EV-TRACK: transparent reporting and centralizing knowledge in extracellular vesicle research.

We argue that the field of extracellular vesicle (EV) biology needs more transparent reporting to facilitate interpretation and replication of experiments. To achieve this, we describe EV-TRACK, a crowdsourcing knowledgebase (http://evtrack.org) that centralizes EV biology and methodology with the goal of stimulating authors, reviewers, editors and funders to put experimental guidelines into practice.

miRNAs in Ancient Tissue Specimens of the Tyrolean Iceman.

The analysis of nucleic acids in ancient samples is largely limited to DNA. Small noncoding RNAs (microRNAs) are known to be evolutionary conserved and stable. To gain knowledge on miRNAs measured from ancient samples, we profiled microRNAs in cryoconserved mummies. First, we established the approach on a World War One warrior, the "Kaiserjäger", which has been preserved for almost one century. Then, we profiled seven ancient tissue specimens including skeletal muscle, stomach mucosa, stomach content and two corpus organ tissues of the 5,300-year-old copper age mummy Iceman and compared these profiles to the presence of organ-specific miRNAs in modern tissues. Our analyses suggest the presence of specific miRNAs in the different Iceman's tissues. Of 1,066 analyzed human miRNAs, 31 were discovered across all biopsies and 87 miRNAs were detected only in a single sample. To check for potential microbiological contaminations, all miRNAs detected in Iceman samples and not present in ancient samples were mapped to 14,582 bacterial and viral genomes. We detected few hits (3.9% of miRNAs compared with 3.6% of miRNAs). Interestingly, the miRNAs with higher abundance across all ancient tissues were significantly enriched for Guanine (P value of 10-13) and Cytosine (P value of 10-7). The same pattern was observed for modern tissues. Comparing miRNAs measured from ancient organs to modern tissue patterns highlighted significant similarities, e.g., for miRNAs present in the muscle. Our first comprehensive analysis of microRNAs in ancient human tissues indicates that these stable molecules can be detected in tissue specimens after 5,300 years.

Distribution of miRNA expression across human tissues.

We present a human miRNA tissue atlas by determining the abundance of 1997 miRNAs in 61 tissue biopsies of different organs from two individuals collected post-mortem. One thousand three hundred sixty-four miRNAs were discovered in at least one tissue, 143 were present in each tissue. To define the distribution of miRNAs, we utilized a tissue specificity index (TSI). The majority of miRNAs (82.9%) fell in a middle TSI range i.e. were neither specific for single tissues (TSI > 0.85) nor housekeeping miRNAs (TSI < 0.5). Nonetheless, we observed many different miRNAs and miRNA families that were predominantly expressed in certain tissues. Clustering of miRNA abundances revealed that tissues like several areas of the brain clustered together. Considering -3p and -5p mature forms we observed miR-150 with different tissue specificity. Analysis of additional lung and prostate biopsies indicated that inter-organism variability was significantly lower than inter-organ variability. Tissue-specific differences between the miRNA patterns appeared not to be significantly altered by storage as shown for heart and lung tissue. MiRNAs TSI values of human tissues were significantly (P = 10(-8)) correlated with those of rats; miRNAs that were highly abundant in certain human tissues were likewise abundant in according rat tissues. We implemented a web-based repository enabling scientists to access and browse the data (https://ccb-web.cs.uni-saarland.de/tissueatlas).

Prioritizing and selecting likely novel miRNAs from NGS data.

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at:www.ccb.uni-saarland.de/novomirank.

Syntaxin 8 is required for efficient lytic granule trafficking in cytotoxic T lymphocytes.

