Tuna Mutis

13.3k total citations · 2 hit papers
180 papers, 9.4k citations indexed

About

Tuna Mutis is a scholar working on Immunology, Oncology and Hematology. According to data from OpenAlex, Tuna Mutis has authored 180 papers receiving a total of 9.4k indexed citations (citations by other indexed papers that have themselves been cited), including 101 papers in Immunology, 84 papers in Oncology and 82 papers in Hematology. Recurrent topics in Tuna Mutis's work include Multiple Myeloma Research and Treatments (66 papers), Immune Cell Function and Interaction (60 papers) and CAR-T cell therapy research (54 papers). Tuna Mutis is often cited by papers focused on Multiple Myeloma Research and Treatments (66 papers), Immune Cell Function and Interaction (60 papers) and CAR-T cell therapy research (54 papers). Tuna Mutis collaborates with scholars based in Netherlands, United States and Denmark. Tuna Mutis's co-authors include Niels W.C.J. van de Donk, Els Goulmy, Henk M. Lokhorst, Paul W.H.I. Parren, Richard W.J. Groen, Sonja Zweegman, Ellen Schrama, Tom H. M. Ottenhoff, Inger S. Nijhof and Anton C. Martens and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Nature Medicine.

In The Last Decade

Tuna Mutis

174 papers receiving 9.2k 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.

Daratumumab, a Novel Therapeutic Human CD38 Monoclonal Antibody, Induces Killing of Multiple Myeloma and Other Hematological Tumors

2010 746 citations Tuna Mutis, Henk M. Lokhorst et al. profile →
Daratumumab depletes CD38+ immune regulatory cells, promotes T-cell expansion, and skews T-cell repertoire in multiple myeloma

2016 649 citations Jakub Krejcik, Tineke Casneuf et al. Blood profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tuna Mutis Netherlands	50	4.7k	4.2k	4.1k	2.7k	1.2k	180	9.4k
Qing Yi United States	54	4.9k 1.0×	1.8k 0.4×	3.6k 0.9×	3.8k 1.4×	478 0.4×	197	9.8k
Steven L. Allen United States	45	4.5k 1.0×	2.5k 0.6×	1.9k 0.4×	3.2k 1.2×	1.1k 0.9×	225	11.4k
Geoffrey S. Kansas United States	52	4.5k 0.9×	1.4k 0.3×	1.5k 0.4×	2.3k 0.8×	946 0.8×	89	8.5k
Elaine Coustan‐Smith United States	60	3.0k 0.6×	6.0k 1.4×	2.2k 0.5×	2.6k 1.0×	181 0.2×	140	11.5k
Yaīr Reisner Israel	50	5.0k 1.1×	4.7k 1.1×	1.7k 0.4×	2.4k 0.9×	584 0.5×	224	9.6k
Maryalice Stetler‐Stevenson United States	57	6.2k 1.3×	2.2k 0.5×	8.9k 2.2×	4.3k 1.6×	1.0k 0.9×	230	15.8k
Håkan Mellstedt Sweden	51	5.4k 1.1×	1.5k 0.4×	3.5k 0.8×	2.7k 1.0×	1.5k 1.3×	298	9.9k
Matthias Edinger Germany	35	5.7k 1.2×	2.3k 0.5×	2.2k 0.5×	2.2k 0.8×	203 0.2×	114	8.9k
Josée Golay Italy	52	4.2k 0.9×	1.1k 0.3×	2.5k 0.6×	2.8k 1.0×	2.0k 1.7×	140	8.8k
Sylvain Latour France	47	5.7k 1.2×	1.2k 0.3×	1.5k 0.4×	1.8k 0.7×	826 0.7×	99	7.7k

Countries citing papers authored by Tuna Mutis

Since Specialization

Citations

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

Fields of papers citing papers by Tuna Mutis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tuna Mutis

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Poels, Renée, Jennemiek van Arkel, Niels W.C.J. van de Donk, et al.. (2025). Surface downmodulation of TIM3 safeguards healthy cells but not acute myeloid leukemia from CAR T‐cell therapy. HemaSphere. 9(7). e70155–e70155.

Duetz, Carolien, Christie P.M. Verkleij, Pieter Sonneveld, et al.. (2025). A T-cell–based metric of immune age predicts outcomes in older patients with myeloma receiving daratumumab-based therapy. Blood. 146(21). 2517–2530.

