Peggy P. Hsu

Cancer Cell Metabolism: Warburg and Beyond

Described decades ago, the Warburg effect of aerobic glycolysis is a key metabolic hallmark of cancer, yet its significance remains unclear. In this Essay, we re-examine the Warburg effect and establish a framework for understanding its contribution to the altered metabolism of cancer cells.

The mTOR-regulated phosphoproteome reveals a mechanism of mTORC1-mediated inhibition of growth factor signaling

A search for substrates of a growth-promoting kinase revealed a regulatory feedback loop involved in tumor suppression. The mammalian target of rapamycin (mTOR) protein kinase is a master growth promoter that nucleates two complexes, mTORC1 and mTORC2. Despite the diverse processes controlled by mTOR, few substrates are known. We defined the mTOR-regulated phosphoproteome by quantitative mass spectrometry and characterized the primary sequence motif specificity of mTOR using positional scanning peptide libraries. We found that the phosphorylation response to insulin is largely mTOR dependent and that mTOR exhibits a unique preference for proline, hydrophobic, and aromatic residues at the +1 position. The adaptor protein Grb10 was identified as an mTORC1 substrate that mediates the inhibition of phosphoinositide 3-kinase typical of cells lacking tuberous sclerosis complex 2 (TSC2), a tumor suppressor and negative regulator of mTORC1. Our work clarifies how mTORC1 inhibits growth factor signaling and opens new areas of investigation in mTOR biology.

Functional genomics reveal that the serine synthesis pathway is essential in breast cancer

Cancer cells adapt their metabolic processes to drive macromolecular biosynthesis for rapid cell growth and proliferation (1,2). RNAi-based loss of function screening has proven powerful for the identification of novel and interesting cancer targets, and recent studies have used this technology in vivo to identify novel tumor suppressor genes (3). Here, we developed a method for identifying novel cancer targets via negative selection RNAi screening in solid tumours. Using this method, we screened a set of metabolic genes associated with aggressive breast cancer and stemness to identify those required for in vivo tumourigenesis. Among the genes identified, phosphoglycerate dehydrogenase (PHGDH) is in a genomic region of recurrent copy number gain in breast cancer and PHGDH protein levels are elevated in 70% of ER-negative breast cancers. PHGDH catalyzes the first step in the serine biosynthesis pathway, and breast cancer cells with high PHGDH expression have elevations in serine synthesis flux. Suppression of PHGDH in cell lines with elevated PHGDH expression, but not those without, causes a strong decrease in cell proliferation and a reduction in serine synthesis. We find that PHGDH suppression does not affect intracellular serine levels, but causes a drop in the levels of alpha-ketoglutarate, another output of the pathway and a TCA cycle intermediate. In cells with high PHGDH expression, the serine synthesis pathway contributes approximately 50% of the total anaplerotic flux of glutamine into the TCA cycle. These results reveal that certain breast cancers are dependent upon increased serine pathway flux caused by PHGDH over-expression and demonstrate the utility of in vivo negative selection RNAi screens for finding potential anticancer targets.

Nucleocytoplasmic Shuttling of the Golgi Phosphatidylinositol 4-Kinase Pik1 Is Regulated by 14-3-3 Proteins and Coordinates Golgi Function with Cell Growth

The yeast phosphatidylinositol 4-kinase Pik1p is essential for proliferation, and it controls Golgi homeostasis and transport of newly synthesized proteins from this compartment. At the Golgi, phosphatidylinositol 4-phosphate recruits multiple cytosolic effectors involved in formation of post-Golgi transport vesicles. A second pool of catalytically active Pik1p localizes to the nucleus. The physiological significance and regulation of this dual localization of the lipid kinase remains unknown. Here, we show that Pik1p binds to the redundant 14-3-3 proteins Bmh1p and Bmh2p. We provide evidence that nucleocytoplasmic shuttling of Pik1p involves phosphorylation and that 14-3-3 proteins bind Pik1p in the cytoplasm. Nutrient deprivation results in relocation of Pik1p from the Golgi to the nucleus and increases the amount of Pik1p-14-3-3 complex, a process reversed upon restored nutrient supply. These data suggest a role of Pik1p nucleocytoplasmic shuttling in coordination of biosynthetic transport from the Golgi with nutrient signaling.

