920778 C>T and rs1899663 G>T) and NME1 (rs16949649 T>C and rs2302254 C>T) genetic polymorphisms in the Indian population for the first time. To investigate the genetic association of these four SNPs, we conducted a population-based case-control study involving 1011 subjects (502 histologically confirmed BC patients and 509 disease-free controls) using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. HOTAIR rs920778 TC genotype elevated the risk of BC (OR=1.39, 95% CI=1.06-1.83, p=0.018) and individuals carrying the mutant allele (T) of rs1899663 had increased BC risk (OR=1.23, 95% CI=1.02-1.47, p=0.026). The presence of the NME1 rs16949649 CC genotype increased the risk of BC (OR=1.76, 95% CI=1.15-2.71, p=0.009). Moreover, the HOTAIR rs920778 variant (TC+CC) increased the risk of BC in pre-menopausal women (OR=5.86; p<0.0001). Women carrying 2 or 3 mutant alleles for the investigated SNPs were observed to have an elevated risk of BC. The results of the present study highlight the presence of significant associations between NME1 rs16949649 and HOTAIR (rs920778 and rs1899663) polymorphisms and breast cancer development in Indian women.

EQTL Mapping Using Transcription Factor Affinity.

In the last decades, thousands of common genetic variants have been associated with human diseases by genome-wide association studies (GWAS). However, the functional interpretation of GWAS hits is usually nontrivial, especially because most of them lay outside the coding genome. These noncoding variants presumably exert their effect by altering gene expression levels; therefore, expression quantitative trait loci (eQTL) mapping analyses represent an important step in understanding their functional relevance and identifying the target genes. Here we describe an alternative strategy for the detection of eQTL that takes into account the combined effect of genetic variants within regulatory regions and leverages the idea that changes in gene expression often are the consequence of the alteration of transcription factor (TF) binding.

Genetic variation in the Hippo pathway and breast cancer risk in women of African ancestry.

Gene expression changes within the Hippo pathway were found to be associated with large tumor size and metastasis in breast cancer. The combined effect of genetic variants in genes of this pathway may have a causal role in breast cancer development. We examined 7086 SNPs that were not highly correlated (r2 < 0.8) in 35 Hippo pathway genes using data from the genome-wide association study of breast cancer from the Root Consortium, which includes 3686 participants of African ancestry from Nigeria, United States of America, and Barbados: 1657 cases (403 estrogen receptor-positive [ER+], 374 ER-) and 2029 controls. Gene-level analyses were conducted using improved AdaJoint test for large-scale genetic association studies adjusting for age, study site and the first four eigenvectors from the principal component analysis. SNP-level analyses were conducted with logistic regression. The Hippo pathway was significantly associated with risk of ER+ breast cancer (pathway-level P = 0.019), with WWC1 (Padj = 0.04) being the leading gene. The pathway-level significance was lost without WWC1 (P = 0.12). rs147106204 in the WWC1 gene was the most statistically significant SNP after gene-level adjustment for multiple comparisons (OR = 0.53, 95%CI = 0.41-0.70, Padj = 0.025). We found evidence of an association between genetic variations in the Hippo pathway and ER+ breast cancer. Moreover, WWC1 was identified as the most important genetic susceptibility locus highlighting the importance of genetic epidemiology studies of breast cancer in understudied populations.

