Bryan Irving

9.9k total citations · 9 hit papers
44 papers, 7.8k citations indexed

About

Bryan Irving is a scholar working on Oncology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Bryan Irving has authored 44 papers receiving a total of 7.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Oncology, 26 papers in Immunology and 23 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Bryan Irving's work include Monoclonal and Polyclonal Antibodies Research (23 papers), CAR-T cell therapy research (18 papers) and Immune Cell Function and Interaction (13 papers). Bryan Irving is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (23 papers), CAR-T cell therapy research (18 papers) and Immune Cell Function and Interaction (13 papers). Bryan Irving collaborates with scholars based in United States, France and Singapore. Bryan Irving's co-authors include Arthur Weiss, Andrew C. Chan, James D. Fraser, Jane L. Grogan, Daniel S. Chen, F. Stephen Hodi, Xin Yu, Dan Eaton, Gerald R. Crabtree and Nicolai S. C. van Oers and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Bryan Irving

44 papers receiving 7.7k citations

Hit Papers

The surface protein TIGIT suppresses T cell... 1990 2026 2002 2014 2008 2014 1991 1994 1991 250 500 750 1000
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.

  1. The surface protein TIGIT suppresses T cell activation by promoting the generation of mature immunoregulatory dendritic cells
    2008 1.1k citations Xin Yu, Lino C. Gonzalez et al. Nature Immunology profile →
  2. The Immunoreceptor TIGIT Regulates Antitumor and Antiviral CD8 + T Cell Effector Function
    2014 893 citations Robert J. Johnston, Laëtitia Comps‐Agrar et al. Cancer Cell profile →
  3. The cytoplasmic domain of the T cell receptor ζ chain is sufficient to couple to receptor-associated signal transduction pathways
    1991 703 citations Bryan Irving, Arthur Weiss profile →
  4. Sequential Interactions of the TCR with Two Distinct Cytoplasmic Tyrosine Kinases
    1994 623 citations Makio Iwashima, Bryan Irving et al. Science profile →
  5. Regulation of Interleukin-2 Gene Enhancer Activity by the T Cell Accessory Molecule CD28
    1991 560 citations Bryan Irving, Arthur Weiss et al. Science profile →
  6. Interaction of the unique N-terminal region of tyrosine kinase p56lck with cytoplasmic domains of CD4 and CD8 is mediated by cysteine motifs
    1990 552 citations Bryan Irving et al. profile →
  7. MAP Kinase Inhibition Promotes T Cell and Anti-tumor Activity in Combination with PD-L1 Checkpoint Blockade
    2016 527 citations Jeanne Cheung, Yagai Yang et al. profile →
  8. Molecular Pathways: Next-Generation Immunotherapy—Inhibiting Programmed Death-Ligand 1 and Programmed Death-1
    2012 496 citations Daniel S. Chen, Bryan Irving et al. Clinical Cancer Research profile →
  9. Bruton Tyrosine Kinase–Dependent Immune Cell Cross-talk Drives Pancreas Cancer
    2015 381 citations Andrew J. Gunderson, Megan M. Kaneda et al. Cancer Discovery profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bryan Irving United States 20 5.5k 4.1k 1.7k 917 469 44 7.8k
Michael Yellin United States 38 5.2k 0.9× 4.7k 1.1× 1.6k 0.9× 601 0.7× 543 1.2× 112 8.2k
Emma Di Carlo Italy 45 4.0k 0.7× 2.9k 0.7× 1.8k 1.0× 715 0.8× 401 0.9× 125 6.1k
Danielle Líénard Switzerland 47 5.3k 1.0× 3.3k 0.8× 2.4k 1.4× 394 0.4× 492 1.0× 89 7.1k
Marina Fabbi Italy 36 3.5k 0.6× 1.5k 0.4× 1.2k 0.7× 929 1.0× 216 0.5× 93 5.2k
Fathia Mami‐Chouaib France 47 4.8k 0.9× 3.7k 0.9× 2.2k 1.3× 219 0.2× 542 1.2× 107 7.9k
Arko Gorter Netherlands 40 2.2k 0.4× 1.5k 0.4× 1.4k 0.8× 698 0.8× 282 0.6× 82 4.1k
J A Ledbetter United States 32 6.1k 1.1× 1.9k 0.5× 1.5k 0.9× 1.1k 1.2× 182 0.4× 41 7.7k
Carla De Giovanni Italy 39 2.0k 0.4× 1.8k 0.4× 2.1k 1.2× 677 0.7× 718 1.5× 149 4.7k
Hassane M. Zarour United States 41 5.2k 1.0× 5.6k 1.4× 1.9k 1.1× 306 0.3× 688 1.5× 104 8.0k
Roberta Mortarini Italy 40 2.9k 0.5× 2.0k 0.5× 2.1k 1.2× 341 0.4× 246 0.5× 100 4.9k

