Abstract:
MicroRNAs (miRNA) are a recently discovered class of small non-coding RNAs (17-14 nucleotides). Due to their function as regulators of gene expression they play a critical role both in physiological and in pathological processes, such as cancer. The present invention provides novel methods for diagnosing a state of health based on the determination of specific miRNAs that have altered expression levels in different conditions, e.g. disease states compared to healthy controls.

Description:
CROSS REFERENCE TO RELATED APPLICATION 
       [0001]    This application is a continuation of U.S. Ser. No. 13/519,959, filed Oct. 24, 2012, which is a 35 U.S.C. 371 National Phase Entry Application from PCT/EP2010/070926, filed Dec. 30, 2010, which claims the benefit of U.S. Ser. No. 61/291,074 filed Dec. 30, 2009 and European Patent Application No. 09181024.2 filed on Dec. 30, 2009 the disclosures of which are incorporated herein in their entirety by reference. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    MicroRNAs (miRNA) are a recently discovered class of small non-coding RNAs (17-14 nucleotides). Due to their function as regulators of gene expression they play a critical role both in physiological and in pathological processes, such as cancer (Calin and Croce 2006; Esquela-Kerscher and Slack 2006; Zhang, Pan et al. 2007; Sassen, Miska et al. 2008). 
         [0003]    There is increasing evidence that miRNAs are not only found in tissues but also in human blood both as free circulating nucleic acids and in mononuclear cells. A recent proof-of-principle study demonstrated miRNA expression pattern in pooled blood sera and pooled blood cells, both in healthy individuals and in cancer patients including patients with lung cancer (Chen, Ba et al. 2008). In addition, a remarkable stability of miRNAs in human sera was recently demonstrated (Chen, Ba et al. 2008; Gilad, Meiri et al. 2008). These findings make miRNA a potential tool for diagnostics for various types of diseases based on blood analysis. 
         [0004]    Thus, although various markers have been proposed to indicate specific types of disorders such as prostate cancer, Wilms&#39; tumour or COPD (Chronic obstructive pulmonary disease) there is still a need for more efficient and effective methods and compositions for the diagnosis of diseases. 
       SUMMARY OF THE INVENTION 
       [0005]    The present invention provides novel methods for diagnosing diseases based on the determination of specific miRNAs that have altered expression levels in disease states compared to healthy controls or altered expression levels in a condition 1 (biological state or health state 1) compared to a condition 2 (biological state or health state 2). The disease is particularly selected from Wilms&#39; tumour. 
       Definitions 
     miRNA 
       [0006]    microRNAs (miRNA or pRNA) are single-stranded RNA molecules of ˜21-23 nucleotides in length, which regulate gene expression. miRNAs are encoded by genes from whose DNA they are transcribed but miRNAs are not translated into protein (i.e. they are non-coding RNAs). The genes encoding miRNAs are much longer than the processed mature miRNA molecule; miRNAs are first transcribed as primary transcripts or pri-miRNA with a cap and poly-A tail and processed to short, 70-nucleotide stem-loop structures known as pre-miRNA in the cell nucleus. This processing is performed in animals by a protein complex known as the Microprocessor complex, consisting of the nuclease Drosha and the double-stranded RNA binding protein Pasha. These pre-miRNAs are then processed to mature miRNAs in the cytoplasm by interaction with the endonuclease Dicer, which also initiates the formation of the RNA-induced silencing complex (RISC). When Dicer cleaves the pre-miRNA stem-loop, two complementary short RNA molecules are formed, but only one is integrated into the RISC. This strand is known as the guide strand and is selected by the argonaute protein, the catalytically active RNase in the RISC, on the basis of the stability of the 5′ end. The remaining strand, known as the miRNA*, anti-guide or passenger strand, is degraded as a RISC substrate. Therefore the miRNA*s are derived from the same hairpin structure like the “normal” miRNAs. So if the “normal” miRNA is then later called the “mature miRNA” or “guided strand”, the miRNA* is the passenger strand. 
       miRNA* (See Also Above “miRNA”) 
       [0007]    The miRNA*s, also known as the anti-guide or passenger strand, are mostly complementary to the guide strand, but there are usually single-stranded overhangs on each end, there is usually one or a few mispairs and there are sometimes extra or missing bases causing single-stranded “bubbles. The miRNA*s are likely to act in a regulatory fashion as the miRNAs. It is understood that according to the present invention the term “miRNA” also includes the term “miRNA*”. 
       miRBase 
       [0008]    A well established repository of validated miRNAs is the miRBase. The miRBase (www.mirbase.org) is a searchable database of published miRNA sequences and annotation. Each entry in the miRBase Sequence database represents a predicted hairpin portion of a miRNA transcript (termed mir in the database), with information on the location and sequence of the mature miRNA sequence (termed miR). Both hairpin and mature sequences are available for searching and browsing, and entries can also be retrieved by name, keyword, references and annotation. All sequence and annotation data are also available for download. 
       miRNA-(Expression) Profile or miRNA Fingerprint 
       [0009]    A miRNA-Profile represents the collection of expression levels of a plurality of miRNAs, therefore it is a quantitative measure of individual miRNA expression levels. Hereby, each miRNA is represented by a numerical value. The higher the value of an individual miRNA the higher is the expression level of this miRNA. A miRNA-profile is obtained from the RNA of a biological sample. The are various technologies to determine a miRNA-Profile, e.g. microarrays, RT-PCR, Next Generation Sequencing. As a starting material for analysis, RNA or total-RNA or any fraction thereof can be used. The plurality of miRNAs that are determined by a miRNA-profile can range from a selection of one up to all known miRNAs. 
       Pre-Determined Set of miRNAs or miRNA Signature 
       [0010]    The pre-determined set of miRNAs or miRNA signature is understood in the present invention as a fixed defined set of miRNAs which is able to differentiate between a condition 1 and another condition 2. e.g. when condition 1 is lung cancer and condition 2 is normal control, the corresponding pre-determined set of miRNAs is able to differentiate between a samples derived from a lung cancer patient or a normal control patient. Alternatively, condition 1 is lung cancer and condition 2 is multiple sclerosis, the corresponding pre-determined set of miRNAs is able to differentiate between a lung cancer patient and a multiple sclerosis patient. In order to be able to perform the sample analysis it is required that, e.g. on the matrix that will be used to determine a miRNA profile, these fixed defined set of miRNAs have to be represented by capture probes that are defined by the predetermined set of miRNAs. For example, when the predetermined set of miRNAs for diagnosing lung cancer from healthy controls consists of 25 miRNAs, probes capable for detecting these 25 miRNAs have to be implemented for performing the diagnostic analysis. 
       Common miRNA Signature Profile 
       [0011]    A common miRNA signature profile is understood in the present invention as a non-fixed defined set of miRNAs or non-coding RNAs which is able to differentiate between a condition 1 and another condition 2. The common miRNA or non-coding RNA signature profile is calculated “on-the-fly” from a plurality of miRNA-profiles that are stored, e.g. in database. The common miRNA signature profile which is able to differentiate between a condition 1 and another condition 2 is changing as soon as an new profile is added to the database which is relevant to either to state of health 1 or another condition 2. In this respect it is different from a predetermined set of miRNAs (see above). Furthermore, the basis for generating the common miRNA signature profile—hence the miRNA profiles stored in the database—is generated from capture probes, e.g. on a matrix that is representing as much as possible different capture probes for detecting as much as possible, ideally all known, miRNAs. 
       Non-Coding RNA 
       [0012]    A non-coding RNA (ncRNA) is a functional RNA molecule that is not translated into a protein. Less-frequently used synonyms are non-protein-coding RNA (npcRNA), non-messenger RNA (nmRNA), small non-messenger RNA (snmRNA), functional RNA (fRNA). The term small RNA (sRNA) is often used for bacterial ncRNAs. The DNA sequence from which a non-coding RNA is transcribed as the end product is often called an RNA gene or non-coding RNA gene. 
         [0013]    Non-coding RNA genes include highly abundant and functionally important RNAs such as transfer RNA (tRNA) and ribosomal RNA (rRNA), as well as RNAs such as snoRNAs, microRNAs, siRNAs and piRNAs and the long ncRNAs that include examples such as Xist and HOTAIR (see here for a more complete list of ncRNAs). The number of ncRNAs encoded within the human genome is unknown, however recent transcriptomic and bioinformatic studies suggest the existence of thousands of ncRNAs. Since most of the newly identified ncRNAs have not been validated for their function, it is possible that many are non-functional. 
       Condition 
       [0014]    A condition (biological state or health state or state of health) is understood in the present invention as status of a subject that can be described by physical, mental or social criteria. It includes as well so-called “healthy” and “diseased” conditions, therefore it is not limited to the WHO definition of health as “a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity.” but includes disease and infirmity. For the definition of diseases comprised, e.g. by the conditions of the present invention, it is referred to the international classification of diseases (ICD) of the WHO (www.who.int/classifications/icd/en/index.html). When 2 or more conditions are compared according to the present invention, it is understood that this is possible for all conditions that can be defined and is not limited to a comparison of a disease versus healthy and extends to multi-way comparisons. Examples for comparison are, but not limited to:
   pairwise comparisons:
       lung cancer vs. healthy control, pancreatic cancer vs. healthy control   lung cancer vs. pancreatic cancer, lung cancer vs. multiple sclerosis   lung cancer WHO grade 1 vs. lung cancer WHO grade 2   lung cancer WHO grade 1 metastasing vs. lung cancer WHO grade 1 non-metastasing   Morbus Crohn vs. collitis   Pancreatic cancer vs. pancreatitis   
       multi-way comparisons:
       Lung cancer vs. pancreatic cancer vs. multiple sclerosis   Pancreas cancer vs. pancreatitis vs. lung cancer WHO grade 1 non-metastasing   
       
 
       Wilms&#39; Tumour 
       [0025]    Wilms&#39; tumour or nephroblastoma is a tumour of the kidneys that typically occurs in children, rarely in adults Its common name is an eponym, referring to Dr. Max Wilms, the German surgeon (1867-1918) who first described this kind of tumour. 
         [0026]    Wilms&#39; tumour is a highly malignant, usually unilateral and rapidly developing tumour of the kidney, composed of malignant epithelial and mesodermal cells. Initially, asymptomatic; later, moderate local pain, nausea, vomiting, apathy, and fever. There is also pallor, weight loss, abdominal distension, and blood hypertension It is the most common malignous kidney tumour in children, usually affecting children aged 3-4 years. 75 percent of patients are under 5 years, but it has also been reported in adults. In the past, the mortality from this cancer was extremely high. Newer approaches to therapy have been very effective in controlling the tumour. In a small proportion of patients Wilms&#39; tumour occurs in conjunction with absence of the iris and the familial form of the association is inherited as an autosomal dominant trait. 
         [0027]    A “biological sample” in terms of the invention means a sample of biological tissue or fluid. Examples of biological samples are sections of tissues, blood, blood fractions, plasma, serum, urine or samples from other peripheral sources, or cell cultures, cell colonies of even single cells, or a collection of single cells. Furthermore, also pools or mixture of the above mentioned samples may be employed. A biological sample may be provided by removing a sample of cells from a subject, but can also be provided by using a previously isolated sample. For example, a tissue sample can be removed from a subject suspected of having a disease by conventional biopsy techniques. In a preferred embodiment, a blood sample is taken from the subject. In one embodiment, the blood or tissue sample is obtained from the subject prior to initiation of radiotherapy, chemotherapy or other therapeutic treatment. According to the invention, the biological sample preferably is a blood or a serum sample. Further, it is also preferred to use blood cells, e.g. erythrocytes, leukocytes or thrombocytes. 
