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Recurrent gene fusions involving oncogenic ETS transcription factors (including ERG, ETV1, and ETV4) have been identified in a large fraction of prostate cancers. The most common fusions contain the 5′ untranslated region of TMPRSS2 fused to ERG. Recently, we identified additional 5′ partners in ETV1 fusions, including TMPRSS2, SLC45A3, HERV-K_22q11.23, C15ORF21, and HNRPA2B1. Here, we identify ETV5 as the fourth ETS family member involved in recurrent gene rearrangements in prostate cancer. Characterization of two cases with ETV5 outlier expression by RNA ligase–mediated rapid amplification of cDNA ends identified one case with a TMPRSS2:ETV5 fusion and one case with a SLC45A3:ETV5 fusion. We confirmed the presence of these fusions by quantitative PCR and fluorescence in situ hybridization. In vitro recapitulation of ETV5 overexpression induced invasion in RWPE cells, a benign immortalized prostatic epithelial cell line. Expression profiling and an integrative molecular concepts analysis of RWPE-ETV5 cells also revealed the induction of an invasive transcriptional program, consistent with ERG and ETV1 overexpression in RWPE cells, emphasizing the functional redundancy of ETS rearrangements. Together, our results suggest that the family of 5′ partners previously identified in ETV1 gene fusions can fuse with other ETS family members, suggesting numerous rare gene fusion permutations in prostate cancer. [Cancer Res 2008;68(1):73–80]

Supplementary Table 1, Figures 1-3 from A Fluorescence In situ Hybridization Screen for E26 Transformation–Specific Aberrations: Identification of DDX5-ETV4 Fusion Protein in Prostate Cancer

Although prostate-specific antigen (PSA) serum level is currently the standard of care for prostate cancer screening in the United States, it lacks ideal specificity and additional biomarkers are needed to supplement or potentially replace serum PSA testing. Emerging evidence suggests that monitoring the noncoding RNA transcript PCA3 in urine may be useful in detecting prostate cancer in patients with elevated PSA levels. Here, we show that a multiplex panel of urine transcripts outperforms PCA3 transcript alone for the detection of prostate cancer. We measured the expression of seven putative prostate cancer biomarkers, including PCA3, in sedimented urine using quantitative PCR on a cohort of 234 patients presenting for biopsy or radical prostatectomy. By univariate analysis, we found that increased GOLPH2, SPINK1, and PCA3 transcript expression and TMPRSS2:ERG fusion status were significant predictors of prostate cancer. Multivariate regression analysis showed that a multiplexed model, including these biomarkers, outperformed serum PSA or PCA3 alone in detecting prostate cancer. The area under the receiver-operating characteristic curve was 0.758 for the multiplexed model versus 0.662 for PCA3 alone (P = 0.003). The sensitivity and specificity for the multiplexed model were 65.9% and 76.0%, respectively, and the positive and negative predictive values were 79.8% and 60.8%, respectively. Taken together, these results provide the framework for the development of highly optimized, multiplex urine biomarker tests for more accurate detection of prostate cancer. [Cancer Res 2008;68(3):645–9]

Supplementary Table 1 from A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

Supplementary Figures 1-2, Tables 1-2 from Characterization of TMPRSS2:ETV5 and SLC45A3:ETV5 Gene Fusions in Prostate Cancer

Supplementary Figure 1 from A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

Supplementary Table 2 from A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

Supplementary Table 3 from A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

Supplementary Figure 1 Legend from A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