Cytotoxic T lymphocytes (CTL) eliminate pathogen-infected and cancerous cells mainly by polarized secretion of lytic granules (LG, containing cytotoxic molecules like perforin and granzymes) at the immunological synapse (IS). Members of the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) family are involved in trafficking (generation, transport and fusion) of vesicles at the IS. Syntaxin 8 (Stx8) is expressed in LG and colocalizes with the T cell receptor (TCR) upon IS formation. Here, we report the significance of Stx8 for human CTL cytotoxicity. We found that Stx8 mostly localized in late, recycling endosomal and lysosomal compartments with little expression in early endosomal compartments. Down-regulation of Stx8 by siRNA resulted in reduced cytotoxicity. We found that following perforin release of the pre-existing pool upon target cell contact, Stx8 down-regulated CTL regenerate perforin pools less efficiently and thus release less perforin compared to control CTL. CD107a degranulation, real-time and end-point population cytotoxicity assays, and high resolution microscopy support our conclusion that Stx8 is required for proper and timely sorting and trafficking of cytotoxic molecules to functional LG through the endosomal pathway in human CTL.

TRPC1- and TRPC3-dependent Ca2+ signaling in mouse cortical astrocytes affects injury-evoked astrogliosis in vivo.

Following brain injury astrocytes change into a reactive state, proliferate and grow into the site of lesion, a process called astrogliosis, initiated and regulated by changes in cytoplasmic Ca2+ . Transient receptor potential canonical (TRPC) channels may contribute to Ca2+ influx but their presence and possible function in astrocytes is not known. By RT-PCR and RNA sequencing we identified transcripts of Trpc1, Trpc2, Trpc3, and Trpc4 in FACS-sorted glutamate aspartate transporter (GLAST)-positive cultured mouse cortical astrocytes and subcloned full-length Trpc1 and Trpc3 cDNAs from these cells. Ca2+ entry in cortical astrocytes depended on TRPC3 and was increased in the absence of Trpc1. After co-expression of Trpc1 and Trpc3 in HEK-293 cells both proteins co-immunoprecipitate and form functional heteromeric channels, with TRPC1 reducing TRPC3 activity. In vitro, lack of Trpc3 reduced astrocyte proliferation and migration whereas the TRPC3 gain-of-function moonwalker mutation and Trpc1 deficiency increased astrocyte migration. In vivo, astrogliosis and cortex edema following stab wound injury were reduced in Trpc3-/- but increased in Trpc1-/- mice. In summary, our results show a decisive contribution of TRPC3 to astrocyte Ca2+ signaling, which is even augmented in the absence of Trpc1, in particular following brain injury. Targeted therapies to reduce TRPC3 channel activity in astrocytes might therefore be beneficial in traumatic brain injury.

Sources to variability in circulating human miRNA signatures.

An increasing number of studies propose circulating microRNAs (miRNAs) as biomarkers for a large number of human diseases including cancer, cardiovascular diseases, neurologic pathologies and others. To further validate miRNA as biomarkers it is indispensable to understand the variability of circulating miRNAs in healthy individuals. We determined the longitudinal miRNomes of 90 serum samples from the Janus Serum Bank in Norway, which have been stored between 23 and 40 y at -25 °Celsius. We profiled 3 serum samples with microarrays for 30 individuals, each. For each individual the samples were collected with a time interval of approximately 5 y. This design allowed insights into inter-individual variability, age dependent miRNA variability and the impact of storage length and pre-processing. A significant proportion of the miRNome was affected by the age of the blood donor and a not negligible, albeit small, part of the miRNome by the storage time. A substantial part of miRNAs was differentially abundant between individuals, independent of the time when samples were collected. Stepwise filtering of the 529 miRNAs that were detected in the serum samples showed 168 miRNAs with differential abundance depending on the time point analyzed, 56 miRNAs differentially abundant between individuals, and 169 miRNAs with an abundance depending on the sampling procedure. While these groups of miRNAs contain generally interesting and biologically important miRNAs, the remaining 135 miRNAs constitute very promising biomarker candidates as they show an overall low variability between healthy individuals, a likewise overall low variability across a longer life span, and a high independence of the sampling process and the storage length.

Deep characterization of blood cell miRNomes by NGS.

