Biological combined marker for predicting radiotherapy sensitivity of esophageal squamous cell carcinoma and application of biological combined marker
By using EZH2, ENOSF1 and PGM5 as combined biomarkers, the radiotherapy sensitivity of patients with esophageal squamous cell carcinoma was solved, and the problem of difficulty in predicting radiotherapy sensitivity of ESCC patients in the prior art was solved, achieving a more accurate prediction effect.
Patent Information
- Application Number
- CN202411814837.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-11
- Publication Date
- 2025-02-11
AI Technical Summary
The prior art is difficult to effectively predict the sensitivity of radiotherapy in patients with esophageal squamous cell carcinoma (ESCC), resulting in the effectiveness of radiotherapy is often limited.
Three biomarkers, EZH2, ENOSF1 and PGM5, were used as joint markers, and their expression levels were detected by immunohistochemical staining, and a predictive model was constructed to evaluate the radiotherapy sensitivity of ESCC patients.
It improves the prediction accuracy of radiotherapy sensitivity in ESCC patients, significantly improves the area under the curve (AUC) of the prediction model to 0.989, which is better than the prediction performance of using EZH2, ENOSF1 or PGM5 alone as markers.
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Figure CN119414020A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of biomedicine technology, and specifically is a biological joint marker for predicting the radiotherapy sensitivity of esophageal squamous cell carcinoma (ESCC) and its application. The biological joint marker involves three biomarkers: EZH2, ENOSF1, and PGM5. Background Art
[0002] Esophageal cancer is the eighth most common cancer in the world and the sixth leading cause of cancer-related death. Among them, esophageal squamous cell carcinoma (ESCC) is the main histological type of esophageal cancer in my country. It is a tumor with high invasiveness and low survival rate, with a 5-year overall survival rate of less than 30%.
[0003] Radiotherapy (RT) is one of the main treatment options for esophageal squamous cell carcinoma (ESCC), but the effect of radiotherapy is often limited due to the inherent radioresistance of ESCC cells. Therefore, finding biomarkers that predict the sensitivity of ESCC to radiotherapy is of great significance to promote the radiotherapy effect of ESCC patients in clinical practice.
[0004] Currently, publicly published literature has revealed the correlation between EZH2 and ESCC chemoradiotherapy sensitivity, but ROC curve analysis has not been performed to clarify the sensitivity and specificity of EZH2 in predicting radiotherapy efficacy, nor has the optimal cutoff value for predicting ESCC radiotherapy sensitivity based on high or low expression of EZH2 been determined. Due to the complexity of the molecular network of EZH2 regulating radiotherapy sensitivity, whether the combination of EZH2 and its downstream molecules for predicting ESCC radiotherapy sensitivity is better than using EZH2 alone remains to be determined. Summary of the invention
[0005] The purpose of the present invention is to provide a biomarker for predicting the radiotherapy sensitivity of esophageal squamous cell carcinoma and its application, so as to solve the shortcomings of the above-mentioned prior art. The biomarker described in the present invention can predict the radiotherapy sensitivity of human esophageal squamous cell carcinoma tissue, and has important clinical value for evaluating the radiotherapy sensitivity of ESCC and guiding clinical personalized treatment.
[0006] In a first aspect, the present invention discloses a biomarker for predicting the radiotherapy sensitivity of esophageal squamous cell carcinoma, wherein the biomarker comprises EZH2, ENOSF1 and PGM5.
[0007] Furthermore, among the biomarkers, the higher the expression level of EZH2 in the tumor tissue of patients with esophageal squamous cell carcinoma, the lower the sensitivity of the patient to radiotherapy; the higher the expression levels of ENOSF1 and PGM5 in the tumor tissue of patients with ESCC esophageal squamous cell carcinoma, the higher the sensitivity of the patient to radiotherapy.
[0008] In a second aspect, the present invention discloses an application of the combined biomarker, and a prediction model for predicting the radiotherapy sensitivity of esophageal squamous cell carcinoma is constructed based on the combined biomarker of the present invention.
