EP3545107A2

EP3545107A2 - Determination of the receptive status of the endometrium

Info

Publication number: EP3545107A2
Application number: EP17857649.2A
Authority: EP
Inventors: Bálint László BÁLINT
Original assignee: Quantbio Kft
Current assignee: Quantbio Kft
Priority date: 2016-11-22
Filing date: 2017-11-22
Publication date: 2019-10-02
Also published as: WO2018096375A2; WO2018096375A3

Abstract

The invention relates to a method for determining the receptive or non-receptive status of the endometrium using a biological sample from a subject of reproductive age, preferably from a human female patient. Moreover, the invention relates to a test kit suitable for performing the method, as well as the use of oligonucleotides suitable for the amplification of gene sets for the determination of the receptive or non- receptive status of the endometrium.

Description

METHOD FOR DETERMINING THE RECEPTIVE STATUS OF ENDOMETRIUM

SCOPE OF INVENTION

The invention relates to a method for determining the receptive or non-receptive status of the endometrium using a biological sample from a human female patient of reproductive age. Moreover, the invention relates to a test kit suitable for performing the method, as well as the use of oligonucleotides suitable for the amplification of gene sets for the determination of the receptive or non-receptive status of the endometrium.

THE STATE OF TECHNOLOGY

According to estimates, 150,000 couples are affected by infertility problems in Hungary. 33% of the couples in their late 30s can be considered infertile. Based on data from the Hungarian Central Statistical Office, the number of women between the ages of 15 and 49 decreased by 10% in the past 25 years, while the live-birth rate decreased to eight and a half per mille from twelve. In the past 20 years the population of Hungary has decreased by more than 600,000. Besides the tools of demographic policy, the treatment of infertility and the improvement of the efficiency of in vitro fertilization could increase the number of children born.

According to the currently accepted definition, a couple is deemed to be infertile if with regular sexual intercourse and without using protection, no child is conceived within one year. Unfortunately, the time for having children is postponed to a later and later date and as time passes, the chances of becoming pregnant decrease. Due to social changes, childbearing at an older age is more and more common, thus for many people it is the in vitro fertilization program that could provide a solution. It is a common problem that couples join a "test-tube baby program", otherwise known as the "In Vitro Fertilization (IVF) program" relatively late and besides the original problems, there are multiple obstacles to becoming pregnant. Unfortunately, the procedure often does not result in the desired conception even if the best medical background is provided.

The implantation of the embryo depends both on the status of the embryo and that of the endometrium. When the condition of the embryo is ideal, its implantation into the endometrium is possible only in a relatively short, maximum few-day -long period. This is called the implantation window. This usually occurs on days 19-21 of the menstrual cycle, 6-7 days after ovulation. In the case of a cycle controlled by medication, the implantation window is between days 15-20 of the cycle.

There has been a longstanding need for monitoring the status of the endometrium not only based on the calendar method but also directly, which would indicate the opportunity for embryo implantation in a more reliable way. One of the options is to study whether the status of the endometrium meets the requirements of implantation with histological and imaging methods [Noyes RW, Hertig AT, Rock J 1975 Dating the Endometrial Biopsy. Am J Obstet Gynecol 122:262-263]. Thus, for example, the monitoring of the status of the endometrium routinely takes place with ultrasound. However, it has been demonstrated several times that the receptive and non-receptive phases of the endometrium cannot be clearly distinguished with this method [Simon Valles C, et al., EP2333107B l].

Methods based on the examination of tissue expression have also been known for the determination of the status of the endometrium.

In an early period, people tried to assign a marker gene to changes in the status of the endometrium, this, however, did not prove to be reliable, although some key markers might play a significant role. This is emphasized by the following findings by Simon Valles C. and co-inventors. For example, int'l publication WO2011089240 recommends the specification of the level of PGE2 and PGF2 genes, where endometrial fluid samples are used for the test; while in int'l publication WO2011061376 they report on the fact that CD98 is an endometrial receptivity marker.

Other inventors have specified smaller sets of genes and with adequate selection they see the opportunity for the determination of endometrial receptivity. Thus, for example, Hamamah S and Haouzi D recommend selecting at least one gene from a set of 15 genes (FGFBP1, MUC20, TMPRSS3, PRUNE2, HES2, MGST1, ERRFI1, EDNl, SLC17A7, MET, CPTIB, DCDC2, LRRC39, IL18RAP and FOXPl), in order to evaluate the status of the endometrium after controlled ovarian hyperstimulation (int'l publication WO2013057316). In another work of the research group, the expression level of 11 genes (MFAP5, ANGPTL1, PROK1, NLF2, LAMB3, BCL2L10, CD68, TRPC4, SORCS1, FST and KRT80) was specified in endometrial biopsy (int'l publication WO2011147976, US patent no. US9260748B2).

The question as to how the different menstrual cycles of the endometrium could be characterized using tools of molecular biology emerged early on.

Mirkin S., et al. found during early, randomized blind clinical trials connected with microarray tests in 2005 that changes in the early and mid-luteal phases may play a significant role in the opening and maintenance of the window of implantation. [Mirkin S, Arslan M, Churikov D, Corica A, Diaz J, Williams S, Bocca S, Oehninger S. In Search of Candidate Genes Critically Expressed in the Human Endometrium During the Window of Implantation. Hum Reprod. 2005 20(8):2104-17].

Yanaihara A, et. al used DNA microarray technology to demonstrate differences in gene expression patterns of the human endometrium in a proliferative phase, in epithelial and stromal areas, as part of which from a total of 1,200 genes, only 14 were strongly expressed in epithelial areas and 12 were strongly expressed in stromal areas. [Yanaihara A, Otsuka Y, Iwasaki S, Aida T, Tachikawa T, Irie T, Okai T. Differences in Gene Expression in the Proliferative Human Endometrium. Fertil Steril. 2005 83 Suppl 1 : 1206-15.].

Talbi et al. have observed in their research group that the gene expression analysis of the endometrium corresponds to the status of the endometrium in different menstrual phases [Talbi S, Hamilton AE, Vo KC, Tulac S et al. Molecular Phenotyping of Human Endometrium Distinguishes Menstrual Cycle Phases and Underlying Biological Processes in No rmo -Ovulatory Women. Endocrinology 2006 Mar; 147(3): 1097-121.]. The complete genomic test was carried out with the involvement of normo-ovulatory women. With gene clustering analysis (with two independent clustering algorithms), they have found that based on their expression, genes can characterize the proliferative (PE), early-secretory (ESE), mid-secretory (MSE), and late-secretory (LSE) endometrium, as phases of the endometrium, which at the same time also indicate the phases of the menstrual cycle. The analysis was carried out with an Affymetrix chip containing a very large number (54,600) of probes. They claim that their study confirms that samples taken at any time during the cycle have a unique molecular signature (pattern), and thus it is not necessary to determine the histological phase a priori before sampling. At the same time, the molecular signatures are not the same among individuals but show significant variability. The authors wished to study samples of healthy women and struggled with the results gained in the case of the different groups, which they could not fully explain. Thus even though they have distinguished the different phases of the endometrium decidedly, they have called for further research in endometrial biology. In a later work the research group studied women suffering from endometriosis and with the use of genetic expression analysis they have found that women with endometriosis demonstrate progesterone resistance and increased candidate susceptibility. [Burney RO, Talbi S, Hamilton AE, Vo KC et al. Gene Expression Analysis of Endometrium Reveals Progesterone Resistance and Candidate Susceptibility Genes in Women with Wndometriosis. Endocrinology 2007 148(8):3814-26.]

Based on the results to date, it is clear for specialists that reliable results can only be achieved with the analysis of complex genetic expression patterns.

One of the approaches is based on the study of the expression level of microRNAs, small RNA molecules that are 18-24 nucleotides in length in their mature state. The microRNAs themselves are molecules encoded in the genome, which regulate the expression of other genes. Such a method was used for assessing the fertility of women by Kresowik, J., et al. (int'l publication WO2014062442A1). Here, however, they are monitoring the expression pattern not of genes indicating the status of the endometrium, but that of their regulating molecules. Simon Valles C. et al., have developed a method in which they study the niRNA expression level of a large number of genes with rnicroarray technology. The authors study the expression status of 238 genes with the help of close to six hundred probes, and the expression pattern is compared in order to establish the receptive or non- receptive status of the endometrium. This method is used by the "Endometrial Receptivity Array" solution of IGENOMIX. During the practical implementation of the procedure, they collect endometrial biopsy in the case of a natural cycle on the 7^th day following the luteal hormone peak, while in the case of a cycle controlled by medication on the 5^th day following the first administration of progesterone. From the biopsy they prepare complete mRNA and it is subjected to rnicroarray testing. In case the biopsy indicates a suitable status, the window of implantation is specified in light of this; otherwise the dislocation of the window of implantation can be established, which has to be specified with further testing. The accuracy and reproducibility of the method proved to be superior to histology as a diagnostic method [Diaz— Gimeno P, Ruiz— Alonso M, Blesa D, Bosch N, Martinez— Conejero Ja, Alama P, Garrido N, Pellicer A, Simon C (2013). The Accuracy and Reproducibility of the Endometrial Receptivity Array is Superior to Histology as a Diagnostic Method for Endometrial Receptivity. Fertil Steril 99: 508-517.].

Endometrial sampling may take place with an invasive method (biopsy) or with a less invasive method, i.e., the collection of detached cells.

Endometrial biopsy removes a small tissue sample from the endometrium. The biopsy contains cells from multiple cell layers and these cells include different cell types, thus the gene expression changes taking place in the cell types may vary from one cell type to the other.

The extraction of cells present in the uterine solution is a much less invasive method than biopsy. As part of this sampling procedure, the free discharge present in the uterine cavity is extracted; the removal of the discharge may be facilitated with physiological saline or other lavage fluids. As the uterine cavity is not closed, by introducing a small quantity, a few ml of solution, we can reabsorb close to the same, although usually lower quantity (min. 50 % quantity) of solution.

The solution removed from the uterine cavity includes both detached endometrial cells and other cells. In this case the other cells may be red and white blood cells, cells of the normal bacterial flora, and, for example, the squamous cells of the cervix.

Irrespective whether we start from biopsy or uterine lavage, besides the cells lining the uterus, there are also other cells in the sample.

It is revealed by the works introduced above that it is not a trivial endeavor to select a set of genes that can reliably indicate the status of the endometrium. No such method has been known before that works with a gene set of a significant size that is not typical of microarrays, which is also suitable for indicating the receptive and non-receptive status of the endometrium with diagnostic accuracy not only in microarray tests but also in tests based on more reliable polymerase chain reactions. Moreover, no such method was known before which could have indicated the status of the endometrium based on endometrial lavage.

The inventors have implemented such a method which is suitable for reliably indicating the status of the endometrium both from biopsy and endometrial (uterine) lavage. Moreover, they have identified those genes which share similar dynamics also in the different sample types.

BRIEF DESCRIPTION OF THE INVENTION

The invention relates to a method for determining receptive or non-receptive status of endometrium using a biological sample from a female subject of reproductive age, preferably from a human female patient and/or thereby for the determination of the window of implantation,

where the method comprises the following steps:

a) defining different stages (phase or status) of the endometrium, including the following: early-secretory endometrium (ESE), mid-secretory endometrium (MSE) and late-secretory endometrium (LSE), and optionally proliferative endometrium,

where the mid-secretory endometrium is in a receptive status,

b) for each given menstrual stage specified herein or for each stage of the endometrium specified in step a) defining a set of genes connected to the given stage, where the mRNA expression level of the genes in the set differs in the mid-secretory endometrium stage from the others and preferably at least in one additional stage, and thus the mRNA expression of the genes in the given set of genes, in case the endometrium is in a given stage, shows an expression pattern characteristic of the given stage,

c) providing or preparing or obtaining a biological sample taken from a female subject, preferably a human female patient on a specific day of her menstrual cycle, in which

d) the mRNA expression levels of at least 5, 8, 10, 15 or 20, preferably at least 10 genes selected from the genes in the gene sets are determined,

e) determining, with the analysis of the mRNA expression levels of at least 5, 8, 10, 15 or 20, preferably at least 10 genes selected from the gene sets related to the particular stages, whether the endometrium is in the mid- secretory stage or not,

- if it is in such a stage, it is considered suitable for the implantation of the embryo (receptive),

- if it is not in such a stage, it is not considered suitable and optionally the analysis is repeated by taking a sample at another time of the menstrual cycle.