A systematic understanding of different factors influencing cell type specific microRNA profiles is essential for state-of-the art biomarker research. We carried out a comprehensive analysis of the biological variability and changes in cell type pattern over time for different cell types and different isolation approaches in technical replicates. All combinations of the parameters mentioned above have been measured, resulting in 108 miRNA profiles that were evaluated by next-generation-sequencing. The largest miRNA variability was due to inter-individual differences (34 %), followed by the cell types (23.4 %) and the isolation technique (17.2 %). The change over time in cell miRNA composition was moderate (<3 %) being close to the technical variations (<1 %). Largest variability (including technical and biological variance) was observed for CD8 cells while CD3 and CD4 cells showed significantly lower variations. ANOVA highlighted that 51.5 % of all miRNAs were significantly influenced by the purification technique. While CD4 cells were least affected, especially miRNA profiles of CD8 cells were fluctuating depending on the cell purification approach. To provide researchers access to the profiles and to allow further analyses of the tested conditions we implemented a dynamic web resource.

DrugTargetInspector: An assistance tool for patient treatment stratification.

Cancer is a large class of diseases that are characterized by a common set of features, known as the Hallmarks of cancer. One of these hallmarks is the acquisition of genome instability and mutations. This, combined with high proliferation rates and failure of repair mechanisms, leads to clonal evolution as well as a high genotypic and phenotypic diversity within the tumor. As a consequence, treatment and therapy of malignant tumors is still a grand challenge. Moreover, under selective pressure, e.g., caused by chemotherapy, resistant subpopulations can emerge that then may lead to relapse. In order to minimize the risk of developing multidrug-resistant tumor cell populations, optimal (combination) therapies have to be determined on the basis of an in-depth characterization of the tumor's genetic and phenotypic makeup, a process that is an important aspect of stratified medicine and precision medicine. We present DrugTargetInspector (DTI), an interactive assistance tool for treatment stratification. DTI analyzes genomic, transcriptomic, and proteomic datasets and provides information on deregulated drug targets, enriched biological pathways, and deregulated subnetworks, as well as mutations and their potential effects on putative drug targets and genes of interest. To demonstrate DTI's broad scope of applicability, we present case studies on several cancer types and different types of input -omics data. DTI's integrative approach allows users to characterize the tumor under investigation based on various -omics datasets and to elucidate putative treatment options based on clinical decision guidelines, but also proposing additional points of intervention that might be neglected otherwise. DTI can be freely accessed at http://dti.bioinf.uni-sb.de.

miRNAs and sports: tracking training status and potentially confounding diagnoses.

BACKGROUND: The dependency of miRNA abundance from physiological processes such as exercises remains partially understood. We set out to analyze the effect of physical exercises on miRNA profiles in blood and plasma of endurance and strength athletes in a systematic manner and correlated differentially abundant miRNAs in athletes to disease miRNAs biomarkers towards a better understanding of how physical exercise may confound disease diagnosis by miRNAs. METHODS: We profiled blood and plasma of 29 athletes before and after exercise. With four samples analyzed for each individual we analyzed 116 full miRNomes. The study set-up enabled paired analyses of individuals. Affected miRNAs were investigated for known disease associations using network analysis. RESULTS: MiRNA patterns in blood and plasma of endurance and strength athletes vary significantly with differences in blood outreaching variations in plasma. We found only moderate differences between the miRNA levels before training and the RNA levels after training as compared to the more obvious variations found between strength athletes and endurance athletes. We observed significant variations in the abundance of miR-140-3p that is a known circulating disease markers (raw and adjusted p value of 5 × 10(-12) and 4 × 10(-7)). Similarly, the levels of miR-140-5p and miR-650, both of which have been reported as makers for a wide range of human pathologies significantly depend on the training mode. Among the most affected disease categories we found acute myocardial infarction. MiRNAs, which are up-regulated in endurance athletes inhibit VEGFA as shown by systems biology analysis of experimentally validated target genes. CONCLUSION: We provide evidence that the mode and the extent of training are important confounding factors for a miRNA based disease diagnosis.

