Toshihide Ueno

8.4k total citations · 2 hit papers
73 papers, 4.1k citations indexed

About

Toshihide Ueno is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Toshihide Ueno has authored 73 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 30 papers in Oncology and 22 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Toshihide Ueno's work include Cancer Genomics and Diagnostics (16 papers), Lung Cancer Treatments and Mutations (12 papers) and RNA modifications and cancer (8 papers). Toshihide Ueno is often cited by papers focused on Cancer Genomics and Diagnostics (16 papers), Lung Cancer Treatments and Mutations (12 papers) and RNA modifications and cancer (8 papers). Toshihide Ueno collaborates with scholars based in Japan, United Kingdom and United States. Toshihide Ueno's co-authors include Hiroyuki Mano, Young Lim Choi, Manabu Soda, Yoshihiro Yamashita, Kengo Takeuchi, Yuichi Ishikawa, Hidenori Haruta, Toru Hamada, Shuji Takada and Yasushi Yatabe and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Toshihide Ueno

70 papers receiving 4.0k citations

Hit Papers

EML4-ALK Mutations in Lung Cancer That Confer Resistance ... 2009 2026 2014 2020 2010 2009 250 500 750

Peers

Toshihide Ueno
Yang Shao China
Toshihide Ueno
Citations per year, relative to Toshihide Ueno Toshihide Ueno (= 1×) peers Yang Shao

Countries citing papers authored by Toshihide Ueno

Since Specialization
Citations

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

Fields of papers citing papers by Toshihide Ueno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Toshihide Ueno