[0009] Furthermore, the calculation formula of the prediction model is:
[0010] logit(P)=9.992+2.898×EZH2-3.170×ENOSF1-2.613×PGM5
[0011] Among them, P is the probability of event occurrence, that is, the probability of judging the sensitivity of esophageal squamous cell carcinoma patients to radiotherapy and whether they will relapse after radiotherapy. EAH2, ENOSF1 and PGM5 represent the expression scores of EZH2, ENOSF1 and PGM5, respectively. The scores are based on the results of immunohistochemistry experiments and are quantified using the IRS scoring system (scoring range: 0-12).
[0012] Furthermore, the expression scores of EAH2, ENOSF1 and PGM5 were determined by immunohistochemical staining to detect the expression of EAH2, ENOSF1 and PGM5. The IRS score was used to determine the expression score based on the staining intensity and the percentage of positively stained cells. The specific scoring calculation method is as follows:
[0013] 1) The staining intensity is divided into four levels:
[0014] 0 point: no positive staining; 1 point: light yellow; 2 points: brownish yellow; 3 points: brownish brown.
[0015] 2) Divide the percentage of positively stained cells into four intervals:
[0016] 1 point: <5% of cells were positive; 2 points: 5%-25% of cells were positive; 3 points: 25%-75% of cells were positive; 4 points: >75% of cells were positive.
[0017] 3) Scoring formula: IRS = staining intensity × percentage of positive cells, the score range is 0-12 points.
[0018] 4) For EZH2 expressed in the nucleus, the protein expression score was calculated according to the scoring formula; for ENOSF1 and PGM5 expressed in the cytoplasm, if they could be detected in the immunohistochemical staining, that is, as long as there were cells with positive staining, the proportion of positive cells was 100%, that is, 4 points, and the expression scores of ENOSF1 and PGM5 were calculated according to the above scoring formula.
[0019] Furthermore, the immunohistochemical staining method comprises the following specific steps:
[0020] Step 1: Tissue dewaxing and antigen retrieval:
[0021] Paraffin-embedded ESCC tumor tissue samples were sliced at 4 μm thickness and baked at 60°C for 40 min. The slices were then deparaffinized with xylene and dehydrated with gradient ethanol, heated in ethylenediaminetetraacetic acid buffer in a microwave oven for 10 min, cooled for 5 min, and then heated for another 5 min;
[0022] Step 2: Immunohistochemical staining using streptavidin-peroxidase (SP):
[0023] 1) Block the activity of endogenous peroxidase with 3% hydrogen peroxide, and then incubate the sections with primary antibodies against EZH2, ENOSF1, and PGM5 at 4°C overnight (incubation time not less than 8 hours);
[0024] 2) Then, incubate with horseradish peroxidase-conjugated anti-mouse or anti-rabbit secondary antibody at room temperature for 1 hour;
[0025] 3) Treat with 3,3'-diaminobenzidine tetrahydrochloride (DAB dye) for 1-5 minutes, and optimize according to the staining intensity;
[0026] 4) After staining, rinse the sections with water;
[0027] 5) Counterstain the sections with hematoxylin for about 0.5-1 minute, and rinse with water for about 15 minutes to reverse the blue color;
[0028] 6) Then, use an oven to dry the slices and mount them with neutral gum;
[0029] 7) Finally, the staining results were observed using a white light microscope. The nuclei of cells stained with hematoxylin appeared blue, and the nuclei of cells stained positively with 3,3'-diaminobenzidine tetrahydrochloride appeared yellow.