Differential blood-based diagnosis between benign prostatic hyperplasia and prostate cancer: miRNA as source for biomarkers independent of PSA level, Gleason score, or TNM status.

Since the benefit of prostate-specific antigen (PSA) screening remains controversial, new non-invasive biomarkers for prostate carcinoma (PCa) are still required. There is evidence that microRNAs (miRNAs) in whole peripheral blood can separate patients with localized prostate cancer from healthy individuals. However, the potential of blood-based miRNAs for the differential diagnosis of PCa and benign prostatic hyperplasia (BPH) has not been tested. We compared the miRNome from blood of PCa and BPH patients and further investigated the influence of the tumor volume, tumor-node-metastasis (TNM) classification, Gleason score, pretreatment risk status, and the pretreatment PSA value on the miRNA pattern. By microarray approach, we identified seven miRNAs that were significantly deregulated in PCa patients compared to BPH patients. Using quantitative real time PCR (qRT-PCR), we confirmed downregulation of hsa-miR-221* (now hsa-miR-221-5p) and hsa-miR-708* (now hsa-miR-708-3p) in PCa compared to BPH. Clinical parameters like PSA level, Gleason score, or TNM status seem to have only limited impact on the overall abundance of miRNAs in patients' blood, suggesting a no influence of these factors on the expression of deregulated miRNAs.

Validating Alzheimer's disease micro RNAs using next-generation sequencing.

INTRODUCTION: Molecular biomarkers for Alzheimer's disease (AD) can support detection and improved care for patients, but novel candidates require verification. We previously reported a 12-micro RNA (miRNA) blood-based signature using next-generation sequencing (NGS) of 54 AD cases and 22 controls. METHODS: We performed validation of 49 AD cases and 55 controls using NGS and also included 20 mild cognitive impairment and 90 multiple sclerosis samples to identify nonspecific markers. Thus, 103 AD cases, 77 unaffected controls, and 110 diseased controls were sequenced. Although the initial cohort came predominantly from the United States, the validation samples were collected in Germany. RESULTS: Five hundred eighty miRNAs were detected in the blood. In the initial cohort, we observed 203, in the validation cohort, 146 dysregulated miRNAs at a significance level of 0.05. With 68 miRNAs, the overlap was significant (P = .0003). Likewise, the area under the receiver operator characteristic curve values of the miRNAs correlated (correlation of 0.93; 95% confidence interval 0.89-0.96; P <10(-16)). DISCUSSION: MiRNAs have the potential to support AD diagnosis and patient care.

Trans-activation response (TAR) RNA-binding protein 2 is a novel modulator of transient receptor potential canonical 4 (TRPC4) protein.

TRPC4 proteins function as Ca(2+) conducting, non-selective cation channels in endothelial, smooth muscle, and neuronal cells. To further characterize the roles of TRPC4 in vivo, detailed information about the molecular composition of native channel complexes and their association with cellular signaling networks is needed. Therefore, a mouse brain cDNA library was searched for novel TRPC4-interacting proteins using a modified yeast two-hybrid assay. This screen identified Trans-activation Response RNA-binding protein 2 (Tarpb2), a protein that recruits the Dicer complex to Ago2 for microRNA processing and gene silencing. Tarbp2 was found to bind to the C terminus of TRPC4 and TRPC5 and to modulate agonist-dependent TRPC4-induced Ca(2+) entry. A stretch of basic residues within the Tarbp2 protein is required for these actions. Tarbp2 binding to and modulation of TRPC4 occurs in the presence of endogenously expressed Dicer but is no longer detectable when the Dicer cDNA is overexpressed. Dicer activity in crude cell lysates is increased in the presence of Ca(2+), most probably by Ca(2+)-dependent proteolytic activation of Dicer. Apparently, Tarbp2 binding to TRPC4 promotes changes of cytosolic Ca(2+) and, thereby, leads to a dynamic regulation of Dicer activity, essentially at low endogenous Dicer concentrations.