Genome-scale RNAi on living-cell microarrays identifies novel regulators of Drosophila melanogaster TORC1–S6K pathway signaling

The evolutionarily conserved target of rapamycin complex 1 (TORC1) controls cell growth in response to nutrient availability and growth factors. TORC1 signaling is hyperactive in cancer, and regulators of TORC1 signaling may represent therapeutic targets for human diseases. To identify novel regulators of TORC1 signaling, we performed a genome-scale RNA interference screen on microarrays of Drosophila melanogaster cells expressing human RPS6, a TORC1 effector whose phosphorylated form we detected by immunofluorescence. Our screen revealed that the TORC1-S6K-RPS6 signaling axis is regulated by many subcellular components, including the Class I vesicle coat (COPI), the spliceosome, the proteasome, the nuclear pore, and the translation initiation machinery. Using additional RNAi reagents, we confirmed 70 novel genes as significant on-target regulators of RPS6 phosphorylation, and we characterized them with extensive secondary assays probing various arms of the TORC1 pathways, identifying functional relationships among those genes. We conclude that cell-based microarrays are a useful platform for genome-scale and secondary screening in Drosophila, revealing regulators that may represent drug targets for cancers and other diseases of deregulated TORC1 signaling.

Lung Cancer: A Wily Genetic Opponent

In two companion reports, the TRACERx consortium investigates tumor heterogeneity and evolution in early-stage non-small cell lung cancer. The studies highlight the prognostic value of copy-number heterogeneity assessment in tumor biopsies and circulating tumor DNA detection in plasma and suggest that tracking the evolution of lung cancers might aid clinical practice.

Abstract 5266: Fast and accurate fusion transcript detection using the Trinity Cancer Transcriptome Analysis Toolkit

Chromosomal rearrangements leading to fusion transcripts represent a class of oncogenic aberrations that are of high interest for understanding cancer biology, treating cancer patients, and as targets for the development of new therapies. Transcriptome sequencing via RNA-Seq coupled with downstream bioinformatics software applications offers an effective method for identifying candidate fusion transcripts, and is more targeted and cost-effective than whole genome sequencing. Although many such fusion detection software tools have recently been made available, they often differ greatly in prediction accuracy, execution times, computational requirements, installation complexity, and in not being readily accessible to non-bioinformatician cancer researchers. Here we present the Trinity Cancer Transcriptome Analysis Toolkit (CTAT), a newly developed suite of RNA-Seq targeted fusion detection tools leveraging a combination of reference genome read-mapping and de novo transcriptome assembly, coupled to in silico fusion transcript validation, annotation, and visualization. We show that components of our Trinity CTAT fusion detection toolkit, including STAR-Fusion and FusionInspector, yield improved accuracy and run times as compared to alternative leading tools. As a demonstration of the utility of Trinity CTAT, we explore fusion transcript discovery in a large cohort of ∼300 chronic lymphocytic leukemia (CLL) patient samples. We identify several novel recurrent fusions that may represent drivers of CLL etiology and provide new avenues to therapies. In addition to fusion transcript identification, Trinity CTAT aims to provide cancer researchers with easy access to methods for analyzing cancer RNA-Seq, including transcript reconstruction, identification of mutations, expression analysis, and tumor heterogeneity. Trinity CTAT is freely available open source software and readily accessible to all cancer researchers via our public Galaxy web portal: https://galaxy.ncgas-trinity.indiana.edu/. Citation Format: Brian Haas, Timothy Tickle, Nathalie Pochet, Jing Sun, Peggy Hsu, Chip Stewart, Carrie Ganote, Ben Fulton, Catherine Wu, Aviv Regev. Fast and accurate fusion transcript detection using the Trinity Cancer Transcriptome Analysis Toolkit. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5266.