Kisato Nosaka

6.4k total citations · 1 hit paper
89 papers, 3.0k citations indexed

About

Kisato Nosaka is a scholar working on Immunology, Ecology, Evolution, Behavior and Systematics and Agronomy and Crop Science. According to data from OpenAlex, Kisato Nosaka has authored 89 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Immunology, 35 papers in Ecology, Evolution, Behavior and Systematics and 24 papers in Agronomy and Crop Science. Recurrent topics in Kisato Nosaka's work include T-cell and Retrovirus Studies (48 papers), Vector-Borne Animal Diseases (35 papers) and Animal Disease Management and Epidemiology (24 papers). Kisato Nosaka is often cited by papers focused on T-cell and Retrovirus Studies (48 papers), Vector-Borne Animal Diseases (35 papers) and Animal Disease Management and Epidemiology (24 papers). Kisato Nosaka collaborates with scholars based in Japan, United States and United Kingdom. Kisato Nosaka's co-authors include Masao Matsuoka, Jun‐ichirou Yasunaga, Hiroaki Mitsuya, Tatsunori Sakai, Yuko Taniguchi, Michiyuki Maeda, Yorifumi Satou, Atae Utsunomiya, Yuetsu Tanaka and Kensei Tobinai and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Kisato Nosaka

83 papers receiving 2.9k citations

Hit Papers

Defucosylated Anti-CCR4 Monoclonal Antibody (KW-0761) for... 2012 2026 2016 2021 2012 100 200 300 400

Peers

Kisato Nosaka
Yuji Wano Japan
Kisato Nosaka
Citations per year, relative to Kisato Nosaka Kisato Nosaka (= 1×) peers Yuji Wano

Countries citing papers authored by Kisato Nosaka

Since Specialization
Citations

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

Fields of papers citing papers by Kisato Nosaka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kisato Nosaka

