Wenfeng Fang

9.8k total citations · 2 hit papers
201 papers, 4.9k citations indexed

About

Wenfeng Fang is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Wenfeng Fang has authored 201 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 152 papers in Oncology, 126 papers in Pulmonary and Respiratory Medicine and 42 papers in Molecular Biology. Recurrent topics in Wenfeng Fang's work include Lung Cancer Treatments and Mutations (120 papers), Cancer Immunotherapy and Biomarkers (58 papers) and Lung Cancer Research Studies (48 papers). Wenfeng Fang is often cited by papers focused on Lung Cancer Treatments and Mutations (120 papers), Cancer Immunotherapy and Biomarkers (58 papers) and Lung Cancer Research Studies (48 papers). Wenfeng Fang collaborates with scholars based in China, United States and Canada. Wenfeng Fang's co-authors include Shaodong Hong, Yan Huang, Yunpeng Yang, Hongyun Zhao, Yuxiang Ma, Li Zhang, Jianhua Zhan, Yaxiong Zhang, Li Zhang and Yuanyuan Zhao and has published in prestigious journals such as JAMA, Journal of Clinical Investigation and Journal of Clinical Oncology.

In The Last Decade

Wenfeng Fang

191 papers receiving 4.8k citations

Hit Papers

Upregulation of PD-L1 by ... 2015 2026 2018 2022 2015 2018 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wenfeng Fang China 33 3.4k 2.4k 1.1k 890 681 201 4.9k
Hidetoshi Hayashi Japan 36 3.7k 1.1× 2.8k 1.2× 1.4k 1.3× 705 0.8× 488 0.7× 248 5.2k
Patrick M. Forde United States 40 4.0k 1.2× 2.7k 1.2× 934 0.9× 645 0.7× 1.1k 1.7× 186 5.7k
Kazuko Sakai Japan 41 2.7k 0.8× 2.3k 1.0× 2.0k 1.9× 1.3k 1.4× 316 0.5× 245 5.4k
Yuanyuan Zhao China 29 1.9k 0.5× 1.1k 0.5× 558 0.5× 533 0.6× 273 0.4× 162 3.0k
Miao‐Zhen Qiu China 38 2.5k 0.7× 1.6k 0.7× 1.6k 1.5× 1.3k 1.4× 408 0.6× 165 4.9k
Young Kwang Chae United States 40 3.1k 0.9× 1.9k 0.8× 2.6k 2.4× 1.7k 1.9× 820 1.2× 274 6.4k
Andréa Varga France 33 3.0k 0.9× 1.2k 0.5× 1.2k 1.1× 547 0.6× 816 1.2× 107 4.6k
Kenji Sugio Japan 47 3.2k 0.9× 3.3k 1.4× 2.7k 2.6× 1.1k 1.3× 664 1.0× 276 7.1k
Ferdinando De Vita Italy 43 3.4k 1.0× 2.2k 0.9× 2.0k 1.8× 1.0k 1.1× 603 0.9× 207 6.0k
Á. Artal Spain 20 3.2k 0.9× 2.5k 1.0× 878 0.8× 606 0.7× 607 0.9× 82 4.3k

