Samuel Haile

1.1k total citations · 1 hit paper
14 papers, 885 citations indexed

About

Samuel Haile is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Samuel Haile has authored 14 papers receiving a total of 885 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 7 papers in Immunology and 4 papers in Molecular Biology. Recurrent topics in Samuel Haile's work include CAR-T cell therapy research (10 papers), Immunotherapy and Immune Responses (5 papers) and Cancer Immunotherapy and Biomarkers (5 papers). Samuel Haile is often cited by papers focused on CAR-T cell therapy research (10 papers), Immunotherapy and Immune Responses (5 papers) and Cancer Immunotherapy and Biomarkers (5 papers). Samuel Haile collaborates with scholars based in United States, Germany and Switzerland. Samuel Haile's co-authors include Suzanne Ostrand‐Rosenberg, Lucas A. Horn, Skyler P. Rietberg, Esther Hulleman, Crystal L. Mackall, Meena Kadapakkam, Michelle Monje, Christopher Mount, Robbie G. Majzner and Louai Labanieh and has published in prestigious journals such as Nature Medicine, The Journal of Immunology and Cancer Research.

In The Last Decade

Samuel Haile

14 papers receiving 873 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.

Potent antitumor efficacy of anti-GD2 CAR T cells in H3-K27M+ diffuse midline gliomas

2018 361 citations Christopher Mount, Robbie G. Majzner et al. Nature Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Samuel Haile United States	10	559	366	202	188	154	14	885
Kevin Bielamowicz United States	12	471 0.8×	200 0.5×	160 0.8×	167 0.9×	203 1.3×	30	684
Selena Lorrey United States	9	373 0.7×	320 0.9×	230 1.1×	159 0.8×	98 0.6×	17	718
Christian Seitz Germany	11	338 0.6×	205 0.6×	246 1.2×	42 0.2×	63 0.4×	40	663
Long Hung United States	11	249 0.4×	116 0.3×	368 1.8×	122 0.6×	55 0.4×	13	712
Stephanie Mgebroff United States	12	1.4k 2.4×	698 1.9×	380 1.9×	43 0.2×	334 2.2×	24	1.7k
Han Dong United States	9	631 1.1×	749 2.0×	297 1.5×	27 0.1×	72 0.5×	20	1.1k
Carole Ramirez France	9	217 0.4×	103 0.3×	272 1.3×	203 1.1×	27 0.2×	23	704
Valentina S. Caputo United Kingdom	14	247 0.4×	221 0.6×	406 2.0×	36 0.2×	79 0.5×	31	822
Dana L. Schalk United States	13	294 0.5×	214 0.6×	170 0.8×	19 0.1×	52 0.3×	30	534
Greta Maria Paola Giordano Attianese Switzerland	14	565 1.0×	363 1.0×	219 1.1×	30 0.2×	85 0.6×	21	759

Countries citing papers authored by Samuel Haile

Since Specialization

Citations

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

Fields of papers citing papers by Samuel Haile

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel Haile

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

All Works

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14 of 14 papers shown

Simonetta, Federico, Juliane K. Lohmeyer, Toshihito Hirai, et al.. (2021). Allogeneic CAR Invariant Natural Killer T Cells Exert Potent Antitumor Effects through Host CD8 T-Cell Cross-Priming. Clinical Cancer Research. 27(21). 6054–6064. 44 indexed citations

Simonetta, Federico, Toshihito Hirai, Juliane K. Lohmeyer, et al.. (2020). Allogeneic Chimeric Antigen Receptor-Invariant Natural Killer T Cells Exert Both Direct and Indirect Antitumor Effects through Host CD8 T Cell Cross-Priming. Biology of Blood and Marrow Transplantation. 26(3). S42–S42. 1 indexed citations

Murty, Surya, Samuel Haile, Corinne Beinat, et al.. (2020). Intravital imaging reveals synergistic effect of CAR T-cells and radiation therapy in a preclinical immunocompetent glioblastoma model. OncoImmunology. 9(1). 1757360–1757360. 76 indexed citations

Mount, Christopher, Robbie G. Majzner, Shree Sundaresh, et al.. (2018). Potent antitumor efficacy of anti-GD2 CAR T cells in H3-K27M+ diffuse midline gliomas. Nature Medicine. 24(5). 572–579. 361 indexed citations breakdown →

Romain, Gabrielle, et al.. (2018). High-Throughput Flow Cytometric Method for the Simultaneous Measurement of CAR-T Cell Characterization and Cytotoxicity against Solid Tumor Cell Lines. SLAS DISCOVERY. 23(7). 603–612. 10 indexed citations

Mount, Christopher, Robbie G. Majzner, Shree Sundaresh, et al.. (2018). Abstract 958: Anti-GD2 chimeric antigen receptor T cells as a potent immunotherapy regimen in xenograft models of histone 3 K27M mutant diffuse midline glioma. Cancer Research. 78(13_Supplement). 958–958. 1 indexed citations

Haile, Samuel, Joe Conner, & Crystal L. Mackall. (2016). Abstract 2304: Attenuated oncolytic virus HSV1716 increases in vivo expansion of GD2- targeting CAR T cells in murine solid tumor models. Cancer Research. 76(14_Supplement). 2304–2304. 2 indexed citations

Haile, Samuel, Lucas A. Horn, & Suzanne Ostrand‐Rosenberg. (2014). A Soluble Form of CD80 Enhances Antitumor Immunity by Neutralizing Programmed Death Ligand-1 and Simultaneously Providing Costimulation. Cancer Immunology Research. 2(7). 610–615. 36 indexed citations

Ostrand‐Rosenberg, Suzanne, Lucas A. Horn, & Samuel Haile. (2014). The Programmed Death-1 Immune-Suppressive Pathway: Barrier to Antitumor Immunity. The Journal of Immunology. 193(8). 3835–3841. 181 indexed citations

10.

Haile, Samuel, et al.. (2013). Soluble CD80 Restores T Cell Activation and Overcomes Tumor Cell Programmed Death Ligand 1–Mediated Immune Suppression. The Journal of Immunology. 191(5). 2829–2836. 64 indexed citations

11.

Haile, Samuel, Lemu Golassa, & Zeleke Mekonnen. (2012). Prevalence of Schistosoma mansoni and effectiveness of Praziquantel in school children in Finchaa valley, Ethiopia. 4(3). 25–30. 20 indexed citations

12.

Haile, Samuel, et al.. (2011). Tumor cell Programmed Death Ligand-1-mediated T cell suppression is overcome by co-expression of CD80 (66.29). The Journal of Immunology. 186(1_Supplement). 66.29–66.29. 1 indexed citations

13.

Haile, Samuel, Jacobus J. Bosch, Minu K. Srivastava, et al.. (2011). Tumor Cell Programmed Death Ligand 1-Mediated T Cell Suppression Is Overcome by Coexpression of CD80. The Journal of Immunology. 186(12). 6822–6829. 70 indexed citations

14.

Yedjou, Clément G., et al.. (2010). N-acetyl-cysteine protects against DNA damage associated with lead toxicity in HepG2 cells.. PubMed. 20(1 Suppl 1). S1–101. 18 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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