Gabriel De Leon

1.1k total citations
17 papers, 641 citations indexed

About

Gabriel De Leon is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Gabriel De Leon has authored 17 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 8 papers in Immunology and 7 papers in Molecular Biology. Recurrent topics in Gabriel De Leon's work include Immunotherapy and Immune Responses (8 papers), RNA Interference and Gene Delivery (4 papers) and CAR-T cell therapy research (3 papers). Gabriel De Leon is often cited by papers focused on Immunotherapy and Immune Responses (8 papers), RNA Interference and Gene Delivery (4 papers) and CAR-T cell therapy research (3 papers). Gabriel De Leon collaborates with scholars based in United States, China and Canada. Gabriel De Leon's co-authors include Duane A. Mitchell, Elias Sayour, John H. Sampson, Roger E. McLendon, Jesse Kresak, Renée M. Reynolds, Nancy A. Krucher, Jianping Huang, Luis Sánchez-Pérez and Gary E. Archer and has published in prestigious journals such as Journal of Clinical Oncology, Nano Letters and PLoS ONE.

In The Last Decade

Gabriel De Leon

16 papers receiving 635 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gabriel De Leon United States 9 323 298 260 174 101 17 641
Neha Kamran United States 15 503 1.6× 307 1.0× 297 1.1× 231 1.3× 150 1.5× 23 920
Hillary G. Caruso United States 8 297 0.9× 539 1.8× 276 1.1× 123 0.7× 234 2.3× 14 813
Brett Schrand United States 12 291 0.9× 272 0.9× 382 1.5× 103 0.6× 158 1.6× 17 795
Ralph Venhaus United States 14 555 1.7× 443 1.5× 302 1.2× 103 0.6× 50 0.5× 44 888
Kyle Dyson United States 11 296 0.9× 425 1.4× 227 0.9× 74 0.4× 220 2.2× 19 796
Akihito Inagaki United States 11 166 0.5× 336 1.1× 287 1.1× 221 1.3× 50 0.5× 18 677
Wei Rui China 8 223 0.7× 433 1.5× 272 1.0× 97 0.6× 174 1.7× 8 754
Jill E. Dusak United States 10 458 1.4× 325 1.1× 245 0.9× 166 1.0× 29 0.3× 11 680
Andrea Muscat Australia 11 232 0.7× 384 1.3× 473 1.8× 299 1.7× 65 0.6× 15 970
Catherine Flores United States 9 243 0.8× 235 0.8× 148 0.6× 189 1.1× 50 0.5× 15 426

Countries citing papers authored by Gabriel De Leon

Since Specialization
Citations

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

Fields of papers citing papers by Gabriel De Leon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gabriel De Leon. 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 Gabriel De Leon. The network helps show where Gabriel De Leon may publish in the future.

