Project description: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.
Project description: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 cancerM-bM-^@M-^Sassociated 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-1M-bM-^@M-^Srepressed 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. 21 prostate cell lines sequenced on the Illumina Genome Analyzer and GAII. Variable number of replicates per sample. RNA-Seq data from prostate cancer tissues used in this study will be made available on dbGAP.
Project description: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.
Project description:<p>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 <i>ab initio</i> 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.</p>
Project description:The molecular mechanisms behind human liver disease progression to cirrhosis remain elusive. Nuclear receptor small heterodimer partner (SHP/Nr0b2) is a hepatic tumor suppressor and a critical regulator of liver function. SHP expression is diminished in human cirrhotic livers, suggesting a regulatory role in human liver diseases. The goal of this study was to identify novel SHP-regulated genes that are involved in the development and progression of chronic liver disease. To achieve this, we conducted the first comprehensive RNA sequencing (RNA-seq) analysis of Shp(-/-) mice, compared the results with human hepatitis C cirrhosis RNA-seq and nonalcoholic steatohepatitis (NASH) microarray datasets, and verified novel results in human liver biospecimens. This approach revealed new gene signatures associated with chronic liver disease and regulated by SHP. Several genes were selected for validation of physiological relevance based on their marked upregulation, novelty with regard to liver function, and involvement in gene pathways related to liver disease. These genes include peptidoglycan recognition protein 2, dual specific phosphatase-4, tetraspanin 4, thrombospondin 1, and SPARC-related modular calcium binding protein-2, which were validated by qPCR analysis of 126 human liver specimens, including steatosis, fibrosis, and NASH, alcohol and hepatitis C cirrhosis, and in mouse models of liver inflammation and injury. This RNA-seq analysis identifies new genes that are regulated by the nuclear receptor SHP and implicated in the molecular pathogenesis of human chronic liver diseases. The results provide valuable transcriptome information for characterizing mechanisms of these diseases.
Project description:Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory - reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression.
Project description:Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.
Project description:Next-generation sequencing is making sequence-based molecular pathology and personalized oncology viable. We selected an individual initially diagnosed with conventional but aggressive prostate adenocarcinoma and sequenced the genome and transcriptome from primary and metastatic tissues collected prior to hormone therapy. The histology-pathology and copy number profiles were remarkably homogeneous, yet it was possible to propose the quadrant of the prostate tumour that likely seeded the metastatic diaspora. Despite a homogeneous cell type, our transcriptome analysis revealed signatures of both luminal and neuroendocrine cell types. Remarkably, the repertoire of expressed but apparently private gene fusions, including C15orf21:MYC, recapitulated this biology. We hypothesize that the amplification and over-expression of the stem cell gene MSI2 may have contributed to the stable hybrid cellular identity. This hybrid luminal-neuroendocrine tumour appears to represent a novel and highly aggressive case of prostate cancer with unique biological features and, conceivably, a propensity for rapid progression to castrate-resistance. Overall, this work highlights the importance of integrated analyses of genome, exome and transcriptome sequences for basic tumour biology, sequence-based molecular pathology and personalized oncology.
Project description:BackgroundHeart failure (HF) has been recognized as a global pandemic with a high rate of hospitalization, morbidity, and mortality. Although numerous advances have been made, its representative molecular signatures remain largely unknown, especially the role of genes in HF progression. The aim of the present prospective follow-up study was to reveal potential biomarkers associated with the progression of heart failure.MethodsWe generated multi-level transcriptomic data from a cohort of left ventricular heart tissue collected from 21 HF patients and 9 healthy donors. By using Masson staining to calculate the fibrosis percentage for each sample, we applied lasso regression model to identify the genes associated with fibrosis as well as progression. The genes were further validated by immunohistochemistry (IHC) staining in the same cohort and qRT-PCR using another independent cohort (20 HF and 9 healthy donors). Enzyme-linked immunosorbent assay (ELISA) was used to measure the plasma level in a validation cohort (139 HF patients) for predicting HF progression.ResultsBased on the multi-level transcriptomic data, we examined differentially expressed genes [mRNAs, microRNAs, and long non-coding RNAs (lncRNAs)] in the study cohort. The follow-up functional annotation and regulatory network analyses revealed their potential roles in regulating extracellular matrix. We further identified several genes that were associated with fibrosis. By using the survival time before transplantation, COL1A1 was identified as a potential biomarker for HF progression and its upregulation was confirmed by both IHC and qRT-PCR. Furthermore, COL1A1 content ≥ 256.5 ng/ml in plasma was found to be associated with poor survival within 1 year of heart transplantation from heart failure [hazard ratio (HR) 7.4, 95% confidence interval (CI) 3.5 to 15.8, Log-rank p value < 1.0 × 10- 4].ConclusionsOur results suggested that COL1A1 might be a plasma biomarker of HF and associated with HF progression, especially to predict the 1-year survival from HF onset to transplantation.
Project description:The identification of novel tumor-specific markers may improve understanding of melanoma progression and prognostic accuracy. Whole genome expression profiling of 46 primary melanomas, 12 metastases, and 16 normal skin samples using Affymetrix U133 PLUS 2.0 array generated gene lists including both known and new melanoma genes. The molecular genetic alterations contributing to the pathogenesis of melanoma are incompletely defined and few independent prognostic features have been identified beyond the pathologic characteristics of the primary tumor. Early stage melanoma is frequently curable, in contrast to the inferior prognosis of melanomas with regional lymph nodes involvement and the incurability of distant metastatic disease. The identification of novel tumor-specific markers may improve our understanding of melanoma progression and prognostic accuracy. To find differentially expressed genes that can distinguish melanoma from normal tissue, we performed a whole genome expression profiling of 46 primary melanoma samples, 12 regional or distant metastases, and 16 normal skin samples using Affymetrix U133 2.0 Plus array. Our study generated lists of differentially expressed genes in melanoma and identified novel prognostic marker HMGA2. It is a novel, highly overexpressed melanoma gene associated with poor prognosis. The overexpression of HMGA2 is strongly associated with regional and distant metastases and serves as an independent predictor of disease-free survival and overall survival in melanoma. Melanoma samples were obtained through an IRB-approved protocol using informed consent at the University of Michigan Multidisciplinary Melanoma Clinic. A portion of pigmented lesions clinically suspicious for melanoma and known melanoma were sampled by punch biopsy at the time of excision. The punch biopsy was bisected; half was sent to for clinical diagnosis and the other half along with adjacent normal skin when available immediately snap-frozen in liquid nitrogen. Snap-frozen tissue was embedded in OCT (TissueTek) followed by frozen sectioning and H&E slide preparation. The slides were evaluated by dermatopathologist who identified areas with greater than 70% tumor cellularity, which were sampled for RNA extraction. Primary melanomas and melanoma metastases were derived from different patients. Metastatic samples included lymph nodes (n=8), subcutaneous soft tissue (n=2), spleen (n=1), and small intestine (n=1).