         [0028]    A biological sample from a patient means a sample from a subject suspected to be affected by a disease. As used herein, the term “subject” refers to any mammal, including both human and other mammals. Preferably, the methods of the present invention are applied to human subjects. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0029]    The invention will now be illustrated by the following figures and the non-limiting experimental examples. 
           [0030]      FIG. 1 : 
           [0031]    Overview of miRNA sequences published in the miRNA database 14.0 plus additional miRNA sequences. 
           [0032]      FIG. 2 : 
           [0033]    General overview of the method of diagnosing and/or predicting the state of health employing predetermined sets of miRNAs. 
           [0034]      FIG. 3 : 
           [0035]    Overview of all miRNAs that are found to be differentially regulated in blood samples of Wilms&#39; tumour patients, grouped accordingly to their results in t-tests. 
           [0036]      FIG. 4 : 
           [0037]    Overview of miRNAs that are found to be differentially regulated between healthy control and subjects suffering from Wilms&#39; tumour. Experimental details: SEQ ID NO: sequence identification number, miRNA: identifier of the miRNA according to miRBase, median g1: median intensity obtained from microarray analysis for healthy controls, median g2: median intensity obtained from microarray analysis for individuals with Wilms&#39; tumour, qmedian: ratio of median g1/median g2, logqmedian: log of qmedian, ttest_rawp: p-value obtained when applying t-test, ttest_adjp: adjusted p-value in order to reduce false discovery rate by Benjamini-Hochberg adjustment, AUC: Area under the curve, wmw_rawp: p-value obtained when applying wmw-test (Wilcoxon Mann Whitney test), wmw_adjp: adjusted p-value in order to reduce false discovery rate by Benjamini-Hochberg adjustment. 
           [0038]      FIG. 5 : 
           [0039]    Predetemined sets of miRNAs (miRNA signatures SNW-1 to 640) that allow for effective diagnosis and/or prognosis of subjects suffering or subjects suspected to suffering from Wilms&#39; tumour. Experimental details: SEQ ID NO: sequence identification number, miRNA: identifier of the miRNA according to miRBase, Acc=accuracy, Spec=specificity, Sens=sensitivity. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0040]    Subject-matter of the invention is a method for diagnosing a disease, comprising the steps
       (a) determining an expression profile of a predetermined set of miRNAs in a biological sample from a patient (or subject); and   (b) comparing said expression profile to a reference expression profile, wherein the comparison of said determined expression profile to said reference expression profile allows for the diagnosis of the disease.       
 
         [0043]    In step (a) of the above method of the invention, an expression profile of a predetermined set of miRNAs is determined. The determination may be carried out by any convenient means for determining nucleic acids. For expression profiling, qualitative, semi-quantitative and preferably quantitative detection methods can be used. A variety of techniques are well known to those of skill in the art. In particular, the determination may comprise nucleic acid hybridization and/or nucleic acid amplification steps. 
         [0044]    Nucleic acid hybridization may for example be performed using a solid phase nucleic acid biochip array, in particular a microarray, or in situ hybridization. The miRNA microarray technology affords the analysis of a complex biological sample for all expressed miRNAs. Nucleotides with complementarity to the corresponding miRNAs are spotted on coated carriers or are fabricated by in-situ synthesis methods on a carrier. Preferably, miRNAs isolated from the sample of interest are not labelled, e.g. before hybridization of the miRNAs to the complementary sequences on the carrier and the resulting signal indicating the occurrence of a distinct miRNA is generated by incorporation of a detectable label (e.g. biotin, fluorescent dye) by means of an enzyme reaction. 
         [0045]    According to another embodiment of the invention, miRNAs isolated from the sample of interest are labelled, e.g. fluorescently labelled, so that upon hybridization of the miRNAs to the complementary sequences on the carrier the resulting signal indicates the occurrence of a distinct miRNA. On one miRNA microarray, preferably at least the whole predetermined set of miRNAs can be analyzed. 
         [0046]    Further, quantitative real-time polymerase chain reaction (RT-PCR) can be used to detect miRNAs even at very low abundance. 
         [0047]    Alternative methods for obtaining expression profiles may also contain sequencing, next generation sequencing or mass spectroscopy. 
         [0048]    The predetermined set of miRNAs in step (a) of the above method of the invention depends on the disease to be diagnosed. The inventors found out that single miRNA biomarkers lack sufficient accuracy, specificity and sensitivity, and therefore it is preferred to analyze more complex miRNA expression patterns, so-called miRNA signatures. The predetermined set of miRNAs comprises one or more, preferably a larger number of miRNAs (miRNA signatures) that are differentially regulated in samples of a patient affected by a particular disease compared to healthy controls. Alternatively, the disease can also be compared to any other defined condition (e.g. another disease). 
         [0049]    The expression profile determined in the above step (a) is subsequently compared to a reference expression profile or to a plurality of reference profiles in the above step (b). The reference expression profile is the expression profile of the same set of miRNAs in a biological sample originating from the same source as the biological sample from a patient but obtained from a healthy subject. Preferably, both the reference expression profile and the expression profile of the above step (a) are determined in a blood or serum sample or in a sample of erythrocytes, leukocytes and/or thrombocytes. It is understood that the reference expression profile is not necessarily obtained from a single healthy subject but may be an average expression profile of a plurality of healthy subjects. It is preferred to use a reference expression profile obtained from a person of the same gender, and a similar age as the patient. 
         [0050]    The above method of the invention is suitable for diagnosing any diseases for which a differential expression of miRNAs compared to healthy controls or other diseases exists. In particular, the method may be used for diagnosing cancer including bladder cancer, brain cancer, breast cancer, colon cancer, endometrium cancer, gastrointestinal stromal cancer, glioma, head- and neck cancer, kidney cancer, leukemia, liver cancer, lung cancer, lymph node cancer, melanoma, meninges cancer, ovarian cancer, pancreas cancer, prostate cancer, sarcoma, stomach cancer, testicular cancer, thyroid cancer, thymus cancer and Wilms&#39; tumour or COPD. The diagnosis may comprise determining type, rate and/or stage of cancer. The course of the disease and the success of therapy such as chemotherapy may be monitored. The method of the invention provides a prognosis on the survivor rate and enables to determine a patient&#39;s response to drugs. 
         [0051]    In addition to cancer, also different types of diseases may be diagnosed by means of the above method of the invention, if the disease state is correlated with a differential expression of miRNAs compared to a healthy control. For example the disease may be Alzheimer&#39;s disease, multiple sclerosis, melanoma, Morbus Crohn and cardiovascular diseases. The inventors found out that also these diseases are correlated with a specific expression profile of miRNAs. 
         [0052]    The inventors succeeded in developing a generally applicable approach to arrive at miRNA signatures that are correlated with a particular disease. In more detail, the following steps are accomplished:
   1. miRNAs are extracted from a biological sample of a patient, preferably a blood or serum or urine sample or a sample comprising erythrocytes, leukocytes or thrombocytes, using suitable kits/purification methods. From these samples preferably the RNA-fraction is used for analysis.   2. The respective samples are measured using experimental techniques. These techniques include but are not restricted to:
       Array based approaches   Real time quantitative polymerase chain reaction   Sequencing   Next Generation Sequencing   Mass Spectroscopy   
       3. Mathematical approaches are applied to gather information on the value and the redundancy of single biomarkers. These methods include, but are not restricted to:
       basic mathematic approaches (e.g. Fold Quotients, Signal to Noise ratios, Correlation)   statistical methods as hypothesis tests (e.g. t-test, Wilcoxon-Mann-Whitney test), the Area under the Receiver operator Characteristics Curve   Information Theory approaches, (e.g. the Mutual Information, Cross-entropy)   Probability theory (e.g. joint and conditional probabilities)   Combinations and modifications of the previously mentioned examples   
       4. The information collected in 3) are used to estimate for each biomarker the diagnostic content or value. Usually, however, this diagnostic value of only one biomarker is too small to get a highly accurate diagnosis with accuracy rates, specificities and sensitivities beyond the 90% barrier. Please note that the diagnostic content for our miRNAs can be found in the tables in  FIGS. 3 and 4 . These tables includes the miRNAs with the sequences, and the significance value as computed by a t-test and further statistical measures.   5. Thus statistical learning/machine learning/bioinformatics/computational approaches are applied to define subsets of biomarkers that are tailored for the detection of diseases. These techniques includes but are not restricted to
       Wrapper subset selection techniques (e.g. forward step-wise, backward step-wise, combinatorial approaches, optimization approaches)   Filter subset selection methods (e.g. the methods mentioned in 3)   Principal Component Analysis   Combinations and modifications of such methods (e.g. hybrid approaches)   
       6. The diagnostic content of each detected set can be estimated by mathematical and/or computational techniques to define the diagnostic information content of subsets.   7. The subsets, detected in step 5, which may range from only a small number (at least two) to all measured biomarkers is then used to carry out a diagnosis. To this end, statistical learning/machine learning/bioinformatics/computational approaches are applied that include but are not restricted to any type of supervised or unsupervised analysis:
       Classification techniques (e.g. naive Bayes, Linear Discriminant Analysis, Quadratic Discriminant Analysis Neural Nets, Tree based approaches, Support Vector Machines, Nearest Neighbour Approaches)   Regression techniques (e.g. linear Regression, Multiple Regression, logistic regression, probit regression, ordinal logistic regression ordinal Probit-Regression, Poisson Regression, negative binomial Regression, multinomial logistic Regression, truncated regression)   Clustering techniques (e.g. k-means clustering, hierarchical clustering, PCA)   Adaptations, extensions, and combinations of the previously mentioned approaches   
       
 
         [0078]    The inventors surprisingly found out that the described approach yields in miRNA signatures that provide high diagnostic accuracy, specificity and sensitivity in the determination of diseases. 
         [0079]    According to a preferred embodiment of the invention, the disease to be determined is Wilms&#39; tumour. 
         [0080]    The inventors succeeded in determining miRNAs that are differentially regulated in samples from Wilms&#39; tumour patients as compared to healthy controls. A complete overview of all miRNAs that are found to be differentially regulated in blood samples of prostate cancer patients is provided in the tables shown in  FIGS. 3 and 4 . 
         [0081]    In the tables shown in  FIGS. 3 and 4 , the miRNAs that are found to be differentially regulated are sorted in the order of their t-test significance. Another method for assessing the significance is to compute the Mutual information (MI) (Shannon, 1984) which is an adequate measure to estimate the overall diagnostic information content of single biomarkers (Keller, Ludwig et al., 2006). According to the invention mutual information is considered as the reduction in uncertainty about the class labels “0” for controls and “1” for tumour samples due to the knowledge of the miRNA expression. 
         [0082]    The higher the value of the MI of a miRNA, the higher is the diagnostic content of the respective miRNA. 
