RESUMO
BACKGROUND: Inflammation is linked to prostate cancer progression and is mediated by NF-κB. Tristetraprolin is a key node of NF-κB activation and we investigated its biological and prognostic role in lethal prostate cancer. METHODS: In vitro assays assessed the function of tristetraprolin and the association between low mRNA tristetraprolin levels and lethal prostate cancer (metastatic disease or death) was assessed across independent prostatectomy cohorts: (i) nested case-control studies from Health Professionals Follow-up Study and Physicians' Health Study, and (ii) prostatectomy samples from Cleveland Clinic, Mayo Clinic, Johns Hopkins and Memorial Sloan Kettering Cancer Center. Tristetraprolin expression levels in prostatectomy samples from patients with localized disease and biopsies of metastatic castration-resistant prostate cancer (mCRPC) were assessed in a Cornell University cohort. RESULTS: In vitro tristetraprolin expression was inversely associated with NF-κB-controlled genes, proliferation, and enzalutamide sensitivity. Men with localized prostate cancer and lower quartile of tumor tristetraprolin expression had a significant, nearly two-fold higher risk of lethal prostate cancer after adjusting for known clinical and histologic prognostic features (age, RP Gleason score, T-stage). Tristetraprolin expression was also significantly lower in mCRPC compared with localized prostate cancer. CONCLUSIONS: Lower levels of tristetraprolin in human prostate cancer prostatectomy tissue are associated with more aggressive prostate cancer and may serve as an actionable prognostic and predictive biomarker. IMPACT: There is a clear need for improved biomarkers to identify patients with localized prostate cancer in need of treatment intensification, such as adjuvant testosterone suppression, or treatment de-intensification, such as active surveillance. Tristetraprolin levels may serve as informative biomarkers in localized prostate cancer.
Assuntos
Biomarcadores Tumorais/metabolismo , Recidiva Local de Neoplasia/patologia , Neoplasias de Próstata Resistentes à Castração/secundário , Neoplasias da Próstata/patologia , Tristetraprolina/metabolismo , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Casos e Controles , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Recidiva Local de Neoplasia/metabolismo , Recidiva Local de Neoplasia/cirurgia , Prognóstico , Prostatectomia , Neoplasias da Próstata/metabolismo , Neoplasias da Próstata/cirurgia , Neoplasias de Próstata Resistentes à Castração/metabolismo , Neoplasias de Próstata Resistentes à Castração/cirurgia , Estudos Retrospectivos , Taxa de SobrevidaRESUMO
An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.
Assuntos
Mutação , Proteína Carregadora de Folato Reduzido/genética , Disrafismo Espinal/genética , Criança , Feminino , Ácido Fólico/metabolismo , Genômica/métodos , Humanos , Modelos Moleculares , Gravidez , Conformação Proteica , Proteína Carregadora de Folato Reduzido/química , Proteína Carregadora de Folato Reduzido/metabolismo , Software , Disrafismo Espinal/metabolismoRESUMO
We have developed Lynx (http://lynx.ci.uchicago.edu)--a web-based database and a knowledge extraction engine, supporting annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Its underlying knowledge base (LynxKB) integrates various classes of information from >35 public databases and private collections, as well as manually curated data from our group and collaborators. Lynx provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization to assist the user in extracting meaningful knowledge from LynxKB and experimental data, whereas its service-oriented architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.