Jason W. Locasale

42.6k total citations · 18 hit papers
182 papers, 24.8k citations indexed

About

Jason W. Locasale is a scholar working on Molecular Biology, Cancer Research and Physiology. According to data from OpenAlex, Jason W. Locasale has authored 182 papers receiving a total of 24.8k indexed citations (citations by other indexed papers that have themselves been cited), including 141 papers in Molecular Biology, 87 papers in Cancer Research and 23 papers in Physiology. Recurrent topics in Jason W. Locasale's work include Cancer, Hypoxia, and Metabolism (82 papers), Epigenetics and DNA Methylation (38 papers) and Metabolomics and Mass Spectrometry Studies (26 papers). Jason W. Locasale is often cited by papers focused on Cancer, Hypoxia, and Metabolism (82 papers), Epigenetics and DNA Methylation (38 papers) and Metabolomics and Mass Spectrometry Studies (26 papers). Jason W. Locasale collaborates with scholars based in United States, China and Canada. Jason W. Locasale's co-authors include Maria V. Liberti, Xiaojing Liu, Ziwei Dai, Lewis C. Cantley, Matthew G. Vander Heiden, Samantha J. Mentch, Xia Gao, Michael A. Reid, John M. Asara and Ahmad A. Cluntun and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Jason W. Locasale

179 papers receiving 24.6k citations

Hit Papers

The Warburg Effect: How Does it Benefit Cancer Cells? 2010 2026 2015 2020 2016 2013 2015 2011 2017 1000 2.0k 3.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The Warburg Effect: How Does it Benefit Cancer Cells?
    2016 3.5k citations Maria V. Liberti, Jason W. Locasale profile →
  2. Serine, glycine and one-carbon units: cancer metabolism in full circle
    2013 1.2k citations Jason W. Locasale profile →
  3. Phosphoenolpyruvate Is a Metabolic Checkpoint of Anti-tumor T Cell Responses
    2015 1.1k citations Ping‐Chih Ho, Andrew N. Macintyre et al. profile →
  4. Inhibition of Pyruvate Kinase M2 by Reactive Oxygen Species Contributes to Cellular Antioxidant Responses
    2011 941 citations John M. Asara, Jason W. Locasale et al. Science profile →
  5. Glutamine Metabolism in Cancer: Understanding the Heterogeneity
    2017 571 citations Jason W. Locasale et al. profile →
  6. Evidence for an alternative glycolytic pathway in rapidly proliferating cells
    2010 509 citations Matthew G. Vander Heiden, Jason W. Locasale et al. Europe PMC (PubMed Central) profile →
  7. Influence of Threonine Metabolism on S -Adenosylmethionine and Histone Methylation
    2012 506 citations Ng Shyh‐Chang, Jason W. Locasale et al. Science profile →
  8. Histone Methylation Dynamics and Gene Regulation Occur through the Sensing of One-Carbon Metabolism
    2015 479 citations Xiaojing Liu, Jason W. Locasale et al. profile →