This figure shows the co-authorship network connecting the top 25 collaborators of Kisato Nosaka. A scholar is included among the top collaborators of Kisato Nosaka 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 Kisato Nosaka. Kisato Nosaka 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.
Tatetsu, Hiro, Yusuke Higuchi, Toshikazu Miyakawa, et al.. (2025). Prognostic impact of valemetostat in relapsed/refractory adult T‐cell leukaemia‐lymphoma. British Journal of Haematology. 208(1). 159–169.
2.
Nosaka, Kisato & Takuya Fukushima. (2025). JSH practical guidelines for hematological malignancies, 2023: II. lymphoma 9—adult T-cell leukemia–lymphoma (ATL). International Journal of Hematology. 122(2). 177–189. 1 indexed citations
3.
Tatetsu, Hiro, Koji Kato, Atsushi Wada, et al.. (2025). Peripheral T cell lymphoma following CD19-targeted chimeric antigen receptor T cell therapy. International Journal of Hematology. 122(6). 815–819.
4.
Watanabe, Miho, et al.. (2025). JunB–HBZ nuclear translocation by TGF-β is a key driver in HTLV-1-mediated leukemogenesis. Proceedings of the National Academy of Sciences. 122(26). e2420756122–e2420756122.
5.
Saijo, Masayuki, Koichi Izumikawa, Koichiro Suemori, et al.. (2025). Efficacy of favipiravir treatment for patients with severe fever with thrombocytopenia syndrome assessed with a historical control. Antimicrobial Agents and Chemotherapy. 69(12). e0106225–e0106225.
6.
Yoshimitsu, Makoto, Ilseung Choi, Shigeru Kusumoto, et al.. (2025). A phase 2 trial of CHOP with anti-CCR4 antibody mogamulizumab for older patients with adult T-cell leukemia/lymphoma. Blood. 146(12). 1440–1449. 5 indexed citations
7.
Fukushima, Takuya, Kunihiro Tsukasaki, Ryunosuke Machida, et al.. (2024). Upfront allo-HSCT after intensive chemotherapy for untreated aggressive ATL: JCOG0907, a single-arm, phase 3 trial.. Journal of Clinical Oncology. 42(16_suppl). 7001–7001. 1 indexed citations
8.
Yasunaga, Jun‐ichirou, Kei Sato, Kisato Nosaka, et al.. (2024). Vulnerability to APOBEC3G linked to the pathogenicity of deltaretroviruses. Proceedings of the National Academy of Sciences. 121(13). e2309925121–e2309925121. 13 indexed citations
9.
Miyamoto, Hideaki, Satoru Shinriki, Katsuya Nagaoka, et al.. (2024). Clinical utility of a comprehensive genomic profiling test for patient with advanced biliary tract cancer. International Journal of Clinical Oncology. 29(12). 1908–1915. 2 indexed citations
10.
Yasunaga, Jun‐ichirou, L. Liang, Shinji Nakaoka, et al.. (2023). Anti‐HTLV‐1 immunity combined with proviral load as predictive biomarkers for adult T‐cell leukemia‐lymphoma. Cancer Science. 115(1). 310–320. 7 indexed citations
11.
Matsuo, Misaki, Takaharu Ueno, Kazuaki Monde, et al.. (2022). Identification and characterization of a novel enhancer in the HTLV-1 proviral genome. Nature Communications. 13(1). 2405–2405. 24 indexed citations
12.
Yano, Hiromu, Yukio Fujiwara, Hasita Horlad, et al.. (2022). Blocking cholesterol efflux mechanism is a potential target for antilymphoma therapy. Cancer Science. 113(6). 2129–2143. 13 indexed citations
13.
Tatetsu, Hiro, Kisato Nosaka, Yusuke Higuchi, et al.. (2022). Predictive impact of soluble interleukin‐2 receptor and number of extranodal sites for identification of patients at very high risk of CNS relapse in diffuse large B‐cell lymphoma. SHILAP Revista de lepidopterología. 3(2). 385–393. 2 indexed citations
14.
Yasunaga, Jun‐ichirou, Kisato Nosaka, Kenji Sugata, et al.. (2021). In vivo dynamics and adaptation of HTLV-1-infected clones under different clinical conditions. PLoS Pathogens. 17(2). e1009271–e1009271. 10 indexed citations
15.
Nosaka, Kisato & Masao Matsuoka. (2021). Adult T‐cell leukemia‐lymphoma as a viral disease: Subtypes based on viral aspects. Cancer Science. 112(5). 1688–1694. 19 indexed citations
16.
Ito, Shigeki, Masako Iwanaga, Kisato Nosaka, et al.. (2021). Epidemiology of adult T‐cell leukemia‐lymphoma in Japan: An updated analysis, 2012‐2013. Cancer Science. 112(10). 4346–4354. 22 indexed citations
17.
Imaizumi, Yoshitaka, Masako Iwanaga, Kisato Nosaka, et al.. (2020). Prognosis of patients with adult T‐cell leukemia/lymphoma in Japan: A nationwide hospital‐based study. Cancer Science. 111(12). 4567–4580. 48 indexed citations
18.
Satou, Yorifumi, Paola Miyazato, Ko Ishihara, et al.. (2016). The retrovirus HTLV-1 inserts an ectopic CTCF-binding site into the human genome. Proceedings of the National Academy of Sciences. 113(11). 3054–3059. 97 indexed citations
19.
Yasunaga, Jun‐ichirou, Yuko Taniguchi, Kisato Nosaka, et al.. (2004). Identification of Aberrantly Methylated Genes in Association with Adult T-Cell Leukemia. Cancer Research. 64(17). 6002–6009. 110 indexed citations
20.
Yasunaga, Jun‐ichirou, Tatsunori Sakai, Kisato Nosaka, et al.. (2001). Impaired production of naive T lymphocytes in human T-cell leukemia virus type I–infected individuals: its implications in the immunodeficient state. Blood. 97(10). 3177–3183. 128 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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