KR102422364B1 - Method of providing information for diagnosis of endometriosis using gene expression level and composition therefor - Google Patents

Abstract

The present invention relates to a method for providing information for diagnosing endometriosis using a gene expression level and a composition for the same, wherein endometriosis is diagnosed by a calculation formula derived using a candidate gene showing a difference in expression between endometriosis and non-endometriosis patients. can be diagnosed early.

Description

Method of providing information for diagnosis of endometriosis using gene expression level and composition therefor

The present invention relates to a method for providing information for diagnosing endometriosis using a gene expression level and a composition therefor.

Endometriosis is a disease in which the tissue of the endometrium, which should be in the uterus, proliferates abnormally in places other than the uterus. Although the exact cause of endometriosis is still unknown, it is known that it is caused by reflux of menstrual blood, genetic factors, and hormonal imbalance. The main symptoms of endometriosis include severe menstrual pain, pain in the lower abdomen, and infertility. Although it is a very frequent disease, it is often difficult to accurately diagnose it before surgery, and it is difficult to treat because it recurs well. Currently, as a clinical test used to diagnose endometriosis, vaginal ultrasound, magnetic resonance imaging (MRI), blood test, or laparoscopy are the most common diagnostic methods. Since endometriosis is not easy to diagnose accurately, the predictability of endometriosis is low at about 45% in the biopsy performed when endometriosis is suspected. Therefore, there is a need for research on an easier, safer and more sensitive method for diagnosing endometriosis.

Meanwhile, Korea Patent No. 1978399 discloses 'a mutant gene as a diagnostic marker for endometriosis and its use', and Korean Patent No. 1687775 discloses 'a composition for diagnosing endometriosis and a diagnostic kit comprising the same'. However, there is no description of the 'method for providing information for diagnosing endometriosis using a gene expression level and a composition therefor' of the present invention.

The present invention was derived from the above needs, and the present inventors compared and analyzed the expression patterns of genes between non-endometriosis patients and endometriosis patients to select candidate genes showing differences in expression, among which TFAP2α (transcription factor activator protein-2 alpha), NRG1 (neuregulin 1), SMAD7 (SMAD family member 7), and TNS4 (tensin 4) by confirming that endometriosis can be diagnosed by a formula derived using the expression levels of the genes, the present invention was completed.

In order to solve the above problems, the present invention includes a substance for measuring the expression level of TFAP2α (transcription factor activator protein-2 alpha), NRG1 (neuregulin 1), SMAD7 (SMAD family member 7) and TNS4 (tensin 4) genes It provides a composition for diagnosing endometriosis.

In addition, the present invention provides a kit for diagnosing endometriosis comprising the composition.

In addition, the present invention provides a method for providing information for diagnosing endometriosis using the following formula.

(In the above formula, Y is the score, X ₁ is The expression value of TFAP2α , X ₂ is The expression value of NRG1 , X ₃ is The expression value of SMAD7 , X ₄ is expression value of TNS4 , X ₅ is expression value of HPRT1 , X ₆ is Expression value of CLTC , X ₇ is expression value of GUSB , X ₈ is expression value of TUBB , X ₉ means the expression value of PGK1 .)

It is expected that endometriosis can be diagnosed early by using the composition and information providing method for diagnosing endometriosis of the present invention.

1 is a Van diagram showing statistically significant Differentially Expressed Genes (DEGs) in tissue samples for each menstrual cycle (proliferative and secretory phase) of endometriosis patients and non-endometriosis patients.
2 is a diagram showing the scores calculated by applying the results of measuring the gene expression level of tissue samples of 119 patients to the draft calculation formula (Equation 1) for diagnosing endometriosis.
3 is a diagram showing the scores calculated by applying the results of measuring the gene expression level of tissue samples from 119 patients to the first modified formula (Equation 2) for diagnosing endometriosis.
4 is a diagram showing the scores calculated by applying the results of measuring the gene expression level of tissue samples from 119 patients to the final equation (Equation 3) for diagnosing endometriosis.
Figure 5 is a diagram showing a ROC (Receiver operating characteristic) curve applied to the final equation (Equation 3) the measurement result of the gene expression level of tissue samples of 119 patients, the vertical axis is sensitivity (sensitivity), the horizontal axis is specificity (specificity) , and the result shows that the sum of sensitivity and specificity is 0.034.

In order to achieve the object of the present invention, the present invention provides a substance for measuring the expression level of TFAP2α (transcription factor activator protein-2 alpha), NRG1 (neuregulin 1), SMAD7 (SMAD family member 7) and TNS4 (tensin 4) genes It provides a composition for diagnosis of endometriosis comprising a.

