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Gene expression profiling to predict responsiveness to immunotherapy
Recent clinical successes with immunotherapy have resulted in expanding indications for cancer therapy. To enhance anti-tumor immune responses, and to better choose specific strategies matched to patient and tumor characteristics, genomic-driven precision immunotherapy will be necessary. Herein, we...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5386795/ https://www.ncbi.nlm.nih.gov/pubmed/27834354 http://dx.doi.org/10.1038/cgt.2016.63 |
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author | Jamieson, Nigel B. Maker, Ajay V. |
author_facet | Jamieson, Nigel B. Maker, Ajay V. |
author_sort | Jamieson, Nigel B. |
collection | PubMed |
description | Recent clinical successes with immunotherapy have resulted in expanding indications for cancer therapy. To enhance anti-tumor immune responses, and to better choose specific strategies matched to patient and tumor characteristics, genomic-driven precision immunotherapy will be necessary. Herein, we explore the role that tumor gene expression profiling (GEP) and transcriptome expression may play in the prediction of an immunotherapeutic response. Genetic markers associated with response to immunotherapy are addressed as they pertain to the tumor genomic landscape, the extent of DNA damage, tumor mutational load, and tumor-specific neoantigens. Furthermore, genetic markers associated with resistance to checkpoint blockade and relapse are reviewed. Finally, the utility of GEP to identify new tumor types for immunotherapy and implications for combinatorial strategies are summarized. |
format | Online Article Text |
id | pubmed-5386795 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
record_format | MEDLINE/PubMed |
spelling | pubmed-53867952017-05-11 Gene expression profiling to predict responsiveness to immunotherapy Jamieson, Nigel B. Maker, Ajay V. Cancer Gene Ther Article Recent clinical successes with immunotherapy have resulted in expanding indications for cancer therapy. To enhance anti-tumor immune responses, and to better choose specific strategies matched to patient and tumor characteristics, genomic-driven precision immunotherapy will be necessary. Herein, we explore the role that tumor gene expression profiling (GEP) and transcriptome expression may play in the prediction of an immunotherapeutic response. Genetic markers associated with response to immunotherapy are addressed as they pertain to the tumor genomic landscape, the extent of DNA damage, tumor mutational load, and tumor-specific neoantigens. Furthermore, genetic markers associated with resistance to checkpoint blockade and relapse are reviewed. Finally, the utility of GEP to identify new tumor types for immunotherapy and implications for combinatorial strategies are summarized. 2016-11-11 2017-03 /pmc/articles/PMC5386795/ /pubmed/27834354 http://dx.doi.org/10.1038/cgt.2016.63 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Jamieson, Nigel B. Maker, Ajay V. Gene expression profiling to predict responsiveness to immunotherapy |
title | Gene expression profiling to predict responsiveness to immunotherapy |
title_full | Gene expression profiling to predict responsiveness to immunotherapy |
title_fullStr | Gene expression profiling to predict responsiveness to immunotherapy |
title_full_unstemmed | Gene expression profiling to predict responsiveness to immunotherapy |
title_short | Gene expression profiling to predict responsiveness to immunotherapy |
title_sort | gene expression profiling to predict responsiveness to immunotherapy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5386795/ https://www.ncbi.nlm.nih.gov/pubmed/27834354 http://dx.doi.org/10.1038/cgt.2016.63 |
work_keys_str_mv | AT jamiesonnigelb geneexpressionprofilingtopredictresponsivenesstoimmunotherapy AT makerajayv geneexpressionprofilingtopredictresponsivenesstoimmunotherapy |