Abhishek K. Jha
Agios Pharmaceuticals
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Publication
Featured researches published by Abhishek K. Jha.
Nature | 2011
Richard Possemato; Kevin Marks; Yoav D. Shaul; Michael E. Pacold; Dohoon Kim; Kivanc Birsoy; Shalini Sethumadhavan; Hin-Koon Woo; Hyun Gyung Jang; Abhishek K. Jha; Walter W. Chen; Francesca G. Barrett; Nicolas Stransky; Zhi-Yang Tsun; Glenn S. Cowley; Jordi Barretina; Nada Y. Kalaany; Peggy P. Hsu; Kathleen Ottina; Albert M. Chan; Bingbing Yuan; Levi A. Garraway; David E. Root; Mari Mino-Kenudson; Elena F. Brachtel; Edward M. Driggers; David M. Sabatini
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.
Nature Chemical Biology | 2012
Dimitrios Anastasiou; Yimin Yu; William J. Israelsen; Jian Kang Jiang; Matthew B. Boxer; Bum Soo Hong; Wolfram Tempel; Svetoslav Dimov; Min Shen; Abhishek K. Jha; Hua Yang; Katherine R. Mattaini; Christian M. Metallo; Brian Prescott Fiske; Kevin D. Courtney; Scott Malstrom; Tahsin M. Khan; Charles Kung; Amanda P. Skoumbourdis; Henrike Veith; Noel Southall; Martin J. Walsh; Kyle R. Brimacombe; William Leister; Sophia Y. Lunt; Zachary R. Johnson; Katharine E. Yen; Kaiko Kunii; Shawn M. Davidson; Heather R. Christofk
Cancer cells engage in a metabolic program to enhance biosynthesis and support cell proliferation. The regulatory properties of pyruvate kinase M2 (PKM2) influence altered glucose metabolism in cancer. PKM2 interaction with phosphotyrosine-containing proteins inhibits enzyme activity and increases availability of glycolytic metabolites to support cell proliferation. This suggests that high pyruvate kinase activity may suppress tumor growth. We show that expression of PKM1, the pyruvate kinase isoform with high constitutive activity, or exposure to published small molecule PKM2 activators inhibit growth of xenograft tumors. Structural studies reveal that small molecule activators bind PKM2 at the subunit interaction interface, a site distinct from that of the endogenous activator fructose-1,6-bisphosphate (FBP). However, unlike FBP, binding of activators to PKM2 promotes a constitutively active enzyme state that is resistant to inhibition by tyrosine-phosphorylated proteins. These data support the notion that small molecule activation of PKM2 can interfere with anabolic metabolism.
Immunity | 2015
Abhishek K. Jha; Stanley Ching-Cheng Huang; Alexey Sergushichev; Vicky Lampropoulou; Yulia Ivanova; Ekaterina Loginicheva; Karina Chmielewski; Kelly M. Stewart; Juliet Ashall; Bart Everts; Edward J. Pearce; Edward M. Driggers; Maxim N. Artyomov
Macrophage polarization involves a coordinated metabolic and transcriptional rewiring that is only partially understood. By using an integrated high-throughput transcriptional-metabolic profiling and analysis pipeline, we characterized systemic changes during murine macrophage M1 and M2 polarization. M2 polarization was found to activate glutamine catabolism and UDP-GlcNAc-associated modules. Correspondingly, glutamine deprivation or inhibition of N-glycosylation decreased M2 polarization and production of chemokine CCL22. In M1 macrophages, we identified a metabolic break at Idh, the enzyme that converts isocitrate to alpha-ketoglutarate, providing mechanistic explanation for TCA cycle fragmentation. (13)C-tracer studies suggested the presence of an active variant of the aspartate-arginosuccinate shunt that compensated for this break. Consistently, inhibition of aspartate-aminotransferase, a key enzyme of the shunt, inhibited nitric oxide and interleukin-6 production in M1 macrophages, while promoting mitochondrial respiration. This systems approach provides a highly integrated picture of the physiological modules supporting macrophage polarization, identifying potential pharmacologic control points for both macrophage phenotypes.