According to a variant of the method of the invention, the definition of the set of differing genes takes place during the implementation of the procedure, at the time of evaluating the expression levels; especially if in this variant of the procedure we specify that the expression of all genes should be different in the case of the different stages.

According to a variant of the method of the invention, the definition of the set of differing genes takes place prior to measurement in the case of reference data or reference patterns, in a pre-defined manner.

According to a variant of the method of the invention, the gene sets connected to the particular stages are identical.

The invention relates to a method for determining the receptive or non-receptive status of the endometrium from a biological sample from female subject of reproductive age, preferably a human female patient and/or thereby for the determination of the window of implantation,

where the procedure includes the following steps:

a) defining different stages of the endometrium, including the following: early-secretory endometrium (ESE), mid-secretory endometrium (MSE) and late-secretory endometrium (LSE), and optionally proliferative endometrium,

where the mid-secretory endometrium is in a receptive status,

b) for each phase of the endometrium specified in step a) defining a set of genes, and thus the mRNA expression of all the genes belonging to the given gene set, in case the endometrium is in a given stage, shows an expression pattern characteristic of the particular stage,

c) providing or preparing or obtaining a biological sample taken from a female subject, preferably human female patient on a specific day of her menstrual cycle, in which

e) determining, with the analysis of the mRNA expression level of at least 5, 8, 10, 15 or 20, preferably at least 10 genes selected from the gene set, whether the endometrium is in the mid-secretory stage or not,

Preferably, in any of steps c) described above, mRNA is prepared.

Reasonably, mRNA preparation can also be implemented with total RNA preparation.

Moreover, the subject of the invention is a procedure for determining the receptive or non-receptive status of the endometrium using a biological sample from a human female patient and/or thereby for the determination of the window of implantation

where the procedure comprises the following steps:

- providing mRNA from the endometrial sample taken from the patient,

- determining the mRNA expression pattern with the quantitative RT-PCR method for such genes expressed at the mRNA level whose expression profile corresponds to the mid-secretory (MID) phase or mid-secretory endometrium (MSE), and the expression profile of which typically differs in the MID phase from the expression profile of the endometrial patterns in the phase prior and/or after the MID phase,

preferably, determining the mRNA expression level of at least 5, 8, 10, 15 or 20, preferably at least 10 genes selected from the genes in the gene sets,

- based on the expression pattern, determining whether the endometrium is in a mid-secretory phase or not; wherein preferably the endometrial sample is uterine lavage. If it is in such a status, it is deemed suitable (receptive) for the implantation of the embryo,

- if it is not in such a status, it is not considered suitable and in a given case the analysis is repeated by taking a sample at another time of the menstrual cycle.

During the method of the invention, the gene expression pattern measured in the sample is compared to the mRNA expression pattern of the sample taken from the endometrium in its early secretory, mid-secretory, and late secretory stage, and optionally in its proliferative stage, and it is determined which stage it is closest to, and it is categorized into the stage it is closest to.

According to a variant of the invention, based on the different stages of the endometrium, we define the different phases of the menstrual cycle, which are at least the following: early -secretory phase, mid- secretory phase, and late-secretory phase, and in a particular case the proliferative phase, where the receptive status of the endometrium is indicated by the mid-secretory.

According to a variant of the invention, the biological sample is endometrial biopsy.

According to a variant of the invention the biological sample is uterine lavage.

According to a preferred variant of the invention, the mRNA expression level (the extent of the expression of genes on mRNA level, i.e., the mRNA level expression of genes) is determined by using quantitative PCR.

Preferably prior to quantitative PCR reverse transcriptase PCR is used, whereby cDNA is created from mRNA.

According to a preferred embodiment, when it is determined by the analysis of the mRNA expression levels whether the endometrium is in a mid-secretory stage or not, a comparison is made between the mRNA expression levels gained from the sample of the female subject, preferably a human female patient and the reference mRNA expression levels, and it is determined which endometrial stage's reference mRNA expression levels the mRNA expression levels gained from the sample are closest to.

Preferably, this comparison or calculation is made using

geometric distance calculation, preferably by the least squares method; according to a preferred variant, as per gene or gene group; and/or

hierarchical clustering.

According to a variant, the calculation can also be made with a self -learning method based on neural networks.

According to a further variant, first reverse transcriptase PCR is used, whereby cDNA is created from mRNA, followed by sequencing.

Preferably, all sets of the genes include at least 10 genes or at least 5 or 8 or 10 or 20 genes, which are selected from the following group:

ADAMTS2, ADAMTS8, ARG2, ClOorflO, CD55, CDKN2B, CEBPD, CRISP3, CSRP2, CTHRC1, CYP24A1, DUOX1, DUOXA1, EDNRB, GNG4, GPX3, GREM2, GZMA, HPGD, IGFBP1, IGFBP3, IGFBP6, IRX3, KCND2, LCP2, LEFTY2, LRP4, MAOA, MAP2K6, MMP10, MT1M, MUC16, OPRK1, PAEP, PKHD1L1, PLAT, PLD1, SGIP1, SLAIN1, SLC15A1, SLC15A2, SLC1A1, SLC26A7, SLC5A3, SPP1, SYT11, TFPI2, TIMP3, TMED6, TNFRSF11B.

Highly preferably, the sets of the genes comprises at least 5 or 8 or 10 genes from the following:

ADAMTS8, ARG2, ClOorflO, CD55, CSRP2, GPX3, GREM2, GZMA, IGFBP1, MUC16, PAEP, PKHD1L1, PLAT, PLD1, SLC15A1, SLC15A2, SLC1A1, SLC26A7, SYT11.

Preferably, the sets of genes belonging to the mid-secretory endometrium comprise at least the following genes: CD55, GPX3, KCND2, OPRKl, PAEP, SGIP1, SLC1A1, SPP1, SYT11, TNFRSF11B.

Preferably, the sets of genes belonging to the mid-secretory endometrium include at least the following genes: ARG2, ClOorflO, CD55, CRISP3, CYP24A1, GNG4, GPX3, GREM2, IRX3, KCND2, LCP2, MAOA, MMP10, MT1M, OPRKl, PAEP, PLD1, SGIP1, SLC1A1, SLC26A7, SPP1, SYT11, TNFRSF11B.

According to a particularly preferred embodiment, the sets of genes related to the early-secretory endometrium, mid-secretory endometrium, late-secretory endometrium and in a particular case to the proliferative endometrium are selected from the genes shown in Figure 4 or in Table 1 or Table 3 for the given sets.

In a given case, the following genes can be used as normalizing genes:

B2M, B2M, TBP, POLR2A.

Preferably the mRNA expression levels of at least 5, 8, 10, 15 or 20, preferably at least 10 genes or 20 or 30 or 40 or 50 or 60 genes are determined.

Preferably the mRNA expression levels of at least 5, 8, 10, 15 or 20 preferably at least 10 genes or 20 or 30 or 40 or 50 or 60 genes from the following gene set are determined, in the case of which the nature of the expression changes are similar both in the biopsy and the endometrial fluid:

IGFBP3, GNG4, C2CD4A, G0S2, C1QTNF6, TNFRSFl lB, CTHRC1, PLAT, SLC15A1, LRP4, TCN1, DPP4,

RGS1, EDNRB, DUOXA1, IGFBP6, SGIP1, LTBP2, SOD2, NID2, MS4A7, DDX52, SLC15A2, ITGB6, OPRKl, GZMA, SYT11, CSRP2, HTR2B, THBS1, MUC16, KALI, PDE4B, MMP10, CEBPD, SLC5A3,

MFSD4, GRAMD1C, ABCC3, IGFBP1, TSPAN8, ITGA2, PHLDB2, PLD1, IRX3, GADD45G, BAMBI,

SLC26A7, TMC5, LEFTY2, ASPN, GNG2, ADAMTS8, SLAIN1, PAEP, KCND2, TMED6, GREM2,

ADAMTS2, RHPN2, RDH10, RARRESl, LCP2, FCER1G, KCNK3, SLC1A1,

preferably the following, and the nature of their change is similar:

GRAMDIC, RGS1, MFSD4, BAMBI, C2CD4A, DDX52, DPP4, GZMA, IGFBP1, ITGA2, KCND2, MMP10,

MUC16, PAEP, PHLDB2, PLAT, RARRESl, RDH10, SLC15A1, SLC1A1, TCN1, THBS1, TMC5, TSPAN8,

ADAMTS8, CSRP2, GREM2, , SLC15A2, SLC26A7, PLD1, SYT11, KCNK3,

i) wherein preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: GRAMDIC, RGS1, MFSD4, BAMBI, C2CD4A;

ii) wherein preferably the expression of the following genes is higher in the early phase and lower in the late phase than in the mid phase: C2CD4A, DDX52, DPP4, GZMA, IGFBP1, ITGA2, KCND2, MMP10, MUC16, PAEP, PHLDB2, PLAT, RARRESl, RDH10, SLC15A1, SLC1A1, TCN1, THBS1, TMC5, TSPAN8;

iii) wherein preferably the expression of the following genes is lower in the early phase and higher in the late phase than in the mid phase: ADAMTS8, CSRP2, GREM2, SLC15A2, SLC26A7;

iv) wherein preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: PLD1, SYT11, KCNK3.

Preferably, one or two or three genes are selected from groups i), ii), iii) and iv) also, preferably at least two genes or at least one gene.

Preferably the mRNA expression levels of at least 5, 8, 10, 15 or 20 preferably at least 10 genes or 20 or 30 or 40 or 50 or 60 genes are determined from the following gene set, in the case of which the nature of the expression change in the mid-secretory phase of the endometrium is significant compared to the early and late secretory endometrium and is distinguishable, which are selected from the following:

IGFBP3, GNG4, POLR2A, RHOB, PKHD1L1, CP, C1QTNF6, TNFRSF11B, CTHRC1, SPP1, PLAT, SLC15A1, LRP4, CD55, DPP4, RGS1, EDNRB, DUOXA1, IGFBP6, SGIP1, CRISP3, SOD2, NID2, MS4A7, DDX52, SLC15A2, ITGB6, GZMA, RIMKLB, SYT11, CSRP2, ClOorflO, HTR2B, GPX3, THBS1, MUC16, DUOX1, PDE4B, NNMT, CEBPD, SLC5A3, MFSD4, GRAMD1C, TSPAN8, MT1M, ITGA2, PHLDB2, PLD1, IRX3, GADD45G, BAMBI, SLC26A7, TMC5, LUM, LEFTY2, GNG2, ARG2, ADAMTS8, SLAIN1, TIMP3, PAEP, MAOA, MAP2K6, ADAMTS2, RHPN2, RDH10, RARRESl, LCP2, FCER1G, SLC1A1, i) wherein preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: ARG2, GRAMDIC, RGS1, ClOorflO, MFSD4, BAMBI;

ii) wherein preferably the expression of the following genes is higher in the early phase and lower in the late phase than in the mid phase: CD55, DDX52, DPP4, GPX3, GZMA, ITGA2, MUC16, NNMT, PAEP, PHLDB2, PLAT, RARRESl, RDH10, SLC15A1, SLC1A1, THBS1, TMC5, TSPAN8;

iii) wherein preferably the expression of the following genes is lower in the early phase and higher in the late phase than in the mid phase: ADAMTS8, CSRP2, PKHD1L1, SLC15A2, SLC26A7;

iv) where preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: PLD1, SYT11, RIMKLB.

Preferably, we choose one or two or three genes from groups i), ii), iii) and iv) also, preferably at least two genes or at least one gene.

According to a highly preferred embodiment, the mRNA expression levels of at least 5, 8, 10, 15 or 20 preferably at least 10 genes are determined from the following gene set, in the case of which the nature of the expression change is similar both in the biopsy and the endometrial fluid, and in the case of which the expression change in the mid-secretory phase of the endometrium is significant compared to the early and late secretory endometrium and is distinguishable (suitable for differentiation):

GRAMDIC, RGS1, MFSD4, BAMBI, DDX52, DPP4, GZMA, ITGA2, MUC16, PAEP, PHLDB2, PLAT, RARRESl, RDH10, SLC15A1, SLC1A1, THBS1, TMC5, TSPAN8, ADAMTS8, CSRP2, SLC15A2, SLC26A7, PLD1, SYT11;

i) wherein preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: GRAMDIC, RGS1, MFSD4, BAMBI;

ii) wherein preferably the expression of the following genes is higher in the early phase and lower in the late phase than in the mid phase: C2CD4A, DDX52, DPP4, GZMA, ITGA2, MUC16, PAEP, PHLDB2, PLAT, RARRES1, RDH10, SLC15A1, SLC1A1, THBS1, TMC5, TSPAN8;

iii) wherein preferably the expression of the following genes is lower in the early phase and higher in the late phase than in the mid phase: ADAMTS8, CSRP2, SLC15A2, SLC26A7;

iv) wherein preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: PLD1, SYT11.

