Blake T. Aftab

3.7k total citations
38 papers, 1.6k citations indexed

About

Blake T. Aftab is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Blake T. Aftab has authored 38 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Oncology, 23 papers in Molecular Biology and 7 papers in Immunology. Recurrent topics in Blake T. Aftab's work include CAR-T cell therapy research (11 papers), Hedgehog Signaling Pathway Studies (6 papers) and Multiple Myeloma Research and Treatments (5 papers). Blake T. Aftab is often cited by papers focused on CAR-T cell therapy research (11 papers), Hedgehog Signaling Pathway Studies (6 papers) and Multiple Myeloma Research and Treatments (5 papers). Blake T. Aftab collaborates with scholars based in United States, Australia and France. Blake T. Aftab's co-authors include Charles M. Rudin, Jun O. Liu, Rajiv Khanna, Irina Dobromilskaya, Ed Croze, Lawrence Steinman, Michael P. Pender, Hans‐Peter Hartung, Gavin Giovannoni and Manher Joshi and has published in prestigious journals such as Journal of Clinical Investigation, The Journal of Experimental Medicine and Journal of Clinical Oncology.

In The Last Decade

Blake T. Aftab

35 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Blake T. Aftab United States 18 839 676 369 320 188 38 1.6k
Meg R. Gerstenblith United States 17 1.2k 1.5× 929 1.4× 254 0.7× 246 0.8× 196 1.0× 35 2.1k
Magdalena Martinka Canada 26 1.2k 1.5× 728 1.1× 444 1.2× 348 1.1× 281 1.5× 62 2.3k
Jessica Dal Col Italy 20 469 0.6× 554 0.8× 550 1.5× 202 0.6× 131 0.7× 35 1.2k
Corina M. Borza United States 23 407 0.5× 833 1.2× 305 0.8× 292 0.9× 425 2.3× 29 1.7k
Gregory M. Hayes United States 19 593 0.7× 296 0.4× 340 0.9× 217 0.7× 132 0.7× 37 1.3k
Sheng Hou China 26 798 1.0× 533 0.8× 696 1.9× 93 0.3× 109 0.6× 73 1.8k
Yasuto Akiyama Japan 27 878 1.0× 937 1.4× 708 1.9× 166 0.5× 117 0.6× 128 2.2k
Sonia Minuzzo Italy 21 824 1.0× 397 0.6× 315 0.9× 159 0.5× 68 0.4× 49 1.5k
Kwun Wah Wen United States 14 460 0.5× 700 1.0× 434 1.2× 158 0.5× 553 2.9× 47 1.5k
Sheng-Bin Peng United States 20 954 1.1× 852 1.3× 358 1.0× 181 0.6× 37 0.2× 38 1.7k

Countries citing papers authored by Blake T. Aftab

Since Specialization
Citations

This map shows the geographic impact of Blake T. Aftab'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 Blake T. Aftab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Blake T. Aftab more than expected).

Fields of papers citing papers by Blake T. Aftab

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Blake T. Aftab. 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 Blake T. Aftab. The network helps show where Blake T. Aftab may publish in the future.

