| 1. |
- Demissie, Meaza, et al.
(författare)
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Unequal group variances in microarray data analyses
- 2008
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 24:9, s. 1168-1174
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: In searching for differentially expressed (DE) genes in microarray data, we often observe a fraction of the genes to have unequal variability between groups. This is not an issue in large samples, where a valid test exists that uses individual variances separately. The problem arises in the small-sample setting, where the approximately valid Welch test lacks sensitivity, while the more sensitive moderated t-test assumes equal variance. Methods: We introduce a moderated Welch test (MWT) that allows unequal variance between groups. It is based on (i) weighting of pooled and unpooled standard errors and (ii) improved estimation of the gene-level variance that exploits the information from across the genes. Results: When a non-trivial proportion of genes has unequal variability, false discovery rate (FDR) estimates based on the standard t and moderated t-tests are often too optimistic, while the standard Welch test has low sensitivity. The MWT is shown to (i) perform better than the standard t, the standard Welch and the moderated t-tests when the variances are unequal between groups and (ii) perform similarly to the moderated t, and better than the standard t and Welch tests when the group variances are equal. These results mean that MWT is more reliable than other existing tests over wider range of data conditions. Availability: R package to perform MWT is available at http://www.meb.ki.se/similar to yudpaw Contact: yudi.pawitan@ki.se Supplementary information: Supplementary data are available at Bioinformatics online.
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| 2. |
- Hall, Per, et al.
(författare)
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Hormone-replacement therapy influences gene expression profiles and is associated with breast-cancer prognosis : a cohort study
- 2006
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Ingår i: BMC Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 4, s. 16-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Postmenopausal hormone-replacement therapy (HRT) increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood. Methods: We obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women. Results: HRT use in patients with estrogen receptor ( ER) protein positive tumors (n = 72) was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen. Conclusion: Our findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells.
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| 3. |
- Huang, J, et al.
(författare)
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Robust smooth segmentation approach for array CGH data analysis
- 2007
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1460-2059 .- 1367-4811. ; 23:18, s. 2463-2469
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Array comparative genomic hybridization (aCGH) provides a genome- wide technique to screen for copy number alteration. The existing segmentation approaches for analyzing aCGH data are based on modeling data as a series of discrete segments with unknown boundaries and unknown heights. Although the biological process of copy number alteration is discrete, in reality a variety of biological and experimental factors can cause the signal to deviate from a stepwise function. To take this into account, we propose a smooth segmentation (smoothseg) approach. Methods: To achieve a robust segmentation, we use a doubly heavy-tailed random-effect model. The first heavy-tailed structure on the errors deals with outliers in the observations, and the second deals with possible jumps in the underlying pattern associated with different segments. We develop a fast and reliable computational procedure based on the iterative weighted least- squares algorithm with band-limited matrix inversion. Results: Using simulated and real data sets, we demonstrate how smoothseg can aid in identification of regions with genomic alteration and in classification of samples. For the real data sets, smoothseg leads to smaller false discovery rate and classification error rate than the circular binary segmentation (CBS) algorithm. In a realistic simulation setting, smoothseg is better than wavelet smoothing and CBS in identification of regions with genomic alterations and better than CBS in classification of samples. For comparative analyses, we demonstrate that segmenting the t- statistics performs better than segmenting the data.
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| 4. |
- Ivshina, Anna V., et al.
(författare)
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Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer
- 2006
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Ingår i: Cancer Research. - 0008-5472 .- 1538-7445. ; 66:21, s. 10292-10301
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Tidskriftsartikel (refereegranskat)abstract
- Histologic grading of breast cancer defines morphologic subtypes informative of metastatic potential, although not without considerable interobserver disagreement and clinical heterogeneity particularly among the moderately differentiated grade 2 (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade 1 (G1) and grade 3 (W) histology might provide a more objective measure of grade with prognostic benefit for patients with G2 disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable with that of lymph node status and tumor size. When incorporated into the Nottingham prognostic index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low- and high-grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression.
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| 5. |
- Lichtenstein, Paul, et al.