[0030] Beneficial effects: The invention uses EZH2, ENOSF1, and PGM5 as a combined biomarker for the first time to predict the radiotherapy sensitivity of esophageal squamous cell carcinoma. The present invention detects the expression of EZH2, ENOSF1, and PGM5 in tissue samples of ESCC patients, and draws a comprehensive ROC curve of EZH2, ENOSF1, and PGM5 as a combined marker. Compared with the ROC curve drawn using EZH2 as a marker alone, ENOSF1 as a marker alone, or PGM5 as a biomarker alone, the area under the curve of the ROC curve of EZH2, ENOSF1, and PGM5 as a combined marker is 0.989, which is significantly higher than the area under the curve of using EZH2 as a marker alone, ENOSF1 as a marker alone, or PGM5 as a biomarker alone. This shows that compared with using EZH2 alone as a marker, ENOSF1 alone as a marker, or PGM5 alone as a marker to predict ESCC radiotherapy sensitivity, using EZH2, ENOSF1, and PGM5 as a combined marker to predict ESCC radiotherapy sensitivity has more accurate prediction performance. Using EZH2, ENOSF1, and PGM5 as a combined marker has broad prospects and clinical application value. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 This is the ROC curve of using EZH2 alone as a biomarker in Example 2 of the present invention;
[0032] Figure 2 This is the ROC curve of using ENOSF1 alone as a biomarker in Example 2 of the present invention;
[0033] Figure 3 This is the ROC curve of using PGM5 alone as a biomarker in Example 2 of the present invention;
[0034] Figure 4 This is the ROC curve of using EZH2, ENOSF1 and PGM5 together as biological joint markers in Example 2 of the present invention;
[0035] Figure 5 The figure is a comparison of the AUC values of the ROC curves when EZH2, ENOSF1, and PGM5 are used in combination as biomarkers and when EZH2, ENOSF1, and PGM5 are used alone as biomarkers in Example 2 of the present invention. DETAILED DESCRIPTION
[0036] The technical solution of the present invention is described in detail below through embodiments, but the protection scope of the present invention is not limited to the embodiments.
[0037] Since EZH2 regulates multiple mechanisms such as tumor proliferation, migration, and radiotherapy, the present invention uses bioinformatics technology to find downstream target genes related to EZH2 and the pathway regulating radiotherapy sensitivity for the construction of biological joint markers. Combined with the radiotherapy and chemotherapy sensitive and resistant patient cohorts and ChIPseq database provided by GSE199630, the present invention analyzed and obtained EZH2 downstream target genes related to radiotherapy sensitivity: ENOSF1 and PGM5. Further collection of ESCC radiotherapy patient cohorts from the First Affiliated Hospital of Anhui Medical University, and immunohistochemical analysis, found that EZH2 expression was negatively correlated with the expression of ENOSF1 and PGM5, and high expression of EZH2 was associated with poor radiotherapy efficacy, while high expression of ENOSF1 and PGM5 was associated with better radiotherapy effects.
[0038] Embodiment 1:
[0039] This example discloses a method for calculating the expression levels of EZH2, ENOSF1, and PGM5 using immunohistochemical staining, and the specific steps are as follows:
[0040] Step 1: Tissue dewaxing and antigen retrieval:
[0041] Paraffin-embedded ESCC tumor tissue samples were sliced at 4 μm thickness and baked at 60°C for 40 min. The sections were then deparaffinized with xylene and dehydrated with gradient ethanol. The samples were heated in ethylenediaminetetraacetic acid (EDTA) buffer (pH 9.0) in a microwave oven for 10 min, cooled for 5 min, and then heated for another 5 min.
[0042] Step 2: Immunohistochemical staining using streptavidin-peroxidase (SP) method:
[0043] 1) First, the activity of endogenous peroxidase was blocked with 3% hydrogen peroxide (3 g of hydrogen peroxide per 100 ml of solution), and then the sections were incubated with primary antibodies against EZH2, ENOSF1, and PGM5 at 4°C overnight (incubation time was not less than 8 hours);
[0044] 2) Incubate the sections with horseradish peroxidase-conjugated anti-mouse or anti-rabbit secondary antibodies at room temperature for 1 hour;
[0045] 3) After that, the stain was treated with 3,3'-diaminobenzidine tetrahydrochloride (DAB dye) for 1-5 minutes and then optimized according to the staining intensity;
[0046] 4) After staining, wash the sections with water;
[0047] 5) Counterstain the sections with hematoxylin for about 0.5-1 minute, and rinse with water for about 15 minutes to reverse the blue color;
[0048] 6) Then, use an oven to dry the slices; and mount them with neutral gum;
[0049] 7) Finally, the staining results were observed using a white light microscope. The nuclei of cells stained with hematoxylin appeared blue, and the nuclei of cells stained positively with 3,3'-diaminobenzidine tetrahydrochloride appeared yellow.