Preferably, at least one or two or three genes are selected from groups i), ii), iii) and iv) also.

In a given case the normalizing genes are the following: B2M, B2M, TBP, ACTB.

According to the invention, the given lists are the set of genes or the set of genes are selected from it, as described herein.

Highly preferably, the gene list, from which the gene set is defined or which is the set of genes itself is the following, which can clearly make a statistically significant distinction between the three stages of the endometrium (or the three clusters corresponding to its phase) in all combinations (i.e., they distinguish between all three groups among those in the three cleaned clusters based on the pairs):

IGFBP1, PAEP, GPX3, MFSD4, ClOorflO, MAP2K6, PKHD1L1, DUOX1, CSRP2, SLAIN1, DDX52, N MT, CD55, CP, TFPI2, OPRK1, ADAMTS8, DUOXA1, SLC26A7, SLC15A2, DPP4, SLC1A1, GZMA, RARRES1, TMED6, GREM2 (26 genes).

Highly preferably, the gene list from which the set of genes is defined or which is the set of genes itself is the following, which clearly makes statistically significant distinctions between two out of the three stages of the endometrium:

IGFBP1, KCND2, KCNK3, PAEP, GPX3, MFSD4, ClOorflO, MAP2K6, PKHD1L1, DUOX1, CSRP2, SLAIN1, IGFBP3, DDX52, NNMT, RHOB, CD55, RIM LB, CP, MAOA, SOD2, LUM, TFPI2, OPRKl, LRP4, ADAMTS8, DUOXA1, SLC26A7, SLC15A2, ITGA2, CEBPD, MUC16, TMC5, BAMBI, GNG4, PHLDB2, DPP4, TSPAN8, SLC1A1, EDNRB, SLC15A1, RDH10, RHPN2, GRAMD1C, GZMA, RARRES1, TMED6, TCN1, C2CD4A, CYP24A1, GREM2, ABCC3, IRX3, GADD45G.

According to a very preferred embodiment, the mRNA level expression of all the genes according to any of the above gene lists is specified with quantitative PCR.

Moreover, the invention also relates to a test kit for the implementation of the method of the invention, said kit comprising an amplification primer connected to the gene set specified according to at least any of the above lists.

Moreover, the invention also relates to a test kit used for the implementation of the method of the invention, said kit comprising an oligonucleotide primer connected to the gene set specified according to at least any of the above lists.

The invention also relates to a test kit for determining the receptive status of the endometrium, which is suitable for simultaneously determining the mRNA expression level of at least 5, 8, 10, 15 or 20, preferably at least 10 genes from the genes listed in the gene lists specified herein, and

includes at least 3' and 5' primer pairs for the amplification of mRNA transcribed from particular genes with quantitative reverse transcription,

and an oligonucleotide probe for the detection of the mRNA expression level by means of quantitative reverse transcription.

The subject of the invention includes a test kit for determining the receptive status of the endometrium, which is suitable for simultaneously determining the mRNA expression level of at least 5, 8, 10, 15 or 20, preferably at least 10 genes from the genes listed in Table 1 or Figure 4, and

includes at least 3 ' and 5' primer pairs for the amplification of mRNA transcribed from particular genes with quantitative reverse transcription,

According to a preferred embodiment the genes are cDNAs.

According to a preferred embodiment the primers are qPCR primer.

According to a preferred embodiment the primers are primers suitable for reverse transcription.

Preferably, the reagent set comprises probes, in particular specific fluorescent probes, preferably specific probes for quantitative PCR also.

Optionally, the test kit includes a data carrier or a unit capable of executing commands, which in the procedure of the invention is programmed for the execution of the calculation and/or evaluation and/or comparison step. Preferably, the test kit includes a probe suitable for the detection of gene set amplification.

Moreover, the invention also relates to the use of primer and probe sets specified in connection with the reagent sets according to the invention for the determination of the receptive or non-receptive status of the endometrium from a biological sample from a female subject of reproductive age, preferably a human female patient and/or thereby for the specification of the window of implantation in an endometrial biopsy sample or endometrial lavage fluid from the patient.

In a particularly preferred case the endometrial sample is endometrial lavage.

Moreover, the invention relates to the use of the test kit for determining the receptive or non-receptive status of the endometrium using a biological sample from a human female patient of reproductive age and/or for the determination of the window of implantation

Moreover, the invention relates to a method connected to an in vitro fertilization method, which may take place separately from the IVF treatment as well, even as part of a routine gynecological examination, during which endometrial sample is collected,

mRNA is isolated from the endometrial sample,

from the mRNA isolate, using the quantitative PCR method, it is determined based on the mRNA expression pattern in the endometrial sample if the endometrium is in an early secretory, mid-secretory, late secretory, or proliferative phase,

when the endometrium is in the mid-secretory phase, the endometrium is deemed to be receptive. In the procedure of the invention, the endometrial sample is biopsy or endometrial lavage (uterine lavage). The in vitro fertilization procedure described in the invention, during which it is determined, based on the mRNA expression pattern in the endometrial sample, whether the endometrium is in an early secretory, mid- secretory, late secretory or proliferative phase, the method according to the invention is used for the determination of the receptive/non-receptive status of the endometrium and/or thereby the specification of the implantation window.

In the description, the singular form (and thus the indefinite article) also includes the plural form and (unless excluded by the correlations) vice versa. For example, and specifically, in case the specification of gene sets is mentioned, it is also understood in a way that several gene sets can represent the same set. Similarly, the term "each and every", in case identical, can be interpreted in the sense of "every" or "all", unless excluded by the relevant correlations.

In the specification, the term "comprises" means that what is included or comprised in what follows the expression might include other species as well, thus the expression is not exclusive. At the same time, in a given case the expression may be limited to the expression "essentially consisting of the following, which means that the important components from the perspective of the effect are those which are exclusively contained in what includes those following the expression, but it may comprise other components that are important from the perspective of the effect. At the same time, in a given case the expression may be limited also with the expression "practically consisting of the following" .

By "isolating" it is understood that the original, natural environment has been changed by Man. RNA isolation also includes the case when the sample is prepared to a minimal extent for further processing, in a given case for PCR. BRIEF DESCRIPTION OF THE FIGURES

Figure 1 shows the grouping of studied genes into 3 sample clusters with K-means clustering. The sample cluster in the middle of the figure corresponds to the mid-secretory phase. 35 instances of pattern clustering took place using the R program package and using all 87 genes for grouping [Metsalu, Tauno and Vilo, Jaak. Clustvis: A Web Tool for Visualizing Clustering of Multivariate Data Using Principal Component Analysis and Heatmap. Nucleic Acids Research, 43(W1):W566-W570, 2015. doi: 10.1093/nar/gkv468.]

The grouping in Figure 2 was made using the results of the narrowed "Genelist 2". The reliability of the list decreased by 8%.

The grouping in Figure 3 was made using the results of the narrowed "Genelist 3". The reliability of the list decreased by 11%.

Figure 4 shows the complete gene list of the 87 genes identified by us.

Figure 5 shows the summary of scores and their relative proportion for a given gene, based on which it can be seen that based on the sample the endometrium is in the mid-secretory phase, i.e., it is receptive.

Figure 6 shows the Hematoxylin Eosin (Fig. 6) microscope image of an endometrial biopsy.

Figure 7 shows the May Griinwald Giemsa (Fig. 7) microscope image of the endometrial lavage.

Figure 8 - hierarchical clustering result from the 94 measurement points (biomarkers and normalizing genes) with comparison carried out for 28 lavage and biopsy sample pairs; it is visible that the average of differences between the two sample groups (lavage vs. biopsy) is significant thus normalizing is needed but the method works in the case of lavage as well. In the case of the hierarchical clustering presented in Figure 9, in both groups we examined lavage and biopsy collected from 28 patients at the same time; in the case of both types of samples, hierarchical clustering clearly distinguishes between two main groups, where the gene group most resembling the reference samples reflecting the receptive status of the endometrium, showing a gene expression pattern characterizing the window of implantation in the sample set included 13 out of 28 samples in the case of biopsy, while in the case of lavage, it was 12 samples; thus separation works even without the optimization of genes.

Figure 10 shows the categorization of 139 samples of different types (lavage or biopsy) with hierarchical clustering based on the gene group which indicated the most dynamic changes

well code gene

A3 PW _35 DDX52

A4 PW 73 GNG2

A7 PW 82 MAP2K6

A9 PW 87 RDH10

A10 PW 93 SLC1A1

Al l PW 48 THBS1

A12 PW 101 B2M

Bl PW 85 ADAMTS2

B2 PW _22 CD55

B3 PW _23 DPP4

B4 PW .10 GNG4

B5 PW 1 IGFBP3

B7 PW _57 MFSD4

B8 PW 78 PAEP

B9 PW 24 RGS 1

BIO PW 69 SLC26A7

Bl l PW 77 TIMP3

B12 PW 102 B2M

CI PW J5 ADAMTS8

C2 PW _55 CEBPD

C3 PW _5 DUOX1

C4 PW 46 GPX3

C5 PW 27 IGFBP6

C6 PW 89 LCP2

C8 PW .51 PDE4B

C9 PW 86 RHPN2

CIO PW 56 SLC5A3

Cl l PW 7 TMC5

C12 PW 103 TBP

Dl PW 74 ARG2

D2 PW .12 CP

D3 PW 26 DUOXA1

D4 PW 58 GRAMD1C

D6 PW .71 LEFTY2

D7 PW 34 MS4A7 D8 PW 64 PHLDB2

D9 PW 40 RIMKLB

D10 PW 30 SOD2

D12 PW 104 ACTB

E2 PW 29 CRISP3

E3 PW _25 EDNRB

E5 PW 66 IRX3

E6 PW 20 LRP4

E7 PW .61 MT1M

E8 PW 11 PKHD1L1

E9 PW 28 SGIP1

E10 PW .18 SPP1

El l PW .15 TNFPvSFl lB

E12 PW 105 POLR2A

Fl PW 68 BAMBI

F2 PW 43 CSRP2

F3 PW 9 FCER1G

F4 PW 4 GZMA

F5 PW 63 ITGA2

F7 PW 49 MUC16

F8 PW .19 PLAT

F9 PW _.76 SLAIN 1

F10 PW .41 SYT11

Fl l PW 60 TSPAN8

Gl PW 44 ClOorflO

G2 PW . 7 CTHRC1

G5 PW 37 ITGB6

G6 PW 70 LUM

G7 PW _32 NID2

G8 PW 65 PLD1

G9 PW 2 SLC15A1

HI PW .14 C1QTNF6

H3 PW _.67 GADD45G

H4 PW _.45 HTR2B

H6 PW 80 MAOA

H7 PW _.54 NNMT

H8 PW 88 RARRES 1

H9 PW 36 SLC15A2

Hl l PW 108 RHOB

DETAILED DESCRIPTION OF THE INVENTION

The success of in vitro fertilization depends on multiple parameters, including the facilities of the clinic, the experience of and care provided by the senior clinicians, the condition of the embryo and the general health of the couple. The implantation of the embryo developed from the fertilized egg cannot be guaranteed despite all efforts. The implantation of the embryo, very simplistically, depends on two factors: the condition of the embryo and that of the endometrium. In case the condition of the embryo is ideal, its implantation into the endometrium is possible only in a relatively short, maximum few -days-long period. This is called the window of implantation. After endometrial estrogen stimulation the progesterone signal initiates a quick transformation in the endometrium and this brings the endometrium into this phase. The implantation of the embryo (blastocyst) is not probable either before, or after this period.

The method of the invention examines the endometrium with the help of molecular biology, as opposed to the traditional histological and imaging approaches, to see whether its condition meets the requirements of implantation.

In the procedure described in the invention, the "patient" is a human or mammalian subject, who needs or requests the determination of endometrial receptivity.

