Maksim Mamonkin

3.8k total citations
59 papers, 2.1k citations indexed

About

Maksim Mamonkin is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Maksim Mamonkin has authored 59 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Oncology, 32 papers in Immunology and 26 papers in Molecular Biology. Recurrent topics in Maksim Mamonkin's work include CAR-T cell therapy research (56 papers), Immune Cell Function and Interaction (27 papers) and Viral Infectious Diseases and Gene Expression in Insects (16 papers). Maksim Mamonkin is often cited by papers focused on CAR-T cell therapy research (56 papers), Immune Cell Function and Interaction (27 papers) and Viral Infectious Diseases and Gene Expression in Insects (16 papers). Maksim Mamonkin collaborates with scholars based in United States, Germany and Portugal. Maksim Mamonkin's co-authors include Malcolm K. Brenner, Rayne H. Rouce, Madhuwanti Srinivasan, Haruko Tashiro, Diogo Gomes‐Silva, Sandhya Sharma, Feiyan Mo, H. Daniel Lacorazza, Cliona M. Rooney and Timothy Davis and has published in prestigious journals such as Science, Journal of Clinical Oncology and Blood.

In The Last Decade

Maksim Mamonkin

58 papers receiving 2.1k citations

Peers

Maksim Mamonkin

ONCOL

IMMUN

GENET

Rayne H. Rouce United States

Barbara Camisa Italy

Antonio Di Stasi United States

Armin Ghobadi United States

Haruko Tashiro Japan

Sherry Adkins United States

Cindy Delbrook United States

Catherine Lindgren United States

Nicholas Tschernia United States

Rayne H. Rouce United States

Maksim Mamonkin

1.6k ×0.9

ONCOL

924 ×1.2

IMMUN

554 ×0.8

488 ×0.7

GENET

209 ×0.6

Citations per year, relative to Maksim Mamonkin Maksim Mamonkin (= 1×) peers Rayne H. Rouce

Countries citing papers authored by Maksim Mamonkin

Since Specialization

Citations

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

Fields of papers citing papers by Maksim Mamonkin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maksim Mamonkin

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

All Works

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20 of 20 papers shown

Shafer, Paul, Maksim Mamonkin, LaQuisa Hill, et al.. (2024). Targeting IDH2R140Q and other neoantigens in acute myeloid leukemia. Blood. 143(17). 1726–1737. 9 indexed citations

Iyer, Swaminathan P., Steven M. Horwitz, Salvia Jain, et al.. (2024). Confirmatory Efficacy and Safety Evaluation of MB-105, a CD5.CAR T Therapy: Multicenter Phase 2 Study in Patients with Relapsed/Refractory T Cell Lymphoma (R/R TCL). Blood. 144(Supplement 1). 7223–7223.

Ma, Royce, Mae Woods, Dayenne G. van Leeuwen, et al.. (2024). Chimeric antigen receptor-induced antigen loss protects CD5.CART cells from fratricide without compromising on-target cytotoxicity. Cell Reports Medicine. 5(7). 101628–101628. 5 indexed citations

Mamonkin, Maksim, et al.. (2024). SOHO State of the Art Updates and Next Questions | CAR T Cells in T Cell Acute Lymphoblastic Leukemia and Lymphoblastic Lymphoma. Clinical Lymphoma Myeloma & Leukemia. 25(2). 77–88. 1 indexed citations

Hill, LaQuisa, Rayne H. Rouce, Meng-Fen Wu, et al.. (2023). Antitumor efficacy and safety of unedited autologous CD5.CAR T cells in relapsed/refractory mature T-cell lymphomas. Blood. 143(13). 1231–1241. 30 indexed citations

Rouce, Rayne H., et al.. (2022). Apoptosis of Hematopoietic Stem Cells Contributes to Bone Marrow Suppression Following Chimeric Antigen Receptor T Cell Therapy. Transplantation and Cellular Therapy. 29(3). 165.e1–165.e7. 15 indexed citations