[0050] Antibody information used in this example:
[0051] Primary antibody against EZH2: mouse anti-EZH2 monoclonal antibody, used at a dilution ratio of 1:200 (1 μl antibody: 200 ml primary antibody diluent), from BD Biosciences, product number: 612666.
[0052] Primary antibody against ENOSF1: rabbit anti-ENOSF1, ENOSF1 polyclonal antibody, used at a dilution ratio of 1:100 (1 μl antibody: 100 ml primary antibody diluent), from ThermoFisher scientific, product number: PA5-61602.
[0053] Primary antibody against PGM5: mouse anti-PGM5 polyclonal antibody, used at a dilution ratio of 1:100 (1 μl antibody: 100 ml primary antibody diluent), from Novus Biologcals, product number: NBP3-13996.
[0054] Horseradish peroxidase-conjugated anti-mouse secondary antibody: from Zhongshan Jinqiao Servicebio, product number: PV-6002, just immerse the sliced tissue when using.
[0055] Horseradish peroxidase-conjugated anti-rabbit secondary antibody: from Zhongshan Jinqiao, product number: PV-6001, just immerse the sliced tissue when using.
[0056] Step 3: IRS scoring method to determine the expression levels of EZH2, ENOSF1, and PGM5
[0057] 1) The staining intensity was divided into four levels: 0 point: no positive staining (negative), 1 point: light yellow (weakly positive), 2 points: brownish yellow (positive), 3 points: brownish brown (strongly positive).
[0058] 2) Divide the percentage of positively stained cells into four intervals:
[0059] 1 point: <5% of cells were positive, 2 points: 5%-25% of cells were positive, 3 points: 25%-75% of cells were positive, 4 points: >75% of cells were positive.
[0060] 3) Scoring formula: IRS = staining intensity × percentage of positive cells, the score range is 0-12 points.
[0061] For example, when the staining intensity is 3 points (brown, strongly positive) and the positive cell ratio is 4 points (>75% of cells are positive), IRS = 3 × 4 = 12 points.
[0062] 4) For EZH2 expressed in the nucleus, the protein expression score is calculated according to the above scoring formula. For ENOSF1 and PGM5 expressed in the cytoplasm, as long as ENOSF1 and PGM5 can be detected in the tissue, that is, there are positively stained cells, the percentage of positive cells is defaulted to 100% (i.e., 4 points), and the protein expression score is calculated according to the above scoring formula.
[0063] Example 2
[0064] This example discloses the construction and application of a combined biomarker prediction model of EZH2, ENOSF1, and PGM5.
[0065] 1. Experimental materials and methods:
[0066] Tumor tissues of ESCC patients who underwent postoperative radiotherapy were collected from the First Affiliated Hospital of Anhui Medical University. The expression of EZH2, ENOSF1, and PGM5 in the ESCC tumor tissue samples was detected by the method provided in Example 1, and their scores were calculated.
[0067] 2. Statistical analysis:
[0068] 1) Based on the scoring results, a formula was constructed by multivariate logistic regression to use EZH2, ENOSF1, and PGM5 as combined biomarkers to predict the radiotherapy sensitivity of ESCC patients:
[0069] logit(P)=9.992+2.898×EZH2-3.170×ENOSF1-2.613×PGM5
[0070] Among them, P is the probability of event occurrence, which is used to judge the radiosensitivity of ESCC patients and the probability of recurrence after radiotherapy. EAH2, ENOSF1 and PGM5 represent the expression scores of EZH2, ENOSF1 and PGM5, respectively. The scores are based on the results of immunohistochemistry experiments and are quantified using the IRS scoring system (scoring range: 0-12)
[0071] 2) Plotting ROC curves using EZH2, ENOSF1, or PGM5 as markers alone or using EZH2, ENOSF1, and PGM5 as combined markers
[0072] The ROC curve is the receiver operating characteristic curve, also known as the sensitivity curve. Each point on the curve reflects the same sensitivity. They are all responses to the same test result and are the results obtained under several different judgment criteria. The curve is drawn with the true positive rate (sensitivity) as the vertical axis and the false positive rate (1-specificity) as the horizontal axis.