  9. Metabolomics in cancer research and emerging applications in clinical oncology
    2021 457 citations Matthew G. Vander Heiden, Jason W. Locasale et al. profile →
  10. Dietary methionine influences therapy in mouse cancer models and alters human metabolism
    2019 439 citations Xia Gao, Sydney M. Sanderson et al. Nature profile →
  11. T cell stemness and dysfunction in tumors are triggered by a common mechanism
    2019 409 citations Xiaojing Liu, Jason W. Locasale et al. Science profile →
  12. Foxp3 and Toll-like receptor signaling balance Treg cell anabolic metabolism for suppression
    2016 409 citations Valerie A. Gerriets, Peter J. Siska et al. Nature Immunology profile →
  13. Methionine metabolism in health and cancer: a nexus of diet and precision medicine
    2019 370 citations Sydney M. Sanderson, Xia Gao et al. profile →
  14. Disturbed mitochondrial dynamics in CD8+ TILs reinforce T cell exhaustion
    2020 370 citations Yi-Ru Yu, Hana Imrichová et al. Nature Immunology profile →
  15. Cancer-cell-secreted exosomal miR-105 promotes tumour growth through the MYC-dependent metabolic reprogramming of stromal cells
    2018 357 citations Juan Liu, Xiaojing Liu et al. profile →
  16. Metabolic landscape of the tumor microenvironment at single cell resolution
    2019 343 citations Zhengtao Xiao, Ziwei Dai et al. Nature Communications profile →
  17. The evolving metabolic landscape of chromatin biology and epigenetics
    2020 304 citations Ziwei Dai, Vijyendra Ramesh et al. Nature Reviews Genetics profile →
  18. The Nucleotide Sensor ZBP1 and Kinase RIPK3 Induce the Enzyme IRG1 to Promote an Antiviral Metabolic State in Neurons
    2019 213 citations Xia Gao, Jason W. Locasale et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jason W. Locasale United States 74 16.2k 9.2k 4.1k 4.0k 2.2k 182 24.8k
Eyal Gottlieb United Kingdom 63 14.6k 0.9× 8.6k 0.9× 2.1k 0.5× 2.9k 0.7× 1.8k 0.8× 135 20.8k
Nissim Hay United States 75 20.2k 1.2× 6.5k 0.7× 3.0k 0.7× 4.9k 1.2× 2.1k 1.0× 160 27.9k
Peng Huang China 82 18.0k 1.1× 7.4k 0.8× 2.2k 0.5× 5.8k 1.5× 1.6k 0.7× 329 31.3k
Russell G. Jones Canada 57 11.2k 0.7× 5.6k 0.6× 8.1k 2.0× 3.8k 1.0× 1.6k 0.7× 112 20.4k
Bernhard Brüne Germany 80 11.8k 0.7× 5.0k 0.5× 5.9k 1.4× 2.2k 0.6× 5.5k 2.5× 426 23.6k
Klaus Schulze‐Osthoff Germany 95 17.8k 1.1× 4.3k 0.5× 7.3k 1.8× 4.6k 1.1× 2.4k 1.1× 311 29.8k
Ralph J. DeBerardinis United States 81 28.3k 1.7× 19.6k 2.1× 4.2k 1.0× 5.2k 1.3× 2.9k 1.3× 233 42.6k
Simone Fulda Germany 82 20.4k 1.3× 4.8k 0.5× 4.4k 1.1× 5.6k 1.4× 818 0.4× 395 27.4k
Boris Zhivotovsky Sweden 85 19.5k 1.2× 3.5k 0.4× 3.0k 0.7× 3.8k 1.0× 2.1k 1.0× 344 30.5k
James A. McCubrey United States 79 16.1k 1.0× 3.9k 0.4× 3.2k 0.8× 6.8k 1.7× 962 0.4× 421 24.9k