We consider that in mammals such a gene set expressed on the mRNA level may be specified in an analogous manner which characterizes the receptive condition of the endometrium and this has a significant overlap with the most comprehensive or partial gene sets introduced in the description.

The implantation window varies from subject to subject and currently its opening can mostly be depicted from ultrasound signs. With the help of biochemical signs (e.g. : urine LH peak) the presence of the implantation window may be deduced. The luteinizing hormone (LH peak) makes the adequate status of the endometrium probable but this marker does not examine the endometrium itself, the ultimate answer for the status of the endometrium can be provided with the examination of the endometrium itself. Currently, the histological examination of the endometrial biopsy by a pathologist represents the most accurate method available for determining the status of the endometrium.

The endometrium goes through tremendous gene expression changes during a cycle, the cells are transformed, the mucous membrane thickens, then loosens, and finally sheds. During this process the expression of the genes also changes markedly, which can be determined from a small tissue sample (endometrial biopsy).

Endometrial samples, however, can be collected not only from biopsy but also from uterine lavage [Hannan, G. et al. Uterine Lavage or Aspirate: Which View of the Intrauterine Environment? Reproductive Sciences 2012 19: 1125]. The advantage of this method is that it is minimally invasive, it does not cause hemorrhaging, has minimal side effects, and can be done even in the same cycle with the implantation. The extent of differences between the two types of samples, lavage and biopsy, however, have not been studied before: it was not obvious at all that the lavage could also be used for the determination of endometrial receptivity based on a genetic expression pattern and if yes, then how it could be carried out. Although there have been such experiments before which detected the product of particular genes on the messenger RNA level from endometrial lavage, the examination of particular genes does not bring reliable results and thus this cannot be considered as a solution to the problem.

It has been recognized by the inventor that with the use of the solution described in the invention, the lavage is also suitable for categorizing the status of the endometrium, despite the fact that the gene expression pattern of the two samples differs greatly at first sight. Moreover, biomarker set, specified from lavage which is capable of characterizing the endometrial lavage, has been found. During the measurements the gene expression profiles of the lavage and biopsy samples have been compared. At first, our results indicated that the gene expression profiles of the endometrial biopsy sample and the endometrial lavage sample collected from a patient at the same time differ from each other significantly.

The changes of the endometrium can also be described with the monitoring of gene expression changes.

The collection of samples from the endometrium may take place with an invasive method (biopsy) or a less invasive method, i.e., the collection of detaching cells.

The solution gained from the uterine cavity includes both detached endometrial cells and other cells. In this case the other cells may be red and white blood cells, cells of the normal bacterial flora, and, for example, the squamous cells of the cervix.

Irrespective whether we start out from biopsy or uterine lavage, besides the cells lining the uterus, there are also other cells in the sample.

With the help of our testing and analytical method, we have identified those genes which share similar dynamics in both sample types, i.e., the endometrial biopsy and uterine lavage.

To illustrate the differences between the two sample types in terms of their cell composition, we attach the Hematoxylin Eosin (Fig. 6) microscopic image of endometrial biopsy and a May Griinwald Giemsa (Fig. 7) image of a lavage.

According to a preferred variant of the invention, the sample is thus endometrial lavage (uterine lavage).

Thus in a preferred examination protocol, measurement would take place in endometrial lavage (uterine lavage) and the sampling protocol would be carried out with one of the minimally invasive methods or both, and the measurements described in the examination are also carried out with the same method.

In an additional, preferred examination protocol, we collect samples from endometrial lavage with the adequate sampling protocol and the measurements described in the invention are performed on these.

According to one embodiment of the invention, the set of genes varies for each sample type but the method is the same.

Thus in the process of developing the solution according to the invention, the inventors have identified mRNA genes the expression pattern of which may be used to identify the favorable condition of the endometrium needed for the implantation of the embryo. According to the terminology developed based on microarray experiments, this corresponds to the mid-secretory (MID) phase or mid-secretory endometrium (MSE). We have managed to identify such genes, the expression profile of which typically differs in the MID phase from the expression profile of endometrial samples both prior and after the MID phase. The mRNA expression level of particular genes is typical of the endometrium's proliferative, early secretory, mid-secretory and late secretory stages. (The acronyms used for the endometrium in these stages are as follows: PE, ESE, MSE and LSE.) The identification of the stages (phases) was introduced by Talbi et al. [Talbi S, Hamilton AE, Vo KC, Tulac S et al. Molecular Phenotyping of Human Endometrium Distinguishes Menstrual Cycle Phases and Underlying Biological Processes in Normo -Ovulatory Women. Endocrinology 2006 Mar;147(3):1097-12L]

First of all, the expression level of particular genes was initially determined with the analysis of microarray data, the expression of which according to the particular, corresponding endometrial phase was known (see the following GEO numbers in the NCBI GEO database (Gene Expression Omnibus database): GSE4888, GEO Dataset GDS2052, (Talbi, et al.., 2006, see above) GSE6364, Dataset: Dataset: GDS2737, (Burney RO, et. al., see above). GEO is an international public repository that archives and freely distributes microarray, next- generation sequencing, and other forms of high-throughput functional genomics data submitted by the research community.

As a result of the analyses, a gene list was compiled, with genes whose mRNA-expression level is sensitive to the status of the endometrium, and where the expression level changes depending on its change in status. In the case of the genes, based on the expression level we set up an order among them, which is typical of the particular phase of the endometrium (one of the four specified stages).

During the analyses, following a similar train of thought, the inventors also identified such genes the expression of which does not change but is stable in the endometrial samples of different stages.

At the same time, the present inventors have identified genes, the expression of which changes significantly in the different phases as these gene sets are particularly suitable for the characterization of the different conditions.

As endometrial biopsy is accepted for the characterization of the endometrium but the cell composition of the lavage differs between the biopsy and the lavage, during our experiments we have tried to identify which of the genes identified with biopsy change the same way in the two sample types. For this purpose, both lavage and biopsy were collected from the patient during the same examination, then this gene panel was measured from the two gene samples. This way gene sets which change analogously in the two conditions were found.

The mRNA-level expression of genes to be studied can be identified with the real-time quantitative PCR method or another quantitative method, including next-generation sequencing.

Due to the time and technological background needed for both microarray and new-generation sequencing, as well as their costs, these two technologies are mostly available in central laboratories.

As opposed to this, the real-time reverse transcription PCR method even enables the immediate processing of individual samples and thus the turn-around-time can be very short, so sample processing and the statement of the results may take place on the same day. The advantage of this is that based on the results embryo implantation that considers the results may be performed even within the same cycle.

This does not exclude that the measurement can be implemented also with other methods studying gene expression. The advantage of the solution described in the invention is that for the identified marker genes we developed a measurement system based on real-time, quantitative polymerase chain reactions.

As the probes are mRNA probes, the very sensitive reverse transcription polymerase chain reaction has to be conducted as the first step of measurement. During this process, the intronless RNA is transformed into a DNA with an RNA-dependent DNA polymerase. Based on the quantity of mRNA measured during the process, we can draw conclusions on the activity of the particular gene.

The qPCR method (Real-Time, quantitative) is suitable for the relative/absolute quantification of nucleic acids (DNA or cDNA). In the case of this method, during the PCR cycles the current DNA quantity can be detected in real time due to the accumulating fluorescent signal.

Depending on the goal of the experiment, PCR primers have to be planned in different ways. In the case of absolute or relative quantitation of RNA it is advisable to plan for two extreme exons, thus ensuring that the genome DNA containing the introns would not multiply simply because the distance to be bridged between the two primer pairs is too large. In both cases we need to pay attention to the presence of SNPs, which in certain cases can completely frustrate the reaction.

Surprisingly, we have found that with the analysis of the received gene set the endometrial status of the female patients (capacity or receptivity status) can be estimated with high confidence, and thus the implantation window can be determined.

Cluster analysis, hierarchical clustering

We have identified the gene sets to be used according to the invention by subjecting the expression values received with qPCR to hierarchical clustering on the samples. This is how the two sample groups (biopsy and lavage) were analyzed separately also.

Cluster analysis is a method suitable for arranging data in arrays into homogeneous groups, clusters and thus classifying them [Kaufman, L., & Roussew, P. J. (1990). Finding Groups in Data - An Introduction to Cluster Analysis. A Wiley-Science Publication John Wiley & Sons.] . Data within particular clusters are similar to one another based on some dimension, they are closer to each other, and along this dimension they differ from the elements of the other clusters. The bases of the grouping are the different distance or similarity measures calculated from the data.

According to the invention, hierarchical clustering was used to decide on the suitability of a newer sample for the procedure described in the invention [Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome (2009). "14.3.12 Hierarchical clustering". The Elements of Statistical Learning (2nd ed.). New York: Springer, pp. 520-528. ISBN 0-387-84857-6. https://www.stanford.edu/~hastie Papers/ESLII.pdf]. This method is expedient to be used if we cannot provide the number of clusters in advance as the algorithm itself searches for these. The basic principle of hierarchical clustering (connectivity -based clustering, hierarchical cluster analysis, HCA) is that particular objects in a data set can be closer connected to each other, i.e., they can be grouped into smaller groups, clusters than other, more distant objects based on specified data. Thus these algorithms arrange the objects into clusters of different levels based on their distance calculated from data characteristic of the given object. A cluster, for example, may be described or defined with the maximum distance necessary for the definition of the association between the cluster elements. During the analysis (clustering or cluster formation) different clusters are created at different distances, which can be characterized with a dendrogram. These algorithms do not only divide the data set but also arrange the data into clusters on different levels based on their distance, and these form a united group in terms of other distances. The objects are positioned along one of the axes (e.g., x- axis) of the dendrogram (tree) - according to their distance from one another, with the closest ones next to each other -, while on the other axes (e.g., y-axis, the height of the "tree") indicates the distance where the clusters are united, thus for example, objects are arranged into clusters or clusters into higher-level clusters.

Based on the calculation of distances between data (i.e., objects characterized by data) different hierarchical clustering procedures exist. During our analysis, we took the symmetrical, Euclidean distance of the data as the basis, but other types of distance measurements are also possible. According to another approach, the two large groups of hierarchical clustering procedures are agglomerative and divisive clustering; in the case of the former, the algorithm considers each and every element as a separate cluster at first, then puts them into increasingly larger clusters, while the algorithm based on division first considers the entire data set as one cluster and divides it into smaller and smaller clusters.

With the use of clustering, preferably with hierarchical clustering, we can decide from newer samples and by also involving newer sets of genes if the sample is suitable for the performance of the procedure of the invention with the given gene set.

In case we have reached a given gene set, the following steps are taken in the process of evaluating the measurement data.

The evaluation of measurement data

During the analysis of the sample, the set of genes is selected based on preliminary evaluation, and the RT- QPCR tests are performed on the specified gene set, followed by data analysis.

The measurement results of the RT-QPCR are validated analytically.

We use housekeeping genes as reference (control) genes, the expression of which is significantly independent from the condition of the endometrium, i.e., their transcription level is practically the same in all phases. Yet, it has to be verified in the case of all experiments that the given circumstances really do not influence the expression stability of the housekeeping genes selected by us. Various algorithms are available for the validation of the reference genes. It is also an accepted procedure if we use the geometric mean of at least 3 internal reference genes selected based on published data to normalize the mRNA level of the examined gene. We may use RNA (control genes) introduced as additional control, the quantity of which we know.

During the completion of PCR experiments, we check if the measurement of control genes has really taken place in full and if it is proportional in its magnitude to the quantity of RNA entered.

In case the measurement is successful, the expression level of the genes (the mRNA quantity characteristic of the sample) is specified in a known way, for example, in a Roche LC480 instrument used by us from the Cp ("crossing point") threshold values (the number of PCR reactions executed, when the fluorescent sign exceeds a predetermined threshold). From the Cp value - with the use of adequate reference, in a known way - a relative copy number is calculated, which is a value characteristic of the extent of expression of particular genes in the sample.

As one option, these values characteristic of the measured genes are normalized with the average of values received for all the genes measured in the given sample.

As another option, normalizing genes are selected for normalization, and normalization is completed based on the expression level of these.

For the determination of the status of the endometrium, references reflecting the following three or four phases of the endometrium are used: early secretory endometrium (ESE), mid-secretory endometrium (MSE), and late secretory endometrium (LSE), and in a given case proliferative endometrium (PE).

According to a variant, the reference may be a known reference value characteristic of a given gene and given phase.

