John G. Facciponte

877 total citations
17 papers, 718 citations indexed

About

John G. Facciponte is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, John G. Facciponte has authored 17 papers receiving a total of 718 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 12 papers in Immunology and 4 papers in Oncology. Recurrent topics in John G. Facciponte's work include Heat shock proteins research (8 papers), Immunotherapy and Immune Responses (5 papers) and Endoplasmic Reticulum Stress and Disease (4 papers). John G. Facciponte is often cited by papers focused on Heat shock proteins research (8 papers), Immunotherapy and Immune Responses (5 papers) and Endoplasmic Reticulum Stress and Disease (4 papers). John G. Facciponte collaborates with scholars based in United States, Italy and Russia. John G. Facciponte's co-authors include John R. Subjeck, Andrea Facciabene, Francesco De Sanctis, Xiangyang Wang, Stefano Ugel, Elizabeth A. Repasky, Masoud H. Manjili, Xiang‐Yang Wang, Min Jin and Qianjun Zhou and has published in prestigious journals such as Journal of Clinical Investigation, The Journal of Immunology and Cancer Research.

In The Last Decade

John G. Facciponte

17 papers receiving 709 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John G. Facciponte United States 17 407 393 236 112 81 17 718
Anne Walter Australia 10 328 0.8× 503 1.3× 311 1.3× 112 1.0× 60 0.7× 12 893
Nancy D. Ebelt United States 15 386 0.9× 219 0.6× 335 1.4× 86 0.8× 91 1.1× 22 773
Dahlia M. Besmer United States 11 397 1.0× 213 0.5× 317 1.3× 48 0.4× 111 1.4× 14 679
Melissa Wassink Netherlands 13 453 1.1× 435 1.1× 184 0.8× 42 0.4× 75 0.9× 16 828
Fengshu Zhao China 19 412 1.0× 365 0.9× 456 1.9× 63 0.6× 196 2.4× 49 872
Caitlyn L. Miller United States 8 601 1.5× 224 0.6× 265 1.1× 68 0.6× 29 0.4× 9 824
Deanna M. Janzen United States 12 520 1.3× 131 0.3× 257 1.1× 68 0.6× 81 1.0× 21 863
Walid Awad United States 9 437 1.1× 586 1.5× 405 1.7× 158 1.4× 107 1.3× 12 1.1k
Łukasz P. Biały Poland 10 469 1.2× 223 0.6× 141 0.6× 108 1.0× 51 0.6× 17 743
Kanstantsin V. Katlinski United States 10 276 0.7× 429 1.1× 254 1.1× 65 0.6× 92 1.1× 14 723

Countries citing papers authored by John G. Facciponte

Since Specialization
Citations

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

Fields of papers citing papers by John G. Facciponte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John G. Facciponte. 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 John G. Facciponte. The network helps show where John G. Facciponte may publish in the future.