Countries citing papers authored by Jason W. Locasale

Since Specialization
Citations

This map shows the geographic impact of Jason W. Locasale's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jason W. Locasale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason W. Locasale more than expected).

Fields of papers citing papers by Jason W. Locasale

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jason W. Locasale. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jason W. Locasale. The network helps show where Jason W. Locasale may publish in the future.

Co-authorship network of co-authors of Jason W. Locasale

This figure shows the co-authorship network connecting the top 25 collaborators of Jason W. Locasale. A scholar is included among the top collaborators of Jason W. Locasale based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jason W. Locasale. Jason W. Locasale is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Karampelias, Christos, Kathleen Watt, Charlotte L. Mattsson, et al.. (2022). MNK2 deficiency potentiates β-cell regeneration via translational regulation. Nature Chemical Biology. 18(9). 942–953. 18 indexed citations
2.
Gu, Xin, Patrick Jouandin, Max L. Valenstein, et al.. (2022). Sestrin mediates detection of and adaptation to low-leucine diets in Drosophila. Nature. 608(7921). 209–216. 36 indexed citations
3.
Contreras, Diana C., Jacqueline Cephus, Nowrin U. Chowdhury, et al.. (2021). Targeting In Vivo Metabolic Vulnerabilities of Th2 and Th17 Cells Reduces Airway Inflammation. The Journal of Immunology. 206(6). 1127–1139. 17 indexed citations
4.
Nam, Hyeyoung, Anirban Kundu, Suman Karki, et al.. (2021). The TGF-β/HDAC7 axis suppresses TCA cycle metabolism in renal cancer. JCI Insight. 6(22). 23 indexed citations
5.
Liao, Chengheng, Cherise Ryan Glodowski, Cheng Fan, et al.. (2021). Integrated Metabolic Profiling and Transcriptional Analysis Reveals Therapeutic Modalities for Targeting Rapidly Proliferating Breast Cancers. Cancer Research. 82(4). 665–680. 19 indexed citations
6.
Yu, Yi-Ru, Hana Imrichová, Haiping Wang, et al.. (2020). Disturbed mitochondrial dynamics in CD8+ TILs reinforce T cell exhaustion. Nature Immunology. 21(12). 1540–1551. 370 indexed citations breakdown →
7.
Liao, Chengheng, Yang Zhang, Cheng Fan, et al.. (2020). Identification of BBOX1 as a Therapeutic Target in Triple-Negative Breast Cancer. Cancer Discovery. 10(11). 1706–1721. 49 indexed citations
8.
Dai, Ziwei, Vijyendra Ramesh, & Jason W. Locasale. (2020). The evolving metabolic landscape of chromatin biology and epigenetics. Nature Reviews Genetics. 21(12). 737–753. 304 indexed citations breakdown →
9.
Hart, Peter C., Tatsuyuki Chiyoda, Xiaojing Liu, et al.. (2019). SPHK1 Is a Novel Target of Metformin in Ovarian Cancer. Molecular Cancer Research. 17(4). 870–881. 60 indexed citations
10.
Sinclair, Linda V., Andrew J.M. Howden, Alejandro J. Brenes, et al.. (2019). Antigen receptor control of methionine metabolism in T cells. eLife. 8. 161 indexed citations
11.
Xiao, Zhengtao, Ziwei Dai, & Jason W. Locasale. (2019). Metabolic landscape of the tumor microenvironment at single cell resolution. Nature Communications. 10(1). 3763–3763. 343 indexed citations breakdown →
12.
Reid, Michael A., Annamarie E. Allen, Shiyu Liu, et al.. (2018). Serine synthesis through PHGDH coordinates nucleotide levels by maintaining central carbon metabolism. Nature Communications. 9(1). 159 indexed citations
13.
Tang, Shuang, Yi Fang, Gang Huang, et al.. (2017). Methionine metabolism is essential for SIRT 1‐regulated mouse embryonic stem cell maintenance and embryonic development. The EMBO Journal. 36(21). 3175–3193. 63 indexed citations
14.
Sadhukhan, Sushabhan, Xiaojing Liu, Dongryeol Ryu, et al.. (2016). Metabolomics-assisted proteomics identifies succinylation and SIRT5 as important regulators of cardiac function. Proceedings of the National Academy of Sciences. 113(16). 4320–4325. 283 indexed citations
15.
Chen, Jinyu, Ho-Jeong Lee, Xuefeng Wu, et al.. (2014). Gain of Glucose-Independent Growth upon Metastasis of Breast Cancer Cells to the Brain. Cancer Research. 75(3). 554–565. 136 indexed citations
16.
Sun, Shengyi, Guojun Shi, Xuemei Han, et al.. (2014). Sel1L is indispensable for mammalian endoplasmic reticulum-associated degradation, endoplasmic reticulum homeostasis, and survival. Proceedings of the National Academy of Sciences. 111(5). E582–91. 160 indexed citations
17.
Parkhitko, Andrey A., Carmen Priolo, Jonathan L. Coloff, et al.. (2013). Autophagy-Dependent Metabolic Reprogramming Sensitizes TSC2-Deficient Cells to the Antimetabolite 6-Aminonicotinamide. Molecular Cancer Research. 12(1). 48–57. 50 indexed citations
18.
Shyh‐Chang, Ng, Jason W. Locasale, Costas A. Lyssiotis, et al.. (2012). Influence of Threonine Metabolism on S -Adenosylmethionine and Histone Methylation. Science. 339(6116). 222–226. 506 indexed citations breakdown →
19.
Heiden, Matthew G. Vander, Jason W. Locasale, Kenneth D. Swanson, et al.. (2010). Evidence for an Alternative Glycolytic Pathway in Rapidly Proliferating Cells. Science. 329(5998). 1492–1499. 31 indexed citations
20.
Heiden, Matthew G. Vander, Jason W. Locasale, Kenneth D. Swanson, et al.. (2010). Evidence for an alternative glycolytic pathway in rapidly proliferating cells. Europe PMC (PubMed Central). 509 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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