Daniel S. Chen
Impact in
- Oncology top 0.02%
- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
- Immunology top 0.05%
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Immune cells in cancer
Papers in
- Oncology 31
- Cancer Immunotherapy and Biomarkers 26
- CAR-T cell therapy research 10
- Immunology 23
- Immunotherapy and Immune Responses 19
- Immune Cell Function and Interaction 6
- Immune cells in cancer 4
- Co-authors
- Ira Mellman (4 shared papers)Priti S. Hegde (6 shared papers)Napoleone Ferrara (1 shared paper)Rajendra S. Apte (1 shared paper)Thomas Powles (5 shared papers)Frank Stephen Hodi (4 shared papers)Bryan A. Irving (1 shared paper)Shannon J. Turley (1 shared paper)
- Journals
- Clinical Cancer Research (5 papers)Journal for ImmunoTherapy of Cancer (5 papers)Nature (4 papers)Immunity (4 papers)PLoS ONE (2 papers)
- Partner nations
- United StatesUnited KingdomSpain
In The Last Decade
Daniel S. Chen
47 papers receiving 35.6k citations
Daniel S. Chen's Hit Papers
Peers
Comparison fields: 5 of 145
- Oncology 21.3k
- Immunology 12.1k
- Cancer Research 3.7k
- Pulmonary and Respiratory Medicine 7.3k
- Molecular Biology 7.1k
Countries citing papers authored by Daniel S. Chen
This map shows the geographic impact of Daniel S. Chen'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 Daniel S. Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel S. Chen more than expected).
Fields of papers citing papers by Daniel S. Chen
This network shows the impact of papers produced by Daniel S. Chen. 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 Daniel S. Chen. The network helps show where Daniel S. Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel S. Chen, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Oncology Meets Immunology: The Cancer-Immunity Cycle Hit paper breakdown → | 2013 | 5437 |
| 2 | Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients Hit paper breakdown → | 2014 | 4417 |
| 3 | Elements of cancer immunity and the cancer–immune set point Hit paper breakdown → | 2017 | 4076 |
| 4 | TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Hit paper breakdown → | 2018 | 4038 |
| 5 | Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial Hit paper breakdown → | 2016 | 3949 |
| 6 | Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer (POPLAR): a multicentre, open-label, phase 2 randomised controlled trial Hit paper breakdown → | 2016 | 2372 |
| 7 | VEGF in Signaling and Disease: Beyond Discovery and Development Hit paper breakdown → | 2019 | 2092 |
| 8 | MPDL3280A (anti-PD-L1) treatment leads to clinical activity in metastatic bladder cancer Hit paper breakdown → | 2014 | 2018 |
| 9 | Top 10 Challenges in Cancer Immunotherapy Hit paper breakdown → | 2020 | 1632 |
| 10 | Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma Hit paper breakdown → | 2018 | 1011 |
| 11 | The cancer-immunity cycle: Indication, genotype, and immunotype Hit paper breakdown → | 2023 | 627 |
| 12 | Atezolizumab in combination with bevacizumab enhances antigen-specific T-cell migration in metastatic renal cell carcinoma Hit paper breakdown → | 2016 | 600 |
| 13 | Molecular Pathways: Next-Generation Immunotherapy—Inhibiting Programmed Death-Ligand 1 and Programmed Death-1 Hit paper breakdown → | 2012 | 534 |
| 14 | Immune escape to PD-L1/PD-1 blockade: seven steps to success (or failure) Hit paper breakdown → | 2016 | 529 |
| 15 | 2006 | 359 | |
| 16 | 2020 | 339 | |
| 17 | 2018 | 280 | |
| 18 | 2010 | 258 | |
| 19 | 2012 | 213 | |
| 20 | 2018 | 197 |
About Daniel S. Chen
Daniel S. Chen is a scholar working on Oncology, Immunology, Animal Science and Zoology, Infectious Diseases and Molecular Medicine, having authored 48 papers that have together received 36.4k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (26 papers), Immunotherapy and Immune Responses (19 papers), CAR-T cell therapy research (10 papers), Bladder and Urothelial Cancer Treatments (6 papers), Immune Cell Function and Interaction (6 papers), Immune cells in cancer (4 papers), Angiogenesis and VEGF in Cancer (4 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). The work is most often cited by research in Oncology (21.3k citations), Immunology (12.1k citations), Cancer Research (3.7k citations), Pulmonary and Respiratory Medicine (7.3k citations) and Molecular Biology (7.1k citations). Daniel S. Chen has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Ira Mellman, Priti S. Hegde, Napoleone Ferrara, Rajendra S. Apte, Thomas Powles, Frank Stephen Hodi, Bryan A. Irving, Shannon J. Turley, Marcus D. Ballinger and Gregg Daniel Fine. Their work appears in journals such as Clinical Cancer Research, Journal for ImmunoTherapy of Cancer, Nature, Immunity and PLoS ONE.
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.