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Gene expression relationship between prostate cancer cells of Gleason 3, 4 and normal epithelial cells as revealed by cell type-specific transcriptomes
Laura E Pascal1,2 nAff6,
Ricardo ZN Vêncio3,4,
Laura S Page1,2,
Emily S Liebeskind1,
Christina P Shadle1,
Pamela Troisch3,
Bruz Marzolf3,
Lawrence D True5,
Leroy E Hood3 &
Alvin Y Liu1,2
BMC Cancer volume 9, Article number: 452 (2009) Cite this article
Prostate cancer cells in primary tumors have been typed CD10-/CD13-/CD24hi/CD26+/CD38lo/CD44-/CD104-. This CD phenotype suggests a lineage relationship between cancer cells and luminal cells. The Gleason grade of tumors is a descriptive of tumor glandular differentiation. Higher Gleason scores are associated with treatment failure.
CD26+ cancer cells were isolated from Gleason 3+3 (G3) and Gleason 4+4 (G4) tumors by cell sorting, and their gene expression or transcriptome was determined by Affymetrix DNA array analysis. Dataset analysis was used to determine gene expression similarities and differences between G3 and G4 as well as to prostate cancer cell lines and histologically normal prostate luminal cells.
The G3 and G4 transcriptomes were compared to those of prostatic cell types of non-cancer, which included luminal, basal, stromal fibromuscular, and endothelial. A principal components analysis of the various transcriptome datasets indicated a closer relationship between luminal and G3 than luminal and G4. Dataset comparison also showed that the cancer transcriptomes differed substantially from those of prostate cancer cell lines.
Genes differentially expressed in cancer are potential biomarkers for cancer detection, and those differentially expressed between G3 and G4 are potential biomarkers for disease stratification given that G4 cancer is associated with poor outcomes. Differentially expressed genes likely contribute to the prostate cancer phenotype and constitute the signatures of these particular cancer cell types.
The Gleason grade is a pathology characterization of prostate tumors. Tumor glands can appear from well-differentiated to poorly differentiated. The degree of differentiation is scaled from 3 to 5 (grades 1 and 2 are no longer in wide use), with 3 to indicate tumors with glandular differentiation, 4 to indicate tumors with aglandular differentiation, and 5 to indicate no differentiation with cancer cells not organized into recognizable structures. Each tumor is assigned a score of two Gleason grades. Gleason 3+3 is associated with favorable outcomes and patient survival while tumors containing 4 or 5 components have a poorer prognosis. A molecular correlate of the Gleason grade was reported where grade 3 could be distinguished from grades 4 and 5 by gene expression, whereas grades 4 and 5 were indistinguishable by gene expression [1]. Another study, however, found a different set of genes associated with degree of tumor differentiation [2]. Reis et al. [3] found that a higher fraction (6.6%) of intronic ncRNAs were significantly correlated to the degree of prostate tumor differentiation (Gleason score) when compared to unannotated genomic regions (1%) or from exons of known genes (2%). The difference in gene signatures reported by different laboratories has yet to be explained, but is likely due to a combination of external factors as well as actual biological difference. These studies have attempted to define a set of gene expression profiles as determined by microarray analysis that could supplement the traditional diagnostics of pathology and clinical parameters to predict disease course [4]. For example, a 5-gene model was proposed that could segregate recurrent from non-recurrent cancer [5]. Although gene signatures have been shown to associate with Gleason grade [6], none so far have been able to discriminate locally invasive from non-invasive tumors.
We have previously shown that prostate tumors contained multiple Gleason grades as well as multiple cancer cell types distinguishable by their cluster designation (CD) phenotypes [7, 8]. CD antigens are cell surface molecules, and each cell type has a unique complement of these molecules. This allowed us to isolate, for example, CD26+ luminal cells, CD104+ basal cells, CD49a+ stromal fibromuscular cells, and CD31+ endothelial cells from prostate tissue samples by magnetic cell sorting (MACS) for microarray analysis using the Affymetrix GeneChip to determine cell type-specific gene expression or transcriptome [9]. These cell type transcriptomes are a powerful tool to discover lineage relationship between cell types. We applied the same cell sorting methodology here to determine the transcriptome of CD26+ prostate cancer cells of Gleason 3+3 and Gleason 4+4 tumor specimens. These specimens, unlike those of 3+4 or 4+3, ensured that cells representative of only grade 3 or 4 would be obtained. The transcriptomes were then compared with each other to identify differentially expressed genes, as well as with those of the normal cell types. Furthermore, dataset comparisons between the transcriptomes of primary tumor cells and prostate cancer cell lines, which were established from metastatic lesions and showed unique CD expression [10, 11], demonstrated that they were not representative of cells in primary tumors.
Prostate tumor tissue and cell sorting
Anonymized tissue samples were obtained at radical prostatectomy under approval by the University of Washington Institutional Review Board. Pertinent pathology information was requested from a research coordinator who was authorized to access the patient database in the Department of Urology. The resected glands were cut into 3-mm thick transverse blocks, and frozen sections from representative right and left areas of the apex, middle and base regions were stained to locate the tumor foci. With the stained sections as guide, tumor tissue samples were excised from the corresponding regions and placed in sterile tubes. Processing of tissue pieces for cell sorting was as described [9, 12]. The collected samples were minced and digested by collagenase type I (Invitrogen, Carlsbad, CA) in serum-free RPMI1640 media supplemented with 10-8 M dihydrotestosterone on a magnetic stirrer at room temperature overnight. The resultant cell suspension was filtered with 70-μm Falcon cell strainer to remove debris, diluted with equal volume of Hanks balanced salt solution (HBSS), and aspirated with 18-gauge needle. Cells were pelleted by centrifugation and the digestion media was analyzed by Western blotting for TIMP1 protein [13] to gauge purity of the cancer specimens. The single cell preparation was partitioned into stromal and epithelial fractions on discontinuous Percoll density gradients (Amersham Pharmacia, Piscataway, NJ). Cells banding at the epithelial density were collected and used for sorting with CD26 antibody. The tumor specimens of 05-179 and 08-032 weighed 0.6 g and 6 g respectively, and were above the minimal weight requirement for cell sorting. The pathology characteristics of tumors from which cancer cells were obtained were as follows - 05-179: Gleason 3+3, T2cN0Mx, 4.7 cc tumor volume; and, 08-032: Gleason 4+4, T3b, 27 cc tumor volume.
MACS cell isolation and FACS analysis of sorted cells
Gradient-purified epithelial cells were labeled with phycoerythrin (PE)-conjugated anti-CD26 (1:20; M-A261, BD PharMingen, San Diego, CA) and sorted by MACS (Miltenyi Biotec, Auburn, CA) as described previously for the normal cell types [9]. Aliquots of positive and negative cell fractions were analyzed by fluorescence activated cell sorting (FACS, Becton Dickinson, Mountain View, CA) to monitor sort efficiency as reported previously; only >85% CD26+ fractions were used for microarray analysis [14]. The sorted cancer cells were pelleted by centrifugation and total RNA was extracted using RNaqueous (Ambion, Austin, TX).
Prostate cancer cell lines
Prostate cancer cell lines LNCaP, C4-2, CL1 (and its subclones CL1.1 and CL1.31), DU145 and PC3 were cultured and harvested for array analysis as described in our previous report on differential gene expression between LNCaP and C4-2 [15].
Serial 5-μm sections were prepared from frozen blocks, fixed in cold acetone, and processed for immunohistochemistry using a three-step indirect avidin-biotin-peroxidase procedure. The primary antibodies used were the CD antibodies described in our previous reports [7, 16]. Anti-Dlx1 (clone AB5724, Chemicon/Millipore, Billerica, MA), was used at 1:500. Sections were counterstained with hematoxylin. The immunostained sections were imaged with Olympus BX41 microscope (Olympus, Melville, NY) equipped with MircoFire digital camera (Optronics, Goleta, CA). Images were processed with Photoshop CS (Adobe Systems, San Jose, CA).
Western blot analysis
Cell-free tissue digestion media preparations (g tissue/ml media) diluted in equal volume of HBSS were resolved by gradient polyacrylamide gel electrophoresis and transferred to membrane filter for probing by AGR2 antibody (1:500; 1C3, Abnova, Taipei, Taiwan). The 17-kDa AGR2 protein was visualized using ECL (GE Healthcare, Piscataway, NJ). Prostate specific antigen (PSA) antibody (1:1,000; A67-B/E3, Santa Cruz Biotechnology, Santa Cruz, CA) was used as sample loading control.
DNA array analysis
Quality and concentration of RNA were determined using Agilent 2100 Bioanalyzer and RNA Nano or Pico Labchip (Agilent Technologies, Santa Clara, CA) where appropriate. Only RNA samples of sufficient concentration and showed no degradation as evidenced by distinct 18S and 28S ribosomal bands were used for microarray experiments. The Human Genome U133 Plus 2.0 GeneChips (Affymetrix, Santa Clara, CA) were used for expression profiling. The U133 array contains probesets representing 54,675 genes, splice variants, and ESTs. The GeneChips were prepared, hybridized, and scanned according to the protocols provided by Affymetrix (P/N 702232 Rev. 2) [9, 15]. In brief, 200 ng RNA was reverse transcribed with poly (dT)/T7 promoter primer, and the cDNA was made double-stranded. In vitro transcription was performed with biotinylated ribonucleotides, and the biotin-labeled cRNA was hybridized to the GeneChips. The chips were washed and stained with streptavidin-PE using FS-450 fluidics station (Affymetrix). Data was collected with Affymetrix GeneChip Scanner 3000. A total of three CD26+ prostate cancer array datasets were obtained from two patients; with 05-179 analyzed twice and 08-032 analyzed once. Two replicates were run for each prostate cancer cell line: CL1, CL1.1, CL1.31, DU145 and PC3. Datasets previously obtained from five non-sorted whole-tissue tumor specimens and their matched non-cancer specimens were used for comparison [14]. All transcriptome datasets are deposited in our public UESC database http://scgap.systemsbiology.net/, which makes them available for data query [17].
Computational analysis of datasets