Co-authorship network of co-authors of Blake T. Aftab

This figure shows the co-authorship network connecting the top 25 collaborators of Blake T. Aftab. A scholar is included among the top collaborators of Blake T. Aftab 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 Blake T. Aftab. Blake T. Aftab 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.
Ding, Beibei, Melinda Au, Yvan H. Chanthery, et al.. (2023). 246 Disruption of the cytokine signaling checkpoint CIS enhances serial-killing and anti-tumor activity of CAR-engineered γδ T cells. SHILAP Revista de lepidopterología. A285–A285. 1 indexed citations
3.
Makkouk, Amani, Xue Yang, Anthony Lucas, et al.. (2021). Off-the-shelf Vδ1 gamma delta T cells engineered with glypican-3 (GPC-3)-specific chimeric antigen receptor (CAR) and soluble IL-15 display robust antitumor efficacy against hepatocellular carcinoma. Journal for ImmunoTherapy of Cancer. 9(12). e003441–e003441. 134 indexed citations
4.
Neller, Michelle A., Sriganesh Srihari, Pauline Crooks, et al.. (2020). Profiling HPV-16–specific T cell responses reveals broad antigen reactivities in oropharyngeal cancer patients. The Journal of Experimental Medicine. 217(10). 44 indexed citations
5.
Sherbenou, Daniel W., Su Yang, Christopher R. Behrens, et al.. (2020). Potent Activity of an Anti-ICAM1 Antibody–Drug Conjugate against Multiple Myeloma. Clinical Cancer Research. 26(22). 6028–6038. 18 indexed citations
6.
Ambalathingal, George, Ross S. Francis, Dillon Corvino, et al.. (2020). Proteome‐wide analysis of T‐cell response to BK polyomavirus in healthy virus carriers and kidney transplant recipients reveals a unique transcriptional and functional profile. Clinical & Translational Immunology. 9(1). e01102–e01102. 14 indexed citations
8.
Bar‐Or, Amit, Michael P. Pender, Rajiv Khanna, et al.. (2019). Epstein–Barr Virus in Multiple Sclerosis: Theory and Emerging Immunotherapies. Trends in Molecular Medicine. 26(3). 296–310. 184 indexed citations
11.
Ferguson, Ian, Megan Murnane, Hui Liu, et al.. (2018). Repurposing tofacitinib as an anti-myeloma therapeutic to reverse growth-promoting effects of the bone marrow microenvironment. Haematologica. 103(7). 1218–1228. 27 indexed citations
12.
Pender, Michael P., Peter A. Csurhes, Corey Smith, et al.. (2018). Epstein-Barr virus–specific T cell therapy for progressive multiple sclerosis. JCI Insight. 3(22). 110 indexed citations
13.
Sherbenou, Daniel W., Blake T. Aftab, Su Yang, et al.. (2016). Antibody-drug conjugate targeting CD46 eliminates multiple myeloma cells. Journal of Clinical Investigation. 126(12). 4640–4653. 83 indexed citations
14.
Li, Xiaokai, Teresa A. Colvin, Jennifer N. Rauch, et al.. (2015). Validation of the Hsp70–Bag3 Protein–Protein Interaction as a Potential Therapeutic Target in Cancer. Molecular Cancer Therapeutics. 14(3). 642–648. 101 indexed citations
15.
Rudin, Charles M., Julie R. Brahmer, Rosalyn A. Juergens, et al.. (2013). Phase 2 Study of Pemetrexed and Itraconazole as Second-Line Therapy for Metastatic Nonsquamous Non–Small-Cell Lung Cancer. Journal of Thoracic Oncology. 8(5). 619–623. 117 indexed citations
16.
Kim, James, Blake T. Aftab, Jean Y. Tang, et al.. (2013). Itraconazole and Arsenic Trioxide Inhibit Hedgehog Pathway Activation and Tumor Growth Associated with Acquired Resistance to Smoothened Antagonists. Cancer Cell. 23(1). 23–34. 271 indexed citations
17.
Wong, Harvey, Laurent Vernillet, Amy Peterson, et al.. (2012). Bridging the Gap between Preclinical and Clinical Studies Using Pharmacokinetic–Pharmacodynamic Modeling: An Analysis of GDC-0973, a MEK Inhibitor. Clinical Cancer Research. 18(11). 3090–3099. 65 indexed citations
18.
Zeng, Jing, Khaled Aziz, Sivarajan T. Chettiar, et al.. (2012). Hedgehog Pathway Inhibition Radiosensitizes Non-Small Cell Lung Cancers. International Journal of Radiation Oncology*Biology*Physics. 86(1). 143–149. 34 indexed citations
19.
Aftab, Blake T., Irina Dobromilskaya, Jun O. Liu, & Charles M. Rudin. (2011). Itraconazole Inhibits Angiogenesis and Tumor Growth in Non–Small Cell Lung Cancer. Cancer Research. 71(21). 6764–6772. 133 indexed citations
20.
Chenna, Venugopal, Chaoxin Hu, Dipankar Pramanik, et al.. (2011). A Polymeric Nanoparticle Encapsulated Small-Molecule Inhibitor of Hedgehog Signaling (NanoHHI) Bypasses Secondary Mutational Resistance to Smoothened Antagonists. Molecular Cancer Therapeutics. 11(1). 165–173. 69 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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