Countries citing papers authored by Bryan Irving

Since Specialization
Citations

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

Fields of papers citing papers by Bryan Irving

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bryan Irving

This figure shows the co-authorship network connecting the top 25 collaborators of Bryan Irving. A scholar is included among the top collaborators of Bryan Irving 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 Bryan Irving. Bryan Irving 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.
Boustany, Leila M., Sherry L. LaPorte, Joel Shen, et al.. (2022). A Probody T Cell–Engaging Bispecific Antibody Targeting EGFR and CD3 Inhibits Colon Cancer Growth with Limited Toxicity. Cancer Research. 82(22). 4288–4298. 35 indexed citations
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Lau, Janet, Jeanne Cheung, Armando Navarro, et al.. (2017). Tumour and host cell PD-L1 is required to mediate suppression of anti-tumour immunity in mice. Nature Communications. 8(1). 14572–14572. 270 indexed citations
6.
Gunderson, Andrew J., Megan M. Kaneda, Takahiro Tsujikawa, et al.. (2015). Bruton Tyrosine Kinase–Dependent Immune Cell Cross-talk Drives Pancreas Cancer. Cancer Discovery. 6(3). 270–285. 381 indexed citations breakdown →
7.
Johnston, Robert J., Laëtitia Comps‐Agrar, Jason A. Hackney, et al.. (2014). The Immunoreceptor TIGIT Regulates Antitumor and Antiviral CD8 + T Cell Effector Function. Cancer Cell. 26(6). 923–937. 893 indexed citations breakdown →
8.
Affara, Nesrine I., Brian Ruffell, Terry R. Medler, et al.. (2014). B Cells Regulate Macrophage Phenotype and Response to Chemotherapy in Squamous Carcinomas. Cancer Cell. 25(6). 809–821. 232 indexed citations
9.
Iwashima, Makio, Bryan Irving, Nicolai S. C. van Oers, Andrew C. Chan, & Arthur Weiss. (2014). Pillars article: Sequential interactions of the TCR with two distinct cytoplasmic tyrosine kinases. Science. 1994. 263: 1136-1139.. PubMed. 193(9). 4279–82. 2 indexed citations
10.
Gordon, Michael S., Omid Hamid, John D. Powderly, et al.. (2013). Abstract LB-288: A phase I study of MPDL3280A, an engineered PD-L1 antibody in patients with locally advanced or metastatic tumors.. Cancer Research. 73(8_Supplement). LB–288. 11 indexed citations
11.
Irving, Bryan, Jeanne Cheung, Yagai Yang, et al.. (2013). MAP kinase inhibitors stimulate T cell and anti-tumor activity in combination with blockade of the PD-L1/PD-1 interaction. Journal for ImmunoTherapy of Cancer. 1(S1). 1 indexed citations
12.
Chen, Daniel S., Bryan Irving, & F. Stephen Hodi. (2012). Molecular Pathways: Next-Generation Immunotherapy—Inhibiting Programmed Death-Ligand 1 and Programmed Death-1. Clinical Cancer Research. 18(24). 6580–6587. 496 indexed citations breakdown →
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Yu, Xin, Lino C. Gonzalez, Michelle Francesco, et al.. (2008). The surface protein TIGIT suppresses T cell activation by promoting the generation of mature immunoregulatory dendritic cells. Nature Immunology. 10(1). 48–57. 1118 indexed citations breakdown →
15.
Irving, Bryan & Arthur Weiss. (2000). Surface chimeric receptors as tools in study of lymphocyte activation. Methods in enzymology on CD-ROM/Methods in enzymology. 327. 210–228. 2 indexed citations
16.
Killeen, Nigel, Bryan Irving, Susanne Pippig, & K Zingler. (1998). Signaling checkpoints during the development of T lymphocytes. Current Opinion in Immunology. 10(3). 360–367. 26 indexed citations
17.
Irving, Bryan, Frederick W. Alt, & Nigel Killeen. (1998). Thymocyte Development in the Absence of Pre-T Cell Receptor Extracellular Immunoglobulin Domains. Science. 280(5365). 905–908. 153 indexed citations
18.
Weiss, Arthur, Makio Iwashima, Bryan Irving, et al.. (1994). Molecular and Genetic Insights Into T Cell Antigen Receptor Signal Transduction. Advances in experimental medicine and biology. 365. 53–62. 14 indexed citations
19.
Oers, Nicolai S. C. van, et al.. (1994). Production and characterization of monoclonal antibodies specific for the murine T cell receptor ζ chain. Journal of Immunological Methods. 170(2). 261–268. 19 indexed citations
20.
Irving, Bryan, Andrew C. Chan, & Arthur Weiss. (1993). Functional characterization of a signal transducing motif present in the T cell antigen receptor zeta chain.. The Journal of Experimental Medicine. 177(4). 1093–1103. 289 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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