For differential gene expression, datasets were analyzed by HTself, a self-self based statistical method for low replication microarrays [18] using a strategy very similar to that described by Pascal et al. [14]. To apply this method, all possible combination of pair-wise comparisons among experiments were taken to create sets of ratios. Gene expression level was defined as the normalized and summarized intensities of each GeneChip probeset, and was presented as its logarithmic value: X = log2(Normalized intensity). This step was carried out using the standard robust multi-array average (RMA) method [19], implemented in the analysis pipeline SBEAMS [20]. The strength of differential expression between any pair of experiments was estimated by M i = log2(ratio) = X i -X a , where a represented one particular cell type and i represented each given cell type in the set: B (basal), L (luminal), S (stromal), E (endothelial), G3 (Gleason 3) or G4 (Gleason 4). To estimate reliability, the HTself method used virtual self-self experiments (i.e., G3 cancer vs. G3 cancer) to derive intensity-dependent cutoffs. Accordingly, a probeset was considered significantly differentially expressed if at least 80% of its log-ratio combinations were outside the 99.9% credibility intensity-dependent cutoff. Moreover, an average greater than 8-fold difference in expression level was chosen. The computational analysis results were verified by dataset query of known differentially expressed genes. In principal components analysis (PCA) of the various transcriptome datasets, a gene expression subspace was obtained that brought out the principal sources of variability among transcriptomes of the different prostate cell types. The rotation matrix was obtained by using averages of X G3 , X G4 , X L , X B , X S , and X E , and these were plotted as projections on the principal components space. The various transcriptomes were then projected into this PCA-generated subspace, which could be rotated freely to visualize the spatial separation of the individual nodes. Pathway analysis of selected genes was done with KEGG [21].
Gene expression of cancer cells of a Gleason 3+3 tumor
CD26+ prostate cancer cells were isolated from tumor specimen 05-179, split into two aliquots, and each was analyzed by DNA array. The 05-179 tumor was scored Gleason 3+3 with negative margins (i.e., with no evidence of extraprostatic spread). Cancer cells of the 05-179 tumor glands were characterized as CD26+/CD13-/CD10- (Figure 1A), the predominant cancer cell type with a frequency of ~70% [7]. Absent expression of CD10 and CD13 distinguished these cancer cells from CD10+/CD13+ luminal cells. Prostate basal cells were negative for CD10, CD13 and CD26, and basal cell CD markers were not detected in the cancer by immunostaining (data not shown). Immunostaining of all representative 05-179 tissue sections containing cancer did not detect the CD10+ cancer cell type, which has a frequency of ~30% [7].
Prostate cancer cell gene expression. A: Cancer CD phenotype. Serial sections of human prostate from specimen 05-179 were stained for CD10, CD13, and CD26. Cancer glands in these serial sections are not stained for CD10 (top left) and CD13 (top right), whereas a single benign gland (lower left in the photomicrographs) is; original magnification 200×. Cells in the cancer glands, like luminal cells of benign glands, are positive for CD26 (bottom left). In the higher magnification (400×, bottom right), the cancer cells show the characteristic prominent nucleoli. B: Dataset clustering. The relationship of the CD26+ cancer cell transcriptome to that of CD49a stromal, CD31 endothelial, CD26 luminal or CD104 basal is shown. Whole transcriptomes were used to generate Euclidean distances. The self replicates of CD26+ cancer (blue) are in the middle. C: Gene expression in virtual Northern blot format. Affymetrix signal values are represented on a gray scale. The cell type-specific transcriptomes are listed on the top with red arrowheads to identify CD26+ cancer and luminal. C4-2, CL1, CL1.1, CL1.31, DU145, LNCaP, PC3 are cancer cell lines.
For the single specimen of 05-179 cancer, statistical analysis of gene expression with traditional methods was not applicable. Instead, HTself was used to analyze for differential gene expression between the CD26+ G3 cancer transcriptome and the previously determined transcriptome of the normal counterpart, CD26+ luminal [9]. Cluster analysis comparing the transcriptome datasets of CD26+ G3 cancer cells and the previously determined principal cell types of the prostate [9] was summarized (Figure 1B). The gene expression profile of CD26+ cancer was closer to that of luminal than basal, in agreement with previous CD phenotype analysis [7] and cell type-specific expression data of cytokeratin subtypes [22].
The array data was reported as RMA-normalized Affymetrix signal intensities implemented in SBEAMS or as a composite value M i = log2(ratio) = X i -X a , where a represented cancer and i represented normal. For dataset query, we enabled simple searches to display results in downloadable formats as previously described [17]. Query results of signal intensity values were graphically shown on a grayscale. Gene expression levels determined by microarray for CD10/MME, CD13/ANPEP, CD24, CD26/DPP4, and CD38 were concordant with immunohistochemistry, i.e., CD26+/CD13-/CD10-; increased CD24 and decreased CD38 compared to luminal cells (Figure 1C). The CD26+ cancer cells also had elevated expression of prostate cancer-associated genes AMACR (α-methylacyl-CoA racemase), HPN (hepsin) and PCA3 (prostate cancer antigen 3). These results indicated minimal contamination of CD26+ luminal cells from non-cancer tissue that might be present in the tumor specimen. In the same display, the expression profiles of these CD in the various prostate cancer cell lines were in agreement with their CD expression previously determined by flow cytometry [10, 11]. For example, LNCaP and C4-2 are CD10+; C4-2 differs from LNCaP in being CD26+; PC3 is CD13+, DU145 is CD24+. Overall, the gene expression and CD phenotype of the CD26+ cancer cells differed substantially from those of the cancer cell lines indicating that it is unlikely that any of the cell lines, which were established from metastatic lesions, could have derived from the CD26+/CD10-/CD13- cancer cell type found in a majority of tumors.
Differential gene expression between CD26+ G3 cancer cells and CD26+ luminal cells analyzed by HTself identified 121 genes with increased cancer expression and 86 genes with decreased cancer expression by at least 8-fold relative to luminal cells (see Additional File 1 for full list, and Additional File 2 for self-self experiment and HTself cutoff for differential expression). Although they were up-regulated, AMACR and HPN were not among those with the highest fold-increase in expression in this set. BRE, which encodes a death receptor-associated anti-apoptotic protein with an inhibitory function in the mitochondrial pathway, was the most up-regulated, followed by FLJ242562, R55784, MMP12, and KCNH8. IL24, which was highly up-regulated in this dataset, was recently found to be up-regulated in tumor-associated stromal cells as well [14]. The many ESTs (highlighted in tan, Additional File 1), e.g., KIAA0960, also contributed to the signature of this prostate cancer cell type. Several Wnt pathway genes (highlighted in yellow, Additional File 1) were identified. Down-regulated genes by at least 8-fold relative to luminal cells included peptidases [ENPEP (glutamyl aminopeptidase), CPM (carboxypeptidase M), in addition to ANPEP/CD13 and MME/CD10], TNFRSF19 (involved in apoptosis), ADD3 (adducin, important for cell-cell contact in epithelial tissues), GEDP (the gene differentially expressed in the prostate), and MSMB/PSP94. MSMB, KLK3/PSA and ACPP (prostatic acid phosphatase) constitute the well-known three most abundant prostatic secretory products. Unlike KLK3 and ACPP, luminal expression of MSMB appears not to be regulated by stromal influence [12], and is known to be down-regulated in cancer cells [23].
The 08-032 tumor was scored Gleason 4+4, margin positive with seminal vesicle involvement. The Gleason scoring of 08-032 indicated that virtually all the cancer cells represented the Gleason grade 4 (G4) type while those of 05-179 the G3 type (no frozen tumor tissue block was available for 08-032 for CD immunohistochemistry). Verification of the "purity" of this rather large (6 g) tumor specimen, i.e., absence of non-cancer, was determined by Western blot analysis of tissue collagenase digestion media for TIMP1 protein (data published in ref. [14]). TIMP1 protein is produced by luminal cells and not cancer cells [13]. Specimen 08-032 showed minimal reactivity for TIMP1, indicating a relatively pure sample with little contamination by non-cancer. Differential gene expression was analyzed between G3 and luminal cells, and between G4 and G3 cells.
PCA (Figure 2) displayed the relatedness of the G3 and G4 transcriptomes to each other and to those of the other previously determined major cell types of the prostate: stromal (S), luminal (L), basal (B), and endothelial (E). Their particular placement suggested that, with respect to the major differences in gene expression of cell types, G3 and G4 were most similar to luminal (L) than any of the other histologically normal prostate cell types. G4 was less similar to luminal (L) than G3 as indicated by the longer separation between the respective data points. Neither the G3 nor the G4 transcriptome clustered near that of basal cells (B) indicating that these CD26+ G3 and G4 cancer cells were more characteristic of luminal cells than basal cells in gene expression as well as CD phenotype.
PCA projections of Gleason 3 and Gleason 4 cancer transcriptomes. A: Three-dimensional projection of G3 and G4 transcriptomes with respect to those of prostate cell transcriptomes for stromal cells (S), luminal cells (L), endothelial cells (E), and basal cells (B) in a PCA-derived subspace. B: Two other orientations from a different point of perspective of the PCA space. The 3D coordinate system was obtained by performing the usual PCA, defining the rotation matrix related to the top three principal components and applying it to all datasets to create a subspace that highlights the expression particularities of each prostate cell type.
Comparison of cancer cell and cancer tissue transcriptomes
The combined CD26+ cancer cell transcriptome datasets were compared to those of five matched cancer (CP) and non-cancer (NP) tissue specimens obtained also via Affymetrix GeneChips by us [14]. Pathology characteristics of the CP tissue specimens are listed in Table 1. Cell sorting was not possible for these CP samples because of insufficient specimen quantity received (<0.5 g) for MACS. Additionally, the presence of significant non-cancer in the samples (as indicated by TIMP1 Western) or that of multiple CD cancer cell types (e.g., CD10+), especially in the higher Gleason grades [7, 8], was also problematic. Some of the most differentially expressed genes identified by HTself in cancer cells were compared to gene expression levels in whole tissue specimens (Figure 3). Data was reported as a composite value of RMA-normalized Affymetrix signal intensities: M i = log2(ratio) = X i -X a . For most, there was concordance between sorted cell and tissue expression (e.g., down-regulation of ABP1 and up-regulation of BCMP11 in cancer). The main apparent discordance was seen in genes analyzed as down-regulated by cell datasets (AFF3, GDEP, RLN1) but not by tissue datasets. This could be explained by the likelihood that these genes were expressed by cell types other than luminal or cancer epithelial in the tissue specimens. Expression of stromal cell genes PENK [24] and THY1/CD90 [14] was minimal indicating that CD26 sorting was efficient enough to exclude CD90+ stromal cells [14], the other major cell type of tumor tissue. These results also indicated that processing for MACS did not significantly affect gene expression.
