Todd VanArsdale

5.7k total citations · 2 hit papers
48 papers, 3.7k citations indexed

About

Todd VanArsdale is a scholar working on Oncology, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Todd VanArsdale has authored 48 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Oncology, 25 papers in Molecular Biology and 17 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Todd VanArsdale's work include Advanced Breast Cancer Therapies (17 papers), Cancer-related Molecular Pathways (11 papers) and Immune Response and Inflammation (6 papers). Todd VanArsdale is often cited by papers focused on Advanced Breast Cancer Therapies (17 papers), Cancer-related Molecular Pathways (11 papers) and Immune Response and Inflammation (6 papers). Todd VanArsdale collaborates with scholars based in United States, Spain and United Kingdom. Todd VanArsdale's co-authors include Carl F. Ware, Paul D. Crowe, Kim Arndt, Chris Boshoff, Robert T. Abraham, Jeffrey L. Browning, Michael J. Munchhof, Annelie Abrahamsson, Hyog Young Kwon and Philip A. Beachy and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Todd VanArsdale

47 papers receiving 3.7k citations

Hit Papers

Hedgehog signalling is essential for maintenance of cance... 2009 2026 2014 2020 2009 2016 200 400 600

Peers

Todd VanArsdale
Marion Dorsch United States
David A. Barbie United States
Carlos Bais United States
Mark Merchant United States
Yun Wu United States
Edward R. Kastenhuber United States
Donald L. Durden United States
Marion Dorsch United States
Todd VanArsdale
Citations per year, relative to Todd VanArsdale Todd VanArsdale (= 1×) peers Marion Dorsch

Countries citing papers authored by Todd VanArsdale

Since Specialization
Citations

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

Fields of papers citing papers by Todd VanArsdale

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Todd VanArsdale

This figure shows the co-authorship network connecting the top 25 collaborators of Todd VanArsdale. A scholar is included among the top collaborators of Todd VanArsdale 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 VanArsdale. Todd VanArsdale 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.
Liu, Zhonglin, Marscha Hirschi, Oleg Brodsky, et al.. (2024). An allosteric cyclin E-CDK2 site mapped by paralog hopping with covalent probes. Nature Chemical Biology. 21(3). 420–431. 7 indexed citations
3.
Arora, Mansi, Justin Moser, Mingwei Min, et al.. (2023). Rapid adaptation to CDK2 inhibition exposes intrinsic cell-cycle plasticity. Cell. 186(12). 2628–2643.e21. 66 indexed citations
4.
Ford, Kyle, Samson Fong, Nongluk Plongthongkum, et al.. (2023). Multimodal perturbation analyses of cyclin-dependent kinases reveal a network of synthetic lethalities associated with cell-cycle regulation and transcriptional regulation. Scientific Reports. 13(1). 7678–7678. 4 indexed citations
5.
Yin, Yandong, Carel Fijen, Lianglin Zhang, et al.. (2022). A two-step mechanism governing PARP1-DNA retention by PARP inhibitors. Science Advances. 8(36). eabq0414–eabq0414. 35 indexed citations
6.
Ding, Xia, Zhou Zhu, John D. Lapek, et al.. (2022). PARP1-SNAI2 transcription axis drives resistance to PARP inhibitor, Talazoparib. Scientific Reports. 12(1). 12501–12501. 8 indexed citations
7.
Álvarez‐Fernández, Mónica, Aicha El Bakkali, Camino Menéndez, et al.. (2020). CDK4/6 Inhibitors Impair Recovery from Cytotoxic Chemotherapy in Pancreatic Adenocarcinoma. Cancer Cell. 37(3). 340–353.e6. 116 indexed citations
8.
Ryan, Kevin, Ben Bolaños, Marissa L. Smith, et al.. (2020). Dissecting the molecular determinants of clinical PARP1 inhibitor selectivity for tankyrase1. Journal of Biological Chemistry. 296. 100251–100251. 54 indexed citations
9.
Álvarez‐Fernández, Mónica, María Salazar‐Roa, David Partida, et al.. (2017). Therapeutic relevance of the PP2A-B55 inhibitory kinase MASTL/Greatwall in breast cancer. Cell Death and Differentiation. 25(5). 828–840. 73 indexed citations
10.
Chen, Ping, Nathan V. Lee, Wenyue Hu, et al.. (2016). Spectrum and Degree of CDK Drug Interactions Predicts Clinical Performance. Molecular Cancer Therapeutics. 15(10). 2273–2281. 307 indexed citations breakdown →
11.
Wardell, Suzanne E., Matthew J. Ellis, Holly M. Alley, et al.. (2015). Efficacy of SERD/SERM Hybrid-CDK4/6 Inhibitor Combinations in Models of Endocrine Therapy–Resistant Breast Cancer. Clinical Cancer Research. 21(22). 5121–5130. 115 indexed citations
12.
Chen, Shihao, Li‐Fen Lee, Timothy S. Fisher, et al.. (2014). Combination of 4-1BB Agonist and PD-1 Antagonist Promotes Antitumor Effector/Memory CD8 T Cells in a Poorly Immunogenic Tumor Model. Cancer Immunology Research. 3(2). 149–160. 207 indexed citations
13.
Koehler, María, Todd VanArsdale, David J. Shields, et al.. (2014). Mechanism of Action for Combined CDK4/6 and Er Inhibition in ER Positive Breast Cancer. Annals of Oncology. 25. i21–i21. 5 indexed citations
14.
Fang, Douglas D., Cathy C. Zhang, Yin Gu, et al.. (2013). Antitumor Efficacy of the Dual PI3K/mTOR Inhibitor PF-04691502 in a Human Xenograft Tumor Model Derived from Colorectal Cancer Stem Cells Harboring a PIK3CA Mutation. PLoS ONE. 8(6). e67258–e67258. 33 indexed citations
15.
Zhang, Cathy C., Zhengming Yan, Qin Zhang, et al.. (2010). PF-03732010: A Fully Human Monoclonal Antibody against P-Cadherin with Antitumor and Antimetastatic Activity. Clinical Cancer Research. 16(21). 5177–5188. 58 indexed citations
16.
Guo, Chuangxing, Xinjun Hou, Liming Dong, et al.. (2009). Structure-based design of novel human Pin1 inhibitors (I). Bioorganic & Medicinal Chemistry Letters. 19(19). 5613–5616. 91 indexed citations
17.
Ye, Xin, Patrick Mehlen, Shahrooz Rabizadeh, et al.. (1999). TRAF Family Proteins Interact with the Common Neurotrophin Receptor and Modulate Apoptosis Induction. Journal of Biological Chemistry. 274(42). 30202–30208. 158 indexed citations
18.
Krajewski, Stanisław, Juan M. Zapata, Maryla Krajewska, et al.. (1997). Immunohistochemical analysis of in vivo patterns of TRAF-3 expression, a member of the TNF receptor-associated factor family. The Journal of Immunology. 159(12). 5841–5852. 40 indexed citations
19.
Ware, Carl F., Todd VanArsdale, Paul D. Crowe, & Jeffrey L. Browning. (1995). The Ligands and Receptors of the Lymphotoxin System. Current topics in microbiology and immunology. 198. 175–218. 218 indexed citations
20.
Crowe, Paul D., et al.. (1994). Production of lymphotoxin (LTα) and a soluble dimeric form of its receptor using the baculovirus expression system. Journal of Immunological Methods. 168(1). 79–89. 39 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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