According to another variant, we use a sample collected from the endometrium in the above three or four phases as a reference sample.

In the preferred solution according to the invention, the reference samples are used the following way :

A sample can be considered as a reference sample, which sample was collected in a well-known phase. Such samples include, for example, the sample collected on days 3, 7, 9 after the LH peak. Such samples may be found in publications too, e.g., in Talbi et al., but they can also be identified experimentally in people whose endometrium is functioning normally (i.e., female members of couples suffering from infertility with a non- female origin), where the LH peak has been identified with laboratory methods from blood or urine, and compared to this, sample collection is repeated from the third day until the ninth.

Later, any of the samples can be compared to the reference sample. The other advantage of the reference sample is that with the phase categorization of the reference samples the groups of hierarchical clustering can also be identified.

How can we compare a given sample to a reference sample?

Our measurement results are compared to designated reference samples.

For each gene we check to what extent our normalized value differs in the reference genes in different phases from the normalized value measured for the given gene.

In this case three reference samples have been used, a sample in an early, a sample in a mid, and a sample in an late secretory phase.

For the given gene, we quantify the differences between the measurement results of all reference samples. According to our given gene, our sample is closest to that reference sample compared to which it shows the smallest difference in absolute value.

After completing this comparison for all genes, we can establish which reference samples our samples are closest to according to the studied genes, by quantifying the number of genes approximating the given reference sample.

The condition of an appropriate comparison is that we should use such genes for the comparison which have been selected in a way that genes characteristic of each reference sample should be present in the same or almost the same proportion. In this case those genes are considered as characteristic genes which show significant differences between the studied phases.

In case the proportions of gene groups characteristic of different phases differ from each other significantly, the number of changing genes has to be normalized with the size of the group, so that they are comparable with one another.

With the help of the calculations carried out this way, we can assign each sample to one of the reference samples and we can decide which phase they are closest to.

The method is independent of the nature of the reference samples, but in this case, for example, it can be carried out in the case of both lavage and biopsy, with those genes which show a significant and identical change between the different phases and where these changes have clear dynamics.

In general, for a given sample and gene set we specify the expression pattern of the gene set. After normalization to the expression level, the expression pattern is compared to the expression pattern specified for the given gene set for the particular phases of the endometrium.

Preferably, we compare the expression level of genes for each gene to the four reference sample groups and we decide which one it is closest to. We say that the mid-secretory endometrium is in a receptive status so in case the expression pattern is closest to this, then the patient is receptive at the time of sample collection.

In this process according to a suitable method, the geometric distance of particular expression values (points) that can be characterized by multiple parameters is defined. Distance measurement is preferably Euclidian distance measurement but any other type of distance measurement may be used. Preferably such distance measurement is used, which can also be used in the case of hierarchical clustering.

Controls

In various stages of the process appropriate controls were and can be applied.

EXAMPLES

In the following, we will introduce the invention through examples as well, which, however, serves only as an illustration. It is clear for person skilled in the art that the invention has other, alternative embodiments, the development of which can be expected from the skilled person based on the teaching provided herein.

EXAMPLE 1.1

Examination-related tasks

At the site designated for the collection of samples patients are examined after prepared in line with the rules of the profession. Pregnancy can and should be excluded, in line with the rules of the profession (e.g. with manual examination, ultrasound and biochemical methods.)

Endometrial biopsy

There are several proven minimally invasive methods available for endometrial biopsy. For our purposes, endometrial biopsy takes place with the use of a thin (few mm thick) flexible, sterile plastic, disposable device, which is lead into the uterine cavity and with its help a small sample from the endometrium is removed. This method is fast and causes only mild symptoms.

Such a procedure can be carried out by an adequately qualified physician and if the rules of the profession are observed, the side effects are negligible. In general, the procedure can be deemed safe.

Cramps in the lesser pelvis, mild pain or slight bleeding may occur.

Infection is considered to be a severe complication. Uterine perforation is a very severe and extremely rare side effect.

The pain involved in the examination is partly due to the opening of the cervix, which can be reduced with local anesthesia.

The course of endometrial biopsy:

1. For the examination, the patient lies on a gynecological examination table. Sample collection can be completed under conditions available at a general gynecological office. On a gynecological examination table, in lithotomy position, with vaginal examination.

2. During a regular gynecological examination the physician leads the disposable device used for the biopsy into the uterine cavity and with a few movements removes a minimal amount of tissue, which is then placed into the prepared sampling tube.

The physician sends the sampling tube to the laboratory, where RNA is isolated from the tissue and after cDNA conversion we determine the expression level of marker genes:

EXAMPLE 1.2

Uterine lavage sampling

Uterine lavage sampling takes place the following way: with the help of a sterile catheter we take a 1-5 ml sterile, pharmaceutical-grade infusion solution into the uterine cavity with the help of a thin, flexible catheter, then after aspirating the fluid, it is centrifuged at 10,000 g for 10 minutes and the supernatant is portioned into microcentrifuge tubes per 1 ml and is frozen. 1 ml of stabilizing solution is added to the sediment and is kept at room temperature until shipping. The method is quick and causes only mild symptoms.

We attach a deaerated syringe filled with 2 ml of physiological saline under sterile circumstances to the catheter. The catheter also has to be filled with the physiological saline and the air has to be removed. During vaginal examination, the catheter is led into the uterine cavity after the disinfection of the cervix. The 2 ml saline is slowly injected into the uterine cavity, then we reabsorb the uterine lavage immediately. This means approximately 1.5 ml of lavage. The catheter is removed. The lavage is injected from the syringe into the prepared tube suitable for the collection of RNA samples.

Such a procedure can be performed by an adequately qualified physician and if the rules of the profession are observed, the side effects are negligible. In general, the procedure can be deemed safe.

Cramps in the lesser pelvis, mild pain or slight bleeding may occur.

Infection is considered a severe complication.

The course of endometrial lavage sampling: 1. For the examination, the patient lies on a gynecological examination table.

2. During a regular gynecological examination the physician completes the washing and the aspiration with the disposable device used for biopsy.

3. The samples are placed in the prepared sampling tubes.

Such stabilizing fluids are commercially available. Stabilizing solutions are disclosed in patents. The following patent documents refer to such patents: U. S. Patent Nos. 4,741,446, 4,991,104, 6,602,718, and 6,617,170. The stabilization of RNA and DNA in blood is described especially in examples 1 and 2 of document no. US 6,617,170. These, especially the latter one, are part of the training by means of referencing. We have discovered unexpectedly that the Paxgene Blood RNA Tube is especially suitable for the stabilization of the endometrial sample and especially favorable for that of endometrial lavage, as not only the mRNA but the sample itself also behaves favorably.

The physician sends the sampling tube to the laboratory where RNA is isolated from the tissue and after cDNA conversion we determine the expression level of marker genes EXAMPLE 2

Sample shipping and RNA extraction

Both biopsy and lavage may be shipped in physiological saline in case it reaches the sample processing laboratory within a short time (max. within one or two hours). The use of those crosslinking agents (e.g., formaldehyde) that are used in routine pathological sample processing should be avoided as these modify nucleic acids chemically. In practice, such stabilizing solutions are available both in the case of biopsy and lavage which enable the shipping of the sample even for a longer time at room temperature in a way that adequate quality RNA can be isolated from it afterwards. Such sample stabilizing solutions include, for example, RNA Later (Thermofisher) or Paxgene Blood RNA Tube (Preanalytics).

After the arrival of the sample to the laboratory, total RNA is extracted from the sample based on the recommendation of the stabilizing solutions. In the case of biopsy, the sample is removed from the solution and is homogenized in Trizol (Thermofisher, Catalog no. 15596026) or similar denaturation solution.

Total RNA is isolated from the homogenate in the familiar manner. A suitable RNA isolation method is the PAXGene Blood RNA kit, QIAGEN (catalog no.:762174), which can also be used here (see Blood RNA Kit Handbook; catalog no. 762164.).

EXAMPLE 3

Measurement and the determination of the expression level

The extraction of mRNA from a sample is considered a routine method in molecular biology, it is most often carried out with Trizol reagent. The samples have to be homogenized, cells lysed, and the serum or plasma has to be mixed with the Trizol reagent. From the extracted total RNA mRNA measurements can be conducted. The mRNA levels are preferably specified in a way that in the first step cDNA is created with reverse transcriptase PCR. In a subsequent step with the use of quantitative PCR we amplify the cDNA and thus we receive quantitative data for the mRNA quantity found in the original sample. Oligo design. After the selection of the genes, we planned a QPCR assay for them operating based on the principle of hydrolysis probes. The assay consists of three elements, two primers and a probe marked with dual dye; the hydrolysis of the probe removes the two dye molecules from each other by means of Taq or other DNA polymerase used for PCR, thus the fluorescent energy transfer phenomenon between them terminates and the paint molecules can be excited independently. There are numerous variants of the method, which may differ from each other in terms of the technology used but they can be measured in a similar format.

In our example we have used a TaqMan probe.

The genes used for the measurement and the IDs needed for specific identification, as the standard RefSeq ID. The start and end of the region used for measurement, and the traditional name of the gene can be seen in Table 1 below.

Table 1 - In the case of the genes that can be used in the solution described in the invention the start

For the quantitative PCR method, we carried out oligonucleotide design for the specification of genes with the Primer3 method. The method is described in the following publications:

Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, Rozen SG (2012) Primer3 - New Capabilities and Interfaces. Nucleic Acids Research 40 (15):el 15,

Koressaar T, Remm M (2007) Enhancements and Modifications of Primer Design Program Primer3 Bioinformatics 23(10): 1289-91.

The method is available on several online interfaces and can be used freely, including, for example, the website of the National Institute of Health (https://www.ncbi.nlm.nih.gov/tools/primer-blast/). Such a device is, for example, the Invitrogen™ OligoPerfect™ Designer.

With the oligonucleotides designed with the primer design method SybrGeen (intercalating dye, but other intercalating dyes operating based on the same principle can also be used) or methods using other probes can be used, including Taqman, Molecular Beacon, or Universal Probe Library, or other quantitative methods. Next- generation sequencing may also be deemed such a method.

Pre-designed qPCR assays and primers may also be ordered from Integrated DNA technologies (USA: Coralville, Iowa 52241, EU: B-3001 Leuven, Belgium).

For the initial measurements, for quantitative PCR, we used Roche's UPL primer design software. The UPL acronym stands for "Universal Probe Library" and it is an oligo set by Roche, which currently includes 165 different fluorescent hydrolysis probes. If we design qPCR, there is no need to design the probe manually but by following the sequence of appropriate steps in the Assay Design Center available on the Roche website, for the desired transcript, we get both the sequence of PCR primer pairs and the UPL probe number recommended for these in good quality. Our laboratory has 90 of these UPL probes, which cover the entire human genome. The characteristic feature of these probes is that the so called LNA technique was used during their preparation, which means that they used such nucleotide analogues during synthesis, which are bound to their templates more strongly in a chemical sense than conventional oligonucleotides. This is needed to be able to keep the Tm sufficiently high even with short probes (the UPL probes are of 8-9 nucleotides in length on average).

For later measurements we ordered from Integrated DNA Technologies (IDT) (see above).

The design of the probes may also be implemented with other, online software and instruments, for example, Primer3Plus (an improvement of the Primer3 method; Untergasser et al. 2007. Nucl. Acids Res. 35(Web Server issue) :W71-W74),

BiSearch Primer Design and Search Tool, Aranyi T, et al. 2006. BMC Bioinformatics 7: 431),

MFEprimer (Qu W et al. 2012. Nucl. Acids Res. 40 (Web Server issue): W205-W208).

Performing qPCR

The qPCR was run on Roche Lyghtcycler 480 II and the Mono Color Hydrolisys Probe protocol is used with the following program.

Measurement from tissue sample: 45 cycles

Measurement from lavage: 55 cycles (as the expression level is weaker)

For the evaluation of the results we use the "Second Derivative Maximum" method and the corresponding baseline setting. The "Second Derivative Maximum" method automatically calculates the fractional crosspoint cycle (Cp) for each sample. Thus the method eliminates the differences caused by the user.

Documentation:

With the help of the device's software, we print the crosspoint cycle numbers and work with this in an evaluation Excel file.

EXAMPLE 4

The assessment of measurement data.

