Ichiro Nakano

13.6k total citations · 2 hit papers
106 papers, 7.3k citations indexed

About

Ichiro Nakano is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Ichiro Nakano has authored 106 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 48 papers in Cancer Research and 37 papers in Genetics. Recurrent topics in Ichiro Nakano's work include Glioma Diagnosis and Treatment (36 papers), MicroRNA in disease regulation (28 papers) and Cancer, Hypoxia, and Metabolism (16 papers). Ichiro Nakano is often cited by papers focused on Glioma Diagnosis and Treatment (36 papers), MicroRNA in disease regulation (28 papers) and Cancer, Hypoxia, and Metabolism (16 papers). Ichiro Nakano collaborates with scholars based in United States, Japan and China. Ichiro Nakano's co-authors include Harley I. Kornblum, Daniel H. Geschwind, Michael Masterman‐Smith, Houman D. Hemmati, Jorge A. Lazareff, Marianne Bronner‐Fraser, Agnieszka Bronisz, Jakub Godlewski, Bo Hu and Sung-Hak Kim and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Ichiro Nakano

105 papers receiving 7.2k citations

Hit Papers

Cancerous stem cells can arise from pediatric brain tumors 2003 2026 2010 2018 2003 2013 400 800 1.2k

Peers

Ichiro Nakano
Benjamin Purow United States
Jeongwu Lee United States
Simone P. Niclou Luxembourg
Qing Shi China
Yueling Hao United States
Do‐Hyun Nam South Korea
Sandra Pastorino United States
Ken Aldape United States
Benjamin Purow United States
Ichiro Nakano
Citations per year, relative to Ichiro Nakano Ichiro Nakano (= 1×) peers Benjamin Purow

Countries citing papers authored by Ichiro Nakano

Since Specialization
Citations

This map shows the geographic impact of Ichiro Nakano'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 Ichiro Nakano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ichiro Nakano more than expected).

Fields of papers citing papers by Ichiro Nakano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ichiro Nakano. 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 Ichiro Nakano. The network helps show where Ichiro Nakano may publish in the future.

