Dean A. Lee

13.6k total citations · 1 hit paper
248 papers, 8.7k citations indexed

About

Dean A. Lee is a scholar working on Immunology, Oncology and Hematology. According to data from OpenAlex, Dean A. Lee has authored 248 papers receiving a total of 8.7k indexed citations (citations by other indexed papers that have themselves been cited), including 169 papers in Immunology, 130 papers in Oncology and 50 papers in Hematology. Recurrent topics in Dean A. Lee's work include Immune Cell Function and Interaction (149 papers), CAR-T cell therapy research (119 papers) and T-cell and B-cell Immunology (46 papers). Dean A. Lee is often cited by papers focused on Immune Cell Function and Interaction (149 papers), CAR-T cell therapy research (119 papers) and T-cell and B-cell Immunology (46 papers). Dean A. Lee collaborates with scholars based in United States, China and United Kingdom. Dean A. Lee's co-authors include Laurence J.N. Cooper, Richard E. Champlin, Srinivas S. Somanchi, Helen Huls, Harjeet Singh, Sourindra N. Maiti, Cecele J. Denman, Simon Olivares, Lenka V. Hurton and Partow Kebriaei and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Dean A. Lee

233 papers receiving 8.6k citations

Hit Papers

Membrane-Bound IL-21 Promotes Sustained Ex Vivo Prolifera... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dean A. Lee United States 51 5.7k 5.2k 2.3k 1.4k 966 248 8.7k
Yolanda D. Mahnke United States 19 4.4k 0.8× 2.6k 0.5× 1.7k 0.7× 1.2k 0.9× 1.1k 1.1× 32 6.4k
Attilio Bondanza Italy 38 3.5k 0.6× 3.2k 0.6× 1.9k 0.8× 1.4k 1.0× 831 0.9× 100 6.3k
Angela Shen United States 18 5.2k 0.9× 1.8k 0.3× 1.8k 0.8× 1.4k 1.0× 1.4k 1.4× 37 6.3k
Steven A. Feldman United States 36 9.6k 1.7× 4.7k 0.9× 3.1k 1.4× 3.0k 2.2× 2.3k 2.4× 87 11.4k
Cameron J. Turtle United States 48 8.7k 1.5× 3.8k 0.7× 3.0k 1.3× 2.4k 1.8× 2.3k 2.3× 167 11.8k
Crystal L. Mackall United States 50 9.7k 1.7× 4.9k 0.9× 3.6k 1.6× 2.5k 1.8× 2.8k 2.9× 154 12.9k
Nirali N. Shah United States 34 6.0k 1.0× 2.0k 0.4× 1.8k 0.8× 1.8k 1.3× 1.6k 1.6× 219 7.4k
Michael Schmitt Germany 43 3.2k 0.6× 2.6k 0.5× 2.6k 1.1× 845 0.6× 546 0.6× 273 7.1k
Katayoun Rezvani United States 51 5.5k 1.0× 4.9k 0.9× 2.8k 1.2× 1.0k 0.8× 992 1.0× 216 11.2k

Countries citing papers authored by Dean A. Lee

Since Specialization
Citations

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

Fields of papers citing papers by Dean A. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dean A. Lee. 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 Dean A. Lee. The network helps show where Dean A. Lee may publish in the future.