Separate and combined effects of genetic variants and pre-treatment whole blood gene expression on response to exposure-based cognitive behavioural therapy for anxiety disorders

Objectives: Exposure-based cognitive behavioural therapy (eCBT) is an effective treatment for anxiety disorders. Response varies between individuals. Gene expression integrates genetic and environmental influences. We analysed the effect of gene expression and genetic markers separately and together on treatment response.Methods: Adult participants (n ≤ 181) diagnosed with panic disorder or a specific phobia underwent eCBT as part of standard care. Percentage decrease in the Clinical Global Impression severity rating was assessed across treatment, and between baseline and a 6-month follow-up. Associations with treatment response were assessed using expression data from 3,233 probes, and expression profiles clustered in a data- and literature-driven manner. A total of 3,343,497 genetic variants were used to predict treatment response alone and combined in polygenic risk scores. Genotype and expression data were combined in expression quantitative trait loci (eQTL) analyses.Results:Expression levels were not associated with either treatment phenotype in any analysis. A total of 1,492 eQTLs were identified with q < 0.05, but interactions between genetic variants and treatment response did not affect expression levels significantly. Genetic variants did not significantly predict treatment response alone or in polygenic risk scores.Conclusions: We assessed gene expression alone and alongside genetic variants. No associations with treatment outcome were identified. Future studies require larger sample sizes to discover associations.

PACSIN2 polymorphism is associated with thiopurine-induced hematological toxicity in children with acute lymphoblastic leukaemia undergoing maintenance therapy.

Adequate maintenance therapy for childhood acute lymphoblastic leukemia (ALL), with 6-mercaptopurine as an essential component, is necessary for retaining durable remission. Interruptions or discontinuations of the therapy due to drug-related toxicities, which can be life threatening, may result in an increased risk of relapse. In this retrospective study including 305 paediatric ALL patients undergoing maintenance therapy, we systematically investigated the individual and combined effects of genetic variants of folate pathway enzymes, as well as of polymorphisms in PACSIN2 and ITPA, on drug-induced toxicities by applying a multi-analytical approach including logistic regression (LR), classification and regression tree (CART) and generalized multifactor dimensionality reduction (GMDR). In addition to the TPMT genotype, confirmed to be a major determinant of drug related toxicities, we identified the PACSIN2 rs2413739TT genotype as being a significant risk factor for 6-MP-induced toxicity in wild-type TPMT patients. A gene-gene interaction between MTRR (rs1801394) and MTHFR (rs1801133) was detected by GMDR and proved to have an independent effect on the risk of stomatitis, as shown by LR analysis. To our knowledge, this is the first study showing PACSIN2 genotype association with hematological toxicity in ALL patients undergoing maintenance therapy.

Combined effect of genetic variants in the GluN2B coding gene (GRIN2B) on prefrontal function during working memory performance.

The GluN2B subunit of N-methyl-d-aspartate receptors is crucially involved in the physiology of the prefrontal cortex during working memory (WM). Consistently, genetic variants in the GluN2B coding gene (GRIN2B) have been associated with cognitive phenotypes. However, it is unclear how GRIN2B genetic variation affects gene expression and prefrontal cognitive processing. Using a composite score, we tested the combined effect of GRIN2B variants on prefrontal activity during WM performance in healthy subjects. We computed a composite score to combine the effects of single nucleotide polymorphisms on post-mortem prefrontal GRIN2B mRNA expression. We then computed the composite score in independent samples of healthy participants in a peripheral blood expression study (n = 46), in a WM behavioural study (n = 116) and in a WM functional magnetic resonance imaging study (n = 122). Five polymorphisms were associated with GRIN2B expression: rs2160517, rs219931, rs11055792, rs17833967 and rs12814951 (all corrected p < 0.05). The score computed to account for their combined effect reliably indexed gene expression. GRIN2B composite score correlated negatively with intelligence quotient, WM behavioural efficiency and dorsolateral prefrontal cortex activity. Moreover, there was a non-linear association between GRIN2B genetic score and prefrontal activity, i.e. both high and low putative genetic score levels were associated with high blood oxygen level-dependent signals in the prefrontal cortex. Multiple genetic variants in GRIN2B are jointly associated with gene expression, prefrontal function and behaviour during WM. These results support the role of GRIN2B genetic variants in WM prefrontal activity in human adults.

