Immunogenomics: using genomics to personalize cancer immunotherapy

Immunogenomics: using genomics to personalize cancer immunotherapy While the use of genomic data has the potential to revolutionize patient care, there is still much work to be done with regard to the transformation of host-tumor interactions into favorable clinical outcomes for our patients. High-throughput technologies, such as next-generation sequencing (NGS), have rapidly advanced our understanding of oncology, and we are learning that most tumors do not simply possess consistently mutated genes that are responsible for tumorigenesis, facilitating the need for personalized cancer therapy. A T cell-dependent mechanism of cancer progression was discovered in 2012, providing a potential link to cancer immunotherapy. Since then, an antibody against cytotoxic T lymphocyte-associated molecule-4 (CTLA-4), ipilimumab, and three programmed death-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitors, pembrolizumab (Keytruda), nivolumab (Opdivo), and atezolizumab (Tecentriq), were approved by the Food and Drug Administration (FDA) in the USA. In this review article, based on evidence that has been emerging in the literature over the last decade, we will discuss the basis for including genomic data in immunotherapy regimens, the current progress in identifying biomarkers targetable by immune checkpoint blockade, and the application of these therapies in modern oncology programs. Going forward, the clinical application of NGS in personalized oncology programs could include dose monitoring and adjustment or the development of individualized vaccines or other personalized therapies based on the mutational landscape. The continued identification of new neoantigens and the efficient mobilization of tumor-reactive lymphocytes in patients with cancer will promote the advancement of immunotherapy using personalized NGS-guided technologies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Virchows Archiv Springer Journals

Immunogenomics: using genomics to personalize cancer immunotherapy

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag Berlin Heidelberg
Subject
Medicine & Public Health; Pathology
ISSN
0945-6317
eISSN
1432-2307
D.O.I.
10.1007/s00428-017-2140-0
Publisher site
See Article on Publisher Site

Abstract

While the use of genomic data has the potential to revolutionize patient care, there is still much work to be done with regard to the transformation of host-tumor interactions into favorable clinical outcomes for our patients. High-throughput technologies, such as next-generation sequencing (NGS), have rapidly advanced our understanding of oncology, and we are learning that most tumors do not simply possess consistently mutated genes that are responsible for tumorigenesis, facilitating the need for personalized cancer therapy. A T cell-dependent mechanism of cancer progression was discovered in 2012, providing a potential link to cancer immunotherapy. Since then, an antibody against cytotoxic T lymphocyte-associated molecule-4 (CTLA-4), ipilimumab, and three programmed death-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitors, pembrolizumab (Keytruda), nivolumab (Opdivo), and atezolizumab (Tecentriq), were approved by the Food and Drug Administration (FDA) in the USA. In this review article, based on evidence that has been emerging in the literature over the last decade, we will discuss the basis for including genomic data in immunotherapy regimens, the current progress in identifying biomarkers targetable by immune checkpoint blockade, and the application of these therapies in modern oncology programs. Going forward, the clinical application of NGS in personalized oncology programs could include dose monitoring and adjustment or the development of individualized vaccines or other personalized therapies based on the mutational landscape. The continued identification of new neoantigens and the efficient mobilization of tumor-reactive lymphocytes in patients with cancer will promote the advancement of immunotherapy using personalized NGS-guided technologies.

Journal

Virchows ArchivSpringer Journals

Published: May 20, 2017

References

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