Bringing the Next Generation of Immuno-Oncology Biomarkers to the Clinic
Open Access
- 1 February 2018
- journal article
- review article
- Published by MDPI AG in Biomedicines
- Vol. 6 (1), 14
- https://doi.org/10.3390/biomedicines6010014
Abstract
The recent successes in the use of immunotherapy to treat cancer have led to a multiplicity of new compounds in development. Novel clinical-grade biomarkers are needed to guide the choice of these agents to obtain the maximal likelihood of patient benefit. Predictive biomarkers for immunotherapy differ from the traditional biomarkers used for targeted therapies: the complexity of the immune response and tumour biology requires a more holistic approach than the use of a single analyte biomarker. This paper reviews novel biomarker approaches for the effective development of immune-oncology therapies, highlighting the promise of the advances in next-generation gene expression profiling that allow biologic information to be efficiently organized and interpreted for a maximum predictive value at the individual patient level.Keywords
This publication has 34 references indexed in Scilit:
- Utilizing the BiTE (bispecific T-cell engager) platform for immunotherapy of cancerExpert Opinion on Biological Therapy, 2015
- Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancerScience, 2015
- Genetic Basis for Clinical Response to CTLA-4 Blockade in MelanomaNew England Journal of Medicine, 2014
- Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patientsNature, 2014
- PD-1 blockade induces responses by inhibiting adaptive immune resistanceNature, 2014
- Association of PD-1, PD-1 Ligands, and Other Features of the Tumor Immune Microenvironment with Response to Anti–PD-1 TherapyClinical Cancer Research, 2014
- Exomics and immunogenicsOncoImmunology, 2014
- Oncology Meets Immunology: The Cancer-Immunity CycleImmunity, 2013
- Predictive Gene Signature in MAGE-A3 Antigen-Specific Cancer ImmunotherapyJournal of Clinical Oncology, 2013
- Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical OutcomeScience, 2006