Accuracy of Gene Scores when Pruning Markers by Linkage Disequilibrium

Objective: Gene scores are often used to model the combined effects of genetic variants. When variants are in linkage disequilibrium, it is common to prune all variants except the most strongly associated. This avoids duplicating information but discards information when variants have independent effects. However, joint modelling of correlated variants increases the sampling error in the gene score. In recent applications, joint modelling has offered only small improvements in accuracy over pruning. We aimed to quantify the relationship between pruning and joint modelling in relation to sample size. Methods: We derived the coefficient of determination R² for a gene score constructed from pruned markers, and for one constructed from correlated markers with jointly estimated effects. Results: Pruned scores tend to have slightly lower R² than jointly modelled scores, but the differences are small at sample sizes up to 100,000. If the proportion of correlated variants is high, joint modelling can obtain modest improvements asymptotically. Conclusions: The small gains observed to date from joint modelling can be explained by sample size. As studies become larger, joint modelling will be useful for traits affected by many correlated variants, but the improvements may remain small. Pruning remains a useful heuristic for current studies.

Genetic risk assessment for cardiovascular disease with seven genes associated with plasma C-reactive protein concentrations in Asian populations

Plasma C-reactive protein (CRP) level is a predictor of cardiovascular risk. We performed a meta-analysis on the effect of 12 single-nucleotide polymorphisms (SNPs) within 8 candidate loci in 36 752 Asians. In addition, we created weighted genetic risk scores (wGRSs) to evaluate the combined effects of genetic variants, which were suggested in the meta-analysis, for predicting the risks of elevated CRP levels as well as increased risks of hypertension and cardiovascular disease (CVD) in 748 Koreans. Nine SNPs located in seven genes, CRP, IL6R, GCKR, IL6, CYP17A1, HNF1A and APOE, were significantly associated with circulating CRP levels in this meta-analysis. Two SNPs, rs7310409 (HNF1A, P=3.4 × 10(-23)) and rs7553007 (CRP, P=3.4 × 10(-17)), had the most significant effects on CRP levels; and two SNPs, rs2097677 (IL6) and rs1004467 (CYP17A1) have never been found in the previous European meta-analysis. In Koreans, the subjects in the highest wGRS group had an ∼2.5-fold higher mean CRP level compared with those in the lowest wGRS group (P=2.1 × 10(-5)). We observed significant increases in the risks of hypertension (odds ratio=2.18, P=0.006) and CVD (odds ratio=9.59, P=3.2 × 10(-6)) among the subjects in the highest wGRS group. The wGRS models specific to Koreans may warrant further validation to be used as a proxy for the risk of CVD in Asians.

Specific glial functions contribute to schizophrenia susceptibility.

Schizophrenia is a highly polygenic brain disorder. The main hypothesis for disease etiology in schizophrenia primarily focuses on the role of dysfunctional synaptic transmission. Previous studies have therefore directed their investigations toward the role of neuronal dysfunction. However, recent studies have shown that apart from neurons, glial cells also play a major role in synaptic transmission. Therefore, we investigated the potential causal involvement of the 3 principle glial cell lineages in risk to schizophrenia. We performed a functional gene set analysis to test for the combined effects of genetic variants in glial type-specific genes for association with schizophrenia. We used genome-wide association data from the largest schizophrenia sample to date, including 13 689 cases and 18 226 healthy controls. Our results show that astrocyte and oligodendrocyte gene sets, but not microglia gene sets, are associated with an increased risk for schizophrenia. The astrocyte and oligodendrocyte findings are related to astrocyte signaling at the synapse, myelin membrane integrity, glial development, and epigenetic control. Together, these results show that genetic alterations underlying specific glial cell type functions increase susceptibility to schizophrenia and provide evidence that the neuronal hypothesis of schizophrenia should be extended to include the role of glia.

