Journal article
Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy
BMC cancer, Vol.18(1), pp.225-225
02/27/2018
DOI: 10.1186/s12885-018-4134-y
PMCID: PMC5897943
PMID: 29486723
Abstract
Background: Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses.
Methods: We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses.
Results: Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses.
Conclusions: Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.
Details
- Title: Subtitle
- Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy
- Creators
- Kim A Brogden - 801 Newton Road, Iowa City, IA 52242 USADeepak Parashar - Whitefield, Bangalore, 560066 IndiaAndrea R Hallier - 5318 SC, Iowa City, IA 52242 USATerry Braun - 5318 SC, Iowa City, IA 52242 USAFang Qian - 801 Newton Road, Iowa City, IA 52242 USANaiyer A Rizvi - 177 Fort Washington Avenue, New York, NY 10032 USAAaron D Bossler - 200 Hawkins Dr., C606GH, Iowa City, IA 52242 USAMohammed M Milhem - Iowa City, IA 52242 USATimothy A Chan - New York, NY 10065 USATaher Abbasi - Cellworks Group, Inc., 2033 Gateway Place Suite 500, San Jose, CA 95110 USAShireen Vali - Cellworks Group, Inc., 2033 Gateway Place Suite 500, San Jose, CA 95110 USA
- Resource Type
- Journal article
- Publication Details
- BMC cancer, Vol.18(1), pp.225-225
- DOI
- 10.1186/s12885-018-4134-y
- PMID
- 29486723
- PMCID
- PMC5897943
- NLM abbreviation
- BMC Cancer
- ISSN
- 1471-2407
- eISSN
- 1471-2407
- Publisher
- BioMed Central; London
- Grant note
- R01 DE014390 / ;
- Language
- English
- Date published
- 02/27/2018
- Academic Unit
- Preventive and Community Dentistry; Roy J. Carver Department of Biomedical Engineering; Hematology, Oncology, and Blood & Marrow Transplantation; Pathology; Dental Research; Periodontics; Internal Medicine
- Record Identifier
- 9984047707302771
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