Janette Sutton

1.2k total citations
15 papers, 515 citations indexed

About

Janette Sutton is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Janette Sutton has authored 15 papers receiving a total of 515 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Oncology, 9 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in Janette Sutton's work include CAR-T cell therapy research (9 papers), Viral Infectious Diseases and Gene Expression in Insects (7 papers) and Nanowire Synthesis and Applications (3 papers). Janette Sutton is often cited by papers focused on CAR-T cell therapy research (9 papers), Viral Infectious Diseases and Gene Expression in Insects (7 papers) and Nanowire Synthesis and Applications (3 papers). Janette Sutton collaborates with scholars based in United States. Janette Sutton's co-authors include Javier Chaparro‐Riggers, David L. Shelton, Arvind Rajpal, Pavel Strop, Liang Hong, Barbra J. Sasu, Tao Geng, Lanfang Bai, Andrea Rossi and Yasmina Abdiche and has published in prestigious journals such as Journal of Biological Chemistry, Blood and Cancer Research.

In The Last Decade

Janette Sutton

15 papers receiving 495 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Janette Sutton United States 9 202 192 151 117 102 15 515
Tatsuyoshi Yamamoto Japan 15 239 1.2× 97 0.5× 107 0.7× 95 0.8× 50 0.5× 43 664
Tanja Stüber Germany 11 162 0.8× 315 1.6× 57 0.4× 84 0.7× 41 0.4× 23 639
David Dadey United States 11 358 1.8× 103 0.5× 44 0.3× 54 0.5× 28 0.3× 21 661
Jennifer Green United States 12 256 1.3× 355 1.8× 121 0.8× 351 3.0× 33 0.3× 36 818
Yasuhiko Akiyama Japan 13 160 0.8× 76 0.4× 43 0.3× 43 0.4× 58 0.6× 54 646
Christo Kole Greece 11 277 1.4× 319 1.7× 34 0.2× 153 1.3× 70 0.7× 17 668
Mitesh Patel United States 11 123 0.6× 86 0.4× 66 0.4× 65 0.6× 33 0.3× 16 346
H. Carl Le United States 8 614 3.0× 310 1.6× 43 0.3× 67 0.6× 40 0.4× 10 824
Nicholas G. Avgeropoulos United States 10 234 1.2× 62 0.3× 66 0.4× 29 0.2× 19 0.2× 19 711
Charles V. Kingsley United States 10 292 1.4× 169 0.9× 37 0.2× 67 0.6× 30 0.3× 17 551

Countries citing papers authored by Janette Sutton

Since Specialization
Citations

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

Fields of papers citing papers by Janette Sutton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Janette Sutton

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

All Works

15 of 15 papers shown
1.
Lin, Regina, Janette Sutton, Trevor Bentley, et al.. (2023). Constitutive Turbodomains enhance expansion and antitumor activity of allogeneic BCMA CAR T cells in preclinical models. Science Advances. 9(31). eadg8694–eadg8694. 3 indexed citations
2.
Tacheva-Grigorova, Silvia K., Janette Sutton, Zea Melton, et al.. (2023). Allogeneic CAR T Cells Targeting DLL3 Are Efficacious and Safe in Preclinical Models of Small Cell Lung Cancer. Clinical Cancer Research. 29(5). 971–985. 31 indexed citations
3.
Lin, Regina, Andrew R. Nager, Spencer Park, et al.. (2022). Design and Validation of Inducible TurboCARs with Tunable Induction and Combinatorial Cytokine Signaling. Cancer Immunology Research. 10(9). 1069–1083. 6 indexed citations
4.
Lin, Regina, Yi Zhang, Shanshan Lang, et al.. (2021). Abstract 1519: PD1 TurboCAR™ T cells: PD1-resistant CAR T cells with programmable cytokine signaling outputs. Cancer Research. 81(13_Supplement). 1519–1519. 1 indexed citations
5.
Sommer, Cesar, Hsin‐Yuan Cheng, Duy Nguyen, et al.. (2020). Allogeneic FLT3 CAR T Cells with an Off-Switch Exhibit Potent Activity against AML and Can Be Depleted to Expedite Bone Marrow Recovery. Molecular Therapy. 28(10). 2237–2251. 70 indexed citations
6.
Sommer, Cesar, Regina Lin, Janette Sutton, et al.. (2020). Preclinical Evaluation of ALLO-605, an Allogeneic BCMA Turbocar TTM Cell Therapy for the Treatment of Multiple Myeloma. Blood. 136(Supplement 1). 8–8. 8 indexed citations
7.
Sommer, Cesar, Trevor Bentley, Janette Sutton, et al.. (2019). Off-the-shelf AlloCAR T™ cells targeting BCMA for the treatment of multiple myeloma. Clinical Lymphoma Myeloma & Leukemia. 19(10). e24–e24. 3 indexed citations
8.
Sommer, Cesar, Hsin‐Yuan Cheng, Yik A. Yeung, et al.. (2019). Preclinical Evaluation of ALLO-819, an Allogeneic CAR T Cell Therapy Targeting FLT3 for the Treatment of Acute Myeloid Leukemia. Blood. 134(Supplement_1). 3921–3921. 2 indexed citations
9.
Sommer, Cesar, Bijan Boldajipour, Julien Valton, et al.. (2018). ALLO-715, an Allogeneic BCMA CAR T Therapy Possessing an Off-Switch for the Treatment of Multiple Myeloma. Blood. 132(Supplement 1). 591–591. 14 indexed citations
10.
DeVay, Rachel M., Kathy Delaria, Guoyun Zhu, et al.. (2017). Improved Lysosomal Trafficking Can Modulate the Potency of Antibody Drug Conjugates. Bioconjugate Chemistry. 28(4). 1102–1114. 42 indexed citations
11.
Chaparro‐Riggers, Javier, Liang Hong, Rachel M. DeVay, et al.. (2012). Increasing Serum Half-life and Extending Cholesterol Lowering in Vivo by Engineering Antibody with pH-sensitive Binding to PCSK9. Journal of Biological Chemistry. 287(14). 11090–11097. 137 indexed citations
12.
Hong, Liang, Javier Chaparro‐Riggers, Pavel Strop, et al.. (2011). Proprotein Convertase Substilisin/Kexin Type 9 Antagonism Reduces Low-Density Lipoprotein Cholesterol in Statin-Treated Hypercholesterolemic Nonhuman Primates. Journal of Pharmacology and Experimental Therapeutics. 340(2). 228–236. 90 indexed citations
13.
Sutton, Janette, Amy E. Berson, Xiaosu Wu, et al.. (2009). Involvement of the neurotensin receptor 1 in the behavioral effects of two neurotensin agonists, NT-2 and NT69L: Lack of hypothermic, antinociceptive and antipsychotic actions in receptor knockout mice. European Neuropsychopharmacology. 19(7). 466–475. 29 indexed citations
14.
Zeller, James R., Kris Poulsen, Janette Sutton, et al.. (2008). CGRP function‐blocking antibodies inhibit neurogenic vasodilatation without affecting heart rate or arterial blood pressure in the rat. British Journal of Pharmacology. 155(7). 1093–1103. 73 indexed citations
15.
Sutton, Janette, Ian Roos, & Brian L. Hillcoat. (1982). Combined actions of 5-fluorouracil and 1-(2-chloroethyl)-3-(4-methylcyclohexyl)-1-nitrosourea on human colonic carcinoma cells in vitro.. PubMed. 42(12). 5172–5. 6 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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