Cancer cell vs . cancer tissue transcriptomes. Profile of genes with ≥ 8-fold difference in expression in cancer compared to normal luminal cells as determined by analysis of sorted CD26+ (NP and CP) cells and whole tissue transcriptomes (NP and CP). Positive log2(Cancer/Normal) on the y-axis indicates increased cancer expression while negative log2 indicates decreased cancer expression.
Table 1 Prostate tumors used to generate CP tissue expression datasets.
Wnt signaling in prostate cancer
FZD8, WIF1 and SOX7 were identified by HTself as differentially expressed between cancer and luminal cells, and in whole tissue CP compared to NP (see Figure 3 and Additional File 1). In the cancer cells as well as cancer cell lines (data not shown), there was increased expression of Wnt receptor FZD8; decreased expression of Wnt inhibitor WIF1, which functions to sequester Wnt molecules from receptor binding, and that of the transcription factor SOX7. Stromal expression of WNT2 and SFRP4 suggests Wnt signaling between stromal and epithelial cells in the prostate. SFRP4 was also recently found to up-regulated in tumor-associated stromal cells [14]. FZD8, WIF1, SOX7 identified in our analysis appeared to contribute to an elevated expression of genes controlled by the Wnt molecule (increase in receptors and decrease in inhibitors). Uncontrolled Wnt signaling had been reported in many types of cancer, including prostate [25]. Here, we identified three key members of this signaling pathway that were abnormally expressed in the CD26+ cancer cells.
Transcription factors with increased expression in cancer
The up-regulation and down-regulation of genes in the cancer cells could also be attributed to the activation of specific transcription factors such as ATF3, RUNX2, ERG, DLX1 (and DLX2) identified in the cancer cell transcriptomes. The fold increase in CD26+ cancer cells over luminal cells for ATF3 = 9, RUNX2 = 9, ERG = 21, DLX1 = 11 was similar to that for AMACR = 12 and HPN = 8. Prostate cancer up-regulation has been previously documented for ATF3 [26], RUNX2 [27] and ERG [28]. ATF3 is involved in cell proliferation and survival, and is regulated by androgen in prostate cancer cells. RUNX2 is overexpressed in cancers that, like prostate cancer, metastasize to bone. ERG is the fusion partner of TMPRSS2 in prostate cancer [29]. DLX1 may be involved in epithelial-neuronal cell conversion [30], as prostate cancer not infrequently displays neuroendocrine differentiation. Immunohistochemistry verification of DLX1 gene expression levels with anti-DLX1 showed protein expression was localized to the cancer cell nuclei (Figure 4A).
Prostate cancer genes. A: Cancer expression of DLX1. Immunohistochemistry shows positive nuclei (three examples indicated by red arrows, left panel) of cancer cells (case 04-030E) strongly stained. Cancer glands are negative for basal CD104 (top right) and luminal CD10 (bottom right); original magnification 200×. B: Candidate prostate cancer biomarkers. Genes with increased expression (based on array signal values as used in Fig. 1C) in CD26+ cancer vs. luminal (arrowheads) that encode secreted - AGR2, CEACAM5, CRISP3, NEO1, membrane anchored - LOX, BCMP11 or transmembrane - KCNH8, KCNG3 proteins are shown. C: Western blot verification of AGR2 expression. In nearly all cases of CP except 08-032 (indicated by arrow), AGR2 protein was detected at higher levels. AGR2 in any matched NP samples may be derived from diffusion from the cancer foci. D: Candidate biomarkers from LNCaP. Through dataset analysis, these genes were found differentially expressed between CD10-/CD26+ cancer and CD10+/CD26- LNCaP.
Prostate cancer biomarkers
Genes encoding secreted or extracellular proteins with increased expression in prostate cancer may serve as potential biomarkers for diagnosis or prognosis. Several genes that encode these proteins were upregulated in the CD26+ cancer cells: AGR2, BCMP11, CEACAM5/CD66e, CRISP3, KCNG3, KCNH8, LOX and NEO1 (Figure 4B). These proteins could be measured in biospecimens by using, for example, quantitative proteomics methods. Except for AGR2 (anterior gradient 2, signal intensity at 4168 vs. 77 in luminal), their signal intensity indicated that their abundance was in the moderate class (e.g., 268 for BCMP11; 217 for CRISP3). BCMP11 (breast cancer membrane protein, also known as AGR3) was originally discovered by proteomics in breast cancer cell lines T-47D and MCF-7 [31]. BCMP11 was specific to cancer and not found in normal ductal epithelial cells. The related AGR2 was previously shown to be androgen-inducible and overexpressed in prostate cancer [32, 33]. A ~19-kDa AGR2 protein was detected in cancer tissue preparation by mass spectrometry of 2-D gel electrophoresis spot [34]. Western blot analysis of CP vs. NP media confirmed overexpression of AGR2 protein in cancer (Figure 4C). Note that the lower level of AGR2 protein in 08-032 CP was concordant with decreased expression of AGR2 in this G4 cancer transcriptome (see below). LOX and NEO1 also appeared to be expressed by NP stromal cells, which would make them less suitable as cancer biomarkers.
Genes potentially associated with node metastasis
The cancer cell transcriptomes were compared to the cancer cell lines for markers potentially associated with advanced disease. These cells have been in culture for many years and have undergone changes as a result; however, the expression of certain genes related to prostate cancer metastasis could still be maintained. For example, for lymph node metastasis, potentially important genes could be identified through a comparison of the CD26+ cancer and LNCaP transcriptomes. Node metastases are CD10+, whereas the CD26+ cancer cells are CD10-, so it is possible that LNCaP is a representative of the CD10+ cancer cell type found in ~30% of prostate tumors and nearly all positive nodes [8]. The two datasets were analyzed to identify genes differentially expressed by ≥8-fold. All genes known to be involved in CELL PROLIFERATION as annotated in GeneOntology were filtered out. There are other genes whose expression appeared to be linked to cell culturing [35], but because they belong to different functional categories they were not filtered out. Genes with increased expression in LNCaP (and its lineage-related C4-2, which has extensive shared gene expression [15]) were examined in CD26+ cancer. Figure 4D shows the expression of cancer/testis melanoma antigens MAGE and GAGE. Expression of GAGE-7 in LNCaP was reported in the literature [36]. Kufer et al. [37] reported that MAGE expression in circulating epithelial cells was detected significantly more in patients carrying a higher risk of disease recurrence than those with a lower risk. Patients with metastasis had higher MAGE expression compared to those with localized disease. There was also concordance in expression between primary tumors and bone marrow. In line with these genes, a gene called preferentially expressed antigen in melanoma (PRAME) was also scored in LNCaP and C4-2. Other candidates included DDC, MANEA, ZWINT, while ERG and SERPINA3 were examples of genes scored with decreased expression in LNCaP compared to CD26+ cancer. Genes with the least fold difference in expression, not unexpectedly, were those encoding ribosomal proteins. For pathway visualization, the LNCaP>CD26+ cancer analysis result was uploaded to KEGG. Two notable networks for the data were ANDROGEN AND ESTROGEN METABOLISM and FATTY ACID METABOLISM. It is known that androgens and lipid metabolism are coupled in LNCaP cells leading to accumulation of neutral lipids [38].
Comparison between Gleason 3 and Gleason 4 cancer cells
HTself analysis of differentially expressed genes between G3 and G4 identified 147 genes with increased expression and 197 genes with decreased expression by at least 8-fold in G3 relative to G4 cells (see Additional File 3 for full list). In this set, the genes with the highest fold differential expression included many of the secreted biomarker candidates (cf. Figure 4B). Their expression ratios in G3 vs. G4 cells were: AGR2 = 13.4, BCMP11 = 18.6, CEACAM5 = 8.6, CRISP3 = 0.1, KCNG3 = 0.5, KCNH8 = 2.0, LOX = 2.5, NEO1 = 1.6 (Figure 5A). For most secreted biomarker candidates, expression was lower in G4 cells. The relative expression of ANXA1 in the CD26+ cancer cells vs. luminal cells was also decreased in G4 compared to G3, whereas relative IL6 expression was increased. Decreased expression of ANXA1 has been associated with prostate cancer and was postulated to enhance tumor aggressiveness via the induction of IL-6 [39]. Loss of the androgen-regulated tumor suppressor EAF2, which has been reported in high grade tumors [40], was also evident in both G3 and G4 cells. Increased CRISP3 immunostaining in grade 4 (8.5-fold) was reported by Bjartell et al. [41]. Note also the decrease in BRE and the loss of CD38 expression, which has as one of its functions to make a cell susceptible to apoptotic signals. Differential CD38 staining has been reported in prostate cancer by us [7]. Like CRISP3 and KCNG3, AMACR, HOXC6, HPN, and PCA3 expression was increased in G4 compared to G3. The G3/G4 ratios were: AMACR = 0.7, HPN = 0.3, PCA3 = 0.6; plus DAD1 = 1.8, HSD17B4 = 3.1, MAOA = 0.7, three of the markers reported to be up-regulated in grade 4 and 5 [1]. Of the 5-gene signature presented by Singh et al. [6], only HOXC6 showed a 5-fold increase in our G4 dataset. Although the whole tissue transcriptomes were derived from tumors of mixed cancer cell types, they could be grouped into two Gleason categories: three of Gleason 3+4, and two of Gleason 4+5 tumors. Relative differential expression with respect to higher Gleason score was verified for the down-regulation of biomarker candidates AGR2, ANXA1, BCMP11, BRE, CD24, FZD8, KCNH8, LOX and the up-regulation of ANPEP, MME, HOX6C, and MAOA (Figure 5B).
Differential gene expression between Gleason 3 and Gleason 4 transcriptomes. A: Expression levels of selected genes in G3 and G4 relative to luminal cells. B: Expression levels of these G3 and G4 genes in G3+4 vs. G4+5 tumors. C: Differential expression of epithelial genes in G3 and G4 relative to luminal cells. D: Display for LNCaP genes in primary tumors. Positive log2(Cancer/Normal) on the y-axis indicates increased cancer expression and negative log2 indicates decreased cancer expression.
The expression of epithelial genes such as ACPP, AZGP1 (zinc α2-glycoprotein), KLK2/hK2, KLK3, and MSMB showed a trend toward down-regulation relative to luminal cells (Figure 5C). With regard to the epithelial cytokeratins (KRT), relative expression levels of luminal cell KRT8 and KRT18 were increased in G3 and G4, whereas those of basal and intermediate cell KRT5, KRT14, KRT17 were significantly decreased. KRT19, which is expressed by both basal and luminal epithelial cells and is thought to be a marker of the transit-amplifying population [42], was slightly increased in G3, but decreased in G4 with respect to luminal cells.
