Kaoru Abiko

6.5k total citations · 3 hit papers
102 papers, 4.0k citations indexed

About

Kaoru Abiko is a scholar working on Reproductive Medicine, Oncology and Obstetrics and Gynecology. According to data from OpenAlex, Kaoru Abiko has authored 102 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Reproductive Medicine, 39 papers in Oncology and 30 papers in Obstetrics and Gynecology. Recurrent topics in Kaoru Abiko's work include Ovarian cancer diagnosis and treatment (37 papers), Endometrial and Cervical Cancer Treatments (25 papers) and Cancer Immunotherapy and Biomarkers (20 papers). Kaoru Abiko is often cited by papers focused on Ovarian cancer diagnosis and treatment (37 papers), Endometrial and Cervical Cancer Treatments (25 papers) and Cancer Immunotherapy and Biomarkers (20 papers). Kaoru Abiko collaborates with scholars based in Japan, United States and Egypt. Kaoru Abiko's co-authors include Tsukasa Baba, Junzo Hamanishi, Noriomi Matsumura, Masaki Mandai, Ikuo Konishi, Ken Yamaguchi, Ryusuke Murakami, Naoki Horikawa, Yumiko Yoshioka and Yuko Hosoe and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Cancer Research.

In The Last Decade

Kaoru Abiko

98 papers receiving 4.0k citations

Hit Papers

IFN-γ from lymphocytes induces PD-L1 expression and promo... 2015 2026 2018 2022 2015 2015 2021 100 200 300 400 500
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. IFN-γ from lymphocytes induces PD-L1 expression and promotes progression of ovarian cancer
    2015 572 citations Kaoru Abiko, Noriomi Matsumura et al. British Journal of Cancer profile →
  2. Chemotherapy Induces Programmed Cell Death-Ligand 1 Overexpression via the Nuclear Factor-κB to Foster an Immunosuppressive Tumor Microenvironment in Ovarian Cancer
    2015 437 citations Peng Jin, Junzo Hamanishi et al. Cancer Research profile →
  3. Tumor Immune Microenvironment during Epithelial–Mesenchymal Transition
    2021 227 citations Mana Taki, Kaoru Abiko et al. Clinical Cancer Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kaoru Abiko Japan 25 2.4k 1.8k 965 697 591 102 4.0k
Marco de Bruyn Netherlands 30 1.7k 0.7× 1.7k 0.9× 986 1.0× 266 0.4× 347 0.6× 77 3.3k
Ryusuke Murakami Japan 19 1.2k 0.5× 952 0.5× 606 0.6× 450 0.6× 324 0.5× 78 2.3k
Regina S. Whitaker United States 34 1.7k 0.7× 673 0.4× 2.2k 2.3× 1.5k 2.1× 263 0.4× 72 4.3k
Makoto Saegusa Japan 38 1.3k 0.6× 460 0.2× 1.8k 1.9× 430 0.6× 565 1.0× 163 3.8k
Burkhard Helmke Germany 28 897 0.4× 418 0.2× 1.3k 1.3× 330 0.5× 291 0.5× 78 2.9k
Joseph Kwong Hong Kong 32 803 0.3× 476 0.3× 1.6k 1.7× 313 0.4× 241 0.4× 56 2.8k
Akira Hirasawa Japan 34 738 0.3× 324 0.2× 1.4k 1.5× 565 0.8× 252 0.4× 130 3.0k
Yoshito Terai Japan 29 697 0.3× 378 0.2× 1.1k 1.2× 908 1.3× 187 0.3× 136 2.7k
Eliana Bignotti Italy 27 578 0.2× 337 0.2× 754 0.8× 650 0.9× 214 0.4× 67 2.3k
Masafumi Koshiyama Japan 24 602 0.3× 400 0.2× 699 0.7× 883 1.3× 200 0.3× 81 2.0k

Countries citing papers authored by Kaoru Abiko

Since Specialization
Citations

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

Fields of papers citing papers by Kaoru Abiko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaoru Abiko