Specification of normalizing genes

According to this example, the normalizing genes were selected as follows:

Position on plate Code Gene

A12 PW_101 B2M

B12 PW_102 B2M

C12 PW_103 TBP

D12 PW_104 ACTB

E12 PW_105 POLR2A

F12 PW_106 PPIA A gene, the B2M gene is measured in duplicate.

The normalization factor calculated from the geometric mean of the other normalizing genes is used for the analysis of the qPCR data.

The objective of the current analysis is to decide which genes are the most stable, which ones have the lowest variability between samples. We would like to provide a ranking of the marked genes and select which genes we should normalize for.

sd: standard deviation; cv%: coefficient of variation"

PW 104 is not used for normalization because of cv% 8.4, which is very high.

Based on these analyses, we have established the ranking from the marked genes. Normalization for more genes provides more reliable data. Besides PW 101 and PW 102, we also normalize for PW 103 (TBP), PW_105(POLR2A), PW 106 (PW 106) using the geometric mean value.

The variance between samples of genes thus received and possibly also used as reference is between 5.63 and 6.6%, SD is between 1.4 and 1.75.

Such normalizing genes may be other genes, too, for example, those about which it is revealed during measurements that they do not significantly change in the different phases of the endometrium.

This method enables the comparison of results of different samples and even samples from different sources (e.g., lavage and biopsy). Assessment of data and the specification of the receptivity of the endometrium with "score" values

According to the example, it is decided if the mid-secretory endometrium is in a receptive status, i.e., which expression pattern it is closest to, with the comparison of the normalized expression values and the expression value characteristic of the given phase (stage).

In the example, distance is characterized with a given value ("score"). Thus for the expression of the given gene, we receive a "score" value characteristic of the given phase. According to a possible version, the score value is calculated from the difference between the expression value characteristic of the given gene and the reference value measured simultaneously or known. In case the score is proportionate to or correlates with the difference, the lower score value reflects a higher degree of similarity. If we calculate this way, the aggregated score value characteristic of the given phase will also be the smallest aggregated value.

According to another, preferred version this score value is 1 for the stage in which the measured expression level of the examined gene is closest to the expression level of the reference gene or to the known value characteristic of this, and it is 0 for all other stages.

The "score" value is aggregated for the given stage. In the representation in the figures, this takes place according to the vertical columns, i.e., according to samples. This way we get a characteristic score value for each stage (ESE-score, MSE-score, LSE-score, and in a given case PE-score). If we divide the calculated amount with the number of genes, this value will be between 0 and 1, if we multiply it by 100, we receive the score values characteristic of the gives stages in a percentage figure.

We take the stage we receive the most typical score value for and we consider that the patient's endometrium is in that stage. If the above-mentioned percentage score value is used, we take the stage with the highest percentage score value, and consider that the patient's endometrium is in that stage.

According to this version, over a score value of 50-60% it can be stated that the sample is close to a given phase.

Figure 5 illustrates this, with the following percentage score values corresponding to the different phases:

The assessment of data and the specification of the receptivity of the endometrium with hierarchical clustering According to the invention, we have proved with hierarchical clustering that based on receptivity, groups (clusters) can be distinguished on the gene set. Based on clustering, we created a group that includes the samples which may be deemed sufficiently receptive.

For clustering we may use, for example, the following programs:

ClustVis method

At the initial experiments, we used the ClustVis program package for hierarchical clustering [Metsalu, Tauno and Vilo, Jaak. Clustvis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap.Nucleic Acids Research, 43(W1):W566-W570, 2015. doi: 10.1093/nar/gkv468]. This requires an adequate number of reference samples, which are grouped by the program with the k-means clustering method. The morpheus method is an alternative method.

Numerous software products are available for hierarchical clustering, including BCLUST 1.0, which was developed specifically for the analysis of gene clusters or gene expression data, and eSOMet 1.0.

As an additional option, we use hierarchical clustering to decide which phase the expression pattern of the given patient sample is closest to.

With hierarchical clustering and based on the expression values the sample is arranged by the method into the given hierarchical order of clusters.

As an example, if the given patient sample is put into the same cluster with samples that are known to be characteristic of the mid-secretory phase, then it can also be stated about the patient sample that it is typical of the endometrium in the mid-secretory phase.

The disadvantage of assessment with clustering in the case of an especially small or unclear sample set is that it is heavily burdened by interpersonal variability as all samples come from a given phase of a given subject. Moreover, if it is examined in the case of each new sample if it fits into the cluster or any of the clusters of samples considered to be receptive, it is possible that in the case of a disorderly sample the entire clustering falls apart and it will be completely different than before.

The assessment of data and the specification of the receptivity of the endometrium with the method of neural networks

According to a variant, the assessment with neural networks may be considered an improvement of clustering, which can eliminate the above-mentioned disadvantages.

In the case of assessment with the neural network method, the result of the clustering is the learning set and there is also an empty set. Using known samples the neural network model learns which algorithm can be used the most reliably to decide about a given sample whether it can be included in the given group, which is the group of receptive samples (expression values connected to them) received as a result of clustering.

According to a preferred variant, in the neural network model, instead of belonging to the group of clustered, (theoretically only) supposedly receptive women, we consider it a more reliable method if the algorithm compares the values to three reference clusters and the result is good if it is further away from non-receptive groups and closer to receptive ones.

Controls - We use control genes on the plates, including the normalizing genes the expression of which remains stable in the different phases of the endometrium, and other controls if necessary.

EXAMPLE 5

The gene set in the case of endometrial biopsy and the assessment of measurement data

The complete gene set is included in Table 3 below. The IDs of genes in the attached table is based on the database of the HUGO Gene Nomenclature Committee (i½†p:/ www.genet)ames.org/), as queried on 20 Nov., 2016. Table 3

Input Match type App. symbol Approved name HGNC ID Location

ABCC3 Approved ABCC3 ATP binding cassette subfamily HGNC: 54 17q21.33 symbol C member 3

ADAMTS2 Approved ADAMTS2 ADAM metallopeptidase with HGNC218 5q35.3 symbol thrombospondin type 1 motif 2

ADAMTS8 Approved ADAMTS8 ADAM metallopeptidase with HGNC224 l lq24.3 symbol thrombospondin type 1 motif 8

ARG2 Approved ARG2 arginase 2 HGNC664 14q24.1 symbol

ASPN Approved ASPN asporin HGNC: 14872 9q22.31 symbol

BAMBI Approved BAMBI BMP and activin membrane HGNC:30251 10pl2.1 symbol bound inhibitor

ClOorflO Approved ClOorflO chromosome 10 open reading HGNC23355 10ql l.21 symbol frame 10

C1QTNF6 Approved C10TNF6 Clq and tumor necrosis factor HGNC: 14343 22ql2.3 symbol related protein 6

CCDC71L Approved CCDC71L coiled-coil domain containing HGNC26685 7q22.3 symbol 71 -like

CD55 Approved CD55 CD55 molecule (Cromer blood HGNC2665 lq32.2 symbol group)

CDKN2B Approved CDKN2B cyclin dependent kinase HGNC: 1788 9p21.3 symbol inhibitor 2B

CEBPD Approved CEBPD CCAAT/enhancer binding HGNC: 1835 8ql l.21 symbol protein delta

CP Approved CP ceruloplasmin HGNC2295 3q24- symbol q25.1

CRISP3 Approved CRISP3 cysteine rich secretory protein 3 HGNC: 16904 6pl2.3 symbol

CSRP2 Approved CSRP2 cysteine and glycine rich HGNC2470 12q21.2 symbol protein 2

CTHRC1 Approved CTHRC1 collagen triple helix repeat HGNC: 18831 8q22.3 symbol containing 1

CYP24A1 Approved CYP24A1 cytochrome P450 family 24 HGNC2602 20ql3.2 symbol subfamily A member 1

DDX52 Approved DDX52 DExD-box helicase 52 HGNC20038 17ql2 symbol DPP4 Approved DPP4 dipeptidyl peptidase 4 HGNC:3009 2q24.2 symbol

DUOX1 Approved DUOX1 dual oxidase 1 HGNC:3062 15q21.1 symbol

DUOXA1 Approved DUOXA1 dual oxidase maturation factor HGNC:26507 15q21.1 symbol 1

EDNRB Approved EDNRB endothelin receptor type B HGNC:3180 13q22.3 symbol

FCER1G Approved FCER1G Fc fragment of IgE receptor Ig HGNC:3611 lq23.3 symbol

G0S2 Approved G0S2 G0/G1 switch 2 HGNC:30229 lq32.2 symbol

GADD45G Approved GADD45G growth arrest and DNA damage HGNC:4097 9q22.2 symbol inducible gamma

GNG2 Approved GNG2 G protein subunit gamma 2 HGNC:4404 14q22.1 symbol

GNG4 Approved GNG4 G protein subunit gamma 4 HGNC:4407 lq42.3 symbol

GPX3 Approved GPX3 glutathione peroxidase 3 HGNC:4555 5q33.1 symbol

GRAMD1C Approved GRAMD1C GRAM domain containing 1C HGNC:25252 3ql3.31 symbol

GREM2 Approved GREM2 gremlin 2, DAN family BMP HGNC: 17655 lq43 symbol antagonist

GZMA Approved GZMA granzyme A HGNC:4708 5ql l.2 symbol

HPGD Approved HPGD hydroxyprostaglandin HGNC: 5154 4q34.1 symbol dehydrogenase 15 -(NAD)

HTR2B Approved HTR2B 5-hydroxytryptamine receptor HGNC: 5294 2q37.1 symbol 2B

IGFBP1 Approved IGFBP1 insulin like growth factor HGNC: 5469 7pl2.3 symbol binding protein 1

IGFBP3 Approved IGFBP3 insulin like growth factor HGNC: 5472 7pl2.3 symbol binding protein 3

IGFBP6 Approved IGFBP6 insulin like growth factor HGNC: 5475 12ql3.13 symbol binding protein 6

IL1B Approved IL1B interleukin 1 beta HGNC:5992 2ql4.1 symbol IRX3 Approved IRX3 iroquois homeobox 3 HGNC: 14360 16ql2.2 symbol

ITGA2 Approved ITGA2 integrin subunit alpha 2 HGNC:6137 5ql l.2 symbol

ITGB6 Approved ITGB6 integrin subunit beta 6 HGNC:6161 2q24.2 symbol

KALI Previous ANOS1 anosmin 1 HGNC:6211 Xp22.31 symbol

KCND2 Approved KCND2 potassium voltage-gated HGNC:6238 7q31.31 symbol channel subfamily D member 2

KCNK3 Approved KCNK3 potassium two pore domain HGNC:6278 2p23.3 symbol channel subfamily K member 3

LCP2 Approved LCP2 lymphocyte cytosolic protein 2 HGNC:6529 5q35.1 symbol

LEFTY2 Approved LEFTY2 left-right determination factor 2 HGNC:3122 lq42.12 symbol

LRP4 Approved LRP4 LDL receptor related protein 4 HGNC:6696 l lpll.2 symbol

LRP4 Synonyms CORIN corin, serine peptidase HGNC: 19012 4pl2

LTBP2 Approved LTBP2 latent transforming growth HGNC:6715 14q24.3 symbol factor beta binding protein 2

LTBP2 Previous LTBP3 latent transforming growth HGNC:6716 l lql3.1 symbol factor beta binding protein 3

LUM Approved LUM lumican HGNC:6724 12q21.33 symbol

MAOA Approved MAOA monoamine oxidase A HGNC:6833 Xpl l.3 symbol

MAP2K6 Approved MAP2K6 mitogen-activated protein HGNC:6846 17q24.3 symbol kinase kinase 6

MFSD4 Previous MFSD4A major facilitator superfamily HGNC:25433 lq32.1 symbol domain containing 4A

MMP10 Approved MMP10 matrix metallopeptidase 10 HGNC:7156 l lq22.2 symbol

MS4A7 Approved MS4A7 membrane spanning 4-domains HGNC: 13378 l lql2 symbol A7

MS4A7 Synonyms MS4A4A membrane spanning 4-domains HGNC: 13371 l lql2.2

A4A

MT1M Approved MT1M metallothionein 1M HGNC: 14296 16ql3 symbol

MUC16 Approved MUC16 mucin 16, cell surface HGNC: 15582 19pl3.2 symbol associated

