A. Kate Sasser

7.6k total citations · 4 hit papers
54 papers, 4.5k citations indexed

About

A. Kate Sasser is a scholar working on Hematology, Oncology and Molecular Biology. According to data from OpenAlex, A. Kate Sasser has authored 54 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Hematology, 26 papers in Oncology and 19 papers in Molecular Biology. Recurrent topics in A. Kate Sasser's work include Multiple Myeloma Research and Treatments (30 papers), Monoclonal and Polyclonal Antibodies Research (18 papers) and CAR-T cell therapy research (11 papers). A. Kate Sasser is often cited by papers focused on Multiple Myeloma Research and Treatments (30 papers), Monoclonal and Polyclonal Antibodies Research (18 papers) and CAR-T cell therapy research (11 papers). A. Kate Sasser collaborates with scholars based in United States, Netherlands and Belgium. A. Kate Sasser's co-authors include Brett M. Hall, Amy Axel, Henk M. Lokhorst, Niels W.C.J. van de Donk, Tahamtan Ahmadi, Nicholas J. Sullivan, Tuna Mutis, Michael Andreeff, Jennifer L. Dembinski and Frank C. Marini and has published in prestigious journals such as Blood, PLoS ONE and Cancer Research.

In The Last Decade

A. Kate Sasser

52 papers receiving 4.4k citations

Hit Papers

Mesenchymal Stem Cell Transition to Tumor-Associated Fibr... 2009 2026 2014 2020 2009 2016 2009 2016 200 400 600

Peers

A. Kate Sasser
D Delia Italy
Mark P. Chao United States
Amy Axel United States
Siddhartha Jaiswal United States
Yusuke Shiozawa United States
Dirk Hose Germany
Meike Burger Germany
Antonio Sacco United States
A. Kate Sasser
Citations per year, relative to A. Kate Sasser A. Kate Sasser (= 1×) peers Valter Gattei

Countries citing papers authored by A. Kate Sasser

Since Specialization
Citations

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

Fields of papers citing papers by A. Kate Sasser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Kate Sasser

