Peter Kufer

11.7k total citations · 1 hit paper
113 papers, 7.5k citations indexed

About

Peter Kufer is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Immunology. According to data from OpenAlex, Peter Kufer has authored 113 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Radiology, Nuclear Medicine and Imaging, 74 papers in Oncology and 50 papers in Immunology. Recurrent topics in Peter Kufer's work include Monoclonal and Polyclonal Antibodies Research (81 papers), CAR-T cell therapy research (63 papers) and Immunotherapy and Immune Responses (29 papers). Peter Kufer is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (81 papers), CAR-T cell therapy research (63 papers) and Immunotherapy and Immune Responses (29 papers). Peter Kufer collaborates with scholars based in Germany, United States and Switzerland. Peter Kufer's co-authors include Patrick A. Baeuerle, Ralf C. Bargou, Gert Riethmüller, G. Riethmüller, Ralf Lutterbüse, Bernd Schlereth, Robert Hofmeister, Gerhard Zugmaier, Christian Brandl and Matthias Mack and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Clinical Oncology.

In The Last Decade

Peter Kufer

111 papers receiving 7.1k citations

Hit Papers

align trajectories

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.

Tumor Regression in Cancer Patients by Very Low Doses of a T Cell–Engaging Antibody

2008 798 citations Ralf C. Bargou, Eugen Leo et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Peter Kufer Germany	46	5.1k	3.6k	3.0k	2.2k	782	113	7.5k
Daniel A. Vallera United States	52	3.1k 0.6×	1.2k 0.3×	5.3k 1.7×	1.7k 0.7×	194 0.2×	203	8.0k
Dirk Nagorsen United States	33	2.7k 0.5×	711 0.2×	2.3k 0.8×	961 0.4×	682 0.9×	88	4.4k
Debra K. Czerwinski United States	34	3.5k 0.7×	1.1k 0.3×	5.2k 1.7×	2.2k 1.0×	1.5k 1.9×	102	7.6k
Dorothee Herlyn United States	46	3.3k 0.6×	3.8k 1.1×	3.2k 1.1×	3.9k 1.8×	320 0.4×	154	8.4k
Pablo Umaña Switzerland	32	1.8k 0.4×	2.7k 0.7×	2.3k 0.7×	2.4k 1.1×	765 1.0×	119	5.2k
Frédéric Triebel France	54	5.2k 1.0×	679 0.2×	7.0k 2.3×	1.1k 0.5×	479 0.6×	167	9.2k
Stephen Gottschalk United States	64	9.4k 1.8×	397 0.1×	4.7k 1.5×	3.0k 1.3×	1.1k 1.4×	256	12.2k
Bryan Irving United States	20	4.1k 0.8×	917 0.3×	5.5k 1.8×	1.7k 0.8×	322 0.4×	44	7.8k
Roch Houot France	38	2.7k 0.5×	462 0.1×	1.9k 0.6×	645 0.3×	1.5k 1.9×	181	4.3k
Maurizio Bendandi Italy	41	1.9k 0.4×	578 0.2×	1.9k 0.6×	1.0k 0.5×	2.4k 3.0×	112	4.7k

Countries citing papers authored by Peter Kufer

Since Specialization

Citations

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

Fields of papers citing papers by Peter Kufer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Kufer

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

All Works

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20 of 20 papers shown

Deegen, Petra, Oliver S. Thomas, Olivier Nolan-Stevaux, et al.. (2021). The PSMA-targeting Half-life Extended BiTE Therapy AMG 160 has Potent Antitumor Activity in Preclinical Models of Metastatic Castration-resistant Prostate Cancer. Clinical Cancer Research. 27(10). 2928–2937. 58 indexed citations

Klinger, Matthias, Gerhard Zugmaier, Maria-Elisabeth Goebeler, et al.. (2019). Adhesion of T Cells to Endothelial Cells Facilitates Blinatumomab-Associated Neurologic Adverse Events. Cancer Research. 80(1). 91–101. 51 indexed citations

Sienel, Wulf, et al.. (2016). A Threshold of Systemic MAGE-A Gene Expression Predicting Survival in Resected Non–Small Cell Lung Cancer. Clinical Cancer Research. 23(5). 1213–1219. 17 indexed citations

Friedrich, Matthias, Anja Henn, Tobias Raum, et al.. (2014). Preclinical Characterization of AMG 330, a CD3/CD33-Bispecific T-Cell–Engaging Antibody with Potential for Treatment of Acute Myelogenous Leukemia. Molecular Cancer Therapeutics. 13(6). 1549–1557. 106 indexed citations

Aigner, Michael, Julian Feulner, Stefanie Schaffer, et al.. (2012). T lymphocytes can be effectively recruited for ex vivo and in vivo lysis of AML blasts by a novel CD33/CD3-bispecific BiTE antibody construct. Leukemia. 27(5). 1107–1115. 101 indexed citations