Co-authorship network of co-authors of Gabriel De Leon

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

All Works

17 of 17 papers shown
1.
Leon, Gabriel De, Feng Chen, Tuo Zhang, et al.. (2025). An ultrasmall core–shell silica nanoparticle improves antitumour immunity and survival by remodelling suppressive melanoma microenvironments. Nature Nanotechnology. 21(2). 311–322.
2.
Sayour, Elias, Adam Grippin, Gabriel De Leon, et al.. (2018). Personalized Tumor RNA Loaded Lipid-Nanoparticles Prime the Systemic and Intratumoral Milieu for Response to Cancer Immunotherapy. Nano Letters. 18(10). 6195–6206. 69 indexed citations
3.
Sayour, Elias, Adam Grippin, Gabriel De Leon, et al.. (2018). MBRS-02. PERSONALIZED IMMUNOTHERAPY WITH TRANSLATABLE RNA NANOPARTICLES TARGETING MEDULLOBLASTOMA. Neuro-Oncology. 20(suppl_2). i128–i129. 2 indexed citations
4.
Mu, Luyan, Yu Long, Changlin Yang, et al.. (2018). The IDH1 Mutation-Induced Oncometabolite, 2-Hydroxyglutarate, May Affect DNA Methylation and Expression of PD-L1 in Gliomas. Frontiers in Molecular Neuroscience. 11. 62 indexed citations
5.
Sayour, Elias, et al.. (2017). IMMU-63. OVERCOMING GLIOBLASTOMA RESISTANCE TO IMMUNE CHECKPOINT BLOCKADE VIA RNA-LOADED NANOPARTICLES. Neuro-Oncology. 19(suppl_6). vi126–vi127. 2 indexed citations
6.
Yang, Changlin, Haitao Ge, Linchun Jin, et al.. (2017). CD70 as a critical mediator of tumor progression and immunosuppression in gliomas.. Journal of Clinical Oncology. 35(7_suppl). 18–18. 1 indexed citations
7.
Jin, Linchun, Haitao Ge, Changlin Yang, et al.. (2017). CD70 as a novel target of CAR-T-cell therapy for gliomas.. Journal of Clinical Oncology. 35(7_suppl). 148–148. 2 indexed citations
8.
Sayour, Elias, Gabriel De Leon, Christina Pham, et al.. (2016). IMST-16. TRANSLATABLE RNA NANOPARTICLES SUPPLANT DENDRITIC CELL VACCINES IN CELLULAR IMMUNOTHERAPY. Neuro-Oncology. 18(suppl_6). vi89–vi89. 2 indexed citations
9.
Hoang-Minh, Lan, Loic P. Deleyrolle, Dorit Siebzehnrubl, et al.. (2016). Disruption of KIF3A in patient-derived glioblastoma cells: effects on ciliogenesis, hedgehog sensitivity, and tumorigenesis. Oncotarget. 7(6). 7029–7043. 24 indexed citations
10.
Sayour, Elias, Gabriel De Leon, Christina Pham, et al.. (2016). Systemic activation of antigen-presenting cells via RNA-loaded nanoparticles. OncoImmunology. 6(1). e1256527–e1256527. 74 indexed citations
11.
Sayour, Elias, Roger E. McLendon, Gabriel De Leon, et al.. (2015). Increased proportion of FoxP3+ regulatory T cells in tumor infiltrating lymphocytes is associated with tumor recurrence and reduced survival in patients with glioblastoma. Cancer Immunology Immunotherapy. 64(4). 419–427. 159 indexed citations
12.
Nair, Smita K., Gabriel De Leon, David Boczkowski, et al.. (2014). Recognition and Killing of Autologous, Primary Glioblastoma Tumor Cells by Human Cytomegalovirus pp65-Specific Cytotoxic T Cells. Clinical Cancer Research. 20(10). 2684–2694. 74 indexed citations
13.
Choi, Bryan D., Carter M. Suryadevara, Luis Sánchez-Pérez, et al.. (2014). EGFRvIII-Specific Chimeric Antigen Receptor T Cells Migrate to and Kill Tumor Deposits Infiltrating the Brain Parenchyma in an Invasive Xenograft Model of Glioblastoma. PLoS ONE. 9(4). e94281–e94281. 96 indexed citations
14.
Nair, Smita K., Gabriel De Leon, David Boczkowski, et al.. (2013). Targeting cytomegalovirus (CMV) antigens for GBM immunotherapy. Journal for ImmunoTherapy of Cancer. 1(S1). 1 indexed citations
15.
Sánchez-Pérez, Luis, et al.. (2012). Immunotherapy with Tumor Vaccines for the Treatment of Malignant Gliomas. Current Drug Discovery Technologies. 9(4). 237–255. 4 indexed citations
16.
Leon, Gabriel De, et al.. (2008). Reduced expression of PNUTS leads to activation of Rb-phosphatase and caspase-mediated apoptosis. Cancer Biology & Therapy. 7(6). 833–841. 36 indexed citations
17.
Krucher, Nancy A., et al.. (2006). Dephosphorylation of Rb (Thr-821) in response to cell stress. Experimental Cell Research. 312(15). 2757–2763. 33 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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