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.
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.
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.
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.
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.
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Quantification of pathogen and host biomarkers is essential for the diagnosis, monitoring, and treatment of infectious diseases. Here, we demonstrate sensitive and rapid quantification of bacterial ...load and cytokines from human biological samples to generate actionable hypotheses. Our digital assay measures IL-6 and TNF-α proteins, gram-negative (GN) and gram-positive (GP) bacterial DNA, and the antibiotic-resistance gene bla
with femtomolar sensitivity. We use our method to characterize bronchoalveolar lavage fluid from patients with asthma, and find elevated GN bacteria and IL-6 levels compared to healthy subjects. We then analyze plasma from patients with septic shock and find that increasing levels of IL-6 and bla
are associated with mortality, while decreasing IL-6 levels are associated with recovery. Surprisingly, lower GN bacteria levels are associated with higher probability of death. Applying decision-tree analysis to our measurements, we are able to predict mortality and rate of recovery from septic shock with over 90% accuracy.
Noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease and to reveal uncharacterized aspects of tumor biology. Here we discover ...121 unannotated prostate cancer-associated ncRNA transcripts (PCATs) by ab initio assembly of high-throughput sequencing of polyA(+) RNA (RNA-Seq) from a cohort of 102 prostate tissues and cells lines. We characterized one ncRNA, PCAT-1, as a prostate-specific regulator of cell proliferation and show that it is a target of the Polycomb Repressive Complex 2 (PRC2). We further found that patterns of PCAT-1 and PRC2 expression stratified patient tissues into molecular subtypes distinguished by expression signatures of PCAT-1-repressed target genes. Taken together, our findings suggest that PCAT-1 is a transcriptional repressor implicated in a subset of prostate cancer patients. These findings establish the utility of RNA-Seq to identify disease-associated ncRNAs that may improve the stratification of cancer subtypes.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Chromosomal rearrangements fusing the androgen-regulated gene
TMPRSS2 to the oncogenic ETS transcription factor
ERG occur in approximately 50% of prostate cancers, but how the fusion products ...regulate prostate cancer remains unclear. Using chromatin immunoprecipitation coupled with massively parallel sequencing, we found that ERG disrupts androgen receptor (AR) signaling by inhibiting AR expression, binding to and inhibiting AR activity at gene-specific loci, and inducing repressive epigenetic programs via direct activation of the H3K27 methyltransferase EZH2, a Polycomb group protein. These findings provide a working model in which TMPRSS2-ERG plays a critical role in cancer progression by disrupting lineage-specific differentiation of the prostate and potentiating the EZH2-mediated dedifferentiation program.
► Genome-wide location analysis of AR, ERG, and epigenetic marks in prostate cancer ► Interaction and colocalization of AR and ERG to target genes in prostate cancer ► ERG disrupts AR-mediated lineage-specific differentiation of the prostate ► ERG induces EZH2 facilitating dedifferentiation in prostate cancer
Enhancer of zeste homolog 2 (EZH2) is a mammalian histone methyltransferase that contributes to the epigenetic silencing of target genes and regulates the survival and metastasis of cancer cells. ...EZH2 is overexpressed in aggressive solid tumors by mechanisms that remain unclear. Here we show that the expression and function of EZH2 in cancer cell lines are inhibited by microRNA-101 (miR-101). Analysis of human prostate tumors revealed that miR-101 expression decreases during cancer progression, paralleling an increase in EZH2 expression. One or both of the two genomic loci encoding miR-101 were somatically lost in 37.5% of clinically localized prostate cancer cells (6 of 16) and 66.7% of metastatic disease cells (22 of 33). We propose that the genomic loss of miR-101 in cancer leads to overexpression of EZH2 and concomitant dysregulation of epigenetic pathways, resulting in cancer progression.