The LNCaP genes as potential markers of metastatic potential were also queried between G3 and G4 (Figure 5D). Note the decrease in ERG (2.3-fold) and SERPINA3 (53.5-fold) in G4 cells as that found in the G3/LNCaP comparison. Of the others, PRAME showed a 13.6-fold increase in G4. No expression of MAGE or GAGE was seen.
For pathway visualization, the G3 vs. G4 cancer analysis result was uploaded to KEGG. Notable networks for the data included EXTRACELLULAR MATRIX-RECEPTOR INTERACTION and CYTOKINE-CYTOKINE RECEPTOR INTERACTION. One of the most differentially up-regulated genes in G4 cells was CCL3 (chemokine C-C motif ligand, Additional File 3). CCL3 encodes the α subunit of MIP1 (macrophage inflammatory protein-1), which is active in recruitment and activation of polymorphonuclear leukocytes in acute inflammation. The β subunit gene, CCL4, was also differentially expressed in G4. CCL4 was recently reported to be associated with prostate cancer recurrence by Blum et al. [43].
Comparison with other cancer datasets
Two publicly available high throughput gene expression datasets available for comparison with our data were GSE6099 [44] and GSE5132 [1]. The GSE6099 dataset is comprised of n = 104 laser-capture microdissected (LCM) cells for non-cancer, premalignant prostatic intraepithelial neoplasia (PIN), primary tumor, and metastasis analyzed against non-cancer prostate RNA obtained from a commercial source in two-color cDNA arrays. The arrays contained 20,000 probes mapped to 9,704 known genes, from which the overlap with the HU133 array was 7,698 genes. The GSE5132 dataset is comprised of n = 30 LCM cells for non-cancer, Gleason grades 3, 4 or 5 cancer analyzed against normal adjacent glands in two-color cDNA arrays. The arrays contained 15,488 probes mapped to 3,615 known genes, from which the overlap with HU133 was 3,135 genes. The overall correlation (~0.2) between the CD26+ G3 cancer dataset and these, which included Gleason 3 cancer, was rather poor (Figure 6A). It is important to bear in mind that the comparison involved different array platforms (Affymetrix DNA vs. cDNA arrays), cell isolation methods (MACS vs. LCM), cancer/normal comparison (sorted normal cells vs. commercial RNA of normal vs. adjacent normal glands). When GSE6099 and GSE5132 were compared for the best correlation possible, the result was also poor with a mean of 0.25 (range: 0.16-0.36 for all possible permutations). We created an Excel-based query tool to display the expression pattern of a particular gene across all these datasets (Figure 6B). For example, MME/CD10 was down-regulated in the CD26+ G3 cancer cells, and both GSE datasets showed agreement (some expression was detected in the stromal cells of GSE6099). The fold decrease was largest between CD26+ G3 cancer cells and luminal cells, as possible from a cell-to-cell comparison. FZD8 was shown up-regulated in CD26+ G3 cancer cells, and the GSE6099 dataset also showed agreement; GSE5132 contained no information regarding FZD8. For the candidate secreted biomarkers, there was no information for CRISP3, KCNG3 or KCNH8 in GSE6099; for BCMP11, CEACAM5, CRISP3, KCNG3 or LOX in GSE5132. AGR2 in the GSE6099 dataset is shown, and increased expression was detected in PIN. Immunohistochemistry had previously shown AGR2 expression in high-grade PIN [32].
Dataset comparison to 05-179 Gleason 3 transcriptome. A: Dataset correlation. Each node represents a single dataset with the first data point being the 05-179 CD26+ cancer transcriptome (in red). In the GSE6099 display, the flanking lowest correlates are those of non-cancer and stromal cells (see B). B: Single-gene query displays. Shown are those for MME/CD10 in both GSE6099 (top), where the laser-captured Gleason grade 3's are indicted by black dots, and GSE 5132 (bottom); FZD8 and AGR2 in GSE6099. Positive log2(Cancer/Normal) on the y-axis indicates increased cancer expression and negative log2 indicates decreased cancer expression.
Transcriptome analysis of CD26+ prostate cancer cells demonstrated that it was possible to isolate and characterize gene expression in cancer cells from solid tumors weighing 0.5 g or more utilizing our cell sorting methodology. The extensive tissue processing also did not appear to alter substantially the gene expression profiles of the cancer cells or the tumor-associated stromal cells reported previously [14]. Because each tumor could be unique in certain aspects we chose to determine differentially expressed genes by HTself data analysis rather than treating them as biological replicates of each other. The CD26+ cancer datasets obtained were representative of Gleason grades 3 and 4. Grade 3 tumors show a glandular morphology whereas grade 4 tumors are typically less glandular. Sorting for grade 5 is problematic as Gleason 5+5 tumors are rarely seen. According to many pathologists, cells of Gleason grade 3 are those that are first recognizable as cancerous. Compared to the normal counterpart luminal cells, the expression of a variety of genes was found to be different. This could be due to the altered expression of several transcription factors. Some of the genes identified are involved in cell division and response to apoptotic signaling. Genes of the Wnt pathway, which is important in epithelial-stromal cell interaction, appeared to be dysregulated to produce increased Wnt signaling in the cancer cells. Targeting this particular pathway may prove effective in prostate cancer.
The cancer cell types profiled in this study were the CD10- luminal-like types, although one populated a Gleason 3+3 tumor and the other a Gleason 4+4 tumor. Their respective transcriptomes represent the signatures of two distinct prostate cancer cell types. As greater numbers of cancer cell types from different cases are analyzed, it will be interesting to determine if dissimilarities in gene expression increase with higher Gleason grades. This could be visualized using PCA. The number of possible prostate cancer cell types is currently unknown, and tumor behavior could be dependent on its composition of various cancer cell types. For example, the CD10+ type is associated with lymph node metastasis and poor outcomes [8, 45]. Isolation of this cell type is hampered by the fact that luminal cells are also CD10+ and CD10 staining of biopsy is currently not a standard practice. Other cell types like CD44+ [46] are even more rarely encountered.
The identification of candidate biomarkers for cancer detection and disease stratification in this study is of practical utility. Their identity would provide for a targeted approach to analyze for their presence in body fluids such as urine and blood. Genes that encode secreted proteins are particularly useful as most, if not all, clinical tests are based on immunodetection of these types of molecules. Since cancer cells are non-functional, it was not expected that many such proteins would be found. As can be inferred from the array signal intensity levels, expression of the major functional prostatic secretory proteins ACPP, AZGP1, KLK2, KLK3, and MSMB was down-regulated in the cancer cells compared to the luminal cells. Of the candidates, AGR2 appeared most promising. AGR2 is a relatively small protein and is produced apparently at a high level based on the array signals (>4000). AGR2 was also readily detectable in the tissue digestion media of cancer specimens by Western blot analysis. AGR2 expression may be decreased in higher Gleason tumors. Thus, AGR2 could potentially serve as a target biomarker for early disease detection. In contrast, the secreted CCL3/CCL4 could serve as a biomarker of tumors containing a G4 cancer cell type. Care must be taken to ensure that these potential biomarker proteins are not produced significantly by other cell types. Expression of these candidates will be examined in greater detail by tissue microarray analysis. A multimarker panel could conceivably be generated to incorporate all informative genes to diagnose prostate cancer.
In summary, we have determined the transcriptomes of CD26+ primary prostate cancer cells isolated from Gleason grade 3 and grade 4. Grade 4 is usually associated with poor clinical outcomes. Therefore, genes differentially expressed between these two grades have prognostic potential. The method we have described to isolate primary prostate cancer cells for transcriptome analysis should be applicable to other solid tumors.
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The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/9/452/prepub
We thank Adam van Mason for specimen collection; Dr. Marc Dall'Era for comments. This research was funded in part by grants CA111244, CA98699, CA85859 and DK63630 from the National Institutes of Health. RZNV was partially supported by P50-GMO-76547 when he was at the Institute for Systems Biology.
Laura E Pascal
Present address: LEP, University of Pittsburgh Medical Center, Department of Urology, 5200 Centre Ave, Pittsburgh, PA, 15232
Department of Urology, University of Washington, Seattle, WA, 98195, USA
, Laura S Page
, Emily S Liebeskind
, Christina P Shadle
& Alvin Y Liu
Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, 98195, USA
Institute for Systems Biology, Seattle, WA, 98103, USA
Ricardo ZN Vêncio
, Pamela Troisch
, Bruz Marzolf
& Leroy E Hood
Genetics Department, University of São Paulo's Medical School at Ribeirão Preto, Brazil, CEP: 14049-900
Department of Pathology, University of Washington, Seattle, WA, 98195, USA
Lawrence D True
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Correspondence to Alvin Y Liu.
LEP and AYL designed research; LEP, LSP, ESL, CPS, PT, BM, and AYL performed research; LDT provided pathology analysis, assisted with study design and helped write the manuscript. LEH assisted with study design. LEP, RZNV, and AYL analyzed data; LEP, RZNV and AYL wrote the manuscript with contribution from the coauthors. All authors read and approved the final manuscript.
Additional file 1: Differentially expressed genes in cancer. Differentially expressed genes between G3 CD26+ cancer cells and CD26+ luminal cells were identified by HTself. Genes with ≥8-fold difference in expression are listed. Entries in green were previously reported in other public datasets. ESTs are highlighted in tan. Wnt pathway genes are highlighted in yellow. (XLS 101 KB)
Additional file 2: Self-self experiment with HTself cutoff for differential expression. The HTself method was applied to self-self experiments (orange points) with a 99.9% credibility interval to generate the intensity-dependent curve (green). The x-axis represents the RMA-normalized intensity average (X i/2 + X j/2) and the y-axis represents the logarithmic ratio (X i - X j) using self-self data (cancer i vs. cancer j). Actual data points (non-self-self) are compared against the intensity-dependent cutoffs. See ref. 18 for details. (PNG 32 KB)
Additional file 3: Differentially expressed genes in G3 and G4. Differentially expressed genes between G3 CD26+ cancer cells and G4 CD26+ cancer cells were identified by HTself. Genes with ≥8-fold difference in expression are listed. (XLS 628 KB)
Pascal, L.E., Vêncio, R.Z., Page, L.S. et al. Gene expression relationship between prostate cancer cells of Gleason 3, 4 and normal epithelial cells as revealed by cell type-specific transcriptomes. BMC Cancer 9, 452 (2009) doi:10.1186/1471-2407-9-452
Prostate Cancer Cell
Prostate Cancer Cell Line
Luminal Cell


