Jay K. Mandula

688 total citations
8 papers, 164 citations indexed

About

Jay K. Mandula is a scholar working on Oncology, Immunology and Cancer Research. According to data from OpenAlex, Jay K. Mandula has authored 8 papers receiving a total of 164 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Oncology, 5 papers in Immunology and 2 papers in Cancer Research. Recurrent topics in Jay K. Mandula's work include Cancer Immunotherapy and Biomarkers (3 papers), Phagocytosis and Immune Regulation (2 papers) and CAR-T cell therapy research (2 papers). Jay K. Mandula is often cited by papers focused on Cancer Immunotherapy and Biomarkers (3 papers), Phagocytosis and Immune Regulation (2 papers) and CAR-T cell therapy research (2 papers). Jay K. Mandula collaborates with scholars based in United States, Canada and China. Jay K. Mandula's co-authors include Paulo C. Rodrı́guez, Camilla Salvagno, Juan R. Cubillos‐Ruiz, Roni J. Bollag, David H. Munn, Ramses Sadek, Rafał Pacholczyk, Thomas F. Cash, Theodore S. Johnson and Sudharshan Eathiraj and has published in prestigious journals such as Journal of Clinical Investigation, Immunity and Cancer Research.

In The Last Decade

Jay K. Mandula

6 papers receiving 164 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jay K. Mandula United States	5	62	62	47	39	28	8	164
Kevin Z. L. Wu United Kingdom	6	156 2.5×	25 0.4×	50 1.1×	45 1.2×	11 0.4×	6	207
Sofia Tyystjärvi Finland	6	101 1.6×	212 3.4×	16 0.3×	81 2.1×	23 0.8×	6	310
Polyxeni Bozatzi United Kingdom	5	229 3.7×	32 0.5×	50 1.1×	81 2.1×	13 0.5×	7	278
Isabella Rusciano Italy	9	186 3.0×	24 0.4×	64 1.4×	21 0.5×	19 0.7×	15	255
Rena Zheng United States	5	95 1.5×	68 1.1×	59 1.3×	14 0.4×	13 0.5×	9	262
Gürkan Mollaoglu United States	5	92 1.5×	63 1.0×	33 0.7×	101 2.6×	29 1.0×	5	222
Sarah M. Maritan Canada	7	90 1.5×	18 0.3×	52 1.1×	57 1.5×	14 0.5×	11	190
Gwenaële Garin France	6	127 2.0×	51 0.8×	35 0.7×	33 0.8×	11 0.4×	10	210
Aaron Rogers United States	4	123 2.0×	64 1.0×	52 1.1×	45 1.2×	8 0.3×	5	196
Małgorzata Kurkowiak Poland	8	121 2.0×	50 0.8×	11 0.2×	48 1.2×	18 0.6×	13	253

Countries citing papers authored by Jay K. Mandula

Since Specialization

Citations

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

Fields of papers citing papers by Jay K. Mandula

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay K. Mandula. 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 Jay K. Mandula. The network helps show where Jay K. Mandula may publish in the future.

Co-authorship network of co-authors of Jay K. Mandula

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

All Works

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8 of 8 papers shown

Wu, Bill X., Hakan Çam, Chelsea Bolyard, et al.. (2025). Targeting TGFβ docking receptor glycoprotein A repetitions predominant (GARP) via novel chimeric antigen receptor (CAR)-T cell platform to treat glioblastoma. Neuro-Oncology. 27(12). 3087–3103. 1 indexed citations

Zhou, Lei, Maria Velegraki, Yi Wang, et al.. (2024). Spatial and functional targeting of intratumoral Tregs reverses CD8+ T cell exhaustion and promotes cancer immunotherapy. Journal of Clinical Investigation. 134(14). 18 indexed citations

Li, Jiannong, Zhihua Chen, Paulo C. Rodrı́guez, et al.. (2023). Differential requirements for CD4+ T cells in the efficacy of the anti-PD-1+LAG-3 and anti-PD-1+CTLA-4 combinations in melanoma flank and brain metastasis models. Journal for ImmunoTherapy of Cancer. 11(12). e007239–e007239. 9 indexed citations

Li, Jiannong, et al.. (2023). Abstract 5109: The anti-PD1+anti-LAG3 and anti-CTLA4+anti-PD1 combinations have non-overlapping mechanisms of action in melanoma cranial and extra cranial metastases. Cancer Research. 83(7_Supplement). 5109–5109.

Mandula, Jay K., Darwin Chang, Rachel Jimenez, et al.. (2022). 944 Targeting of notch ligand Jagged2 in lung cancer cells drives anti-tumor immunity via notch-induced functional reprogramming of tumor-associated macrophages. Regular and Young Investigator Award Abstracts. A986–A986.

Salvagno, Camilla, Jay K. Mandula, Paulo C. Rodrı́guez, & Juan R. Cubillos‐Ruiz. (2022). Decoding endoplasmic reticulum stress signals in cancer cells and antitumor immunity. Trends in cancer. 8(11). 930–943. 67 indexed citations

Sharma, Madhav, Rafał Pacholczyk, Huidong Shi, et al.. (2021). Inhibition of the BTK-IDO-mTOR axis promotes differentiation of monocyte-lineage dendritic cells and enhances anti-tumor T cell immunity. Immunity. 54(10). 2354–2371.e8. 56 indexed citations

Mandula, Jay K. & Paulo C. Rodrı́guez. (2021). Tumor-related stress regulates functional plasticity of MDSCs. Cellular Immunology. 363. 104312–104312. 13 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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