This figure shows the co-authorship network connecting the top 25 collaborators of A. Kate Sasser. A scholar is included among the top collaborators of A. Kate Sasser 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 A. Kate Sasser. A. Kate Sasser 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.
Belch, Andrew, Torben Plesner, Paul G. Richardson, et al.. (2024). Clinical efficacy of daratumumab monotherapy in patients with heavily pretreated relapsed or refractory multiple myeloma. Carolina Digital Repository (University of North Carolina at Chapel Hill).
2.
Hiemstra, Ida H., Kim C. M. Santegoets, Maarten L. Janmaat, et al.. (2023). Preclinical anti-tumour activity of HexaBody-CD38, a next-generation CD38 antibody with superior complement-dependent cytotoxic activity. EBioMedicine. 93. 104663–104663. 18 indexed citations
3.
Kemper, Kristel, Péter Boross, Mischa Houtkamp, et al.. (2022). Mechanistic and pharmacodynamic studies of DuoBody-CD3x5T4 in preclinical tumor models. Life Science Alliance. 5(11). e202201481–e202201481. 3 indexed citations
4.
Hiemstra, Ida H., Patricia Garrido Castro, Roberto S Oliveri, et al.. (2021). PRECLINICAL EVALUATION OF EPCORITAMAB COMBINED WITH STANDARD OF CARE AGENTS FOR THE TREATMENT OF B‐CELL LYMPHOMAS. Hematological Oncology. 39(S2). 1 indexed citations
5.
Soong, David, Jeran K. Stratford, Hervé Avet‐Loiseau, et al.. (2020). CNV Radar: an improved method for somatic copy number alteration characterization in oncology. BMC Bioinformatics. 21(1). 98–98. 11 indexed citations
6.
Usmani, Saad Z., Imran Khan, Christopher Chiu, et al.. (2018). Deep sustained response to daratumumab monotherapy associated with T-cell expansion in triple refractory myeloma. Experimental Hematology and Oncology. 7(1). 3–3. 12 indexed citations
7.
Krejcik, Jakub, Inger S. Nijhof, Berris van Kessel, et al.. (2017). Monocytes and Granulocytes Reduce CD38 Expression Levels on Myeloma Cells in Patients Treated with Daratumumab. Clinical Cancer Research. 23(24). 7498–7511. 119 indexed citations
8.
Casneuf, Tineke, Homer Adams, Andrew C. Lysaght, et al.. (2017). Proteomic Profiling Reveals Targetable Pathways in MGUS (SLAMF6, TNFRSF8, TIMP1, TRL2) That May Contribute to Disease Progression. Blood. 130. 3805–3805. 1 indexed citations
9.
Casneuf, Tineke, Xu Steven Xu, Homer Adams, et al.. (2017). Effects of daratumumab on natural killer cells and impact on clinical outcomes in relapsed or refractory multiple myeloma. Blood Advances. 1(23). 2105–2114. 160 indexed citations
10.
Nijhof, Inger S., Tineke Casneuf, Berris van Kessel, et al.. (2016). CD38 expression and complement inhibitors affect response and resistance to daratumumab therapy in myeloma. Blood. 128(7). 959–970. 275 indexed citations
11.
Mateos, María‐Victoria, Jane Estell, Wolney Barreto, et al.. (2016). Efficacy of Daratumumab, Bortezomib, and Dexamethasone Versus Bortezomib and Dexamethasone in Relapsed or Refractory Myeloma Based on Prior Lines of Therapy: Updated Analysis of Castor. Blood. 128(22). 1150–1150. 28 indexed citations
12.
Donk, Niels W.C.J. van de, Maarten L. Janmaat, Tuna Mutis, et al.. (2016). Monoclonal antibodies targeting CD38 in hematological malignancies and beyond. Immunological Reviews. 270(1). 95–112. 237 indexed citations
14.
Plesner, Torben, Hendrik‐Tobias Arkenau, Peter Gimsing, et al.. (2015). Daratumumab in Combination with Lenalidomide and Dexamethasone in Patients with Relapsed or Relapsed and Refractory Multiple Myeloma: Updated Results of a Phase 1/2 Study (GEN503). Blood. 126(23). 507–507. 35 indexed citations
15.
Sasser, A. Kate, Tineke Casneuf, Dhammika Amaratunga, et al.. (2013). Development Of a Serum Biomarker Panel That Predicts Imminent Risk Of Multiple Myeloma (MM) Progression From Premalignancy. Blood. 122(21). 3115–3115. 3 indexed citations
16.
Sullivan, Nicholas J., A. Kate Sasser, Amy Axel, et al.. (2009). Interleukin-6 induces an epithelial–mesenchymal transition phenotype in human breast cancer cells. Oncogene. 28(33). 2940–2947. 605 indexed citations breakdown →
17.
Studebaker, Adam, Gianluca Storci, Jillian L. Werbeck, et al.. (2008). Fibroblasts Isolated from Common Sites of Breast Cancer Metastasis Enhance Cancer Cell Growth Rates and Invasiveness in an Interleukin-6–Dependent Manner. Cancer Research. 68(21). 9087–9095. 198 indexed citations
18.
Hall, Brett M., Jennifer L. Dembinski, A. Kate Sasser, et al.. (2007). Mesenchymal Stem Cells in Cancer: Tumor-Associated Fibroblasts and Cell-Based Delivery Vehicles. International Journal of Hematology. 86(1). 8–16. 138 indexed citations
19.
Sasser, A. Kate, Bethany L. Mundy-Bosse, Kristen M. Smith, et al.. (2007). Human bone marrow stromal cells enhance breast cancer cell growth rates in a cell line-dependent manner when evaluated in 3D tumor environments. Cancer Letters. 254(2). 255–264. 102 indexed citations
20.
Sasser, A. Kate, et al.. (2006). Metabolic Biotinylation Provides a Unique Platform for the Purification and Targeting of Multiple AAV Vector Serotypes. Molecular Therapy. 14(1). 97–106. 69 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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