Chikashi Ishioka

11.4k total citations · 2 hit papers
243 papers, 8.5k citations indexed

About

Chikashi Ishioka is a scholar working on Oncology, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Chikashi Ishioka has authored 243 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 133 papers in Oncology, 106 papers in Molecular Biology and 53 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Chikashi Ishioka's work include Cancer-related Molecular Pathways (51 papers), Colorectal Cancer Treatments and Studies (38 papers) and Genetic factors in colorectal cancer (34 papers). Chikashi Ishioka is often cited by papers focused on Cancer-related Molecular Pathways (51 papers), Colorectal Cancer Treatments and Studies (38 papers) and Genetic factors in colorectal cancer (34 papers). Chikashi Ishioka collaborates with scholars based in Japan, United States and Canada. Chikashi Ishioka's co-authors include Shunsuke Kato, Ryunosuke Kanamaru, Hiroyuki Shibata, Pierre Hainaut, Magali Olivier, Ewy A. Mathé, Audrey Petitjean, Sean V. Tavtigian, Kazunori Otsuka and Thierry Soussi and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Chikashi Ishioka

235 papers receiving 8.4k citations

Hit Papers

Impact of mutant p53 functional properties onTP53mutation... 2003 2026 2010 2018 2007 2003 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chikashi Ishioka Japan 47 5.0k 4.3k 2.0k 1.1k 1.0k 243 8.5k
Magali Olivier France 37 5.6k 1.1× 5.1k 1.2× 3.2k 1.6× 894 0.8× 1.3k 1.2× 68 9.4k
Steven de Jong Netherlands 53 5.2k 1.0× 3.3k 0.8× 1.9k 0.9× 730 0.7× 1.0k 1.0× 188 9.1k
C C Harris United States 35 5.6k 1.1× 5.4k 1.2× 2.6k 1.3× 1.0k 0.9× 986 0.9× 65 9.9k
Kenneth H. Cowan United States 61 7.6k 1.5× 6.1k 1.4× 1.9k 0.9× 1.0k 0.9× 691 0.7× 195 13.4k
Monica Mita United States 47 4.5k 0.9× 3.6k 0.8× 1.2k 0.6× 686 0.6× 1.9k 1.8× 239 8.2k
Wells A. Messersmith United States 52 4.3k 0.9× 5.3k 1.2× 1.7k 0.8× 1.2k 1.1× 1.8k 1.7× 298 9.5k
Hal W. Hirte Canada 45 3.2k 0.6× 3.7k 0.9× 977 0.5× 1.0k 0.9× 1.3k 1.2× 156 8.1k
Timothy J. Yeatman United States 56 5.9k 1.2× 5.1k 1.2× 2.9k 1.4× 2.1k 1.9× 1.6k 1.6× 169 11.8k
Dick J. Richel Netherlands 43 3.5k 0.7× 4.5k 1.1× 2.2k 1.1× 795 0.7× 1.7k 1.6× 107 9.6k
Paula Soares Portugal 54 4.4k 0.9× 2.8k 0.6× 1.3k 0.6× 1.4k 1.3× 902 0.9× 290 10.0k

Countries citing papers authored by Chikashi Ishioka

Since Specialization
Citations

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

Fields of papers citing papers by Chikashi Ishioka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chikashi Ishioka

