The mammalian runt-related factor 1 (RUNX1) is a master transcription factor that regulates lineage specification of hematopoietic stem cells. RUNX1 translocations result in the development of myeloid leukemias. Recently, RUNX1 has been implicated as a tumor suppressor in other cancers. We postulated RUNX1 expression may be associated with lung adenocarcinoma etiology and/or progression. We evaluated the association of RUNX1 mRNA expression with overall survival data from The Cancer Genome Atlas (TCGA), a publically available database. Compared to high expression levels, Low RUNX1 levels from lung adenocarcinomas were associated with a worse overall survival (Hazard Ratio = 2.014 (1.042-3.730 95% confidence interval), log-rank p = 0.035) compared to those that expressed high RUNX1 levels. Further immunohistochemical examination of 85 surgical specimens resected at the University of Vermont Medical Center identified that low RUNX1 protein expression was associated with larger tumors (p = 0.038). Gene expression network analysis was performed on the same subset of TCGA cases that demonstrated differential survival by RUNX1 expression. This analysis, which reveals regulatory relationships, showed that reduced RUNX1 levels were closely linked to upregulation of the transcription factor E2F1. To interrogate this relationship, RUNX1 was depleted in a lung cancer cell line that expresses high levels of RUNX1. Loss of RUNX1 resulted in enhanced proliferation, migration, and invasion. RUNX1 depletion also resulted in increased mRNA expression of E2F1 and multiple E2F1 target genes. Our data implicate loss of RUNX1 as driver of lung adenocarcinoma aggression, potentially through deregulation of the E2F1 pathway.
Pubmed ID: 28926105 RIS Download
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Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
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View all literature mentionsA unified data repository of the National Cancer Institute (NCI)'s Genomic Data Commons (GDC) that enables data sharing across cancer genomic studies in support of precision medicine. The GDC supports several cancer genome programs at the NCI Center for Cancer Genomics (CCG), including The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization Initiative (CGCI). The GDC Data Portal provides a platform for efficiently querying and downloading high quality and complete data. The GDC also provides a GDC Data Transfer Tool and a GDC API for programmatic access.
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