Massive transcriptional perturbation in subgroups of diffuse large B-cell lymphomas.

Based on the assumption that molecular mechanisms involved in cancerogenesis are characterized by groups of coordinately expressed genes, we developed and validated a novel method for analyzing transcriptional data called Correlated Gene Set Analysis (CGSA). Using 50 extracted gene sets we identified three different profiles of tumors in a cohort of 364 Diffuse large B-cell (DLBCL) and related mature aggressive B-cell lymphomas other than Burkitt lymphoma. The first profile had high level of expression of genes related to proliferation whereas the second profile exhibited a stromal and immune response phenotype. These two profiles were characterized by a large scale gene activation affecting genes which were recently shown to be epigenetically regulated, and which were enriched in oxidative phosphorylation, energy metabolism and nucleoside biosynthesis. The third and novel profile showed only low global gene activation similar to that found in normal B cells but not cell lines. Our study indicates novel levels of complexity of DLBCL with low or high large scale gene activation related to metabolism and biosynthesis and, within the group of highly activated DLBCLs, differential behavior leading to either a proliferative or a stromal and immune response phenotype.

Directional multivariate tests rejecting null and negative effects in all variables.

This paper suggests two directional multivariate tests that aim at establishing superiority of a treatment over a control in at least one of several endpoints that are assumed to have a multivariate normal distribution. One of these tests is a one-sided, scale-invariant version of the classical Hotelling T²-test. The other is based on a summary score with weights derived from the data. Both tests overcome an important shortcoming of previous "one-sided" multivariate suggestions, namely that the null hypothesis was restricted to a single point in the multidimensional parameter space. The derivation of the tests is supplemented by simulations investigating their performance and by the application in an osteoporosis trial.

High-dimensional data analysis: selection of variables, data compression and graphics--application to gene expression.

The paper presents effective and mathematically exact procedures for selection of variables which are applicable in cases with a very high dimension as, for example, in gene expression analysis. Choosing sets of variables is an important method to increase the power of the statistical conclusions and to facilitate the biological interpretation. For the construction of sets, each single variable is considered as the centre of potential sets of variables. Testing for significance is carried out by means of the Westfall-Young principle based on resampling or by the parametric method of spherical tests. The particular requirements for statistical stability are taken into account; each kind of overfitting is avoided. Thus, high power is attained and the familywise type I error can be kept in spite of the large dimension. To obtain graphical representations by heat maps and curves, a specific data compression technique is applied. Gene expression data from B-cell lymphoma patients serve for the demonstration of the procedures.

ErbB-3 predicts survival in ovarian cancer.

BACKGROUND: HER3 (erbB-3) is a member of the epidermal growth factor receptor (EGFR) family. After dimerization with other members of the EGFR family several signal transduction cascades can be activated, including phosphoinosite 3'-kinase (PI3-K)/Akt and extracellular signal-regulated kinase (ERK1/2). Here, we studied a possible association between HER3 expression and prognosis in patients with ovarian cancer. METHODS: Tumor tissue of 116 consecutive patients diagnosed with primary epithelial ovarian cancer between 1986 and 1995 was analyzed immunohistochemically for HER3 expression. A possible influence of HER3 expression on survival was studied by multivariate Cox regression adjusting for established clinical prognostic factors. RESULTS: A positive HER3 expression was observed in 53.4% of the patients. HER3 expression was associated with decreased survival in proportional hazard modeling, including the International Federation of Gynecology and Obstetrics (FIGO) stage, histologic grade and type, residual disease, and age. After likelihood ratio forward as well as backward selection, only HER3 expression (hazard ratio, 1.71; 95% CI, 1.10 to 2.67; P = .018), FIGO stage (hazard ratio, 4.78; 95% CI, 1.89 to 12.08; P = .001), residual tumor (hazard ratio, 2.69; 95% CI, 1.40 to 5.17; P = .003), and age (hazard ratio, 2.06; 95% CI, 1.17 to 3.65; P = .013) were found to be significant. Kaplan-Meier plots demonstrated a clear influence of HER3 expression on survival time. Median survival time was 3.31 years (95% CI, 1.93 to 4.68) for patients with low HER3 expression, compared with only 1.80 years (95% CI, 0.83 to 2.78) for patients with HER3 overexpression (log-rank test P = .0034). CONCLUSION: HER3 may represent a new prognostic factor in primary epithelial ovarian cancer. Pending validation, exploration of therapeutic strategies to block HER3 could be warranted.

