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As a hallmark of cancer, the Warburg effect (aerobic glycolysis) confers a selective advantage for the survival and proliferation of cancer cells. Due to frequent aberration of upstream proto-oncogenes and tumor suppressors, hyperactive mammalian/mechanistic target of rapamycin (mTOR) is a potent inducer of the Warburg effect. Here, we report that overexpression of a glycolytic enzyme, phosphoglyceric acid mutase-1 (PGAM1), is critical to oncogenic mTOR-mediated Warburg effect. mTOR stimulated PGAM1 expression through hypoxia-inducible factor 1α-mediated transcriptional activation. Blockage of PGAM1 suppressed mTOR-dependent glycolysis, cell proliferation, and tumorigenesis. PGAM1 expression and mTOR activity were positively correlated in non-small cell lung cancer (NSCLC) tissues and PGAM1 abundance was an adverse predictor for patient survival. PGAM1 is thus a downstream effector of mTOR signaling pathway and mTOR-PGAM1 signaling cascade may contribute to the development of Warburg effect observed in cancer. We consider PGAM1 as a novel prognostic biomarker for NSCLC and a therapeutic target for cancer.
Pubmed ID: 29362480
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Commercial antibody vendor which supplies antibodies and other products to life science researchers.
View all literature mentionsProject 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).
View all literature mentionsSoftware package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
View all literature mentionslaboratory mouse with name BALB/cAnNCrl from MGI.
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