Zhong‐Yi Dong

4.3k total citations · 2 hit papers
73 papers, 3.0k citations indexed

About

Zhong‐Yi Dong is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Zhong‐Yi Dong has authored 73 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Oncology, 35 papers in Pulmonary and Respiratory Medicine and 20 papers in Cancer Research. Recurrent topics in Zhong‐Yi Dong's work include Cancer Immunotherapy and Biomarkers (30 papers), Lung Cancer Treatments and Mutations (27 papers) and Cancer Genomics and Diagnostics (14 papers). Zhong‐Yi Dong is often cited by papers focused on Cancer Immunotherapy and Biomarkers (30 papers), Lung Cancer Treatments and Mutations (27 papers) and Cancer Genomics and Diagnostics (14 papers). Zhong‐Yi Dong collaborates with scholars based in China, United States and Germany. Zhong‐Yi Dong's co-authors include Yi‐Long Wu, Wen‐Zhao Zhong, Jian Su, Li‐Xu Yan, Zhi Xie, Qing Zhou, Hai‐Yan Tu, Si‐Yang Maggie Liu, Dehua Wu and Li Liu and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Advanced Functional Materials.

In The Last Decade

Zhong‐Yi Dong

67 papers receiving 3.0k citations

Hit Papers

Potential Predictive Value of TP53 and KRAS Mutation Stat... 2016 2026 2019 2022 2016 2017 200 400 600

Peers

Zhong‐Yi Dong
Davey B. Daniel United States
Joshua K. Sabari United States
Marleen Kok Netherlands
V.A. Miller United States
Liza C. Villaruz United States
Davey B. Daniel United States
Zhong‐Yi Dong
Citations per year, relative to Zhong‐Yi Dong Zhong‐Yi Dong (= 1×) peers Davey B. Daniel

Countries citing papers authored by Zhong‐Yi Dong

Since Specialization
Citations

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

Fields of papers citing papers by Zhong‐Yi Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhong‐Yi Dong. 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 Zhong‐Yi Dong. The network helps show where Zhong‐Yi Dong may publish in the future.

