Gene dosage is a key defining factor to understand cancer pathogenesis and progression, which requires the development of experimental models that aid better deconstruction of the disease. Here, we model an aggressive form of prostate cancer and show the unconventional association of LKB1 dosage to prostate tumorigenesis. Whereas loss of Lkb1 alone in the murine prostate epithelium was inconsequential for tumorigenesis, its combination with an oncogenic insult, illustrated by Pten heterozygosity, elicited lethal metastatic prostate cancer. Despite the low frequency of LKB1 deletion in patients, this event was significantly enriched in lung metastasis. Modeling the role of LKB1 in cellular systems revealed that the residual activity retained in a reported kinase-dead form, LKB1K78I, was sufficient to hamper tumor aggressiveness and metastatic dissemination. Our data suggest that prostate cells can function normally with low activity of LKB1, whereas its complete absence influences prostate cancer pathogenesis and dissemination.

• MeSH
• epitel enzymologie   patologie   MeSH
• fosfohydroláza PTEN metabolismus   MeSH
• HEK293 buňky MeSH
• heterozygot MeSH
• lidé MeSH
• metastázy nádorů MeSH
• mutantní proteiny metabolismus   MeSH
• myši inbrední C57BL MeSH
• myši nahé MeSH
• nádorové buněčné linie MeSH
• nádory prostaty enzymologie   MeSH
• progrese nemoci MeSH
• prostata enzymologie   patologie   MeSH
• protein-serin-threoninkinasy nedostatek   genetika   metabolismus   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The dysregulation of gene expression is an enabling hallmark of cancer. Computational analysis of transcriptomics data from human cancer specimens, complemented with exhaustive clinical annotation, provides an opportunity to identify core regulators of the tumorigenic process. Here we exploit well-annotated clinical datasets of prostate cancer for the discovery of transcriptional regulators relevant to prostate cancer. Following this rationale, we identify Microphthalmia-associated transcription factor (MITF) as a prostate tumor suppressor among a subset of transcription factors. Importantly, we further interrogate transcriptomics and clinical data to refine MITF perturbation-based empirical assays and unveil Crystallin Alpha B (CRYAB) as an unprecedented direct target of the transcription factor that is, at least in part, responsible for its tumor-suppressive activity in prostate cancer. This evidence was supported by the enhanced prognostic potential of a signature based on the concomitant alteration of MITF and CRYAB in prostate cancer patients. In sum, our study provides proof-of-concept evidence of the potential of the bioinformatics screen of publicly available cancer patient databases as discovery platforms, and demonstrates that the MITF-CRYAB axis controls prostate cancer biology.

• MeSH
• alfa-krystaliny - řetězec B genetika   MeSH
• buňky PC-3 MeSH
• lidé MeSH
• myši nahé MeSH
• myši MeSH
• nádorové buněčné linie MeSH
• nádorové supresorové proteiny genetika   MeSH
• nádory prostaty genetika   patologie   MeSH
• prognóza MeSH
• regulace genové exprese u nádorů genetika   MeSH
• transkripční faktor spojený s mikroftalmií genetika   MeSH
• transkripční faktory genetika   MeSH
• transkriptom genetika   MeSH
• výpočetní biologie metody   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• myši MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

With the advent of OMICs technologies, both individual research groups and consortia have spear-headed the characterization of human samples of multiple pathophysiologic origins, resulting in thousands of archived genomes and transcriptomes. Although a variety of web tools are now available to extract information from OMICs data, their utility has been limited by the capacity of nonbioinformatician researchers to exploit the information. To address this problem, we have developed CANCERTOOL, a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer (breast, prostate, lung, and colorectal). CANCERTOOL provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets. This visualization is accompanied by generation of reports customized to the interest of the researcher (e.g., editable figures, detailed statistical analyses, and access to raw data for reanalysis). It also carries out gene-to-gene correlations in multiple datasets at the same time or using preset patient groups. Finally, this new tool solves the time-consuming task of performing functional enrichment analysis with gene sets of interest using up to 11 different databases at the same time. Collectively, CANCERTOOL represents a simple and freely accessible interface to interrogate well-annotated datasets and obtain publishable representations that can contribute to refinement and guidance of cancer-related investigations at all levels of hypotheses and design.Significance: In order to facilitate access of research groups without bioinformatics support to public transcriptomics data, we have developed a free online tool with an easy-to-use interface that allows researchers to obtain quality information in a readily publishable format. Cancer Res; 78(21); 6320-8. ©2018 AACR.

• MeSH
• algoritmy MeSH
• databáze faktografické MeSH
• databáze genetické MeSH
• genomika MeSH
• internet MeSH
• lékařská onkologie MeSH
• lidé MeSH
• nádory genetika   MeSH
• počítačová grafika MeSH
• proteomika MeSH
• průběh práce MeSH
• software MeSH
• transkriptom MeSH
• uživatelské rozhraní počítače MeSH
• výpočetní biologie metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH