Fengdong Cheng

3.4k total citations
53 papers, 2.5k citations indexed

About

Fengdong Cheng is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Fengdong Cheng has authored 53 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 26 papers in Immunology and 18 papers in Oncology. Recurrent topics in Fengdong Cheng's work include Histone Deacetylase Inhibitors Research (33 papers), Protein Degradation and Inhibitors (16 papers) and Immunotherapy and Immune Responses (13 papers). Fengdong Cheng is often cited by papers focused on Histone Deacetylase Inhibitors Research (33 papers), Protein Degradation and Inhibitors (16 papers) and Immunotherapy and Immune Responses (13 papers). Fengdong Cheng collaborates with scholars based in United States, China and Czechia. Fengdong Cheng's co-authors include Eduardo M. Sotomayor, Alejandro Villagra, Dmitry I. Gabrilovich, Javier Pinilla‐Ibarz, Edward Seto, Yulia Nefedova, Sergei Kusmartsev, Bin Yu, Jason Brayer and Richard M. Lush and has published in prestigious journals such as Journal of Clinical Investigation, Journal of Clinical Oncology and Blood.

In The Last Decade

Fengdong Cheng

53 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fengdong Cheng United States 22 1.3k 1.3k 1.1k 148 137 53 2.5k
Tomohisa Baba Japan 26 865 0.6× 597 0.5× 756 0.7× 180 1.2× 99 0.7× 54 1.8k
Jonathan S. Maltzman United States 25 1.8k 1.4× 765 0.6× 789 0.7× 137 0.9× 183 1.3× 60 3.0k
Mengkun Zhang United States 13 524 0.4× 728 0.6× 677 0.6× 147 1.0× 125 0.9× 24 1.8k
Seijiro Minamoto Japan 17 1.5k 1.1× 694 0.5× 1.4k 1.3× 315 2.1× 130 0.9× 30 2.6k
Michal Shahar Israel 7 976 0.7× 590 0.5× 684 0.6× 117 0.8× 150 1.1× 13 1.8k
Gary C. Starling United States 28 1.6k 1.2× 894 0.7× 658 0.6× 167 1.1× 417 3.0× 59 2.6k
Helena Harlin United States 16 1.6k 1.2× 742 0.6× 1.3k 1.3× 185 1.3× 76 0.6× 25 2.4k
Cinzia Fionda Italy 28 1.8k 1.4× 805 0.6× 914 0.9× 260 1.8× 405 3.0× 62 2.7k

