George S. Laszlo

1.3k total citations
35 papers, 814 citations indexed

About

George S. Laszlo is a scholar working on Oncology, Molecular Biology and Hematology. According to data from OpenAlex, George S. Laszlo has authored 35 papers receiving a total of 814 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Oncology, 21 papers in Molecular Biology and 10 papers in Hematology. Recurrent topics in George S. Laszlo's work include CAR-T cell therapy research (11 papers), Acute Myeloid Leukemia Research (10 papers) and Immune Cell Function and Interaction (8 papers). George S. Laszlo is often cited by papers focused on CAR-T cell therapy research (11 papers), Acute Myeloid Leukemia Research (10 papers) and Immune Cell Function and Interaction (8 papers). George S. Laszlo collaborates with scholars based in United States, South Africa and Switzerland. George S. Laszlo's co-authors include Roland B. Walter, Elihu H. Estey, Kimberly H. Harrington, Chelsea J. Gudgeon, Jonathan A. Cooper, Angus M. Sinclair, Kathryn J. Newhall, Stanley R. Frankel, Roman Kischel and Neil M. Nathanson and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

George S. Laszlo

30 papers receiving 806 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
George S. Laszlo United States 15 435 401 224 208 97 35 814
Zijie Feng China 16 530 1.2× 436 1.1× 129 0.6× 110 0.5× 97 1.0× 33 958
Francesco Lanza Italy 15 292 0.7× 205 0.5× 116 0.5× 159 0.8× 60 0.6× 31 809
Andreas Enns Germany 9 506 1.2× 289 0.7× 126 0.6× 137 0.7× 48 0.5× 9 889
Tad Kornaga United States 8 400 0.9× 250 0.6× 119 0.5× 359 1.7× 127 1.3× 12 870
Cecilia Carpio Spain 15 214 0.5× 388 1.0× 110 0.5× 197 0.9× 60 0.6× 55 774
Leah DiMascio United States 7 504 1.2× 206 0.5× 253 1.1× 184 0.9× 49 0.5× 11 896
Nadja Zaborsky Austria 18 283 0.7× 336 0.8× 102 0.5× 386 1.9× 69 0.7× 49 945
Christina Krupka Germany 13 398 0.9× 861 2.1× 502 2.2× 594 2.9× 113 1.2× 25 1.3k
Paula B. van Hennik Netherlands 18 426 1.0× 200 0.5× 330 1.5× 243 1.2× 152 1.6× 35 935
Alexis Dumortier Switzerland 8 549 1.3× 146 0.4× 297 1.3× 318 1.5× 43 0.4× 8 1.0k

Countries citing papers authored by George S. Laszlo

Since Specialization
Citations

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

Fields of papers citing papers by George S. Laszlo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by George S. Laszlo. 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 George S. Laszlo. The network helps show where George S. Laszlo may publish in the future.