Joint Effect of Genetic and Lifestyle Risk Factors on Type 2 Diabetes Risk among Chinese Men and Women

More than 40 genetic susceptibility loci have been reported for type 2 diabetes (T2D). Recently, the combined effect of genetic variants has been investigated by calculating a genetic risk score. We evaluated 36 genome-wide association study (GWAS) identified SNPs in 2,679 T2D cases and 3322 controls in middle-age Han Chinese. Fourteen SNPs were significantly associated with T2D in analysis adjusted for age, sex and BMI. We calculated two genetic risk scores (GRS) (GRS1 with all the 36 SNPs and GRS2 with the 14 SNPs significantly associated with T2D). The odds ratio for T2D with each GRS point (per risk allele) was 1.08 (95% CI: 1.06–1.09) for GRS1 and 1.15 (95% CI: 1.13–1.18) for GRS2. The OR for quintiles were 1.00, 1.26, 1.69, 1.95 and 2.18 (P<0.0001) for GRS1 and 1.00, 1.33, 1.60, 2.03 and 2.80 (P<0.001) for GRS2. Participants in the higher tertile of GRS1 and the higher BMI category had a higher risk of T2D compared to those on the lower tertiles of the GRS1 and of BMI (OR = 11.08; 95% CI: 7.39–16.62). We found similar results when we investigated joint effects between GRS1 and WHR terciles and exercise participation. We finally investigated the joint effect between tertiles of GRSs and a composite high risk score (no exercise participation and high BMI and WHR) on T2D risk. We found that compared to participants with low GRS1 and no high risk factors for T2D, those with high GRS1 and three high risk factors had a higher risk of T2D (OR = 13.06; 95% CI: 8.65–19.72) but the interaction factor was of marginal significance. The association was accentuated when we repeated analysis with the GRS2. In conclusion we found an association between GRS and lifestyle factors, alone and in combination, contributed to the risk of and T2D among middle age Chinese.

Analytical and simulation methods for estimating the potential predictive ability of genetic profiling: a comparison of methods and results

Various modeling methods have been proposed to estimate the potential predictive ability of polygenic risk variants that predispose to various common diseases. However, it is unknown whether differences between them affect their conclusions on predictive ability. We reviewed input parameters, assumptions and output of the five most common methods and compared their estimates of the area under the receiver operating characteristic (ROC) curve (AUC) using hypothetical data representing effect sizes and frequencies of genetic variants, population disease risk and number of variants. To assess the accuracy of the estimated AUCs, we aimed to reproduce the AUCs of published empirical studies. All methods assumed that the combined effect of genetic variants on disease risk followed a multiplicative risk model of independent genetic effects, but they either assumed per allele, per genotype or dominant/recessive effects for the genetic variants. Modeling strategy and input parameters differed. Methods used simulation analysis or analytical formulas with effect sizes quantified by odds ratios (ORs) or relative risks. Estimated AUC values were similar for lower ORs (<1.2). When AUCs were larger (>0.7) due to variants with strong effects, differences in estimated AUCs between methods increased. The simulation methods accurately reproduced the AUC values of empirical studies, but the analytical methods did not. We conclude that despite differences in input parameters, the modeling methods estimate similar AUC for realistic values of the ORs. When one or more variants have stronger effects and AUC values are higher, the simulation methods tend to be more accurate.

Lrrk2 S1647T and BDNF V66M interact with environmental factors to increase risk of Parkinson’s disease