       Diagnosis of Wilms&#39; Tumour 
       [0083]    According to a preferred embodiment of the invention, the disease to be determined is Wilms&#39; tumour. Surprisingly, the inventors found out that miRNAs are differentially regulated in samples from Wilms&#39; tumour patients as compared to healthy controls. In total, 49 miRNAs were found to be significantly deregulated (t-test significance &lt;0.05) in blood cells of Wilms&#39; tumour patients as compared to the healthy controls. 
         [0084]    Thus, preferably the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more nucleic acids selected from the 49 most deregulated miRNAs. 
         [0085]    Preferably, the predetermined set of miRNAs comprises at least 7, preferably at least 10, 15, 20, 25, 30, 35, 40, 50, 75, 100 or all of the above-indicated nucleic acids. 
         [0086]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581. 
         [0087]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f. 
         [0088]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913. 
         [0089]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639. 
         [0090]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*. 
         [0091]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470. 
         [0092]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470, hsa-miR-634, hsa-miR-488, hsa-miR-1298, hsa-miR-20a, hsa-miR-302b*. 
         [0093]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470, hsa-miR-634, hsa-miR-488, hsa-miR-1298, hsa-miR-20a, hsa-miR-302b*, hsa-miR-1258, hsa-miR-548k, hsa-miR-579, hsa-miR-1228, hsa-miR-548h. 
         [0094]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-81d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-90b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470, hsa-miR-634, hsa-miR-488, hsa-miR-1298, hsa-miR-20a, hsa-miR-302b*, hsa-miR-1258, hsa-miR-548k, hsa-miR-579, hsa-miR-1228, hsa-miR-548h, hsa-miR-17, hsa-miR-609, hsa-miR-296-5p, hsa-miR-625*, hsa-miR-1276, hsa-miR-425, hsa-miR-520c-3p, hsa-miR-432, hsa-miR-30a*, hsa-miR-302a. 
         [0095]    In a further embodiment the predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour comprises one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470, hsa-miR-634, hsa-miR-488, hsa-miR-1298, hsa-miR-20a, hsa-miR-302b*, hsa-miR-1258, hsa-miR-548k, hsa-miR-579, hsa-miR-1228, hsa-miR-548h, hsa-miR-17, hsa-miR-609, hsa-miR-296-5p, hsa-miR-625*, hsa-miR-1276, hsa-miR-425, hsa-miR-520c-3p, hsa-miR-432, hsa-miR-30a*, hsa-miR-302a, hsa-miR-384, hsa-miR-106a, hsa-miR-617, hsa-miR-342-3p, hsa-miR-548f, hsa-miR-218-1*, hsa-miR-10b, hsa-miR-548a-3p, hsa-miR-1252, hsa-miR-662, hsa-miR-590-5p, hsa-miR-374a, hsa-miR-126, hsa-miR-876-3p, hsa-miR-720, hsa-miR-519d, hsa-miR-141*, hsa-miR-665, hsa-miR-18b, hsa-miR-589, hsa-miR-30c-2*, hsa-miR-1267, hsa-miR-101, hsa-miR-382. 
         [0096]    Most preferably, the predetermined set of miRNAs comprises those miRNAs that were most significantly deregulated. 
         [0097]    The predetermined set of miRNAs for the diagnosis of Wilms&#39; tumour should preferably comprise at least 7, preferably at least 10, 15, 20, 25, 30, 35, 40, 50, 75, 100, preferably all of the known miRNAs, preferably all of the 863 (see  FIG. 1 , representing the current status of all known miRNAs in the version 12, 13, and 14 of the miRBase repository (www.mirbase.org). 
         [0098]    Another embodiment of the present invention is a kit for diagnosing a disease, comprising means for determining an expression profile of a predetermined set of miRNAs in a biological sample, in particular in a blood and/or serum sample. Preferably, one or more reference expression profiles are also provided which show the expression profile of the same set of miRNAs in the same type of biological sample, in particular in a blood and/or serum sample, obtained from one or more healthy subjects. A comparison to said reference expression profile(s) allows for the diagnosis of the disease. 
         [0099]    Another preferred embodiment of the present invention is a kit for diagnosing Wilms&#39; tumour, comprising means for determining the expression profile of one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470, hsa-miR-634, hsa-miR-488, hsa-miR-1298, hsa-miR-20a, hsa-miR-302b*, hsa-miR-1258, hsa-miR-548k, hsa-miR-579, hsa-miR-1228, hsa-miR-548h, hsa-miR-17, hsa-miR-609, hsa-miR-296-5p, hsa-miR-625*, hsa-miR-1276, hsa-miR-425, hsa-miR-520c-3p, hsa-miR-432, hsa-miR-30a*, hsa-miR-302a. 
         [0100]    The kit for diagnosing Wilms&#39; tumour is particularly suitable for diagnosing Wilms&#39; tumour in a blood and/or serum sample or in a sample comprising erythrocytes, leukocytes and/or thrombocytes. 
         [0101]    The means for determining a predetermined set of miRNAs may for example comprise a microarray comprising miRNA-specific oligonucleotide probes. In a preferred embodiment, the microarray comprises miRNA-specific oligonucleotide probes for the detection of miRNAs. Depending on the intended use of the microarray in the diagnosis or prognosis of a particular disease, probes for detecting different miRNAs may be included. 
         [0102]    A microarray intended for use in the diagnosis of Wilms&#39; tumour preferably comprises miRNA specific oligonucleotide probes for one or more miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470, hsa-miR-634, hsa-miR-488, hsa-miR-1298, hsa-miR-20a, hsa-miR-302b*, hsa-miR-1258, hsa-miR-548k, hsa-miR-579, hsa-miR-1228, hsa-miR-548h, hsa-miR-17, hsa-miR-609, hsa-miR-296-5p, hsa-miR-625*, hsa-miR-276, hsa-miR-425, hsa-miR-520c-3p, hsa-miR-432, hsa-miR-30a*, hsa-miR-302a. 
         [0103]    In a preferred embodiment the microarray comprises oligonucleotide probes for determining at least 7, preferably at least 10, 15, 20, 25, 30, 35, 40, 50, 75, 100 or all of the indicated miRNAs. 
         [0104]    The microarray can comprise oligonucleotide probes obtained from known or predicted miRNA sequences. The array may contain different oligonucleotide probes for each miRNA, for example one containing the active mature sequence and another being specific for the precursor of the miRNA. The array may also contain controls such as one or more sequences differing from the human orthologs by only a few bases, which can serve as controls for hybridization stringency conditions. It is also possible to include viral miRNAs or putative miRNAs as predicted from bioinformatic tools. Further, it is possible to include appropriate controls for non-specific hybridization on the microarray. 
         [0105]    In summary the present invention is composed of the following items: 
         [0106]    1. A method of diagnosing a disease, comprising the steps
       (a) determining an expression profile of a predetermined set of non-coding RNAs, including miRNAs, in a biological sample from a patient; and   (b) comparing said expression profile to a reference expression profile,   wherein the comparison of said determined expression profile to said reference expression profile allows for the diagnosis of the disease, wherein the disease is Wilms&#39; tumour.       
 