(författare)
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Common genetic determinants of schizophrenia and bipolar disorder in Swedish families : a population-based study
- 2009
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 373:9659, s. 234-239
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Tidskriftsartikel (refereegranskat)abstract
- Background Whether schizophrenia and bipolar disorder are the clinical outcomes of discrete or shared causative processes is much debated in psychiatry. We aimed to assess genetic and environmental contributions to liability for schizophrenia, bipolar disorder, and their comorbidity. Methods We linked the multi-generation register, which contains information about all children and their parents in Sweden, and the hospital discharge register, which includes all public psychiatric inpatient admissions in Sweden. We identified 9 009 202 unique individuals in more than 2 million nuclear families between 1973 and 2004. Risks for schizophrenia, bipolar disorder, and their comorbidity were assessed for biological and adoptive parents, offspring, full-siblings and half-siblings of probands with one of the diseases. We used a multivariate generalised linear mixed model for analysis of genetic and environmental contributions to liability for schizophrenia, bipolar disorder, and comorbidity. Findings First-degree relatives of probands with either schizophrenia (n=35 985) or bipolar disorder (n=40 487) were at increased risk of these disorders. Half-siblings had a significantly increased risk (schizophrenia: relative risk [RR] 3.6, 95% CI 2.3-5.5 for maternal half-siblings, and 2.7, 1. 9-3 . 8 for paternal half-siblings; bipolar disorder: 4.5, 2.7-7.4 for maternal half-siblings, and 2.4, 1.4-4-1 for paternal half-siblings), but substantially lower than that of the full-siblings (schizophrenia: 9.0, 8.5-11 .6; bipolar disorder: 7.9, 7.1-8.8). When relatives of probands with bipolar disorder were analysed, increased risks for schizophrenia existed for all relationships, including adopted children to biological parents with bipolar disorder. Heritability for schizophrenia and bipolar disorder was 64% and 59%, respectively. Shared environmental effects were small but substantial (schizophrenia: 4.5%, 4.4%-7.4%; bipolar disorder: 3.4%, 2.3%-6.2%) for both disorders. The comorbidity between disorders was mainly (63%) due to additive genetic effects common to both disorders. Interpretation Similar to molecular genetic studies, we showed evidence that schizophrenia and bipolar disorder partly share a common genetic cause. These results challenge the current nosological dichotomy between schizophrenia and bipolar disorder, and are consistent with a reappraisal of these disorders as distinct diagnostic entities. Funding Swedish Council for Working Life and Social Research, and the Swedish Research Council.
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| 6. |
- Mucci, Lorelei A., et al.
(författare)
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Nine-gene molecular signature is not associated with prostate cancer death in a watchful waiting cohort
- 2008
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - Baltimore : Waverly Press. - 1055-9965 .- 1538-7755. ; 17:1, s. 249-251
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Tidskriftsartikel (refereegranskat)abstract
- Tumor molecular markers hold promise to distinguish potentially lethal from indolent prostate cancer and to guide treatment choices. A previous study identified a nine-gene molecular signature in tumors associated with prostate-specific antigen relapse after prostatectomy. We examined this molecular model in relation to prostate cancer death among 172 men with initially localized disease. We quantified protein expression of the nine genes in tumors to classify progression risk. Accounting for clinical prognostic factors, the nine-gene model did not provide discrimination to predict lethal and indolent prostate cancer.
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| 7. |
- Mucci, Lorelei A., et al.
(författare)
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Testing a multigene signature of prostate cancer death in the Swedish Watchful Waiting Cohort
- 2008
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 17:7, s. 1682-1688
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Tidskriftsartikel (refereegranskat)abstract
- Although prostate cancer is a leading cause of cancer death, most men die with and not from their disease, underscoring the urgency to distinguish potentially lethal from indolent prostate cancer. We tested the prognostic value of a previously identified multigene signature of prostate cancer progression to predict cancer-specific death. The Örebro Watchful Waiting Cohort included 172 men with localized prostate cancer of whom 40 died of prostate cancer. We quantified protein expression of the markers in tumor tissue by immunohistochemistry and stratified the cohort by quintiles according to risk classification. We accounted for clinical variables (age, Gleason, nuclear grade, and tumor volume) using Cox regression and calculated receiver operator curves to compare discriminatory ability. The hazard ratio of prostate cancer death increased with increasing risk classification by the multigene model, with a 16-fold greater risk comparing highest-risk versus lowest-risk strata, and predicted outcome independent of clinical factors (P = 0.002). The best discrimination came from combining information from the multigene markers and clinical data, which perfectly classified the lowest-risk stratum where no one developed lethal disease; using the two lowest-risk groups as reference, the hazard ratio (95% confidence interval) was 11.3 (4.0-32.8) for the highest-risk group and difference in mortality at 15 years was 60% (50-70%). The combined model provided greater discriminatory ability (area under the curve = 0.78) than the clinical model alone (area under the curve = 0.71; P = 0.04). Molecular tumor markers can add to clinical variables to help distinguish lethal and indolent prostate cancer and hold promise to guide treatment decisions.
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| 8. |
- Pawitan, Yudi, et al.
(författare)
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Gene expression profiling spares early breast cancer patients from adjuvant therapy : derived and validated in two population-based cohorts
- 2005
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Ingår i: Breast cancer research : BCR. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 7:6, s. R953-64
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction. METHODS: We obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature associated with prognosis and impact of adjuvant therapies, defined as distant metastasis or death within 5 years. Independent datasets of 76 treated population-derived Swedish patients, 135 untreated population-derived Swedish patients and 78 Dutch patients were used for validation. The inclusion and exclusion criteria for the studies of population-derived Swedish patients were defined. RESULTS: Among the 159 patients, a subset of 64 genes was found to give an optimal separation of patients with good and poor outcomes. Hierarchical clustering revealed three subgroups: patients who did well with therapy, patients who did well without therapy, and patients that failed to benefit from given therapy. The expression profile gave significantly better prognostication (odds ratio, 4.19; P = 0.007) (breast cancer end-points odds ratio, 10.64) compared with the Elston-Ellis histological grading (odds ratio of grade 2 vs 1 and grade 3 vs 1, 2.81 and 3.32 respectively; P = 0.24 and 0.16), tumor stage (odds ratio of stage 2 vs 1 and stage 3 vs 1, 1.11 and 1.28; P = 0.83 and 0.68) and age (odds ratio, 0.11; P = 0.55). The risk groups were consistent and validated in the independent Swedish and Dutch data sets used with 211 and 78 patients, respectively. CONCLUSION: We have identified discriminatory gene expression signatures working both on untreated and systematically treated primary breast cancer patients with the potential to spare them from adjuvant therapy.
