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Abstract miR-Blood is a high-quality, small RNA expression atlas for the major components of human peripheral blood (plasma, erythrocytes, thrombocytes, monocytes, neutrophils, eosinophils, basophils, natural killer cells, CD4+ T cells, CD8+ T cells, and B cells). Based on the purified blood components from 52 individuals, the dataset provides a comprehensive repository for the expression of 4971 small RNAs from eight non-coding RNA classes.

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

Introduction: Patients with advanced, non-oncogene-driven NSCLC with high programmed death-ligand 1 (PD-L1) expression are eligible for treatment with immunotherapy. There is, however, an urgent medical need for biomarkers identifying cases that require additional combination with chemotherapy. We previously uncovered a myeloid-based 5-microRNA (miRNA) signature that identified responders to immunotherapy in PD-L1 unstratified patients; however, its potential utility in treatment guidance for patients with PD-L1 high tumors remained unclear. Methods: We trained (n = 68) and validated (n = 56) a 5-miRNA multivariable Cox proportional hazards model predictive of overall survival on small RNA sequencing data of whole blood samples prospectively collected before the commencement of immunotherapy for stage IV NSCLC with PD-L1 tumor proportion score greater than or equal to 50%, treated with PD-1 inhibitor monotherapy (immunotherapy alone [IO]). Specificity was demonstrated in a control cohort treated with immunochemotherapy (ICT) (n = 31). Results: The revised 5-miRNA risk score (miRisk) stratified IO-treated patients and identified a high-risk group with significantly shorter overall survival (hazard ratio = 5.24, 95% confidence interval: 2.17–12.66, p < 0.001). There was a significant interaction between the miRisk score and type of treatment (IO or ICT, p = 0.036), indicating that the miRisk score may serve as a predictive biomarker for immunotherapy response. Furthermore, the miRisk score could identify a group of high-risk patients who may benefit from treatment with ICT as opposed to IO (hazard ratio = 0.35, 95% confidence interval: 0.15–0.82, p = 0.018). Conclusions: The miRisk score can distinguish a group of patients with PD-L1 high, stage IV NSCLC likely to benefit from adding chemotherapy to immunotherapy and may support treatment decisions as a blood-based complementary diagnostic.