         [0110]    2. The method according to any one of item 1, wherein the expression profile is determined of non-coding RNAs, including miRNAs selected from the group consisting of hsa-miR-99b*, hsa-miR-99b, hsa-miR-99a*, hsa-miR-99a, hsa-miR-98, hsa-miR-96*, hsa-miR-96, hsa-miR-95, hsa-miR-944, hsa-miR-943, hsa-miR-942, hsa-miR-941, hsa-miR-940, hsa-miR-939, hsa-miR-938, hsa-miR-937, hsa-miR-936, hsa-miR-935, hsa-miR-934, hsa-miR-933, hsa-miR-93*, hsa-miR-93, hsa-miR-92b*, hsa-miR-92b, hsa-miR-92a-2*, hsa-miR-92a-1*, hsa-miR-92a, hsa-miR-924, hsa-miR-922, hsa-miR-921, hsa-miR-920, hsa-miR-9*, hsa-miR-9, hsa-miR-892b, hsa-miR-892a, hsa-miR-891 b, hsa-miR-891 a, hsa-miR-890, hsa-miR-889, hsa-miR-888*, hsa-miR-888, hsa-miR-887, hsa-miR-886-5p, hsa-miR-886-3p, hsa-miR-885-5p, hsa-miR-885-3p, hsa-miR-877*, hsa-miR-877, hsa-miR-876-5p, hsa-miR-876-3p, hsa-miR-875-5p, hsa-miR-875-3p, hsa-miR-874, hsa-miR-873, hsa-miR-802, hsa-miR-770-5p, hsa-miR-769-5p, hsa-miR-769-3p, hsa-miR-767-5p, hsa-miR-767-3p, hsa-miR-766, hsa-miR-765, hsa-miR-764, hsa-miR-762, hsa-miR-761, hsa-miR-760, hsa-miR-759, hsa-miR-758, hsa-miR-744*, hsa-miR-744, hsa-miR-720, hsa-miR-7-2*, hsa-miR-718, hsa-miR-711, hsa-miR-7-1*, hsa-miR-708*, hsa-miR-708, hsa-miR-7, hsa-miR-675*, hsa-miR-675, hsa-miR-671-5p, hsa-miR-671-3p, hsa-miR-670, hsa-miR-668, hsa-miR-665, hsa-miR-664*, hsa-miR-664, hsa-miR-663b, hsa-miR-663, hsa-miR-662, hsa-miR-661, hsa-miR-660, hsa-miR-659, hsa-miR-658, hsa-miR-657, hsa-miR-656, hsa-miR-655, hsa-miR-654-5p, hsa-miR-654-3p, hsa-miR-653, hsa-miR-652, hsa-miR-651, hsa-miR-650, hsa-miR-649, hsa-miR-648, hsa-miR-647, hsa-miR-646, hsa-miR-645, hsa-miR-644, hsa-miR-643, hsa-miR-642, hsa-miR-641, hsa-miR-640, hsa-miR-639, hsa-miR-638, hsa-miR-637, hsa-miR-636, hsa-miR-635, hsa-miR-634, hsa-miR-633, hsa-miR-632, hsa-miR-631, hsa-miR-630, hsa-miR-629*, hsa-miR-629, hsa-miR-628-5p, hsa-miR-628-3p, hsa-miR-627, hsa-miR-626, hsa-miR-625*, hsa-miR-625, hsa-miR-624*, hsa-miR-624, hsa-miR-623, hsa-miR-622, hsa-miR-621, hsa-miR-620, hsa-miR-619, hsa-miR-618, hsa-miR-617, hsa-miR-616*, hsa-miR-616, hsa-miR-615-5p, hsa-miR-615-3p, hsa-miR-614, hsa-miR-613, hsa-miR-612, hsa-miR-611, hsa-miR-610, hsa-miR-609, hsa-miR-608, hsa-miR-607, hsa-miR-606, hsa-miR-605, hsa-miR-604, hsa-miR-603, hsa-miR-602, hsa-miR-601, hsa-miR-600, hsa-miR-599, hsa-miR-598, hsa-miR-597, hsa-miR-596, hsa-miR-595, hsa-miR-593*, hsa-miR-593, hsa-miR-592, hsa-miR-591, hsa-miR-590-5p, hsa-miR-590-3p, hsa-miR-589*, hsa-miR-589, hsa-miR-588, hsa-miR-587, hsa-miR-586, hsa-miR-585, hsa-miR-584, hsa-miR-583, hsa-miR-582-5p, hsa-miR-582-3p, hsa-miR-581, hsa-miR-580, hsa-miR-579, hsa-miR-578, hsa-miR-577, hsa-miR-576-5p, hsa-miR-576-3p, hsa-miR-575, hsa-miR-574-5p, hsa-miR-574-3p, hsa-miR-573, hsa-miR-572, hsa-miR-571, hsa-miR-570, hsa-miR-569, hsa-miR-568, hsa-miR-567, hsa-miR-566, hsa-miR-564, hsa-miR-563, hsa-miR-562, hsa-miR-561, hsa-miR-559, hsa-miR-558, hsa-miR-557, hsa-miR-556-5p, hsa-miR-556-3p, hsa-miR-555, hsa-miR-554, hsa-miR-553, hsa-miR-552, hsa-miR-551 b*, hsa-miR-551 b, hsa-miR-551a, hsa-miR-550*, hsa-miR-550, hsa-miR-549, hsa-miR-548q, hsa-miR-548p, hsa-miR-548o, hsa-miR-548n, hsa-miR-548m, hsa-miR-5481, hsa-miR-548k, hsa-miR-548j, hsa-miR-548i, hsa-miR-548h, hsa-miR-548g, hsa-miR-548f, hsa-miR-548e, hsa-miR-548d-5p, hsa-miR-548d-3p, hsa-miR-548c-5p, hsa-miR-548c-3p, hsa-miR-548b-5p, hsa-miR-548b-3p, hsa-miR-548a-5p, hsa-miR-548a-3p, hsa-miR-545*, hsa-miR-545, hsa-miR-544, hsa-miR-543, hsa-miR-542-5p, hsa-miR-542-3p, hsa-miR-541*, hsa-miR-541, hsa-miR-539, hsa-miR-532-5p, hsa-miR-532-3p, hsa-miR-527, hsa-miR-526b*, hsa-miR-526b, hsa-miR-526a, hsa-miR-525-5p, hsa-miR-525-3p, hsa-miR-524-5p, hsa-miR-524-3p, hsa-miR-523*, hsa-miR-523, hsa-miR-522*, hsa-miR-522, hsa-miR-521, hsa-miR-520h, hsa-miR-520g, hsa-miR-520f, hsa-miR-520e, hsa-miR-520d-5p, hsa-miR-520d-3p, hsa-miR-520c-5p, hsa-miR-520c-3p, hsa-miR-520b, hsa-miR-520a-5p, hsa-miR-520a-3p, hsa-miR-519e*, hsa-miR-519e, hsa-miR-519d, hsa-miR-519c-5p, hsa-miR-5 9c-3p, hsa-miR-519b-5p, hsa-miR-5 9b-3p, hsa-miR-519a*, hsa-miR-519a, hsa-miR-518f, hsa-miR-518f, hsa-miR-518e*, hsa-miR-518e, hsa-miR-518d-5p, hsa-miR-518d-3p, hsa-miR-518c*, hsa-miR-518c, hsa-miR-518b, hsa-miR-518a-5p, hsa-miR-518a-3p, hsa-miR-517c, hsa-miR-517b, hsa-miR-517a, hsa-miR-517*, hsa-miR-516b*, hsa-miR-516b, hsa-miR-516a-5p, hsa-miR-516a-3p, hsa-miR-515-5p, hsa-miR-515-3p, hsa-miR-514, hsa-miR-513c, hsa-miR-513b, hsa-miR-513a-5p, hsa-miR-513a-3p, hsa-miR-512-5p, hsa-miR-512-3p, hsa-miR-511, hsa-miR-510, hsa-miR-509-5p, hsa-miR-509-3p, hsa-miR-509-3-5p, hsa-miR-508-5p, hsa-miR-508-3p, hsa-miR-507, hsa-miR-506, hsa-miR-505*, hsa-miR-505, hsa-miR-504, hsa-miR-503, hsa-miR-502-5p, hsa-miR-502-3p, hsa-miR-501-5p, hsa-miR-501-3p, hsa-miR-500*, hsa-miR-500, hsa-miR-499-5p, hsa-miR-499-3p, hsa-miR-498, hsa-miR-497*, hsa-miR-497, hsa-miR-496, hsa-miR-495, hsa-miR-494, hsa-miR-493*, hsa-miR-493, hsa-miR-492, hsa-miR-491-5p, hsa-miR-491 -3p, hsa-miR-490-5p, hsa-miR-490-3p, hsa-miR-489, hsa-miR-488*, hsa-miR-488, hsa-miR-487b, hsa-miR-487a, hsa-miR-486-5p, hsa-miR-486-3p, hsa-miR-485-5p, hsa-miR-485-3p, hsa-miR-484, hsa-miR-483-5p, hsa-miR-483-3p, hsa-miR-455-5p, hsa-miR-455-3p, hsa-miR-454*, hsa-miR-454, hsa-miR-453, hsa-miR-452*, hsa-miR-452, hsa-miR-451, hsa-miR-450b-5p, hsa-miR-450b-3p, hsa-miR-450a, hsa-miR-449c*, hsa-miR-449c, hsa-miR-449b*, hsa-miR-449b, hsa-miR-449a, hsa-miR-448, hsa-miR-433, hsa-miR-432*, hsa-miR-432, hsa-miR-431*, hsa-miR-431, hsa-miR-429, hsa-miR-425*, hsa-miR-425, hsa-miR-424*, hsa-miR-424, hsa-miR-423-5p, hsa-miR-423-3p, hsa-miR-422a, hsa-miR-421, hsa-miR-412, hsa-miR-411*, hsa-miR-411, hsa-miR-410, hsa-miR-409-5p, hsa-miR-409-3p, hsa-miR-384, hsa-miR-383, hsa-miR-382, hsa-miR-381, hsa-miR-380*, hsa-miR-380, hsa-miR-379*, hsa-miR-379, hsa-miR-378*, hsa-miR-378, hsa-miR-377*, hsa-miR-377, hsa-miR-376c, hsa-miR-376b, hsa-miR-376a*, hsa-miR-376a, hsa-miR-375, hsa-miR-374b*, hsa-miR-374b, hsa-miR-374a*, hsa-miR-374a, hsa-miR-373*, hsa-miR-373, hsa-miR-372, hsa-miR-371-5p, hsa-miR-371-3p, hsa-miR-370, hsa-miR-369-5p, hsa-miR-369-3p, hsa-miR-367*, hsa-miR-367, hsa-miR-365*, hsa-miR-365, hsa-miR-363*. hsa-miR-363, hsa-miR-362-5p, hsa-miR-362-3p, hsa-miR-361-5p, hsa-miR-361-3p, hsa-miR-34c-5p, hsa-miR-34c-3p, hsa-miR-34b*, hsa-miR-34b, hsa-miR-34a*, hsa-miR-34a, hsa-miR-346, hsa-miR-345, hsa-miR-342-5p, hsa-miR-342-3p, hsa-miR-340*, hsa-miR-340, hsa-miR-33b*, hsa-miR-33b, hsa-miR-33a*, hsa-miR-33a, hsa-miR-339-5p, hsa-miR-339-3p, hsa-miR-338-5p, hsa-miR-338-3p, hsa-miR-337-5p, hsa-miR-337-3p, hsa-miR-335*, hsa-miR-335, hsa-miR-331-5p, hsa-miR-331-3p, hsa-miR-330-5p, hsa-miR-330-3p, hsa-miR-329, hsa-miR-328, hsa-miR-326, hsa-miR-325, hsa-miR-324-5p, hsa-miR-324-3p, hsa-miR-323-5p, hsa-miR-323-3p, hsa-miR-320d, hsa-miR-320c, hsa-miR-320b, hsa-miR-320a, hsa-miR-32*, hsa-miR-32, hsa-miR-31*, hsa-miR-31, hsa-miR-30e*, hsa-miR-30e, hsa-miR-30d*, hsa-miR-30d, hsa-miR-30c-2*, hsa-miR-30c-1*, hsa-miR-30c, hsa-miR-30b*, hsa-miR-30b, hsa-miR-30a*, hsa-miR-30a, hsa-miR-302f, hsa-miR-302e, hsa-miR-302d*, hsa-miR-302d, hsa-miR-302c*, hsa-miR-302c, hsa-miR-302b*, hsa-miR-302b, hsa-miR-302a*, hsa-miR-302a, hsa-miR-301 b, hsa-miR-301 a, hsa-miR-300, hsa-miR-29c*, hsa-miR-29c, hsa-miR-29b-2*, hsa-miR-29b-1*, hsa-miR-29b, hsa-miR-29a*, hsa-miR-29a, hsa-miR-299-5p, hsa-miR-299-3p, hsa-miR-298, hsa-miR-297, hsa-miR-296-5p, hsa-miR-296-3p, hsa-miR-28-5p, hsa-miR-28-3p, hsa-miR-27b*, hsa-miR-27b, hsa-miR-27a*, hsa-miR-27a, hsa-miR-26b*, hsa-miR-26b, hsa-miR-26a-2*, hsa-miR-26a-1*, hsa-miR-26a, hsa-miR-25*, hsa-miR-25, hsa-miR-24-2*, hsa-miR-24-1*, hsa-miR-24, hsa-miR-23b*, hsa-miR-23b, hsa-miR-23a*, hsa-miR-23a, hsa-miR-2278, hsa-miR-2277, hsa-miR-2276, hsa-miR-224*, hsa-miR-224, hsa-miR-223*, hsa-miR-223, hsa-miR-222*, hsa-miR-222, hsa-miR-221*, hsa-miR-221, hsa-miR-220c, hsa-miR-220b, hsa-miR-220a, hsa-miR-22*, hsa-miR-22, hsa-miR-219-5p, hsa-miR-219-2-3p, hsa-miR-219-1-3p, hsa-miR-218-2*, hsa-miR-218-1*, hsa-miR-218, hsa-miR-217, hsa-miR-216b, hsa-miR-216a, hsa-miR-2 