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| 9. |
- Setlur, Sunita R., et al.
(författare)
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Estrogen-dependent signaling in a molecularly distinct subclass of aggressive prostate cancer
- 2008
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Ingår i: Journal of the National Cancer Institute. - Oxford : Oxford University Press. - 0027-8874 .- 1460-2105. ; 100:11, s. 815-825
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The majority of prostate cancers harbor gene fusions of the 5'-untranslated region of the androgen-regulated transmembrane protease serine 2 (TMPRSS2) promoter with erythroblast transformation-specific transcription factor family members. The common fusion between TMPRESS2 and v-ets erythroblastosis virus E26 oncogene homolog (avian) (ERG) is associated with a more aggressive clinical phenotype, implying the existence of a distinct subclass of prostate cancer defined by this fusion. METHODS: We used complementary DNA-mediated annealing, selection, ligation, and extension to determine the expression profiles of 6144 transcriptionally informative genes in archived biopsy samples from 455 prostate cancer patients in the Swedish Watchful Waiting cohort (1987-1999) and the United States-based Physicians(') Health Study cohort (1983-2003). A gene expression signature for prostate cancers with the TMPRSS2-ERG fusion was determined using partitioning and classification models and used in computational functional analysis. Cell proliferation and TMPRSS2-ERG expression in androgen receptor-negative (NCI-H660) prostate cancer cells after treatment with vehicle or estrogenic compounds were assessed by viability assays and quantitative polymerase chain reaction, respectively. All statistical tests were two-sided. RESULTS: We identified an 87-gene expression signature that distinguishes TMPRSS2-ERG fusion prostate cancer as a discrete molecular entity (area under the curve = 0.80, 95% confidence interval [CI] = 0.792 to 0.81; P < .001). Computational analysis suggested that this fusion signature was associated with estrogen receptor (ER) signaling. Viability of NCI-H660 cells decreased after treatment with estrogen (viability normalized to day 0, estrogen vs vehicle at day 8, mean = 2.04 vs 3.40, difference = 1.36, 95% CI = 1.12 to 1.62) or ERbeta agonist (ERbeta agonist vs vehicle at day 8, mean = 1.86 vs 3.40, difference = 1.54, 95% CI = 1.39 to 1.69) but increased after ERalpha agonist treatment (ERalpha agonist vs vehicle at day 8, mean = 4.36 vs 3.40, difference = 0.96, 95% CI = 0.68 to 1.23). Similarly, expression of TMPRSS2-ERG decreased after ERbeta agonist treatment (fold change over internal control, ERbeta agonist vs vehicle at 24 hours, NCI-H660, mean = 0.57- vs 1.0-fold, difference = 0.43-fold, 95% CI = 0.29- to 0.57-fold) and increased after ERalpha agonist treatment (ERalpha agonist vs vehicle at 24 hours, mean = 5.63- vs 1.0-fold, difference = 4.63-fold, 95% CI = 4.34- to 4.92-fold). CONCLUSIONS: TMPRSS2-ERG fusion prostate cancer is a distinct molecular subclass. TMPRSS2-ERG expression is regulated by a novel ER-dependent mechanism.
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| 10. |
- Svensson, C, et al.
(författare)
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Maternal Effects for Preterm Birth : A Genetic Epidemiologic Study of 630,000 Families
- 2009
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Ingår i: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 170:11, s. 1365-1372
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Tidskriftsartikel (refereegranskat)abstract
- This study was undertaken to disentangle the maternal genetic from the fetal genetic effects for preterm birth and to study the possibility of these effects being explained by known risk factors. By cross-linking of the population-based Swedish Multigeneration and Medical Birth registers, 989,027 births between 1992 and 2004 were identified. Alternating logistic regression was applied to model the familial clustering with pairwise odds ratios (PORs), and covariates were included to evaluate if the familial aggregation was explained by exposure to shared risk factors. Generalized linear mixed models were used to estimate the contribution of genetic and environmental effects. Sisters of women who had a preterm delivery had themselves an increased odds of having a preterm delivery (POR = 1.8, 95% confidence interval: 1.5, 2.1), while there was no corresponding increase in odds in families joined by brothers (POR = 1.1, 95% confidence interval: 0.9, 1.4). Twenty-five percent of the variation in preterm birth was explained by maternal genetic factors, whereas fetal genetic factors only marginally influenced the variation in liability. The increased odds ratio between offspring of sisters was independent of maternal risk factors for preterm birth, suggesting that the relative importance of maternal effects is not explained by these well-known risk factors.
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