Article (Scientific journals)
Large-scale database mining reveals hidden trends and future directions for cancer immunotherapy.
Kather, Jakob Nikolas; Berghoff, Anna Sophie; Ferber, Dyke et al.
2018In Oncoimmunology, 7 (7), p. 1444412
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Keywords :
Cancer immunotherapy; checkpoint inhibition; database mining; gastrointestinal cancer; lung cancer; translational research
Abstract :
[en] Cancer immunotherapy has fundamentally changed the landscape of oncology in recent years and significant resources are invested into immunotherapy research. It is in the interests of researchers and clinicians to identify promising and less promising trends in this field in order to rationally allocate resources. This requires a quantitative large-scale analysis of cancer immunotherapy related databases. We developed a novel tool for text mining, statistical analysis and data visualization of scientific literature data. We used this tool to analyze 72002 cancer immunotherapy publications and 1469 clinical trials from public databases. All source codes are available under an open access license. The contribution of specific topics within the cancer immunotherapy field has markedly shifted over the years. We show that the focus is moving from cell-based therapy and vaccination towards checkpoint inhibitors, with these trends reaching statistical significance. Rapidly growing subfields include the combination of chemotherapy with checkpoint blockade. Translational studies have shifted from hematological and skin neoplasms to gastrointestinal and lung cancer and from tumor antigens and angiogenesis to tumor stroma and apoptosis. This work highlights the importance of unbiased large-scale database mining to assess trends in cancer research and cancer immunotherapy in particular. Researchers, clinicians and funding agencies should be aware of quantitative trends in the immunotherapy field, allocate resources to the most promising areas and find new approaches for currently immature topics.
Disciplines :
Oncology
Author, co-author :
Kather, Jakob Nikolas
Berghoff, Anna Sophie
Ferber, Dyke
Suarez-Carmona, Meggy ;  Université de Liège - ULiège
Reyes-Aldasoro, Constantino Carlos
Valous, Nektarios A.
Rojas-Moraleda, Rodrigo
Jager, Dirk
Halama, Niels
Language :
English
Title :
Large-scale database mining reveals hidden trends and future directions for cancer immunotherapy.
Publication date :
2018
Journal title :
Oncoimmunology
ISSN :
2162-4011
eISSN :
2162-402X
Publisher :
Landes Bioscience, United States - Pennsylvania
Volume :
7
Issue :
7
Pages :
e1444412
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 11 January 2019

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