5, hsa-miR-214*, hsa-miR-214, hsa-miR-212, hsa-miR-2117, hsa-miR-2116*, hsa-miR-2116, hsa-miR-2115*, hsa-miR-2115, hsa-miR-2114*, hsa-miR-2114, hsa-miR-2113, hsa-miR-2 10, hsa-miR-211, hsa-miR-210, hsa-miR-21*, hsa-miR-21, hsa-miR-20b*, hsa-miR-20b, hsa-miR-20a*, hsa-miR-20a, hsa-miR-208b, hsa-miR-208a, hsa-miR-206, hsa-miR-2054, hsa-miR-2053, hsa-miR-2052, hsa-miR-205*, hsa-miR-205, hsa-miR-204, hsa-miR-203, hsa-miR-202*, hsa-miR-202, hsa-miR-200c*, hsa-miR-200c, hsa-miR-200b*, hsa-miR-200b, hsa-miR-200a*, hsa-miR-200a, hsa-miR-19b-2*, hsa-miR-19b-1*, hsa-miR-19b, hsa-miR-19a*, hsa-miR-19a, hsa-miR-99b-5p, hsa-miR-199b-3p, hsa-miR-199a-5p, hsa-miR-199a-3p, hsa-miR-198, hsa-miR-1979, hsa-miR-1978, hsa-miR-1977, hsa-miR-1976, hsa-miR-1975, hsa-miR-1974, hsa-miR-1973, hsa-miR-1972, hsa-miR-197, hsa-miR-196b*, hsa-miR-196b, hsa-miR-196a*, hsa-miR-196a, hsa-miR-195*, hsa-miR-195, hsa-miR-194*, hsa-miR-194, hsa-miR-193b*, hsa-miR-193b, hsa-miR-193a-5p, hsa-miR-193a-3p, hsa-miR-192*, hsa-miR-192, hsa-miR-1915*, hsa-miR-1915, hsa-miR-1914*, hsa-miR-1914, hsa-miR-1913, hsa-miR-1912, hsa-miR-1911*, hsa-miR-1911, hsa-miR-1910, hsa-miR-191*, hsa-miR-191, hsa-miR-190b, hsa-miR-1909*, hsa-miR-1909, hsa-miR-1908, hsa-miR-190, hsa-miR-18b*, hsa-miR-18b, hsa-miR-18a*, hsa-miR-18a, hsa-miR-188-5p, hsa-miR-188-3p, hsa-miR-187*, hsa-miR-187, hsa-miR-186*, hsa-miR-186, hsa-miR-185*, hsa-miR-185, hsa-miR-184, hsa-miR-183*, hsa-miR-183, hsa-miR-1827, hsa-miR-1826, hsa-miR-1825, hsa-miR-182*, hsa-miR-182, hsa-miR-181d, hsa-miR-181c*, hsa-miR-181c, hsa-miR-181 b, hsa-miR-181a-2*, hsa-miR-181a*, hsa-miR-181a, hsa-miR-17*, hsa-miR-17, hsa-miR-16-2*, hsa-miR-16-1*, hsa-miR-16, hsa-miR-15b*, hsa-miR-15b, hsa-miR-15a*, hsa-miR-15a, hsa-miR-155*, hsa-miR-155, hsa-miR-154*, hsa-miR-154, hsa-miR-1539, hsa-miR-1538, hsa-miR-1537, hsa-miR-153, hsa-miR-152, hsa-miR-151-5p, hsa-miR-151-3p, hsa-miR-150*, hsa-miR-150, hsa-miR-149*, hsa-miR-149, hsa-miR-148b*, hsa-miR-148b, hsa-miR-148a*, hsa-miR-148a, hsa-miR-147b, hsa-miR-1471, hsa-miR-1470, hsa-miR-147, hsa-miR-146b-5p, hsa-miR-146b-3p, hsa-miR-146a*, hsa-miR-146a, hsa-miR-1469, hsa-miR-1468, hsa-miR-145*, hsa-miR-145, hsa-miR-144*, hsa-miR-144, hsa-miR-143*, hsa-miR-143, hsa-miR-142-5p, hsa-miR-142-3p, hsa-miR-41*, hsa-miR-141, hsa-miR-140-5p, hsa-miR-140-3p, hsa-miR-139-5p, hsa-miR-139-3p, hsa-miR-138-2*, hsa-miR-138-1*, hsa-miR-138, hsa-miR-137, hsa-miR-136*, hsa-miR-136, hsa-miR-135b*, hsa-miR-135b, hsa-miR-135a*, hsa-miR-135a, hsa-miR-134, hsa-miR-133b, hsa-miR-133a, hsa-miR-1324, hsa-miR-1323, hsa-miR-1322, hsa-miR-1321, hsa-miR-132*, hsa-miR-132, hsa-miR-130b*, hsa-miR-130b, hsa-miR-130a*, hsa-miR-130a, hsa-miR-1308, hsa-miR-1307, hsa-miR-1306, hsa-miR-1305, hsa-miR-1304, hsa-miR-1303, hsa-miR-1302, hsa-miR-1301, hsa-miR-1299, hsa-miR-1298, hsa-miR-1297, hsa-miR-1296, hsa-miR-129-5p, hsa-miR-1295, hsa-miR-1294, hsa-miR-129-3p, hsa-miR-1293, hsa-miR-1292, hsa-miR-1291, hsa-miR-1290, hsa-miR-129*, hsa-miR-1289, hsa-miR-1288, hsa-miR-1287, hsa-miR-1286, hsa-miR-1285, hsa-miR-1284, hsa-miR-1283, hsa-miR-1282, hsa-miR-1281, hsa-miR-1280, hsa-miR-128, hsa-miR-1279, hsa-miR-1278, hsa-miR-1277, hsa-miR-1276, hsa-miR-127-5p, hsa-miR-1275, hsa-miR-1274b, hsa-miR-1274a, hsa-miR-127-3p, hsa-miR-1273, hsa-miR-1272, hsa-miR-1271, hsa-miR-1270, hsa-miR-1269, hsa-miR-1268, hsa-miR-1267, hsa-miR-1266, hsa-miR-1265, hsa-miR-1264, hsa-miR-1263, hsa-miR-1262, hsa-miR-1261, hsa-miR-1260, hsa-miR-126*, hsa-miR-126, hsa-miR-125b-2*, hsa-miR-125b-1*, hsa-miR-125b, hsa-miR-125a-5p, hsa-miR-125a-3p, hsa-miR-1259, hsa-miR-1258, hsa-miR-1257, hsa-miR-1256, hsa-miR-1255b, hsa-miR-1255a, hsa-miR-1254, hsa-miR-1253, hsa-miR-1252, hsa-miR-1251, hsa-miR-1250, hsa-miR-1249, hsa-miR-1248, hsa-miR-1247, hsa-miR-1246, hsa-miR-1245, hsa-miR-1244, hsa-miR-1243, hsa-miR-124*, hsa-miR-124, hsa-miR-1238, hsa-miR-1237, hsa-miR-1236, hsa-miR-1234, hsa-miR-1233, hsa-miR-1231, hsa-miR-1229, hsa-miR-1228*, hsa-miR-1228, hsa-miR-1227, hsa-miR-1226*, hsa-miR-1226, hsa-miR-1225-5p, hsa-miR-1225-3p, hsa-miR-1224-5p, hsa-miR-1224-3p, hsa-miR-122*, hsa-miR-122, hsa-miR-1208, hsa-miR-1207-5p, hsa-miR-1207-3p, hsa-miR-1206, hsa-miR-1205, hsa-miR-1204, hsa-miR-1203, hsa-miR-1202, hsa-miR-1201, hsa-miR-1200, hsa-miR-1197, hsa-miR-1185, hsa-miR-1184, hsa-miR-1183, hsa-miR-1 82, hsa-miR-1181, hsa-miR-1180, hsa-miR-1179, hsa-miR-1178, hsa-miR-10b*, hsa-miR-10b, hsa-miR-10a*, hsa-miR-10a, hsa-miR-107, hsa-miR-106b*, hsa-miR-106b, hsa-miR-106a*, hsa-miR-106a, hsa-miR-105*, hsa-miR-105, hsa-miR-103-as, hsa-miR-03-2*, hsa-miR-103, hsa-miR-101*, hsa-miR-101, hsa-miR-100*, hsa-miR-100, hsa-miR-1, hsa-let-7i*, hsa-let-7i, hsa-let-7g*, hsa-let-7g, hsa-let-7f-2*, hsa-let-7f-1*, hsa-let-7f, hsa-let-7e*, hsa-let-7e, hsa-let-7d*, hsa-let-7d, hsa-let-7c*, hsa-let-7c, hsa-let-7b*, hsa-let-7b, hsa-let-7a-2*, hsa-let-7a*, hsa-let-7a, hsa-life-1, hsa-life-2, hsa-life-2-AS, hsa-life-3, hsa-life-4, hsa-life-6-5p, hsa-life-6-3p, hsa-life-7-AS, hsa-life-7, hsa-life-9, hsa-life-9-AS, hsa-life-1, hsa-life-12-5p, hsa-life-12-3p, hsa-life-13-3p, hsa-life-13-5p, hsa-life-14-3p, hsa-life-4-5p, hsa-life-17, hsa-life-21, hsa-life-22, hsa-life-26-3p, hsa-life-26-5p, hsa-life-27, hsa-life-31-5p, hsa-life-31-3p, hsa-life-33-AS, hsa-life-33, hsa-life-36-3p, hsa-life-36-5p, hsa-life-37-3p, hsa-life-37-5p, hsa-life-5-5p, hsa-life-5-3p, hsa-life-8, hsa-life-10, hsa-life-5-3p, hsa-life-15-5p, hsa-life-16-5p, hsa-life-16-3p, hsa-life-18, hsa-life-19-5p, hsa-life-19-3p, hsa-life-20-3p, hsa-life-20-5p, hsa-life-23-3p, hsa-life-23-5p, hsa-life-24, hsa-life-25, hsa-life-28-3p, hsa-life-28-5p, hsa-life-29, hsa-life-30, hsa-life-32-AS, hsa-life-32, hsa-life-34-3p, hsa-life-34-5p, hsa-life-35. 
         [0111]    3. The method according to item 1 or 2, wherein the predetermined set of miRNAs representative for Wilms&#39; tumour comprises at least 1, 7, 10, 15, 20, 25, 30, 35, 40, 50, 75, 100 of non-coding RNAs including miRNAs. 
         [0112]    4. The method according to item 1, 2 or 3, wherein the predetermined set of miRNAs representative for diagnosis of Wilms&#39; tumour comprises at least 1, 7, 10, 15, 20, 25, 30, 35, 40, 50, 75, 100 of the miRNAs selected from the group consisting of hsa-miR-23b*, hsa-miR-875-5p, hsa-miR-181d, hsa-miR-144*, hsa-miR-10a*, hsa-miR-144, hsa-miR-581, hsa-miR-218, hsa-miR-1294, hsa-miR-302f, hsa-miR-944, hsa-miR-92a-1*, hsa-miR-190b, hsa-miR-20b, hsa-miR-1913, hsa-miR-96, hsa-miR-363, hsa-miR-590-3p, hsa-miR-140-5p, hsa-miR-639, hsa-miR-1305, hsa-miR-651, hsa-miR-556-3p, hsa-miR-139-5p, hsa-miR-545*, hsa-miR-632, hsa-miR-103, hsa-miR-105*, hsa-miR-1249, hsa-miR-1470, hsa-miR-634, hsa-miR-488, hsa-miR-1298, hsa-miR-20a, hsa-miR-302b*, hsa-miR-1258, hsa-miR-548k, hsa-miR-579, hsa-miR-1228, hsa-miR-548h, hsa-miR-17, hsa-miR-609, hsa-miR-296-5p, hsa-miR-625*, hsa-miR-1276, hsa-miR-425, hsa-miR-520c-3p, hsa-miR-432, hsa-miR-30a*, hsa-miR-302a, hsa-miR-384, hsa-miR-106a, hsa-miR-617, hsa-miR-342-3p, hsa-miR-548f, hsa-miR-218-1*, hsa-miR-10b, hsa-miR-548a-3p, hsa-miR-1252, hsa-miR-662, hsa-miR-590-5p, hsa-miR-374a, hsa-miR-126, hsa-miR-876-3p, hsa-miR-720, hsa-miR-519d, hsa-miR-141*, hsa-miR-665, hsa-miR-18b, hsa-miR-589, hsa-miR-30c-2*, hsa-miR-1267, hsa-miR-101, hsa-miR-382. 
         [0113]    5. The method according to any one of items 1-4 wherein said biological sample is selected from blood and/or serum or urine samples. 
