Todd D. Prickett

9.5k total citations · 4 hit papers
52 papers, 5.9k citations indexed

About

Todd D. Prickett is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Todd D. Prickett has authored 52 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Oncology, 31 papers in Immunology and 20 papers in Molecular Biology. Recurrent topics in Todd D. Prickett's work include CAR-T cell therapy research (29 papers), Immunotherapy and Immune Responses (26 papers) and Cancer Immunotherapy and Biomarkers (21 papers). Todd D. Prickett is often cited by papers focused on CAR-T cell therapy research (29 papers), Immunotherapy and Immune Responses (26 papers) and Cancer Immunotherapy and Biomarkers (21 papers). Todd D. Prickett collaborates with scholars based in United States, Israel and Malaysia. Todd D. Prickett's co-authors include Steven A. Rosenberg, Jared J. Gartner, Paul F. Robbins, Anna Pasetto, Eric Tran, Maria R. Parkhurst, David L. Brautigan, Yong‐Chen Lu, Lee Jia and Zhili Zheng and has published in prestigious journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Todd D. Prickett

49 papers receiving 5.8k 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.

T-Cell Transfer Therapy Targeting Mutant KRAS in Cancer

2016 950 citations Eric Tran, Paul F. Robbins et al. profile →
Prospective identification of neoantigen-specific lymphocytes in the peripheral blood of melanoma patients

2016 597 citations Alena Gros, Maria R. Parkhurst et al. profile →
Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer

2018 544 citations Nikolaos Zacharakis, Harshini Chinnasamy et al. profile →
mRNA vaccine–induced neoantigen-specific T cell immunity in patients with gastrointestinal cancer

2020 313 citations Jared J. Gartner, Biman C. Paria et al. Journal of Clinical Investigation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Todd D. Prickett United States	34	4.0k	3.2k	2.3k	561	540	52	5.9k
Suchit Jhunjhunwala United States	23	1.7k 0.4×	2.2k 0.7×	2.4k 1.0×	825 1.5×	269 0.5×	38	4.5k
Gary E. Archer United States	42	3.7k 0.9×	3.2k 1.0×	1.8k 0.8×	484 0.9×	520 1.0×	80	6.5k
Matthew J. Scanlan United States	36	2.5k 0.6×	4.2k 1.3×	4.3k 1.8×	682 1.2×	468 0.9×	50	7.3k
Ali O. Güre United States	34	1.7k 0.4×	3.5k 1.1×	3.9k 1.7×	907 1.6×	399 0.7×	70	6.3k
Ken‐ichi Hanada United States	29	2.1k 0.5×	2.6k 0.8×	1.9k 0.8×	210 0.4×	430 0.8×	56	4.9k
José Luís Barrera Mexico	9	3.3k 0.8×	2.0k 0.6×	1.5k 0.6×	618 1.1×	140 0.3×	35	4.6k
Alena Gros Spain	28	4.3k 1.1×	3.6k 1.1×	1.5k 0.7×	307 0.5×	939 1.7×	54	5.6k
Monica Rodolfo Italy	33	1.4k 0.4×	1.8k 0.6×	2.1k 0.9×	852 1.5×	392 0.7×	89	4.0k
Christine Feig United Kingdom	20	3.9k 1.0×	1.9k 0.6×	3.0k 1.3×	1.7k 3.1×	220 0.4×	25	6.6k
Connie L. Sommers United States	33	1.1k 0.3×	2.4k 0.8×	1.9k 0.8×	457 0.8×	288 0.5×	59	4.7k

Countries citing papers authored by Todd D. Prickett

Since Specialization

Citations

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

Fields of papers citing papers by Todd D. Prickett

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todd D. Prickett. 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 Todd D. Prickett. The network helps show where Todd D. Prickett may publish in the future.

Co-authorship network of co-authors of Todd D. Prickett

This figure shows the co-authorship network connecting the top 25 collaborators of Todd D. Prickett. A scholar is included among the top collaborators of Todd D. Prickett 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 Todd D. Prickett. Todd D. Prickett 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

Nah, Shirley, A. Gustafson, Billel Gasmi, et al.. (2025). Adoptive Cell Transfer of Tumor-Infiltrating Lymphocytes for Metastatic Acral Lentiginous Melanoma. Journal of Clinical Oncology. 43(22). 2479–2489.