TMPRSS2-ERG gene fusions are the predominant molecular subtype of prostate cancer. Here, we explored the role of TMPRSS2-ERG gene fusion product using in vitro and in vivo model systems. Transgenic ...mice expressing the ERG gene fusion product under androgen-regulation develop mouse prostatic intraepithelial neoplasia (PIN), a precursor lesion of prostate cancer. Introduction of the ERG gene fusion product into primary or immortalized benign prostate epithelial cells induced an invasion-associated transcriptional program but did not increase cellular proliferation or anchorage-independent growth. These results suggest that TMPRSS2-ERG may not be sufficient for transformation in the absence of secondary molecular lesions. Transcriptional profiling of ERG knockdown in the TMPPRSS2-ERG-positive prostate cancer cell line VCaP revealed decreased expression of genes over-expressed in prostate cancer versus PIN and genes overexpressed in ETS-positive versus -negative prostate cancers in addition to inhibiting invasion. ERG knockdown in VCaP cells also induced a transcriptional program consistent with prostate differentiation. Importantly, VCaP cells and benign prostate cells overexpressing ERG directly engage components of the plasminogen activation pathway to mediate cellular invasion, potentially representing a downstream ETS target susceptible to therapeutic intervention. Our results support previous work suggesting that TMPRSS2-ERG fusions mediate invasion, consistent with the defining histologic distinction between PIN and 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.
Recently, we identified recurrent gene fusions involving the 5′ untranslated region of the androgen-regulated gene TMPRSS2 and the ETS (E26 transformation-specific) family genes ERG, ETV1 or ETV4 in ...most prostate cancers. Whereas TMPRSS2-ERG fusions are predominant, fewer TMPRSS2-ETV1 cases have been identified than expected on the basis of the frequency of high (outlier) expression of ETV1 (refs 3-13). Here we explore the mechanism of ETV1 outlier expression in human prostate tumours and prostate cancer cell lines. We identified previously unknown 5′ fusion partners in prostate tumours with ETV1 outlier expression, including untranslated regions from a prostate-specific androgen-induced gene (SLC45A3) and an endogenous retroviral element (HERV-K_22q11.23), a prostate-specific androgen-repressed gene (C15orf21), and a strongly expressed housekeeping gene (HNRPA2B1). To study aberrant activation of ETV1, we identified two prostate cancer cell lines, LNCaP and MDA-PCa 2B, that had ETV1 outlier expression. Through distinct mechanisms, the entire ETV1 locus (7p21) is rearranged to a 1.5-megabase prostate-specific region at 14q13.3-14q21.1 in both LNCaP cells (cryptic insertion) and MDA-PCa 2B cells (balanced translocation). Because the common factor of these rearrangements is aberrant ETV1 overexpression, we recapitulated this event in vitro and in vivo, demonstrating that ETV1 overexpression in benign prostate cells and in the mouse prostate confers neoplastic phenotypes. Identification of distinct classes of ETS gene rearrangements demonstrates that dormant oncogenes can be activated in prostate cancer by juxtaposition to tissue-specific or ubiquitously active genomic loci. Subversion of active genomic regulatory elements may serve as a more generalized mechanism for carcinoma development. Furthermore, the identification of androgen-repressed and insensitive 5′ fusion partners may have implications for the anti-androgen treatment of advanced prostate cancer.