If Corinne Aultman (Voice, Aug. 24) says the asterisk should remain next to Roger Maris` name in the record books, then stars should also accompany the names of Pete Rose and Hank Aaron.
It took Rose more than 2,000 at-bats and Aaron more than 3,000 to establish their records. They also played in longer seasons, thus accounting for many of those ''extra'' at-bats. How many hits did Rose have at the same at-bats Ty Cobb had when he set his record? How many home runs for Aaron at Ruth`s equal at-bats? Standards should be fair, not convenient or popular.


Just letting you know we have snared a slot at this years New Years Eve Celebrations on the Parramatta River. It's a family friendly, alcohol free event. Apart from the usual fireworks (and us), there's a stack of entertainment from roaming street theatre to a jet ski display. Bring on the New Year!!


text:
Q: How to implement polymorphism correctly with protobuf.js and reflection Suppose I have a class hierarchy implemented in c# with Protobuf.net. (There would also be a Rectangle class which implements Shape, but I've omitted this for brevity.)
[ProtoContract]
[ProtoInclude(1, typeof(Circle))]
public class Shape {
}

[ProtoContract]
public class Circle : Shape {

    [ProtoMember(1)]
    public int Radius {get;set;}
}

I want to represent this same class hierarchy in TypeScript using protobuf.js. However, I can't seem to figure out how to map back the 'oneof' field to the subclass.
This is the best I've been able to come up with:
// It's not possible to make this inherit from 'Shape'
class Circle extends Message<Circle> {
  @Field.d(1, "int32")
  radius: number;
}

class Shape extends Message<Shape> implements IShape {
  @Field.d(1, Circle)
  circle: Circle;

  @OneOf.d("circle") // ,"rectangle"
  which: string;

  // Implements the property on ICircle
  get radius(): number {
    return this.circle.radius;
  }
}

interface IShape {
}

interface ICircle extends IShape {
  radius: number;
}

function isCircle(shape: IShape): shape is ICircle {
  return (shape as any).which === "circle";
}

const shape = new Shape({
  circle: new Circle({ radius: 5 }),
  which: "circle"
});

const buffer = Shape.encode(shape).finish();
const decoded = Shape.decode(buffer);

if (isCircle(decoded)) {
  const itsACircle: ICircle = decoded;
  // Do something
}

This feels hacky to me, because:

*

*We have to expose all the possible sub-class fields as properties on the base Shape class (in this case the radius property of Circle).

*None of the classes actually implement ICircle, so if we fail to properly expose some properties, the compiler won't warn us.

*The type guard relies on a cast to any.

Can anyone suggest a better way of achieving this?

redpajama_set_name: RedPajamaStackExchange


The shrine buildings reveal the beauty of magnificent Japanese architecture at the center of worship toward Mt. Myogi.
Myogi Shrine is located at the foot of Mt. Hakuun which is the main peak for Mt. Myogi known for its strangely-shaped rocks, and is a dignified shrine with an abundance of old cedar trees. Known to grant good fortune, thriving business, scholastic excellence for children, matchmaking success, and even good luck to farming silkworms, it has attracted many worshipers especially from the Kanto area. The various buildings including the National Important Cultural Asset of the head shrine, the Karamon gate and the main gate were built between the early and middle Edo Era, and as magnificent structures holding the gist of the architecture from those times along with the 10m-high gigantic mossy stone walls, the beauty of traditional Japanese architecture can be viewed everywhere. The view from the shrine repository (a former palace) displaying the shrine's treasures brings in the full view of the Kanto Plain which forms a borrowed landscape garden.


An open and free forum to ask your plumbing questions. The Plumbing Forum boasts that they are the "Most popular, dynamic plumbing, kitchen and bath discussion, help, and advice forum on the net." We agree!
A great resource for homeowners and businesses, this site goes way beyond choosing efficient appliances. Find hints from making your home more comfortable to using your TV more efficiently. If you would like to land directly on the page for information on hot water heaters, click here.
The entire sewer lateral line from your home to the MSD main is private property. However, the City's Sewer Lateral Repair Program (SLRP) was created to assist homeowners with the cost of repairs under the public right of way section of the line. Click here to find out more about your local Sewer Lateral Program.
While spring brings the promise of warm weather and longer days, it also brings a variety of conditions that can include heavy rains, flash flooding, and rapid snow-melt that can increase your flood risk. Consider your risk and the consequences of a flood event, and make the choice to protect yourself.
MSD Project Clear is the initiative to improve water quality and alleviate many wastewater concerns in the St. Louis region. It will invest billions of dollars over a generation in planning, designing, and building community rain-scaping, system improvements, and an ambitious program of maintenance and repair.