The TFAP2α , NRG1 , SMAD7 and TNS4 genes may each consist of the nucleotide sequence of SEQ ID NOs: 1 to 4, but is not limited thereto.

In the composition for diagnosing endometriosis of the present invention, the substance for measuring the expression level of the gene includes a primer, a probe, or an antisense nucleotide that specifically binds to the gene, but is not limited thereto.

In addition, the present invention provides a kit for diagnosing endometriosis comprising the composition.

The kit for diagnosing endometriosis may include a substance for measuring the expression levels of TFAP2α , NRG1 , SMAD7 and TNS4 genes, and may further include a user description describing optimal conditions for performing the reaction.

In addition, the present invention comprises the steps of isolating a nucleic acid from a biological sample isolated from the subject;

Using the isolated nucleic acid, TFAP2α (transcription factor activator protein-2 alpha), NRG1 (neuregulin 1), SMAD7 (SMAD family member 7), TNS4 (tensin 4), HPRT1 (hypoxanthine phosphoribosyltransferase 1), CLTC (clathrin heavy chain) ), calculating the expression values of GUSB (glucuronidase beta), TUBB (tubulin beta class I) and PGK1 (phosphoglycerate kinase 1) genes; and

It provides an information providing method for diagnosing endometriosis, including; substituting the calculated expression value of the gene into the values of X ₁ to X ₉ of the following formula.

(In the above formula, Y is the score, X ₁ is the expression value of TFAP2α , X ₂ is the expression value of NRG1 , X ₃ is the expression value of SMAD7 , X ₄ is the expression value of TNS4 , X ₅ is the expression value of HPRT1 , X ₆ is the expression value of CLTC , X ₇ is the expression value of GUSB , X ₈ is the expression value of TUBB , X ₉ is the expression value of PGK1 )

The 1, 2, 3, 4, 5, 6, 7, 8 and 9 genes may each consist of the nucleotide sequence of SEQ ID NOs: 1 to 9, but is not limited thereto.

The information providing method for diagnosing endometriosis of the present invention includes calculating the expression value of a gene in a biological sample from an individual. The biological sample includes a wide range of all biological fluids obtained from a subject, and preferably includes cells, tissues, biopsies, paraffin tissues, blood, serum, plasma, urine, and combinations thereof derived from a subject suspected of or diagnosed with endometriosis. It may be one or more selected from the group consisting of, but is not limited thereto. A method for obtaining a body fluid, tissue, biopsy, etc. from a mammal may use a conventional method known in the art.

In the information providing method of the present invention, the expression value of the gene is characterized in that it is calculated using nCounter flex, but is not limited thereto. The nCounter flex (NanoString Technologies ^® , USA) is a system that can quantify large-capacity gene expression in DNA, RNA, and protein samples extracted from the sample. It is possible to diagnose endometriosis by easily substituting it into the formula of

In the information providing method of the present invention, the score (Y) is weighted to each gene of TFAP2α (transcription factor activator protein-2 alpha), NRG1 (neuregulin 1), SMAD7 (SMAD family member 7) and TNS4 (tensin 4). It is characterized by giving

The weight is selected for the case of having the smallest p-value by repeatedly performing the operation of calculating the p-value after assigning a weight to each gene. It is characterized in that it is possible to effectively differentiate between endometriosis patients and non-endometriosis patients by using a formula in which different weights are assigned to each gene.

In the information providing method according to an embodiment of the present invention, if the score (Y) is 0.034 or less, endometriosis is diagnosed.

The score of 0.034 is the value (Y) calculated through the formula for diagnosing endometriosis of the present invention, and it is established as a condition that can best differentiate between endometriosis and non-endometriosis patients through several steps, and the p-value =0.001384, confirming that there is statistical significance in the difference between the endometriosis and non-endometriosis groups.

Hereinafter, the present invention will be described in detail by way of Examples. However, the following examples are merely illustrative of the present invention, and the content of the present invention is not limited thereto.

Example 1. Comparative analysis of gene expression in non-endometriosis patients and endometriosis patients

In order to select candidate genes that can be used for diagnosis of endometriosis, gene expression of non-endometriosis and endometriosis patients was compared and analyzed. As a sample for this purpose, endometrial tissue from endometriosis patients was used, and endometrial tissue from non-endometriosis patients was used as a control. The patient's tissues were provided by Gangnam Severance Hospital and Sinchon Severance Hospital, and were not used for purposes other than analysis for the present invention. 17 tissues per menstrual cycle (6 proliferative, 6 secretory, 5 other) in endometriosis patients under 40 years of age and 9 tissues per menstrual cycle in non-endometriosis patients (4 proliferative, 3 secretory, mRNA was isolated from the other 2) and sequencing was performed through Illumina NextSeq500 76 paired-end read sequencing. The nucleotide sequence analysis results were applied to the STAR program (Spliced Transcripts Alignment to a Reference, Dobin et al ., 2013. Bioinformatics 29: 15-21). After mapping RNA sequence data using Genome Reference Consortium Human Build 37 (GRCh37, hg19) as a reference genome, the expression value of each gene was obtained using the number of mapped reads. Expression values calculated using the STAR program were applied to the Cufflinks program to compare and analyze the expression levels of each gene.

