MOLECULAR MARKERS IN BLADDER CANCER

Information

  • Patent Application
  • 20160017434
  • Publication Number
    20160017434
  • Date Filed
    March 07, 2014
    10 years ago
  • Date Published
    January 21, 2016
    8 years ago
Abstract
The Present invention relates methods for establishing the presence, or absence, of a bladder tumour and/or classification of the tumor according to the aggressiveness and/or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer. Specifically, the present invention relates to methods for establishing the presence, or absence, of a bladder tumour in a human individual comprising: determining the expression of one or more genes chosen from the group consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and transcript cluster 2526896 in a biological sample (tissue or bodyfluid) originating from said human individual; establishing up regulation of expression of said one or more genes as compared to expression of said respective one or more genes in a sample originating from said human individual not comprising tumour cells or tissue.
Description

The present invention relates to methods for establishing the presence, or absence, of a bladder tumour and/or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer. The present invention further relates to the use of expression analysis of the indicated genes, or molecular markers, for establishing the presence, or absence, of a bladder tumour and/or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer and to kit of parts for establishing the presence, or absence, of a bladder tumour and/or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer.


Urinary bladder (or bladder) cancer is one of the most common cancers worldwide, with the highest incidence in industrialized countries. In the Western world, the chances of developing this type of cancer is 1 in 26, for women the chance is 1 in 90. Bladder cancer is the 4th most common cancer in men.


Two main histological types of bladder cancer are the urothelial cell carcinomas (UCC) and the squamous cell carcinomas (SCC). The UCCs are the most prevalent in Western and industrialized countries and are related to cigarette smoking and occupational exposure. The squamous cell carcinomas (SCC) are more frequently seen in some Middle Eastern and African countries where the schistosoma haematobium parasite is endemic.


In the Western world, 90% of the bladder tumours are UCCs, 3 to 5% are SCCs, and 1 to 2% are adenocarcinomas. Two third of the patients with UCC can be categorized into non-muscle invasive bladder cancer (NMIBC) and one third in muscle invasive bladder cancer (MIBC).


In NMIBC, the disease is generally confined to the bladder mucosa (stage Ta, carcinoma in situ (CIS)) or bladder submucosa (stage T1). In MIBC, the patient has a tumour initially invading the detrusor muscle (stage T2), followed by the perivesical fat (stage T3) and the organs surrounding the bladder (stage T4). The management of these two types of UCC differs significantly. The management of NMIBC consists of transurethral resection of the bladder tumour (TURBT). However, after TURBT, 30% to 85% of patients develop recurrences. This high risk of recurrence makes bladder cancer one of the most prevalent human tumours.


Patients with NMIBC can be divided into 3 groups. 20% to 30% of patients have a relatively benign type of UCC, with a low recurrence rate. These low risk tumours do not exhibit progression. 40% to 50% of patients have so-called intermediate risk tumours. These patients often develop a superficial recurrence, but seldom progression. A small group of patients (20% to 30%) has a relatively aggressive superficial tumour at presentation and despite maximum treatment and 70% to 80% of these patients will have recurrent disease. 50% of these patients will develop muscle invasive disease associated with a poor prognosis. Therefore, there is a need to identify the patient group at risk for progression.


The primary treatment for MIBC is cystectomy. Despite this radical treatment, 50% of patients with primary MIBC develop metastases within 2 years after cystectomy and subsequently die of the disease. The 5-year tumour-specific survival of these patients is 55%. In comparison, patients with NMIBC have a 5-year tumour-specific survival of 88-90%. However, patients with MIBC who have a history of NMIBC, the 5-year tumour-specific survival drops to only 28%. These percentages emphasize the need for the identification of patients with a high risk of progression of their NMIBC.


The risk for progression and cancer related death is associated with tumour stage and grade. Currently, staging and grading of the tumour is used for making treatment decisions. Unfortunately, this procedure has led to overtreatment (e.g. cystectomy in patients who would have survived without this treatment) or undertreatment (i.e. patients with progressive disease dying after TURBT and who would have survived if they underwent cystectomy at an earlier stage). At present no reliable methods are available to accurately predict prognosis of individual patients with bladder cancer. The limited value of the established prognostic markers requires the analysis of new molecular parameters in predicting the prognosis and treatment of bladder cancer patients.


Bladder cancer is a genetic disorder driven by the progressive accumulation of multiple genetic and epigenetic changes. At the molecular level, these genetic changes result in uncontrolled cell proliferation, decreased cell death, invasion, and metastasis. The specific alterations in gene expression that occur as a result of interactions between various cellular pathways determine the biological behavior of the tumor, including growth, recurrence, progression, and metastasis, and may influence patient survival. To detect and monitor cancer and determine the likely prognosis, it is necessary to identify molecular markers of the disease that can be used in the clinic.


Considering the above, there is a need in the art for molecular markers capable of establishing the presence, or absence, of a bladder tumour and/or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer. A suitable molecular marker preferably fulfils the following criteria:


1) it must be reproducible (intra- and inter-institutional); and


2) it must have an impact on clinical management.


It is an object of the present invention, amongst other objects, to meet at least partially, if not completely, the above stated needs of the art.


According to the present invention, the above object, amongst other objects, is met by bladder tumour markers and methods as outlined in the appended claims.


Specifically, the above object, amongst other objects, is met by an (in vitro) method for establishing the presence, or absence, of a bladder tumour in a human individual; or classification of the tumours according to aggressiveness, prediction of prognosis and/or disease outcome for a human individual suffering from bladder cancer comprising:

  • a) determining the expression of one or more genes chosen from the group consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and transcript cluster 2526896 in a sample originating from said human individual; and
  • b) establishing up, or down, regulation of expression of said one or more genes as compared to expression of said respective one or more genes in a sample originating from said human individual not comprising tumour cells or tissue, or from an individual, or group of individuals, not suffering from bladder cancer; and
  • c) establishing the presence, or absence, of a bladder tumour based on the established up- or down regulation of said one or more genes; or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer based on the established up- or down regulation of said one or more genes.


According to the present invention, establishing the presence, or absence, of bladder cancer in a human individual preferably includes diagnosis, prognosis and/or prediction of disease survival.


It should be noted that the present method, when taken alone, does not suffice to diagnose an individual as suffering from bladder cancer. For this, a trained physician is required capable of taking into account factors not related to the present invention such as disease symptoms, history, pathology, general condition, age, sex, and/or other indicators. The present methods and molecular markers provide the trained physician with additional tools, or aids, to arrive at a reliable diagnosis.


According to the present invention, expression analysis comprises establishing an increased, or decreased, expression of a gene as compared to expression of this gene in non-bladder cancer tissue, i.e., under non-disease conditions.


For example, establishing an increased expression of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, or transcript cluster 2526896, as compared to expression of these genes under non-bladder cancer conditions, allows establishing the presence, or absence, of a bladder tumour in a human individual suspected of suffering from bladder cancer and allows establishing the prediction of prognosis and disease outcome for an individual patient suffering from bladder cancer.


INHBA: Inhibin βA is a ligand in the TGF-β superfamily. INHBA forms a disulphide-linked homodimer known as activin A. In cancer a biological mechanism is suggested that is centered on activin A induced TGF-β signalling.


CTHRC1: collagen triple helix repeat containing-1 is a 30 kDa secreted protein that has the ability to inhibit collagen matrix synthesis. It is typically expressed at epithelial-mesenchymal interfaces. CTHRC1 is a cell-type-specific inhibitor TGF-β. Increased CTHRC1 expression results in morphological cell changes, increased cell proliferation, and decreased apoptosis.


CHI3L1: Chitinase 3-like 1 is a member of the mammalian chitinase family. It has been suggested that CHI3L1 is associated with cancer cell proliferation, differentiation, metastatic potential, and extracellular tissue remodelling, but in vivo proofs are yet to be obtained.


COL10A1: controls growth and maturation of endochondral bone. Overexpression of COL10A1 was also found in advanced breast cancer tissue specimen. COL10A1 was identified as a gene with restricted expression in most normal tissues and elevated expression in many diverse tumour types.


FAP: Human fibroblast activation protein alpha is a 97-kDa membrane bound serine protease. FAP was found to be selectively expressed on fibroblasts within the tumour stroma or on tumour-associated fibroblasts in epithelial cancers (e.g. colon cancer, myeloma, esophageal cancer, gastric cancer, breast cancer).


ASPN: asporin is an extracellular matrix protein that belongs to the small leucine-rich repeat proteoglycan family of proteins. Its biological role is unknown, but there is an association between ASPN and various bone and joint diseases, including rheumatoid arthritis. ASPN binds to various growth factors, including TGFβ and BMP2. ASPN was found to be upregulated in invasive ductal and lobular carcinomas.


ADAMTS12 is a desintegrin and metalloprotease with thrombospondin motif ADAMTS12 transcripts were only detected at significant levels in fetal lung, but not in any other analysed normal tissue. ADAMTS12 could be detected in gastric, colorectal, renal, and pancreatic carcinomas. ADAMTS12 may play roles in pulmonary cells during fetal development or in tumour processes through its proteolytic activity or as a molecule potentially involved in regulation of cell adhesion. In colon carcinomas, the expression of ADAMTS12 in fibroblasts is linked with an anti-proliferative effect on tumour cells. It seems that ADAMTS12 is a novel anti-tumour proteinase that plays an important role in inhibiting tumour development in colorectal cancer.