Influence of next-generation sequencing and storage conditions on miRNA patterns generated from PAXgene blood.

Whole blood derived miRNA signatures determined by Next-Generation Sequencing (NGS) offer themselves as future minimally invasive biomarkers for various human diseases. The PAXgene system is a commonly used blood storage system for miRNA analysis. Central to all miRNA analyses that aim to identify disease specific miRNA signatures, is the question of stability and variability of the miRNA profiles that are generated by NGS. We characterized the influence of five different conditions on the genome wide miRNA expression pattern of human blood isolated in PAXgene RNA tubes. In detail, we analyzed 15 miRNomes from three individuals. The blood was subjected to different numbers of freeze/thaw cycles and analyzed for the influence of storage at -80 or 8 °C. We also determined the influence of blood collection and NGS preparations on the miRNA pattern isolated from a single individual, which has been sequenced 10 times. Here, five PAXGene tubes were consecutively collected that have been split in two replicates, representing two experimental batches. All samples were analyzed by Illumina NGS. For each sample, approximately 20 million NGS reads have been generated. Hierarchical clustering and Principal Component Analysis (PCA) showed an influence of the different conditions on the miRNA patterns. The effects of the different conditions on miRNA abundance are, however, smaller than the differences that are due to interindividual variability. We also found evidence for an influence of the NGS measurement on the miRNA pattern. Specifically, hsa-miR-1271-5p and hsa-miR-182-5p showed coefficients of variation above 100% indicating a strong influence of the NGS protocol on the abundance of these miRNAs.

Next-generation sequencing identifies altered whole blood microRNAs in neuromyelitis optica spectrum disorder which may permit discrimination from multiple sclerosis.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) have a similar clinical phenotype but represent distinct diseases, requiring different therapies. MicroRNAs (miRNAs) are short non-coding RNAs whose expression profiles can serve as diagnostic biomarkers and which may be involved in the pathophysiology of neuroinflammatory diseases. Here, we analyzed miRNA profiles in serum and whole blood of patients with NMOSD and clinically isolated syndrome (CIS)/relapsing-remitting MS (RRMS) as well as healthy controls by next-generation sequencing (NGS). METHODS: MiRNA expression profiles were determined by NGS in sera of patients with aquaporin-4 antibody-positive NMOSD (n = 20), CIS/RRMS (n = 20), and healthy controls (n = 20) and in whole blood of patients with NMOSD (n = 11), CIS/RRMS (n = 60), and healthy controls (n = 43). Differentially expressed miRNAs were calculated by analysis of variance and t tests. All significance values were corrected for multiple testing. Selected miRNAs were validated in whole blood of patients with NMOSD (n = 18) and CIS/RRMS (n = 19) by quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: None of 261 miRNAs detected in serum but 178 of 416 miRNAs detected in whole blood showed significantly different expression levels among the three groups. Pairwise comparisons revealed 115 (NMOSD vs. CIS/RRMS), 141 (NMOSD vs. healthy controls), and 44 (CIS/RRMS vs. healthy controls) miRNAs in whole blood with significantly different expression levels. qRT-PCR confirmed different expression levels in whole blood of patients with NMOSD and CIS/RRMS for 9 out of 10 exemplarily chosen miRNAs. In silico enrichment analysis demonstrated an accumulation of altered miRNAs in NMOSD in particular in CD15(+) cells (i.e., neutrophils and eosinophils). CONCLUSIONS: This study identifies a set of miRNAs in whole blood, which may have the potential to discriminate NMOSD from CIS/RRMS and healthy controls. In contrast, miRNA profiles in serum do not appear to be promising diagnostic biomarkers for NMOSD. Enrichment of altered miRNAs in CD15(+) neutrophils and eosinophils, which were previously implicated in the pathophysiology of NMOSD, suggests that miRNAs could be involved in the regulation of these cells in NMOSD.

miFRame: analysis and visualization of miRNA sequencing data in neurological disorders.