This figure shows the co-authorship network connecting the top 25 collaborators of Kaoru Abiko. A scholar is included among the top collaborators of Kaoru Abiko 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 Kaoru Abiko. Kaoru Abiko 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.
Kotani, Yasushi, Aki Kido, Tomoyuki Otani, et al.. (2025). Differentiation of uterine fibroids and sarcomas by MRI and serum LDH levels: a multicenter study of the KAMOGAWA study. Journal of Gynecologic Oncology. 36(4). e58–e58.
2.
Yamaguchi, Ken, Koji Yamanoi, Shiro Takamatsu, et al.. (2024). YAP1 Suppression by ZDHHC7 Is Associated with Ferroptosis Resistance and Poor Prognosis in Ovarian Clear Cell Carcinoma. Molecular Cancer Therapeutics. 23(11). 1652–1665. 7 indexed citations
3.
Yachida, Nozomi, Manako Yamaguchi, Kaoru Yamawaki, et al.. (2023). SLFN11 is a BRCA Independent Biomarker for the Response to Platinum-Based Chemotherapy in High-Grade Serous Ovarian Cancer and Clear Cell Ovarian Carcinoma. Molecular Cancer Therapeutics. 23(1). 106–116. 8 indexed citations
4.
Konishi, Ikuo, Kaoru Abiko, Takuma Hayashi, et al.. (2022). Peritoneal dissemination of high-grade serous ovarian cancer: pivotal roles of chromosomal instability and epigenetic dynamics. Journal of Gynecologic Oncology. 33(5). e83–e83. 10 indexed citations
5.
Abiko, Kaoru, Junzo Hamanishi, Noriomi Matsumura, & Masaki Mandai. (2022). Dynamic host immunity and PD-L1/PD-1 blockade efficacy: developments after “IFN-γ from lymphocytes induces PD-L1 expression and promotes progression of ovarian cancer”. British Journal of Cancer. 128(3). 461–467. 23 indexed citations
6.
Hayashi, Takuma, et al.. (2022). Characteristic of Uterine Rhabdomyosarcoma by Algorithm of Potential Biomarkers for Uterine Mesenchymal Tumor. Current Oncology. 29(4). 2350–2363. 5 indexed citations
7.
Ikeda, A., et al.. (2021). Lymphoepithelioma‐like carcinoma of uterine cervix: Preoperative diagnosis and course in three cases. Journal of obstetrics and gynaecology research. 47(11). 4093–4100. 1 indexed citations
8.
Horikawa, Naoki, Kaoru Abiko, Noriomi Matsumura, et al.. (2020). Anti-VEGF therapy resistance in ovarian cancer is caused by GM-CSF-induced myeloid-derived suppressor cell recruitment. British Journal of Cancer. 122(6). 778–788. 72 indexed citations
9.
Watanabe, Koichi, et al.. (2020). Right-sided Sigmoid Colon Revealed during Laparoscopic Sacrocolpopexy. Journal of Minimally Invasive Gynecology. 28(7). 1267–1268. 1 indexed citations
10.
Hayashi, Takuma, Kaoru Abiko, Ken Yamaguchi, Masaki Mandai, & Ikuo Konishi. (2020). Potential Novel Ovarian Cancer Treatment Targeting Myeloid-Derived Suppressor Cells. 1–5. 2 indexed citations
11.
Watanabe, Koichi, Kaoru Abiko, Sachiko Minamiguchi, et al.. (2019). Aggressive adult granulosa cell tumor of the ovary without a FOXL2 mutation: A case report. Journal of obstetrics and gynaecology research. 45(7). 1404–1409. 4 indexed citations
12.
Miyamoto, Taito, Ryusuke Murakami, Kaoru Abiko, et al.. (2019). The efficacy of secondary cytoreductive surgery for recurrent ovarian, tubal, or peritoneal cancer in Tian-model low-risk patients. Journal of Gynecologic Oncology. 30(6). e100–e100. 10 indexed citations
13.
Abiko, Kaoru, et al.. (2017). Case of rapidly progressing condylomatous squamous cell carcinoma of the uterine cervix associated with low‐risk human papillomavirus type 6. Journal of obstetrics and gynaecology research. 44(3). 583–587. 8 indexed citations
14.
Abiko, Kaoru, et al.. (2017). Adult granulosa cell tumors of the ovary: a retrospective study of 30 cases with respect to the expression of steroid synthesis enzymes. Journal of Gynecologic Oncology. 28(4). e31–e31. 12 indexed citations
15.
Yamaguchi, Ken, Yasuhisa Kurata, Ryusuke Murakami, et al.. (2017). Unenhanced region on magnetic resonance imaging represents tumor progression in uterine carcinosarcoma. Journal of Gynecologic Oncology. 28(5). e62–e62. 4 indexed citations
16.
Yamaguchi, Ken, Noriomi Matsumura, Hidekatsu Nakai, et al.. (2016). Groin lymph node detection and sentinel lymph node biopsy in vulvar cancer. Journal of Gynecologic Oncology. 27(6). e57–e57. 9 indexed citations
17.
Horikawa, Naoki, Kaoru Abiko, Noriomi Matsumura, et al.. (2016). Expression of Vascular Endothelial Growth Factor in Ovarian Cancer Inhibits Tumor Immunity through the Accumulation of Myeloid-Derived Suppressor Cells. Clinical Cancer Research. 23(2). 587–599. 228 indexed citations
18.
Jin, Peng, Junzo Hamanishi, Noriomi Matsumura, et al.. (2015). Chemotherapy Induces Programmed Cell Death-Ligand 1 Overexpression via the Nuclear Factor-κB to Foster an Immunosuppressive Tumor Microenvironment in Ovarian Cancer. Cancer Research. 75(23). 5034–5045. 437 indexed citations breakdown →
19.
Abiko, Kaoru, Masaki Mandai, Junzo Hamanishi, et al.. (2013). PD-L1 on Tumor Cells Is Induced in Ascites and Promotes Peritoneal Dissemination of Ovarian Cancer through CTL Dysfunction. Clinical Cancer Research. 19(6). 1363–1374. 187 indexed citations
20.
Shintaku, Masayuki, Ryoji Kushima, & Kaoru Abiko. (2009). Colloid carcinoma of the intestinal type in the uterine cervix: Mucin immunohistochemistry. Pathology International. 60(2). 119–124. 5 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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