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The tiger springs in the new year. Us he devours.
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People, Religion
Well, dating has become a sport and not about finding the person you love.
I really appreciate family. I really can't imagine life without them!
I hope to make people realize how totally helpless animals are, how dependent on us, trusting as a child must that we will be kind and take care of their needs.
The greatest work of art about New York? The question seems nebulous. The city's magic and majesty are distilled in the photographs of Alfred Stieglitz and Paul Strand.
Jerry Saltz
We live in this world like a child who enters a room where a clever person is speaking. The child did not hear the beginning of the speech, and he leaves before the end; and there are certain things which he hears but does not understand.
In both business and personal life, I've always found that travel inspires me more than anything else I do. Evidence of the languages, cultures, scenery, food, and design sensibilities that I discover all over the world can be found in every piece of my jewelry.
There is little of the true philosophic spirit in Aquinas. He does not, like the Platonic Socrates, set out to follow wherever the argument may lead.
Philosophy, Spirit
Whether you come from heaven or hell, what does it matter, O Beauty!
The Holy Spirit can't save saints or seats. If we don't know any non-Christians, how can we introduce them to the Savior?
Paul Little
The test of a man or woman's breeding is how they behave in a quarrel.
Man, Tests
Some people think that God peers over the balcony of heaven trying to find anybody who is enjoying life. And when He spots a happy person, He yells, Now cut that out! That concept of God should make us shudder because it's blasphemous!
Even voting for the right is doing nothing for it. It is only expressing to men feebly your desire that it should prevail. A wise man will not leave the right to the mercy of chance, nor wish it to prevail through the power of the majority. There is but little virtue in the action of masses of men.
Has it ever struck you that the vast majority of the will of God for your life has already been revealed in the Bible? That is a crucial thing to grasp.
I'm one of five kids and we lived on a massive farm in New South Wales with my mum and dad.
I was frustrated out of my mind, trying to figure out the will of God. I was doing everything but getting into the presence of God and asking Him to show me.
I need to develop a car and engineer a car in a position that feels comfortable for me, and I don't think anyone can do a better job than I can in that position. The problem for me is if I can't get the car there I do struggle more than some.
I regard myself as a soldier, though a soldier of peace.
Others think it's a choice between doing what we want to do and being happy, and doing what God wants us to do and being miserable.
A seared conscience is one whose warning voice has been suppressed and perverted habitually, so that eventually instead of serving as a guide, it only confirms the person in his premeditatedly evil course.
Robert J. Little
There is no try. There is only do.
Doing, success, Trying
Never let an inventor run a company. You can never get him to stop tinkering and bring something to market.
Royal Little
We don't watch the film anymore because we've seen it so many times, so we'll introduce it, walk out and we'll come back in right about when I wake up in the morning and walk over to the shop and everything's changed.
There is no such thing as a perfect leader either in the past or present, in China or elsewhere. If there is one, he is only pretending, like a pig inserting scallions into its nose in an effort to look like an elephant.
Liu ShaoCh'I
After spending many years in Wall Street and after making and losing millions of dollars I want to tell you this: It never was my thinking that made the big money for me. It always was my sitting.
I determined never to stop until I had come to the end and achieved my purpose.
Nothing earthly will make me give up my work in despair.
I will place no value on anything I have or may possess except in relation to the kingdom of Christ.
I will go anywhere, provided it be forward.
The more wit the less courage.
Using your mind is a faster method to getting what you want. I mean, all you have to do is sit there. What could be easier?
Cosmic, Cosmic-ordering, Law-of-attraction, Mind-body-spirit, Mind-power, money, New-age, New-thought, Positive-thinking, Self-help
Fear God and work hard.
We were all born equal, but where we are in life now is of our own making.
Abundance-creation, Cosmic-ordering, Focus, Goal-setting, Goals, happiness, Law-of-attraction, Life-changing, Manifestation, Manifesting
What a squalid and irresponsible little profession it is. Nothing prepares you for how bad Fleet Street really is until it craps on you from a great height.
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redpajama_set_name: RedPajamaCommonCrawl