Parkinson’s disease (PD) is a complex neurodegenerative disorder contributed by both environmental and genetic factors. The inconsistent findings in genetic association studies may be due to unrecognized interactions with other genetic or environmental factors. Therefore, we assessed the combined effects of genetic variants of three candidate genes of familial PD and environmental exposure on risk of PD in Taiwanese population. A total of 744 study subjects, 453 PD cases and 291 ethnicity-matched controls, were included. The genetic variants on the PINK1, BDNF, and LRRK2 genes were sequenced accordingly. We used a regression approach based on a generalized linear model to evaluate single-locus genotype effects and detection of gene–environment interaction by incorporating interaction terms in the model. We found a significant difference of LRRK2 G2385R and R1628P between PD patients and controls, which confirmed our previous findings. A logistic regression model which included gene–environment interactions was applied. Notably, we identified the variant of LRRK2 T4939A (S1647T) (TT, OR = −0.36, p = 0.03) is associated with increased PD risk, after considering the interaction effects with environmental factors in the model. Additionally, two novel interactions were detected: pesticide exposure with BDNF (OR = −0.85, p = 0.01) and to a lesser extent, with PINK1 (OR = 1.99, p = 0.07). Our findings reinforced the importance that PD risk is modulated by both genetic and environmental exposures. LRRK2 S1647T may be another risk factor for PD development in our ethnicity while considering the joint interaction effects with environmental factors.

Abstract C118: Influence of CYP2D6 phenotype on tamoxifen-treatment outcome in women with metastatic breast cancer

Abstract Introduction: Cytochrome P450 2D6 (CYP2D6) plays a crucial role in the metabolism of tamoxifen into the active metabolite endoxifen. Genetic variation in the CYP2D6 gene and co-administration of CYP2D6 inhibiting medication markedly reduce endoxifen plasma concentrations in patients. The impact hereof on the outcome of tamoxifen therapy in metastatic breast cancer is insufficiently known. In this cohort study, we examined the effect of CYP2D6 predicted phenotype (the combined effect of genetic variants and concomitant use of CYP2D6 inhibiting medication) on time to progression (TTP) and overall survival (OS) in women using tamoxifen for metastatic breast cancer was examined. Methods: We selected patients treated with tamoxifen (40mg/day) for hormone receptor positive metastatic breast cancer of whom blood samples for pharmacogenetic analysis (CYP2D6*3,*4,*5,*6) were available. Patient charts were reviewed to assess patient and tumor characteristics, TTP, OS, and use of CYP2D6 inhibitors. Results: Patients with poor CYP2D6 metabolizer phenotype (PMs) had a worse OS compared to extensive metabolizers (EMs) (HR = 2.11; P=0.031; 95% CI: 1.07–4.15, see Table). Patients with an intermediate (IM) and extensive metabolizer (EM) phenotype had comparable TTP and OS, and were further considered as one group in the Kaplan-Meier estimates. For PMs, the Kaplan-Meier estimate demonstrated a shorter TTP compared to the combined group of IMs and EMs: 1.7 years (95% CI: 0.9–2.5) versus 2.9 years (95% CI: 2.3 – 3.6) respectively (P = 0.089). Overall survival of the group of IM/EM patients was significantly longer than for PM patients, being 9.9 years (95% CI: 8.2–11.6) versus 5.4 years (95% CI: 3.7–7.1), respectively (P=0.012). Co-administration of CYP2D6 inhibitors alone was also associated with a worse OS (HR=3.55; P=0.002; 95% CI: 1.59–7.96) and a worse TTP (HR=2.97; P=0.008; 95% CI: 1.33–6.67) compared to patients without CYP2D6 inhibitors. Conclusions: CYP2D6 phenotype is an important predictor of treatment outcome in women treated with tamoxifen for hormone receptor positive metastatic breast cancer. Co-administration of CYP2D6 inhibitors worsens outcome of tamoxifen therapy, and should therefore be discouraged. Effect of CYP2D6 phenotype on TTP and OS CYP2D6 phenotype Time to progression (TTP) Overall Survival(OS) Cases (n=99) Cases (n=99) HR (95% CI) HR (95% CI) P-value P-value EM n=50 n=33 HR=1.00 (ref) HR=1.00 (ref) IM n=36 n=22 HR=1.05 (0.67–1.65) HR=0.88 (0.51–1.53) P=0.82 P=0.66 PM n=13 n=12 HR=1.74 (0.92–3.28) HR=2.11 (1.07–4.15) P=0.09 P=0.03 Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C118.