Co-authorship network of co-authors of Dean A. Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Dean A. Lee. A scholar is included among the top collaborators of Dean A. Lee 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 Dean A. Lee. Dean A. Lee 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.
Jokinen, Emmi, Essi Laajala, Shady Adnan Awad, et al.. (2025). High-throughput drug screening identifies SMAC mimetics as enhancers of NK-cell cytotoxicity in chronic myeloid leukemia. Blood. 145(15). 1670–1686. 2 indexed citations
2.
Chu, Yaya, Gaurav Nayyar, Dean A. Lee, et al.. (2024). Efficiently targeting neuroblastoma with the combination of anti-ROR1 CAR NK cells and N-803 in vitro and in vivo in NB xenografts. SHILAP Revista de lepidopterología. 32(2). 200820–200820. 2 indexed citations
3.
Chu, Yaya, Uksha Saini, M. Fevzi Özkaynak, et al.. (2024). Combinatorial immunotherapy with anti-ROR1 CAR NK cells and an IL-21 secreting oncolytic virus against neuroblastoma. SHILAP Revista de lepidopterología. 33(1). 200927–200927. 5 indexed citations
4.
Hai, Hoang, Yaya Chu, Yanling Liao, et al.. (2024). Combinatorial immunotherapy of anti-MCAM CAR-modified expanded natural killer cells and NKTR-255 against neuroblastoma. PubMed. 32(4). 200894–200894.
5.
Chen, Chun‐Yu, et al.. (2023). Opportunities and challenges of combining adoptive cellular therapy with oncolytic virotherapy. Molecular Therapy — Oncolytics. 29. 118–124. 12 indexed citations
7.
Ciurea, Stefan O., Jolie Schafer, Piyanuch Kongtim, et al.. (2021). Results of a Phase I Study with Mb-IL21 Ex Vivo Expanded NK Cells (FC21-NK) for Patients with Refractory Acute Myeloid Leukemia. Transplantation and Cellular Therapy. 27(3). S77–S78. 1 indexed citations
8.
Trikha, Prashant, et al.. (2021). A Multi-Omics Approach for Evaluating the Impact of Cytokines and Donor Source on NK Cell Expansion. Blood. 138(Supplement 1). 1769–1769.
10.
Trikha, Prashant, Jena E. Moseman, Amanda R. Campbell, et al.. (2021). Defining the AHR-regulated transcriptome in NK cells reveals gene expression programs relevant to development and function. Blood Advances. 5(22). 4605–4618. 21 indexed citations
11.
Kararoudi, Meisam Naeimi, Brian P. Tullius, Nitin Chakravarti, et al.. (2020). Genetic and epigenetic modification of human primary NK cells for enhanced antitumor activity. Seminars in Hematology. 57(4). 201–212. 17 indexed citations
12.
Poznanski, Sophie M., Tina Nham, Marianne V. Chew, et al.. (2018). Expanded CD56superbrightCD16+ NK Cells from Ovarian Cancer Patients Are Cytotoxic against Autologous Tumor in a Patient-Derived Xenograft Murine Model. Cancer Immunology Research. 6(10). 1174–1185. 43 indexed citations
13.
Ciurea, Stefan O., Jolie Schafer, Roland L. Bassett, et al.. (2017). Phase 1 clinical trial using mbIL21 ex vivo–expanded donor-derived NK cells after haploidentical transplantation. Blood. 130(16). 1857–1868. 250 indexed citations
16.
Hurton, Lenka V., Harjeet Singh, Amer Najjar, et al.. (2016). Tethered IL-15 augments antitumor activity and promotes a stem-cell memory subset in tumor-specific T cells. Proceedings of the National Academy of Sciences. 113(48). E7788–E7797. 341 indexed citations
17.
Caruso, Hillary G., Lenka V. Hurton, Amer Najjar, et al.. (2015). Tuning Sensitivity of CAR to EGFR Density Limits Recognition of Normal Tissue While Maintaining Potent Antitumor Activity. Cancer Research. 75(17). 3505–3518. 324 indexed citations
18.
Deniger, Drew C., Sourindra N. Maiti, Tiejuan Mi, et al.. (2014). Activating and Propagating Polyclonal Gamma Delta T Cells with Broad Specificity for Malignancies. Clinical Cancer Research. 20(22). 5708–5719. 104 indexed citations
19.
Liu, Yin, Michael A. Sheard, Richard Sposto, et al.. (2013). Growth and Activation of Natural Killer Cells Ex Vivo from Children with Neuroblastoma for Adoptive Cell Therapy. Clinical Cancer Research. 19(8). 2132–2143. 85 indexed citations
20.
Singh, Harjeet, Matthew J. Figliola, Margaret J. Dawson, et al.. (2011). Reprogramming CD19-Specific T Cells with IL-21 Signaling Can Improve Adoptive Immunotherapy of B-Lineage Malignancies. Cancer Research. 71(10). 3516–3527. 161 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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