Marta Cuenca

486 total citations
21 papers, 335 citations indexed

About

Marta Cuenca is a scholar working on Immunology, Hematology and Oncology. According to data from OpenAlex, Marta Cuenca has authored 21 papers receiving a total of 335 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Immunology, 9 papers in Hematology and 8 papers in Oncology. Recurrent topics in Marta Cuenca's work include T-cell and B-cell Immunology (11 papers), Immune Cell Function and Interaction (11 papers) and Multiple Myeloma Research and Treatments (8 papers). Marta Cuenca is often cited by papers focused on T-cell and B-cell Immunology (11 papers), Immune Cell Function and Interaction (11 papers) and Multiple Myeloma Research and Treatments (8 papers). Marta Cuenca collaborates with scholars based in Netherlands, Spain and United States. Marta Cuenca's co-authors include Pablo Engel, Cox Terhorst, Jordi Sintes, Xavier Romero, Victor Peperzak, Monique C. Minnema, Árpád Lányi, Anne Slomp, Jianan Gong and Pieter Sonneveld and has published in prestigious journals such as The Journal of Experimental Medicine, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Marta Cuenca

19 papers receiving 334 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marta Cuenca Netherlands 9 183 123 85 74 30 21 335
Darlene Monlish United States 11 228 1.2× 135 1.1× 116 1.4× 68 0.9× 13 0.4× 25 387
Stefanie Bugl Germany 8 164 0.9× 85 0.7× 41 0.5× 66 0.9× 21 0.7× 14 291
Christine W. Bruggeman Netherlands 9 234 1.3× 152 1.2× 69 0.8× 62 0.8× 8 0.3× 14 415
Il‐Kyoo Park United States 7 297 1.6× 94 0.8× 90 1.1× 95 1.3× 16 0.5× 10 420
Maria Torp Larsen Denmark 8 189 1.0× 144 1.2× 30 0.4× 50 0.7× 23 0.8× 13 361
Olga Ignatovich United Kingdom 7 175 1.0× 187 1.5× 40 0.5× 43 0.6× 28 0.9× 12 366
Zonghong Shao China 12 228 1.2× 58 0.5× 197 2.3× 50 0.7× 16 0.5× 68 384
Sun-Ok Yoon United States 10 283 1.5× 87 0.7× 24 0.3× 58 0.8× 42 1.4× 14 409
Sachi Tsunemi Japan 8 167 0.9× 168 1.4× 37 0.4× 42 0.6× 11 0.4× 10 357
Carine Bosshard Switzerland 7 228 1.2× 41 0.3× 48 0.6× 53 0.7× 13 0.4× 8 308

Countries citing papers authored by Marta Cuenca

Since Specialization
Citations

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

Fields of papers citing papers by Marta Cuenca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marta Cuenca