Co-authorship network of co-authors of Ichiro Nakano

This figure shows the co-authorship network connecting the top 25 collaborators of Ichiro Nakano. A scholar is included among the top collaborators of Ichiro Nakano 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 Ichiro Nakano. Ichiro Nakano 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.
Meehan, Brian, Lata Adnani, Xianbing Zhu, et al.. (2025). Curative timed NK cell-based immunochemotherapy aborts brain tumour recurrence driven by mesenchymal glioma stem cells. Acta Neuropathologica Communications. 13(1). 64–64. 1 indexed citations
2.
Patel, Kunal, Riki Kawaguchi, Alvaro G. Alvarado, et al.. (2024). Single-nucleus expression characterization of non-enhancing region of recurrent high-grade glioma. Neuro-Oncology Advances. 6(1). vdae005–vdae005. 2 indexed citations
3.
Spinelli, Cristiana, Lata Adnani, Brian Meehan, et al.. (2024). Mesenchymal glioma stem cells trigger vasectasia—distinct neovascularization process stimulated by extracellular vesicles carrying EGFR. Nature Communications. 15(1). 2865–2865. 16 indexed citations
4.
Fletcher, Michael, Thomas Hielscher, Tobias Keßler, et al.. (2021). A novel patient stratification strategy to enhance the therapeutic efficacy of dasatinib in glioblastoma. Neuro-Oncology. 24(1). 39–51. 27 indexed citations
5.
Kant, Shiva, Pravin Kesarwani, Stewart F. Graham, et al.. (2020). Perhexiline Demonstrates FYN-mediated Antitumor Activity in Glioblastoma. Molecular Cancer Therapeutics. 19(7). 1415–1422. 25 indexed citations
6.
Yamashita, Daisuke, Mutsuko Minata, Shinobu Yamaguchi, et al.. (2020). Identification of ALDH1A3 as a Viable Therapeutic Target in Breast Cancer Metastasis–Initiating Cells. Molecular Cancer Therapeutics. 19(5). 1134–1147. 27 indexed citations
7.
Song, Xiao, Xuechao Wan, Tianzhi Huang, et al.. (2019). SRSF3-Regulated RNA Alternative Splicing Promotes Glioblastoma Tumorigenicity by Affecting Multiple Cellular Processes. Cancer Research. 79(20). 5288–5301. 73 indexed citations
8.
Olmez, Inan, Ying Zhang, Mouadh Benamar, et al.. (2018). Combined c-Met/Trk Inhibition Overcomes Resistance to CDK4/6 Inhibitors in Glioblastoma. Cancer Research. 78(15). 4360–4369. 44 indexed citations
9.
Chhipa, Rishi Raj, Qiang Fan, Jane L. Anderson, et al.. (2018). AMP kinase promotes glioblastoma bioenergetics and tumour growth. Nature Cell Biology. 20(7). 823–835. 104 indexed citations
10.
Olmez, Inan, Aizhen Xiao, Vlad Serbulea, et al.. (2017). Combined CDK4/6 and mTOR Inhibition Is Synergistic against Glioblastoma via Multiple Mechanisms. Clinical Cancer Research. 23(22). 6958–6968. 76 indexed citations
12.
Bell, Jonathan B., Frank Eckerdt, Yingtao Bi, et al.. (2016). MNK Inhibition Disrupts Mesenchymal Glioma Stem Cells and Prolongs Survival in a Mouse Model of Glioblastoma. Molecular Cancer Research. 14(10). 984–993. 30 indexed citations
13.
Geng, Feng, Xiang Cheng, Xiaoning Wu, et al.. (2016). Inhibition of SOAT1 Suppresses Glioblastoma Growth via Blocking SREBP-1–Mediated Lipogenesis. Clinical Cancer Research. 22(21). 5337–5348. 244 indexed citations
14.
Cheng, Peng, Jia Wang, Indrayani Waghmare, et al.. (2016). FOXD1–ALDH1A3 Signaling Is a Determinant for the Self-Renewal and Tumorigenicity of Mesenchymal Glioma Stem Cells. Cancer Research. 76(24). 7219–7230. 117 indexed citations
15.
Ricklefs, Franz, Marco Mineo, Arun K. Rooj, et al.. (2016). Extracellular Vesicles from High-Grade Glioma Exchange Diverse Pro-oncogenic Signals That Maintain Intratumoral Heterogeneity. Cancer Research. 76(10). 2876–2881. 81 indexed citations
16.
Bronisz, Agnieszka, Yan Wang, Michal O. Nowicki, et al.. (2013). Extracellular Vesicles Modulate the Glioblastoma Microenvironment via a Tumor Suppression Signaling Network Directed by miR-1. Cancer Research. 74(3). 738–750. 197 indexed citations
17.
Miyazaki, Takeshi, Kaushal Joshi, Bin Hu, et al.. (2012). Telomestatin Impairs Glioma Stem Cell Survival and Growth through the Disruption of Telomeric G-Quadruplex and Inhibition of the Proto-oncogene, c-Myb. Clinical Cancer Research. 18(5). 1268–1280. 97 indexed citations
18.
Visnyei, Koppany, Hideyuki Onodera, Robert Damoiseaux, et al.. (2011). A Molecular Screening Approach to Identify and Characterize Inhibitors of Glioblastoma Stem Cells. Molecular Cancer Therapeutics. 10(10). 1818–1828. 69 indexed citations
19.
Dougherty, Joseph D., Ainhoa García, Ichiro Nakano, et al.. (2005). PBK/TOPK, a Proliferating Neural Progenitor-Specific Mitogen-Activated Protein Kinase Kinase. Journal of Neuroscience. 25(46). 10773–10785. 84 indexed citations
20.
Fujimoto, K, et al.. (2000). [Intracranial inhibitory mechanisms in clinically diagnosed corticobasal degeneration: a study of a silent period followed by transcranial magnetic stimulation].. PubMed. 40(7). 701–6. 2 indexed citations

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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