The lncRNA landscape of breast cancer reveals a role for DSCAM-AS1 in breast cancer progression.

Molecular classification of cancers into subtypes has resulted in an advance in our understanding of tumour biology and treatment response across multiple tumour types. However, to date, cancer profiling has largely focused on protein-coding genes, which comprise <1% of the genome. Here we leverage a compendium of 58,648 long noncoding RNAs (lncRNAs) to subtype 947 breast cancer samples. We show that lncRNA-based profiling categorizes breast tumours by their known molecular subtypes in breast cancer. We identify a cohort of breast cancer-associated and oestrogen-regulated lncRNAs, and investigate the role of the top prioritized oestrogen receptor (ER)-regulated lncRNA, DSCAM-AS1. We demonstrate that DSCAM-AS1 mediates tumour progression and tamoxifen resistance and identify hnRNPL as an interacting protein involved in the mechanism of DSCAM-AS1 action. By highlighting the role of DSCAM-AS1 in breast cancer biology and treatment resistance, this study provides insight into the potential clinical implications of lncRNAs in breast cancer

Coordinating Tissue Regeneration Through Transforming Growth Factorâ β Activated Kinase 1 Inactivation and Reactivation

Aberrant wound healing presents as inappropriate or insufficient tissue formation. Using a model of musculoskeletal injury, we demonstrate that loss of transforming growth factorâ β activated kinase 1 (TAK1) signaling reduces inappropriate tissue formation (heterotopic ossification) through reduced cellular differentiation. Upon identifying increased proliferation with loss of TAK1 signaling, we considered a regenerative approach to address insufficient tissue production through coordinated inactivation of TAK1 to promote cellular proliferation, followed by reactivation to elicit differentiation and extracellular matrix production. Although the current regenerative medicine paradigm is centered on the effects of drug treatment (â drug onâ ), the impact of drug withdrawal (â drug offâ ) implicit in these regimens is unknown. Because current TAK1 inhibitors are unable to phenocopy genetic Tak1 loss, we introduce the dualâ inducible COmbinational Sequential Inversion ENgineering (COSIEN) mouse model. The COSIEN mouse model, which allows us to study the response to targeted drug treatment (â drug onâ ) and subsequent withdrawal (â drug offâ ) through genetic modification, was used here to inactivate and reactivate Tak1 with the purpose of augmenting tissue regeneration in a calvarial defect model. Our study reveals the importance of both the â drug onâ (Creâ mediated inactivation) and â drug offâ (Flpâ mediated reactivation) states during regenerative therapy using a mouse model with broad utility to study targeted therapies for disease. Stem Cells 2019;37:766â 778Manipulating transforming growth factor βâ activated kinase 1 for cell and scaffold free tissue regeneration using a dualâ inducible Combinational Sequential Inversion Engineering mouse model.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149573/1/stem2991_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149573/2/stem2991.pd

The DEK Oncoprotein Functions in Ovarian Cancer Growth and Survival

DNA damage repair alterations play a critical role in ovarian cancer tumorigenesis. Mechanistic drivers of the DNA damage response consequently present opportunities for therapeutic targeting. The chromatin-binding DEK oncoprotein functions in DNA double-strand break repair. We therefore sought to determine the role of DEK in epithelial ovarian cancer. DEK is overexpressed in both primary epithelial ovarian cancers and ovarian cancer cell lines. To assess the impact of DEK expression levels on cell growth, small interfering RNA and short hairpin RNA approaches were utilized. Decreasing DEK expression in ovarian cancer cell lines slows cell growth and induces apoptosis and DNA damage. The biologic effects of DEK depletion are enhanced with concurrent chemotherapy treatment. The in vitro effects of DEK knockdown are reproduced in vivo, as DEK depletion in a mouse xenograft model results in slower tumor growth and smaller tumors compared to tumors expressing DEK. These findings provide a compelling rationale to target the DEK oncoprotein and its pathways as a therapeutic strategy for treating epithelial ovarian cancer

MiPanda: A Resource for Analyzing and Visualizing Next-Generation Sequencing Transcriptomics Data