Fresh off revelations over his involvement in Sestak-gate, former president Bill Clinton pounded the podium yesterday in support of a fellow member of the Democratic Party's endangered species: moderates. Senator Blanche Lincoln (D-AR) is facing a tough run-off against the sitting Lt. Governor who is allied with a vast leftwing conspiracy to make an example out of the on again, off again liberal.
And Bill Clinton doesn't like it.
Playing on both local pride and a wariness of outside influence, he suggested voters would be mere pawns for an agenda of party purification if they opposed Lincoln.
With a detailed recitation of Lincoln's work on behalf of Arkansas down to the jobs she saved at a manufacturer in Ft. Smith, Clinton exhorted voters to not direct their discontent at her.
Good luck with that. Of all the endangered political species this election cycle, none seems as likely for a population reduction than "moderate" Democrats. Liberals, like conservatives, like politicians who take a consistent ideological stand for issues. Too often being a "moderate" is just code for policymaking as situational ethics. If Clinton fails to push Lincoln over the 50% mark, he'll be on the hook for letting down yet another female senator seeking federal office (his wife Hillary being the other). With Obama 0-for-3 in hotly contested races, that means Democrats running for reelection in 2010 will have to look to someone other than the two most recent Democratic presidents to gin up enough support to get a win on Election Day.
We can hope that Obama, an intelligent man, learns from the errors of his ways. But the great danger in all of this is that in the face of his troubles Obama and his aides become increasingly defensive, display a greater sense of entitlement and even a touch of paranoia. When arrogant men lose control of events it can easily lead to feelings of isolation, to striking out at critics, to bullying opponents, and to straying across lines that should not be crossed.
And so the president needs to surround himself with people who can tamp down on the uglier impulses within his administration, who are willing to tell Obama that the lore created by him, Axelrod, Plouffe, and Gibbs during the campaign has given way to reality, that cockiness is not the same as wisdom, and that spin is no substitute for substantive achievements. And Obama needs someone who has standing in his life to tell him that the presidency is a revered institution that should not be treated as if it were a ward in Chicago.
The last line is the most telling because it goes to the nub of the problem facing every president: you go with what you know. For top level politics, that means once you assume high office the learning is over; all you have time for is applying your principles and experiences to the situation of the moment. For Obama, that means two things: rallying the troops for an us-vs.-them campaign, and treating every political decision as though being president is the same as being the mayor of Chicago – which is to say, a distributor of political patronage.
The criminal silliness of the Sestak Scandal can only be understood in the context of brash, Illinois-style horse trading. That it happened isn't much of a surprise. That it happened without much subtlety and discretion is – to me – much more troubling. Like Obama's naïve approach to America's enemies and his self-indulgent speeches, this is yet another example of his immaturity.
Yesterday, the Commerce Department revised its already-sluggish initial 3.2% first quarter gross domestic product (GDP) estimate downward to 3.0%. Additionally, the Commerce Department reported that corporate profits slowed to 5.5% in the first quarter of 2010, down from the 8% growth rate of the 2009 fourth quarter.
These numbers are disturbing because our economic recovery should be much stronger at this point, and gaining steam rather than slowing. Coming out of the 1981-1982 recession, the last downturn comparable to the 2008-2009 recession, the U.S. logged remarkable GDP quarterly growth rates of 5.1%, 9.3%, 8.1% and 8.5% for 1983. America's torrid Reagan Recovery continued into 1984, with 8.0% and 7.1% growth rates in the first two quarters. That constituted impressive growth, on the heels of Reagan's tax-cutting and deregulatory platform.
In contrast, we've now witnessed GDP growth rates of 2.2%, 5.6% and now a deceleration to 3.0%. Obama and Democrats take joy in claiming credit for our natural cyclical recovery, but what they should instead be doing is explaining why their policies are tossing a wet blanket over what should be stronger growth.
That's the point made by Daniel Henninger in today's Wall Street Journal.
I would argue that the Reform wave building in the land is not antigovernment, but pro-government. When people call themselves Americans, Californians, New Yorkers, Illinoisans, Texans or, yes, New Jerseyans, they aren't just talking about a place name, but a fought-for legal entity with a grand political history. Anger at Albany, Sacramento, Springfield, Trenton and Washington, D.C., isn't antigovernment. It's rightful rage at years of misgovernance.
I think Henninger's argument is the best description of the anger roiling supporters and critics of the Obama Administration's handling of the Gulf Oil Spill. It may very be that there are limited options for "plugging the hole," but the fact remains that people expect leaders to show they know how to prioritize problems, and work towards a solution. Even James Carville is apoplectic at Obama's seeming inability to do either during this crisis.
For the president who promised competence, we're getting an awful lot of failing grades in Leadership 101.
Since the Obama Administration and newly minted Senate candidate Joe Sestak (D-PA) won't discuss Sestak's February allegation that a White House official offered him a job not to primary party-switching Arlen Specter, Rep. Darrell Issa (R-CA) is looking into the matter. As CFIF readers remember, Issa's interest is not desired by most people in public life. The conservative foil to liberal Investigator-in-Chief Henry Waxman (D-CA), Issa is now comparing the Obama-Sestak offer to the Watergate fiasco.
That may be going a bit far, but the facts – and the stonewalling – are at least as important to uncover as the Valerie Plame Affair. In that case, the Vice President's Chief of Staff was convicted of four felonies for lying to federal agents and obstructing their investigation. Notice any similarities with Press Secretary Robert Gibbs' refusal to comment, and the White House declining to appoint an independent investigator?
It sounds old to keep comparing how the media would be covering Obama's actions if done by Bush, but the contrasts are still striking. This is now the second time potentially illegal negotiations over a United States Senate seat have been linked to Obama's White House. The first instance cost Illinois Governor Rod Blagojevich his job and may yet lead to a prison sentence. Now, another round of Chicago-style deal making may imperil Joe Sestak's senate campaign. At some point, you'd think lower level Democrats would start reconsidering their allegiance to a president who clearly favors backroom deals to open electoral processes.
One of the pillars of Barack Obama's 2008 campaign was that America had become too didactic toward the rest of the world, particularly toward the more anti-American elements of Europe. A kinder, gentler Obama would be the ointment to soothe all international discord, they promised.
But the Obama Administration has proven even more didactic than the Bush Administration. The primary difference is that Obama bows to antagonists like Russia and the Palestinians, while disrespecting friends like Israel.
This prompts the question of whether there exists any remaining tether whatsoever between the Obama Administration and reality. The euro has plummeted following Greece's bailout, and even the American Dow Jones Industrial Average fell below 10,000 yesterday on fears that the contagion will spread.
A word of advice to Europe: reconsider your love affair with Obama before he steers you toward even greater catastrophe.
"Any healthcare funding plan that is just, equitable, civilized and humane, must redistribute wealth from the richer among us to the poorer and the less fortunate. Excellent healthcare is by definition redistributional".
Indeed, lest there be any doubt about the range of Dr Berwick's schemes for "redistribution" – code for transferring power to the government — he makes clear how grand his vision for statist health care.
But if Dr Berwick leaves little doubt who is going to be in charge of the redistribution, global caps, and the single payer systems, he shows with his use of words like "politically accountable" or "democratic", the sort of verbal tic that betrays his own understanding. He seeks not broad-based, bottom-up decision-making but top-own edicts from elite panels of enlightened and, of course, "global" thinkers like himself that preempt decisions now made by doctors and their patients.
And that is what those of us who are practicing physicians find so troubling about Dr. Berwick's nomination. We see him as a White House Rose Garden, photo-op doctor with a borrowed white coat; an academic who runs a $58 million institute, who analyzes numbers and reports and theories about populations but is now totally out of touch with his former peers and the patients that they treat every day. And this is the sobering point– Dr Berwick will not be there with us at the patient's bedside looking them in the eye and telling them that the life saving treatment that they need is not approved because they don't fit into the right demographic.
Pretty bold stuff. Reasonable minds knew then that an Obama victory would only exacerbate the nation's deficit, even if the fawning mainstream media was refusing to press him on tough questions. But even skeptics didn't foresee just how bad and how rapidly he would do so. Today, we received sobering news that the national debt surpassed the $13 trillion mark overnight. That's now $42,000 per American citizen, and $118,000 per American taxpayer.
And that $407 billion deficit that Obama cavalierly promised to reduce in September 2008? He's now raised it from $400 billion to $1.4 trillion.
That's the type of change for which only America's enemies could have hoped.
Will Obama Blame Bush for America's Popularity?
It's become a bit of a cliché in the Obama Administration to blame George W. Bush for…well, just about everything wrong with the country. Job numbers are down because of the previous administration's mismanagement of the economy. The deficit is exploding because Bush & Co. started two allegedly needless wars. Even the Gulf Oil Spill catastrophe is being laid at the feet of alleged coziness between Bush Era regulators and BP management. If nothing else, the Obama White House knows how to trace problems occurring on its watch to other people.
Will it do the same with success? According to Gallup polls of foreign nations, America is most popular in Sub-Saharan Africa. The fact that President Obama's ancestry touches the region doesn't explain fully the reason.
It's a good question, one our friends over at Gallup have given some consideration in past surveys. Since 2008, Sub-Saharan Africa may be the one region of the world where the United States has reaped the highest benefits of what has been termed "The Obama Effect." Being of Kenyan descent, Obama enjoys high approval ratings throughout much of Africa. More substantively, 5 out of the 7 listed nations have been targeted in the president's $3.5 billion Feed the Future initiative.
And let's not give the 44th president all of the credit. Obama's predecessor, George W. Bush, invested American aid and resources into Africa at a record pace. President Bush's PEPFAR program was a groundbreaking policy endeavor, and while Bush's domestic approval numbers were low upon leaving office, U.S. approval throughout much of Africa remained rather strong.
As with much of his social spending, the most recent President Bush doesn't get the credit he deserves for the good – and goodwill – many of his initiatives achieved. Still, it must give W some sort of quiet pride to know that America's popularity in Africa can be traced directly to his policy decisions.
Fire the Census Worker, Hire the Postman?
For my fellow limited government types out there, here's an idea to save money and get the decennial census done competently: hire postal workers to count heads. The suggestion comes from one of the Census Bureau's "seasonal" workers quoted in the New York Post.
I am totally convinced that the Census work could be very easily done by the US Postal Service.
"When I was trying to look for an address or had a question about a building, I would ask the postman on the beat. They knew the history of the route and can expand in detail who moved in or out etc. I have found it interesting that if someone works one hour, they are included in the labor statistics as a new job being full.
With these facts, it seems like the census could be achieved much more efficiently by getting the postal worker on the street to knock on the door, deliver some mail, and casually ask how many people live in the unit. Since people are already comfortable with their usual postal worker, having them ask the questions would be much more likely to guarantee a response. And, it would save taxpayers the indignity of funding inflated job creation numbers.
Let's review: you cannot have a welfare state without a private sector vibrant enough to fund it. You cannot have a private sector vibrant enough to fund it unless government allows the market to function relatively unimpeded. And the market can't function relatively unimpeded unless the welfare state stays modest in scope. What exactly don't the folks in Washington, Sacramento, and Athens understand?
In an effort to circumvent a unanimous federal appeals court ruling, the Federal Communications Commission ("FCC") announced earlier this month that it will pursue a "third way" to obtain regulatory control over the Internet. Specifically, lacking the straightforward authority to impose burdensome and unnecessary regulations on the World Wide Web, the FCC is now seeking "to shoehorn Internet service into regulations drafted in the 1930s for old-fashioned landline telephones" in an effort to dramatically expand its regulatory reach.
CFIF and others have written extensively about how such an unprecedented power grab threatens to suffocate private broadband investment, jobs and Internet innovation. And, in a rare display of bipartisanship, Congress is now adding its voice of opposition, too.
The people have spoken. The courts have spoken. And now, a bipartisan and sizable group of elected officials in Congress have spoken. Will Obama's FCC finally listen?
For three months, the White House has refused to say whether it offered a job to Representative Joe Sestak to get him to drop his challenge to Senator Arlen Specter in a Pennsylvania Democratic primary, as Mr. Sestak has asserted.
That's about as succinct an explanation of a growing kerfuffle as can be written. The kerfuffle is growing because the second worst White House Press Secretary in living memory, Robert Gibbs, decided to run a cutesy stonewall when Sestak first made his allegation (when the White House was against his candidacy before it was for his candidacy), and now has escalated it into the annals of political kerfuffledom.
It would take a Special Prosecutor longer to get an office set up than it would to resolve this.
Someone (maybe multiple someones) carrying a White House briefcase said something to Sestak about a job, seemingly linked to him abandoning his candidacy. Couldn't have been a very long conversation.
Interview Sestak. Interview the someone (or someones). Conclude whether or not there is reason to believe the conversation crossed the legal line. Conclude whether or not any party interviewed committed perjury during the really brief investigation. Proceed to grand jury or issue a report.
But hey. Summer's here. Let's instead have yet another spittle-spewing Washington circus.
Already, businesses small and large are warning of the ill effects of the law's changes to the tax code. In order to generate the nearly $1 trillion necessary to pay for the law, its authors scoured the tax code looking to squeeze out more money whereever possible. And sure enough, within a few days of its passage, a handful of big companies took tax write downs in response to changes in the tax treatment of an existing drug subsidy. An estimate by Credit Suisse puts the total damage across the economy at around $4.5 billion—with $1 billion coming from AT&T alone.
The change involved the tax treatment of a subsidy that never should have existed, but it suggests the extent to which America's health care system is already reliant on government meddling, and how costly expanding the government's role in the system can be. And, perhaps more importantly, a planned investigation into the write-downs revealed that many big corporations are considering dropping their health care coverage and dumping employees onto the public dole.
When Rep. Henry Waxman (D-Calif.) heard about the write-downs, he called a hearing with AT&T and other companies claiming big hits. But soon after the subpoenaed corporate documents were turned in, the hearing was canceled. Why? Likely because, as Fortune magazine reported, the documents showed that the companies were considering dropping coverage for many employees—directly contradicting one of the president's key promises, that, under ObamaCare, "if you like your health care plan, you can keep your health care plan." Even with penalties in place for employers who decline to provide health insurance, documents showed that Caterpillar could reduce its health care costs by as much as 70 percent and AT&T could save as much as $1.8 billion by shifting their employees into public programs.
The Political Class continues to be a strong supporter of the plan, however. While 67% of Mainstream voters believe the plan will be bad for America, 77% of the Political Class disagree and think it be good for the country.
The political class is about to get knocked on their heels. And to show how it can happen (warning: incoming teaser) , later this week I'll be looking at a couple of little known-provisions in the health care bill that could prove its ultimate undoing.
The most toxic substance floating around Louisiana's coastline isn't oil – it's the confusion that comes with the federal government's alphabet soup of bureaucracy. Click on any article describing the feds' response, and you get a myriad of people and institutions allegedly "in charge" of directing the cleanup activity. So far, the heads of the EPA, Interior Department, Homeland Security, and Coast Guard have all visited the state and personally weighed in on what should be done. Now, they are contradicting each other.
In a news conference on Sunday outside the BP headquarters in Houston, Mr. Salazar repeated the phrase that the government would keep its "boot on BP's neck" for results. He also said the company had repeatedly missed deadlines and had not been open with the public.
That statement, however, conflicted with comments made only hours earlier by the Coast Guard commandant, Adm. Thad W. Allen, who said on CNN's "State of the Union" program that the access BP has to the mile-deep well site meant that the government could not take over the lead in efforts to stop the leak.
"They are necessarily the modality by which this is going to get solved," he said.
One of the consequences of bloated bureaucracies is overlapping areas of responsibility. Coupled with a politician's aversion to risk (an element of bold decision making), and the result is many people responsible, but no one is ultimately in charge.
The last few days offered a study in contrasts. Charles Djou won a plurality special election becoming just the third Republican to represent Hawaii in Congress. He did so by sticking relentlessly to a pro-growth, low tax message that resonated in a heavily Democratic district. While Djou won't vote with the GOP on every issue, his commitment to fiscal conservatism will be a huge factor in whether he gets reelected to a full term in November.
Contrast Djou's steady drum beat approach to Rand Paul's improvisational jazz. The Kentucky GOP senate nominee erased the euphoria of a double digit beat down of the establishment candidate last Tuesday by questioning the constitutionality of the 1964 Civil Rights Act, a federal law mandating racial equality. His points aside, Paul took his eye off the ball by engaging the issue. The 2010 midterm election results – and Rand Paul's popularity – are not the product of a national rethink on the scope of Congress's power to enforce the 14th Amendment's equal protection clause.
It's about the economy, Rand. The safest ground for limited government types this cycle is to stay on message that tax-and-spend must end. Just Djou it.