NID2 Approved NID2 nidogen 2 HGNC: 13389 14q22.1 symbol

N MT Approved NNMT nicotinamide N- HGNC:7861 l lq23.1 symbol methyltransferase

OPRK1 Approved OPRKl opioid receptor kappa 1 HGNC: 8154 8ql l.23 symbol

PAEP Approved PAEP progestagen associated HGNC: 8573 9q34.3 symbol endometrial protein

PDE4B Approved PDE4B phosphodiesterase 4B HGNC: 8781 lp31.3 symbol

PHLDB2 Approved PHLDB2 pleckstrin homology like HGNC:29573 3ql3.2 symbol domain family B member 2

PKHD1L1 Approved PKHD1L1 polycystic kidney and hepatic HGNC:20313 8q23.1- symbol disease 1 (autosomal recessive)- q23.2 like 1

PLAT Approved PLAT plasminogen activator, tissue HGNC: 9051 8pl l.21 symbol type

PLD1 Approved PLD1 phospholipase Dl HGNC: 9067 3q26.31 symbol

PLD1 Previous PRKCSH protein kinase C substrate 80K- HGNC: 9411 19pl3.2 symbol H

RARRES1 Approved RARRESl retinoic acid receptor responder HGNC: 9867 3q25.32 symbol 1

RDH10 Approved RDH10 retinol dehydrogenase 10 (all- HGNC: 19975 8q21.11 symbol trans)

RGS1 Approved RGS1 regulator of G-protein signaling HGNC: 9991 lq31.2 symbol 1

RHPN2 Approved RHPN2 rhophilin Rho GTPase binding HGNC: 19974 19ql3.12 symbol protein 2

RIMKLB Approved RIMKLB ribosomal modification protein HGNC:29228 12pl3.31 symbol rimK like family member B

SGIP1 Approved SGIP1 SH3 domain GRB2 like HGNC:25412 lp31.3 symbol endophilin interacting protein 1

SLAIN1 Approved SLAIN1 SLAIN motif family member 1 HGNC:26387 13q22.3 symbol SLC15A1 Approved SLC15A1 solute carrier family 15 member HGNC: 10920 13q32.2- symbol 1 q32.3

SLC15A2 Approved SLC15A2 solute carrier family 15 member HGNC: 10921 3ql3.33 symbol 2

SLC1A1 Approved SLC1A1 solute carrier family 1 member HGNC: 10939 9p24.2 symbol 1

SLC26A7 Approved SLC26A7 solute carrier family 26 member HGNC: 14467 8q21.3 symbol 7

SLC5A3 Approved SLC5A3 solute carrier family 5 member HGNC: 11038 21q22.11 symbol 3

SOD2 Approved SOD2 superoxide dismutase 2, HGNC: 11180 6q25.3 symbol mitochondrial

SPP1 Approved SPP1 secreted phosphoprotein 1 HGNC: 11255 4q22.1 symbol

SPP1 Synonyms CXXC1 CXXC finger protein 1 HGNC:24343 18q21.1

SYT11 Approved SYT11 synaptotagmin 11 HGNC: 19239 lq22 symbol

TCN1 Approved TCN1 transcobalamin 1 HGNC: 11652 l lql2.1 symbol

TFPI2 Approved TFPI2 tissue factor pathway inhibitor HGNC: 11761 7q21.3 symbol 2

THBS1 Approved THBS1 thrombospondin 1 HGNC: 11785 15ql4 symbol

TIMP3 Approved TIMP3 TIMP metallopeptidase HGNC: 11822 22ql2.3 symbol inhibitor 3

TMC5 Approved TMC5 transmembrane channel like 5 HGNC:22999 16pl2.3 symbol

TMED6 Approved TMED6 transmembrane p24 trafficking HGNC:28331 16q22.1 symbol protein 6

TNFRSF11B Approved TNFRSFl lB TNF receptor superfamily HGNC: 11909 8q24.12 symbol member 1 lb

TNFRSFl lB Synonyms BTF3P11 basic transcription factor 3 HGNC: 1126 13q22.3 pseudogene 11

TSPAN8 Approved TSPAN8 tetraspanin 8 HGNC: 11855 12q21.1 symbol

The gene sets corresponding to the particular phases are presented in Fig.4. EXAMPLE 6

The determination of the receptivity of the lavage and biopsy with hierarchical clustering

Conducting the comparison for 28 lavage and biopsy sample pairs from 94 measurement points (biomarkers and normalizing genes) in an experiment, the significance value of the difference between the two groups was pO.001 in 81 cases, thus in the majority of the cases the difference is deemed significant. These differences, however, cannot be described with a simple formula, for example, due to the fact that the quantity of RNA extracted from the lavage is significantly lower than from the sample from biopsy. This is supported by the fact that the average of differences between the two sample groups (lavage versus biopsy) showed a variation between 2.2 and 122-fold difference in the experiment, where the differences between the individual measurement points were on a very wide scale: the smallest difference was 9.09xl0e-13 and the largest one was 3.2xl0e+3. This undoubtedly represents a major difficulty in the analysis of the lavage (Fig. 8).

In the next experiment we have shown that the lavage can still be used reliably for the determination of the endometrium's receptivity.

In the process of hierarchical clustering, in both groups we examined lavage and biopsy collected from 28 patients at the same time. In hierarchical clustering we grouped both the samples and the genes, based on their Euclidian distance. We have found that in the case of both types of samples, hierarchical clustering clearly distinguishes between two main groups. The gene group most resembling the reference samples reflecting the receptive status of the endometrium, showing a gene expression pattern characteristic of the window of implantation, included 13 samples out of the 28 samples in the examined sample set in the case of biopsy, while in the case of lavage, it was 12 samples. Studying the two subgroups, we found that the patients making up the two sub-groups were the same in 11 cases! Thus, in case we consider the biopsy as the reference, the hit ratio was 11/13, meaning that compared to the reference sample, the lavage provided an 85 % hit ratio. This ratio may be deemed especially good considering the fact that the procedure involved in sample collection is less invasive and can also be performed in the same cycle with embryo implantation. (Fig. 9).

EXAMPLE 7.1.

In this example, we ranked the genes according to their expression level based on mRNA expression data gained for biopsy samples. We used different biopsy samples depending on whether they were gained from the proliferative, early, mid or late secretory endometrium. Fig. 4 presents this ranking of a set of genes according to the level of expression. It is visible that the expression pattern - which is characterized here by the order of the expression level of the genes - is different in each phase of the endometrium.

Based on this, we can define a gene set for each phase of the endometrium which includes such genes that - show high mRNA-level expression if the endometrium is in the given state,

and such genes that

- show low mRNA-level expression if the endometrium is in the phase related to the given gene set.

According to an embodiment, we specify the mRNA expression level of genes selected from the first gene set characteristic of each menstrual phase (preferably at least 5, more preferably at least 10 genes), and we specify the mRNA expression level of genes selected from the second gene set characteristic of each menstrual phase (preferably at least 5, more preferably at least 10 genes). The following are examples for such gene groups. According to one example, genes showing a high mRNA-level expression are at least the following:

preferably at least the following:

and / or

- genes showing a low mRNA-level expression are at least the following:

and / or

MMP10 SYT11 MMP10 CEBPD

PLD1 CYP24A1 GNG4 KCND2

SLC15A1 EDNRB CYP24A1 ADAMTS8

CYP24A1 CDKN2B LCP2 HPGD

EDNRB PLD1 GREM2 DUOX1

LCP2 LCP2 PLD1 SLC15A2 CDKN2B GNG4 SLC26A7 TMED6

IGFBP1 MMP10 SGIP1 GREM2

KCND2 CEBPD SYT11 SLAIN1

TNFRSF11B TNFRSF11B TNFRSF11B PKHD1L1

CEBPD IGFBP1 OPRKl OPRKl

OPRK1 KCND2 KCND2 SLC26A7

EXAMPLE 7.2

The gene set in the case of endometrial lavage and the assessment of measurement data.

After the measurement of our gene panel, the genes were normalized in line with those described above, then we examined which of our genes change in an identical way (in parallel) in the two sample types. For this purpose, based on the 37 biopsy and lavage sample pairs studied by us, we chose those genes in the case of which the difference between the normalized values of the genes in the two sample types, divided by the mean of normalized values measured in the two sample types, showed a smaller difference than 1 Cp, i.e., a difference of a PCR cycle.

Based on our measurement and analysis, the following genes from our gene panel showed similar differences in the two sample types, thus they are capable of the characterization of the endometrium in a similar manner also from lavage as from biopsy. The genes used for normalization were marked in green.

Based on our measurement and analysis, the following genes from our gene panel show similar differences in the two sample types, thus they are capable of the characterization of the endometrium in a similar manner also from lavage as from biopsy. Thus, these genes do not necessarily show marked changes, but the nature of their changes is similar both in biopsy and endometrial fluid. Therefore, in the case of this gene set it is more probable that they characterize the endometrial changes specifically.

The genes used for normalization were marked in italics.

Discriminating genes, i.e., genes changing together in the two types of samples: IGFBP3, GNG4, B2M, B2M, TBP, POLR2A, C2CD4A, G0S2, C1QTNF6, TNFRSF11B, CTHRC1, PLAT, SLC15A1, LRP4, TCN1, DPP4, RGS1, EDNRB, DUOXA1, IGFBP6, SGIP1, LTBP2, SOD2, NID2, MS4A7, DDX52, SLC15A2, ITGB6, OPRKl, GZMA, SYT11, CSRP2, HTR2B, THBS1, MUC16, KALI, PDE4B, MMP10, CEBPD, SLC5A3, MFSD4, GRAMD1C, ABCC3, IGFBP1, TSPAN8, ITGA2, PHLDB2, PLD1, IRX3, GADD45G, BAMBI, SLC26A7, TMC5, LEFTY2, ASPN, GNG2, ADAMTS8, SLAIN1, PAEP, KCND2, TMED6, GREM2, ADAMTS2, RHPN2, RDH10, RARRESl, LCP2, FCER1G, KCNK3, SLCIAL .

In the next approach, we examined which genes changed to a great extent in our sample set. For this analysis we examined 163 samples, which included both lavage and biopsy samples. The genes showing the largest change between the particular phases and thus the ones that are most suitable for use in phase categorization due to their variability are the following:

Genes showing great changes between the phases are the following: IGFBP3, GNG4, B2M, B2M, TBP, ACTB, POLR2A, RHOB, PKHD1L1, CP, C1QTNF6, TNFRSF11B, CTHRC1, SPP1, PLAT, SLC15A1, LRP4, CD55, DPP4, RGS1, EDNRB, DUOXA1, IGFBP6, SGIP1, CRISP3, SOD2, NID2, MS4A7, DDX52, SLC15A2, ITGB6, GZMA, RIMKLB, SYT11, CSRP2, ClOorflO, HTR2B, GPX3, THBS1, MUC16, DUOX1, PDE4B, N MT, CEBPD, SLC5A3, MFSD4, GRAMD1C, TSPAN8, MT1M, ITGA2, PHLDB2, PLD1, IRX3, GADD45G, BAMBI, SLC26A7, TMC5, LUM, LEFTY2, GNG2, ARG2, ADAMTS8, SLAIN1, TIMP3, PAEP, MAO A, MAP2K6, ADAMTS2, RHPN2, RDHIO, RARRESl, LCP2, FCER1G, SLC1A1.

The section of the two narrowed lists leads to an especially advantageous gene set. Thus these are the ones that show a great degree of change, and which, however, is practically identical in the case of the two types of samples.

Genes showing a similar direction of change in the two different sample types, which are also featured in the list of genes changing to a larger degree are the following:

The list of genes changing together (in parallel) and showing a great degree of change:

ADAMTS2, ADAMTS8, BAMBI, C1QTNF6, CEBPD, CSRP2, CTHRC1, DDX52, DPP4, DUOXA1, EDNRB, FCER1G, GADD45G, GNG2, GNG4, GRAMD1C, GZMA, HTR2B, IGFBP3, IGFBP6, IRX3, ITGA2, ITGB6, LCP2, LEFTY2, LRP4, MFSD4, MS4A7, MUC16, NID2, PAEP, PDE4B, PHLDB2, PLAT, PLD1, RARRESl, RDH10, RGS1, RHPN2, SGIP1, SLAIN1, SLC15A1, SLC15A2, SLC1A1, SLC26A7, SLC5A3, SOD2, SYT11, THBS1, TMC5, TNFRSF11B, TSPAN8.