This figure shows the co-authorship network connecting the top 25 collaborators of Marta Cuenca. A scholar is included among the top collaborators of Marta Cuenca 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 Marta Cuenca. Marta Cuenca 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.
Revilla, Sonia Aristín, Dedeke Rockx-Brouwer, Marc Falandt, et al.. (2025). Impact of 3D cell culture hydrogels derived from basement membrane extracts or nanofibrillar cellulose on CAR-T cell activation. iScience. 28(9). 113234–113234.
2.
Cuenca, Marta, et al.. (2023). Identifying clinical response to daratumumab therapy in relapsed/refractory multiple myeloma using a patient‐derived in vitro model. SHILAP Revista de lepidopterología. 5(1). 141–146. 1 indexed citations
3.
Cuenca, Marta, Alfonso Serrano del Valle, Gemma Azaceta, et al.. (2023). Dinaciclib synergizes with BH3 mimetics targeting BCL‐2 and BCL‐XL in multiple myeloma cell lines partially dependent on MCL‐1 and in plasma cells from patients. Molecular Oncology. 17(12). 2507–2525. 2 indexed citations
4.
Cuenca, Marta, et al.. (2021). Targeting B-cell maturation antigen increases sensitivity of multiple myeloma cells to MCL-1 inhibition. Haematologica. 107(4). 980–983. 4 indexed citations
5.
Cuenca, Marta, et al.. (2021). In Vitro Model to Predict Response to Daratumumab Therapy in Relapsed/Refractory Multiple Myeloma. Blood. 138(Supplement 1). 1568–1568. 1 indexed citations
6.
Cuenca, Marta & Victor Peperzak. (2021). Advances and Perspectives in the Treatment of B-Cell Malignancies. Cancers. 13(9). 2266–2266. 5 indexed citations
7.
Slomp, Anne, et al.. (2021). Direct P70S6K1 inhibition to replace dexamethasone in synergistic combination with MCL-1 inhibition in multiple myeloma. Blood Advances. 5(12). 2593–2607. 6 indexed citations
8.
Cañete, Pablo F., Rebecca A. Sweet, Paula González-Figueroa, et al.. (2019). Regulatory roles of IL-10–producing human follicular T cells. The Journal of Experimental Medicine. 216(8). 1843–1856. 64 indexed citations
9.
Wang, Ninghai, Cees E. van der Poel, Marta Cuenca, et al.. (2019). The Checkpoint Regulator SLAMF3 Preferentially Prevents Expansion of Auto-Reactive B Cells Generated by Graft-vs.-Host Disease. Frontiers in Immunology. 10. 831–831. 7 indexed citations
10.
Kalina, Tomáš, Karel Fišer, Martín Pérez‐Andrés, et al.. (2019). CD Maps—Dynamic Profiling of CD1–CD100 Surface Expression on Human Leukocyte and Lymphocyte Subsets. Frontiers in Immunology. 10. 2434–2434. 48 indexed citations
11.
Slomp, Anne, Jianan Gong, Marta Cuenca, et al.. (2019). Multiple myeloma with 1q21 amplification is highly sensitive to MCL-1 targeting. Blood Advances. 3(24). 4202–4214. 62 indexed citations
12.
Slomp, Anne, Jianan Gong, Marta Cuenca, et al.. (2019). Multiple myeloma with amplification of chromosome 1q is highly sensitive to MCL-1 targeting. Clinical Lymphoma Myeloma & Leukemia. 19(10). e49–e50. 1 indexed citations
13.
Fišer, Karel, Tomáš Kalina, Martín Pérez‐Andrés, et al.. (2019). CD Maps - Dynamic Profiling of CD1 to CD100 Surface Expression on Human Leukocyte and Lymphocyte Subsets. Blood. 134(Supplement_1). 4878–4878. 1 indexed citations
14.
Cuenca, Marta, et al.. (2019). CD38 and CD45 expression on plasma cells and response to daratumumab in Multiple Myeloma. Clinical Lymphoma Myeloma & Leukemia. 19(10). e164–e164.
15.
Angulo, Ana, et al.. (2019). Viral CD229 (Ly9) homologs as new manipulators of host immunity. Journal of Leukocyte Biology. 105(5). 947–954. 7 indexed citations
16.
Cuenca, Marta, Jordi Sintes, Árpád Lányi, & Pablo Engel. (2018). CD84 cell surface signaling molecule: An emerging biomarker and target for cancer and autoimmune disorders. Clinical Immunology. 204. 43–49. 31 indexed citations
17.
18.
Cuenca, Marta, et al.. (2017). Ly9 (SLAMF3) receptor differentially regulates iNKT cell development and activation in mice. European Journal of Immunology. 48(1). 99–105. 8 indexed citations
19.
Cuenca, Marta, Xavier Romero, Jordi Sintes, Cox Terhorst, & Pablo Engel. (2015). Targeting of Ly9 (CD229) Disrupts Marginal Zone and B1 B Cell Homeostasis and Antibody Responses. The Journal of Immunology. 196(2). 726–737. 17 indexed citations
20.
Cuenca, Marta, et al.. (2013). Ly9 (CD229) Cell-Surface Receptor is Crucial for the Development of Spontaneous Autoantibody Production to Nuclear Antigens. Frontiers in Immunology. 4. 225–225. 30 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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