         [0114]    6. The method according to any one of items 1-5 wherein miRNA the expression profile is determined by nucleic acid hybridization, nucleic acid amplification, polymerase extension, sequencing, mass spectroscopy or any combinations thereof. 
         [0115]    7. The method according to any one of items 1-6, wherein the miRNA expression profile of said subject and the reference expression profiles and optionally the predetermined set of miRNAs are stored in a database. 
         [0116]    8. The method according to any one of items 1-7, wherein the biological sample is not labeled prior to determination of the expression profile. 
         [0117]    9. The method according to any one of items 1-8 wherein the diagnosis comprises determining survival rate, responsiveness to drugs, and/or monitoring the course of the disease or the therapy, e.g. chemotherapy. 
         [0118]    10. The method of item 6 wherein the nucleic acid hybridisation is performed using a solid-phase nucleic acid biochip array, in particular a microarray or in situ hybridisation, and/or wherein the nucleic acid amplification is performed via a real-time PGR (RT-PCR). 
         [0119]    11. A kit for diagnosing and/or predicting Wilms&#39; tumour of a subject, comprising:
       (a) means for determining the miRNA expression profile of a RNA sample of a subject, and   (b) at least one reference set of miRNA profile characteristic for a particular condition.       
 
         [0122]    So far, miRNAs have been extensively studied in tissue material. It has been found that miRNAs are expressed in a highly tissue-specific manner. Disease-specific expression of miRNAs have been reported in many human cancers employing primarily tissue material as the miRNA source. In this context miRNAs expression profiles were found to be useful in identifying the tissue of origin for cancers of unknown primary origin. Since recently it is known that miRNAs are not only present in tissues but also in other body fluid samples, including human blood. Nevertheless, the mechanism why miRNAs are found in body fluids, especially in blood, or their function in these body fluids is not understood yet. 
         [0123]    Various miRNA biomarkers found in tissue material have been proposed to be correlated with certain diseases, e.g. cancer. However, there is still a need for novel miRNAs as biomarkers for the detection and/or prediction of these and other types of diseases. Especially desirable are non-invasive biomarkers, that allow for quick, easy and cost-effective diagnosis/prognosis which cause only minimal stress for the patient eliminating the need for surgical intervention 
         [0124]    Particularly, the potential role of miRNAs as non-invasive biomarkers for the diagnosis and/or prognosis of Wilms&#39; tumour has not been systematically evaluated yet. In addition, many of the miRNA biomarkers presently available for diagnosing and/or prognosing of diseases have shortcomings such as reduced sensitivity, not sufficient specificity or do not allow timely diagnosis or represent invasive biomarkers. Accordingly, there is still a need for novel and efficient miRNAs or sets of miRNAs as markers, effective methods and kits for the non-invasive diagnosis and/or prognosis of diseases such as Wilms&#39; tumour. 
         [0125]    The inventors of the present invention assessed for the first time the expression of miRNAs on a whole-genome level in subjects with Wilms&#39; tumour as non-invasive biomarkers from body fluids, preferably in blood. They surprisingly found that miRNAs are significantly dysregulated in blood of Wilms&#39; tumour subjects in comparison to healthy controls and thus, miRNAs are appropriated non-invasive biomarkers for diagnosing and/or prognosing of Wilms&#39; tumour. This finding is surprising, since there is nearly no overlap of the miRNA biomarkers found in blood and the miRNA biomarkers found in tissue material representing the origin of the disease. The inventors of the present invention surprisingly found miRNA biomarkers in body fluids, especially in blood, that have not been found to be correlated to Wilms&#39; tumour when tissues material was used for this kind of analysis. Therefore, the inventors of the invention identified for the first time miRNAs as non-invasive surrogate biomarkers for diagnosis and/or prognosis of Wilms&#39; tumour. The inventors of the present invention identified single miRNAs which predict Wilms&#39; tumour with high specificity, sensitivity and accuracy. The inventors of the present invention also pursued a multiple biomarker strategy, thus implementing sets of miRNA biomarkers for diagnosing and/or prognosing of Wilms&#39; tumour leading to added specificity, sensitivity, accuracy and predictive power, thereby circumventing the limitations of single biomarker. In detail, by using a machine learning algorithms, they identified unique sets of miRNAs (miRNA signatures) that allow for non-invasive diagnosis of Wilms&#39; tumour with even higher power, indicating that sets of miRNAs (miRNA signatures) derived from a body fluid sample, such as blood from a subject (e.g. human) can be used as novel non-invasive biomarkers. 
         [0126]    The inventors of the present invention surprisingly found that miRNAs are significantly dysregulated in body fluid samples such as blood of Wilms&#39; tumour subjects in comparison to a cohort of controls (healthy subjects) and thus, miRNAs are appropriated biomarkers for diagnosing and/or prognosing of Wilms&#39; tumour in a non-invasive fashion. Furthermore, the predetermined sets of miRNAs of the present invention lead to high performance in diagnosing and/or prognosing of Wilms&#39; tumour, thus expose very high specificity, sensitivity and accuracy. They succeeded in determining the miRNAs that are differentially regulated in body fluid samples from patients having Wilms&#39; tumour compared to a cohort of controls (healthy subjects) (see experimental section for experimental details). Additionally, the inventors of the present invention performed hypothesis tests (e.g. t-test, limma-test) or other measurements (e.g. AUC, mutual information) on the expression level of the found miRNAs, in all controls (healthy subjects) and subjects suffering from Wilms&#39; tumour. These tests resulted in a significance value (p-value) for each miRNA. This p-value is a measure for the diagnostic power of each of these single miRNAs to discriminate, for example, between the two clinical conditions: controls (healthy subjects), i.e. not suffering from Wilms&#39; tumour, or diseased, i.e. suffering from Wilms&#39; tumour. Since a manifold of tests are carried out, one for each miRNA, the p-values may be too optimistic and, thus, over-estimate the actual discriminatory power. Hence, the p-values are corrected for multiple testing by the Benjamini Hochberg approach. 
         [0127]    The term “body fluid sample”, as used in the context of the present invention, refers to liquids originating from the body of a subject. Said body fluid samples include, but are not limited to, blood, urine, sputum, breast milk, cerebrospinal fluid, cerumen (earwax), endolymph, perilymph, gastric juice, mucus, peritoneal fluid, pleural fluid, saliva, sebum (skin oil), semen, sweat, tears, vaginal secretion, vomit including components or fractions thereof. Said body fluid samples may be mixed or pooled, e.g. a body fluid sample may be a mixture of blood and urine samples or blood and tissue material. A “body fluid sample” may be provided by removing a body liquid from a subject, but may also be provided by using previously isolated sample material. Preferably, the body fluid sample from a subject (e.g. human or animal) has a volume of between 0.1 and 20 ml, more preferably of between 0.5 and 10 ml, more preferably between 1 and 8 ml and most preferably between 2 and 5 ml, i.e. 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 ml. In the context of the present invention said “body fluid sample” allows for a non-invasive diagnosis/and or prognosis of a subject. 
         [0128]    The term “blood sample”, as used in the context of the present invention, refers to a blood sample originating from a subject. The “blood sample” may be derived by removing blood from a subject by conventional blood collecting techniques, but may also be provided by using previously isolated and/or stored blood samples. For example a blood sample may be whole blood, plasma, serum, PBMC (peripheral blood mononuclear cells), blood cellular fractions including red blood cells (erythrocytes), white blood cells (leukocytes), platelets (thrombocytes), or blood collected in blood collection tubes (e.g. EDTA-, heparin-, citrate-, PAXgene- , Tempus-tubes) including components or fractions thereof. For example, a blood sample may be taken from a subject suspected to be affected or to be suspected to be affected by Wilms&#39; tumour, prior to initiation of a therapeutic treatment, during the therapeutic treatment and/or after the therapeutic treatment. Preferably, the blood sample from a subject (e.g. human or animal) has a volume of between 0.1 and 20 ml, more preferably of between 0.5 and 10 ml, more preferably between 1 and 8 ml and most preferably between 2 and 5 ml, i.e. 
         [0129]    0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 ml. In the context of the present invention said “body fluid sample” allows for a non-invasive diagnosis/and or prognosis of a subject. 
         [0130]    Preferably, when the blood sample is collected from the subject the RNA-fraction, especially the miRNA fraction, is guarded against degradation. For this purpose special collection tubes (e.g. PAXgene RNA tubes from Preanalytix, Tempus Blood RNA tubes from Applied Biosystems) or additives (e.g. RNAlater from Ambion, RNAsin from Promega) that stabilize the RNA fraction and/or the miRNA fraction are employed. 
         [0131]    The biological sample, preferably the body fluid sample may be from a subject (e.g. human or mammal) that has been therapeutically treated or that has not been therapeutically treated. In one embodiment, the therapeutical treatment is monitored on the basis of the detection of the miRNA or set of imiRNAs by the polynucleotide or set of polynucleotides of the invention. It is also preferred that total RNA or a subfraction thereof, isolated (e.g. extracted) from a biological sample of a subject (e.g. human or animal), is used for detecting the miRNA or set of miRNAs by the polynucleotide or set of polynucleotides or primer pairs of the invention. 
         [0132]    The term “non-invasive”, as used in the context of the present invention, refers to methods for obtaining a biological sample, particularly a body fluid sample, without the need for an invasive surgical intervention or invasive medical procedure. In the context of the present invention, a blood drawn represents a non-invasive procedure, therefore a blood-based test (utilizing blood or fractions thereof) is a non-invasive test. Other body fluid samples for non-invasive tests are e.g. urine, sputum, tears, mothers mild, cerumen, sweat, saliva, vaginal secretion, vomit, etc. 
         [0133]    The term “diagnosis” as used in the context of the present invention refers to the process of determining a possible disease or disorder and therefore is a process attempting to define the (clinical) condition of a subject. The determination of the expression level of a set of miRNAs according to the present invention correlates with the (clinical) condition of a subject. Preferably, the diagnosis comprises (i) determining the occurrence/presence of Wilms&#39; tumour, (ii) monitoring the course of Wilms&#39; tumour, (iii) staging of Wilms&#39; tumour, (iv) measuring the response of a patient with Wilms&#39; tumour to therapeutic intervention, and/or (v) segmentation of a subject suffering from Wilms&#39; tumour. 
         [0134]    The term “prognosis” as used in the context of the present invention refers to describing the likelihood of the outcome or course of a disease or a disorder. Preferably, the prognosis comprises (i) identifying of a subject who has a risk to develop Wilms&#39; tumour, (ii) predicting/estimating the occurrence, preferably the severity of occurrence of Wilms&#39; tumour, and/or(iii) predicting the response of a subject with Wilms&#39; tumour to therapeutic intervention. 
         [0135]    The term “suffering or suspected to be suffering from Wilms&#39; tumour” as used in the context of the present invention comprises the diagnosis and/or prognosis of Wilms&#39; tumour in a suspect as defined above. 
         [0136]    In a first aspect, the present invention relates to a method for diagnosing and/or prognosing of Wilms&#39; tumour comprising the steps of:
       (i) determining an expression profile of a predetermined set comprising at least two miRNAs representative for Wilms&#39; tumour in a body fluid sample from a subject, and   (ii) comparing said expression profile to a reference expression profile, wherein the comparison of said expression profile to said reference expression profile allows for the diagnosis and/or prognosis of Wilms&#39; tumour.       