Countries citing papers authored by Fengdong Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Fengdong Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fengdong Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of Fengdong Cheng. A scholar is included among the top collaborators of Fengdong Cheng 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 Fengdong Cheng. Fengdong Cheng 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, Ya, Xuefeng Wu, Kai Yan, et al.. (2019). Secretome profiling identifies neuron-derived neurotrophic factor as a tumor-suppressive factor in lung cancer. JCI Insight. 4(24). 20 indexed citations
2.
3.
Sun, Lei, Molly Karl, Fengdong Cheng, et al.. (2018). Loss of HDAC11 ameliorates clinical symptoms in a multiple sclerosis mouse model. Life Science Alliance. 1(5). e201800039–e201800039. 34 indexed citations
4.
Wang, Michael, Fengdong Cheng, Jie Chen, et al.. (2017). A Novel Role for Histone Deacetylase 10 (HDAC10) in the Regulation of PD-L1 Expression and Immune Tolerance Mediated By Antigen Presenting Cells (APCs). Blood. 130. 3561–3561. 2 indexed citations
5.
Lienlaf, Maritza, Patricio Perez-Villarroel, Tessa Knox, et al.. (2016). Essential role of HDAC6 in the regulation of PD‐L1 in melanoma. Molecular Oncology. 10(5). 735–750. 136 indexed citations
6.
Sahakian, Eva, John J. Powers, Jie Chen, et al.. (2014). Histone deacetylase 11: A novel epigenetic regulator of myeloid derived suppressor cell expansion and function. Molecular Immunology. 63(2). 579–585. 96 indexed citations
7.
Chen, Jie, Eva Sahakian, John J. Powers, et al.. (2014). Histone Deacetylase 11 (HDAC11) As a Novel Transcriptional Regulator of C/EBP-β, in Immature Myeloid Cell to Myeloid Derived Suppressor Cell Transition. Blood. 124(21). 225–225. 1 indexed citations
8.
Lienlaf, Maritza, Patricio Perez-Villarroel, Calvin Lee, et al.. (2014). Abstract 4089: Histone deacetylase 6 (HDAC6) as a regulator of PD-L1 expression through STAT3 modulation in melanoma. Cancer Research. 74(19_Supplement). 4089–4089. 1 indexed citations
9.
Cheng, Fengdong, Maritza Lienlaf, Patricio Perez-Villarroel, et al.. (2014). Divergent roles of histone deacetylase 6 (HDAC6) and histone deacetylase 11 (HDAC11) on the transcriptional regulation of IL10 in antigen presenting cells. Molecular Immunology. 60(1). 44–53. 113 indexed citations
10.
Woods, David, Karrune Woan, Fengdong Cheng, et al.. (2013). The antimelanoma activity of the histone deacetylase inhibitor panobinostat (LBH589) is mediated by direct tumor cytotoxicity and increased tumor immunogenicity. Melanoma Research. 23(5). 341–348. 81 indexed citations
11.
Lwin, Tint, Xiaohong Zhao, Fengdong Cheng, et al.. (2013). A microenvironment-mediated c-Myc/miR-548m/HDAC6 amplification loop in non-Hodgkin B cell lymphomas. Journal of Clinical Investigation. 123(11). 4612–4626. 59 indexed citations
12.
Cheng, Fengdong, Hongwei Wang, Pedro Horna, et al.. (2012). Stat3 Inhibition Augments the Immunogenicity of B-cell Lymphoma Cells, Leading to Effective Antitumor Immunity. Cancer Research. 72(17). 4440–4448. 15 indexed citations
13.
Sahakian, Eva, John J. Powers, Jennifer Rock-Klotz, et al.. (2011). A Novel Role of Histone Deacetylase 11 (HDAC11) in Regulation of Myeloid-Derived Suppressor Cell (MDSC) Expansion. Blood. 118(21). 2439–2439. 1 indexed citations
14.
Brayer, Jason, Fengdong Cheng, Hongwei Wang, et al.. (2010). Enhanced CD8 T cell cross-presentation by macrophages with targeted disruption of STAT3. Immunology Letters. 131(2). 126–130. 16 indexed citations
15.
16.
Villagra, Alejandro, Fengdong Cheng, Hongwei Wang, et al.. (2008). The histone deacetylase HDAC11 regulates the expression of interleukin 10 and immune tolerance. Nature Immunology. 10(1). 92–100. 355 indexed citations
17.
Takahashi, Yoshinori, et al.. (2007). Identification of a novel negative role of flagellin in regulating IL‐10 production. European Journal of Immunology. 37(11). 3164–3175. 25 indexed citations
18.
Ghansah, Tomar, Kim H.T. Paraiso, Steven L. Highfill, et al.. (2004). Expansion of Myeloid Suppressor Cells in SHIP-Deficient Mice Represses Allogeneic T Cell Responses. The Journal of Immunology. 173(12). 7324–7330. 87 indexed citations
19.
Cheng, Fengdong, Hongwei Wang, Alex G. Cuenca, et al.. (2003). A Critical Role for Stat3 Signaling in Immune Tolerance. Immunity. 19(3). 425–436. 293 indexed citations
20.
Burdelya, Lyudmila G., Robyn Catlett-Falcone, Alexander Levitzki, et al.. (2002). Combination therapy with AG-490 and interleukin 12 achieves greater antitumor effects than either agent alone.. PubMed. 1(11). 893–9. 40 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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