ArticleCancer immunology, immunotherapy : CII2016
Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models.
Article in Cancer immunology, immunotherapy : CII, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- High PD-L1 expression in the tumour cells did not correlate with poor prognosis of patients suffering for oral squamous cells carcinoma: A meta-analysis of the literature.Cell proliferation · 2019Pooled it
- Morphometric analysis of nuclear shape irregularity as a novel predictor of programmed death-ligand 1 expression in lung squamous cell carcinoma.Virchows Archiv : an international journal of pathology · 2024Article
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- Epigenetic derepression converts PPARγ into a druggable target in triple-negative and endocrine-resistant breast cancers.Cell death discovery · 2021Article
- HBD3 Induces PD-L1 Expression on Head and Neck Squamous Cell Carcinoma Cell Lines.Antibiotics (Basel, Switzerland) · 2019Article
- Glycogen synthase kinase-3 beta inhibitors protectagainst the acute lung injuries resulting from acute necrotizing pancreatitis.Acta cirurgica brasileira · 2019Article
- Computational Models Accurately Predict Multi-Cell Biomarker Profiles in Inflammation and Cancer.Scientific reports · 2019Article
- Predicting response to BET inhibitors using computational modeling: A BEAT AML project study.Leukemia research · 2019Article
- Matrix metalloproteinase (MMP) and immunosuppressive biomarker profiles of seven head and neck squamous cell carcinoma (HNSCC) cell lines.Translational cancer research · 2018Article
- Human beta defensin 3 alters matrix metalloproteinase production in human dendritic cells exposed to Porphyromonas gingivalis hemagglutinin B.Journal of periodontology · 2018Article
- Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy.BMC cancer · 2018Article
- Cell genomics and immunosuppressive biomarker expression influence PD-L1 immunotherapy treatment responses in HNSCC-a computational study.Oral surgery, oral medicine, oral pathology and oral radiology · 2017Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
Abstract
purposeInteraction of the programmed death-1 (PD-1) co-receptor on T cells with the programmed death-ligand 1 (PD-L1) on tumor cells can lead to immunosuppression, a key event in the pathogenesis of many tumors. Thus, determining the amount of PD-L1 in tumors by immunohistochemistry (IHC) is important as both a diagnostic aid and a clinical predictor of immunotherapy treatment success. Because IHC reactivity can vary, we developed computational simulation models to accurately predict PD-L1 expression as a complementary assay to affirm IHC reactivity.
methodsMultiple myeloma (MM) and oral squamous cell carcinoma (SCC) cell lines were modeled as examples of our approach. Non-transformed cell models were first simulated to establish non-tumorigenic control baselines. Cell line genomic aberration profiles, from next-generation sequencing (NGS) information for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines, were introduced into the workflow to create cancer cell line-specific simulation models. Percentage changes of PD-L1 expression with respect to control baselines were determined and verified against observed PD-L1 expression by ELISA, IHC, and flow cytometry on the same cells grown in culture.
resultThe observed PD-L1 expression matched the predicted PD-L1 expression for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines and clearly demonstrated that cell genomics play an integral role by influencing cell signaling and downstream effects on PD-L1 expression.
conclusionThis concept can easily be extended to cancer patient cells where an accurate method to predict PD-L1 expression would affirm IHC results and improve its potential as a biomarker and a clinical predictor of treatment success.
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