 
         [0139]    It is preferred that the body fluid sample is a blood sample, particularly preferred it is a whole blood, PBMC, serum or plasma sample, more particularly preferred it is a whole blood sample. 
         [0140]    It is preferred that the subject is a mammal including both a human and another mammal, e.g. an animal such as a mouse, a rat, a rabbit, or a monkey. It is particularly preferred that the subject is a human. 
         [0141]    Preferably, the predetermined set comprising at least two miRNAs is selected from the set of miRNAs listed in  FIG. 3  or  4 . 
         [0142]    It is preferred that the predetermined set comprising at least two miRNAs is selected from the sets of miRNAs listed in  FIG. 5  (SNW-1 to SNW-640). 
         [0143]    It is also preferred that the predetermined set comprising at least two miRNAs comprises at least one set of miRNAs listed in  FIG. 5 . 
         [0144]    Further, in a preferred embodiment of the method of the present invention, for determining an expression profile of the predetermined set comprising at least two miRNAs representative for Wilms&#39; tumour in a body fluid sample from a subject comprises the miRNAs from one set or a plurality of sets of miRNAs listed in  FIG. 5 . 
         [0145]    For example, a set comprising 30 miRNAs representative for Wilms&#39; tumour in a body fluid sample from a subject comprises at least the miRNAs from one predetermined set or several sets of miRNAs listed in  FIG. 5 . Alternatively, a set comprising 29, 28, 27,26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4 or 3 miRNAs representative for Wilms&#39; tumour comprises at least the miRNAs from one set or several sets of miRNAs listed in  FIG. 5 . 
         [0146]    Further, in another preferred embodiment of the method of the present invention, for determining an expression profile of the predetermined set comprising at least two miRNAs representative for Wilms&#39; tumour in a body fluid sample from a subject comprises combinations of sets of miRNAs listed in  FIG. 5 . 
         [0147]    For example, said predetermined set comprising 30 miRNAs representative for Wilms&#39; tumour in a body fluid sample from a subject comprises at least 2, e.g. 2, 3, 4, 5 or 6, sets of miRNAs listed in  FIG. 5 . Alternatively, said set comprising 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5 or 4 miRNAs comprises a least 2, e.g. 2, 3, 4, 5 or 6, sets of miRNAs listed in  FIG. 5 . 
         [0148]    The reference expression profile may be obtained from at least two subjects (e.g. human or animal). Preferably the reference expression profile is an average expression profile (data) of at least 2 to 400 subjects, more preferably at least 20 to 200 subjects, and most preferably at least 40 to 150 subjects, with one known clinical condition which is Wilms&#39; tumour or a specific form of Wilms&#39; tumour. 
         [0149]    It is particularly preferred that the reference expression profile is an algorithm or mathematical function. Preferably the algorithm or mathematical function is obtained from a reference expression profile (data) of at least two subjects, preferably the algorithm or mathematical function is obtained from an average reference expression profile (data) of at least 2 to 400 subjects, more preferably of at least 20 to 200 subjects, and most preferably of at least 40 to 150 subjects. 
         [0150]    It is preferred that the algorithm or mathematical function is obtained using a machine learning approach. 
         [0151]    Preferably, the algorithm or mathematical function is saved on a data carrier comprised in the kit (according to the seventh aspect of the invention) or the computer program, wherein the algorithm or mathematical function is comprised, is saved on a data carrier comprised in the kit. 
         [0152]    It is preferred that the miRNA expression profile may be generated by any convenient means, e.g. nucleic acid hybridization (e.g. to a microarray), nucleic acid amplification (PCR, RT-PCR, qRT-PCR, high-throughput RT-PCR), ELISA for quantitation, next generation sequencing (e.g. ABI SOLID, IIlumina Genome Analyzer, Roche/454 GS 
         [0153]    FLX), flow cytometry (e.g. LUMINEX) and the like, that allow the analysis of differential miRNA expression levels between samples of a subject (e.g. diseased) and a control subject (e.g. healthy, reference sample). 
         [0154]    Nucleic acid hybridization may be performed using a microarray/biochip or in situ hybridization. In situ hybridization is preferred for the analysis of a single miRNA or a set comprising a low number of miRNAs (e.g. a set of at least 2 to 50 miRNAs such as a set of 2, 5, 10, 20, 30, or 40 miRNAs). The microarray/biochip, however, allows the analysis of a single miRNA as well as a complex set of miRNAs (e.g. [[a]] all known miRNAs or subsets thereof). 
         [0155]    Nucleic acid amplification may be performed using real time polymerase chain reaction (RT-PCR) such as real time quantitative polymerase chain reaction (RT qPCR). The standard real time polymerase chain reaction (RT-PCR) is preferred for the analysis of a single miRNA or a set comprising a low number of miRNAs (e.g. a set of at least 2 to 50 miRNAs such as a set of 2, 5, 10, 20, 30, or 40 miRNAs), whereas high-throughput RT-PCR technologies (e.g. OpenArray from Applied Biosystems, SmartPCR from Wafergen, Biomark System from Fluidigm) are also able to measure large sets of miRNAS (e.g. a set of 10, 20, 30, 50, 80, 100, 200 or more) or all known miRNAs in a high parallel fashion. RT-PCR is particularly suitable for detecting low abandoned miRNAs. 
         [0156]    In a second aspect, the invention relates to a set comprising polynucleotides for detecting a predetermined set comprising at least two miRNAs for diagnosing and/or prognosing of Wilms&#39; tumour in a body fluid sample from a subject. 
         [0157]    It is preferred that the body fluid sample is a blood sample, particularly preferred it is a whole blood, PBMC, serum or plasma sample, more particularly preferred it is a whole blood sample. 
         [0158]    It is preferred that the subject is a mammal including both a human and another mammal, e.g. an animal such as a mouse, a rat, a rabbit, or a monkey. It is particularly preferred that the subject is a human. 
         [0159]    Preferably, the predetermined set comprising at least two miRNAs is selected from the set of miRNAs listed in  FIG. 3  or  4 . 
         [0160]    It is preferred that the predetermined set comprising at least two miRNAs is selected from the set of miRNAs listed in  FIG. 5 . It is preferred that the predetermined set comprising at least two miRNAs comprises at least one set of miRNAs listed in  FIG. 5 . 
         [0161]    It is preferred that the polynucleotides comprised in the set of the present invention are complementary to the miRNAs comprised in the predetermined set, wherein the nucleotide sequences of said miRNAs are preferably selected from the group consisting of miRNAs listed in  FIG. 3  or  4  or set of miRNAs listed in  FIG. 5 , a fragment thereof, and a sequence having at least 80%, 85%, 90% or 95% sequence identity thereto. 
         [0162]    For example, the polynucleotides of the present invention are for detecting a predetermined set of 40 or 39 or 38 or 37 or 36 or 35 or 34 or 33 or 32 or 31 or 30 or 29 or 28 or 27 or 26 or 25 or 24 or 23 or 22 or 21 or 20 or 19 or 18 or 17 or 16 or 15 or 14 or 13 or 12 or 11 or 10 or 9 or 8 or 7 or 6 or 5 or 4 or 3 miRNAs wherein the set of miRNAs comprises at least one, e.g. 1, 2, 3, 4, 5 or 6, of the set of miRNAs listed in  FIG. 5 . 
         [0163]    In a third aspect, the invention relates to the use of set of polynucleotides according to the second aspect of the invention for diagnosing and/or prognosing Wilms&#39; tumour in a subject. 
         [0164]    In a fourth aspect, the invention relates to a set of at least two primer pairs for determining the expression level of a predetermined set of miRNAs in a body fluid sample of a subject suffering or suspected of suffering from Wilms&#39; tumour. 
         [0165]    It is preferred that the body fluid sample is a blood sample, particularly preferred it is a whole blood, PBMC, serum or plasma sample, more particularly preferred it is a whole blood sample. 
         [0166]    It is preferred that the subject is a mammal including both a human and another mammal, e.g. an animal such as a mouse, a rat, a rabbit, or a monkey. It is particularly preferred that the subject is a human. 
         [0167]    Preferably, the predetermined set comprising at least two miRNAs is selected from the set of miRNAs listed in  FIG. 3  or  4 . 
         [0168]    It is preferred that the predetermined set comprising at least two miRNAs is selected from the sets of miRNAs listed in  FIG. 5 . It is preferred that the predetermined set comprising at least two miRNAs comprises at least one set of miRNAs listed in  FIG. 5 . 
         [0169]    It is preferred that the set of at least two primer pairs for determining the expression level of a predetermined set of miRNAs in a body fluid sample of a subject suffering or suspected of suffering from Wilms&#39; tumour are primer pairs that are specific for at least one miRNA listed in  FIG. 3  or  4 . 
         [0170]    It is preferred that the set of at least two primer pairs for determining the expression level of a predetermined set of miRNAs in a body fluid sample of a subject suffering or suspected of suffering from Wilms&#39; tumour are primer pairs that are specific for at least one set of miRNAs listed in  FIG. 5 . 
         [0171]    It is preferred that the set of at least two primer pairs of the present invention are for detecting a set comprising, essentially consisting of, or consisting of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40 or more miRNAs, and wherein the set of miRNAs comprises at least one of the sets listed in  FIG. 5 . 
         [0172]    For example, the set of at least two primer pairs of the present invention are for detecting a predetermined set of 40 or 39 or 38 or 37 or 36 or 35 or 34 or 33 or 32 or 31 or 30 or 29 or 28 or 27 or 26 or 25 or 24 or 23 or 22 or 21 or 20 or 19 or 18 or 17 or 16 or 15 or 14 or 13 or 12 or 11 or 10 or 9 or 8 or 7 or 6 or 5 or 4 or 3 or 2 miRNAs wherein the predetermined set of miRNAs comprises at least one of the set of miRNAs listed in  FIG. 5 . 
         [0173]    Preferably, the said primer pairs may be used for amplifying cDNA transcripts of the predetermined set of miRNAs selected from the miRNAs listed in  FIG. 2  or  FIG. 5 . Furthermore, the said primer pairs may be used for amplifying cDNA transcripts of the set of miRNAs listed in  FIG. 5 . 
         [0174]    It is understood that the primer pairs for detecting a predetermined set of miRNAs may consist of specific and or non-specific primers. Additionally, the set of primer pairs may be complemented by other substances or reagents (e.g. buffers, enzymes, dye, labelled probes) known to the skilled in the art for conducting real time polymerase chain reaction (RT-PCR). 
         [0175]    In a fifth aspect, the invention relates to the use of a set of primer pairs according to the fourth aspect of the invention for diagnosing and/or prognosing Wilms&#39; tumour in a subject. 
         [0176]    In a sixth aspect, the invention relates to means for diagnosing and/or prognosing of Wilms&#39; tumour in a body fluid sample of a subject. Preferably, the invention relates to means for diagnosing and/or prognosing of Wilms&#39; tumour in a body fluid sample of a subject comprising
       (i) a set of at least two polynucleotides according to the second aspect of the invention or   (ii) a set of at least two primer pairs according the fourth aspect of the invention.       
 
         [0179]    It is preferred that the body fluid sample is a blood sample, particularly preferred it is a whole blood, PBMC, serum or plasma sample, more particularly preferred it is a whole blood sample. 
         [0180]    It is preferred that the subject is a mammal including both a human and another mammal, e.g. an animal such as a mouse, a rat, a rabbit, or a monkey. It is particularly preferred that the subject is a human. 