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Importantly, the cohorts had a racial balance that was majority white (62% and 66%), with relatively few African Americans (11% and 23%). Because African Americans have a greater prevalence of ...diseases associated with low-grade systemic inflammation,6,7 the definition of an IL-6–high phenotype might differ based on race. Asthmatic patients met the criteria defined by the Expert Panel Report 3 guidelines on asthma.E9 Control subjects had no lifetime history of pulmonary disease, were in good health, did not use respiratory-related medication, and had a less than 16% reduction in FEV1 after inhalation of 25 mg/mL methacholine. Subjects with a smoking history of 10 pack years or greater or who were actively smoking within 6 months of potential recruitment; had a history of chronic obstructive pulmonary disease, allergic bronchopulmonary aspergillosis, or Churg-Strauss syndrome; or had any medical contraindication to bronchoscopy were excluded.Statistical analysis Statistical analyses were conducted in STATA 14 software (StataCorp, College Station, Tex). Parameter Control subjects (n = 68) Asthmatic patients (n = 124) Age (y), median (IQR) 31 (21-48) 33.5 (25-48) Women, no. (%) 43 (63) 81 (65) Ancestry (EA/AA/other), no. 27/32/9 44/77/2 BMI (kg/m2), median (IQR) 26.1 (23.5-31.4) 28.7 (25.1-34.6) BMI >30 kg/m2, no. (%) 19 (28) 57 (46)∗ History of sinusitis, no. (%) 1 (1) 22 (18) History of GERD, no. (%) 2 (3) 22 (18) Serum IgE (IU/mL), median (IQR) 39 (17-157) 134 (39-383)† Inhaled corticosteroid use, no. (%) — 72 (58) Oral corticosteroid use, no. (%) — 21 (17) Blood eosinophil count/μL (mean ± SD) 123 ± 82 297 ± 77† Blood eosinophil count >300/μL, no. (%) 1 (1) 35 (28)† Blood neutrophil count/μL (mean ± SD) 3718 ± 1649 3818 ± 1984 Feno (ppb), median (IQR) 15 (12-22) 24 (14-42)† FEV1 (% predicted), mean ± SD 96.2 ± 12.2 79.2 ± 21.0† FEV1 ≥80% of predicted value, no. (%) — 65 (52) FEV1 60% to 80% of predicted value, no. (%) — 35 (28) FEV1 ≤60% of predicted value, no. (%) — 24 (19) Plasma IL-6 in all subjects (pg/mL mean ± SD) 1.77 ± 1.26 2.69 ± 3.19‡ Plasma IL-6 in subjects of EA ancestry (pg/mL mean ± SD) 1.58 ± 1.26 2.67 ± 4.20‡ Plasma IL-6 in subjects of AA ancestry (pg/mL mean ± SD) 2.15 ± 1.30§ 2.75 ± 2.52 Table I Baseline characteristics of the control subjects and asthmatic patients in this study Parameter (asthmatic patients only) IL-6−low group (n = 105) IL-6−high group (n = 16) Age (y), median (IQR) 32 (24-47) 44 (34.8-55.8)† Female sex, no. (%) 64 (61) 15 (94)‡ Ancestry (EA/AA/other), no. 36/69/0 8/8/0 Subjects of AA ancestry in phenotype, no. (%) 69 (90) 8 (10) Subjects of EA ancestry in phenotype, no. (%) 36 (82) 8 (18) BMI (kg/m2), median (IQR) 28.1 (24.9-34.0) 42.7 (27.5-50.3)† BMI >30 kg/m2, no. (%) 46 (44) 11 (69) Inhaled corticosteroid use, no. (%) 59 (56) 12 (75) Oral corticosteroid use, no. (%) 16 (15) 5 (31) Blood eosinophil count/μL, median (IQR) 200 (110-320) 155 (82-290) Blood neutrophil count/μL, median (IQR) 3200 (2490-4540) 3690 (2898-4920) Feno (ppb), median (IQR) 25 (14-44) 16 (7-33) Serum IgE (IU/mL), median (IQR) 141 (41-505) 101 (25-231) FEV1 (% predicted mean ± SD) 79.4 ± 21.9 75.1 ± 15.7 Table II Characteristics of patients with asthma in the IL-6−low and IL-6−high groups∗
Molecular profiling of cancer at the transcript level has become routine. Large-scale analysis of proteomic alterations during cancer progression has been a more daunting task. Here, we employed ...high-throughput immunoblotting in order to interrogate tissue extracts derived from prostate cancer. We identified 64 proteins that were altered in prostate cancer relative to benign prostate and 156 additional proteins that were altered in metastatic disease. An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed, revealing only 48%–64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors.
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