IGF2BP2: Insulin-like growth factor-II mRNA-binding protein 2 (IMP2) belongs to a family of RNA-binding proteins implicated in mRNA localization, turnover and translational control. Translational control and mRNA localization are important mechanisms for control of gene expression in germ cells and during early embryogenesis. Although the fetal expression is prominent, data indicating that the proteins are also present in mature tissues have been accumulating. In colon cancer, IGF2BP2 transcripts were shown to exist in sense:antisense pairs, which may have a direct regulatory function.


PDCD1LG2: Programmed cell death 1 (PD-1) and its ligands, Programmed death ligand 1 (PD-L1) and PD-L2, have an important inhibitory function to play in the regulation of immune homeostasis and in the maintenance of peripheral tolerance. The selective blockade of these inhibitory molecules is an attractive approach to cancer immunotherapy. PD-L1 is upregulated by many human cancers. On the other hand, the role of PD-L2 in modulating immune responses is less clear, and its expression is more restricted compared to PD-L1, thus making it a less obvious target in cancer immunotherapy.


SFRP4: Secreted frizzled-related protein 4 (SFRP4) is a secreted protein with putative inhibitory activity of the Wnt-signaling cascade. Membranous SFRP4 expression predicted for biochemical relapse. In colorectal carcinoma, SFRP4 is upregulated, which is in contrast to other SFRP family members. In ovarian cancers, there is supporting evidence that SFRP4 acts as a tumour suppressor gene via the inhibition of the Wnt signalling pathway. Although the risk of invasive bladder cancer increases with the number of methylated SFRP genes, methylation of sFRP-4 is not an independent predictor of bladder cancer and therefore an exception.


KRT6A: The keratin 6 (K6 or Krt6) gene family is comprised of three members, K6a, K6b, and K6hf (or Krt75). Only KRT6A is expressed in the mammary gland, and only in a very small fraction of mammary luminal epithelial cells.


TPX2: The microtubule-associated protein TPX2 (Xklp2) has been reported to be crucial for mitotic spindle which can bind to tubulin and induce microtubule polymerization. TPX2 mRNA is closely linked to increased or abnormal cell proliferation in malignant salivary gland tumours, breast cancer, endometrioid adenocarcinoma, neuroblastoma, pancreatic cancer, ovarian cancer and cervical cancer. An increased expression of TPX2 might reflect an advanced loss of cell cycle inhibitory mechanisms resulting in more aggressive tumours.


CCNB2: Cyclin B2 is a member of the cyclin protein family. Cyclins B1 and B2 are particularly critical for the maintenance of the mitotic state. Cyclin B2 has been found to be up-regulated in human tumors, such as colorectal cancer, lung cancer, pituitary cancer. Recently it was shown that circulating CCNB2 in serum was significantly higher in cancer patients than in normal controls. The CCNB2 mRNA level was correlated with cancer stage and metastases status of patients with lung cancer and digestive tract cancer.


ANLN: Anillin is a gene highly expressed in the brain and ubiquitously present in various tissues. ANLN is overexpressed in breast cancer, endometrial carcinomas and gastric cancer. A tumor-progression-related pattern of ANLN expression was found in breast, ovarian, kidney, colorectal, hepatic, lung, endometrial and pancreatic cancer.


FOXM1: The human cell cycle transcription factor Forkhead box M1 is known to play a key role in regulating timely mitotic progression and accurate chromosomal segregation during cell division. Deregulation of FOXM1 has been linked to a majority of human cancers. Up-regulation of FOXM1 precedes malignancy in a number of solid cancers including oral, oesophagus, lung, breast, kidney bladder and uterus cancer. It is an early molecular signal required for aberrant cell cycle and cancer initiation.


CDC20: cell division cycle 20 homolog is a component of the mammalian cell cycle mechanism that activates the anaphase-promoting complex (APC). Its expression is essential for cell division. P53 was found to inhibit tumor cell growth through the indirect regulation of CDC20. CDC20 was found to be upregulated in many types of malignancies like ovarian cancer, bladder cancer, glioblastomas, pancreatic ductal carcinomas. In ovarian cancer and non-small cell lung cancer CDC20 appears to be associated with a poor prognosis. It has been suggested that CDC20 may function as an oncoprotein that promotes the development and progression of human cancers.


According to the present invention, the method as described above is preferably an ex vivo or in vitro method. In this embodiment, expression analysis of the indicated genes is performed on a sample derived, originating or obtained from an individual suspected of suffering from bladder cancer. Such sample can be a body fluid such as saliva, lymph, blood or urine, or a tissue sample such as a transurethral resection of a bladder tumour (TURBT). Samples of, derived or originating from blood, such as plasma or cells, and urine, such as urine sediments, are preferably contemplated within the context of the present invention as are samples of, derived or originating from TURBT specimens.


According to another preferred embodiment of the present method, determining the expression comprises determining mRNA expression of the said one or more genes.


Expression analysis based on mRNA is generally known in the art and routinely practiced in diagnostic labs world-wide. For example, suitable techniques for mRNA analysis are Northern blot hybridisation and amplification based techniques such as PCR, and especially real time PCR, and NASBA.


According to a particularly preferred embodiment, expression analysis comprises high-throughput DNA array chip analysis not only allowing the simultaneous analysis of multiple samples but also an automatic processing of the data obtained.


According to another preferred embodiment of the present method, determining the expression comprises determining protein levels of the said genes. Suitable techniques are, for example, matrix-assisted laser desorption-ionization time-of-flight mass spectrometer (MALDI-TOF).


According to the present invention, the present method is preferably provided by expression analysis of a number of the present genes selected from the group consisting of two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, sixteen or more, seventeen or more or eighteen of the genes chosen from the group consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and/or transcript cluster 2526896.


Preferred combinations within the context of the present invention are CCNB2 in combination with one or more selected from the consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and/or transcript cluster 2526896, such as in combination with CDC20 and, preferably further in combination with PDCD1LG2, more preferably further in combination with INHBA, i.e. the combination at least comprising CCNB2, CDC20, PDCD1LG2 and INHBA. The latter panel of four markers provides a prediction of 0.991 (95% CI: 0.977-1.000). Within the present group of combinations with CCNB2, the preferred samples are urine or urine derived samples such as urine sediments.


Other preferred combinations within the context of the present invention are FAP in combination with one or more selected from the consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and/or transcript cluster 2526896 such as in combination with CDC20 and, preferably, further in combination with INHBA, more preferably further in combination with IGF2BP2, i.e. the combination at least comprising FAP, CDC20, INHBA and IGF2BP2. Within the present group of combinations with FAP, the preferred samples are tissue or tissue derived samples such as biopses. The Area Under the Curve (AUC) for the combination of IGF2BP2+FAP+CHI3L1+CDC20 expression is 0.955 (95% CI: 0.929-0.980).


According to a most preferred embodiment of the above methods, the present invention relates to methods, wherein establishing the presence, or absence, of a tumour further comprises establishing suspected metastasis or no metastasis. Establishing whether the bladder tumour identified is capable to metastasize, is likely to metastasize, or has metastasized, is inherently a valuable tool for a trained physician to develop an individualised treatment protocol.


In case of metastasis, the survival rate of a patient is generally directly correlated with the point in time on which the metastasis is identified, detected or established. The earlier in time the treatment commences, the higher the survival rates. Additionally, if a tumour is not capable of metastasis, is not likely to metastasize, or has not metastasized, the patient needs not to be subjected to, or can be spared of, treatments severely affecting the quality of life.


Establishing the presence, or absence, of a tumour, according to another preferred embodiment, can further comprise establishing whether a NMIBC will, or is likely to, progress into MIBC.


Considering the diagnostic- and/or prognostic value of the present markers, the present invention also relates to the use of expression analysis of one or more genes selected from the group consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and transcript cluster 2526896 for establishing the presence, or absence, of a bladder tumour or establishing the prediction of prognosis and disease outcome for an individual patient suffering from bladder cancer.


The present use, for reasons indicated above, is preferably an ex vivo or in vitro use and, preferably, involves the use of two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, sixteen or more, seventeen or more and eighteen of the present markers for establishing the presence, or absence of a bladder tumour, and establishing the prediction of prognosis and disease outcome for an individual patient suffering from bladder cancer.


Preferred combinations within the context of the present use are CCNB2 in combination with one or more selected from the consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and/or transcript cluster 2526896, such as in combination with CDC20 and, preferably further in combination with PDCD1LG2, more preferably further in combination with INHBA, i.e. the combination at least comprising CCNB2, CDC20, PDCD1LG2 and INHBA. The latter panel of four markers provides a prediction of 0.991 (95% CI: 0.977-1.000). Within the present group of combinations with CCNB2, the preferred samples are urine or urine derived samples such as urine sediments.


Other preferred combinations within the context of the present use are FAP in combination with one or more selected from the consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and/or transcript cluster 2526896 such as in combination with CDC20 and, preferably, further in combination with INHBA, more preferably further in combination with IGF2BP2, i.e. the combination at least comprising FAP, CDC20, INHBA and IGF2BP2. Within the present group of combinations with FAP, the preferred samples are tissue or tissue derived samples such as biopses. The Area Under the Curve (AUC) for the combination of IGF2BP2+FAP+CHI3L1+CDC20 expression is 0.955 (95% CI: 0.929-0.980).


Considering the diagnostic and/or prognostic value of the present genes as biomarkers for bladder cancer, the present invention also relates to a kit of parts for establishing the presence, or absence, of a bladder tumour and establishing the prediction of prognosis and disease outcome for an individual patient suffering from bladder cancer said kit of parts comprises:

    • expression analysis means for determining the expression of one or more genes chosen from the group consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and transcript cluster 2526896;
    • instructions for use.


Preferred combinations included in the present kits are CCNB2 in combination with one or more selected from the consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and/or transcript cluster 2526896, such as in combination with CDC20 and, preferably further in combination with PDCD1LG2, more preferably further in combination with INHBA, i.e. the combination at least comprising CCNB2, CDC20, PDCD1LG2 and INHBA.


Other preferred combinations included in the present kits are FAP in combination with one or more selected from the consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and/or transcript cluster 2526896 such as in combination with CDC20 and, preferably, further in combination with INHBA, more preferably further in combination with IGF2BP2, i.e. the combination at least comprising FAP, CDC20, INHBA and IGF2BP2.


According to a preferred embodiment, the present kit of parts comprises mRNA expression analysis means, preferably for PCR, rtPCR or NASBA.


According to a particularly preferred embodiment, the present kit of parts comprises means for expression analysis of two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, sixteen or more, seventeen or more or eighteen of the present genes.


In the present description, reference is made to genes suitable as biomarkers for bladder cancer by referring to their arbitrarily assigned names. Although the skilled person is readily capable of identifying and using the present genes as biomarkers based on the indicated names, the appended FIGS. 1 to 18 provide the cDNA and amino acid sequences of these genes, thereby readily allowing the skilled person to develop expression analysis assays based on analysis techniques commonly known in the art.


Such analysis techniques can, for example, be based on the genomic sequence of the gene or the provided cDNA or amino acid sequences. This sequence information can either be derived from the provided sequences, or can be readily obtained from public databases, for example by using the provided accession numbers.





The present invention will be further elucidated in the following examples of preferred embodiments of the invention. In the examples, reference is made to figures, wherein:



FIGS. 1-18: show the cDNA and amino acid sequences of the INHBA gene (NM002192, NP002183); the CTHRC1 gene (NM138455, NP612464); the CHI3L1 gene (NM001276, NP001267); the COL10A1 gene (NM000493, NP000484); the FAP gene (NM004460, NP004451); the sequence of transcript cluster 2526896 (no assigned mRNA and protein sequences); the ASPN gene (NM017680, NP060150); the sequence of transcript cluster 2526893 (no assigned mRNA and protein sequences); the ADAMTS12 gene (NM030955, NP112217); the IGF2BP2 gene (NM006548, NP006539); the PDCD1LG2 gene (NM025239, NP079515); the SFRP4 gene (NM003014, NP003005); the KRT6A gene (NM005554, NP005545); the TPX2 gene (NM012112, NP036244); the CCNB2 gene (NM004701, NP004692); the ANLN gene (NM018685, NP061155); the FOXM1 gene (NM202002, NP973731) and the CDC20 gene (NM001255, NP001246), respectively;



FIG. 19: shows boxplots for the identified five best performing individual biomarkers that could distinguish NBl from BCa (NMIBC+MIBC) in tissue;



FIG. 20: shows boxplots for the identified five best performing individual biomarkers that could distinguish MIBC tissue from NMIBC tissue;



FIG. 21: shows boxplots for the identified best performing individual biomarkers for the detection of BCa in urine and/or that could distinguish MIBC from NMIBC in urine;



FIG. 22: shows receiver under Operation Curves (ROC) showing a combination of biomarkers for predicting the occurrence of BCa (NMIBC and MIBC) based on the expression of the markers in urine. The Area Under the Curve (AUC) for the combination of CCNB2+CDC20+PDCD1LG2+INHBA expression in urine is 0.991 (95% CI: 0.977-1.000)



FIG. 23: shows Receiver under Operation Curves (ROC) showing a combination of biomarkers for predicting the occurrence of MIBC based on the expression of the markers in tissue. The Area Under the Curve (AUC) for the combination of IGF2BP2+FAP+CHI3L1+CDC20 expression in tissue is 0.955 (95% CI: 0.929-0.980).





Below the present invention will be further illustrated by examples of preferred embodiments of the present invention.


EXAMPLES
Example 1

To identify markers for bladder cancer, the gene expression profile (GeneChip® Human Exon 1.0 ST arrays, Affymetrix) of samples from patients with and without bladder cancer were used. The expression analysis was performed according to standard protocols.


Briefly, tissue was obtained after radical cystectomy from patients with bladder cancer. The tissues were snap frozen and cryostat sections were hematoxylin-eosin (H.E.) stained for classification by a pathologist.


Malignant- and non-malignant areas were dissected and total RNA was extracted with TRIpure® (Roche, Indianapolis, Ind., CA, USA) following manufacturer's instructions. Total RNA was purified with the Qiagen RNeasy mini kit (Qiagen, Valencia, Calif., USA). The integrity of the RNA was checked by electrophoresis using the Agilent 2100 Bioanalyzer.


From the purified total RNA, 1 μg was used for the GeneChip® Whole Transcript (WT) Sense Target Labeling Assay. (Affymetrix, Santa Clara, Calif., USA). Using a random hexamer incorporating a T7 promoter, double-stranded cDNA was synthesized.


Then, cRNA was generated from the double-stranded cDNA template through an in vitro transcription reaction and purified using the Affymetrix sample clean-up module. Single-stranded cDNA was regenerated through a random-primed reverse transcription using a dNTP mix containing dUTP. The RNA was hydrolyzed with RNaseH and the cDNA was purified. Subsequently, the cDNA was fragmented by incubation with a mixture of UDG (uracil DNA glycosylase) and APE 1 (apurinic/apyrimidinic endonuclease 1) restriction endonucleases and, finally, end-labeled via a terminal transferase reaction incorporating a biotinylated dideoxynucleotide. Of the fragmented, biotinylated cDNA, 5.5 μg was added to a hybridization mixture, loaded on a GeneChip® Human Exon 1.0 ST array and hybridized for 16 hours at 45° C. and 60 rpm.


Using the GeneChip® Human Exon 1.0 ST array, genes are indirectly measured by exon analysis which measurements can be combined into transcript clusters measurements. There are more than 300,000 transcript clusters on the array, of which 90,000 contain more than one exon. Of these 90,000 there are more than 17,000 high confidence (CORE) genes which are used in the default analysis. In total there are more than 5.5 million features per array.


Following hybridization, the array was washed and stained according to the Affymetrix protocol. The stained array was scanned at 532 nm using a GeneChip® Scanner 3000, generating CEL files for each array.


Exon-level and gene level expression values were derived from the CEL file probe-level hybridization intensities using Partek Genomics Suite 6.2, (Partek Incorporated, Saint Louis, Mo., USA). Data analysis with this software was performed with the GeneChip® array core meta probe sets as well as the extended meta probe sets.


Differentially expressed genes between conditions, e.g. NMIBC versus MIBC and MIBC versus NBl, are calculated using Anova (ANalysis Of Variance), a T-test for more than two groups. The target identification is biased since clinically well-defined risk groups were analyzed. The markers are categorized based on their role in cancer biology. For the identification of markers the non-muscle invasive bladder cancer (NMIBC) group (N=48), the muscle invasive bladder cancer (MIBC) group (N=49), the bladder cancer metastasis (BC-Meta) group (N=5) and the normal bladder (NBl) group (N=12) were compared.


Based on the GeneChip® microarrays expression analysis data, the most differentially expressed genes between NBl and NMIBC/MIBC (diagnostic genes) and also the most differentially expressed genes between the NMIBC and MIBC (prognostic genes) were selected.


In total, a group of 46 genes of interest were selected which will be further elucidated in example 2 and listed in Table 2. Based on the selected 18 genes in example 2, the GeneChip® expression data for these genes are shown in Table 1.


Table 1:

GeneChip® Microarray data showing the expression characteristics of 18 targets characterizing bladder cancer tissue, based on the analysis of 12 well annotated NBl, 48 NMIBC, 49 MIBC and 5 BC-Meta tissue specimens.













TABLE 1A










up in MIBC
up in MIBC





vs NMIBC
vs NBl













Gene

Gene
Fold-

Fold-



symbol
Gene Name
assignment
Change
P-value
Change
P-value
















INHBA
inhibin, beta A
NM_002192
10.1
3.3E−12
5.7
1.7E−8


CTHRC1
collagen triple helix repeat
NM_138455
4.5
5.1E−22
2.4
7.9E−6



containing 1







CHI3L1
chitinase 3-like 1 (cartilage
NM_001276
13.5
1.5E−19
6.8
4.1E−7



glycoprotein-39)







COL10A1
collagen, type X, alpha 1
NM_000493
3.7
1.0E−16
3.8
1.3E−9


FAP
fibroblast activation protein,
NM_004460
6.3
2.5E−17
3.5
1.3E−5



alpha







TC2526896*
Transcript cluster 2526896,
N/A**
7.6
1.1E−15
7.8
5.6E−9



N/A**







ASPN
Asporin
NM_017680
7.6
1.1E−16
2.0
2.7E−2


TC2526893*
Transcript cluster 2526893,
N/A**
4.2
1.2E−12
4.2
1.8E−7



N/A**







ADAMTS12
ADAM metallopeptidase with
NM_016568
4.3
8.2E−21
3.8
1.9E−10



thrombospondin type 1 motif, 12







IGF2BP2
insulin-like growth factor 2
NM_006548
4.0
1.8E−12
2.7
2.5E−4



mRNA binding protein 2







PDCD1LG2
programmed cell death
NM_025239
5.6
1.2E−13
1.8
7.1E−2



1 ligand 2







SFRP4
secreted frizzled-related
NM_003014
6.6
1.6E−12
2.9
3.5E−3



protein 4







KRT6A
keratin 6A
NM_005554
6.1
2.3E−07
4.6
2.6E−3





*data based on the GeneChip ® extended meta probesets


**N/A = there are no assigned mRNA sequences for this transcript cluster.

















TABLE 1B










up in MIBC
up in MIBC





vs NBl
vs NMIBC













Gene

Gene
Fold-

Fold-



symbol
Gene Name
assignment
Change
P-value
Change
P-value
















TPX2
TPX2,
NM_012112
18.4
1.6E−19
2.6
3.9E−



micro-




07



tubule-








associated,








homolog








(Xenopus








laevis)







CCNB2
cyclin B2
NM_004701
10.0
3.6E−19
1.6
5.6E−








04


ANLN
anilin,
NM_018685
16.3
1.8E−18
3.1
2.0E−



actin




09



binding








protein







FOXM1
forkhead
NM_202002
8.5
5.5E−18
2.4
2.2E−



box M1




09


CDC20
cell
NM_001255
29.0
6.4E−18
2.4
6.4E−



devision




05



cycle 20








homolog









As can be clearly seen in Table IA an up regulation of expression of INHBA (FIG. 1), CTHRC1 (FIG. 2), CHI3L1 (FIG. 3), COL10A1 (FIG. 4), FAP (FIG. 5), transcript cluster 2526896 (FIG. 6), ASPN (FIG. 7), transcript cluster 2526893 (FIG. 8), ADAMTS12 (FIG. 9), IGF2BP2 (FIG. 10), PDCD1LG2 (FIG. 11), SFRP4 (FIG. 12), KRT6A (FIG. 13) was associated with MIBC and as such has prognostic value. Eleven out of thirteen were identified using the core probe sets, two were identified using the extended probe sets and have no assigned mRNA sequence and gene symbol.


As can be clearly seen in Table 1B an up regulation of expression of TPX2 (FIG. 14), CCNB2 (FIG. 15), ANLN (FIG. 16), FOXM1 (FIG. 17) and CDC20 (FIG. 18) was associated with the presence bladder cancer and as such has diagnostic value.


Example 2

Using the gene expression profile (GeneChip® Human Exon 1.0 ST Array, Affymetrix) on 114 tissue specimens of normal bladder (NBl), non-muscle invasive bladder cancer (NMIBC), muscle invasive bladder cancer (MIBC) and bladder cancer metastasis (BC-Meta) several genes were found to be differentially expressed. The expression levels of 46 of these differentially expressed genes, together with the expression level of a housekeeping gene (GAPDH) and reference gene (TBP) were validated using the TaqMan® Low Density arrays (TLDA, Applied Biosystems). In Table 2 an overview of the validated genes is shown.









TABLE 2







Gene expression assays used for TLDA analysis











Gene symbol
Accesion nr.
Assay number







LOXL2
NM_002318
Hs00158757_m1



INHBA
NM_002192
Hs01081598_m1



ADAMIS12
NM_030955
Hs00229594_m1



CTHRC1
NM_138455
Hs00298917_m1



SULF1
NM_001128205
Hs00290918_m1



CHI3L1
NM_001276
Hs00609691_m1



MMP11
NM_005940
Hs00968295_m1



OLFML2B
NM_015441
Hs00295836_m1



CD109
NM_133493
Hs00370347_m1



COL10A1
NM_000493
Hs00166657_m1



NID2
NM_007361
Hs00201233_m1



LOX
NM_002317
Hs00942480_m1



ADAMTS2
NM_014244
Hs01029111_m1



FAP
NM_004460
Hs00990806_m1



GREM1
NM_013372
Hs01879841_s1



WISP1
NM_003882
Hs00365573_m1



ITGA11
NM_001004439
Hs00201927_m1



ASPN
NM_017680
Hs00214395_m1



NTM
NM_001144058
Hs00275411_m1



PRR11
NM_018304
Hs00383634_m1



BMP8A
NM_181809
Hs00257330_s1



SLC12A8
NM_024628
Hs00226405_m1



SFRP4
NM_003014
Hs00180066_m1



KRT6A
NM_005554
Hs01699178_g1



PDCD1LG2
NM_025239
Hs00228839_m1



BCAT1
NM_001178094
Hs00398962_m1



IGF2BP2
NM_006548
Hs01118009_m1



TPX2
NM_012112
Hs00201616_m1



CCNB2
NM_004701
Hs00270424_m1



PLK1
NM_005030
Hs00153444_m1



ANLN
NM_018685
Hs01122612_m1



AURKA
NM_198433
Hs01582072_m1



FOXM1
NM_202002
Hs01073586_m1



CDC20
NM_001255
Hs00426680_mH



ECT2
NM_018098
Hs00216455_m1



PLXNA1
NM_032242
Hs00413698_m1



BUB1
NM_004336
Hs01557701_m1



CKAP2
NM_018204
Hs00217068_m1



TOP2A
NM_001067
Hs00172214_m1



TTK
NM_003318
Hs01009870_m1



CYB561D1
NM_001134404
Hs00699482_m1



HMGB3
NM_005342
Hs00801334_s1



SKP2
NM_005983
Hs01021864_m1



FAPP6
NM_001130958
Hs01031183_m1



FAM107A
NM_007177
Hs00200376_m1



NTRK3
NM_001007156
Hs00176797_m1



TBP
NM_003194
Hs00427620_m1



GAPDH
NM_002046
Hs99999905_m1










The validation with TLDA analysis was performed with 66 bladder tissue samples. Among these, 64 samples were newly selected and isolated, 2 normal bladder samples had been used before in the identification step with the GeneChip® Human Exon 1.0 ST Array.


Bladder cancer specimens in the following categories were used: Normal bladder (NBl, n=7), non-muscle invasive bladder cancer (NMIBC, n=29), muscle invasive bladder cancer (MIBC, n=27) and bladder cancer metastasis (BC-Meta, n=3).


To determine whether the identified biomarkers for bladder cancer could be used in a kit for specific detection in urine, 16 urinary sediments from patients suffering from bladder cancer (8 NMIBC and 8 MIBC) were included in the TLDA analysis and validation.


All tissue samples were snap frozen and cryostat sections were stained with hematoxylin and eosin (H.E.). These H.E.-stained sections were classified by a pathologist. Tumor areas were dissected. RNA was extracted from 10 μm thick serial sections that were collected from each tissue specimen at several levels. Tissue was evaluated by HE-staining of sections at each level and verified microscopically. Total RNA was extracted with TRIpure® (Roche, Indianapolis, Ind., CA, USA) according to the manufacturer's instructions. Total RNA was purified using the RNeasy mini kit (Qiagen, Valencia, Calif., USA).


The 16 urine samples of patients with bladder cancer were immediately cooled to 4° C. and were processed within 48 h after collection to guarantee good sample quality. The urine, EDTA stabilized, was centrifuged at 4° C. and 1.800×g for 10 minutes. The obtained urinary sediment were washed twice with icecold buffered sodium chloride solution. On centrifugation at 4° C. and 1.000×g for 10 minutes, the sediments were snap frozen in liquid nitrogen and stored at −70° C. RNA was extracted from the urinary sediments using a modified TriPure reagent protocol. After the chloroform extraction, GlycoBlue was added to the aquous phase to precipitate the RNA using isopropanol. Total RNA from the sediments was used to generate amplified sense-strand cDNA using the Whole Transcriptome Expression kit according to the manufacturers protocol.


RNA quantity and quality were assessed on a NanoDrop 1000 spectrophotometer (NanoDrop Technologies, Wilmington, Del., USA) and on an Agilent 2100 Bioanalyzer (Agilent Technologies Inc., Santa Clara, Calif., USA).


Two μg total RNA was eliminated from genomic DNA and reverse transcribed using the Quantitect® Reverse Transcription Kit Qiagen gMBH, Hilden, D) according to the manufacturer's instructions. Gene expression levels were measured using the TaqMan® Low Density Arrays (TLDA; Applied Biosystems).


A list of assays used in this study is given in Table 2. Of the individual cDNAs, 3 μl is added to 50 μl Taqman® Universal Probe Master Mix (Applied Biosystems) and 47 μl milliQ. One hundred μl of each sample was loaded into 1 sample reservoir of a TaqMan® Array (384-Well Micro Fluidic Card) (Applied Biosystems). The TaqMan® Array was centrifuged twice for 1 minute at 280 g and sealed to prevent well-to-well contamination. The cards were placed in the micro-fluid card sample block of an 7900 HT Fast Real-Time PCR System (Applied Biosystems). The thermal cycle conditions were: 2 minutes 50° C., 10 minutes at 94.5° C., followed by 40 cycles for 30 seconds at 97° C. and 1 minute at 59.7° C.


Raw data were recorded with the Sequence detection System (SDS) software of the instruments. Micro Fluidic Cards were analyzed with RQ documents and the RQ Manager Software for automated data analysis. Delta cycle threshold (Ct) values were determined as the difference between the Ct of each test gene and the Ct of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (endogenous control gene).


Furthermore, gene expression values were calculated based on the comparative threshold cycle (Ct) method, in which a normal bladder RNA sample was designated as a calibrator to which the other samples were compared.


For the validation of the differentially expressed genes found by the GeneChip® Human Exon 1.0 ST array, 66 bladder tissue specimens and 16 urinary sediments from bladder cancer patients were used in Taqman Low Density Arrays (TLDAs). In these TLDAs, expression levels were determined for the 48 genes of interest. The bladder tissue specimens were put in order from normal bladder, bladder cancer with low to high T-stage and finally bladder cancer metastasis.


Both GeneChip® Human Exon 1.0 ST array and TLDA data were analyzed using scatter- and box plots.


After analysis of the data a list of genes, shown in Table 3, was derived the expression of which is indicative for establishing the presence, or absence, of bladder tumour in a human individual suspected of suffering from bladder cancer comprising and, accordingly, indicative for bladder cancer and prognosis thereof









TABLE 3







List of genes identified









Gene




Symbol
Gene description
FIG.












INHBA
inhibin, beta A
1


CTHRC1
collagen triple helix repeat containing 1
2


CHI3L1
chitinase 3-like 1 (cartilage glycoprotein-39)
3


COL10A1
collagen, type X, alpha 1
4


FAP
fibroblast activation protein, alpha
5


TC2526896*
transcript cluster 2526896, N/A**
6


ASPN
Aspirin
7


TC2526893*
transcript cluster 2526893, N/A**
8


ADAMTS12
ADAM metallopeptidase with thrombospondin
9



type 1 motif, 12


IGF2BP2
insulin-like growth factor 2 mRNA binding
10



protein 2


PDCD1LG2
programmed cell death 1 ligand 2
11


SFRP4
secreted frizzled-related protein 4
12


KRT6A
keratin 6A
13


TPX2
TPX2, microtubule-associated, homolog
14



(Xenopus laevis)


CCNB2
cyclin B2
15


ANLN
anilin, actin binding protein
16


FOXM1
forkhead box M1
17


CDC20
cell devision cycle 20 homolog
18





*data based on the GeneChip ® extended meta probesets


**N/A = there are no assigned mRNA sequences for this transcript cluster.






Below detailed GeneChip® Human Exon 1.0 ST array data and TLDA validation data is presented for the 16 genes and only GeneChip® array data for the two transcript clusters, based on the groups normal bladder (NBl), non-muscle invasive bladder cancer (NMIBC), muscle invasive bladder cancer (MIBC) and bladder cancer metastasis (BC-Meta). For the identification of markers the non-muscle invasive bladder cancer (NMIBC) group, the muscle invasive bladder cancer (MIBC) group, the bladder cancer metastasis (BC-Meta) group and the normal bladder (NBl) group were compared.




















GeneChip

TLDA














Fold Change

Fold Change



Mean
MIBC vs
Mean
MIBC vs




2log

NMIBC
(RQ)
NMIBC





INHBA


NBl
6.33

3.04


NMIBC
5.50
10.1 
0.68
21.4


MIBC
8.84

14.56


BC-Meta
9.80

4.43


Urine NMIBC


29.52
2.2


Urine MIBC


65.53


FAP


NBl
5.17

0.73


NMIBC
4.34
6.3
0.15
28.8


MIBC
6.99

4.32


BC-Meta
8.32

1.37


Urine NMIBC






Urine MIBC





ADAMTS12


NBl
4.95

1.47


NMIBC
4.76
4.3
0.32
16.4


MIBC
6.86

5.26


BC-Meta
7.93

1.27


Urine NMIBC






Urine MIBC





KRT6A


NBl
5.02

0.60


NMIBC
4.62
6.1
4.44
9.8


MIBC
7.22

43.66


BC-Meta
4.69

1.06


Urine NMIBC






Urine MIBC


















GeneChip

TLDA














Fold Change

Fold Change



Mean
MIBC vs
Mean
MIBC vs




2log

NBl
(RQ)
NBl





TPX2


NBl
5.01
18.4 
2.46
12.0 


MIBC
9.21

29.62


NMIBC
7.86

11.55


BC-Meta
8.80

53.10


Urine NMIBC


10.00



Urine MIBC


17.50


FOXM1


NBl
4.90
8.5
2.80
7.8


MIBC
7.99

21.75


NMIBC
6.70

6.80


BC-Meta
7.79

36.41


Urine NMIBC






Urine MIBC
















GeneChip
TLDA













Fold Change

Fold Change



Mean
MIBC vs
Mean
MIBC vs




2log

NMIBC
(RQ)
NMIBC





Transcript cluster


2526896


NBl
3.73


NMIBC
3.79
7.5


MIBC
6.70


BC-Meta
9.23


CTHRC1


NBl
5.64

0.71


NMIBC
4.74
4.5
0.13
15.5 


MIBC
6.90

2.01


BC-Meta
7.73

0.87


Urine NMIBC






Urine MIBC





IGF2BP2


NBl
5.39

1.30


NMIBC
4.83
4.0
0.30
9.4


MIBC
6.82

2.83


BC-Meta
5.29

0.92


Urine NMIBC


2.19
9.9


Urine MIBC


21.79 















GeneChip

TLDA














Fold Change

Fold Change



Mean
MIBC vs
Mean
MIBC vs




2log

NBl
(RQ)
NBl





CCNB2


NBl
4.92
10.0
3.00
10.3


MIBC
8.24

30.88


NMIBC
7.52

10.23


BC-Meta
8.34

38.30


Urine NMIBC


28.81



Urine MIBC


45.33


CDC20


NBl
4.91
29.0
7.20
12.1


MIBC
9.77

87.53


NMIBC
8.48

16.76


BC-Meta
9.72

76.90


Urine NMIBC






Urine MIBC
















GeneChip
TLDA













Fold Change

Fold Change



Mean
MIBC vs
Mean
MIBC vs




2log

NMIBC
(RQ)
NMIBC





Transcript cluster


2526893


NBl
4.05


NMIBC
4.03
4.2


MIBC
6.12


BC-Meta
8.38


CHI3L1


NBl
6.12

25.83


NMIBC
5.13
13.5 
2.54
40.6


MIBC
8.89

103.10


BC-Meta
7.60

18.44


Urine NMIBC


347.7
2.0


Urine MIBC


712.8


ASPN


NBl
6.75

0.88


NMIBC
4.83
7.6
0.69
9.9


MIBC
7.76

6.82


BC-Meta
8.21

0.46


Urine NMIBC






Urine MIBC





PDCD1LG2


NBl
6.64

0.83


NMIBC
4.97
5.6
0.13
6.7


MIBC
7.45

0.87


BC-Meta
7.58

0.59


Urine NMIBC


1.31
14.4


Urine MIBC


18.91















GeneChip

TLDA














Fold Change

Fold Change



Mean
MIBC vs
Mean
MIBC vs


ANLN

2log

NBl
(RQ)
NBl





NBl
5.04
16.3
1.24
20.0


MIBC
9.06

24.86


NMIBC
7.42

4.58


BC-Meta
8.60

36.69


Urine NMIBC


13.97



Urine MIBC


27.27









Example 3

The identified genes mentioned in example 2 and listed in Table 3 were used for further validation and selection in a larger cohort of patient samples. For 17 of the 18 identified genes and for the control gene TBP used for normalization, fluorescence based real-time qPCR assays were designed and established according the MIQE guidelines. The performance of transcript clusters 2526896 and 2526893 were very similar. Therefore, no qPCR assay was established for transcript cluster 2526893. PCR products were cloned in either the pCR2.1-TOPO cloning vector (Invitrogen). Calibration curves with a wide linear dynamic range (10-1,000,000 copies) were generated using serial dilutions of the plasmids. The amplification efficiency of the primer pair was determined using the calibration curve and was >1.85. Control samples with known template concentrations were used as a reference. Two μl of each cDNA sample were amplified in a 20 μl PCR reaction containing optimized amounts of forward primer and reverse primer, 2 pmol of hydrolysis probe and 1× Probes Master mix (Roche, Cat No. 04902343001). The following amplification conditions were used: 95° C. for 10 minutes followed by 50 cycles at 95° C. for 10 seconds, 60° C. for 30 seconds and a final cooling step at 40° C. for 55 seconds (LightCycler LC480, Roche). The crossing point (Cp) values were determined using the Lightcycler 480 SW 1.5 software (Roche). The Cp values of the samples were converted to concentrations by interpolation in the generated calibration curve. The assay performance of the real-time PCR experiments was evaluated during in-study validation. The reference control samples had an inter- and intra-assay variation<30%.


Total RNA was extracted from bladder tissue and urinary sediments and used for reverse transcription to generate cDNA. In total 211 bladder tissue specimen and 100 urinary sediments were used. The group of 206 bladder tissue specimen consisted of 10 normal bladders, 124 NMIBC, 72 MIBC. The group of 100 urinary sediments consisted of urinary sediments from 15 healthy controls (defined as normal), and from 65 patients with NMIBC, and 18 patients with MIBC.


Statistical analyses were performed with SPSS® version 20.0. All data were log-transformed prior to statistical analysis as a transformation to a normal distribution. Two-tailed P values of 0.05 or less were considered to indicate statistical significance. The nonparametric Mann Whitney test (for continuous variables) was used to test if biomarker levels were significantly correlated with the presence of BCa and/or BCa prognosis (muscle invasiveness, metastasis).


The assay results for the 17 selected biomarkers are shown in Tables 4-7.









TABLE 4







Absolute and relative expression of the 17 biomarkers in NBl and BCa tissue













relative



copy numbers
copy numbers
expression1














NBl
BCa (NMIBC + MIBC)
NBl
BCa

P-



N = 10
N = 196
N = 10
N = 196
Fold
value

















Biomarker
Mean
Median
Range
Mean
Median
Range
Mean
Mean
Change
MW2




















CTHRC1
1041
1263
   1-1810
3129
835
   1-42200
917.8
1891.7
2.1
0.29


IGF2BP2
203
130
 69-651
544
85
     0-5750
182.1
248.8
1.4
0.74


ADAMTS12
91
74
 24-259
472
103
 1-4180
75.5
275.8
3.7
0.31


INHBA
411
437
 30-869
3472
386
  1-61500
400.5
1895.9
4.7
0.38


SFRP4
231
92
 55-896
1365
26
  1-37300
201.7
911.5
4.5
0.18


FAP
568
403
 146-1440
1239
270
  1-12500
469.2
738.0
1.6
0.52


CHI3L1
81
52
 1-339
1468
158
  1-21700
104.5
883.2
8.5
0.45


COL10A1
275
205
58-585
2991
984
  1-88200
225.6
1881.5
8.3
0.56


ASPN
548
205
 23-3500
608
210
  1-15700
397.8
372.0
−1.1
0.8


ANLN
92
35
 1-412
1297
772
17-8000
56.9
521.8
9.2
<0.05


TPX2
73
28
 1-325
1768
964
  1-13000
45.8
715.0
15.6
<0.05


FOXM1
57
16
 1-251
806
397
 1-5650
32.9
271.3
8.2
<0.05


CCNB2
156
47
 1-669
2160
1485
  1-11100
93.8
811.1
8.6
<0.05


CDC20
185
54
 1-795
2727
1650
  1-22000
122.0
1057.5
8.7
<0.05


KRT6A
1983
26
   1-19500
32220
132
    1-1470000
1386.7
12483.6
9.0
0.48


PDCD1LG2
288
223
119-536 
570
336
 1-3440
262.1
298.0
1.1
0.14


TC2526896
3
1
1-11
110
1
 1-1920
1.9
63.8
33.6
0.67


TBP
1230
1058
492-2820
2890
2585
77-9320









Relative expression1: ratio (copy numbers biomarker/copy number TBP)*1000


MW2: Mann-Whitney test













TABLE 5







Absolute and relative expression of the 17 biomarkers in NMIBC and MIBC tissue











copy numbers
copy numbers
relative expression1















NMIBC
MIBC
NMIBC
MIBC

P-
P-



N = 124
N = 72
N = 124
N = 72
Fold
value
value


















Biomarker
Mean
Median
Range
Mean
Median
Range
Mean
Mean
Change
MW2
T-test





















CTHRC1
898
585
 24-5360
6972
4625
 1-42200
364.6
4521.7
12.4
<0.05
3.5E−20


IGF2BP2
206
38
  0-1950
1126
611
1-5750
74.2
549.4
7.4
<0.05
1.0E−20


ADAMTS12
124
65
  1-1880
1070
515
1-4180
48.2
667.9
13.9
<0.05
1.4E−19


INHBA
529
230
  1-7440
8540
3775
29-61500
183.0
4846.0
26.5
<0.05
1.1E−22


SFRP4
76
1
 1-2300
3567
509
 1-37300
41.6
2367.6
56.9
<0.05
3.3E−23


FAP
323
167
 1-2510
2817
1915
39-12500
135.2
1776.3
13.1
<0.05
9.6E−34


CHI3L1
475
37
  1-21700
3177
1420
15-14800
170.6
2110.5
12.4
<0.05
2.6E−30


COL10A1
1087
804
  1-4670
6271
2040
 1-88200
337.4
4540.6
13.5
<0.05
2.3E−10


ASPN
223
134
  1-1450
1271
551
 1-15700
105.7
830.6
7.9
<0.05
2.2E−18


ANLN
1001
582
 17-6930
1806
1380
25-8000 
318.5
871.9
2.7
<0.05
2.6E−16


TPX2
1358
579
  1-8760
2474
1620
 1-13000
430.5
1205.1
2.8
<0.05
3.2E−10


FOXM1
723
336
 1-5650
948
515
1-3660
196.1
400.8
2.0
<0.05
4.6E−07


CCNB2
2075
1275
 17-11100
2306
1575
1-7360
637.3
1110.4
1.7
<0.05
6.2E−07


CDC20
2062
1210
  1-15300
3873
2445
 1-22000
642.0
1773.0
2.8
<0.05
3.7E−10


KRT6A
2257
71
    1-1810008
3822
2320
  1-1470000
721.9
32739.8
45.4
<0.05
1.3E−11


PDCD1LG2
477
292
  1-3200
728
413
1-3440
185.4
492.0
2.7
<0.05
6.3E−10


TC2526896
14
1
 1-606
276
70
1-1920
4.4
166.7
37.9
<0.05
1.1E−16


TBP
3354
3250
129-9320
2090
1675
77-9260 










Relative expression: ratio (copy numbers biomarker/copy number TBP)*1000


MW2: Mann-Whitney test













TABLE 6







Expression levels of the 17 biomarkers in normal bladder and BCa urine samples













copy numbers





copy numbers
BCa





NBl
(NMIBC + MIBC)

P-



N = 15
N = 85
Fold
value















Biomarker
Mean
Median
Range
Mean
Median
Range
Change
MW1


















CTHRC1
1764
1030
 58-5140
17901
10200
 12-190000
10.1
<0.005


IGF2BP2
9994
6160
 94-34600
135158
36700
1040-4000000
13.5
<0.005


ADAMTS12
1
1
1-1 
110
1
1-1490
110.0
0.037


INHBA
10487
4220
  1-70300
373104
89400
 64-6070000
35.6
<0.005


SFRP4
24
1
1-210
181
50
1-1520
7.5
0.007


FAP
8
1
1-106
758
107
 1-21000
94.8
<0.005


CHI3L1
53324
24600
2220-368000
754615
234000
2900-5380000
14.2
<0.005


COL10A1
1296
160
 1-5630
7700
6130
 1-43300
5.9
<0.005


ASPN
122
1
1-632
75
1
1-1000
0.6
0.881


ANLN
2283
832
  1-10700
37092
13600
 25-454000
16.2
<0.005


TPX2
946
521
 1-3120
28382
8860
   1-310000
30.0
<0.005


FOXM1
231
209
1-649
12502
4000
 16-165000
54.1
<0.005


CCNB2
1951
1290
 12-10000
30857
16000
1120-240000 
15.8
<0.005


CDC20
3490
2600
189-11100
40674
15800
280-61200 
11.7
<0.005


KRT6A
140105
70000
1230-762000
70419
27200
 13-576000
0.5
0.362


PDCD1LG2
1869
877
  1-8650
52224
16300
 1-679000
27.9
<0.005


TC2526896
2876
2840
557-6590
4356
3100
 73-28600
1.5
0.382


TBP
29783
21100
1160-94400
199980
161000
6000-950000


















TABLE 7







Expression levels of the 17 biomarkers in NMIBC and MIBC urine samples












copy numbers
copy numbers





NMIBC
MIBC

P-



N = 66
N = 19
Fold
value















Biomarker
Mean
Median
Range
Mean
Median
Range
Change
MW1


















CTHRC1
13991
9860
 12-76100
31483
11400
1190-190000
2.3
0.143


IGF2BP2
71976
31500
 1040-1740000
365297
85250
 2290-4000000
5.1
0.087


ADAMTS12
71
1
1-790
253
1
 1-1490
3.6
0.070


INHBA
288446
79500
  64-3420000
667174
1010001
 3200-6070000
2.3
0.451


SFRP4
153
13
1-919
276
123
 1-1520
1.8
0.085


FAP
427
100
 1-8390
1905
352
  1-21000
4.5
0.023


CHI3L1
689779
204000
   2900-505000097
9837
3940002
 8300-5380000
1.4
0.117


COL10A1
7596
6170
 1-43300
8060
6130
409-28200
1.1
0.587


ASPN
54
1
1-436
151
1
 1-1000
2.8
0.203


ANLN
31291
12450
  25-454000
57243
21300
 350-273000
1.8
0.083


TPX2
16665
7180
   1-188000
69081
14200
 232-310000
4.1
0.017


FOXM1
7218
3465
 16-76800
30299
10600
 101-156000
4.2
0.008


CCNB2
22387
14900
1120-161000
60280
27300
1130-240000
2.7
0.014


CDC20
22898
12700
 396-184000
102422
23700
 280-612000
4.5
0.013


KRT6A
6226
27650
 166-500000
99574
26200
  13-576000
16.0
0.780


PDCD1LG2
38805
16200
   1-679000
98840
22600
1900-477000
2.5
0.207


TC2526896
4294
3185
 73-27300
4571
2810
274-28600
1.1
0.609


TBP
189411
167000
6000-596000
236691
142000
9730-950000
1.2





MW1: Mann-Whitney test






In Table 4 the expression data of the 17 selected biomarkers in tissue are shown for the groups NBl and BCa total (NMIBC+MIBC). The difference (Fold-Change) between the groups and P-value provide information about/deter mine the diagnostic performance of the markers. In Table 5 the data in tissue are shown for the groups NMIBC and MIBC and thereby provide information about the prognostic performance of the biomarkers. In Tables 6 and 7 the data in the urine samples are shown.


Summary Results Examples 1, 2 and 3

INHBA (FIGS. 1, 20; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that INHBA was highly and significantly up-regulated in tissue from MIBC and BC-meta compared to NMIBC tissue. INHBA could also be detected in urine and was highly and significantly up-regulated in urine from BCa patients vs. normal urine. Therefore, INHBA has prognostic value in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


CTHRC1 (FIG. 2, Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that CTHRC1 was highly and significantly up-regulated in tissue from MIBC and BC-meta compared to NMIBC. CTHRC1 could also be detected in urine and was significantly and highly up-regulated in urine from BCa patients vs. normal urine. Therefore, CTHRC1 has prognostic value in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


CHI3L1 (FIGS. 3, 20: Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that CHI3L1 was highly and significantly up-regulated in tissue from MIBC compared to NMIBC. CHI3L1 could also be detected in urine and was significantly and highly up-regulated in urine from BCa patients vs. normal urine. Therefore, CHI3L1 has prognostic value in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


COL10A1 (FIG. 4, Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that COL10A1 was highly and significantly up-regulated in MIBC and BC-meta compared to NMIBC. COL10A1 could also be detected in urine and was significantly up-regulated in urine from BCa patients vs. normal urine. Therefore, COL10A1 has prognostic value in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


FAP (FIGS. 5, 20, 21; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that FAP was highly and significantly up-regulated in tissue from MIBC and BC-meta compared to NMIBC. FAP could also be detected in urine and was significantly and highly up-regulated in urine from BCa patients vs. normal urine and significantly up-regulated in urine from MIBC patients vs. NMIBC patients. Therefore, FAP has prognostic value in urine and in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


Transcript cluster 2526896 (FIG. 6, Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, and qPCR assay data showed that transcript cluster TC2526896 was highly and significantly up-regulated in tissue from MIBC and BC-meta compared to NMIBC. Therefore, transcript cluster 2526896 has prognostic value in tissue of patients with BCa.


ASPN (FIG. 7, Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that ASPN was highly and significantly up-regulated in tissue from MIBC compared to NMIBC. Therefore, ASPN has prognostic value in tissue of patients with BCa.


Transcript cluster 2526893 (FIG. 8): The present GeneChip® Human Exon 1.0 ST Array data showed that transcript cluster 2526893 was highly up-regulated in tissue from MIBC and BC-meta compared to NMIBC. Therefore, transcript cluster 2526893 has prognostic value in tissue of patients with BCa.


ADAMTS12 (FIGS. 9, 20; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that ADAMTS12 was highly and significantly up-regulated in tissue from MIBC and BC-meta compared to NMIBC. Low copy numbers of ADAMTS12 could also be detected in urine. ADAMTS12 was significantly up-regulated in urine from BCa patients vs. normal urine and significantly up-regulated in urine from MIBC patients vs. NMIBC patients. Therefore, ADAMTS12 has prognostic value in urine and tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


IGF2BP2 (FIGS. 10, 20; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that IGF2BP2 was highly and significantly up-regulated in tissue from MIBC compared to NMIBC. IGF2BP2 could also be detected in urine and was significantly and highly up-regulated in urine from BCa patients vs. normal urine. Therefore, IGF2BP2 has prognostic value in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


PDCD1LG2 (FIGS. 11, 21; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that PDCD1LG2 was significantly up-regulated in tissue from MIBC and BC-meta compared to NMIBC. PDCD1LG2 could also be detected in urine and was significantly and highly up-regulated in urine from BCa patients vs. normal urine. Therefore, PDCD1LG2 has prognostic value in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


SFRP4 (FIG. 12; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that SFRP4 was highly and significantly up-regulated in tissue from MIBC and BC-meta compared to NMIBC. Low copy numbers of SFRP4 could also be detected in urine. SFRP4 was significantly up-regulated in urine from BCa patients vs. normal urine. Therefore, SFRP4 has prognostic value in tissue of patients with BCa and diagnostic value in the detection of BCa in urine.


KRT6A (FIG. 13; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that KRT6A was highly and significantly up-regulated in tissue from MIBC compared to NMIBC. Therefore, KRT6A has prognostic value in tissue of patients with BCa.


TPX2 (FIGS. 14, 19, 21; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that TPX2 was highly and significantly up-regulated in tissue as well as in urine from patients with BCa compared to normal bladder and significantly up-regulated in tissue and urine from MIBC and BC-meta patients compared to NMIBC patients. Therefore, TPX2 has diagnostic value in tissue and in the detection of BCa in urine and has prognostic value in urine and in tissue of patients with BCa.


CCNB2 (FIGS. 15, 19, 21; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that CCNB2 was highly and significantly up-regulated in tissue as well as in urine from patients with BCa compared to NBl and significantly up-regulated in tissue and urine from MIBC and BC-meta patients compared to NMIBC patients. Therefore, CCNB2 has diagnostic value in tissue and in the detection of BCa in urine and has prognostic value in urine and in tissue of patients with BCa.


ANLN (FIGS. 16, 19; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that ANLN was highly and significantly up-regulated in tissue as well as in urine from patients with BCa compared to NBl and significantly up-regulated in tissue from MIBC and BC-meta patients compared to NMIBC patients. Therefore, ANLN has diagnostic value in tissue and in the detection of BCa in urine and has prognostic value in tissue of patients with BCa.


FOXM1 (FIGS. 17, 19, 21; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that FOXM1 was highly and significantly up-regulated in tissue as well as in urine from patients with BCa compared to NBl and significantly up-regulated in tissue and urine from MIBC and BC-meta patients compared to NMIBC patients. Therefore, FOXM1 has diagnostic value in tissue and in the detection of BCa in urine and has prognostic value in urine and in tissue of patients with BCa.


CDC20 (FIGS. 18, 19, 21; Tables 1, 4-7): The present GeneChip® Human Exon 1.0 ST Array data, TLDA validation and qPCR assay data showed that CDC20 was highly and significantly up-regulated in tissue as well as in urine from patients with BCa compared to NBl and significantly up-regulated in tissue and urine from MIBC and BC-meta patients compared to NMIBC patients. Therefore, CDC20 has diagnostic value in tissue and in the detection of BCa in urine and has prognostic value in urine and in tissue of patients with BCa.


Example 4
Selection of the Best Candidate Biomarkers

Based on the highest up-regulation in BCa vs NBl and MIBC vs. NMIBC, lowest P-value and high copy numbers the best performing diagnostic and prognostic individual biomarkers in tissue and urine were identified. The five best performing individual biomarkers for the detection of BCa in tissue were identified and are shown in boxplots in FIG. 19: ANLN, TPX2, FOXM1, CCNB2 and CDC20.


The five best performing individual biomarkers that could distinguish MIBC tissue from NMIBC tissue were identified and are shown in boxplots in FIG. 20: IGF2BP2, INHBA, ADAMTS12 FAP and CHI3L1.


The six best performing individual biomarkers for the detection of BCa in urine were identified and are shown in a boxplot in FIG. 21: FAP, TPX2, CCNB2, CDC20, FOXM1 and PDCD1LG2. The first five genes could also significantly distinguish MIBC from NMIBC in urine.


Given that the nature of these tumors is very heterogeneous, it is likely that combination of markers can identify different patients and have additional diagnostic and/or prognostic value to each other. For the identification of the best combinations of biomarkers for the diagnosis of BCa in urine and/or tissue and for the best combinations of markers that had prognostic value by distinguishing MIBC from NMIBC in tissue and/or urine the method of binary logistic regression analysis was performed. All data were log-transformed prior to statistical analysis as a transformation to a normal distribution. Binary logistic regression analysis (stepwise forward) was performed with the 17 biomarkers in order to find regression models and marker combinations for predicting the presence of bladder cancer (NMIBC and MIBC) in urine or for predicting whether BCa is muscle invasive or not. The statistical significant level for all tests was set at P=0.05.


As example two possible identified combinations of biomarkers are described, one for predicting the occurrence of BCa based on the expression of the markers in urine and one for predicting the occurrence of muscle invasive disease based on the expression of the markers in tissue.


In urine, CCNB2 is a key predictor and predicts that 66.7% of healthy controls have no cancer and that 96.5% from the cancer patients do have cancer. With the addition of CDC20 and PDCD1LG2 the new model predicts that 80% of the healthy controls have no cancer and 96.5% of the cancer patients are correctly classified. When INHBA is added to this model the model model predicts that 93.3% of the healthy controls have no cancer and that 98.8% of the cancer patients are correctly classified. This four biomarker model is highly significant (P=1.9E-13) showing that the biomarkers can predict the presence of bladder cancer in urine well. To visualize the performance of the biomarker combinations a ROC curve is shown (FIG. 22).


In a ROC curve, the true positive rate to detect BCa or MIBC (sensitivity) is plotted in function of the false positive rate (i.e. positives in the control group, 1-specificity) for different cut-off points. Each point on the curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. The Area Under the Curve (AUC) of the ROC curve is a measure how well a parameter can distinguish between two groups and is maximum 1.0 (all samples correctly classified). The AUC for the combination of CCNB2, CDC20, PDCD1LG2 and INHBA expression is 0.991 (95% CI: 0.977-1.000).


In tissue, FAP is a key predictor and predicts that 87% of the NMIBC are NMIBC and that 80.3% of the MIBC specimen are correctly classified. When CDC20 and CHI3L1 are added 89.3 of the NMIBC are correctly classified and 83.1% of the MIBC are correctly classified. The addition of IGF2BP2 leads to the correct classification of 90.2% of the NMIBC and 83.1% of the MIBC. This four marker model is higly significant (P=4.9×10-32) showing that the biomarkers can predict the occurrence of muscle invasive disease well. The Area Under the Curve (AUC) for the combination of IGF2BP2+FAP+CHI3Li+CDC20 expression is 0.955 (95% CI: 0.929-0.980). See FIG. 23.


Based on the binary logistic regression model the following genes and combinations were identified. For predicting the occurrence of BCa (diagnosis) based on the detection and quantification expression of the markers in tissue: at least ANLN combined with one or more markers from the list: IGF2BP2, FAP, CTHRC1, CCNB2, COL10A1 and/or TPX2.


For predicting the occurrence of muscle invasive disease (prognosis) based on the expression of the markers in tissue: at least FAP, combined with one or more markers from the list: CDC20, CHI3L1, IGF2BP2, INHBA, ADAMTS12, CCNB2 and/or ANLN or at least CHI3L1, combined with one or more markers from the list: CDC20, FAP, IGF2BP2, INHBA, ADAMTS12, CCNB2 and/or ANLN.


For predicting the occurrence of BCa based on the expression of the markers in urine at least CCNB2, combined with one or more markers from the list: CDC20, PDCD1LG2, TPX2, SFRP4, COL10A1, INHBA and/or TC2526896 or at least PDCD1LG2, combined with one or more markers from the list: CCNB2, CDC20, TPX2, SFRP4, COL10A1, INHBA and/or CTHRC1


For predicting the occurrence of muscle invasive disease based on the expression of the markers in urine at least FAP, combined with one or more from the list FOXM1, CCNB2, CDC20 and/or TC2526896


CONCLUSIONS

The present invention relates to biomarkers and their diagnostic and prognostic uses for bladder cancer. The biomarkers can be used alone or in combination. The invention provides methods for diagnosing bladder cancer in a subject, comprising measuring the levels of a single or a plurality of biomarkers in a biological sample derived from a subject suspected of having bladder cancer. Differential expression of one or more biomarkers in the biological sample is compared to one or more biomarkers in a healthy control sample indicates that a subject has cancer. Furthermore, the invention provides methods for determining classification of tumors according to the aggressiveness or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer, comprising measuring the levels of a single or a plurality of biomarkers in a biological sample derived from a subject having bladder cancer. Differential expression of one or more biomarkers in the biological sample is compared to one or more biomarkers in a NMIBC control sample that indicates that a subject has an aggressive type of bladder cancer.


Based on the results obtained and described in examples 1, 2, 3 and 4, the following observations can be made:

    • 1) Given that the biological sample is urine, the identified best performing individual biomarkers for diagnosis of BCa were: FAP, TPX2, CCNB2, CDC20, FOXM1 and PDCD1LG2. The first five markers could also significantly distinguish MIBC from NMIBC in urine and therefore had prognostic value.
    • 2) The best combinations of biomarkers for predicting the occurrence of BCa based on the expression of the markers in urine contain at least CCNB2, combined with one or more markers from the list: CDC20, PDCD1LG2, TPX2, SFRP4, COL10A1, INHBA and/or TC2526896; or contain at least: PDCD1LG2, combined with one or more markers from the list: CCNB2, CDC20, TPX2, SFRP4, COL10A1, INHBA and/or CTHRC1;
    • 3) The best combination of biomarkers for predicting the occurrence of muscle invasive disease based on the expression of the markers in urine contains at least FAP, combined with one or more from the list FOXM1, CCNB2, CDC20 and/or TC2526896;
    • 4) Given that the biological sample is tissue, the identified best performing individual biomarkers for diagnosis of BCa were: ANLN, TPX2, FOXM1, CCNB2 and CDC20;
    • 5) The identified best performing individual biomarkers that could distinguish MIBC tissue from NMIBC tissue were: IGF2BP2, INHBA, ADAMTS12 FAP and CHI3L1;
    • 6) The best combination of biomarker s for predicting the occurrence of BCa based on the expression of the markers in tissue contains at least ANLN combined with one or more markers from the list: IGF2BP2, FAP, CTHRC1, CCNB2, COL10A1 and/or TPX2;
    • 7) The best combinations of biomarkers for predicting the occurrence of muscle invasive disease based on the expression of the markers in tissue contain at least FAP, combined with one or more markers from the list: CDC20, CHI3L1, IGF2BP2, INHBA, ADAMTS12, CCNB2 and/or ANLN or at least CHI3L1, combined with one or more markers from the list: CDC20, FAP, IGF2BP2, INHBA, ADAMTS12, CCNB2 and/or ANLN

Claims
  • 1. Method, preferably an in vitro method, for establishing the presence, or absence, of a bladder tumour in a human individual; or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer comprising: a) determining the expression of one or more genes chosen from the group consisting of CCNB2, ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and transcript cluster 2526896 in a sample originating from said human individual; andb) establishing up regulation of expression of said one or more genes as compared to expression of said respective one or more genes in a sample originating from said human individual not comprising tumour cells or tissue, or from an individual, or group of individuals, not suffering from bladder cancer; andc) establishing the presence, or absence, of a bladder tumour based on the established up- or down regulation of said one or more genes; or establishing the prediction of prognosis and disease outcome for a human individual suffering from bladder cancer based on the established up- or down regulation of said one or more genes.
  • 2. Method according to claim 1, wherein establishing the presence, or absence, of bladder cancer in a human individual preferably includes diagnosis, prognosis and/or prediction of disease survival.
  • 3. Method according to claim 1, wherein the method is an ex vivo or in vitro method.
  • 4. Method according to claim 3, wherein expression analysis is performed on a sample selected from the group consisting of body fluid, saliva, lymph, blood, urine, tissue sample and a transurethral resection of a bladder tumour (TURBT), preferably blood, urine, urine desiment, and samples of, derived or originating from TURBT specimens.
  • 5. Method according to claim 1, wherein determining the expression comprises determining mRNA expression of the one or more genes, preferably by Northern blot hybridisation or amplification based techniques, preferably PCR, real time PCR, or NASBA.
  • 6. Method according to claim 1, wherein expression analysis comprises high-throughput array chip analysis.
  • 7. Method according to claim 1, wherein expression analysis comprises determining protein levels of the said genes, preferably by matrix-assisted laser desorption-ionization time-of-flight mass spectrometer (MALDI-TOF).
  • 8. Use of expression analysis of one or more genes selected from the group consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and transcript cluster 2526896 for establishing the presence, or absence, of a bladder tumour or establishing the prediction of prognosis and disease outcome for an individual patient suffering from bladder cancer.
  • 9. Kit of parts for establishing the presence, or absence, of a bladder tumour and establishing the prediction of prognosis and disease outcome for an individual patient suffering from bladder cancer said kit of parts comprises: expression analysis means for determining the expression of one or more genes chosen from the group consisting of ADAMTS12, ASPN, CDC20, COL10A1, CTHRC1, FAP, SFRP4, FOXM1, KRT6A, ANLN, CHI3L1, TPX2, CCNB2, IGF2BP2, INHBA, PDCD1LG2, transcript cluster 2526893, and transcript cluster 2526896;instructions for use.
Priority Claims (1)
Number Date Country Kind
PCT/EP2013/054777 Mar 2013 EP regional
PCT Information
Filing Document Filing Date Country Kind
PCT/EP2014/054501 3/7/2014 WO 00