The Michigan Portal for the Analysis of NGS data portal (http://mipanda.org) is an open-access online resource that provides the scientific community with access to the results of a large-scale computational analysis of thousands of high-throughput RNA sequencing (RNA-seq) samples. The portal provides access to gene expression profiles, enabling users to interrogate expression of genes across myriad normal and cancer tissues and cell lines. From these data, tissue- and cancer-specific expression patterns can be identified. Gene-gene coexpression profiles can also be interrogated. The current portal contains data for over 20,000 RNA-seq samples and will be continually updated

Multigene profiling of CTCs in mCRPC identifies a clinically relevant prognostic signature

The trend toward precision-based therapeutic approaches dictated by molecular alterations offers substantial promise for men with metastatic castration-resistant prostate cancer (mCRPC). However, current approaches for molecular characterization are primarily tissue based, necessitating serial biopsies to understand changes over time and are limited by the challenges inherent to extracting genomic material from predominantly bone metastases. Therefore, a circulating tumor cell (CTC)-based assay was developed to determine gene expression across a panel of clinically relevant and potentially actionable prostate cancer-related genes. CTCs were isolated from the whole blood of mCRPC patients (n = 41) and multiplex qPCR was performed to evaluate expression of prostate cancer-related target genes (n = 78). A large fraction of patients (27/41, 66%) had detectable CTCs. Increased androgen receptor (AR) expression (70% of samples) and evidence of Wnt signaling (67% of samples) were observed. The TMPRSS2:ERG fusion was expressed in 41% of samples, and the aggressive prostate cancer-associated long noncoding RNA SChLAP1 was upregulated in 70%. WNT5a [HR 3.62, 95% confidence interval (CI), 1.63-8.05, P = 0.002], AURKA (HR 5.56, 95% CI, 1.79-17.20, P = 0.003), and BMP7 (HR 3.86, 95% CI, 1.60-9.32, P = 0.003) were independently predictive of overall survival (FDR < 10%) after adjusting for a panel of previously established prognostic variables in mCRPC (Halabi nomogram). A model including Halabi, WNT5a, and AURKA expression, termed the miCTC score, outperformed the Halabi nomogram alone (AUC = 0.89 vs. AUC = 0.70). Understanding the molecular landscape of CTCs has utility in predicting clinical outcomes in patients with aggressive prostate cancer and provides an additional tool in the arsenal of precision-based therapeutic approaches in oncology.Implications: Analysis of CTC gene expression reveals a clinically prognostic "liquid biopsy" signature in patients with metastatic castrate-resistance prostate cancer. Mol Cancer Res; 16(4); 643-54. ©2018 AACR

Identification and Validation of PCAT14 as Prognostic Biomarker in Prostate Cancer

Rapid advances in the discovery of long noncoding RNAs (lncRNAs) have identified lineage- and cancer-specific biomarkers that may be relevant in the clinical management of prostate cancer (PCa). Here we assembled and analyzed a large RNA-seq dataset, from 585 patient samples, including benign prostate tissue and both localized and metastatic PCa to discover and validate differentially expressed genes associated with disease aggressiveness. We performed Sample Set Enrichment Analysis (SSEA) and identified genes associated with low versus high Gleason score in the RNA-seq database. Comparing Gleason 6 versus 9+ PCa samples, we identified 99 differentially expressed genes with variable association to Gleason grade as well as robust expression in prostate cancer. The top-ranked novel lncRNA PCAT14, exhibits both cancer and lineage specificity. On multivariate analysis, low PCAT14 expression independently predicts for BPFS (P = .00126), PSS (P = .0385), and MFS (P = .000609), with trends for OS as well (P = .056). An RNA in-situ hybridization (ISH) assay for PCAT14 distinguished benign vs malignant cases, as well as high vs low Gleason disease. PCAT14 is transcriptionally regulated by AR, and endogenous PCAT14 overexpression suppresses cell invasion. Thus, Using RNA-sequencing data we identify PCAT14, a novel prostate cancer and lineage-specific lncRNA. PCAT14 is highly expressed in low grade disease and loss of PCAT14 predicts for disease aggressiveness and recurrence

