Massimo D’Apuzzo
Impact in
- Oncology top 1%
- CAR-T cell therapy research
- Chemokine receptors and signaling
- Cancer Immunotherapy and Biomarkers
- Immunology top 2%
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
Papers in ⓘ
- Co-authors
- Behnam Badie (22 shared papers)Marcel Loetscher (3 shared papers)Marco Baggiolini (3 shared papers)Christine E. Brown (15 shared papers)Stephen J. Forman (17 shared papers)Michael E. Barish (15 shared papers)Leopoldo Angrisani (12 shared papers)Renate Starr (12 shared papers)
- Journals
- Journal of Clinical Oncology (10 papers)IEEE Transactions on Instrumentation and Measurement (7 papers)Clinical Cancer Research (4 papers)Cancer Research (4 papers)Measurement (3 papers)
- Partner nations
- United StatesItalySwitzerland
In The Last Decade
Massimo D’Apuzzo
70 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Oncology 1.8k
- Immunology 1.2k
- Genetics 564
- Developmental Neuroscience 117
- Immunology and Allergy 113
Countries citing papers authored by Massimo D’Apuzzo
This map shows the geographic impact of Massimo D’Apuzzo'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 Massimo D’Apuzzo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo D’Apuzzo more than expected).
Fields of papers citing papers by Massimo D’Apuzzo
This network shows the impact of papers produced by Massimo D’Apuzzo. 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 Massimo D’Apuzzo. The network helps show where Massimo D’Apuzzo may publish in the future.
Co-authors
The 25 scholars most cited alongside Massimo D’Apuzzo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Bioactivity and Safety of IL13Rα2-Redirected Chimeric Antigen Receptor CD8+ T Cells in Patients with Recurrent Glioblastoma Hit paper breakdown → | 2015 | 592 |
| 2 | 1995 | 308 | |
| 3 | 1997 | 279 | |
| 4 | 2017 | 226 | |
| 5 | 2012 | 185 | |
| 6 | 2013 | 184 | |
| 7 | 2015 | 156 | |
| 8 | 2016 | 127 | |
| 9 | 2009 | 113 | |
| 10 | 2013 | 82 | |
| 11 | 2001 | 80 | |
| 12 | 1997 | 76 | |
| 13 | 1995 | 68 | |
| 14 | 2018 | 60 | |
| 15 | 2015 | 53 | |
| 16 | 2015 | 53 | |
| 17 | 2017 | 49 | |
| 18 | 2016 | 42 | |
| 19 | 1999 | 38 | |
| 20 | 2012 | 37 |
About Massimo D’Apuzzo
Massimo D’Apuzzo is a scholar working on Genetics, Oncology, Structural Biology, Biotechnology and Immunology, having authored 73 papers that have together received 3.3k indexed citations. Recurring topics across this work include CAR-T cell therapy research (15 papers), Glioma Diagnosis and Treatment (12 papers), Immune Cell Function and Interaction (7 papers), Cancer Research and Treatments (6 papers), Cancer Immunotherapy and Biomarkers (6 papers), Immunotherapy and Immune Responses (6 papers), Image and Signal Denoising Methods (6 papers) and Chemokine receptors and signaling (5 papers). The work is most often cited by research in Oncology (1.8k citations), Immunology (1.2k citations), Genetics (564 citations), Developmental Neuroscience (117 citations) and Immunology and Allergy (113 citations). Massimo D’Apuzzo has collaborated with scholars based in United States, Italy and Switzerland. Frequent co-authors include Behnam Badie, Marcel Loetscher, Marco Baggiolini, Christine E. Brown, Stephen J. Forman, Michael E. Barish, Leopoldo Angrisani, Renate Starr, Michael C. Jensen and Pasquale Daponte. Their work appears in journals such as Journal of Clinical Oncology, IEEE Transactions on Instrumentation and Measurement, Clinical Cancer Research, Cancer Research and Measurement.
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.