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Purpose: The human SIM2 gene is located within the Down's syndrome critical region of chromosome 21 and encodes transcription factors involved in brain development and neuronal differentiation. SIM2 has been assigned a possible role in the pathogenesis of solid tumors, and the SIM2-short isoform (SIM2-s) was recently proposed as a molecular target for cancer therapy. We previously reported SIM2 among the highly up-regulated genes in 29 prostate cancers, and the purpose of our present study was to examine the expression status of SIM2 at the transcriptional and protein level as related to outcome in prostate cancer.Experimental Design: By quantitative PCR, mRNA in situ hybridization, and immunohistochemistry, we evaluated the expression and significance of SIM2 isoforms in 39 patients with clinically localized prostate cancer and validated the expression of SIM2-s protein in an independent cohort of 103 radical prostatectomies from patients with long and complete follow-up.Results: The SIM2 isoforms (SIM2-s and SIM2-l) were significantly coexpressed and increased in prostate cancer. Tumor cell expression of SIM2-s protein was associated with adverse clinicopathologic factors like increased preoperative serum prostate-specific antigen, high histologic grade, invasive tumor growth with extra-prostatic extension, and increased tumor cell proliferation by Ki-67 expression. SIM2-s protein expression was significantly associated with reduced cancer-specific survival in multivariate analyses.Conclusions: These novel findings indicate for the first time that SIM2 expression might be important for clinical progress of human cancer and support the recent proposal of SIM2-s as a candidate for targeted therapy in prostate cancer.

Supplementary Figure 2 from Increased Expression of SIM2-s Protein Is a Novel Marker of Aggressive Prostate Cancer

Supplementary Figure 1 from Increased Expression of SIM2-s Protein Is a Novel Marker of Aggressive Prostate Cancer

Supplementary Figure 2 Legend from Increased Expression of SIM2-s Protein Is a Novel Marker of Aggressive Prostate Cancer

Background and Objectives Chemokines are soluble mediators involved in angiogenesis, cellular growth control and immunomodulation. In the present study we investigated the effects of various chemokines on proliferation of acute myelogenous leukemia (AML) cells and constitutive chemokine release by primary AML cells.Design and Methods Native human AML cells derived from 68 consecutive patients were cultured in vitro. We investigated AML cell proliferation (3H-thymidine incorporation, colony formation), chemokine receptor expression, constitutive chemokine release and chemotaxis of normal peripheral blood mononuclear cells.Results Exogenous chemokines usually did not have any effect on AML blast proliferation in the absence of hematopoietic growth factors, but when investigating growth factor-dependent (interleukin 3 + granulocyte-macrophage colony-stimulating factor + stem cell factor) proliferation in suspension cultures the following patient subsets were identified: (i) patients whose cells showed chemokine-induced growth enhancement (8 patients); (ii) divergent effects on proliferation (15 patients); and (iii) no effect (most patients). These patient subsets did not differ in chemokine receptor expression, but, compared to CD34− AML cells, CD34+ cells showed higher expression of several receptors. Chemokines also increased the proliferation of clonogenic AML cells from the first subset of patients. Furthermore, a broad constitutive chemokine release profile was detected for most patients, and the following chemokine clusters could be identified: CCL2-4/CXCL1/8, CCL5/CXCL9-11 (possibly also CCL23) and CCL13/17/22/24/CXCL5 (possibly also CXCL6). Only the CCL2-4/CXCL1/8 cluster showed significant correlations between corresponding mRNA levels and NFκB levels/activation. The chemotaxis of normal immunocompetent cells for patients without constitutive chemokine release was observed to be decreased.Interpretation and Conclusions Differences in chemokine responsiveness as well as chemokine release contribute to patient heterogeneity in AML. Patients with AML can be classified into distinct subsets according to their chemokine responsiveness and chemokine release profile.

Multiway methods are tested for their ability to explore and model near-infrared (NIR) spectra from a pharmaceutical batch process. The study reveals that blocking of data having a nonlinear behaviour into higher-order array can improve the predictive ability. The variation in each control point is independently modelled and N-way techniques overcome the nonlinearity problem. Important issues as variable selection and how to fill in for missing values have been discussed. Variable selection was shown to be essential to be able to perform multiway modelling. For spectra not yet monitored, use of mean spectra from calibration set gave close to the best results. Decomposing the spectra by N-way techniques gave additional information about the chemical system. To support the results simulated data sets were used.