Using the Cufflinks program (Trapnell et al ., 2010. Nat Biotechnol 28: 511-515), a total of 26 samples and gene expression by menstrual cycle were comparatively analyzed, and fold change (fold difference value) and q-value (significant value), respectively. probability value) was used to generate a statistically significant DEG (Differentially Expressed Gene) list. As a result, we found DEGs satisfying the criteria with fold change greater than ±2 and q-value less than 0.05. 382 DEGs in the 26 samples, 86 DEGs in the proliferative phase samples, and 438 DEGs in the secretory phase samples were confirmed. Among the DEGs of the 26 samples, 218 overlapping DEGs in each menstrual cycle were selected as genes capable of distinguishing the presence or absence of endometriosis regardless of the menstrual cycle ( FIG. 1 ).

Example 2. Selection of candidate gene sets for diagnosis of endometriosis

The expression values of 218 genes with differences in expression in non-endometriosis and endometriosis patients were applied to the Generalized Linear Modeling program (Friedman et al ., 2010. J Stat Softw 33: 1-22) to obtain cross-validation (cross-validation). validation) and modeling, 9 candidate genes that can best differentiate between non-endometriosis and endometriosis patients were selected (Table 1).

In addition, the 218 genes were divided into overexpression DEG and underexpression DEG, and the fold change value was large and the q-value was lowered, the higher the ranking (ranking) and sorting. When statistical analysis is performed on more than 20,000 genes at the same time, many errors may occur if statistical significance is tested using only p-value values. Therefore, in order to obtain more accurate and meaningful statistical analysis results, was used to analyze the results. As a result, a total of 14 overexpressed genes were selected, excluding 3 genes used in modeling and genes with a standard deviation greater than 100 among genes showing overexpression in endometriosis patients compared to non-endometriosis patients (Table 2). Among the genes showing low expression in endometriosis patients compared to non-endometriosis patients, when 9 genes used in modeling and genes with a standard deviation greater than 50 were excluded, a total of 21 genes with high ranking were selected (Table 3). ).

A total of 44 gene sets were selected as candidate genes for diagnosing endometriosis based on the results of Tables 1 to 3 above.

Example 3. Assay of candidate gene sets and final gene selection

Gene expression patterns in 119 tissue samples were further comparatively analyzed to test the selected set of 44 candidate genes. 79 tissues per menstrual cycle in endometriosis patients (37 proliferative phase, 35 secretory phases, 7 other) and 40 tissues per menstrual cycle in non-endometriosis patients (15 proliferative phase, 23 glands, 2 other) was used as a sample. Total RNA was isolated from each sample and the expression pattern was confirmed using nCounter flex (NanoString Technologies ^® , USA). nCounter flex is a system that derives the level of gene expression in a sample using a digital signal detection method. The advantage that results can be obtained even from degraded samples because amplification and library synthesis are not included in the experimental process. There is this. The result of nCounter flex Using the nSolver analysis program (NanoString Technologies ^® , USA), five housekeeping genes, HPRT1 (hypoxanthine phosphoribosyltransferase 1), CLTC (clathrin heavy chain), GUSB (glucuronidase beta), TUBB (tubulin beta class I) and PGK1 (phosphoglycerate kinase 1). Then, using the 'Advanced Analysis' function of the nSolver program, statistical values for gene expression comparison between non-endometriosis patients and endometriosis tissues were derived, and 6 genes with p-value of 0.05 or less were finally selected (Table 4).

Example 4. Derivation of formula for diagnosis of endometriosis

(1) Draft calculation formula

MMP25 (matrix metalloproteinase-25) , TFAP2A (transcription factor activator protein-2 alpha) , FCGR3B (Fc fragment of IgG receptor IIIb) , NRG1 (neuregulin 1) , Using SMAD7 (SMAD family member 7) , TNS4 (tensin 4) and five housekeeping genes used for normalization, the following draft calculation formula (Equation 1) for diagnosing endometriosis was designed.

Scores were calculated using a draft formula for tissue samples from 119 non-endometriosis and endometriosis patients. Since the distribution of score values between non-endometriosis and endometriosis patients did not satisfy normality, a Mann-Whitney U test was performed. As a result, the difference between the two groups was calculated as p-value = 0.2408 was confirmed (FIG. 2).

