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It’s a long way to the top (if you want to personalize immunotherapy)

Overview of attention for article published in Journal for Immunotherapy of Cancer, January 2017
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Title
It’s a long way to the top (if you want to personalize immunotherapy)
Published in
Journal for Immunotherapy of Cancer, January 2017
DOI 10.1186/s40425-016-0207-0
Pubmed ID
Authors

Sarah Haebe, Oliver Weigert

Abstract

Harnessing the immune system to attack tumor cells by targeting tumor-associated or -preferably- tumor-specific antigens has emerged as a promising but challenging treatment option for malignant lymphomas. Follicular lymphoma is among the most common lymphomas worldwide and remains incurable for most patients. Considered to be an immunogenic disease it represents an interesting disease entity for various immunotherapeutic approaches. In an article published in the May issue of Clinical Cancer Research, Nielsen and colleagues provided important proof-of-principle data on the immunogenicity of follicular lymphoma that might represent a first step towards personalized adoptive immunotherapies in this disease. The authors combined targeted next-generation sequencing and in silico analyses to explore the concept of somatic neoepitope prediction. Neoantigen-specific CD8(+) T-cells could be identified in a small subset of patients selected for in vitro immunogenicity experiments, however at remarkably low frequencies and in only a few patients at single time-points. Of note, the immunogenic neoepitopes were derived from mutant CREBBP and MEF2B, two genes that have previously been shown to be functionally and prognostically relevant in this disease. In this commentary we discuss the promises but also the challenges of how to translate these findings into clinical practice.

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Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 40%
Professor 3 15%
Student > Bachelor 2 10%
Professor > Associate Professor 2 10%
Student > Master 1 5%
Other 3 15%
Unknown 1 5%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 35%
Medicine and Dentistry 4 20%
Immunology and Microbiology 4 20%
Agricultural and Biological Sciences 2 10%
Business, Management and Accounting 1 5%
Other 2 10%