Partial least squares (PLS) is a powerful tool for multivariate linear regression. But what if the data show a non-linear structure? Near infrared spectra from a pharmaceutical process were used as a case study. An ANOVA test revealed that the data are well described by a 2nd order polynomial. This work investigates the application of regression techniques that account for slightly non-linear data. The regression techniques investigated are: linearising data by applying transformations, local PLS, i.e. splitting of data, and quadratic PLS. These models were compared with ordinary PLS and principal component regression (PCR). The predictive ability of the models was tested on an independent data set acquired a year later. Using the knowledge of non-linear pattern and important spectral regions, simpler models with better predictive ability can be obtained.

Self-association of 1-propanol, 1-butanol, 1-pentanol, 1-hexanol, 1-heptanol, 2-propanol, 2-methyl-1-propanol, and 2-methyl-2-propanol in carbon tetrachloride (concentration range 0.01−1.00 M) has for the first time been investigated by means of multivariate curve resolution in the near-infrared region of 1900−2200 nm. Rank analysis was carried out prior to resolution to determine the number of distinct species. In addition to principal component analysis (PCA) and evolving factor analysis (EFA), smooth PCA was used with good results. For all of the investigated alcohols, the rank was unambiguously assessed as three over the entire concentration range. At low concentrations, EFA detected a concentration region with only two species. Eigenstructure tracking analysis (ETA) revealed one-component regions in the spectral direction. The first loadings of the selective regions gave the concentration profiles of the two species. The spectral profiles of these two species were then resolved by using the least squ...

Multivariate calibration models for predicting the initial reactant and an impurity in a synthesis of contrast media have been developed using near-infrared (NIR) spectroscopy. The reaction is presently monitored off-line by HPLC. The calibration models are based on spectra measured on-line. The process solution is chemically complex and the intention of this study was to enhance knowledge about the predictive ability of the models. Different data-preprocessing and variable selection methods reported in the literature have been tested in order to enhance chemical information and reduce irrelevant variability due to physical influences on measured spectra such as scattering and temperature. In addition to standard preprocessing methods such as normalization, differentiation and multiplicative scatter correction, orthogonal signal correction and optimized scaling were tested. The modelling was performed by partial least squares (PLS), except for optimized scaling which uses principal component regression (PCR). Optimized scaling on differentiated data gave the lowest prediction error. The NIR region from 1100 to 1900 nm gave better models than variable selection and fewer variables. Models with correlation coefficients for best fit equal to 0.998 and 0.961 were obtained for the initial reactant and the impurity, respectively. Copyright © 2002 John Wiley & Sons, Ltd.

Most spectra with structural information are smooth. Making use of this feature, a new procedure is proposed for automatic chemical rank determination. In order to avoid accumulation of noise, key spectra instead of the full matrix are analyzed in the procedure. A simplified morphological factor, morphological score (MS), is proposed. The noise level of morphological analysis is established with the help of F -test. The proposed procedure was successfully applied in the study of self-association behavior of alcohol. Results show that two classes of aggregates contribute to near infrared (NIR) spectra besides the monomer. Data sets produced by other techniques were also tested.

Background The molecular changes in vivo in acute myeloid leukemia cells early after start of conventional genotoxic chemotherapy are incompletely understood, and it is not known if early molecular modulations reflect clinical response. Methods The gene expression was examined by whole genome 44 k oligo microarrays and 12 k cDNA microarrays in peripheral blood leukocytes collected from seven leukemia patients before treatment, 2–4 h and 18–24 h after start of chemotherapy and validated by real-time quantitative PCR. Statistically significantly upregulated genes were classified using gene ontology (GO) terms. Parallel samples were examined by flow cytometry for apoptosis by annexin V-binding and the expression of selected proteins were confirmed by immunoblotting. Results Significant differential modulation of 151 genes were found at 4 h after start of induction therapy with cytarabine and anthracycline, including significant overexpression of 31 genes associated with p53 regulation. Within 4 h of chemotherapy the BCL2/BAX and BCL2/PUMA ratio were attenuated in proapoptotic direction. FLT3 mutations indicated that non-responders (5/7 patients, 8 versus 49 months survival) are characterized by a unique gene response profile before and at 4 h. At 18–24 h after chemotherapy, the gene expression of p53 target genes was attenuated, while genes involved in chemoresistance, cytarabine detoxification, chemokine networks and T cell receptor were prominent. No signs of apoptosis were observed in the collected cells, suggesting the treated patients as a physiological source of pre-apoptotic cells. Conclusion Pre-apoptotic gene expression can be monitored within hours after start of chemotherapy in patients with acute myeloid leukemia, and may be useful in future determination of therapy responders. The low number of patients and the heterogeneity of acute myeloid leukemia limited the identification of gene expression predictive of therapy response. Therapy-induced gene expression reflects the complex biological processes involved in clinical cancer cell eradication and should be explored for future enhancement of therapy.