There is a life-long relationship between rhinovirus (RV) infection and the development and clinical manifestations of asthma. In this study we demonstrate that cultured primary bronchial epithelial cells from adults with asthma (n = 9) show different transcriptional and chromatin responses to RV infection compared to those without asthma (n = 9). Both the number and magnitude of transcriptional and chromatin responses to RV were muted in cells from asthma cases compared to controls. Pathway analysis of the transcriptionally responsive genes revealed enrichments of apoptotic pathways in controls but inflammatory pathways in asthma cases. Using promoter capture Hi-C we tethered regions of RV-responsive chromatin to RV-responsive genes and showed enrichment of these regions and genes at asthma GWAS loci. Taken together, our studies indicate a delayed or prolonged inflammatory state in cells from asthma cases and highlight genes that may contribute to genetic risk for asthma., Britney Helling et al. report that cultured bronchial cells from adults with asthma show different gene expression and chromatin accessibility patterns when exposed to rhinovirus than do cells from individuals without asthma. Their data suggest that rhinovirus infection leads to a delayed or elongated activation of inflammatory genes in individuals with asthma compared to those without asthma.

Background The relationship between asthma, atopy, and underlying type 2 (T2) airway inflammation is complex. Although the bacterial airway microbiota is known to differ in asthmatic patients, the fungal and bacterial markers that discriminate T2-high (eosinophilic) and T2-low (neutrophilic/mixed-inflammation) asthma and atopy are still incompletely identified. Objectives The aim of this study was to demonstrate the fungal microbiota structure of airways in asthmatic patients associated with T2 inflammation, atopy, and key clinical parameters. Methods We collected endobronchial brush (EB) and bronchoalveolar lavage (BAL) samples from 39 asthmatic patients and 19 healthy subjects followed by 16S gene and internal transcribed spacer–based microbiota sequencing. The microbial sequences were classified into exact sequence variants. The T2 phenotype was defined by using a blood eosinophil count with a threshold of 300 cells/μL. Results Fungal diversity was significantly lower in EB samples from patients with T2-high compared with T2-low inflammation; key fungal genera enriched in patients with T2-high inflammation included Trichoderma species, whereas Penicillium species was enriched in patients with atopy. In BAL fluid samples the dominant genera were Cladosporium, Fusarium, Aspergillus, and Alternaria. Using generalized linear models, we identified significant associations between specific fungal exact sequence variants and FEV1, fraction of exhaled nitric oxide values, BAL fluid cell counts, and corticosteroid use. Investigation of interkingdom (bacterial-fungal) co-occurrence patterns revealed different topologies between asthmatic patients and healthy control subjects. Random forest models with fungal classifiers predicted asthma status with 75% accuracy for BAL fluid samples and 80% accuracy for EB samples. Conclusions We demonstrate clear differences in bacterial and fungal microbiota in asthma-associated phenotypes. Our study provides additional support for considering microbial signatures in delineating asthma phenotypes.

High circulating IL-6 may define a phenotype of asthma associated with obesity and systemic inflammation. We demonstrate that circulating IL-6 is higher in African-American patients with asthma, and that race-specific thresholds should be considered.

Positive correlation between starting bacterial density and raw optical density of positive control. A positive correlation was noted between the starting bacterial density values obtained at 600Â nm and the raw optical density values of the positive control wells. P and rho values were obtained using the Spearmanâ s correlation test. (PDF 18Â kb)

NMDS ordination plot for seven CF subjects at two clinic visits (paired analysis). Principal coordinate analysis by non-metric multidimensional scaling generated from Bray-Curtis dissimilarity matrices at the genus level from seven CF subjects at two clinic visits. P value was obtained using HOMOVA. No separation was noted between the paired samples. (PDF 139Â kb)

Diversity and richness of CF microbiome in subjects at two clinic visits (paired analysis). Panels show uncensored number of genera, inverse Simpson index, Chao1 index, Shannon diversity Index. P values were generated using Wilcoxon matched-pairs signed-rank tests. No significant differences were noted between clinic visits. (PDF 17Â kb)

Soluble human leukocyte antigen-G (sHLA-G), an immunomodulatory molecule associated with suppression of inflammation, is elevated in the airways of asthmatic patients with a low inflammatory endotype as evidenced by low airway eosinophils and low exhaled nitric oxide.