text:
High school football: This week's final AP state poll
Green Bay Press Gazette
Here is the final Associated Press high school football poll of the season. The poll includes first-place votes in parentheses, season record, total points and last week's ranking, as voted upon by a statewide panel of sports writers. Teams are arranged in three divisions of equal size based on current enrollments.
Large Division (enrollment 900 and up)
1. Fond du Lac (8), 9-0, 80, 1; 2. Kimberly, 8-1, 64, 3; 3. Waunakee, 9-0, 6, 2; 4. Muskego, 9-0, 54, 4; 5. Franklin, 9-0, 47, 5; 6. Marquette University, 9-0, 40, 6; 7. Bay Port, 9-0, 31, 7; 8. Monona Grove, 9-0, 29, 8; 9. Mequon Homestead, 9-0, 15, 9; 10. Brookfield Central, 8-1, 9, T10.
Others receiving votes: Sun Prairie 4, River Falls 2, Madison Memorial 2, Marshfield 1.
Medium Division (301-899)
1. New Berlin Eisenhower (4), 9-0, 74, 1; 2. St. Croix Central (2), 9-0, 72, 2; 3. Waukesha Catholic Memorial (2), 8-1, 68, 3; T4. West De Pere, 9-0, 49, 5; T4. Racine St. Catherine's, 9-0, 49, 4; 6. Little Chute, 9-0, 40, T7; 7. McFarland, 9-0, 38, 9; 8. Lakeside Lutheran, 8-1, 13, NR; 9. Maple Northwestern, 9-0, 12, NR; 10. Omro, 9-1, 7, NR.
Others receiving votes: New Berlin West 6, Winneconne 2, Amherst 2, Cedar Grove-Belgium 2, Green Bay Notre Dame 2, Spencer/Marshfield Columbus 2, Kewaunee 1, Mount Horeb/Barneveld 1.
Small Division (300 and lower)
1. Fond du Lac Springs (8), 9-0, 80, 1; 2. Edgar, 9-0, 64, 2; 3. Iola-Scandinavia, 9-0, 59, 4; 4. Lake Country Lutheran, 9-0, 54, 3; 5. Eau Claire Regis, 9-0, 45, 5; 6. Black Hawk, 8-0, 40, 6; 7. Grantsburg, 9-0, 35, 7; 8. Bangor, 8-1, 21, 8; 9. Pecatonica/Argyle, 8-1 11, 9; 10. Johnson Creek, 8-1, 10 , T10.
Others receiving votes: Hilbert 7, Cambridge 7, Stratford 5, Mineral Point 1, Almond-Bancroft 1.


Contrary to conventional views, Rigg reveals that a startlingly large number of German military men were classified by the Nazis as Jews or "partial-Jews" (Mischlinge), in the wake of racial laws first enacted in the mid-1930s. Rigg demonstrates that the actual number was much higher than previously thought-perhaps as many as 150,000 men, including decorated veterans and high-ranking officers, even generals and admirals.
Bryan Mark Rigg received his B.A. with honors in history from Yale University in 1996. Yale awarded him the Henry Fellowship for graduate study at Cambridge University, where he received his M.A. in 1997. Currently an adjunct professor of military history at American Military University, he has served as a volunteer in the Israeli Army and as an officer in the U.S. Marine Corps. His research for this book has been featured in the New York Times, Los Angeles Times, and London Daily Telegraph.


I've truly never had any crazy issues with Shein. I order a lot from them. Yes, I love how cheap the prices are but I also love the fun selection they have for everything. My love for the website started with bathing suits. I was wanting bold, fun, colourful bathing suits and I thought most bathing suits online were so boring. When I stumbled on Shein I wanted every bathing suit.
When it comes to bathing suits I think the quality is great. Don't expect next level quality, but I think it's totally comparable to most brands. I have well over 10 bathing suits from them and I've never had issues. I've also never had issues washing any item either. I even wore a full piece white bathing suit thinking it may go see through when I got it wet..but it passed the test!!
The fit is the only thing that can be a little tricky. I love to read reviews for each item because people will give their honest opinion and let you know if the product fits big, small or true to size. I still order my regular size small and for the most part everything has been fine. My last order of bathing suits I did decide to order medium because I did notice some smalls were a little tight (they still fit) but I wanted to be super comfy and medium was great. If you are tall lady like me (I'm about 5'9 - 5'10) most of the dresses and skirts are going to be way too short. I try to stay away from skirts and dresses.
I think within the last year Shein has majorly stepped up their game with everything. When I first started ordering from them my packages would honestly take a month to arrive. Now I find them totally comparable to most brands. I believe my last shipment took 11-12 days. If you want something for a trip I would still give yourself some extra time just incase. Most of my orders have been under $100 and I get regular shipping and I've never had to pay Canadian duties. However, my last order was over $100 with express shipping and I did have to pay $30 in duties. I wasn't sure if it was the price or the express shipping that was the reason for duties, but just be aware of that!


3 especially as thou art skilled both in all the customs, and questions which respect the Jews: wherefore I beg the favour of thee to hear me patiently.
5 who previously knew me a long while ago, (if they chose to bear testimony,) that according to the most precise sect of our religion I lived a Pharisee.
7 which promise our twelve tribes, with fervour night and day worshipping God, hope to attain. For which hope, king Agrippa, I am criminated by the Jews.
8 What! is it judged a thing incredible by you, that God should raise the dead?
9 I indeed then thought in myself, that I ought to do many things in opposition to the name of Jesus the Nazarean.
10 Which also I did at Jerusalem: and many of the saints did I shut up in prisons, having received authority from the chief priests; and when they were killed, I gave my vote against them.
11 And in every synagogue oftentimes punishing them, I compelled them to blaspheme; and being exceedingly maddened with rage against them, I persecuted them even to the cities that are without.
13 at midday, O king, I saw on the road a light from heaven, beyond the splendour of the sun, shining around myself and those who were travelling with me.
14 And as we were all fallen prostrate on the earth, I heard a voice speaking to me, and saving in the Hebrew tongue, Saul, Saul, why persecutest thou me? it is difficult for thee to kick against the goads.
15 Then I said, Who art thou, Lord? And he replied, I am Jesus whom thou art persecuting.
18 to open their eyes, to convert them from darkness to light, and from the dominion of Satan unto God, that they may receive remission of sins, and an inheritance with those who are sanctified by faith which is in me.
20 but preached first to those at Damascus, and Jerusalem, and to all the region of Judea, and to the Gentiles, that they should repent and turn to God, practicing works worthy of repentance.
21 Because of these things, the Jews seizing me in the temple, attempted to kill me on the spot.
23 that the Messiah should suffer, [and] that he being the first who should rise from the dead, should display light to the people, and to the Gentiles.
24 As thus he was proceeding in his defence, Festus with a loud voice said, Paul, thou art raving; much reading hath driven thee to madness.
25 But he said, I am not mad, most noble Festus; but utter words of truth and sobriety.
26 For the king is well acquainted with these things, before whom also I speak with the greatest freedom. For I am persuaded that none of these events have escaped his notice; for this thing was not done in a corner.
27 King Agrippa! believest thou the prophets? I know that thou believest.
28 Then Agrippa said to Paul, Almost thou persuadest me to be a Christian.
29 And Paul replied, would to God, that not only thou, but also that all who are hearing me this day, were both almost, and altogether such as I am, except these chains.
31 and retiring, conversed together, saying, This man hath done nothing worthy of death, or of chains.
32 And Agrippa said to Festus, This man might have been discharged, if he had not appealed to Caesar.


Rachel and Matt's wedding took place at The Bell In Ticehurst, East Sussex. I love this quirky venue! Something to look at and smile at around every corner!
Rachel's hair was curled before braiding the two sides, keeping the style very soft and natural. The back was pinned into a loose curly 'boho' knot.
Makeup was done by the very talented Jane Mather and the photography by Penny Young Photography. Such a pleasure to work with these ladies!