Verkleij, Christie P.M., Marloes E.C. Broekmans, Kristine A. Frerichs, et al.. (2024). T-Cell Characteristics Impact Response and Resistance to T-Cell–Redirecting Bispecific Antibodies in Multiple Myeloma. Clinical Cancer Research. 30(14). 3006–3022. 25 indexed citations

Verkleij, Christie P.M., Diane Le Clerre, Maria Themeli, et al.. (2024). Preclinical activity of allogeneic SLAMF7-specific CAR T-cells (UCARTCS1) in multiple myeloma. Journal for ImmunoTherapy of Cancer. 12(7). e008769–e008769. 5 indexed citations

Arkel, Jennemiek van, Afroditi Katsarou, Ruud Ruiter, et al.. (2023). Specific Targeting of Multiple Myeloma by Dual Split-signaling Chimeric Antigen Receptor T cells Directed against CD38 and CD138. Clinical Cancer Research. 29(20). 4219–4229. 10 indexed citations

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

Katsarou, Afroditi, Renée Poels, Esther Drent, et al.. (2021). Bone Marrow Mesenchymal Stromal Cells Can Render Multiple Myeloma Cells Resistant to Cytotoxic Machinery of CAR T Cells through Inhibition of Apoptosis. Clinical Cancer Research. 27(13). 3793–3803. 47 indexed citations

Frerichs, Kristine A., Monique C. Minnema, Mark‐David Levin, et al.. (2021). Efficacy and safety of daratumumab combined with all-transretinoic acid in relapsed/refractory multiple myeloma. Blood Advances. 5(23). 5128–5139. 27 indexed citations

Frerichs, Kristine A., Christie P.M. Verkleij, Meletios Α. Dimopoulos, et al.. (2021). Efficacy and Safety of Durvalumab Combined with Daratumumab in Daratumumab-Refractory Multiple Myeloma Patients. Cancers. 13(10). 2452–2452. 17 indexed citations

10.

Verkleij, Christie P.M., Marloes E.C. Broekmans, Mark van Duin, et al.. (2021). Preclinical activity and determinants of response of the GPRC5DxCD3 bispecific antibody talquetamab in multiple myeloma. Blood Advances. 5(8). 2196–2215. 117 indexed citations

11.

Verkleij, Christie P.M., et al.. (2021). Current State of the Art and Prospects of T Cell-Redirecting Bispecific Antibodies in Multiple Myeloma. Journal of Clinical Medicine. 10(19). 4593–4593. 17 indexed citations

12.

Frerichs, Kristine A., Marloes E.C. Broekmans, Berris van Kessel, et al.. (2020). Preclinical Activity of JNJ-7957, a Novel BCMA×CD3 Bispecific Antibody for the Treatment of Multiple Myeloma, Is Potentiated by Daratumumab. Clinical Cancer Research. 26(9). 2203–2215. 68 indexed citations

13.

Verkleij, Christie P.M., Marloes E.C. Broekmans, Kristine A. Frerichs, et al.. (2020). Preclinical Rationale for Targeting the PD-1/PD-L1 Axis in Combination with a CD38 Antibody in Multiple Myeloma and Other CD38-Positive Malignancies. Cancers. 12(12). 3713–3713. 26 indexed citations

14.

Drent, Esther, Renée Poels, Ruud Ruiter, et al.. (2019). Combined CD28 and 4-1BB Costimulation Potentiates Affinity-tuned Chimeric Antigen Receptor–engineered T Cells. Clinical Cancer Research. 25(13). 4014–4025. 135 indexed citations

15.

Pont, Margot J., Rimke Oostvogels, Cornelis A.M. van Bergen, et al.. (2019). T Cells Specific for an Unconventional Natural Antigen Fail to Recognize Leukemic Cells. Cancer Immunology Research. 7(5). 797–804. 8 indexed citations

16.

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

17.

Horst, Hilma J. van der, Marije B. Overdijk, Esther C.W. Breij, et al.. (2017). Potent Ex Vivo Anti-Tumor Activity in Relapsed Refractory Multiple Myeloma Using Novel DR5-Specific Antibodies with Enhanced Capacity to Form Hexamers upon Target Binding. Blood. 130. 1835–1835. 4 indexed citations

18.

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

19.

Guichelaar, Teun, Maarten E. Emmelot, Henk Rozemuller, et al.. (2013). Human Regulatory T Cells Do Not Suppress the Antitumor Immunity in the Bone Marrow: A Role for Bone Marrow Stromal Cells in Neutralizing Regulatory T Cells. Clinical Cancer Research. 19(6). 1467–1475. 22 indexed citations

20.

Donk, Niels W.C.J. van de, Monique C. Minnema, Julie H. Huang, et al.. (2013). Accessory Cells of the Microenvironment Protect Multiple Myeloma from T-Cell Cytotoxicity through Cell Adhesion-Mediated Immune Resistance. Clinical Cancer Research. 19(20). 5591–5601. 51 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.

Explore authors with similar magnitude of impact