Association of Urinary MyProstateScore, Age, and Prostate Volume in a Longitudinal Cohort of Healthy Men: Long-term Findings from the Olmsted County Study

Background: Serum prostate-specific antigen (PSA), used in prostate cancer screening, is nonspecific for cancer and is affected by age and prostate volume. More specific biomarkers could be more accurate for early detection of prostate cancer and reduce unnecessary prostate biopsies. Objective: To evaluate the association of age and prostate volume with urinary MyProstateScore (MPS) in a screened, longitudinal cohort without evidence of prostate cancer. Design, setting, and participants: The Olmsted County Study included men aged 40–79 yr who underwent biennial prostate cancer screening. PSA ≥4.0 ng/ml or abnormal rectal examination triggered prostate biopsy, and patients with cancer were excluded. The remaining men submitted urinary specimens for PCA3 and TMPRSS2:ERG testing. Outcome measurements and statistical analysis: MPS was calculated using the validated, locked model for grade group ≥2 cancer that includes serum PSA, urinary PCA3, and urinary TMPRSS2:ERG. The associations of age and volume with biomarkers were assessed in multivariable regression models. The t statistic was used to quantify the strength of associations independent of the unit of measurement, and R2 values were used to estimate the proportion of biomarker variance explained by each factor. Results and limitations: The study included 314 screened men without evidence of cancer. In multivariable models including age and volume, PCA3 score was significantly associated with age (t = 7.51; p < 0.001), while T2:ERG score was not associated with age or volume. MPS was significantly associated with both age (t = 7.45; p < 0.001) and volume (t = 3.56; p < 0.001), but accounting for age alone explained the variability observed (R2 = 0.29) in a similar way to the model including age and volume (R2 = 0.31). The variability of PCA3, T2:ERG, and MPS was less dependent on age and volume than the variability for PSA (R2 = 0.45). Conclusions: In a cohort of longitudinally screened men without evidence of cancer, we found that MPS demonstrated less variability with noncancer factors (age, prostate volume) than PSA did. These findings support the biology of these markers as more cancer-specific than PSA and highlight their promise in reducing the morbidity associated with PSA-based screening. Patient summary: In a group of men with no evidence of prostate cancer, we found that each of three urine-based markers of cancer—PCA3, T2:ERG, and the commercially available MyProstateScore test—showed less variability with noncancer factors (age and prostate volume) than serum PSA (prostate-specific antigen) did. These findings support their proposed use as noninvasive markers of prostate cancer that could improve the accuracy of early detection

The landscape of long noncoding RNAs in the human transcriptome

Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development

The lncRNA PCAT29 Inhibits Oncogenic Phenotypes in Prostate Cancer

UnlabelledLong noncoding RNAs (lncRNA) have recently been associated with the development and progression of a variety of human cancers. However, to date, the interplay between known oncogenic or tumor-suppressive events and lncRNAs has not been well described. Here, the novel lncRNA, prostate cancer-associated transcript 29 (PCAT29), is characterized along with its relationship to the androgen receptor. PCAT29 is suppressed by DHT and upregulated upon castration therapy in a prostate cancer xenograft model. PCAT29 knockdown significantly increased proliferation and migration of prostate cancer cells, whereas PCAT29 overexpression conferred the opposite effect and suppressed growth and metastases of prostate tumors in chick chorioallantoic membrane assays. Finally, in prostate cancer patient specimens, low PCAT29 expression correlated with poor prognostic outcomes. Taken together, these data expose PCAT29 as an androgen-regulated tumor suppressor in prostate cancer.ImplicationsThis study identifies PCAT29 as the first androgen receptor-repressed lncRNA that functions as a tumor suppressor and that its loss may identify a subset of patients at higher risk for disease recurrence. Visual Overview: http://mcr.aacrjournals.org/content/early/2014/07/31/1541-7786.MCR-14-0257/F1.large.jpg