Cancer Cell | 2013
Krushna C. Patra; Qi Wang; Prashanth T. Bhaskar; Luke Miller; Zebin Wang; Will Wheaton; Navdeep S. Chandel; Markku Laakso; William J. Muller; Eric L. Allen; Abhishek K. Jha; Gromoslaw A. Smolen; Michelle F. Clasquin; R.Brooks Robey; Nissim Hay
Accelerated glucose metabolism is a common feature of cancer cells. Hexokinases catalyze the first committed step of glucose metabolism. Hexokinase 2 (HK2) is expressed at high level in cancer cells, but only in a limited number of normal adult tissues. Using Hk2 conditional knockout mice, we showed that HK2 is required for tumor initiation and maintenance in mouse models of KRas-driven lung cancer, and ErbB2-driven breast cancer, despite continued HK1 expression. Similarly, HK2 ablation inhibits the neoplastic phenotype of human lung and breast cancer cells in vitro and in vivo. Systemic Hk2 deletion is therapeutic in mice bearing lung tumors without adverse physiological consequences. Hk2 deletion in lung cancer cells suppressed glucose-derived ribonucleotides and impaired glutamine-derived carbon utilization in anaplerosis.
Cell Metabolism | 2016
Shawn M. Davidson; Thales Papagiannakopoulos; Benjamin A. Olenchock; Julia E. Heyman; Mark A. Keibler; Alba Luengo; Matthew R. Bauer; Abhishek K. Jha; James P. O’Brien; Kerry A. Pierce; Dan Y. Gui; Lucas B. Sullivan; Thomas M. Wasylenko; Lakshmipriya Subbaraj; Christopher R. Chin; Gregory Stephanopolous; Bryan T. Mott; Tyler Jacks; Clary B. Clish; Matthew G. Vander Heiden
Cultured cells convert glucose to lactate, and glutamine is the major source of tricarboxylic acid (TCA)-cycle carbon, but whether the same metabolic phenotype is found in tumors is less studied. We infused mice with lung cancers with isotope-labeled glucose or glutamine and compared the fate of these nutrients in tumor and normal tissue. As expected, lung tumors exhibit increased lactate production from glucose. However, glutamine utilization by both lung tumors and normal lung was minimal, with lung tumors showing increased glucose contribution to the TCA cycle relative to normal lung tissue. Deletion of enzymes involved in glucose oxidation demonstrates that glucose carbon contribution to the TCA cycle is required for tumor formation. These data suggest that understanding nutrient utilization by tumors can predict metabolic dependencies of cancers in vivo. Furthermore, these data argue that the in vivo environment is an important determinant of the metabolic phenotype of cancer cells.
Nucleic Acids Research | 2016
Alexey Sergushichev; Alexander A. Loboda; Abhishek K. Jha; Emma E. Vincent; Edward M. Driggers; Russell G. Jones; Edward J. Pearce; Maxim N. Artyomov
Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM (‘genes and metabolites’): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at: https://artyomovlab.wustl.edu/shiny/gam/
Cancer and Metabolism | 2014
Danielle Ulanet; Abhishek K. Jha; Kiley Couto; Sung Choe; Amanda Wang; Hin-Koon Woo; Mya Steadman; Byron DeLaBarre; Stefan Gross; Edward M. Driggers; Marion Dorsch; Jonathan Hurov
Nature Chemical Biology | 2012
Dimitrios Anastasiou; Yimin Yu; William J. Israelsen; Jian Kang Jiang; Matthew B. Boxer; Bum Soo Hong; Wolfram Tempel; Svetoslav Dimov; Min Shen; Abhishek K. Jha; Hua Yang; Katherine R. Mattaini; Christian M. Metallo; Brian Prescott Fiske; Kevin D. Courtney; Scott Malstrom; Tahsin M. Khan; Charles Kung; Amanda P. Skoumbourdis; Henrike Veith; Noel Southall; Martin J. Walsh; Kyle R. Brimacombe; William Leister; Sophia Y. Lunt; Zachary R. Johnson; Katharine E. Yen; Kaiko Kunii; Shawn M. Davidson; Heather R. Christofk
Protein and Peptide Folding, Misfolding, and Non-Folding | 2012
Joe DeBartolo; Abhishek K. Jha; Karl F. Freed; Tobin R. Sosnick
Blood | 2014
Charles Kung; Collin Hill; Yue Chen; Abhishek K. Jha; Penelope Kosinski; Michelle F. Clasquin; Yaguang Si; Hyeryun Kim; Jeff Hixon; Lenny Dang; Sam Agresta; Lee Silverman; Hua Yang