BACKGROUND: While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians. METHODS: We developed miFRame, which supports the analysis of human small RNA NGS data. Our tool carries out different data analyses for known as well as predicted novel mature microRNAs from known precursors and presents the results in a well interpretable manner. Analyses include among others expression analysis of precursors and mature miRNAs, detection of novel precursors and detection of potential iso-microRNAs. Aggregation of results from different users moreover allows for evaluation whether remarkable results, such as novel mature miRNAs, are indeed specific for the respective experimental set-up or are frequently detected across a broad range of experiments. RESULTS: We demonstrate the capabilities of miFRame, which is freely available at http://www.ccb.uni-saarland.de/miframe on two studies, circulating biomarker screening for Multiple Sclerosis (cohort includes clinically isolated syndrome, relapse remitting MS, matched controls) as well as Alzheimer Disease (cohort includes Alzheimer Disease, Mild Cognitive Impairment, matched controls). Here, our tool allowed for an improved biomarker discovery by identifying likely false positive marker candidates.

MicroRNA in vitro diagnostics using immunoassay analyzers.

BACKGROUND: The implementation of new biomarkers into clinical practice is one of the most important areas in medical research. Besides their clinical impact, novel in vitro diagnostic markers promise to have a substantial effect on healthcare costs. Although numerous publications report the discovery of biomarkers, only a fraction of those markers are routinely used. One key challenge is a measurement system that is compatible with clinical workflows. METHODS: We designed a new immunoassay for microRNA (miRNA) quantification. The assay combines streptavidin-linked microparticles, a biotinylated catcher oligonucleotide complementary to a single miRNA species, and finally, a monoclonal antibody to DNA/RNA heterohybrids labeled with acridinium ester. Importantly, our assay runs on standard immunoassay analyzers. After a technical validation of the assay, we evaluated the clinical performance on 4 Alzheimer disease miRNAs. RESULTS: Our assay has an analytical specificity of 99.4% and is at the same time sensitive (concentrations in the range of 1 pmol/L miRNA can be reliably profiled). Because the novel approach did not require amplification steps, we obtained high reproducibility for up to 40 biological replicates. Importantly, our assay prototype exhibited a time to result of <3 h. With human blood samples, the assay was able to measure 4 miRNAs that can detect Alzheimer disease with a diagnostic accuracy of 82% and showed a Pearson correlation >0.994 with the gold standard qRT-PCR. CONCLUSIONS: Our miRNA immunoassay allowed the measurement of miRNA signatures with sufficient analytical sensitivity and high specificity on commonly available laboratory equipment.

The human miRNA repertoire of different blood compounds.

BACKGROUND: MiRNAs from body fluids gain more and more attraction as biomarker candidates. Besides serum, patterns from whole blood are increasingly considered as markers for human pathologies. Usually, the contribution of different cell types to the respective signature remains however unknown. In this study we provide insights into the human miRNome of different compounds of the blood including CD3, CD14, CD15, CD19, CD56 positive cells as well as exosomes. METHODS: We measured the miRNA repertoire for each cell type and whole blood for two individuals at three time points over the course of one year in order to provide evidence that the cell type miRNomes can be reproducibly detected. RESULTS: For measurements repeated after 24 hours we found on average correlation of 0.97, even after one year profiles still correlated with 0.96, demonstrating the enormous stability of the cell type specific miRNomes. Highest correlation was found for CD15 positive cells, exceeding Pearson correlation of 0.99. For exosomes a significantly higher variability of miRNA expression was detected. In order to estimate the complexity and variability of the cell type specific miRNomes, we generated profiles for all considered cell types in a total of seven unaffected individuals. While CD15 positive cells showed the most complex miRNome consisting of 328 miRNAs, we detected significantly less miRNAs (186, p = 1.5*10(-5)) in CD19 positive cells. Moreover, our analysis showed functional enrichment in many relevant categories such as onco-miRNAs and tumor miRNA suppressors. Interestingly, exosomes were enriched just for onco-miRNAs but not for miRNA tumor suppressors. CONCLUSION: In sum, our results provide evidence that blood cell type specific miRNomes are very consistent between individuals and over time.

