| Autor: |
Timothy Rajakumar, Rastislav Horos, Julia Jehn, Judith Schenz, Thomas Muley, Oana Pelea, Sarah Hofmann, Paul Kittner, Mustafa Kahraman, Marco Heuvelman, Tobias Sikosek, Jennifer Feufel, Jasmin Skottke, Dennis Nötzel, Franziska Hinkfoth, Kaja Tikk, Alberto Daniel-Moreno, Jessika Ceiler, Nathaniel Mercaldo, Florian Uhle, Sandra Uhle, Markus A. Weigand, Mariam Elshiaty, Fabienne Lusky, Hannah Schindler, Quentin Ferry, Tatjana Sauka-Spengler, Qianxin Wu, Klaus F. Rabe, Martin Reck, Michael Thomas, Petros Christopoulos, Bruno R. Steinkraus |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
npj Precision Oncology, Vol 6, Iss 1, Pp 1-13 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2397-768X |
| DOI: |
10.1038/s41698-022-00262-y |
| Popis: |
Abstract Immunotherapies have recently gained traction as highly effective therapies in a subset of late-stage cancers. Unfortunately, only a minority of patients experience the remarkable benefits of immunotherapies, whilst others fail to respond or even come to harm through immune-related adverse events. For immunotherapies within the PD-1/PD-L1 inhibitor class, patient stratification is currently performed using tumor (tissue-based) PD-L1 expression. However, PD-L1 is an accurate predictor of response in only ~30% of cases. There is pressing need for more accurate biomarkers for immunotherapy response prediction. We sought to identify peripheral blood biomarkers, predictive of response to immunotherapies against lung cancer, based on whole blood microRNA profiling. Using three well-characterized cohorts consisting of a total of 334 stage IV NSCLC patients, we have defined a 5 microRNA risk score (miRisk) that is predictive of overall survival following immunotherapy in training and independent validation (HR 2.40, 95% CI 1.37–4.19; P |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full text from SpringerLink