Discovery of lncRNA biomarkers of prostate cancer
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ABSTRACT:
PROVIDER: PRJNA474912 | ENA |
REPOSITORIES: ENA
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Project description:In the last decade, new high-throughput sequencing techniques have revealed the complexity of the human transcriptome, allowing the characterization of long non-coding (lnc)RNAs. Since their expression has been reported as very specific to tissue, developmental stage and pathological variations, some lncRNAs have been proposed as biomarkers for diagnosis as well as prognosis of tumors. In this project, we aim to build an exhaustive catalogue of long non-coding RNAs and isolate those which allow detection and risk assessement of prostate cancer. For this purpose we performed a high throughput total stranded RNA-sequencing of 24 samples (8 normal and 16 tumor tissues).
2019-11-12 | GSE115414 | GEO
Project description:Transcriptomics biomarkers in prostate cancer
| PRJNA827124 | ENA
Project description:Long noncoding RNAs (lncRNAs) 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 (AR). PCAT29 is suppressed by dihydrotestosterone (DHT) and up-regulated upon castration therapy in a prostate cancer xenograft model. PCAT29 knockdown significantly increased proliferation and migration of prostate cancer cells, while PCAT29 overexpression conferred the opposite effect and suppressed growth and metastases of prostate tumors in chick chorioallantoic membrane (CAM) 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 PCAT29 was knockdown using shRNA in two prostate cancer cell lines VCaP and LNCaP.
2014-07-01 | E-GEOD-58397 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE26022: [Gene Expression Training Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy GSE26242: [Gene Expression Validation Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy GSE26245: [miRNA Training Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy GSE26247: [miRNA Validation Set] Protein-coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy Refer to individual Series
2011-06-01 | E-GEOD-26367 | biostudies-arrayexpress
Project description:Prostate cancer (PCa) is one of the most prevalent cancer types in men worldwide. However, the main diagnostic tests available for PCa have limitations and need biopsy for histopathological confirmation of the disease. The prostate-specific antigen (PSA) is the main biomarker used for PCa early detection, but an elevated serum concentration is not cancer-specific. Therefore, there is a need for discovery of new non-invasive biomarkers that can accurately diagnose PCa. Here, we used trichloroacetic acid-induced protein precipitation and liquid chromatography-mass spectrometry to profile endogenous peptides in urine samples from patients with PCa (n = 33), benign prostatic hyperplasia (n = 25), and healthy individuals (n = 28). Receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance of urinary peptides. In addition, proteasix tool was used for in silico prediction of protease cleavage sites. We found five urinary peptides derived from uromodulin significantly altered between the study groups, all of which were less abundant in the PCa group. In addition, urinary peptides outperformed PSA in discriminating between malignant and benign prostate conditions (AUC = 0.847), showing high sensitivity (81.82%) and specificity (88%). Overall, our study allowed the identification of urinary peptides with potential for use as non-invasive biomarkers in PCa diagnosis.
2022-10-25 | PXD037031 | Pride
Project description:Ovarian cancer is the leading cause of death in gynecological diseases, and has been considered as one of the most fatal cancers due to lack of reliable detection strategy in the early stage. Therefore the capability to detect the morbidity initiation with an sensitive and effective approach is one of the most desirable goals for curing ovarian cancer. In this study, we used microarray technology for salivary mRNA biomarkers discovery, and evaluated the performance and translational utilities of discovered markers from a clinical study using an independent sample cohort . We used microarrays to profile and compare the gene expressions between ovairan cancer patient and matched controls, and identified seven down-regulated genes after the validation study. To find salivary transcriptomic biomarkers for ovarian cancer, salivary transcriptomes in 11 ovarian cancer patients and 11 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 array, and followed by t-test and fold-change analyses. The biomarker candidates selected from the microarray results were subjected to clinical validation using an independent sample cohort by RT-qPCR. The prediction power of biomarkers was analyzed by logistic regression approach
2011-05-12 | E-GEOD-29220 | biostudies-arrayexpress
Project description:Intra-individual stability of the urine miRNA transcriptome was examined by investigating longitudinal changes over time in a cohort of patients with localized prostate cancer. Using training and validation cohorts, urinary miRNA biomarkers are characterized and validated their utility to identify aggressive prostate cancer.
2019-10-24 | GSE104431 | GEO
Project description:LncRNA and mRNA expression profiles of 3 prostate cancer tumor samples and 3 normal prostate samples were measured by microarray
2017-06-12 | GSE73397 | GEO
Project description:Prostate cancer (PCa) is the number one cancer in men. It represents a challenge for its management due to its very high incidence but low risk of lethal cancer. Over-diagnosis and over-treatment are therefore two pitfalls. The PSA (Prostate Specific Antigen) assay used for early diagnosis and clinical or molecular prognostic factors are not sufficiently reliable to predict the evolution of the cancer and its lethal or non-lethal character. Although PCa is most often detected at a localised stage, there are almost 30% of metastatic or locally advanced forms for which treatments can slow down the evolution but cannot be curative. With the use of high-throughput technological tools such as transcriptomics , it is becoming possible to define molecular signatures and identify predictive biomarkers of tumour aggressiveness . Here, we have analyzed 137 samples.
2022-05-18 | GSE200879 | GEO
Project description:Urine miRNA transcriptome of prostate cancer patients [Discovery cohort]
| PRJNA412691 | ENA