The blood-borne miRNA signature of lung cancer patients is independent of histology but influenced by metastases.

OBJECTIVES: In our previous studies we reported a panel of 24 miRNAs that allowed discrimination between blood of lung tumor patients independent of the histological subtype and blood of healthy controls with an accuracy of 95.4% [94.9%-95.9%]. Here, we now separately analyzed the miRNA expression in blood of non-small cell lung cancer (NSCLC), including squamous cell lung cancer and adenocarcinoma, and small cell lung cancer (SCLC) patients. PATIENTS AND METHODS: In total, we examined the expression levels of 1,205 miRNAs in blood samples from 20 patients from each of the three histological groups and determined differentially expressed miRNAs between histological subtypes and metastatic and non-metastatic lung cancer. We further determined the overlap of miRNAs expressed in each subgroup with the 24-miRNA signature of lung tumor patients. RESULTS: Based on a raw p-value < 0.05, only 18 blood-borne miRNAs were differentially expressed between patients with adenocarcinoma and with squamous cell lung carcinoma, 11 miRNAs between adenocarcinoma and SCLC, and 2 between squamous cell lung carcinoma and SCLC. Likewise, the comparison based on a fold change of 1.5 did not reveal major differences of the blood-borne miRNA expression pattern between NSCLC and SCLC. In addition, we found a large overlap between the blood-borne miRNAs detected in the three histological subgroups and the previously described 24-miRNA signature that separates lung cancer patients form controls. We identified several miRNAs that allowed differentiating between metastatic and non-metastatic tumors both in blood of patients with adenocarcinoma and in blood of patients with SCLC. CONCLUSION: There is a common miRNA expression pattern in blood of lung cancer patients that does not allow a reliable further subtyping into NSCLC or SCLC, or into adenocarcinoma and squamous cell lung cancer. The previously described 24-miRNA signature for lung cancer appears not primarily dependent on histological subtypes. However, metastatic adenocarcinoma and SCLC can be predicted with 75% accuracy.

miRNAs can be generally associated with human pathologies as exemplified for miR-144.

BACKGROUND: miRNA profiles are promising biomarker candidates for a manifold of human pathologies, opening new avenues for diagnosis and prognosis. Beyond studies that describe miRNAs frequently as markers for specific traits, we asked whether a general pattern for miRNAs across many diseases exists. METHODS: We evaluated genome-wide circulating profiles of 1,049 patients suffering from 19 different cancer and non-cancer diseases as well as unaffected controls. The results were validated on 319 individuals using qRT-PCR. RESULTS: We discovered 34 miRNAs with strong disease association. Among those, we found substantially decreased levels of hsa-miR-144* and hsa-miR-20b with AUC of 0.751 (95% CI: 0.703-0.799), respectively. We also discovered a set of miRNAs, including hsa-miR-155*, as rather stable markers, offering reasonable control miRNAs for future studies. The strong downregulation of hsa-miR-144* and the less variable pattern of hsa-miR-155* has been validated in a cohort of 319 samples in three different centers. Here, breast cancer as an additional disease phenotype not included in the screening phase has been included as the 20th trait. CONCLUSIONS: Our study on 1,368 patients including 1,049 genome-wide miRNA profiles and 319 qRT-PCR validations further underscores the high potential of specific blood-borne miRNA patterns as molecular biomarkers. Importantly, we highlight 34 miRNAs that are generally dysregulated in human pathologies. Although these markers are not specific to certain diseases they may add to the diagnosis in combination with other markers, building a specific signature. Besides these dysregulated miRNAs, we propose a set of constant miRNAs that may be used as control markers.