Hausmann, Susanne, et al.. (2010). Epitope distance to the target cell membrane and antigen size determine the potency of T cell-mediated lysis by BiTE antibodies specific for a large melanoma surface antigen. Cancer Immunology Immunotherapy. 59(8). 1197–1209. 162 indexed citations

Haas, Cornelia, Klaus Brischwein, Patrick Hoffmann, et al.. (2009). Mode of cytotoxic action of T cell-engaging BiTE antibody MT110. Immunobiology. 214(6). 441–453. 144 indexed citations

Kischel, Roman, Susanne Hausmann, Patrick A. Baeuerle, & Peter Kufer. (2009). Abstract #3252: Effector memory T cells make a major contribution to redirected target cell lysis by T cell-engaging BiTE antibody MT110. Cancer Research. 69. 3252–3252. 14 indexed citations

Amann, Maria, Grit Lorenczewski, Klaus Brischwein, et al.. (2009). Antitumor Activity of an EpCAM/CD3-bispecific BiTE Antibody During Long-term Treatment of Mice in the Absence of T-cell Anergy and Sustained Cytokine Release. Journal of Immunotherapy. 32(5). 452–464. 43 indexed citations

10.

Mulgrew, Kathy, David J. Stewart, Wendy L. Trigona, et al.. (2008). Bioavailability, pharmacodynamic activity, and anti-tumor efficacy of the CD19/CD3-specific BiTE antibody MEDI-538 (MT103) delivered subcutaneously in animal models. Cancer Research. 68. 2131–2131. 2 indexed citations

11.

Brandl, Christian, Nadja Prang, Ralf Lutterbuese, et al.. (2008). Combination of rituximab with blinatumomab (MT103/MEDI-538), a T cell-engaging CD19-/CD3-bispecific antibody, for highly efficient lysis of human B lymphoma cells. Leukemia Research. 33(3). 465–473. 58 indexed citations

12.

Hammond, Scott A., Ralf Lutterbuese, Shannon Roff, et al.. (2007). Selective Targeting and Potent Control of Tumor Growth Using an EphA2/CD3-Bispecific Single-Chain Antibody Construct. Cancer Research. 67(8). 3927–3935. 66 indexed citations

13.

Baeuerle, Patrick A., Maria Amann, Klaus Brischwein, et al.. (2007). Therapeutic window of MuS110, a single-chain antibody construct bispecific for EpCAM (CD326) and CD3. Molecular Cancer Therapeutics. 6. 3 indexed citations

14.

Mack, Matthias, Jochen Pfirstinger, Jürgen Haas, et al.. (2005). Preferential Targeting of CD4-CCR5 Complexes with Bifunctional Inhibitors: A Novel Approach to Block HIV-1 Infection. The Journal of Immunology. 175(11). 7586–7593. 8 indexed citations

15.

Schlereth, Bernd, Cornelia Quadt, Torsten Dreier, et al.. (2005). T-cell activation and B-cell depletion in chimpanzees treated with a bispecific anti-CD19/anti-CD3 single-chain antibody construct. Cancer Immunology Immunotherapy. 55(5). 503–514. 77 indexed citations

16.

Offner, Sonja, Armin Hekele, Ulrike Teichmann, et al.. (2004). Epithelial tight junction proteins as potential antibody targets for pancarcinoma therapy. Cancer Immunology Immunotherapy. 54(5). 431–445. 54 indexed citations

17.

Dreier, Torsten, Patrick A. Baeuerle, Iduna Fichtner, et al.. (2003). T Cell Costimulus-Independent and Very Efficacious Inhibition of Tumor Growth in Mice Bearing Subcutaneous or Leukemic Human B Cell Lymphoma Xenografts by a CD19-/CD3- Bispecific Single-Chain Antibody Construct. The Journal of Immunology. 170(8). 4397–4402. 155 indexed citations

18.

Flieger, Dimitri, Peter Kufer, Imke Beier, Tilman Sauerbruch, & Ingo G.H. Schmidt‐Wolf. (2000). A bispecific single-chain antibody directed against EpCAM/CD3 in combination with the cytokines interferon α and interleukin-2 efficiently retargets T and CD3 + CD56 + natural-killer-like T lymphocytes to EpCAM-expressing tumor cells. Cancer Immunology Immunotherapy. 49(8). 441–448. 16 indexed citations

19.

Kufer, Peter, Matthias Mack, Rudolf Gruber, et al.. (1997). Construction and biological activity of a recombinant bispecific single-chain antibody designed for therapy of minimal residual colorectal cancer. Cancer Immunology Immunotherapy. 45(3-4). 193–197. 37 indexed citations

20.

Orlikowsky, Thorsten, et al.. (1996). AIDS Patient Monocytes Target CD4 T Cells for Cellular Conjugate Formation and Deletion through the Membrane Expression of HIV-1 Envelope Molecules. AIDS Research and Human Retroviruses. 12(10). 893–899. 18 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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