Co-authorship network of co-authors of George S. Laszlo

This figure shows the co-authorship network connecting the top 25 collaborators of George S. Laszlo. A scholar is included among the top collaborators of George S. Laszlo 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 George S. Laszlo. George S. Laszlo 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.
Petty, Nicholas, Stefan Radtke, Olivier Humbert, et al.. (2025). Protection of CD33-modified hematopoietic stem cell progeny from CD33-directed CAR T cells in rhesus macaques. Blood Advances. 9(10). 2367–2378.
2.
Laszlo, George S., Patrick A. Zweidler‐McKay, Eduardo Rodríguez‐Arbolí, et al.. (2025). Preclinical characterization of the anti-leukemia activity of the CD123 antibody-drug conjugate, pivekimab sunirine (IMGN632). Leukemia. 39(5). 1243–1246. 1 indexed citations
3.
Laszlo, George S., et al.. (2024). Optimizing Siglec-8-Directed Immunotherapy for Eosinophilic and Mast Cell Disorders. Cancers. 16(20). 3476–3476. 1 indexed citations
4.
5.
6.
Laszlo, George S., Erik L. Kimble, Tinh-Doan Phi, et al.. (2024). Targeting the membrane-proximal C2-set domain of CD33 for improved CAR T cell therapy. SHILAP Revista de lepidopterología. 32(3). 200854–200854. 5 indexed citations
7.
Laszlo, George S., Brenda M. Sandmaier, Johnnie J. Orozco, et al.. (2023). [ 211 At]astatine-based anti-CD22 radioimmunotherapy for B-cell malignancies. Leukemia & lymphoma. 64(7). 1335–1339. 2 indexed citations
8.
Petty, Nicholas, Stefan Radtke, Olivier Humbert, et al.. (2023). Efficient long-term multilineage engraftment of CD33-edited hematopoietic stem/progenitor cells in nonhuman primates. Molecular Therapy — Methods & Clinical Development. 31. 101121–101121. 7 indexed citations
9.
Laszlo, George S., Johnnie J. Orozco, Donald K. Hamlin, et al.. (2022). Development of [211At]astatine-based anti-CD123 radioimmunotherapy for acute leukemias and other CD123+ malignancies. Leukemia. 36(6). 1485–1491. 15 indexed citations
10.
Godwin, Colin D., George S. Laszlo, Tinh-Doan Phi, et al.. (2021). Targeting the membrane-proximal C2-set domain of CD33 for improved CD33-directed immunotherapy. Leukemia. 35(9). 2496–2507. 12 indexed citations
11.
Sun, Xiaoyan, Hongsheng Qi, Xiuzhen Zhang, et al.. (2018). Src activation decouples cell division orientation from cell geometry in mammalian cells. Biomaterials. 170. 82–94. 1 indexed citations
12.
13.
Laszlo, George S., Todd A. Alonzo, Chelsea J. Gudgeon, et al.. (2015). Multimerin-1 ( MMRN1 ) as Novel Adverse Marker in Pediatric Acute Myeloid Leukemia: A Report from the Children's Oncology Group. Clinical Cancer Research. 21(14). 3187–3195. 20 indexed citations
14.
Laszlo, George S., Todd A. Alonzo, Chelsea J. Gudgeon, et al.. (2015). High expression of myocyte enhancer factor 2C (MEF2C) is associated with adverse-risk features and poor outcome in pediatric acute myeloid leukemia: a report from the Children’s Oncology Group. Journal of Hematology & Oncology. 8(1). 115–115. 41 indexed citations
15.
Harrington, Kimberly H., Chelsea J. Gudgeon, George S. Laszlo, et al.. (2015). The Broad Anti-AML Activity of the CD33/CD3 BiTE Antibody Construct, AMG 330, Is Impacted by Disease Stage and Risk. PLoS ONE. 10(8). e0135945–e0135945. 49 indexed citations
16.
Laszlo, George S., Elihu H. Estey, & Roland B. Walter. (2014). The past and future of CD33 as therapeutic target in acute myeloid leukemia. Blood Reviews. 28(4). 143–153. 146 indexed citations
17.
Teckchandani, Anjali, et al.. (2013). Cullin5 destabilizes Cas to inhibit Src-dependent cell transformation. Journal of Cell Science. 127(Pt 3). 509–20. 24 indexed citations
18.
Laszlo, George S., et al.. (2006). Multiple promoter elements required for leukemia inhibitory factor‐stimulated M2 muscarinic acetylcholine receptor promoter activity. Journal of Neurochemistry. 98(4). 1302–1315. 2 indexed citations
19.
Gibson, Robin M., George S. Laszlo, & Neil M. Nathanson. (2005). Calmodulin-dependent protein kinases phosphorylate gp130 at the serine-based dileucine internalization motif. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1714(1). 56–62. 14 indexed citations
20.
Amieux, Paul S., Douglas G. Howe, David C. Lee, et al.. (2002). Increased Basal cAMP-dependent Protein Kinase Activity Inhibits the Formation of Mesoderm-derived Structures in the Developing Mouse Embryo. Journal of Biological Chemistry. 277(30). 27294–27304. 93 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

Breakdown of academic impact, for papers by Zijie Feng Breakdown of academic impact, for papers by Francesco Lanza Breakdown of academic impact, for papers by Andreas Enns Breakdown of academic impact, for papers by Tad Kornaga Breakdown of academic impact, for papers by Cecilia Carpio Breakdown of academic impact, for papers by Leah DiMascio Breakdown of academic impact, for papers by Nadja Zaborsky Breakdown of academic impact, for papers by Christina Krupka Breakdown of academic impact, for papers by Paula B. van Hennik Breakdown of academic impact, for papers by Alexis Dumortier
Rankless by CCL
2026