(2) First Modified Conception

The draft of the formula was modified in order to design a formula with a meaningful p-value. A p-value is obtained as a result of the Mann-Whitney U test. A lower p-value means that there is a difference in the distribution between the two groups. Therefore, by weighting each of the six genes located in the molecule as '0', the p-value when the expression value of each gene was not used in the formula was calculated and compared with the p-value for the draft calculation formula. .

As a result, the p-value for the draft formula including the expression values of all six genes located in the molecule was 0.2408, while the p-value for the formula excluding the expression value of the MMP25 gene was 0.2276, and the expression value of the FCGR3B gene was The p-value for the excluded calculation formula was found to be 0.01023. Therefore, when the expression values of MMP25 or FCGR3B genes are excluded, the p-value is lower, which means that there is a difference in the distribution between the two groups, that is, it means that endometriosis and non-endometriosis patients can be better distinguished. and FCGR3B genes were excluded from the formula, and the following first modified formula (Equation 2) was designed.

For 119 non-endometriotic and endometriotic tissue samples, scores were calculated using the first-order modification. Since the distribution of score values between non-endometriosis and endometriosis patients did not satisfy normality, a Mann-Whitney U test was performed. As a result, the difference between the two groups was calculated as p-value=0.00786. was confirmed (FIG. 3).

(3) Conception of the final expression

In order to design the calculation formula with the lowest p-value, the first correction formula was modified. After weighting each of the four genes located in the molecule, TFAP2A (transcription factor activator protein-2 alpha) , NRG1 (neuregulin 1) , SMAD7 (SMAD family member 7) , and TNS4 (tensin 4), the p-value was calculated. Iteratively, the following final formula (Equation 3) having the smallest p-value was conceived.

Scores were calculated using the above final formula for tissue samples from 119 non-endometriosis patients and endometriosis patients. Since the distribution of score values between non-endometriosis and endometriosis patients did not satisfy normality, a Mann-Whitney U test was performed. was confirmed (FIG. 4).

The final formula was applied to 119 samples to generate a ROC (Receiver operating characteristic) curve (Robin et al ., 2011. BMC Bioinformatics 12), and the sensitivity and specificity were analyzed (FIG. 5). Sensitivity refers to the case of diagnosing endometriosis patients as endometriosis, and specificity refers to diagnosing endometriosis patients as non-endometriosis patients. As a result, it was confirmed that the sensitivity was 0.620 (49/79) and the specificity was 0.775 (31/40) (Table 5).

In addition, it was confirmed that the score (Y) calculated by applying the above final formula to the samples of endometriosis patients and non-endometriosis patients was 0.034, and if the score of each sample was 0.034 or less, it was confirmed that endometriosis could be diagnosed.

Therefore, it was found that patients with endometriosis and non-endometriosis patients could be distinguished by using the final formula of the present invention.

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Claims (6)

A composition for diagnosing endometriosis, comprising a substance measuring the expression level of TFAP2α (transcription factor activator protein-2 alpha), NRG1 (neuregulin 1), SMAD7 (SMAD family member 7) and TNS4 (tensin 4) genes. The composition for diagnosing endometriosis according to claim 1, wherein the substance for measuring the expression level of the gene comprises a primer, a probe or an antisense nucleotide that specifically binds to the gene. A kit for diagnosing endometriosis comprising the composition of claim 1 or 2. isolating the nucleic acid from the biological sample isolated from the subject;
Using the isolated nucleic acid, TFAP2α (transcription factor activator protein-2 alpha), NRG1 (neuregulin 1), SMAD7 (SMAD family member 7) , TNS4 (tensin 4), HPRT1 (hypoxanthine phosphoribosyltransferase 1), CLTC (clathrin heavy chain) ), calculating the expression values of GUSB (glucuronidase beta), TUBB (tubulin beta class I) and PGK1 (phosphoglycerate kinase 1) genes; and
Substituting the calculated expression value of the gene into the X ₁ to X ₉ values of the following formula; A method for providing information for diagnosing endometriosis, including:

(In the above formula, Y is the score, X ₁ is The expression value of TFAP2α , X ₂ is The expression value of NRG1 , X ₃ is The expression value of SMAD7 , X ₄ is expression value of TNS4 , X ₅ is expression value of HPRT1 , X ₆ is Expression value of CLTC , X ₇ is expression value of GUSB , X ₈ is expression value of TUBB , X ₉ means the expression value of PGK1 .) The method of claim 4, wherein the gene expression value is calculated using nCounter flex. The information providing method for diagnosing endometriosis according to claim 4, wherein when the score is 0.034 or less, endometriosis is diagnosed.

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