Zoine, Jaquelyn T., Jeremy Chase Crawford, Abishek Vaidya, et al.. (2022). Engineering naturally occurring CD7− T cells for the immunotherapy of hematological malignancies. Blood. 140(25). 2684–2696. 43 indexed citations

Rouce, Rayne H., LaQuisa Hill, Tyler S. Smith, et al.. (2021). Early Signals of Anti-Tumor Efficacy and Safety with Autologous CD5.CAR T-Cells in Patients with Refractory/Relapsed T-Cell Lymphoma. Blood. 138(Supplement 1). 654–654. 14 indexed citations

Watanabe, Norihiro & Maksim Mamonkin. (2021). Off-the-Shelf Chimeric Antigen Receptor T Cells. The Cancer Journal. 27(2). 176–181. 11 indexed citations

10.

Mo, Feiyan, Maksim Mamonkin, Malcolm K. Brenner, & Helen E. Heslop. (2021). Taking T-Cell Oncotherapy Off-the-Shelf. Trends in Immunology. 42(3). 261–272. 15 indexed citations

11.

Rathi, Purva, Linjie Guo, Amy N. Courtney, et al.. (2020). Glypican-3–Specific CAR T Cells Coexpressing IL15 and IL21 Have Superior Expansion and Antitumor Activity against Hepatocellular Carcinoma. Cancer Immunology Research. 8(3). 309–320. 193 indexed citations

12.

Olbrich, Henning, Sebastian J. Theobald, Andreas Schneider, et al.. (2020). Adult and Cord Blood-Derived High-Affinity gB-CAR-T Cells Effectively React Against Human Cytomegalovirus Infections. Human Gene Therapy. 31(7-8). 423–439. 26 indexed citations

13.

Hill, LaQuisa, Rayne H. Rouce, Tyler S. Smith, et al.. (2019). Safety and Anti-Tumor Activity of CD5 CAR T-Cells in Patients with Relapsed/Refractory T-Cell Malignancies. Blood. 134(Supplement_1). 199–199. 51 indexed citations

14.

Lulla, Premal, Maksim Mamonkin, & Malcolm K. Brenner. (2019). Adoptive Cell Therapy for Acute Myeloid Leukemia and T-Cell Acute Lymphoblastic Leukemia. The Cancer Journal. 25(3). 199–207. 7 indexed citations

15.

Brenner, Malcolm K., et al.. (2019). Chimeric Antigen Receptors for T-Cell Malignancies. Frontiers in Oncology. 9. 126–126. 46 indexed citations

16.

Mamonkin, Maksim, Malini Mukherjee, Madhuwanti Srinivasan, et al.. (2017). Reversible Transgene Expression Reduces Fratricide and Permits 4-1BB Costimulation of CAR T Cells Directed to T-cell Malignancies. Cancer Immunology Research. 6(1). 47–58. 79 indexed citations

17.

Gomes‐Silva, Diogo, Haruko Tashiro, Madhuwanti Srinivasan, et al.. (2017). Chimeric Antigen Receptor (CAR) T Cell Therapy for CD7-Positive Acute Myeloid Leukemia. Blood. 130. 2642–2642. 2 indexed citations

18.

Tashiro, Haruko, Tim Sauer, Thomas Shum, et al.. (2017). Treatment of Acute Myeloid Leukemia with T Cells Expressing Chimeric Antigen Receptors Directed to C-type Lectin-like Molecule 1. Molecular Therapy. 25(9). 2202–2213. 116 indexed citations

19.

Mamonkin, Maksim, et al.. (2013). Differential roles of KLF4 in the development and differentiation of CD8+ T cells. Immunology Letters. 156(1-2). 94–101. 18 indexed citations

20.

Yamada, Takeshi, Chun Shik Park, Maksim Mamonkin, & H. Daniel Lacorazza. (2009). Transcription factor ELF4 controls the proliferation and homing of CD8+ T cells via the Krüppel-like factors KLF4 and KLF2. Nature Immunology. 10(6). 618–626. 115 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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