This figure shows the co-authorship network connecting the top 25 collaborators of Toshihide Ueno. A scholar is included among the top collaborators of Toshihide Ueno 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 Toshihide Ueno. Toshihide Ueno 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.
Maruno, Takahiro, Yasuo Tsunaka, Yuki Yamaguchi, et al.. (2025). Variation of VP2 stoichiometry and deamidation of VP1 during production and their impacts on the transduction efficiency of AAV vectors. Molecular Therapy — Methods & Clinical Development. 33(4). 101581–101581.
2.
Ueno, Toshihide, Shinya Kojima, Hiroshi Ikeuchi, et al.. (2024). The development of a custom RNA-sequencing panel for the identification of predictive and diagnostic biomarkers in glioma. Journal of Neuro-Oncology. 167(1). 75–88. 2 indexed citations
3.
Ikeuchi, Hiroshi, Rika Kusumoto‐Matsuo, Shinya Kojima, et al.. (2024). GLI1 confers resistance to PARP inhibitors by activating the DNA damage repair pathway. Oncogene. 43(41). 3037–3048. 2 indexed citations
4.
Koyama, Takafumi, Toshio Shimizu, Yuki Kojima, et al.. (2023). Clinical Activity and Exploratory Resistance Mechanism of Milademetan, an MDM2 Inhibitor, in Intimal Sarcoma with MDM2 Amplification: An Open-Label Phase Ib/II Study. Cancer Discovery. 13(8). 1814–1825. 25 indexed citations
5.
Ueno, Toshihide, Masanaka Sugiyama, Shinya Kojima, et al.. (2023). Promoter swapping of truncated PDGFRB drives Ph-like acute lymphoblastic leukemia. npj Precision Oncology. 7(1). 132–132. 1 indexed citations
6.
Ryo, Eijitsu, Satoshi Inoue, Masahito Kawazu, et al.. (2023). Strategic Approach to Heterogeneity Analysis of Cutaneous Adnexal Carcinomas Using Computational Pathology and Genomics. SHILAP Revista de lepidopterología. 3(6). 100229–100229. 1 indexed citations
7.
Ikegami, Masachika, Takafumi Koyama, Kuniko Sunami, et al.. (2022). High-Throughput Functional Evaluation of MAP2K1 Variants in Cancer. Molecular Cancer Therapeutics. 22(2). 227–239. 15 indexed citations
8.
Nagai, Sumimasa, Hiroshi Nishihara, Takayoshi Suzuki, et al.. (2022). Recommendations related to the analytical equivalence assessment of gene panel testing. Cancer Science. 113(10). 3282–3290. 1 indexed citations
9.
Tanaka, Yosuke, Fumiko Chiwaki, Shinya Kojima, et al.. (2021). Multi-omic profiling of peritoneal metastases in gastric cancer identifies molecular subtypes and therapeutic vulnerabilities. Nature Cancer. 2(9). 962–977. 61 indexed citations
10.
Ikegami, Masachika, Shinji Kohsaka, Takeshi Hirose, et al.. (2021). MicroSEC filters sequence errors for formalin-fixed and paraffin-embedded samples. Communications Biology. 4(1). 1396–1396. 5 indexed citations
11.
Chida, Keigo, Akihito Kawazoe, Masahito Kawazu, et al.. (2021). A Low Tumor Mutational Burden and PTEN Mutations Are Predictors of a Negative Response to PD-1 Blockade in MSI-H/dMMR Gastrointestinal Tumors. Clinical Cancer Research. 27(13). 3714–3724. 76 indexed citations
12.
Yagishita, Shigehiro, Yoshiharu Hayashi, Mikiko Suzuki, et al.. (2021). Comparative Study on the Efficacy and Exposure of Molecular Target Agents in Non–small Cell Lung Cancer PDX Models with Driver Genetic Alterations. Molecular Cancer Therapeutics. 21(2). 359–370. 6 indexed citations
13.
Sato, Kazuhito, Masahito Kawazu, Yoko Yamamoto, et al.. (2018). Fusion Kinases Identified by Genomic Analyses of Sporadic Microsatellite Instability–High Colorectal Cancers. Clinical Cancer Research. 25(1). 378–389. 44 indexed citations
14.
Yasuda, Takahiko, Shinya Kojima, Masahito Kawazu, et al.. (2018). Genomic and Clinical Characterization of Adult Ph-Negative B-Cell Acute Lymphoblastic Leukemia. Blood. 132(Supplement 1). 2821–2821. 4 indexed citations
15.
Ando, Mizuo, Masahito Kawazu, Toshihide Ueno, et al.. (2013). Cancer‐associated missense mutations of caspase‐8 activate nuclear factor‐κB signaling. Cancer Science. 104(8). 1002–1008. 34 indexed citations
16.
Soda, Manabu, Kazutoshi Isobe, Akira Inoue, et al.. (2012). A Prospective PCR-Based Screening for the EML4-ALK Oncogene in Non–Small Cell Lung Cancer. Clinical Cancer Research. 18(20). 5682–5689. 96 indexed citations
17.
Choi, Young Lim, Manabu Soda, Yoshihiro Yamashita, et al.. (2010). EML4-ALK Mutations in Lung Cancer That Confer Resistance to ALK Inhibitors. New England Journal of Medicine. 363(18). 1734–1739. 915 indexed citations breakdown →
18.
Takeuchi, Kengo, Young Lim Choi, Yuki Togashi, et al.. (2009). KIF5B-ALK, a Novel Fusion Oncokinase Identified by an Immunohistochemistry-based Diagnostic System for ALK-positive Lung Cancer. Clinical Cancer Research. 15(9). 3143–3149. 557 indexed citations breakdown →
19.
Choi, Young Lim, Kengo Takeuchi, Manabu Soda, et al.. (2008). Identification of Novel Isoforms of the EML4-ALK Transforming Gene in Non–Small Cell Lung Cancer. Cancer Research. 68(13). 4971–4976. 346 indexed citations
20.
Soda, Manabu, Shuji Takada, Kengo Takeuchi, et al.. (2008). A mouse model for EML4-ALK -positive lung cancer. Proceedings of the National Academy of Sciences. 105(50). 19893–19897. 396 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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