Purpose: The human SIM2 gene is located within the Down's syndrome critical region of chromosome 21 and encodes transcription factors involved in brain development and neuronal differentiation. SIM2 has been assigned a possible role in the pathogenesis of solid tumors, and the SIM2-short isoform (SIM2-s) was recently proposed as a molecular target for cancer therapy. We previously reported SIM2 among the highly up-regulated genes in 29 prostate cancers, and the purpose of our present study was to examine the expression status of SIM2 at the transcriptional and protein level as related to outcome in prostate cancer. Experimental Design: By quantitative PCR, mRNA in situ hybridization, and immunohistochemistry, we evaluated the expression and significance of SIM2 isoforms in 39 patients with clinically localized prostate cancer and validated the expression of SIM2-s protein in an independent cohort of 103 radical prostatectomies from patients with long and complete follow-up. Results: The SIM2 isoforms (SIM2-s and SIM2-l) were significantly coexpressed and increased in prostate cancer. Tumor cell expression of SIM2-s protein was associated with adverse clinicopathologic factors like increased preoperative serum prostate-specific antigen, high histologic grade, invasive tumor growth with extra-prostatic extension, and increased tumor cell proliferation by Ki-67 expression. SIM2-s protein expression was significantly associated with reduced cancer-specific survival in multivariate analyses. Conclusions: These novel findings indicate for the first time that SIM2 expression might be important for clinical progress of human cancer and support the recent proposal of SIM2-s as a candidate for targeted therapy in prostate cancer.

The aim of this study was to identify and validate differentially expressed genes in matched pairs of benign and malignant prostate tissue. Samples included 29 histologically verified primary tumors and 23 benign controls. Microarray analysis was initially performed using a sequence verified set of 40,000 human cDNA clones. Among the genes most consistently and highly upregulated in prostate cancer was the ETS family transcription factor ERG (ETS related gene). This finding was validated in an expanded patient series (37 tumors and 38 benign samples) using DNA oligonucleotide microarray and real-time quantitative PCR assays. ERG was 20- to more than 100-fold overexpressed in prostate cancer compared with benign prostate tissue in more than 50% of patients according to quantitative PCR. Surprisingly, ERG mRNA levels were found to be significantly higher in the endothelial cell line, HUVEC, than in the prostate cell lines PC3, DU145 and LNCaP. In situ hybridization of prostate cancer tissue revealed that ERG was abundantly expressed in both prostate cancer cells and associated endothelial cells. The consistency and magnitude of ERG overexpression in prostate cancer appeared unique, but several related ETS transcription factors were also overexpressed in matched pairs of tumor and benign samples, whereas ETS2 was significantly underexpressed. Our findings support the hypothesis that ERG overexpression and related ETS transcription factors are important for early prostate carcinogenesis.

Prostate carcinoma is the most common cancer of western men and is a markedly heterogeneous disease. The aim of this study was to identify signatures of differentially expressed genes in prostate cancer using DNA microarray technology, evaluating expression profiles in matched pairs of benign and malignant tissue. Samples were collected from 33 radical prostatectomies, and 52 specimens were included, representing 29 histologically verified primary tumours, 19 paired samples of malignant and benign tissue, and 4 non-paired benign tissue samples. Microarray analysis was performed using an expanded sequence verified set of 40,000 human cDNA clones, revealing several genes with significant differences between malignant and benign tissue, including recently reported genes like alpha-methylacyl-CoA racemase (AMACR) and hepsin, as well as genes relevant for tumour development and progression. Leave out cross validation (LOCV) test correctly predicted tumour or benign tissue in 47 (90.3%) out of 52 cases, significantly better than cross validation tests using randomly permuted tissue labels. Unsupervised clustering analysis revealed 3 distinct patient clusters significantly associated with Gleason score, and high grade tumours (Gleason score >/=7) accumulated in cluster 1 (C1). Gene expression profiles correctly predicted 100% of tumour samples segregating to C1, as also validated by LOCV. Gene expression profiles were analysed in filtered and floored datasets with similar results, and a pair-wise design was also tested. Gene expression profiles provided tumour clusters linked to differentiation, and revealed novel markers relevant for molecular classification, grading and therapy of prostate cancer.