miR-Blood - a small RNA atlas of human blood components.

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.

Early Detection of Lung Cancer Using Small RNAs.

INTRODUCTION: Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting. METHODS: We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin. RESULTS: We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling. CONCLUSIONS: These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.

A blood-based miRNA signature with prognostic value for overall survival in advanced stage non-small cell lung cancer treated with immunotherapy.

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 < 0.01) cohorts. We have traced the signature to a myeloid origin and performed miRNA target prediction to make a direct mechanistic link to the PD-L1 signaling pathway and PD-L1 itself. The miRisk score offers a potential blood-based companion diagnostic for immunotherapy that outperforms tissue-based PD-L1 staining.

Cerebellar transcranial direct current stimulation interacts with BDNF Val66Met in motor learning.

BACKGROUND: Cerebellar transcranial direct current stimulation has been reported to enhance motor associative learning and motor adaptation, holding promise for clinical application in patients with movement disorders. However, behavioral benefits from cerebellar tDCS have been inconsistent. OBJECTIVE: Identifying determinants of treatment success is necessary. BDNF Val66Met is a candidate determinant, because the polymorphism is associated with motor skill learning and BDNF is thought to mediate tDCS effects. METHODS: We undertook two cerebellar tDCS studies in subjects genotyped for BDNF Val66Met. Subjects performed an eyeblink conditioning task and received sham, anodal or cathodal tDCS (N = 117, between-subjects design) or a vestibulo-ocular reflex adaptation task and received sham and anodal tDCS (N = 51 subjects, within-subjects design). Performance was quantified as a learning parameter from 0 to 100%. We investigated (1) the distribution of the learning parameter with mixture modeling presented as the mean (M), standard deviation (S) and proportion (P) of the groups, and (2) the role of BDNF Val66Met and cerebellar tDCS using linear regression presented as the regression coefficients (B) and odds ratios (OR) with equally-tailed intervals (ETIs). RESULTS: For the eyeblink conditioning task, we found distinct groups of learners (MLearner = 67.2%; SLearner = 14.7%; PLearner = 61.6%) and non-learners (MNon-learner = 14.2%; SNon-learner = 8.0%; PNon-learner = 38.4%). Carriers of the BDNF Val66Met polymorphism were more likely to be learners (OR = 2.7 [1.2 6.2]). Within the group of learners, anodal tDCS supported eyeblink conditioning in BDNF Val66Met non-carriers (B = 11.9% 95%ETI = [0.8 23.0]%), but not in carriers (B = 1.0% 95%ETI = [-10.2 12.1]%). For the vestibulo-ocular reflex adaptation task, we found no effect of BDNF Val66Met (B = -2.0% 95%ETI = [-8.7 4.7]%) or anodal tDCS in either carriers (B = 3.4% 95%ETI = [-3.2 9.5]%) or non-carriers (B = 0.6% 95%ETI = [-3.4 4.8]%). Finally, we performed additional saccade and visuomotor adaptation experiments (N = 72) to investigate the general role of BDNF Val66Met in cerebellum-dependent learning and found no difference between carriers and non-carriers for both saccade (B = 1.0% 95%ETI = [-8.6 10.6]%) and visuomotor adaptation (B = 2.7% 95%ETI = [-2.5 7.9]%). CONCLUSIONS: The specific role for BDNF Val66Met in eyeblink conditioning, but not vestibulo-ocular reflex adaptation, saccade adaptation or visuomotor adaptation could be related to dominance of the role of simple spike suppression of cerebellar Purkinje cells with a high baseline firing frequency in eyeblink conditioning. Susceptibility of non-carriers to anodal tDCS in eyeblink conditioning might be explained by a relatively larger effect of tDCS-induced subthreshold depolarization in this group, which might increase the spontaneous firing frequency up to the level of that of the carriers.