Comparison of differential gene expression of hot and cold thyroid nodules with primary epithelial cell culture models by investigation of co-regulated gene sets.

Both autonomously functioning thyroid nodules (AFTNs) and cold thyroid nodules (CTNs) are characterized by an increased proliferation, however, they have opposite functional activities. Therefore, with the aim to further understand the distinct molecular pathology of each entity and to discover common mechanisms like those leading to increased proliferation in both, AFTNs and CTNs, we now compared gene expression of AFTNs and CTNs with in vitro model systems (TSH-stimulated and ras-transfected primary cultures (PC)) whose gene expression patterns can be attributed to specific molecular alterations. Since combinations of co-regulated genes are more likely to reveal molecular mechanisms, we used a procedure which groups co-regulated genes within "gene sets". We found a co-regulated gene set in the AFTNs that overlaps with differential expression in TSH-stimulated PCs but not in CTNs or ras-transfected PCs. In addition to thyroid peroxidase and sialyltransferase 1, this set of co-regulated genes comprises metallothioneins and the G-protein-coupled receptor 56. Although their role in the thyroid is unknown so far, their appearance in one group indicates a functional relevance in TSH-TSH receptor-stimulated mechanisms. Furthermore, we identified down-regulated gene sets with concordant expression patterns in AFTNs, CTNs and ras-transfected PCs. However, these expression patterns are not of relevance in the TSH-stimulated PCs. These findings suggest that TSH-stimulated PCs can be used as a model of increased thyroid function (AFTNs), whereas the ras-transfected PCs better reflect the increased proliferation of both AFTNs and CTNs.

Meta- and reanalysis of gene expression profiles of hot and cold thyroid nodules and papillary thyroid carcinoma for gene groups.

CONTEXT: There are an increasing number of studies analyzing gene expression profiles in various benign and malignant thyroid tumors. This creates the opportunity to validate results obtained from one microarray study with those from other data sets. This process requires rigorous methods for accurate comparison. OBJECTIVE: The ability to compare data sets derived from different Affymetrix GeneChip generations and the influence of intra- and interindividual comparisons of gene expression data were evaluated to build multigene classifiers of benign thyroid nodules to verify a previously proposed papillary thyroid carcinoma (PTC) classifier and to look for molecular pathways essential for PTC oncogenesis. METHODS: Gene expression profile data sets from autonomously functioning and cold thyroid nodules and from PTC were analyzed by support vector machines. GenMAPP analysis was used for PTC data analysis to examine the expression patterns of biologically relevant gene sets. RESULTS: Only intraindividual reference samples allowed the identification of subtle changes in the expression patterns of relevant signaling cascades, such as the MAPK pathway in PTC. Using an artificial intelligence approach, the autonomously functioning and cold thyroid nodule multigene classifiers were derived and evaluated by cross-comparisons. CONCLUSION: We recommend defining classifiers within one generation of gene chips and subsequently checking them across different array generations. Using this approach, we have demonstrated the specificity of a previously reported PTC classifier on an independent collection of benign tumors. Moreover, we propose multigene classifiers for different types of benign thyroid nodules.

On testing simultaneously non-inferiority in two multiple primary endpoints and superiority in at least one of them.

In a clinical trial with an active treatment and a placebo the situation may occur that two (or even more) primary endpoints may be necessary to describe the active treatment's benefit. The focus of our interest is a more specific situation with two primary endpoints in which superiority in one of them would suffice given that non-inferiority is observed in the other. Several proposals exist in the literature for dealing with this or similar problems, but prove insufficient or inadequate at a closer look (e.g. Bloch et al. (2001, 2006) or Tamhane and Logan (2002, 2004)). For example, we were unable to find a good reason why a bootstrap p-value for superiority should depend on the initially selected non-inferiority margins or on the initially selected type I error alpha. We propose a hierarchical three step procedure, where non-inferiority in both variables must be proven in the first step, superiority has to be shown by a bivariate test (e.g. Holm (1979), O'Brien (1984), Hochberg (1988), a bootstrap (Wang (1998)), or Läuter (1996)) in the second step, and then superiority in at least one variable has to be verified in the third step by a corresponding univariate test. All statistical tests are performed at the same one-sided significance level alpha. From the above mentioned bivariate superiority tests we preferred Läuter's SS test and the Holm procedure for the reason that these have been proven to control the type I error strictly, irrespective of the correlation structure among the primary variables and the sample size applied. A simulation study reveals that the performance regarding power of the bivariate test depends to a considerable degree on the correlation and on the magnitude of the expected effects of the two primary endpoints. Therefore, the recommendation of which test to choose depends on knowledge of the possible correlation between the two primary endpoints. In general, Läuter's SS procedure in step 2 shows the best overall properties, whereas Holm's procedure shows an advantage if both a positive correlation between the two variables and a considerable difference between their standardized effect sizes can be expected.

Gene expression analysis reveals evidence for increased expression of cell cycle-associated genes and Gq-protein-protein kinase C signaling in cold thyroid nodules.

In contrast to the molecular etiology of autonomously functioning thyroid nodules, the molecular cause of cold thyroid nodules (CTNs), their benign, functional inactive counterparts, are so far largely unknown. Because of the partially dedifferentiated phenotype of CTNs, alterations in signaling cascades that favor proliferation, but not differentiation, are likely candidates for tumor induction and progression. The importance of RAS mutations for the development of benign nodules with follicular histology is still in question. However, differentially expressed genes in the context of their signaling cascades could define aberrant signaling in CTNs. Therefore, we investigated gene expression in 22 CTNs and their normal surrounding tissue using Affymetrix GeneChips. Most prominently, data analysis revealed an increased expression of cell cycle-associated genes and a special relevance of protein kinase C signaling, whereas no evidence of RAS-MAPK signaling in CTNs was found. Moreover, we determined 31 differentially regulated genes in CTNs, including several histone mRNAs. Taken together, these results explain recent findings showing an increased proliferation in CTNs and draw attention to protein kinase C signaling, but away from RAS-MAPK signaling, as being involved in the etiology of CTNs.

Comprehensive survey of the relationship between serum concentration and therapeutic effect of amitriptyline in depression.

The relationship between serum concentration (C(s)) of amitriptyline and its therapeutic effect in depression has been investigated frequently over the last 3 decades; however, the results were controversial and no consensus was reached. Therefore, we have performed a comprehensive survey and meta-analysis of the subject. All relevant literature was included, and the design of studies on the serum concentration-therapeutic effect relationship (SCTER) of amitriptyline was evaluated. Pooled original data from SCTER studies with adequate design were analysed by various statistical methods: regression analysis of therapeutic effect and C(s); comparison of the mean therapeutic effect in various ranges of C(s); dichotomisation of outcome and analysis according to sensitivity of receiver operation curves; frequency of responders and nonresponders in ranges determined by points of sensitivity; analysis of the distribution of C(s) in responders and nonresponders; logistic regression of responders and nonresponders with C(s) and other independent variables; calculation of effect size (g) and mean effect size (g(m)). Forty-five SCTER studies of amitriptyline were identified, and 27 studies met the minimum criteria of adequate study design. Inadequate study design predicted the finding of no SCTER. Analysis of the pooled data from studies with adequate design confirmed a therapeutic window of the sum of C(s) of amitriptyline and its active metabolite nortriptyline of about 80 to 200 microg/L. A moderate and significant positive g(m) (0.538, 95% confidence interval 0.167 to 0.909) was calculated for treatment with C(s) within the therapeutic window in comparison with treatment with C(s) outside the therapeutic window (19 studies with adequate design and original data available, n = 583). In conclusion, the evidence for a biphasic SCTER of amitriptyline in depression is considerably improved, and the results may help to find a consensus in the future. However, the clinical benefit of therapeutic drug monitoring of amitriptyline can only be demonstrated in a controlled and randomised study. Furthermore, the results provide further evidence that antidepressants at optimum C(s) are superior to placebo in the treatment of depression.