         [0181]    Preferably, that the set of at least two polynucleotides or the set of at least 2 primer pairs are for detecting a predetermined set comprising at least two miRNAs for diagnosing and/or prognosing of Wilms&#39; tumour in a body fluid sample, e.g. blood sample, from a subject, e.g. patient, human or animal, wherein the set of miRNAs is selected from the miRNAs listed in  FIG. 3  or  FIG. 4 . 
         [0182]    It is preferred that the set of at least two polynucleotides or the set of at least 2 primer pairs are for detecting a predetermined set comprising at least two miRNAs for diagnosing and/or prognosing of Wilms&#39; tumour in a body fluid sample, e.g. blood sample, from a subject, e.g. patient, human or animal, wherein the set of miRNAs is selected from the sets of miRNAs listed in  FIG. 5 . 
         [0183]    It is preferred that the set of at least two primer pairs for determining the expression level of a predetermined set of miRNAs in a body fluid sample of a subject suffering or suspected of suffering from Wilms&#39; tumour are primer pairs that are specific for at least two miRNAs selected from the miRNAs listed in  FIG. 3  or  FIG. 4 . 
         [0184]    It is preferred that the set of at least two primer pairs for determining the expression level of a set of miRNAs in a body fluid sample of a subject suffering or suspected of suffering from Wilms&#39; tumour are primer pairs that are specific for at least one set of miRNAs listed in  FIG. 5 . 
         [0185]    It is also preferred that said means for diagnosing and/or prognosing of Wilms&#39; tumour comprise, of a set of beads comprising a at least two polynucleotides according to the second aspect of the present invention. It is especially preferred that the beads are employed within a flow cytometer setup for diagnosing and/or prognosing of Wilms&#39; tumour, e.g. in a LUMINEX system (www.luminexcorp.com). 
         [0186]    In a seventh aspect, the invention relates to a kit for diagnosing and/or prognosing of Wilms&#39; tumour in a subject. 
         [0187]    Preferably, the invention relates to a kit for diagnosing and/or prognosing of Wilms&#39; tumour comprising
       (i) means for determining an expression profile of a predetermined set comprising at least two miRNAs representative for Wilms&#39; tumour in a body fluid sample from a subject, and   (ii) at least one reference.       
 
         [0190]    It is preferred that the body fluid sample is a blood sample, particularly preferred it is a whole blood, PBMC, serum or plasma sample, more particularly preferred it is a whole blood sample. 
         [0191]    It is preferred that the subject is a mammal including both a human and another mammal, e.g. an animal such as a mouse, a rat, a rabbit, or a monkey. It is particularly preferred that the subject is a human. 
         [0192]    Said means may comprise of at least two polynucleotides according to the second aspect of the present invention, a set of at least 2 primer pairs according to the fourth aspect of the invention; means according to the sixth aspect of the present invention; primers suitable to perform reverse transcriptase reaction and/or real time polymerase chain reaction such as quantitative polymerase chain reaction; and/or means for conducting next generation sequencing. 
         [0193]    In an eighth aspect, the invention relates to a predetermined set of miRNAs in a body fluid sample isolated from a subject for diagnosing and/or prognosing of Wilms&#39; tumour. 
         [0194]    It is preferred that the body fluid sample is a blood sample, particularly preferred it is a whole blood, PBMC, serum or plasma sample, more particularly preferred it is a whole blood sample. 
         [0195]    It is preferred that the subject is a mammal including both a human and another mammal, e.g. an animal such as a mouse, a rat, a rabbit, or a monkey. It is particularly preferred that the subject is a human. 
         [0196]    Preferably, the predetermined set comprising at least two miRNAs is selected from the set of miRNAs listed in  FIG. 3  or  4 . 
         [0197]    It is preferred that the predetermined set comprising at least two miRNAs is selected from the set of miRNAs listed in  FIG. 5 . It is preferred that the predetermined set comprising at least two miRNAs comprises at least one set of miRNAs listed in  FIG. 5 . 
         [0198]    In a ninth aspect, the invention relates to the use of a set of miRNAs according to the eighth aspect of the invention for diagnosing and/or prognosing of Wilms&#39; tumour in a subject. 
       REFERENCES  
       [0199]    Alvarez-Garcia, I. and E. A. Miska (2005). “MicroRNA functions in animal development and human disease.”  Development  132 (21): 4653-62. 
         [0200]    Benjamini, Y. and Y. Hochberg (1995). “Controlling the false discovery rate: A practical and powerful approach to multiple testing.” J R Statist Soc B 57: 289-300. 
         [0201]    Bolstad, B. M., R. A. Irizarry, et al. (2003). “A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.” Bioinformatics  19 (2): 185-93. 
         [0202]    Calin, G. A. and C. M. Croce (2006). “MicroRNA-cancer connection: the beginning of a new tale.”  Cancer Res  66 (15): 7390-4. 
         [0203]    Calin, G. A. and C. M. Croce (2006). “MicroRNA signatures in human cancers.”  Nat Rev Cancer  6 (11): 857-66. 
         [0204]    Chen, X., Y. Ba, et al. (2008). “Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases.”  Cell Res  18 (10): 997-1006. 
         [0205]    Crawford, M., E. Brawner, et al. (2008). “MicroRNA-126 inhibits invasion in non-small cell lung carcinoma cell lines.”  Biochem Biophys Res Commun  373 (4): 607-12. 
         [0206]    Esquela-Kerscher, A. and F. J. Slack (2006). “Oncomirs-microRNAs with a role in cancer.”  Nat Rev Cancer  6 (4): 259-69. 
         [0207]    Feitelson, M. A. and J. Lee (2007). “Hepatitis B virus integration, fragile sites, and hepatocarcinogenesis.”  Cancer Lett  252 (2): 157-70. 
         [0208]    Gilad, S., E. Meiri, et al. (2008). “Serum microRNAs are promising novel biomarkers.” PLoS ONE  3 (9): e3148. 
         [0209]    Griffiths-Jones, S., R. J. Grocock, et al. (2006). “miRBase: microRNA sequences, targets and gene nomenclature.”  Nucleic Acids Res  34 (Database issue): D140-4. 
         [0210]    Griffiths-Jones, S., S. Moxon, et al. (2005). “Rfam: annotating non-coding RNAs in complete genomes.”  Nucleic Acids Res  33 (Database issue): D121-4. 
         [0211]    Griffiths-Jones, S., H. K. Saini, et al. (2008). “miRBase: tools for microRNA genomics.”  Nucleic Acids Res  36 (Database issue): D154-8. 
         [0212]    Guo, L, Z. X. Huang, et al. (2008). “Differential Expression Profiles of microRNAs in NIH3T3 Cells in Response to UVB Irradiation.”  Photochem Photobiol.    
         [0213]    Harris, T. A, M. Yamakuchi, et al. (2008). “MicroRNA-126 regulates endothelial expression of vascular cell adhesion molecule 1.”  Proc Natl Acad Sci U S A  105 (5): 1516-21. 
         [0214]    Hayashita, Y, H. Osada, et al. (2005). “A polycistronic microRNA cluster, miR-17-92, is overexpressed in human lung cancers and enhances cell proliferation.”  Cancer Res  65 (21): 9628-32. 
         [0215]    He, L, J. M. Thomson, et al. (2005). “A microRNA polycistron as a potential human oncogene.”  Nature  435 (7043): 828-33. 
         [0216]    Henschke, C. I. and D. F. Yankelevitz (2008). “CT screening for lung cancer: update 2007.”  Oncologist  13 (1): 65-78. 
         [0217]    Hochberg, Y (1988). “A sharper bonferroni procedure for multiple tests of significance.”  Biometrica  75: 185-193. 
         [0218]    Ichimi, T., H. Enokida, et al. (2009). “Identification of novel microRNA targets based on microRNA signatures in bladder cancer.”  Int J Cancer.    
         [0219]    Jemal, A, R. Siegel, et al. (2008). “Cancer statistics, 2008.”  CA Cancer J Clin  58 (2): 71-96. 
         [0220]    Johnson, S. M., H. Grosshans, et al. (2005). “RAS is regulated by the let-7 microRNA family.”  Cell  120 (5): 635-47. 
         [0221]    Keller, A., N. Ludwig, et al. (2006). “A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumours.”  BMC Bioinformatics  7: 539. 
         [0222]    Lee, R. C, R. L. Feinbaum, et al. (1993). “The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.”  Cell  75 (5): 843-54. 
         [0223]    Lu, J., G. Getz, et al. (2005). “MicroRNA expression profiles classify human cancers.”  Nature  435 (7043): 834-8. 
         [0224]    Mann, H. and F. Wilcoxon (1947). “On a test whether one of two random variables is stochastically larger than the other.”  Ann Mat Stat  18: 50-60. 
         [0225]    Sassen, S., E. A. Miska, et al. (2008). “MicroRNA: implications for cancer.”  Virchows Arch  452 (1): 1-10. 
         [0226]    Scott, W. J., J. Howington, et al. (2007). “Treatment of non-small cell lung cancer stage I and stage II: ACCP evidence-based clinical practice guidelines (2nd edition).”  Chest  132 (3 Suppl): 234S-242S. 
         [0227]    Shannon, C. (1984). “A mathematical theory of communication.” The Bell System  Technical Journal  27: 623-656. 
         [0228]    Stahlhut Espinosa, C. E. and F. J. Slack (2006). “The role of microRNAs in cancer.”  Yale J Biol Med  79 (3-4): 131-40. 
         [0229]    Takamizawa, J., H. Konishi, et al. (2004). “Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival.”  Cancer Res  64 (11): 3753-6. 
         [0230]    Team, R. D. C. (2008).  R: A Language and Environment for Statistical Computing.  Vienna, Austria, R Foundation for Statistical Computing. 
         [0231]    Tong, A. W. (2006). “Small RNAs and non-small cell lung cancer.”  Curr Mol Med  6 (3): 339-49. 
         [0232]    Vapnik, V. (2000).  The Nature of Statistical Learning Theory,  Springer. 
         [0233]    Volinia, S., G. A. Calin, et al. (2006). “A microRNA expression signature of human solid tumours defines cancer gene targets.”  Proc Natl Acad Sci U S A  103 (7): 2257-61. 
         [0234]    Vorwerk, S., K. Ganter, et al. (2008). “Microfluidic-based enzymatic on-chip labeling of miRNAs.”  N Biotechnol  25 (2-3): 142-9. 
         [0235]    Wilcoxon, F. (1945). “Individual comparisons by ranking methods.”  Biometric Bull  1: 80-83. 
         [0236]    Williams, A. E. (2008). “Functional aspects of animal microRNAs.”  Cell Mol Life Sci  65 (4): 545-62. 
         [0237]    Yanaihara, N., N. Caplen, et al. (2006). “Unique microRNA molecular profiles in lung cancer diagnosis and prognosis.”  Cancer Cell  9 (3): 189-98. 
         [0238]    Zhang, B., X. Pan, et al. (2007). “microRNAs as oncogenes and tumour suppressors.”  Dev Biol  302 (1): 1-12. 
         [0239]    Zhang, B., Q. Wang, et al. (2007). “MicroRNAs and their regulatory roles in animals and plants.”  J Cell Physiol  210 (2): 279-89.