Co-authorship network of co-authors of Zhong‐Yi Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Zhong‐Yi Dong. A scholar is included among the top collaborators of Zhong‐Yi Dong 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 Zhong‐Yi Dong. Zhong‐Yi Dong 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.
Zhang, Jinhui, Zhong‐Yi Dong, Yang Fu, et al.. (2025). Silver niobate/platinum piezoelectric heterojunction enhancing intra-tumoral infiltration of immune cells for transforming “cold tumor” into “hot tumor”. Journal of Colloid and Interface Science. 690. 137303–137303. 2 indexed citations
2.
Deng, Yi, Zhong‐Yi Dong, Gong Yang, et al.. (2025). Streptococcus intermedius promotes synchronous multiple primary lung cancer progression through apoptosis regulation. Frontiers in Immunology. 15. 1482084–1482084. 3 indexed citations
3.
4.
Zhang, Yan-Pei, et al.. (2024). Regular Use of Aspirin and Statins Reduces the Risk of Cancer in Individuals with Systemic Inflammatory Diseases. Cancer Research. 84(11). 1889–1897. 8 indexed citations
5.
Geng, Haigang, Chen Huang, Lei Xu, et al.. (2024). Targeting cellular senescence as a therapeutic vulnerability in gastric cancer. Life Sciences. 346. 122631–122631. 4 indexed citations
6.
Bai, Xue, Ze-Qin Guo, Yan-Pei Zhang, et al.. (2023). CDK4/6 inhibition triggers ICAM1-driven immune response and sensitizes LKB1 mutant lung cancer to immunotherapy. Nature Communications. 14(1). 1247–1247. 35 indexed citations
7.
Ma, Si-Cong, Ze-Qin Guo, Yan-Pei Zhang, et al.. (2022). PARP Inhibition Induces Synthetic Lethality and Adaptive Immunity in LKB1-Mutant Lung Cancer. Cancer Research. 83(4). 568–581. 19 indexed citations
8.
Xiao, Lushan, Qimei Li, Hao Cui, et al.. (2021). Lung metastasis and lymph node metastasis are risk factors for hyperprogressive disease in primary liver cancer patients treated with immune checkpoint inhibitors. Annals of Palliative Medicine. 10(11). 11244–11254. 10 indexed citations
9.
Liu, Li, Xue Bai, Jian Wang, et al.. (2019). Combination of TMB and CNA Stratifies Prognostic and Predictive Responses to Immunotherapy Across Metastatic Cancer. Clinical Cancer Research. 25(24). 7413–7423. 233 indexed citations
10.
Tang, Wen‐Fang, Junxin Lin, Zhong‐Yi Dong, et al.. (2019). P1.01-81 A New Prognostic Index Combines the Metabolic Response and RECIST 1.1 to Evaluate the Therapeutic Response in Patients with Lung Cancer. Journal of Thoracic Oncology. 14(10). S391–S391. 1 indexed citations
11.
Wang, Jian, Hao Sun, Qin Zeng, et al.. (2019). HPV-positive status associated with inflamed immune microenvironment and improved response to anti-PD-1 therapy in head and neck squamous cell carcinoma. Scientific Reports. 9(1). 13404–13404. 117 indexed citations
12.
Peng, Jie, Lushan Xiao, Zhong‐Yi Dong, et al.. (2018). Potential predictive value of JAK2 expression for Pan-cancer response to PD-1 blockade immunotherapy. Translational Cancer Research. 7(3). 462–471. 2 indexed citations
13.
Zhang, Qi, Xu‐Chao Zhang, Jin‐Ji Yang, et al.. (2018). EGFR L792H and G796R: Two Novel Mutations Mediating Resistance to the Third-Generation EGFR Tyrosine Kinase Inhibitor Osimertinib. Journal of Thoracic Oncology. 13(9). 1415–1421. 56 indexed citations
14.
Su, Shan, Zhong‐Yi Dong, Jian Su, et al.. (2018). MA15.01 Strong PD-L1 Expression Predicts Poor Response and de Novo Resistance to EGFR TKIs Among Non-Small Cell Lung Cancer Patients with EGFR Mutation. Journal of Thoracic Oncology. 13(10). S407–S407.
15.
Su, Shan, Zhong‐Yi Dong, Zhi Xie, et al.. (2018). Strong Programmed Death Ligand 1 Expression Predicts Poor Response and De Novo Resistance to EGFR Tyrosine Kinase Inhibitors Among NSCLC Patients With EGFR Mutation. Journal of Thoracic Oncology. 13(11). 1668–1675. 101 indexed citations
16.
Han, Jiefei, Qiuyi Zhang, Qing Zhou, et al.. (2017). P3.02b-116 Molecular Mechanism of Transformation from Adenocarcinoma to Small-Cell Lung Cancer after EGFR-TKI. Journal of Thoracic Oncology. 12(1). S1263–S1264. 1 indexed citations
17.
Huang, Shu‐Mei, Si-Pei Wu, Ri-Qiang Liao, et al.. (2017). P2.03b-043 Peripheral Blood CD45RA+ CCR7+ Naive T Cells Were Correlated with Prognosis in Non-Small Cell Lung Cancer Patients. Journal of Thoracic Oncology. 12(1). S961–S962. 1 indexed citations
18.
Zhang, Yichen, E‐E Ke, Zhihong Chen, et al.. (2017). P3.02b-095 Tracing Spatiotemporal T790M Heterogeneity in Patients with EGFR-Mutant Advanced NSCLC after Acquired Resistance to EGFR TKIs. Journal of Thoracic Oncology. 12(1). S1249–S1249.
19.
20.
Dong, Zhong‐Yi, Wen‐Zhao Zhong, Xu‐Chao Zhang, et al.. (2016). Potential Predictive Value of TP53 and KRAS Mutation Status for Response to PD-1 Blockade Immunotherapy in Lung Adenocarcinoma. Clinical Cancer Research. 23(12). 3012–3024. 741 indexed citations breakdown →

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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