Countries citing papers authored by Wenfeng Fang

Since Specialization
Citations

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

Fields of papers citing papers by Wenfeng Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenfeng Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Wenfeng Fang. A scholar is included among the top collaborators of Wenfeng Fang 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 Wenfeng Fang. Wenfeng Fang 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.
Lu, Di, Wenfeng Fang, Shuai Zhang, et al.. (2025). ZDHHC18 promotes renal fibrosis development by regulating HRAS palmitoylation. Journal of Clinical Investigation. 135(6). 4 indexed citations
3.
Ma, Yuxiang, Huaqiang Zhou, Fan Luo, et al.. (2024). Remodeling the tumor-immune microenvironment by anti-CTLA4 blockade enhanced subsequent anti-PD-1 efficacy in advanced nasopharyngeal carcinoma. npj Precision Oncology. 8(1). 65–65. 6 indexed citations
4.
Huang, Yan, Yunpeng Yang, Yuanyuan Zhao, et al.. (2024). QL1706 (anti-PD-1 IgG4/CTLA-4 antibody) plus chemotherapy with or without bevacizumab in advanced non-small cell lung cancer: a multi-cohort, phase II study. Signal Transduction and Targeted Therapy. 9(1). 23–23. 10 indexed citations
6.
Liu, Tingting, Xueyuan Chen, Ting Zhou, et al.. (2024). Molecular subtypes and prognostic factors of lung large cell neuroendocrine carcinoma. Translational Lung Cancer Research. 13(9). 2222–2235. 2 indexed citations
7.
Zhuang, Weitao, Dongfang Wu, Lanlan Pang, et al.. (2024). EGFR Oncogenic Mutations in NSCLC Impair Macrophage Phagocytosis and Mediate Innate Immune Evasion Through Up-Regulation of CD47. Journal of Thoracic Oncology. 19(8). 1186–1200. 23 indexed citations
9.
Fang, Wenfeng, Yunpeng Yang, Yan Huang, et al.. (2023). 74P A single-center, phase II study of surufatinib combined with toripalimab, pemetrexed(A), and platinum (P) in patients with advanced non-squamous non-small cell lung cancer (nsq-NSCLC). Immuno-Oncology Technology. 20. 100546–100546. 1 indexed citations
10.
Li, Anlin, Zhixin Yu, Zihui Tan, et al.. (2023). STK11/LKB1-Deficient Phenotype Rather Than Mutation Diminishes Immunotherapy Efficacy and Represents STING/Type I Interferon/CD8+ T-Cell Dysfunction in NSCLC. Journal of Thoracic Oncology. 18(12). 1714–1730. 21 indexed citations
12.
Ma, Yuxiang, Yuanyuan Zhao, Yang Zhang, et al.. (2023). Phase I trial of KN046, a novel bispecific antibody targeting PD-L1 and CTLA-4 in patients with advanced solid tumors. Journal for ImmunoTherapy of Cancer. 11(6). e006654–e006654. 34 indexed citations
13.
Wang, Yixuan, Jiayin Wang, Wenfeng Fang, et al.. (2023). TMBserval: a statistical explainable learning model reveals weighted tumor mutation burden better categorizing therapeutic benefits. Frontiers in Immunology. 14. 15 indexed citations
14.
15.
Ma, Yuxiang, Qun Chen, Yang Zhang, et al.. (2023). Pharmacokinetics, safety, tolerability, and feasibility of apatinib in combination with gefitinib in stage IIIB-IV EGFR-mutated non-squamous NSCLC: a drug-drug interaction study. Cancer Chemotherapy and Pharmacology. 92(5). 411–418. 1 indexed citations
16.
Chen, Xi, Wen Xie, Heng Liang, et al.. (2022). FOXM1 Variant Contributes to Gefitinib Resistance via Activating Wnt/β-Catenin Signal Pathway in Patients with Non–Small Cell Lung Cancer. Clinical Cancer Research. 28(17). 3770–3784. 32 indexed citations
17.
Zhou, Huaqiang, Jiaqing Liu, Yaxiong Zhang, et al.. (2020). PBRM1 mutation and preliminary response to immune checkpoint blockade treatment in non-small cell lung cancer. npj Precision Oncology. 4(1). 6–6. 36 indexed citations
18.
Ma, Yuxiang, Qingguang Lin, Yunpeng Yang, et al.. (2020). Clinical pharmacokinetics and drug exposure-toxicity correlation study of docetaxel based chemotherapy in Chinese head and neck cancer patients. Annals of Translational Medicine. 8(5). 236–236. 9 indexed citations
19.
Fang, Wenfeng, Yuxiang Ma, Jiani C. Yin, et al.. (2019). Comprehensive Genomic Profiling Identifies Novel Genetic Predictors of Response to Anti–PD-(L)1 Therapies in Non–Small Cell Lung Cancer. Clinical Cancer Research. 25(16). 5015–5026. 139 indexed citations
20.
Zhou, Yixin, Chen Chen, Xuanye Zhang, et al.. (2018). Immune-checkpoint inhibitor plus chemotherapy versus conventional chemotherapy for first-line treatment in advanced non-small cell lung carcinoma: a systematic review and meta-analysis. Journal for ImmunoTherapy of Cancer. 6(1). 155–155. 82 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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