After all these, we performed hierarchical clustering on the sample pairs (biopsy and lavage). As a result of hierarchical clustering, we categorized our samples into the different phases of the endometrium with a non- supervised automatic algorithm.

In the sample groups created this way, we examined the changes of genes in different endometrial phases. In the different sample clusters we examined the differences of the normalized values of genes, i.e., the minimum and maximum values. From the examined genes we managed to identify gene groups where the direction of change proved to be unambiguous and which were distinct in the three sample clusters, i.e., in the early, mid, and late secretory phases.

The genes which show clearly distinct changes based on the comparison of the minimum and maximum values between the different phases are the following:

Table 7

e re erence samp es were eterm ne as esc e a ove.

EXAMPLE 7.3

During the observation of the above changes we started out from the expression values, however, we did not complete statistical analysis.

In the experiment described in this example we performed a T-test analysis on the pairs gained from the lavage and biopsy on the samples showing the most obvious changes in the groups. This meant altogether 36 samples, both lavage and biopsy (this time not 36 sample pairs but 36 samples, the samples showing the most well- marked changes).

With the T-test we checked the p-value to be lower than 0.05, in pairs for the three groups or for at least two- two groups.

The shorter gene list introduced in the following list includes those genes which can clearly distinguish between the three clusters in all combinations (i.e., they distinguish between all three groups among the ones in the three cleaned clusters based on the pairs).

The longer list introduced in the following list includes those which can distinguish at least two -two groups well, i.e., such a combination of comparisons in pairs in which we do not see significant differences but we do in combination with the other condition (in comparison with it) (54 genes)

IGFBP1, KCND2, KCNK3, PAEP, GPX3, MFSD4, ClOorflO, MAP2K6, PKHD1L1, DUOX1, CSRP2, SLAIN1, IGFBP3, DDX52, NNMT, RHOB, CD55, RIMKLB, CP, MAOA, SOD2, LUM, TFPI2, OPRK1, LRP4, ADAMTS8, DUOXA1, SLC26A7, SLC15A2, ITGA2, CEBPD, MUC16, TMC5, BAMBI, GNG4, PHLDB2, DPP4, TSPAN8, SLC1A1, EDNRB, SLC15A1, RDH10, RHPN2, GRAMD1C, GZMA, RARRES1, TMED6, TCN1, C2CD4A, CYP24A1, GREM2, ABCC3, IRX3, GADD45G.

EXAMPLE 8

Conclusions regarding the condition of the patient, further steps

In case endometrial biopsy is used, it should be collected at the time of recommended implantation. The measurement results confirm or disprove whether the endometrium was receptive at the time of sampling or not, or if it was in such a phase prior or after that. In case the endometrium deviated from receptive status at the time of sampling, with the use of the results and by repeating the sampling procedure in a subsequent cycle under similar circumstances (e.g. spontaneous cycles or similarly induced medicated cycles) at a time modified in line with the results of the first measurement, it can be established if the endometrium was receptive at the time of the repeated sampling or not. Thus with repeated sampling, we identify the most suitable time for implantation. With the analysis of endometrial lavage and even more so in the case of serum or plasma samples several samples may be collected within the same cycle, thus the time of implantation may be specified better. According to a preferred variant, if the endometrium is found to be in a status suitable for implantation, implantation can be carried out immediately.

As opposed to this, in the case of biopsy, implantation should take place only in the next cycle.

Claims

1. A method for determining the receptive or non-receptive status of the endometrium using a biological sample from a female subject of reproductive age, preferably a human female patient of reproductive age and/or thereby for the determination of the implantation window,

wherein the method comprises the following steps:

a) defining different stages of the endometrium, which are the following: early-secretory endometrium (ESE), mid-secretory endometrium (MSE) and late-secretory endometrium (LSE), and optionally proliferative endometrium, where the mid-secretory endometrium is in a receptive status,

b) for each stage of the menstrual cycle or that of the endometrium specified in step a) defining a set of genes, where the mRNA expression level of the genes in the given set of genes, in case the endometrium is in a given stage, shows an expression pattern characteristic of the given stage,

c) providing, preparing or obtaining a biological sample from a female subject, preferably a human female patient on a given day of her menstrual cycle,

d) in said sample determining the mRNA expression level of at least 5, 8, 10, 15 or 20, preferably at least 10 genes selected from the genes included in the set of genes,

e) determining, with the analysis of the mRNA expression level of genes selected from the sets of genes defined for each stages and having the determined expression level, whether the endometrium is in the mid-secretory stage or not,

- if it is in such a stage, considering it suitable for the implantation of the embryo (receptive),

2. A method for determining receptive or non-receptive status of the endometrium using a biological sample from a human female patient of reproductive age and/or thereby the specification of the implantation window, wherein the method includes the following steps:

- providing mRNA from the endometrial sample collected from the patient,

- determining mRNA expression pattern with quantitative RT-PCR method for such genes expressed on the mRNA level the expression profile of which corresponds to the mid-secretory (MID) stage or the mid-secretory endometrium (MSE) and the expression profile of which typically differs in the MID stage from the expression profile of the endometrial samples in a stage preceding and/or following the MID stage,

preferably the determining the mRNA expression level of 5, 8, 10, 15 or 20, preferably at least 10 genes selected from the genes belonging to the gene sets,

- determining, based on the expression pattern, whether the endometrium is in a mid-secretory phase or not; wherein preferably the endometrial sample is uterine lavage;

- if it is in such a phase, it is considered to be suitable for implantation of the embryo (receptive),

- if it is not in such a phase, it is not deemed suitable and optionally the analysis is repeated by collecting a sample at another time of the menstrual cycle.

3. The method of claim 1 or 2, wherein the biological sample is endometrial biopsy or the biological sample is uterine lavage.

4. The method of any of the previous claims, wherein it is determined, with the analysis of the mRNA expression levels, whether the endometrium is in a mid-secretory phase,

the mRNA expression levels gained from the sample of the female subject, preferably the human female patient and the reference mRNA expression levels are compared, and

it is established which reference mRNA expression levels, characteristic of the endometrial stages, the mRNA expression levels obtained from the samples are the closest to.

5. The method of any of the previous claims, wherein the set of genes comprises at last 10 genes or comprises at least 5 or 8 or 10 or 20 genes, which are selected from the following group:

ADAMTS2, ADAMTS8, ARG2, ClOorflO, CD55, CDKN2B, CEBPD, CRISP3, CSRP2, CTHRC1, CYP24A1, DUOX1, DUOXA1, EDNRB, GNG4, GPX3, GREM2, GZMA, HPGD, IGFBP1, IGFBP3, IGFBP6, IRX3, KCND2, LCP2, LEFTY2, LRP4, MAOA, MAP2K6, MMP10, MT1M, MUC16, OPRKl, PAEP, PKHD1L1, PLAT, PLD1, SGIP1, SLAIN1, SLC15A1, SLC15A2, SLC1A1, SLC26A7, SLC5A3, SPP1, SYT11, TFPI2, TIMP3, TMED6, TNFRSFl lB;

preferably, all of the sets of the genes comprises at least 5 or 8 or 10 genes from the following:

6. The method of any of the previous claims, wherein the mRNA expression levels of at least 5, 8, 10, 15 or 20 genes from the following gene set are determined, in the case of which the nature of the expression change is analogous both in the biopsy and in the endometrial fluid:

IGFBP3, GNG4, C2CD4A, G0S2, C1QTNF6, TNFRSFl IB, CTHRC1, PLAT, SLC15A1, LRP4, TCN1, DPP4, RGS1, EDNRB, DUOXA1, IGFBP6, SGIP1, LTBP2, SOD2, NID2, MS4A7, DDX52, SLC15A2, ITGB6, OPRKl, GZMA, SYT11, CSRP2, HTR2B, THBS1, MUC16, KALI, PDE4B, MMP10, CEBPD, SLC5A3, MFSD4, GRAMD1C, ABCC3, IGFBP1, TSPAN8, ITGA2, PHLDB2, PLD1, IRX3, GADD45G, BAMBI, SLC26A7, TMC5, LEFTY2, ASPN, GNG2, ADAMTS8, SLAIN1, PAEP, KCND2, TMED6, GREM2, ADAMTS2, RHPN2, RDH10, RARRESl, LCP2, FCER1G, KCNK3, SLC1A1,

preferably from the following, and the nature of their changes is similar:

GRAMDIC, RGS1, MFSD4, BAMBI, C2CD4A, DDX52, DPP4, GZMA, IGFBP1, ITGA2, KCND2, MMP10, MUC16, PAEP, PHLDB2, PLAT, RARRESl, RDH10, SLC15A1, SLC1A1, TCN1, THBS1, TMC5, TSPAN8, ADAMTS8, CSRP2, GREM2, , SLC15A2, SLC26A7, PLD1, SYT11, KCNK3,

ii) wherein preferably the expression of the following genes is higher in the early phase and lower in the late phase than in the mid phase: C2CD4A, DDX52, DPP4, GZMA, IGFBP1, ITGA2, KCND2, MMP10, MUC16, PAEP, PHLDB2, PLAT, RARRES1, RDH10, SLC15A1, SLC1A1, TCN1, THBS1, TMC5, TSPAN8;

iii) wherein preferably the expression of the following genes is lower in the early phase and higher in the late phase than in the mid phase: ADAMTS8, CSRP2, GREM2, , SLC15A2, SLC26A7;

7. The method of any of the previous claims, wherein the mRNA expression levels of at least 5, 8, 10, 15 or 20 preferably at least 10 genes from the following gene sets are determined, in the case of which the expression change in the mid-secretory phase of the endometrium is significant compared to the early and late secretory endometrium and is distinguishable, wherein the genes are selected from the following:

IGFBP3, GNG4, POLR2A, RHOB, PKHD1L1, CP, C1QTNF6, TNFRSF11B, CTHRC1, SPP1, PLAT, SLC15A1, LRP4, CD55, DPP4, RGS1, EDNRB, DUOXA1, IGFBP6, SGIP1, CRISP3, SOD2, NID2, MS4A7, DDX52, SLC15A2, ITGB6, GZMA, RIMKLB, SYT11, CSRP2, ClOorflO, HTR2B, GPX3, THBS1, MUC16, DUOX1, PDE4B, N MT, CEBPD, SLC5A3, MFSD4, GRAMD1C, TSPAN8, MT1M, ITGA2, PHLDB2, PLD1, IRX3, GADD45G, BAMBI, SLC26A7, TMC5, LUM, LEFTY2, GNG2, ARG2, ADAMTS8, SLAIN1, TIMP3, PAEP, MAOA, MAP2K6, ADAMTS2, RHPN2, RDH10, RARRESl, LCP2, FCER1G, SLC1A1, i) wherein preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: ARG2, GRAMDIC, RGS1, ClOorflO, MFSD4, BAMBI;

ii) wherein preferably the expression of the following genes is higher in the early phase and lower in the late phase than in the mid phase: CD55, DDX52, DPP4, GPX3, GZMA, ITGA2, MUC16, NNMT, PAEP, PHLDB2,

PLAT, RARRESl, RDHIO, SLC15A1, SLC1A1, THBS1, TMC5, TSPAN8;

iv) wherein preferably the expression of the following genes is higher both in the early and the late phase than in the mid phase: PLD1, SYT11, RIMKLB;

preferably, at least one or two or three genes from groups i), ii), iii) and iv) are also selected, preferably at least two genes or at least one gene.

8. Test kit for determining the receptive status of the endometrium, which is suitable for simultaneously determining the mRNA expression level of at least 5, 8, 10, 15 or 20, preferably at least 10 genes from the genes listed in table 1 or in figure 4, and

comprises at least 3 ' and 5' primer pairs for the amplification of mRNA transcribed from particular genes with quantitative reverse transcription,

9. The test kit of claim 8, wherein the primers are primers suitable for reverse transcription and the test kit includes a probe suitable for the detection of a gene set's amplification, moreover, in a given case the test kit includes a data carrier or a unit capable of executing commands, which in the method of the invention is programmed for the execution of the calculation and/or evaluation and/or comparison step.

10. Use of primer and probe sets as defined in connection with the reagent kits of claim 8 or 9 for the determination of the receptive or non-receptive status of the endometrium from a biological sample collected from a female subject of reproductive age, preferably a human female patient and/or thereby for the determination of the window of implantation in an endometrial biopsy sample or endometrial lavage fluid collected from the patient.

11. The use of claim 10, wherein the endometrial sample is endometrial lavage.