This figure shows the co-authorship network connecting the top 25 collaborators of Chikashi Ishioka. A scholar is included among the top collaborators of Chikashi Ishioka 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 Chikashi Ishioka. Chikashi Ishioka 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
2.
Takahashi, Masanobu, et al.. (2024). Tretinoin synergistically enhances the antitumor effect of combined BRAF, MEK, and EGFR inhibition in BRAFV600E colorectal cancer. Cancer Science. 115(11). 3740–3754. 1 indexed citations
3.
Imai, Hiroo, et al.. (2024). Nivolumab-induced Thrombotic Thrombocytopenic Purpura in Patients with Gastric Tube Cancer. Internal Medicine. 63(19). 2667–2671. 1 indexed citations
4.
Tahara, Makoto, Tatsunori Shimoi, Satoshi Nishiwaki, et al.. (2023). Phase II trial of dabrafenib and trametinib in patients with BRAFV600E/R or non-BRAFV600 mutated advanced solid tumors: Results from the BELIEVE trial (NCCH1901).. Journal of Clinical Oncology. 41(16_suppl). 3096–3096. 1 indexed citations
6.
Imai, Hiroo, Ken Saijo, Keigo Komine, et al.. (2022). Antibiotic Treatment Improves the Efficacy of Oxaliplatin-Based Therapy as First-Line Chemotherapy for Patients with Advanced Gastric Cancer: A Retrospective Study. SHILAP Revista de lepidopterología. 7 indexed citations
7.
Kawamura, Yoshifumi, Ken Saijo, Hiroo Imai, & Chikashi Ishioka. (2021). Inhibition of IRAK1/4 enhances the antitumor effect of lenvatinib in anaplastic thyroid cancer cells. Cancer Science. 112(11). 4711–4721. 6 indexed citations
8.
9.
Yoshino, Yuki, Hiroki Fujita, Matsuyuki Shirota, et al.. (2018). BRCA1-Interacting Protein OLA1 Requires Interaction with BARD1 to Regulate Centrosome Number. Molecular Cancer Research. 16(10). 1499–1511. 23 indexed citations
10.
Shirota, Hidekazu, et al.. (2016). IL4 from T Follicular Helper Cells Downregulates Antitumor Immunity. Cancer Immunology Research. 5(1). 61–71. 31 indexed citations
11.
Yoshino, Yuki & Chikashi Ishioka. (2015). Inhibition of glycogen synthase kinase-3 beta induces apoptosis and mitotic catastrophe by disrupting centrosome regulation in cancer cells. Scientific Reports. 5(1). 13249–13249. 61 indexed citations
12.
Kawai, S., et al.. (2012). Suppression of FUT1 attenuates cell proliferation in the HER2-overexpressing cancer cell line NCI-N87. Oncology Reports. 29(1). 13–20. 30 indexed citations
14.
Chiba, Natsuko, et al.. (2010). Identification of Breast Tumor Mutations in BRCA1 That Abolish Its Function in Homologous DNA Recombination. Cancer Research. 70(3). 988–995. 96 indexed citations
15.
Watanabe, Gou, et al.. (2009). αB‐crystallin: A novel p53‐target gene required for p53‐dependent apoptosis. Cancer Science. 100(12). 2368–2375. 48 indexed citations
16.
Soussi, Thierry, Bernard Asselain, Dalil Hamroun, et al.. (2006). Meta-analysis of the p53 Mutation Database for Mutant p53 Biological Activity Reveals a Methodologic Bias in Mutation Detection. Clinical Cancer Research. 12(1). 62–69. 58 indexed citations
17.
Ohori, Hisatsugu, Hiroyuki Yamakoshi, Masaki Tomizawa, et al.. (2006). Synthesis and biological analysis of new curcumin analogues bearing an enhanced potential for the medicinal treatment of cancer. Molecular Cancer Therapeutics. 5(10). 2563–2571. 210 indexed citations
18.
Kakudo, Yuichi, Hiroyuki Shibata, Kazunori Otsuka, Shunsuke Kato, & Chikashi Ishioka. (2005). Lack of Correlation between p53-Dependent Transcriptional Activity and the Ability to Induce Apoptosis among 179 Mutant p53s. Cancer Research. 65(6). 2108–2114. 72 indexed citations
19.
Kato, Shunsuke, Shuang-Yin Han, Wen Liu, et al.. (2003). Understanding the function–structure and function–mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis. Proceedings of the National Academy of Sciences. 100(14). 8424–8429. 626 indexed citations breakdown →
20.
Suzuki, Takashi, et al.. (1994). [Genetic alterations of human colorectal cancer].. PubMed. 21(3). 343–50. 1 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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