Co-authorship network of co-authors of John G. Facciponte

This figure shows the co-authorship network connecting the top 25 collaborators of John G. Facciponte. A scholar is included among the top collaborators of John G. Facciponte 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 John G. Facciponte. John G. Facciponte is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Pierini, Stefano, Abhishek Mishra, Renzo Perales‐Linares, et al.. (2021). Combination of vasculature targeting, hypofractionated radiotherapy, and immune checkpoint inhibitor elicits potent antitumor immune response and blocks tumor progression. Journal for ImmunoTherapy of Cancer. 9(2). e001636–e001636. 25 indexed citations
2.
Sanctis, Francesco De, Stefano Ugel, John G. Facciponte, & Andrea Facciabene. (2018). The dark side of tumor-associated endothelial cells. Seminars in Immunology. 35. 35–47. 93 indexed citations
3.
Facciabene, Andrea, Francesco De Sanctis, Stefano Pierini, et al.. (2017). Local endothelial complement activation reverses endothelial quiescence, enabling t-cell homing, and tumor control during t-cell immunotherapy. OncoImmunology. 6(9). e1326442–e1326442. 56 indexed citations
4.
Pierini, Stefano, Chongyun Fang, Stavros Rafail, et al.. (2015). A Tumor Mitochondria Vaccine Protects against Experimental Renal Cell Carcinoma. The Journal of Immunology. 195(8). 4020–4027. 29 indexed citations
5.
Ugel, Stefano, John G. Facciponte, Francesco De Sanctis, & Andrea Facciabene. (2015). Targeting tumor vasculature: expanding the potential of DNA cancer vaccines. Cancer Immunology Immunotherapy. 64(10). 1339–1348. 24 indexed citations
6.
Facciponte, John G., Stefano Ugel, Francesco De Sanctis, et al.. (2014). Tumor endothelial marker 1–specific DNA vaccination targets tumor vasculature. Journal of Clinical Investigation. 124(4). 1497–1511. 59 indexed citations
7.
Zhou, Qianjun, John G. Facciponte, Min Jin, Qiang Shen, & Qiang Lin. (2013). Humanized NOD-SCID IL2rg –/– mice as a preclinical model for cancer research and its potential use for individualized cancer therapies. Cancer Letters. 344(1). 13–19. 74 indexed citations
8.
Yokota, Sandra J., John G. Facciponte, Raymond J. Kelleher, et al.. (2013). Changes in ovarian tumor cell number, tumor vasculature, and T cell function monitored in vivo using a novel xenograft model.. PubMed. 13. 11–11. 20 indexed citations
9.
Wang, Xiang‐Yang, Xiaolei Sun, Xing Chen, et al.. (2010). Superior Antitumor Response Induced by Large Stress Protein Chaperoned Protein Antigen Compared with Peptide Antigen. The Journal of Immunology. 184(11). 6309–6319. 44 indexed citations
10.
Facciponte, John G., Xiangyang Wang, & John R. Subjeck. (2007). Hsp110 and Grp170, members of the Hsp70 superfamily, bind to scavenger receptor‐A and scavenger receptor expressed by endothelial cells‐I. European Journal of Immunology. 37(8). 2268–2279. 62 indexed citations
11.
Wang, Xiang‐Yang, John G. Facciponte, Xing Chen, John R. Subjeck, & Elizabeth A. Repasky. (2007). Scavenger Receptor-A Negatively Regulates Antitumor Immunity. Cancer Research. 67(10). 4996–5002. 65 indexed citations
12.
Facciponte, John G., Xing Chen, Ian J. MacDonald, et al.. (2006). Chaperoning Function of Stress Protein grp170, a Member of the hsp70 Superfamily, Is Responsible for its Immunoadjuvant Activity. Cancer Research. 66(2). 1161–1168. 48 indexed citations
13.
Manjili, Masoud H., et al.. (2006). Immunoadjuvant chaperone, GRP170, induces ‘danger signals’ upon interaction with dendritic cells. Immunology and Cell Biology. 84(2). 203–208. 23 indexed citations
14.
Manjili, Masoud H., et al.. (2005). HSP110 induces “danger signals” upon interaction with antigen presenting cells and mouse mammary carcinoma. Immunobiology. 210(5). 295–303. 33 indexed citations
15.
Facciponte, John G., Xiangyang Wang, Ian J. MacDonald, et al.. (2005). Heat shock proteins HSP70 and GP96: structural insights. Cancer Immunology Immunotherapy. 55(3). 339–346. 18 indexed citations
16.
Facciponte, John G., et al.. (2005). Molecular Chaperones and Cancer Immunotherapy. Handbook of experimental pharmacology. 305–329. 20 indexed citations
17.
Facciponte, John G., Ian J. MacDonald, Xiangyang Wang, et al.. (2005). Heat Shock Proteins and Scavenger Receptors: Role in Adaptive Immune Responses. Immunological Investigations. 34(3). 325–342. 25 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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