RESUMEN
Recessive mutations in the genes encoding the four subunits of the tRNA splicing endonuclease complex (TSEN54, TSEN34, TSEN15, and TSEN2) cause various forms of pontocerebellar hypoplasia, a disorder characterized by hypoplasia of the cerebellum and the pons, microcephaly, dysmorphisms, and other variable clinical features. Here, we report an intronic recessive founder variant in the gene TSEN2 that results in abnormal splicing of the mRNA of this gene, in six individuals from four consanguineous families affected with microcephaly, multiple craniofacial malformations, radiological abnormalities of the central nervous system, and cognitive retardation of variable severity. Remarkably, unlike patients with previously described mutations in the components of the TSEN complex, all the individuals that we report developed atypical hemolytic uremic syndrome (aHUS) with thrombotic microangiopathy, microangiopathic hemolytic anemia, thrombocytopenia, proteinuria, severe hypertension, and end-stage kidney disease (ESKD) early in life. Bulk RNA sequencing of peripheral blood cells of four affected individuals revealed abnormal tRNA transcripts, indicating an alteration of the tRNA biogenesis. Morpholino-mediated skipping of exon 10 of tsen2 in zebrafish produced phenotypes similar to human patients. Thus, we have identified a novel syndrome accompanied by aHUS suggesting the existence of a link between tRNA biology and vascular endothelium homeostasis, which we propose to name with the acronym TRACK syndrome (TSEN2 Related Atypical hemolytic uremic syndrome, Craniofacial malformations, Kidney failure).
Asunto(s)
Síndrome Hemolítico Urémico Atípico , Microcefalia , Animales , Síndrome Hemolítico Urémico Atípico/genética , Endonucleasas/genética , Femenino , Humanos , Masculino , Microcefalia/complicaciones , Mutación/genética , ARN de Transferencia , Pez Cebra/genéticaRESUMEN
The AP-2γ transcription factor, encoded by the TFAP2C gene, regulates the expression of estrogen receptor-alpha (ERα) and other genes associated with hormone response in luminal breast cancer. Little is known about the role of AP-2γ in other breast cancer subtypes. A subset of HER2+ breast cancers with amplification of the TFAP2C gene locus becomes addicted to AP-2γ. Herein, we sought to define AP-2γ gene targets in HER2+ breast cancer and identify genes accounting for physiologic effects of growth and invasiveness regulated by AP-2γ. Comparing HER2+ cell lines that demonstrated differential response to growth and invasiveness with knockdown of TFAP2C, we identified a set of 68 differentially expressed target genes. CDH5 and CDKN1A were among the genes differentially regulated by AP-2γ and that contributed to growth and invasiveness. Pathway analysis implicated the MAPK13/p38δ and retinoic acid regulatory nodes, which were confirmed to display divergent responses in different HER2+ cancer lines. To confirm the clinical relevance of the genes identified, the AP-2γ gene signature was found to be highly predictive of outcome in patients with HER2+ breast cancer. We conclude that AP-2γ regulates a set of genes in HER2+ breast cancer that drive cancer growth and invasiveness. The AP-2γ gene signature predicts outcome of patients with HER2+ breast cancer and pathway analysis predicts that subsets of patients will respond to drugs that target the MAPK or retinoic acid pathways. IMPLICATIONS: A set of genes regulated by AP-2γ in HER2+ breast cancer that drive proliferation and invasion were identified and provided a gene signature that is predictive of outcome in HER2+ breast cancer.
Asunto(s)
Neoplasias de la Mama/genética , Regulación Neoplásica de la Expresión Génica , Receptor ErbB-2/genética , Factor de Transcripción AP-2/genética , Neoplasias de la Mama/enzimología , Neoplasias de la Mama/metabolismo , Línea Celular Tumoral , Femenino , Técnicas de Silenciamiento del Gen , Humanos , Células MCF-7 , Receptor ErbB-2/biosíntesis , Receptor ErbB-2/metabolismo , Transfección , Resultado del TratamientoRESUMEN
INTRODUCTION: The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. METHODS: We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. RESULTS: There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. CONCLUSIONS: As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers.