COMBINATIONS OF MOLECULAR MARKERS IN PROSTATE CANCER PROVIDING A DIAGNOSTIC TOOL WITH IMPROVED SENSITIVITY/SPECIFICITY

Description

The present invention relates to methods for in vitro establishing, or diagnosing, high grade or low grade prostate cancer in a sample, preferably from a readily obtainable sample such as an urine, a prostatic fluid or ejaculate sample or a processed, or derived sample thereof, originating from human individual suspected of suffering from prostate cancer using expression level analysis of a combination of two, three or four molecular markers for prostate cancer. The present invention further relates to the use in expression level analysis of these combined markers for in vitro establishing high grade or low grade prostate cancer and to a kit of parts providing expression analysis of combinations of the present molecular markers for establishing high grade or low grade prostate cancer.

In the Western male population, prostate cancer has become a major public health problem. In many developed countries it is not only the most commonly diagnosed malignancy, but it is the second leading cause of cancer related deaths in males as well. Because the incidence of prostate cancer increases with age, the number of newly diagnosed cases continues to increase as the life expectancy of the general population increases. In the United States, approximately 218,000 men, and in Europe approximately 382,000 men are newly diagnosed with prostate cancer every year.

Epidemiology studies show that prostate cancer is an indolent disease and that more men die with prostate cancer than from it. However, a significant fraction of the tumors behave aggressively and as a result approximately 32,000 American men and approximately 89,000 European men die from this disease on a yearly basis.

The high mortality rate is a consequence of the fact that there are no curative therapeutic options for metastatic prostate cancer. Androgen ablation is the treatment of choice in men with metastatic disease. Initially, 70 to 80% of the patients with advanced disease show response to therapy, but with time the majority of the tumors will become androgen independent. As a result most patients will develop progressive disease.

Since there are no effective therapeutic options for advanced prostate cancer, early detection of this tumor is pivotal and can increase the curative success rate. Although the routine use of serum prostate-specific antigen (PSA) testing has undoubtedly increased prostate cancer detection, one of the main drawbacks of the serum PSA (sPSA) test is the low specificity. Also conditions such as benign prostatic hyperplasia (BPH) and prostatitis can lead to an elevated sPSA level. This results in high negative biopsy rates of 70-80% in the so-called 'grey area' of PSA levels 4.0-10.0 ng/ml.

Moreover, PSA-based screening has led to the diagnosis of clinically insignificant prostate tumors, i.e. in the absence of screening, these tumors would not have been diagnosed within the patient' s lifetime, which results in over-treatment.

Therefore, (non-invasive) molecular tests, that can accurately identify those men who have early stage, clinically localized prostate cancer and who would gain prolonged survival and quality of life from early radical intervention, are urgently needed. The prime challenge for molecular diagnostics is the identification of clinically significant prostate cancer, i.e. a Gleason Score of >=7 and/or percentage biopsy positive cores >=33% and/or clinical stage >=T2 (Epstein criteria). Furthermore, markers predicting and monitoring the response to treatment are urgently needed. Molecular biomarkers identified in tissues can serve as target for new body fluid based molecular tests. A suitable biomarker preferably fulfils the following criteria:

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

2) it must have an impact on clinical management.

Further, for diagnostic purposes, it is important that the biomarkers are tested in terms of tissue- specificity and discrimination potential between prostate cancer, normal prostate and BPH.

Furthermore, it can be expected that (multiple) biomarker-based assays enhance the sensitivity for cancer detection.

Considering the above, there is an urgent need for molecular prognostic biomarkers capable of predicting the biological behaviour of prostate cancer and outcome.

For the identification of new candidate markers for prostate cancer, it is necessary to study expression patterns in malignant as well as non-malignant prostate tissues, preferably in relation to other medical data.

Recent developments in the field of molecular techniques have provided new tools that enabled the assessment of both genomic alterations and proteomic alterations in samples in a comprehensive and rapid manner. These tools have led to the discovery of many new promising biomarkers for prostate cancer. These biomarkers may be instrumental in the development of new tests that have a high specificity in the diagnosis and prognosis of prostate cancer.

For the molecular diagnosis of prostate cancer, genes that are highly up-regulated in prostate cancer compared to low or normal expression in normal prostate tissue are of special interest. Such genes could enable the detection of one tumor cell in a large background of normal cells, and could thus be applied as a diagnostic marker in prostate cancer detection.

In the search for PCa specific biomarkers, two promising candidates have been identified: Prostate CAncer gene 3 (PCA3) and TMPRSS2-ERG gene fusions. These biomarkers can be measured using a non-invasive urine test. The PCA3 gene is highly over-expressed in prostate tumors, and has diagnostic value to predict biopsy outcome, but its prognostic value is limited. The Progensa® PCA3 test is a FDA-approved molecular diagnostic test that is available to urologists.

Gene fusions in which ETS family members are mostly fused to androgen- regulated genes, particularly TMPRSS2, are PCa-specific molecular events. TMPRSS2-ERG gene fusions are present in approximately 50% of PCa patients. The prognostic value of this gene fusion is still unclear. Consequently, the urgent need for more accurate prognostic biomarkers for PCa persists.

In the art, there is a continuing need for assays providing establishment, or diagnosis, of all prostate cancers with maximal sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). All prostate cancers include both low-grade (Gleason Score >7) and high-grade (Gleason Score >=7) prostate cancers and will be further referred to as PrCa_total.

Furthermore, there is a continuing need for assays for the prediction, or prognosis, of clinical significant prostate cancer, i.e. a Gleason Score of >=7 and/or a percentage biopsy positive cores >=33% and/or a clinical stage >=T2 (Epstein criteria) with maximal sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). These clinically significant prostate cancers will be further referred to as Sign-PrCa.

The present invention disclosed a two, three or four gene based model for improved diagnosis of PrCa_total and/or Sign-PrCa for meeting the above indicated needs of the art.

Sensitivity relates to the assay's ability to identify positive results. In the present context, sensitivity indicates the proportion of individuals suffering from prostate cancer testing positive for PrCa_total or Sign-PrCa.

Specificity relates to the ability of the test to identify negative results. In the present context, specificity is defined as the proportion of individuals not suffering from prostate cancer (based on negative prostate biopsies) testing negative for PrCa_total or Sign-PrCa.

Positive predictive value (PPV) relates to the ability of a test to identify the proportion of positive test results that are true positives. In the present context, PPV is defined as the proportion of individuals with prostate cancer (PrCa_total or Sign-PrCa) testing correctly positive among all positive test results.

Negative predictive value (NPV) relates to the ability of a test to identify the proportion of negative test results that are true negatives. In the present context, NPV is defined as the proportion of individuals without prostate cancer (i.e. negative prostate biopsies) testing correctly negative among all negative test results. It is an object of the present invention, amongst other objects, to provide an assay for establishing, or diagnosing, PrCa_total or Sign-PrCa in a sample of a human individual suspected to suffer from prostate cancer thereby aiding in the development of an effective clinical strategy to treat prostate cancer.

The above object, amongst other objects, is met by the present invention as outlined in the appended claims providing an assay and means for performing the assay allowing detecting, amongst others, PrCa_total or Sign-PrCa with improved sensitivity, specificity, PPV and NPV.

Specifically, the above object, amongst other objects, is met, according to a first aspect of the present invention, by methods for in vitro establishing prostate cancer (PrCa), or PrCa_total, preferably, preferably Sign_PrCa, in a sample originating from a human individual suspected of or suffering from prostate cancer comprising:

a) determining expression levels of DLX1 and HOXC6;

b) establishing up-regulation of the expression levels of DLX1 and HOXC6 as compared to expression levels of DLX1 and HOXC6 in a sample originating from an individual not suffering from prostate cancer or as compared to a reference value indicative of a non-disease expression level; and

c) establishing the presence or absence of prostate cancer (PrCa) based on the up-regulation of the expression levels of DLX1 and HOXC6 in said sample.

In the present description, reference is made to human genes, such as DLX1 and HOXC6, suitable as biomarkers for prostate cancer by referring to their arbitrarily assigned names. Although the skilled person is readily capable to identify, and use, the present genes as biomarkers based on these names, the appended sequence listing provides both the cDNA sequence and protein sequences of these genes in the public database. Based on the data provided in the tables and figures, the skilled person, without undue experimentation and using standard molecular biology means, will be capable of determining the expression levels of the indicated biomarkers in a sample thereby providing the present methods.

According to a preferred embodiment of this first aspect of the present invention, the present methods, in step (a), further comprise determining the expression level of HOXC4; in step (b) further comprise establishing up-regulation of the expression level of HOXC4 as compared to expression level of HOXC4 in a sample originating from an individual not suffering from prostate cancer or as compared to a reference value indicative of a non-disease expression level; and in step (c), further comprise establishing the presence or absence of prostate cancer (PrCa) based on the up-regulation of the expression levels of DLX1, HOXC6 and HOXC4 in said sample. According to another preferred embodiment of this first aspect of the present invention, the present methods, in step (a), further comprise determining the expression level of TDRD1 ; in step (b) further comprise establishing up-regulation of the expression level of TDRD1 as compared to expression level of TDRD1 in a sample originating from an individual not suffering from prostate cancer or as compared to a reference value indicative of a non-disease expression level; and in step (c), further comprise establishing the presence or absence of prostate cancer (PrCa) based on the up-regulation of the expression levels of DLX1, HOXC6 and TDRD1 in said sample.

According to an especially preferred embodiment of this first aspect of the present invention, the present methods, in step (a), further comprise determining the expression level of HOXC4 and TDRD1 ; in step (b) further comprise establishing up-regulation of the expression level of HOXC4 and TDRD1 as compared to expression level of HOXC4 and TDRD1 in a sample originating from an individual not suffering from prostate cancer or as compared to a reference value indicative of a non-disease expression level; and in step (c), further comprise establishing the presence or absence of prostate cancer (PrCa) based on the up-regulation of the expression levels of DLX1, HOXC6, HOXC4 and TDRD1 in said sample

In the present description, prostate biopsies are considered to be the gold standard for PrCa diagnosis. Negative biopsies indicate normal prostate conditions and will be further referred to as no-PrCa.

In the present description, expression level analysis comprises establishing an increased expression of least two biomarkers selected from the group consisting of HOXC4, HOXC6, DLX1 and TDRD1, or any combination thereof, as compared to expression of these genes in a similar, equivalent, or corresponding sample originating from a human individual not suffering from prostate cancer (no-PrCa). In other words, an increased expression level of a gene or biomarker according to the present invention is a measure of gene expression relative to a non- disease standard.

Suitable combinations of biomarkers according to the present inventon are, amongst others, HOXC4/DLX1 ; HOXC4/DLX 1 /TDRD 1 ; HOXC4/DLX 1/TDRD 1/HOXC6; HOXC4/TDRD 1 ; or DLX1/TDR1.

For example, establishing an increased expression of at least two biomarkers selected from the group consisting of HOXC4, HOXC6, DLX1 and TDRD1, or any combination thereof, as compared to expression of these genes under non-prostate cancer conditions (no-PrCa), allows establishing, or diagnosing prostate cancer (PrCa_total) or significant prostate cancer (Sign- PrCa), thereby providing prognosis and/or prediction of disease survival and an aid to design a clinical treatment protocol. HOXC4 and HOXC6 are family members of the homeobox superfamily of genes and the HOX subfamily contain members that are transcription factors involved in controlling and coordinating complex functions during development via spatial and temporal expression patterns. In humans, there are 39 classical HOX genes organized into the clusters A, B, C and D.

HOXC4, is one of several homeobox HOXC genes located in a cluster on chromosome 12. Three genes, HOXC4, HOXC5 and HOXC6, share a 5' non-coding exon.

Transcripts may include the shared exon spliced to the gene-specific exons, or they may include only the gene-specific exons. Two alternatively spliced variants that encode the same protein have been described for HOXC4. Transcript variant one represents the longer transcript and includes the shared exon. Transcript variant two includes only gene-specific exons and differs in the 5'UTR compared to variant 1. Within the context of the present invention, HOXC4 expression level determination refers to the expression levels of variants one and two.

Also for HOXC6, alternatively spliced transcript variants encoding different isoforms have been identified. Transcript variant two represents the longer transcript and includes the shared exon. It contains a distinct 5'UTR and lacks an in-frame portion of 5' coding region compared to variant one. The resulting isoform two has a shorter N-terminus when compared to isoform one. Transcript variant one includes only gene-specific exons and encodes the longer isoform. Within the context of the present invention, HOXC6 expression level determination refers to the expression levels of variants 1 and 2.

TDRD1 is a tudor related gene essential for male germ-cell differentiation. Tudor domains are found in many eukaryotic organisms and have been implicated in protein-protein interactions in which methylated protein substrates bind to these domains. TDRD1 plays a central role during spermatogenesis by participating in the repression transposable elements and prevent their mobilization, which is essential for the germline integrity.

DLXl belongs to the family of homeodomain transcription factors which are related to the Drosophila distal-less (Dll) gene. The family has been related to a number of developmental features and appears to be well preserved across species. Dlx genes are implicated in tangential migration of interneurons from the subpallium to the pallium during vertebrate brain development. It has been suggested that Dlx promotes the migration of interneurons by repressing a set of proteins that are normally expressed in terminally differentiated neurons and act to promote the outgrowth of dendrites and axons.

With respect to DLXl expression, at least two transcript variants are known. Transcript variant 1 is longer than transcript variant 2 and contains an internal exon in the coding region that results in a frame shift and premature stop codon. Within the context of the present invention, DLXl expression level determination refers to determination of the expression levels of both transcripts. According to a preferred embodiment of this first aspect of the present invention, determining expression levels comprises determining mRNA expression levels. In other words, determining expression levels comprises determining transcription levels.

According to another preferred embodiment of this first aspect of the present invention, determining expression levels comprises determining protein levels. In other words, determining expression levels comprises determining translation levels.

According to other particularly preferred embodiments of this first aspect of the present invention, establishing prostate cancer (PrCa) comprises establishing high grade (Gleason score >= 7) or low grade (Gleason score <7) prostate cancer and/or establishing prostate cancer (PrCa) comprises establishing a percentage of positive cores of >=33 and/or establishing prostate cancer (PrCa) comprises establishing a clinical stage of >= T2 according to the Epstein criteria.

According to the present invention, the present methods are preferably performed using a sample selected from the group consisting of urine, urine derived, prostatic fluid, prostatic fluid derived, ejaculate and ejaculate derived, an urine, or an urine derived, sample. These samples are the most readily obtainable samples of human bodily derivable samples.

Within the context of the present description, an urine, prostatic fluid or ejaculate derived sample is a sample originating from these bodily fluids, i.e. sample of these fluids further processed, for example, by sedimentation, extraction, precipitation, dilution etc.

According to a second aspect, the present invention relates to the use of a combination of DLXl and HOXC6; DLXl, HOXC6 and HOXC4; DLXl, HOXC6 and TDRDl ; or DLXl, HOXC6, HOXC4 and TDRDl expression markers expression markers for in vitro establishing prostate cancer (PrCa) or PrCa_total, preferably Sign_PrCa. Other suitable combinations according to this second aspect of the present invention are, amongst others, HOXC4/DLX1 ; HOXC4/DLX1 /TDRDl; HOXC4/TDRD 1 ; or DLX1/TDR1.

According to a preferred embodiment of this second aspect of the present invention, establishing prostate cancer comprises establishing prostate cancer in a sample selected from the group consisting of urine, urine derived, prostatic fluid, prostatic fluid derived, ejaculate and ejaculate derived.

According to a third aspect, the present invention relates to kits of parts for in vitro establishing prostate cancer in a sample originating from human individual suspected of suffering from prostate cancer comprising:

expression level analysis means for determining the expression levels of a combination of biomarkers selected from the group consisting of HOXC6 and DLXl; HOXC6, DLXl and HOXC4; HOXC6, DLXl, TDRDl ; and HOXC6, DLX 1 , HOXC4 and TDRD 1 ; and

instructions for use. Other suitable combinations according this third aspect of the present invention include, amongst others, HOXC4/DLX1 ; HOXC4/DLX1 /TDRDl; HOXC4/TDRD 1 ; or

DLX1/TDR1.

In the present kits of parts, the expression level analysis means allow detection and quantification of the gene mRNA expression levels of the indicated gene combinations of HOXC4, HOXC6, DLXl and TDRDl using any non-invasive molecular biology technique suitable for the purposes of the invention, such as, for example, expression micro-arrays, quantitative real-time PCR, conventional PCR, NASBA, etc.

Quantitative real-time PCR (qRT-PCR) is preferably used according to the present invention to detect and quantify the present diagnostic and/or prognostic genes. This technique is accurate and it allows quantifying the specific mRNA of the genes of interest.

In a particular advantageous embodiment, the invention provides methods and means for determining whether a sample is to be classified as no prostate cancer no-PrCa (prostate biopsies negative for prostate cancer), PrCa_total (all prostate cancers; low- and high grade) or Sign-PrCa (significant prostate cancer: Gleason Score of >=7 and/or a percentage biopsy positive cores >=33 and/or a clinical stage >=T2).

Considering the heterogeneous nature of prostate tumors, the use of at least two biomarkers appears to be necessary for most, if not all, prostate cancers.

Binary logistic regression analysis can be used to define the best gene panel for the most reliable classification of the patient samples in no prostate cancer, prostate cancer total (diagnosis) or clinical significant prostate cancer (prognosis). The goal of this binary logistic regression analysis is to find the best set of genes so that cases that belong to a particular category of prostate cancer will have a very high calculated probability that they will be allocated to that category.

Using this analysis, combinations of biomarkers selected from the group consisting of HOXC6 and DLXl ; HOXC6, DLXl and HOXC4; HOXC6, DLXl, TDRDl; and HOXC6, DLXl, HOXC4 and TDRDl can be identified for the diagnosis of prostate cancer (i.e. PrCa_total) and prognosis (i.e. Sign-PrCa) of prostate cancer. Other suitable combinations include, amongst others, HOXC4/DLX1 ; HOXC4/DLX1 /TDRDl ; HOXC4/TDRD 1 ; or DLX1/TDR1.

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

Figure 1 shows the Receiver Operating Characteristic curve to visualize the

diagnostic potential of the individual biomarkers HOXC4, HOXC6, DLXl and TDRDl to discriminate PrCa_total from no PrCa in the absence of an arbitrary cut-off value. Figure 2 shows the Receiver Operating Characteristic curve to visualize the

prognostic potential of the individual biomarkers HOXC4, HOXC6, DLX1 and TDRD1 to discriminate Sign-PrCa from the Rest (i.e. negative biopsy and insignificant PCa) in the absence of an arbitrary cut-off value.

Insignificant PrCa is defined as tumors with GS<7, biopsy positive cores

<33 and < cT2 stage.

Figure 3 shows the Receiver Operating Characteristic curve to visualize the

diagnostic potential of HOXC6, the combination of HOXC6 with DLX1, the combination of HOXC6 with DLX1 and HOXC4 and the combination of HOXC6 with DLX 1 and HOXC4 and TDRD 1 to discriminate

PrCa_total from no PrCa in the absence of an arbitrary cut-off value.

Figure 4 shows the Receiver Operating Characteristic curve to visualize the

prognostic potential of HOXC6, the combination of HOXC6 with DLX1, the combination of HOXC6 with DLX1 and HOXC4 and the combination of HOXC6 with DLX 1 and HOXC4 and TDRD 1 to discriminate Sign-

PrCa from the Rest (i.e. negative biopsy and insignificant PCa) in the absence of an arbitrary cut-off value.

Figure 5 shows the Receiver Operating Characteristic curve to visualize the

diagnostic potential of the four gene panel (HOXC6, DLX1, HOXC4 and TDRD1) in comparison with mPCA3 levels and serum PSA values to discriminate PrCa_total from no PrCa in the absence of an arbitrary cut-off value.

Figure 6 shows the Receiver Operating Characteristic curve to visualize the

prognostic potential of the four gene panel (HOXC6, DLX1, HOXC4 and TDRD1) in comparison with mPCA3 levels and serum PSA values to discriminate Sign-PrCa from the Rest (i.e. negative biopsy and insignificant PCa) in the absence of an arbitrary cut-off value.

Example 1

Initial preclinical discovery of candidate biomarkers

To identify markers for prostate cancer diagnosis and prediction of prognosis, the platform of Affymetrix GeneChips was used. Based on the robustness of this platform and the high resolution (many oligoprobes located in most exons of each gene) we decided to use the GeneChip Exon 1.0 ST array to determine the gene profiles of prostate tissue specimens that were collected at the Radboud University Nijmegen Medical Centre and Canisius Wilhemmina Hospital Nijmegen after a consent form approved by the institutional review board was signed by all participants.

Tissue specimens of patients with prostate cancer in the following groups were collected: normal prostate (NPr; n=8),Benign Prostatic Hyperplasia (BPH; n=12), Low grade prostate cancer (LG-PrCa; n=25),High grade prostate cancer (HG-PrCa;n=24), Castration resistant prostate cancer (CRPC; n=23)and prostate cancer metastases (PrCa Met; n=7).

Briefly, NPr tissue was obtained after radical or TURP from cancer free regions of these samples or from autopsy. BPH tissue was obtained from TURP or transvesical open prostatectomy (Hryntschak).LG-PrCa tissue was obtained from primary tumors with a Gleason Score <6, HG-PrCa tissue was obtained from primary tumors with a Gleason Score >7, CRPC tissue was obtained from patients that are progressive under endocrine therapy and who underwent a transurethral resection of the prostate (TURP) and PrCa Met tissue specimens were obtained from positive lymfnodes after LND or after autopsy. The tissues were snap frozen and cryostat sections were H.E. stained for classification by a pathologist.

Total RNA was extracted from tumor- and tumor-free areas using TRIzol

(Invitrogen, Carlsbad, CA, USA) following manufacturer's instructions. The total RNA was DNase treated and purified with the Qiagen RNeasy mini kit (Qiagen, Valencia, CA, USA).

Integrity of the RNA was checked by electrophoresis using the Agilent 2100 Bioanalyzer. Samples with RNA integrity number (RIN) >=6 were included.

Gene expression profiles were determined using the GeneChip Human Exon 1.0

Sense Target arrays (Affymetrix) according manufacturer's instructions. Gene-level and exon-level expression values were derived from the CEL file using the model-based Robust Multiarray Average algorithm as implemented in Partek® software (Partek Genomics Suite 6.6). P-values of differentially expressed genes between conditions were calculated using ANOVA analysis. For the identification of biomarkers the expression analysis of the different groups were compared:

NP/BPH with LG- and HG-PCa, PCa-M+ with LG- and HG-PCa, CRPC with LG- and HG-PCa.

Results and conclusion Using the GeneChip Exon 1.0 ST array we were able to identify an initial group of

47 interesting genes. These selected genes were further analysed and validated with RT-qPCR technique using Taqman Low Density Arrays(TLDA; Applied Biosystems) as will be further elucidated in example 2. Example 2

Preclinical selection of candidate biomarkers

Further analysis of the 47 biomarkers was performed using Taqman® Low Density Arrays (TLDA; Applied Biosystems). Tissue and urine specimens were collected at the Radboud University Nijmegen Medical Centre and Canisius Wilhemmina Hospital Nijmegen. Tissue specimens of patients with prostate cancer in the following groups were collected: normal prostate (NPr; n=6),Benign Prostatic Hyperplasia (BPH; n=6), Low grade prostate cancer (LG- PrCa; n=14),High grade prostate cancer (HG-PrCa;n=14), Castration resistant prostate cancer (CRPC; n=14)and prostate cancer metastases (PrCa Met; n=8). Tissue selection and RNA extraction and purification were performed as described in example 1. Two ug DNase-treated total RNA was reverse transcribed using Superscript II Reverse Transcriptase (Invitrogen) according manufacturer's instructions.

For the validation not only prostate tissue specimens were used. To investigate whether the selected markers could successfully be detected in body fluids also normal bladder tissue specimens (n=2), peripheral blood lymphocytes (PBL,n=2) and urinary sediment specimens from patients which had PrCa in their biopsies (n=9) and 7 from patients with negative biopsies (n=7)) were included included in the marker validation step. The background signal of the markers in normal bladder and urinary sediments from patients without prostate cancer should be low.

First voided urine samples were collected after digital rectal examination (DRE) from men scheduled for prostate cancer. After urine specimen collection, the urologist performed prostate biopsies according to a standard protocol. Prostate biopsies were evaluated and in case prostate cancer was present the Gleason score was determined. First voided urine after DRE (20-30 ml) was collected in a tube containing 2 ml 0.5M EDTA pH 8.0. All samples were immediately cooled to 4°C and were mailed 10 in batches with cold packs to the laboratory.

The samples were processed within 48 h after the samples were acquired to guarantee good sample quality. Upon centrifugation at 4°C and 1,800 x g for 10 minutes, urinary sediments were obtained. These urinary sediments were washed twice with ice-cold buffered sodium chloride solution (at 4°C and 1,800 x g for 10 minutes), snap-frozen in liquid nitrogen, and stored at -70°C. Total RNA was extracted from these urinary sediments, using Trizol according to the manufacturers protocol. Two additional steps were added. Firstly, 2 μΐ glycogen (15 mg/ml) was added as a carrier (Ambion, Austin (TX), USA) before precipitation with isopropanol.

Secondly, a second precipitation step with 3M sodium-acetate pH 5.2 and 100% ethanol was performed to discard traces of Trizol.

The RNA was DNase treated using amplification grade DNasel (Invitrogen™,

Breda, the Netherlands) according to the manufacturers protocol. Again glycogen was added as carrier and the RNA was precipitated with 3M sodium-acetate pH 5.2 and 100% ethanol for 2hr at -20°C. The RNA was dissolved in 16.5 μΐ RNase-free water and 1 μg of total RNA was used for RNA amplification using the Ambion® WT Expression Kit (Ambion, Austin (TX), USA) according to the manufacturer's instructions. Two ug amplified RNA was reverse transcribed using Superscript II Reverse Transcriptase (Invitrogen) according manufacturer's instructions.

To determine gene expressions levels the cDNA generated from RNA extracted from both tissue specimens and urinary sediments was used as template in the TLDA's. After centrifugation of the 384-well TLDA cards for 1 minute at 280g the cards were run in a 7900 HT Fast Real-Time PCR System (Applied Biosystems). Raw data were recorded with the Sequence detection System (SDS) software of the instruments analyzed with RQ documents and the RQ Manager Software for automated data analysis. Delta cycle threshold 30 (Ct) values were determined as the difference between the Ct of each test gene and the Ct of hypoxanthine phosphoribosyltransf erase 1 (HPRT1) (endogenous control gene). Furthermore, gene expression values were calculated based on the comparative threshold cycle (Ct) method, in which a normal prostate RNA sample was designated as a calibrator to which the other samples were compared.

Results

After analysis of the generated data, a list of 10 most promising biomarkers indicative for prostate cancer and the prognosis thereof was obtained.

Example 3

Final selection and model development of candidate biomarkers and combinations thereof in a clinical prospective study

Study design

In a prospective multicenter study it was tested whether the ten in the pre -clinical biomarker discovery selected biomarkers or a combination of these markers could identify patients with PrCa_total or Sign-PrCa based on expression levels in urine samples. If so, these markers or a combination of markers could be used in an in vitro non-invasive method for diagnosing

PrCa_total or Sign-PrCa.

Men who were scheduled for (initial or repeat) prostate biopsies, based on elevated sPSA levels, a family history of PCa or an abnormal DRE were included. First-catch urine after DRE was collected from 443 men. Prostate biopsies were performed and evaluated per hospital's standard procedure. In addition, one experienced genitourinary pathologist reviewed all biopsy Gleason scores independently, being blinded for the biomarker scores. Men were recruited at six urology clinics in the Netherlands (Radboud University Nijmegen Medical Centre, Nijmegen; Academic Medical Centre, Amsterdam; ZGT Hospital, Hengelo; Canisius Wilhelmina Hospital, Nijmegen; Scheper Hospital, Emmen; and St. Elisabeth Hospital, Tilburg). Exclusion criteria were: history of PCa, medical therapy known to affect sPSA levels, prostate biopsies within three months prior to enrolment, or invasive treatment for BPH within six months prior to enrolment. The respective independent ethics committees approved the study protocol and all included patients provided written informed consent. The biomarker discovery and the clinical validation study were both performed in accordance with the STARD (S Andards for Reporting of Diagnostic accuracy) criteria and REMARK (Reporting Recommendations for Tumor Marker Prognostic Studies) guidelines.

Data collection

Clinical pathological data were collected for each patient, including: age, sPSA, DRE and TRUS results, prostate volume, biopsy results (current and history), radiological results, clinical TNM stage (if diagnosed with PCa) and radical prostatectomy results (if applicable).

Specimen processing

First-catch urine specimens after DRE were processed using a validated standard operating procedure (SOP), total RNA was extracted from the urinary sediments, RNA was amplified and cDNA was generated as was described in example 2.

To determine the expression levels (copy numbers) for the selected biomarkers and for the genes KLK3, PCA3 and HPRT1 in these specimens, optimized real-time quantitative PCR assays were developed (according the MIQE guidelines). Fluorescence based real-time PCR assays with primers and hydrolysis probe were designed. PCR products were cloned into vectors and calibration curves with a wide linear dynamic range (10 - 1.000.000 copies) were made in order to calculate copy numbers.

Two μΐ of each cDNA sample was amplified in a 20 μΐ PCR reaction containing optimized amounts of forward primer and reverse primer, 2 pmol of hydrolysis probe and lx Probes Master mix (Roche). 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 copy numbers by interpolation in the generated calibration curve. Samples that had HPRT1 mRNA < 4000 copies were excluded for this study. Statistical analyses

Statistical analyses were performed with SPSS® version 20.0. Two-sided P values of < 0.05 were considered to indicate statistical significance. For a normal distribution expression data were log transformed and an univariate analysis was performed using forward logistic regression to determine whether the single biomarkers had significant predictive value (p<0.05) for diagnosis of PrCa_total and/or Sign-PrCa. The Odds Ratio's (O.R.) and corresponding 95% Confidence Intervals (CI) were determined.

To determine whether the markers had independent predictive value and had additional value to each other a multivariate analysis was performed using forward logistic regression. The best combinations of biomarkers for the prediction of PrCa or Sign-PrCa were identified.

To visualize the performance of the selected biomarkers in the absence of an arbitrary cut-off value, the data were summarized using a Receiver Operating Characteristic (ROC) curve. In a ROC curve, the true positive rate to detect prostate cancer (Sensitivity) is plotted in function of the false positive rate (i.e. positives in the no-PrCa group) (1 -Specificity) for different cut-off points of a parameter. Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. The area under the ROC curve is a measure of how well a parameter can distinguish between two groups, e.g. (PrCa_total versus no-PrCa). When the variable under study cannot distinguish between the two groups, i.e. in case there is no difference between the two distributions, the area will be equal to 0.5 (the ROC curve will coincide with the diagonal). A test with perfect discrimination (no overlap in the two distributions) has a ROC curve that passes through the upper left corner (100% sensitivity, 100% specificity).

Therefore the closer the ROC curve is to the upper left corner, the higher the overall accuracy of the test.

Results

In total, 443 patients were enrolled in this prospective multicenter study. Samples with HPRT1 mRNA < 4000 copies were excluded (n=85). This resulted in 358 evaluable samples. In this cohort, 157 patients had prostate cancer in their biopsies. Of all the prostate cancers found (PrCa_total), 93 (59%) had a Gleason score >=7 and 64 (41%) had a Gleason score <=6.

Furthermore, of all the prostate cancers found (PrCa_total), 118 (75%) could be classified as significant prostate cancer (Sign-PrCa), i.e. a Gleason Score of >=7 and/or a percentage biopsy positive cores >=33% and/or a clinical stage >=T2 (Epstein criteria)

Table 1A shows the univariate forward logistic regression data with the 10 biomarkers for diagnosis of PrCa. The P-values and Odds Ratios (O.R.) with corresponding 95% Confidence Intervals (CI) are presented. mRNA levels of HOXC4, HOXC6, DLX1, TDRD1, NKAINl, PTPRT, CGREFl, GLYATLl and PPFIA2 were significantly higher in patients with PrCa (PrCa_total) compared to patients without PrCa, whereas RRM2 was not.

Table 1A: Univariate forward logistic regression data with the 10 biomarkers for diagnosis of PrCa.

Table IB shows the univariate forward logistic regression data with the 10 biomarkers for diagnosis of Sign-PrCa. mRNA levels of HOXC4, HOXC6, DLX1, TDRD1, NKAINl, PTPRT, CGREFl, GLYATLl and PPFIA2 were significantly higher in patients with Sign-PrCa compared to the rest (patients without PrCa or insignificant PrCa), whereas RRM2 was not.

Table IB: Univariate forward logistic regression data with the 10 biomarkers for diagnosis of Sign-PrCa.

95% C.I.

P-value OR Lower Upper

LN_HOXC4 6.7E-05 1.34 1.16 1.55

LN_HOXC6 4.7E-10 1.65 1.41 1.94

LN_DLX1 1.3E-11 1.36 1.24 1.48

LN_TDRD1 1.0E-09 1.31 1.20 1.43

LN_NKAIN1 6.1E-05 1.26 1.13 1.42

LN_PTPRT 4.8E-08 1.24 1.15 1.34

LN_RRM2 5.9E-02 1.19 0.99 1.42

LN_CGREF1 2.4E-04 1.28 1.12 1.47

LN_GLYATL1 5.0E-03 1.30 1.08 1.56

LN_PPFIA2 2.4E-05 1.20 1.10 1.30 Table 2A shows the multivariate analysis data with forward logistic regression nosis of PrCa. Only DLXl and HOXC6 had independent additional predictive value for nosing PrCa (P- value <0.05) and are stepwise added to the model.

Table 2A: Multivariate analysis data with forward logistic regression for diagnosis of PrCa.

Variables in the Equation Variables not in the Equation

P-value

Step 2 LN HOXC4 0.40

LN TDRDl 0.20

LN _PPFIA 0.40

LN GLYATLl 0.33

LN RRM2 0.20

LN CGREF1 0.06

LN NKAINl 0.60

LN PTPRT 0.72

LN RRM2 0.20

Table 2B shows the multivariate analysis data with forward logistic regression for diagnosis of Sign-PrCa. Only DLXl, HOXC6 and TDRDl had independent additional predictive value for diagnosing Sign-PrCa (P-value <0.05) and are stepwise added to the model.

Table 2B: multivariate analysis data with forward logistic regression for diagnosis of

Sign-PrCa.

Variables in the Equation Variables not in the Equation

95% C.I.

P-value OR Lower Upper P-value

Step 1 LN_DLX1 <0.001 1.37 1.25 1.49 Step 3 LN_HOXC4 0.75

Constant <0.001 0.27 LN_GLYATL1 0.18

Step 2 LN_HOXC6 <0.001 1.43 1.21 1.69 LN_NKAIN1 0.44

LN_DLX1 <0.001 1.26 1.14 1.40 LN_PPFIA2 0.72

Constant <0.001 0.03 LN_PTPRT 0.49

Step 3 LN_HOXC6 <0.001 1.36 1.15 1.62 LN_RRM2 0.15

LN_DLX1 0,001 1.20 1.08 1.34 LN_CGREF1 0.10

LN_TDRD1 0,013 1.14 1.03 1.26

Constant <0.001 0.03 HOXC4 and HOXC6 are transcribed from the same transcriptional unit. The expression patterns of both genes show high correlation and both are significant diagnostic and prognostic biomarkers. In the multivariate logistic regression with the 10 biomarkers and with both genes included HOXC4 is not an independent predictor. HOXC6 performs better for diagnosing PrCa_total and Sign-PrCa than HOXC4 however, the differences are very small and these markers can be interexchanged in many cases. When a multivariate analysis is performed without either HOXC4 or HOXC6, of all other 8 biomarkers again only DLX1 and/or TDRD1 have independent additional value and are added to the model for diagnosing PrCa_total and Sign-PrCa. Therefore it was decided to perform further detailed data analysis for the four genes HOXC4, HOXC6, DLX1 and TDRD1 and combinations thereof.

In Tables 3A and 3B, the copy numbers, copy number ranges and fold-changes between the groups of the individual genes of interest are shown for no PrCa, and PrCa_total (diagnosis) and for Sign-PrCa and the rest (prognosis) for the cohort of 358 urinary sediments.

Table 3A: The copy numbers, copy number ranges and fold-changes between the groups of the individual genes.

Rest*= neg. biopsy and insign PrCa (GS<7, biopsy pos. cores <33 and < T2 stage)

To visualize the performance of the four selected biomarkers to discriminate PrCa_total from no-PrCa and to discriminate Sign-PrCa from the rest {i.e. negative biopsy and insignificant PrCa) the data were summarized using a Receiver Operating Characteristic (ROC) curve. The ROC curves were made for the four single biomarkers and for the combinations of these biomarkers. In a Receiver under Operation (ROC)-curve, the diagnostic potential of HOXC4, HOXC6, DLX1 and TDRD1 expression in the cohort of 358 urinary sediments to discriminate no PrCa from PrCa_total is visualized in Figure 1. The area under the curve (AUC) for HOXC4 is 0.69 (95% CI: 0.63-0.74), for HOXC6 is 0.72 (95% CI: 0.67-0.77), for DLX1 is 0.65 (95%CI: 0.59-0.71) and for TDRD1 is 0.66 (95% CI: 0.60-0.72).

In a Receiver under Operation (ROC)-curve, the prognostic potential of HOXC4, HOXC6, DLX1 and TDRD1 expression in urinary sediments to discriminate Sign-PrCa from the rest (i.e. insignificant PrCa and negative biopsies) is visualized in Figure 2. The area under the curve (AUC) for HOXC4 is 0.69 (95% CI: 0.63-0.75), for HOXC6 is 0.73 (95% CI:0.67-0.79), for DLX1 is 0.68 (95% CI: 0.62-0.74) and for TDRD1 is 0.71 (95% CI: 0.65-0.77).

The diagnostic potential of combinations of HOXC4, HOXC6, DLX1 and TDRD1 for the expression in the cohort of 358 urinary sediments to discriminate no PrCa from PrCa_total is visualized in a Receiver under Operation (ROC)-curve in Figure 3. The area under the curve (AUC) for HOXC6 expression is 0.719 (95% CI: 0.67-0.77), for the combination of HOXC6 with DLX1 is 0.726 (95% CI:0.67-0.78), for the combination of HOXC6, DLX1 and HOXC4 expression is 0.733 (95% CI: 0.68-0.79) and for the combination of HOXC6, DLX1, HOXC4 and TDRD1 is 0.732 (95% CI: 0.68-0.78).

To discriminate no PrCa from PrCa_total (diagnosis) in urinary sediments, at a specificities of 70%, 80% and 90% cut-off values were extrapolated from the ROC-curves and the sensitivity, positive predictive value (PPV), negative predictive value (NPV) was calculated for HOXC6 and for the combinations with HOXC4, DLX1 and TDRD1. Furthermore the number of patients with prostate cancer detected by the markers was determined as well. The results are summarized in Table 4A.

Table 4A: Discrimination of no PrCa from PrCa_total (diagnosis) in urinary sediments

PCa = number of detected cancer patients The prognostic potential of combinations of HOXC4, HOXC6, DLXl and TDRDl for the expression in the cohort of 358 urinary sediments to discriminate Sign-PrCa from the rest (insignificant PrCa and negative biopsies)are visualized in a Receiver under Operation (ROC)- curve in Figure 4. The area under the curve (AUC) for HOXC6 expression is 0.731 (95% CI: 0.67- 0.79), for the combination of HOXC6 with DLXl is 0.745 (95% CL0.69-0.80), for the

combination of HOXC6, DLXl and HOXC4 is 0.750 (95% CI: 0.69-0.81) and for the combination of HOXC6, DLXl, HOXC4 and TDRDl expression is 0.753 (95% CI: 0.70-0.81).

To discriminate Sign-PrCa from the rest (prognosis) in urinary sediments, at a specificities of 70%, 80% and 90% cut-off values were extrapolated from the ROC-curves and the sensitivity, positive predictive value (PPV), negative predictive value (NPV) were calculated for HOXC6 and for the combinations with HOXC4, DLXl and TDRDl. Furthermore the number of significant prostate cancers detected was determined as well. The results are summarized in Table 4B.

Table 4B: Discrimination of Sign-PrCa from the rest (prognosis) in urinary sediments

PCa = number of detected cancer patients

In a Receiver under Operation (ROC)-curve, the diagnostic potential of the combination of HOXC6, DLXl, HOXC4 and TDRDl expression and the expression of PCA3 in urinary sediments and the serum PSA value to discriminate no PrCa from PrCa_total is visualized in Figure 5. The area under curve (AUC) for the combination of HOXC6, DLXl,HOXC4 and TDRDl expression is 0.732 (95% CI: 0.68-0.78), for the expression of PCA3 is 0,716 (95% CI: 0.66-0.77) and for serum PSA is 0,658 (95% CI: 0.60-0.72).

In a Receiver under Operation (ROC)-curve, the prognostic potential of the combination of HOXC6 with DLXl, HOXC4 and TDRDl expression, the expression of PC A3 in urinary sediments and the serum PSA value to discriminate Sign-PrCa from the rest (insignificant PrCa and negative biopsies) is visualized in Figure 6. The area under curve (AUC) for the combination of HOXC6, DLXl, HOXC4 and TDRDl expression is 0.753 (95% CI: 0.70-0.81), for the expression of PCA3 is 0,706 (95% CI: 0.65-0.76) and for serum PSA is 0,693 (95% CI: 0.63- 0.75).

Discussion

The present example shows that the individual selected genes (HOXC4, HOXC6, DLX1 and TDRD1) each show overexpression in prostate cancer versus no-prostate cancer (diagnosis) and overexpression in Sign-PrCa versus the rest (prognosis). Especially TDRD1 and DLX1 show in both situations a high fold change difference between the groups.

Based on the AUC of the ROC curves for the single biomarkers, HOXC6 shows the best results for diagnosing prostate cancer (PrCa_total) (Figure 1). When combined with DLX1, HOXC4 and or TDRD1 the overall diagnostic performance is improved. This does not mean that this combination is the best under all conditions. Depending on where the biomarkers will be used for (screening, reduction of biopsies) a high specificity or a high sensitivity is desired. If a higher sensitivity is desired, e.g. at a lower specificity of 80%, the combination of HOXC4, DLX1 and TDRD1 performs best (see Table 4A).

At a specificity of 70%, HOXC6 detects 97 of the prostate cancers (sensitivity of 62%), when combined with HOXC4, DLX1 and TDRD1 102 prostate cancers are detected (sensitivity of 65%). If a higher specificity is required, e.g. at 80%, the combination of HOXC4, DLX1 and TDRD1 performs best; 83 cancers are detected (sensitivity 53%) and this is a significant improvement compared to the number of cancers detected by serum PSA (65) and mPCA3 (69). These tests have a sensitivity of only 41% and 44% respectively at a specificity of 80% (Table 4A).

For the detection of significant prostate cancer (prognosis), from the 4 single biomarkers HOXC6 shows the best results based on the AUC of the ROC curves (Figure 6).

When combined with DLX1, HOXC4 and or TDRD1 the prognostic performance is improved, especially at a high specificity.

At a specificity of 90%, HOXC6 detects 48 of the significant prostate cancers (sensitivity of 41%), when combined with HOXC4, DLX1 and TDRD1 58 significant prostate cancers are detected (sensitivity of 50%). This is a significant improvement compared to the number of cancers detected by serum PSA (43) and mPCA3 (29). These tests have a sensitivity of only 36% and 25% respectively at a specificity of 90% (Table 4B).

For a urologist the probability of having significant prostate cancer should be as high as possible. Therefore the specificity and PPV are very important for treatment decision making. At a high specificity of 90%, the PPV of the four gene panel is 71%. This indicates that a man with a positive test for the four gene panel has a probability of 71% for having significant prostate cancer. This is significantly higher than the PPV for serum PSA (63%) and mPCA3 (55%).

Conclusion

As demonstrated above, the present molecular markers, or biomarkers, for prostate cancer provide, in combination, methods and means allowing discrimination between prostate cancer and no-prostate cancer and allowing detecting significant prostate cancer from the rest (insignificant PrCa and negative biopsies) with improved sensitivity, specificity, PPV and NPV, especially when compared with presently available biomarkers such as the serum PSA and mPCA3.

SEQUENCE LISTING

<110> NovioGendix Research B.v. <120> COMBINATIONS OF MOLECULAR MARKERS IN PROSTATE CANCER PROVIDING A DIAGNOSTIC TOOL WITH IMPROVED SENSITIVITY/SPECIFICITY

<130> 4/2QK29/12P <150> PCT/EP2013/066889

<151> 2013-08-13

<160> 14 <170> Patentln version 3.5

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<223> amino acid sequence of the variant 1 of the HOXC4 gene

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Met lie Met Ser Ser Tyr Leu Met Asp Ser Asn Tyr lie Asp Pro Lys

1 5 10 15

Phe Pro Pro Cys G ^~ lu G ^~ lu Tyr Ser Gin Asn Ser Tyr lie Pro G ^~ lu His

20 25 30

Ser Pro Glu Tyr Tyr Gly Arg Thr Arg Glu Ser Gly Phe Gin His His

35 40 45

His Gin Glu Leu Tyr Pro Pro Pro Pro Pro Arg Pro Ser Tyr Pro Glu

50 55 60

Arg Gin Tyr Ser Cys Thr Ser Leu Gin Gly Pro Gly Asn Ser Arg Gly

65 70 75 80

His Gly Pro Ala Gin Ala Gly His His His Pro Glu Lys Ser Gin Ser

85 90 95

Leu Cys Glu Pro Ala Pro Leu Ser Gly Ala Ser Ala Ser Pro Ser Pro

100 105 110

Ala Pro Pro Ala Cys Ser Gin Pro Ala Pro Asp His Pro Ser Ser Ala

115 120 125

Ala Ser Lys Gin Pro lie val Tyr Pro Trp Met Lys Lys lie His val

130 135 140

Ser Thr val Asn Pro Asn Tyr Asn Gly Gly Glu Pro Lys Arg Ser Arg

145 150 155 160

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165 170 175

Tyr Asn Arg Tyr Leu Thr Arg Arg Arg Arg lie Glu lie Ala His Ser

180 185 190

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Met Lys Trp Lys Lys Asp His Arg Leu Pro Asn Thr Lys val Arg Ser

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Gly Thr Ser Glu Asp His Ser Gin Ser Ala Thr Pro Pro Glu Gin Gin

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260

<210> 3

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agaaaaacga caaagcgaga aaaattattt tccactccag aaattaatga tcatgagctc 60 gtatttgatg gactctaact acatcgatcc gaaatttcct ccatgcgaag aatattcgca 120 aaatagctac atccctgaac acagtccgga atattacggc cggaccaggg aatcgggatt 180 ccagcatcac caccaggagc tgtacccacc accgcctccg cgccctagct accctgagcg 240 ccagtatagc tgcaccagtc tccaggggcc cggcaattcg cgaggccacg ggccggccca 300 ggcgggccac caccaccccg agaaatcaca gtcgctctgc gagccggcgc ctctctcagg 360 cgcctccgcc tccccgtccc cagccccgcc agcctgcagc cagccagccc ccgaccatcc 420 ctccagcgcc gccagcaagc aacccatagt ctacccatgg atgaaaaaaa ttcacgttag 480 cacggtgaac cccaattata acggagggga acccaagcgc tcgaggacag cctatacccg 540 gcagcaagtc ctggaattag agaaagagtt tcattacaac cgctacctga cccgaaggag 600 aaggatcgag atcgcccact cgctgtgcct ctctgagagg cagatcaaaa tctggttcca 660 aaaccgtcgc atgaaatgga agaaggacca ccgactcccc aacaccaaag tcaggtcagc 720 acccccggcc ggcgctgcgc ccagcaccct ttcggcagct accccgggta cttctgaaga 780 ccactcccag agcgccacgc cgccggagca gcaacgggca gaggacatta ccaggttata 840 aaacataact cacacccctg cccccacccc atgcccccac cctcccctca cacacaaatt 900 gactcttatt tatagaattt aatatatata tatatatata tatatatagg ttcttttctc 960 tcttcctctc accttgtccc ttgtcagttc caaacagaca aaacagataa acaaacaagc 1020 cccctgccct cctctccctc ccactgttaa ggaccctttt aagcatgtga tgttgtctta 1080 gcatggtacc tgctgggtgt ttttttttaa aaggccattt tggggggtta tttatttttt 1140 aagaaaaaaa gctgcaaaaa ttatatattg caaggtgtga tggtctggct tgggtgaatt 1200 tcaggggaaa tgaggaaaag aaaaaaggaa agaaatttta aagccaattc tcatccttct 1260 cctcctcctc cttccccccc tctttcctta ggccttttgc attgaaaatg caccagggga 1320 ggttagtgag ggggaagtca ttttaaggag aacaaagcta tgaagttctt ttgtattatt 1380 gttggggggg ggtgtgggag gagagggggc gaagacagca gacaaagcta aatgcatctg 1440 gagagcctct cagagctgtt cagtttgagg agccaaaaga aaatcaaaat gaactttcag 1500 ttcagagagg cagtctatag gtagaatctc tccccacccc tatcgtggtt attgtgtttt 1560 tggactgaat ttacttgatt attgtaaaac ttgcaataaa gaattttagt gtcgatgtga 1620 aatgccccgt gatcaataat aaaccagtgg atgtgaatta gttttaaaaa aaaaaaaaaa 1680 aaaaaaaaa 1689

<210> 4

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<223> amino acid sequence of the variant 2 of the HOXC4 gene

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<400> 4

Met lie Met Ser Ser Tyr Leu Met Asp Ser Asn Tyr lie Asp Pro Lys

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Phe Pro Pro Cys G ^~ lu Glu Tyr Ser Gin Asn Ser Tyr lie Pro G ^~ lu His

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35 40 45

His Gin Glu Leu Tyr Pro Pro Pro Pro Pro Arg Pro Ser Tyr Pro Glu

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Arg Gin Tyr Ser Cys Thr Ser Leu Gin Gly Pro Gly Asn Ser Arg Gly

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His Gly Pro Ala Gin Ala Gly His His His Pro Glu Lys Ser Gin Ser

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100 105 110

Ala Pro Pro Ala Cys Ser Gin Pro Ala Pro Asp His Pro Ser Ser Ala

115 120 125

Ala Ser Lys Gin Pro lie val Tyr Pro Trp Met Lys Lys lie His val

130 135 140

Ser Thr val Asn Pro Asn Tyr Asn Gly Gly Glu Pro Lys Arg Ser Arg

145 150 155 160

Thr Ala Tyr Thr Arg Gin Gin val Leu Glu Leu Glu Lys Glu Phe His

165 170 175

Tyr Asn Arg Tyr Leu Thr Arg Arg Arg Arg lie Glu lie Ala His Ser

180 185 190

Leu Cys Leu Ser Glu Arg Gin lie Lys lie Trp Phe Gin Asn Arg Arg

195 200 205

Met Lys Trp Lys Lys Asp His Arg Leu Pro Asn Thr Lys val Arg Ser

210 215 220

Ala Pro Pro Ala Gly Ala Ala Pro Ser Thr Leu Ser Ala Ala Thr Pro

225 230 235 240

Gly Thr Ser Glu Asp His Ser Gin Ser Ala Thr Pro Pro Glu Gin Gin

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Arg Ala Glu Asp lie Thr Arg Leu

260

<210> 5

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NP_004494.1)

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<210> 6

<211> 235

<212> PRT

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> amino acid sequence of the variant 1 of the HOXC6 gene

(NM_004503 . 3 , NP_004494 . 1)

<400> 6

Met Asn Ser Tyr Phe Thr Asn Pro Ser Leu Ser Cys His Leu Ala Gly

1 5 10 15

Gly Gin Asp val Leu Pro Asn val Ala Leu Asn Ser Thr Ala Tyr Asp

20 25 30

Pro val Arg His Phe Ser Thr Tyr Gly Ala Ala val Ala Gin Asn Arg

35 40 45

lie Tyr Ser Thr Pro Phe Tyr Ser Pro Gin Glu Asn val val Phe Ser

50 55 60

Ser Ser Arg Gly Pro Tyr Asp Tyr Gly Ser Asn Ser Phe Tyr Gin Glu

65 70 75 80

Lys Asp Met Leu Ser Asn Cys Arg Gin Asn Thr Leu Gly His Asn Thr

85 90 95

Gin Thr Ser lie Ala Gin Asp Phe Ser Ser Glu Gin Gly Arg Thr Ala

100 105 110

Pro Gin Asp Gin Lys Ala Ser lie Gin lie Tyr Pro Trp Met Gin Arg 115 120 125

Met Asn Ser His Ser Gly val Gly Tyr Gly Ala Asp Arg Arg Arg Gly

130 135 140

Arg Gin lie Tyr Ser Arg Tyr Gin Thr Leu Glu Leu Glu Lys Glu Phe

145 150 155 160

His Phe Asn Arg Tyr Leu Thr Arg Arg Arg Arg lie Glu lie Ala Asn

165 170 175

Ala Leu Cys Leu Thr Glu Arg Gin lie Lys lie Trp Phe Gin Asn Arg

180 185 190

Arg Met Lys Trp Lys Lys Glu Ser Asn Leu Thr Ser Thr Leu Ser Gly

195 200 205

Gly Gly Gly Gly Ala Thr Ala Asp Ser Leu Gly Gly Lys Glu Glu Lys

210 215 220

Arg Glu Glu Thr Glu Glu Glu Lys Gin Lys Glu

225 230 235

<210> 7

<211> 2072

<212> DNA

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> cDNA sequence of the variant 2 of the HOXC6 gene (NM_153693 . 3 , NP_710160 . 1)

<400> 7

ttattgtggt ttgtccgttc cgagcgctcc gcagaacagt cctccctgta agagcctaac 60 cattgccagg gaaacctgcc ctgggcgctc ccttcattag cagtattttt tttaaattaa 120 tctgattaat aattattttt cccccattta attttttttc ctcccaggtg gagttgccga 180 agctgggggc agctggggag ggtggggatg ggaggggaga gacagaagtt gagggcatct 240 ctctcttcct tcccgaccct ctggccccca aggggcagga ggaatgcagg agcaggagtt 300 gagcttggga gctgcagatg cctccgcccc tcctctctcc caggctcttc ctcctgcccc 360 cttcttgcaa ctctccttaa ttttgtttgg cttttggatg attataatta tttttatttt 420 tgaatttata taaagtatat gtgtgtgtgt gtggagctga gacaggctcg gcagcggcac 480 agaatgaggg aagacgagaa agagagtggg agagagagag gcagagaggg agagagggag 540 agtgacagca gcgctcggac gtcctcccca acgtcgccct caattccacc gcctatgatc 600 cagtgaggca tttctcgacc tatggagcgg ccgttgccca gaaccggatc tactcgactc 660 ccttttattc gccacaggag aatgtcgtgt tcagttccag ccgggggccg tatgactatg 720 gatctaattc cttttaccag gagaaagaca tgctctcaaa ctgcagacaa aacaccttag 780 gacataacac acagacctca atcgctcagg attttagttc tgagcagggc aggactgcgc 840 cccaggacca gaaagccagt atccagattt acccctggat gcagcgaatg aattcgcaca 900 gtggggtcgg ctacggagcg gaccggaggc gcggccgcca gatctactcg cggtaccaga 960 ccctggaact ggagaaggaa tttcacttca atcgctacct aacgcggcgc cggcgcatcg 1020 agatcgccaa cgcgctttgc ctgaccgagc gacagatcaa aatctggttc cagaaccgcc 1080 ggatgaagtg gaaaaaagaa tctaatctca catccactct ctcggggggc ggcggagggg 1140 ccaccgccga cagcctgggc ggaaaagagg aaaagcggga agagacagaa gaggagaagc 1200 agaaagagtg accaggactg tccctgccac ccctctctcc ctttctccct cgctccccac 1260 caactctccc ctaatcacac actctgtatt tatcactggc acaattgatg tgttttgatt 1320 ccctaaaaca aaattaggga gtcaaacgtg gacctgaaag tcagctctgg accccctccc 1380 tcaccgcaca actctctttc accacgcgcc tcctcctcct cgctcccttg ctagctcgtt 1440 ctcggcttgt ctacaggccc ttttccccgt ccaggccttg ggggctcgga ccctgaactc 1500 agactctaca gattgccctc caagtgagga cttggctccc ccactccttc gacgccccca 1560 cccccgcccc ccgtgcagag agccggctcc tgggcctgct ggggcctctg ctccagggcc 1620 tcagggcccg gcctggcagc cggggagggc cggaggccca aggagggcgc gccttggccc 1680 cacaccaacc cccagggcct ccccgcagtc cctgcctagc ccctctgccc cagcaaatgc 1740 ccagcccagg caaattgtat ttaaagaatc ctgggggtca ttatggcatt ttacaaactg 1800 tgaccgtttc tgtgtgaaga tttttagctg tatttgtggt ctctgtattt atatttatgt 1860 ttagcaccgt cagtgttcct atccaatttc aaaaaaggaa aaaaaagagg gaaaattaca 1920 aaaagagaga aaaaaagtga atgacgtttg tttagccagt aggagaaaat aaataaataa 1980 ataaatccct tcgtgttacc ctcctgtata aatccaacct ctgggtccgt tctcgaatat 2040 ttaataaaac tgatattatt tttaaaactt ta 2072

<210> 8

<211> 153

<212> PRT

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> mi no acid sequence of the variant 2 of the HOXC6 gene

(NM_153693 . 3 , NP_710160. 1)

<400> 8

Met Leu Ser Asn Cys Arg Gin Asn Thr Leu Gly His Asn Thr Gin Thr

1 5 10 15

Ser lie Ala Gin Asp Phe Ser Ser Glu Gin Gly Arg Thr Ala Pro Gin

20 25 30

Asp Gin Lys Ala Ser lie Gin lie Tyr Pro Trp Met Gin Arg Met Asn

35 40 45

Ser His Ser Gly val Gly Tyr Gly Ala Asp Arg Arg Arg Gly Arg Gin

50 55 60

lie Tyr Ser Arg Tyr Gin Thr Leu Glu Leu Glu Lys Glu Phe His Phe

65 70 75 80

Asn Arg Tyr Leu Thr Arg Arg Arg Arg lie Glu lie Ala Asn Ala Leu

85 90 95

Cys Leu Thr Glu Arg Gin lie Lys lie Trp Phe Gin Asn Arg Arg Met

100 105 110

Lys Trp Lys Lys Glu Ser Asn Leu Thr Ser Thr Leu Ser Gly Gly Gly

115 120 125

Gly Gly Ala Thr Ala Asp Ser Leu Gly Gly Lys Glu Glu Lys Arg Glu

130 135 140

Glu Thr Glu Glu Glu Lys Gin Lys Glu

145 150

<210> 9

<211> 2403

<212> DNA

<213> Homo sapiens

<220>

<221> misc_feature

<223> cDNA sequence of transcript variant one of the DLXl gene

(NM_178120 , NP_835221)

<400> 9

aagctttgaa ccgagtttgg ggagctcagc agcatcatgc ttagactttt caaagagaca 60 aactccattt tcttatgaat ggaaagtgaa aacccctgtt ccgcttaaat tgggttcctt 120 cctgtcctga gaaacataga gacccccaaa agggaagcag aggagagaaa gtcccacacc 180 cagaccccgc gagaagagat gaccatgacc accatgccag aaagtctcaa cagccccgtg 240 tcgggcaagg cggtgtttat ggagtttggg ccgcccaacc agcaaatgtc tccttctccc 300 atgtcccacg ggcactactc catgcactgt ttacactcgg cgggccattc gcagcccgac 360 ggcgcctaca gctcagcctc gtccttctcc cgaccgctgg gctaccccta cgtcaactcg 420 gtcagcagcc acgcatccag cccctacatc agttcggtgc agtcctaccc gggcagcgcc 480 agcctcgccc agagccgcct ggaggaccca ggggcggact cggagaagag cacggtggtg 540 gaaggcggtg aagtgcgctt caatggcaag ggaaaaaaga tccgtaaacc caggacgatt 600 tattccagtt tgcagttgca ggctttgaac cggaggttcc agcaaactca gtacctagct 660 ctgccggaga gggcggagct cgcggcctct ttgggactca cacagactca ggtcaagatc 720 tggttccaaa acaagcgatc caagttcaag aagctgatga agcagggtgg ggcggctctg 780 gagggtagtg cgttggccaa cggtcgggcc ctgtctgctg gctccccacc cgtgccgccc 840 ggctggaacc ctaactcttc atccgggaag ggctcaggag gaaacgcggg ctcctatatc 900 cccagctaca catcgtggta cccttcagcg caccaagaag ctatgcagca accccaactt 960 atgtgaggtt gcccgcccgt ctccttcttg tctccccggc ccaggtccct cccgcctcca 1020 ggtccatcca tcccgtccgg aaaagaagga cccagaggga agaaggaaca gtggaggcgg 1080 gacgccctcc atctcctcgg agccccgcga ggtccggccc agcaacttcc cggcatccgc 1140 gctctagcct gaaccctggc ctgggccgag cagtggcagc agagagtggc ctcggaggga 1200 agccactgcc acctgagaca gcccaagcag caagataaac ccgctccacc cgacccgccg 1260 accttcagct ttgtgggact atcaggaaaa aacaaaacaa aaacaaaatg tagaaaaagc 1320 aaaagctctt ttctgtcctg tcagtctcct gtctcctttt gctctgtctg tgcgctggta 1380 aagtccaggt cctcatccgt ccgctgtcct cattctgcgg cctcagcaaa aagccacaag 1440 gtctgagcgg cccgggtcct gccgggctga ccatctccgg atcctgggac actctgcctg 1500 accatctgtg tagctggtgt gggaatctgg gggcattgga gggagggggt tttatttatt 1560 gagaaatgga cttcgcctga ggctgtttgc caattcaggg ttctgctggg cgcaaggaac 1620 gcactgttca aacgcactgt ttactttaag cgcacgggga gaaacgaata aggaggacgt 1680 ggtgattttt aatttataca gtaacttttg tacttctctg gtatggagag tttggagccg 1740 aatgatttgc attttttaca tgtccgacat tatttaataa ataattttta aaagaaaaga 1800 acgataaatg aagccaacat gattttctca tttcgggagg aactctgttg cttcgcctgg 1860 acaagaagga aaatgctgat ttcctccttg ggtagaaaga gggagcgagg gcaaatgggg 1920 agtagagaga aaacaggcga gaacaagcac tctaattcca gtgggcttta aaataagaca 1980 aaatcagctt tacaacaatc cctagaggct cgaccacaga ataatgccag tcaccaccct 2040 gaacgcacaa tctccagtgc aggatctaat gactgtacat attattgtta ttattattat 2100 tgttattatt gttgttctgt aaacatgttg cacaagctta gcctttttgc gttctgttgt 2160 gtgtggctgt aaaaccccat gctttgtgaa atgagaatct tgacattttt cttgtgaaat 2220 ttggaaaatg tgatcaattg aaatcaactg tgttttgtgt tctctatgtc aaagtttagt 2280 tttatattga gaatgttaac ttattgcttt gtatcttggg aaaaaaactt tgtaaataag 2340 ttataaagtt tctttgagac agtaaaatta tgatttcttg aaaaaaaaaa aaaaaaaaaa 2400 aaa 2403

<210> 10

<211> 255

<212> PRT

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> amino acid sequence of ranscnpt variant one of the DLXl gene (NM_178120 , NP_835221)

<400> 10

Met Thr Met Thr Thr Met Pro Gl Ser Leu Asn Ser Pro val Ser Gly

1 5 10 15 Lys Ala val Phe Met Glu Phe Gly Pro Pro Asn Gin Gin Met Ser Pro

20 25 30

Ser Pro Met Ser His Gly His Tyr Ser Met His Cys Leu His Ser Ala

35 40 45

Gly His Ser Gin Pro Asp Gly Ala Tyr Ser Ser Ala Ser Ser Phe Ser

50 55 60

Arg Pro Leu Gly Tyr Pro Tyr val Asn Ser val Ser Ser His Ala Ser

65 70 75 80

Ser Pro Tyr lie Ser Ser val Gin Ser Tyr Pro Gly Ser Ala Ser Leu

85 90 95

Ala Gin Ser Arg Leu Glu Asp Pro Gly Ala Asp Ser Glu Lys Ser Thr

100 105 110

val val Glu Gly Gly Glu val Arg Phe Asn Gly Lys Gly Lys Lys lie

115 120 125

Arg Lys Pro Arg Thr lie Tyr Ser Ser Leu Gin Leu Gin Ala Leu Asn

130 135 140

Arg Arg Phe Gin Gin Thr Gin Tyr Leu Ala Leu Pro Glu Arg Ala Glu

145 150 155 160

Leu Ala Ala Ser Leu Gly Leu Thr Gin Thr Gin val Lys lie Trp Phe

165 170 175

Gin Asn Lys Arg Ser Lys Phe Lys Lys Leu Met Lys Gin Gly Gly Ala

180 185 190

Ala Leu Glu Gly Ser Ala Leu Ala Asn Gly Arg Ala Leu Ser Ala Gly

195 200 205

Ser Pro Pro val Pro Pro Gly Trp Asn Pro Asn Ser Ser Ser Gly Lys

210 215 220

Gly Ser Gly Gly Asn Ala Gly Ser Tyr lie Pro Ser Tyr Thr Ser Trp

225 230 235 240

Tyr Pro Ser Ala His Gin Glu Ala Met Gin Gin Pro Gin Leu Met

245 250 255

<210> 11

<211> 2203

<212> DNA

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> cDNA sequence of transcript variant two of the DLXl gene

(NM_001038493 . 1 , NP_001033582 . 1)

<400> 11

aagctttgaa ccgagtttgg ggagctcagc agcatcatgc ttagactttt caaagagaca 60 aactccattt tcttatgaat ggaaagtgaa aacccctgtt ccgcttaaat tgggttcctt 120 cctgtcctga gaaacataga gacccccaaa agggaagcag aggagagaaa gtcccacacc 180 cagaccccgc gagaagagat gaccatgacc accatgccag aaagtctcaa cagccccgtg 240 tcgggcaagg cggtgtttat ggagtttggg ccgcccaacc agcaaatgtc tccttctccc 300 atgtcccacg ggcactactc catgcactgt ttacactcgg cgggccattc gcagcccgac 360 ggcgcctaca gctcagcctc gtccttctcc cgaccgctgg gctaccccta cgtcaactcg 420 gtcagcagcc acgcatccag cccctacatc agttcggtgc agtcctaccc gggcagcgcc 480 agcctcgccc agagccgcct ggaggaccca ggtcaagatc tggttccaaa acaagcgatc 540 caagttcaag aagctgatga agcagggtgg ggcggctctg gagggtagtg cgttggccaa 600 cggtcgggcc ctgtctgctg gctccccacc cgtgccgccc ggctggaacc ctaactcttc 660 atccgggaag ggctcaggag gaaacgcggg ctcctatatc cccagctaca catcgtggta 720 cccttcagcg caccaagaag ctatgcagca accccaactt atgtgaggtt gcccgcccgt 780 ctccttcttg tctccccggc ccaggtccct cccgcctcca ggtccatcca tcccgtccgg 840 aaaagaagga cccagaggga agaaggaaca gtggaggcgg gacgccctcc atctcctcgg 900 agccccgcga ggtccggccc agcaacttcc cggcatccgc gctctagcct gaaccctggc 960 ctgggccgag cagtggcagc agagagtggc ctcggaggga agccactgcc acctgagaca 1020 gcccaagcag caagataaac ccgctccacc cgacccgccg accttcagct ttgtgggact 1080 atcaggaaaa aacaaaacaa aaacaaaatg tagaaaaagc aaaagctctt ttctgtcctg 1140 tcagtctcct gtctcctttt gctctgtctg tgcgctggta aagtccaggt cctcatccgt 1200 ccgctgtcct cattctgcgg cctcagcaaa aagccacaag gtctgagcgg cccgggtcct 1260 gccgggctga ccatctccgg atcctgggac actctgcctg accatctgtg tagctggtgt 1320 gggaatctgg gggcattgga gggagggggt tttatttatt gagaaatgga cttcgcctga 1380 ggctgtttgc caattcaggg ttctgctggg cgcaaggaac gcactgttca aacgcactgt 1440 ttactttaag cgcacgggga gaaacgaata aggaggacgt ggtgattttt aatttataca 1500 gtaacttttg tacttctctg gtatggagag tttggagccg aatgatttgc attttttaca 1560 tgtccgacat tatttaataa ataattttta aaagaaaaga acgataaatg aagccaacat 1620 gattttctca tttcgggagg aactctgttg cttcgcctgg acaagaagga aaatgctgat 1680 ttcctccttg ggtagaaaga gggagcgagg gcaaatgggg agtagagaga aaacaggcga 1740 gaacaagcac tctaattcca gtgggcttta aaataagaca aaatcagctt tacaacaatc 1800 cctagaggct cgaccacaga ataatgccag tcaccaccct gaacgcacaa tctccagtgc 1860 aggatctaat gactgtacat attattgtta ttattattat tgttattatt gttgttctgt 1920 aaacatgttg cacaagctta gcctttttgc gttctgttgt gtgtggctgt aaaaccccat 1980 gctttgtgaa atgagaatct tgacattttt cttgtgaaat ttggaaaatg tgatcaattg 2040 aaatcaactg tgttttgtgt tctctatgtc aaagtttagt tttatattga gaatgttaac 2100 ttattgcttt gtatcttggg aaaaaaactt tgtaaataag ttataaagtt tctttgagac 2160 agtaaaatta tgatttcttg aaaaaaaaaa aaaaaaaaaa aaa 2203

<210> 12

<211> 129

<212> PRT

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> amino acid sequence of transcript variant two of the DLXl gene (NM_001038493 . 1 , NP_001033582 . 1)

<400> 12

Met Thr Met Thr Thr Met Pro G ^~ lu Ser Leu Asn Ser Pro val Ser Gly

1 5 10 15

Lys Ala val Phe Met Glu Phe Gly Pro Pro Asn Gin Gin Met Ser Pro

20 25 30

Ser Pro Met Ser His Gly His Tyr Ser Met His Cys Leu His Ser Ala

35 40 45

Gly His Ser Gin Pro Asp Gly Ala Tyr Ser Ser Ala Ser Ser Phe Ser

50 55 60

Arg Pro Leu Gly Tyr Pro Tyr val Asn Ser val Ser Ser His Ala Ser

65 70 75 80

Ser Pro Tyr lie Ser Ser val Gin Ser Tyr Pro Gly Ser Ala Ser Leu

85 90 95

Ala Gin Ser Arg Leu Glu Asp Pro Gly Gin Asp Leu val Pro Lys Gin

100 105 110

Ala lie Gin val Gin Glu Ala Asp Glu Ala Gly Trp Gly Gly Ser Gly 115 120 125

Gl y <210> 13

<211> 4510

<212> DNA

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> cDNA sequence of the TDRDl gene (NM_198795 . 1 , NP_942090 . 1)

<400> 13

gctgaggcca ggagggcgca ctggggattg gaggcgaggg aagtgcaggg cgcatcccag 60 gcggcagggc tcccagcatc ggcagtcgcc atcaccgcca gaccgcagag acaggttcgg 120 atccgcggtc ctcttgcctc tttccaggcc tcgatgagtg ttaaatcgcc atttaatgtg 180 atgtcaagaa ataatttgga agcacctcct tgtaagatga cagagccatt taattttgag 240 aaaaatgaaa acaagcttcc accacatgag tctttaagaa gtcctggaac acttcctaac 300 caccctaatt tcaggctgaa aagctcagag aatggaaata aaaagaacaa ttttttgctt 360 tgtgagcaaa ccaaacaata tttggctagt caggaagaca attcagtttc ttcaaacccg 420 aatggcatca acggagaagt agttggctcc aaaggagaca ggaaaaaatt gccagcagga 480 aactcagtgt caccaccaag tgctgaaagt aattcaccac ccaaagaagt gaatattaag 540 cctggaaata atgtacgtcc tgcaaaatca aaaaaactaa acaagttggt cgagaattcc 600 ttgtccataa gtaatccagg gctcttcacc tccttaggac ctcctcttcg gtccacaact 660 tgccatcgct gtggcctatt tggatcgctg aggtgctctc agtgcaagca gacctactat 720 tgctccacag catgtcaaag aagagactgg tctgcacaca gcatcgtgtg caggcctgtt 780 cagccaaatt tccacaaact tgaaaataaa tcatctattg aaacaaagga tgtggaggta 840 aacaataaga gtgactgtcc acttggagtt actaaggaaa tagccatttg ggctgagaga 900 ataatgtttt ctgatttgag aagtctacaa ctcaagaaaa ccatggaaat aaagggtacg 960 gttaccgaat tcaaacaccc aggggacttc tacgtgcagt tatattcttc agaagtttta 1020 gaatacatga accaactctc tgccagctta aaagaaacat atgcaaatgt gcatgaaaaa 1080 gactatattc ctgttaaggg ggaagtttgt attgccaagt acactgttga tcagacctgg 1140 aacagagcaa tcatacaaaa cgttgatgtg cagcaaaaga aggcacatgt cttatatatt 1200 gattatggaa atgaagaaat aattccatta aacagaattt accacctcaa caggaacatt 1260 gacttgtttc ctccttgtgc cataaagtgc tttgtagcca atgttatccc agcagaaggg 1320 aattggagca gtgattgtat caaagctact aaaccactgt taatggagca gtactgctcc 1380 ataaagattg tcgacatctt ggaagaggaa gtggttacct ttgctgtaga agttgagctg 1440 ccaaattcag gaaaactttt agaccatgtg cttatagaaa tgggatatgg cttgaaaccc 1500 agtggacaag attctaagaa ggaaaatgca gatcaaagtg atcctgaaga tgttggaaaa 1560 atgacaactg aaaacaacat tgtcgtagac aaaagtgacc taatcccaaa agtgttaact 1620 ttgaatgtag gtgatgagtt ttgtggtgtg gttgcccaca ttcaaacacc agaagacttc 1680 ttttgtcaac aactgcaaag tggccgaaag cttgctgaac ttcaggcatc ccttagcaag 1740 tactgtgatc agttgcctcc acgctctgat ttttatccag ccattggtga tatatgttgt 1800 gctcagttct cagaggatga tcagtggtac cgtgcctctg ttttggctta cgcttctgaa 1860 gaatctgtac tggtcggata tgtagattat ggaaactttg aaatccttag tttgatgaga 1920 ctttgtccca taatcccaaa gttgttggaa ttgccaatgc aagctataaa gtgtgtacta 1980 gcaggagtaa agccatcatt aggaatttgg actccagaag ctatttgtct catgaaaaaa 2040 cttgtacaga acaaaataat cacagtgaaa gtggtggaca agttggaaaa cagttccctg 2100 gtggagctta ttgataaatc cgagacgcct catgtcagtg ttagcaaagt tctcctagat 2160 gcaggctttg ctgtgggaga acagagtatg gtgacagata aacccagtga cgtgaaagaa 2220 accagtgttc ccttgggtgt ggaaggaaaa gtaaatccat tggagtggac atgggttgaa 2280 cttggtgttg accaaacagt agatgttgtg gtctgtgtga tatatagtcc tggagaattt 2340 tattgccatg tgcttaaaga ggatgcttta aagaaactca atgatttgaa caagtcatta 2400 gcagaacact gccagcagaa gttacctaat ggtttcaagg cagagatagg acaaccttgt 2460 tgtgcttttt ttgcaggtga tggtagttgg tatcgtgctt tagtcaagga aatcttacca 2520 aatggacatg ttaaagtaca ttttgtggat tatggaaaca tcgaagaagt tactgcagat 2580 gaactccgaa tgatatcatc aacattttta aaccttccct ttcagggaat acggtgccag 2640 ttagcagata tacagtctag aaacaaacat tggtctgaag aagccataac aagattccag 2700 atgtgtgttg ctgggataaa attgcaagcc agagtggttg aagtcactga aaatgggata 2760 ggagttgaac tcaccgatct ctccacttgt tatcccagaa taattagtga tgttctgatt 2820 gatgaacatc tggttttaaa atctgcttca ccacataaag acttaccaaa tgacagactt 2880 gttaataaac atgagcttca agttcatgta cagggacttc aagctacctc ttcagctgag 2940 caatggaaga cgatagaatt gccagtggat aaaactatac aagcaaatgt attagaaatc 3000 ataagcccaa acttgtttta tgctctacca aaagggatgc cagaaaatca ggaaaagctg 3060 tgcatgttga cagctgaatt attagaatac tgcaatgctc cgaaaagtcg accaccctat 3120 agaccaagaa ttggagacgc atgctgtgcc aaatacacaa gtgatgattt ttggtatcgt 3180 gcagttgttc tggggacatc agacactgat gtggaagtgc tctatgcaga ctatggaaac 3240 attgaaaccc tgcctctttg cagagtgcaa ccaatcacct ctagccacct ggcgcttcct 3300 ttccaaatta ttagatgttc acttgaagga ttaatggaat tgaatggaag ctcttctcaa 3360 ttaataataa tgctattaaa aaatttcatg ttgaatcaga atgtaatgct ttctgtgaaa 3420 ggaattacaa agaatgtcca tacagtgtca gttgagaaat gttctgagaa tgggactgtc 3480 gatgtagctg ataagctagt gacatttggt ctggcaaaaa acatcacacc tcaaaggcag 3540 agtgctttaa atacagaaaa gatgtatagg atgaattgct gctgcacaga gttacagaaa 3600 caagttgaaa aacatgaaca tattcttctc ttcctcttaa acaattcaac caatcaaaat 3660 aaatttattg aaatgaaaaa actgttaaaa aaaacagcat ctcttggagg taaaccctta 3720 tgagacagga aacagcaaag gctagcttta ggagagaaag tacagcacct ggtgttttta 3780 tttatgagaa ccttttcttt gtccactttc tctgtaatga ccttctatcc ctccgttttt 3840 gcctgcctgc cattctccta ttaggttggt ggtttttatt ttcctctaag ttccttccac 3900 caaataaata ttacgtaaaa aattcatacc aaatcaatga gaatactggc aaggaataca 3960 tagggacttt ctgctatata tgtaactttt tattacttaa aggtaccgaa ggaaggccag 4020 gtgcagtggc tcacgcccag cactttggga ggctgaggtg ggaggatccc ttgaggccag 4080 gagttcaagg ttacagtgag ctatgatagt gccactgcac tccagcctgg gtgacagatt 4140 ttgtcttaaa aaaaaaaaaa aaaaagttga tatgagtttt attttctgtc cgtttgaaat 4200 attttgtaat attccctgca ttctctgtcg tctgcctctt ccacataatg tcctttgctt 4260 tcatgtttgt tatcttcttt ttctgttcac tcagaggtca tcaatttctt tctctccgtc 4320 cttaattgga ttatttttct tttggccttt gggcacagag tctgacctct ggaccactct 4380 aactggagaa ggaactttat gttccctctc ctgctgtgtc cacaacctta gaaatctgta 4440 gctagatttt tgttgttata gatagaattt actgtttctg aaacccaaat acagttatca 4500 gtttaaggtt 4510

<210> 14

<211> 1189

<212> PRT

<213> Homo sapiens

<220>

<221> mi sc_feature

<223> amino acid sequence of the TDRDl gene (NM_198795 . 1 , NP_942090 . 1) <400> 14

Met Ser val Lys Ser Pro Phe Asn val Met Ser Arg Asn Asn Leu G ^~ lu

1 5 10 15

Ala Pro Pro Cys Lys Met Thr G ^~ lu Pro Phe Asn Phe G ^~ lu Lys Asn G ^~ lu

20 25 30

Asn Lys Leu Pro Pro His G ^~ lu Ser Leu Arg Ser Pro Gly Thr Leu Pro 35 40 45

Asn His Pro Asn Phe Arg Leu Lys Ser Ser Glu Asn Gly Asn Lys Lys

50 55 60

Asn Asn Phe Leu Leu Cys Glu Gin Thr Lys Gin Tyr Leu Ala Ser Gin 65 70 75 80

Glu Asp Asn Ser val Ser Ser Asn Pro Asn Gly lie Asn Gly Glu val

85 90 95 val Gly Ser Lys Gly Asp Arg Lys Lys Leu Pro Ala Gly Asn Ser val

100 105 110

Ser Pro Pro Ser Ala Glu Ser Asn Ser Pro Pro Lys Glu val Asn lie

115 120 125

Lys Pro Gly Asn Asn val Arg Pro Ala Lys Ser Lys Lys Leu Asn Lys

130 135 140

Leu val Glu Asn Ser Leu Ser lie Ser Asn Pro Gly Leu Phe Thr Ser 145 150 155 160

Leu Gly Pro Pro Leu Arg Ser Thr Thr Cys His Arg Cys Gly Leu Phe

165 170 175

Gly Ser Leu Arg Cys Ser Gin Cys Lys Gin Thr Tyr Tyr Cys Ser Thr

180 185 190

Ala Cys Gin Arg Arg Asp Trp Ser Ala His Ser lie val Cys Arg Pro

195 200 205

val Gin Pro Asn Phe His Lys Leu Glu Asn Lys Ser Ser lie Glu Thr

210 215 220

Lys Asp val Glu val Asn Asn Lys Ser Asp Cys Pro Leu Gly val Thr 225 230 235 240

Lys Glu lie Ala lie Trp Ala Glu Arg lie Met Phe Ser Asp Leu Arg

245 250 255

Ser Leu Gin Leu Lys Lys Thr Met Glu lie Lys Gly Thr val Thr Glu

260 265 270

Phe Lys His Pro Gly Asp Phe Tyr val Gin Leu Tyr Ser Ser Glu val

275 280 285

Leu Glu Tyr Met Asn Gin Leu Ser Ala Ser Leu Lys Glu Thr Tyr Ala

290 295 300

Asn val His Glu Lys Asp Tyr lie Pro val Lys Gly Glu val Cys lie 305 310 315 320

Ala Lys Tyr Thr val Asp Gin Thr Trp Asn Arg Ala lie lie Gin Asn

325 330 335 val Asp val Gin Gin Lys Lys Ala His val Leu Tyr lie Asp Tyr Gly

340 345 350

Asn Glu Glu lie lie Pro Leu Asn Arg lie Tyr His Leu Asn Arg Asn

355 360 365

lie Asp Leu Phe Pro Pro Cys Ala lie Lys Cys Phe val Ala Asn val

370 375 380

lie Pro Ala Glu Gly Asn Trp Ser Ser Asp Cys lie Lys Ala Thr Lys 385 390 395 400

Pro Leu Leu Met Glu Gin Tyr Cys Ser lie Lys lie val Asp lie Leu

405 410 415

Glu Glu Glu val val Thr Phe Ala val Glu val Glu Leu Pro Asn Ser

420 425 430

Gly Lys Leu Leu Asp His val Leu lie Glu Met Gly Tyr Gly Leu Lys

435 440 445 Pro Ser Gly Gin Asp Ser Lys Lys Glu Asn Ala Asp Gin Ser Asp Pro 450 455 460

Glu Asp val Gly Lys Met Thr Thr Glu Asn Asn lie val val Asp Lys 465 470 475 480

Ser Asp Leu lie Pro Lys val Leu Thr Leu Asn val Gly Asp Glu Phe

485 490 495

Cys Gly val val Ala His lie Gin Thr Pro Glu Asp Phe Phe Cys Gin

500 505 510

Gin Leu Gin Ser Gly Arg Lys Leu Ala Glu Leu Gin Ala Ser Leu Ser

515 520 525

Lys Tyr Cys Asp Gin Leu Pro Pro Arg Ser Asp Phe Tyr Pro Ala lie

530 535 540

Gly Asp lie Cys Cys Ala Gin Phe Ser Glu Asp Asp Gin Trp Tyr Arg 545 550 555 560

Ala Ser val Leu Ala Tyr Ala Ser Glu Glu Ser val Leu val Gly Tyr

565 570 575 val Asp Tyr Gly Asn Phe Glu lie Leu Ser Leu Met Arg Leu Cys Pro

580 585 590

lie lie Pro Lys Leu Glu Leu Pro Met Gin Ala lie Lys Cys val

595 600 605

Leu Ala Gly val Pro Ser Leu Gly lie Trp Thr Pro Glu Ala lie

610 615 620

Cys Leu Met Lys Lys Leu val Gin Asn Lys lie lie Thr val Lys val 625 630 635 640 val Asp Lys Leu Glu Asn Ser Ser Leu val Glu Leu lie Asp Lys Ser

645 650 655

Glu Thr Pro His val Ser val Ser Lys val Leu Leu Asp Ala Gly Phe

660 665 670

Ala val Gly Glu Gin Ser Met val Thr Asp Lys Pro Ser Asp val Lys

675 680 685

Glu Thr Ser val Pro Leu Gly val Glu Gly Lys val Asn Pro Leu Glu

690 695 700

Trp Thr Trp val Glu Leu Gly val Asp Gin Thr val Asp val val val 705 710 715 720

Cys val lie Tyr Ser Pro Gly Glu Phe Tyr Cys His val Leu Lys Glu

725 730 735

Asp Ala Leu Lys Lys Leu Asn Asp Leu Asn Lys Ser Leu Ala Glu His

740 745 750

Cys Gin Gin Lys Leu Pro Asn Gly Phe Lys Ala Glu lie Gly Gin Pro

755 760 765

Cys Cys Ala Phe Phe Ala Gly Asp Gly Ser Trp Tyr Arg Ala Leu val

770 775 780

Lys Glu lie Leu Pro Asn Gly His val Lys val His Phe val Asp Tyr 785 790 795 800

Gly Asn lie Glu Glu val Thr Ala Asp Glu Leu Arg Met lie Ser Ser

805 810 815

Thr Phe Leu Asn Leu Pro Phe Gin Gly lie Arg Cys Gin Leu Ala Asp

820 825 830

lie Gin Ser Arg Asn Lys His Trp Ser Glu Glu Ala lie Thr Arg Phe

835 840 845

Gin Met Cys val Ala Gly lie Lys Leu Gin Ala Arg val val Glu val 850 855 860

Thr Glu Asn Gly lie Gly val Glu Leu Thr Asp Leu Ser Thr Cys Tyr 865 870 875 880

Pro Arg lie lie Ser Asp val Leu lie Asp Glu His Leu val Leu Lys

885 890 895

Ser Ala Ser Pro His Lys Asp Leu Pro Asn Asp Arg Leu val Asn Lys

900 905 910

His Glu Leu Gin val His val Gin Gly Leu Gin Ala Thr Ser Ser Ala

915 920 925

Glu Gin Trp Lys Thr lie Glu Leu Pro val Asp Lys Thr lie Gin Ala

930 935 940

Asn val Leu Glu lie lie Ser Pro Asn Leu Phe Tyr Ala Leu Pro Lys 945 950 955 960

Gly Met Pro Glu Asn Gin Glu Lys Leu Cys Met Leu Thr Ala Glu Leu

965 970 975

Leu Glu Tyr Cys Asn Ala Pro Lys Ser Arg Pro Pro Tyr Arg Pro Arg

980 985 990 lie Gly Asp Ala Cys Cys Ala Lys Tyr Thr Ser Asp Asp Phe Trp Tyr

995 1000 1005

Arg Ala val val Leu Gly Thr Ser Asp Thr Asp val Glu val Leu

1010 1015 1020

Tyr Ala Asp Tyr Gly Asn lie Glu Thr Leu Pro Leu Cys Arg val

1025 1030 1035

Gin Pro lie Thr Ser Ser His Leu Ala Leu Pro Phe Gin lie lie

1040 1045 1050

Arg Cys Ser Leu Glu Gly Leu Met Glu Leu Asn Gly Ser Ser Ser

1055 1060 1065

Gin Leu lie lie Met Leu Leu Lys Asn Phe Met Leu Asn Gin Asn

1070 1075 1080

val Met Leu Ser val Lys Gly lie Thr Lys Asn val His Thr val

1085 1090 1095

Ser val Glu Lys Cys Ser Glu Asn Gly Thr val Asp val Ala Asp

1100 1105 1110

Lys Leu val Thr Phe Gly Leu Ala Lys Asn lie Thr Pro Gin Arg

1115 1120 1125

Gin Ser Ala Leu Asn Thr Glu Lys Met Tyr Arg Met Asn Cys Cys

1130 1135 1140

Cys Thr Glu Leu Gin Lys Gin val Glu Lys His Glu His lie Leu

1145 1150 1155

Leu Phe Leu Leu Asn Asn Ser Thr Asn Gin Asn Lys Phe lie Glu

1160 1165 1170

Met Lys Lys Leu Leu Lys Lys Thr Ala Ser Leu Gly Gly Lys Pro

1175 1180 1185

Leu