Cytokines are produced locally by myocytes in rat skeletal muscle during endotoxemia.

Cytokines act as chemical mediators during the inflammatory process. Measurements of cytokine levels in tissue have previously been performed in homogenized tissue, but the true concentrations in native interstitial fluid (ISF), i.e., the compartment where cytokines exert their biologically active role, have remained unknown. The role of skeletal muscle myocytes as a source for cytokines during endotoxemia was explored by collecting muscle ISF using a wick method, and the levels of 14 cytokines in ISF and plasma were related to the corresponding changes in mRNA levels to reveal any potential discrepancies between gene expression and protein release of cytokines to ISF. The majority of investigated cytokines were elevated in muscle ISF during endotoxemia, and an analysis of cytokine mRNA levels revealed consistency between gene expression and protein release. The elevated cytokine level in ISF, in addition to elevated gene expression in muscle, indicated a significant local production and release of several proinflammatory cytokines and chemokines within skeletal muscle tissue during endotoxemia. Immunohistochemistry revealed that myocytes constituted a significant source of IL-1beta and TNF-alpha production during endotoxemia, whereas the contribution from inflammatory cells i.e., leukocytes, was found to be less significant. Muscle cells apparently constitute an important source of several different cytokines during endotoxemia, governing the level in the muscle microenvironment, and are likely to contribute significantly to cytokine levels in plasma.

Comparison of nucleic acid targets prepared from total RNA or poly(A) RNA for DNA oligonucleotide microarray hybridization.

The aim of this work was to compare DNA microarray results using either total RNA or affinity-purified poly(A) RNA from the same biological sample for target preparation. The high-density oligonucleotide microarrays of both Agilent Technologies (based on two-color detection) and Applied Biosystems (based on single-color detection) were evaluated. Real-time quantitative PCR was used to quantify messenger RNA (mRNA) and ribosomal RNA (rRNA) at different stages of target preparations. Poly(A) RNA versus total RNA target hybridizations exhibited slightly lower correlation coefficients than did self versus self hybridizations (i.e., poly(A) RNA targets vs. poly(A) RNA targets or total RNA targets vs. total RNA targets). Only a small fraction of all transcripts appeared to be significantly over- or underrepresented when total RNA targets or poly(A) RNA targets from the same biological sample were compared. Therefore, the conclusion is that poly(A) affinity purification from total RNA can be omitted during target preparation for routine mRNA expression analysis using high-density oligonucleotide microarrays. Among consistently overrepresented transcripts in total RNA targets were histone mRNAs known to lack poly(A) tails. Therefore, structurally exceptional RNA species can be identified by comparing targets derived from either poly(A) RNA or total RNA using microarray hybridization.

Increased expression of SIM2-s protein is a novel marker of aggressive prostate cancer.

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.

ERG upregulation and related ETS transcription factors 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.

Gene expression profiles in prostate cancer: association with patient subgroups and tumour differentiation.

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.