Sindiri, Sivasish, Victoria Hill, Billel Gasmi, et al.. (2023). Specific recognition of an FGFR2 fusion by tumor infiltrating lymphocytes from a patient with metastatic cholangiocarcinoma. Journal for ImmunoTherapy of Cancer. 11(4). e006303–e006303. 2 indexed citations

Hanada, Ken‐ichi, Chihao Zhao, Jared J. Gartner, et al.. (2022). A phenotypic signature that identifies neoantigen-reactive T cells in fresh human lung cancers. Cancer Cell. 40(5). 479–493.e6. 90 indexed citations

Gartner, Jared J., Maria R. Parkhurst, Alena Gros, et al.. (2021). A machine learning model for ranking candidate HLA class I neoantigens based on known neoepitopes from multiple human tumor types. Nature Cancer. 2(5). 563–574. 56 indexed citations

Lo, Winifred, Maria R. Parkhurst, Paul F. Robbins, et al.. (2019). Immunologic Recognition of a Shared p53 Mutated Neoantigen in a Patient with Metastatic Colorectal Cancer. Cancer Immunology Research. 7(4). 534–543. 105 indexed citations

Deniger, Drew C., Anna Pasetto, Paul F. Robbins, et al.. (2018). T-cell Responses to TP53 “Hotspot” Mutations and Unique Neoantigens Expressed by Human Ovarian Cancers. Clinical Cancer Research. 24(22). 5562–5573. 110 indexed citations

Assadipour, Yasmine, Nikolaos Zacharakis, Jessica S. Crystal, et al.. (2017). Characterization of an Immunogenic Mutation in a Patient with Metastatic Triple-Negative Breast Cancer. Clinical Cancer Research. 23(15). 4347–4353. 28 indexed citations

Stevanović, Sanja, Anna Pasetto, Sarah R. Helman, et al.. (2017). Landscape of immunogenic tumor antigens in successful immunotherapy of virally induced epithelial cancer. Science. 356(6334). 200–205. 279 indexed citations

Pasetto, Anna, Alena Gros, Paul F. Robbins, et al.. (2016). Tumor- and Neoantigen-Reactive T-cell Receptors Can Be Identified Based on Their Frequency in Fresh Tumor. Cancer Immunology Research. 4(9). 734–743. 148 indexed citations

10.

Parkhurst, Maria R., Alena Gros, Anna Pasetto, et al.. (2016). Isolation of T-Cell Receptors Specifically Reactive with Mutated Tumor-Associated Antigens from Tumor-Infiltrating Lymphocytes Based on CD137 Expression. Clinical Cancer Research. 23(10). 2491–2505. 136 indexed citations

11.

Prickett, Todd D., Jessica S. Crystal, Cyrille J. Cohen, et al.. (2016). Durable Complete Response from Metastatic Melanoma after Transfer of Autologous T Cells Recognizing 10 Mutated Tumor Antigens. Cancer Immunology Research. 4(8). 669–678. 88 indexed citations

12.

Cohen, Cyrille J., Jared J. Gartner, Miryam Horovitz‐Fried, et al.. (2015). Isolation of neoantigen-specific T cells from tumor and peripheral lymphocytes. Journal of Clinical Investigation. 125(10). 3981–3991. 275 indexed citations

13.

Prickett, Todd D., Xiaomu Wei, Jamie K. Teer, et al.. (2011). Exon capture analysis of G protein-coupled receptors identifies activating mutations in GRM3 in melanoma. Nature Genetics. 43(11). 1119–1126. 115 indexed citations

14.

Wei, Xiaomu, Todd D. Prickett, Cristina G. Viloria, et al.. (2010). Mutational and Functional Analysis Reveals ADAMTS18 Metalloproteinase as a Novel Driver in Melanoma. Molecular Cancer Research. 8(11). 1513–1525. 41 indexed citations

15.

Cronin, Julia C., John R. Wunderlich, Stacie K. Loftus, et al.. (2009). Frequent mutations in the MITF pathway in melanoma. Pigment Cell & Melanoma Research. 22(4). 435–444. 115 indexed citations

16.

Prickett, Todd D., Jun Ninomiya‐Tsuji, Peter M. Broglie, et al.. (2008). TAB4 Stimulates TAK1-TAB1 Phosphorylation and Binds Polyubiquitin to Direct Signaling to NF-κB. Journal of Biological Chemistry. 283(28). 19245–19254. 40 indexed citations

17.

Prickett, Todd D. & David L. Brautigan. (2007). Cytokine Activation of p38 Mitogen-Activated Protein Kinase and Apoptosis Is Opposed by alpha-4 Targeting of Protein Phosphatase 2A for Site-Specific Dephosphorylation of MEK3. Molecular and Cellular Biology. 27(12). 4217–4227. 49 indexed citations

18.

Prickett, Todd D. & David L. Brautigan. (2004). Overlapping Binding Sites in Protein Phosphatase 2A for Association with Regulatory A and α-4 (mTap42) Subunits. Journal of Biological Chemistry. 279(37). 38912–38920. 33 indexed citations

19.

Eto, Masumi, Elizabeth Elliott, Todd D. Prickett, & David L. Brautigan. (2002). Inhibitor-2 Regulates Protein Phosphatase-1 Complexed with NimA-related Kinase to Induce Centrosome Separation. Journal of Biological Chemistry. 277(46). 44013–44020. 84 indexed citations

20.

Terry-Lorenzo, Ryan T., et al.. (2002). Neurabins Recruit Protein Phosphatase-1 and Inhibitor-2 to the Actin Cytoskeleton. Journal of Biological Chemistry. 277(48). 46535–46543. 67 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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