[0073] The ROC curve usually uses the area under the curve (AUC) to evaluate the diagnostic value. The larger the AUC, the more diagnostic value it has. It is generally believed that an AUC between 0.5 and 0.7 has a low diagnostic value, between 0.7 and 0.9 has a medium diagnostic value, and greater than 0.9 has a high diagnostic value.
[0074] According to the results of immunohistochemistry, ROC curves were drawn to evaluate the sensitivity and specificity of predicting radiotherapy sensitivity using EZH2, ENOSF1 or PGM5 as markers alone or using EZH2, ENOSF1 and PGM5 as combined markers. Then, a plot was drawn with specificity as the abscissa and sensitivity as the ordinate to determine the predictive value of the radiotherapy sensitivity detection model using EZH2, ENOSF1 or PGM5 as markers or using EZH2, ENOSF1 and PGM5 as combined markers.
[0075] The ROC curve is plotted as follows: Figures 1 to 5 : Figure 1 This is the ROC curve of using EZH2 alone as a biomarker in Example 2 of the present invention; Figure 2 This is the ROC curve of using ENOSF1 alone as a biomarker in Example 2 of the present invention; Figure 3 This is the ROC curve of using PGM5 alone as a biomarker in Example 2 of the present invention; Figure 4 This is the ROC curve of using EZH2, ENOSF1 and PGM5 together as biological joint markers in Example 2 of the present invention; Figure 5 The AUC values of the ROC curves of the combined use of EZH2, ENOSF1, and PGM5 as biomarkers and the use of EZH2, ENOSF1, and PGM5 as biomarkers in Example 2 of the present invention are compared. The plotted results are: the area under the curve detected by using EZH2 as a marker alone is 0.88; the area under the curve detected by using ENOSF1 as a marker alone is 0.867, the area under the curve detected by using PGM5 as a marker alone is 0.871, and the area under the curve detected by using EZH2, ENOSF1, and PGM5 as a combined marker is 0.989. It can be seen that the area under the curve and specificity of EZH2, ENOSF1, and PGM5 as a combined marker for detecting ESCC are significantly better than using EZH2, ENOSF1, or PGM5 as a single marker to predict the radiotherapy sensitivity of ESCC.
[0076] 3. Interpretation and clinical application of the prediction model
[0077] In the present invention, the P value calculated by the model indicates the value of predicting the radiotherapy sensitivity and recurrence of ESCC patients. Taking the detection of the present invention as an example: Figure 4 As shown, the expression scores of EZH2, ENOSF1 and PGM5 are used. The prediction model formula is:
[0078] logit(P)=9.992+2.898×EZH2-3.170×ENOSF1-2.613×PGM5
[0079] The calculated P value predicts the radiotherapy sensitivity of ESCC patients and the AUC value of recurrence after radiotherapy, reaching 0.989, indicating that the combined biomarker can effectively predict the radiotherapy sensitivity of ESCC patients and provide key guidance for clinical practice. Figure 4 The optimal cutoff value corresponding to the P value of the model is 0.661, which means that 0.661 is the critical value of the combined biomarker to predict the critical state of high and low radiotherapy sensitivity of ESCC patients. When P>=0.661, ESCC patients have low radiotherapy sensitivity and high probability of recurrence after radiotherapy; when P<=0.661, ESCC patients have high radiotherapy sensitivity and low probability of recurrence after radiotherapy.
[0080] That is, the prediction model of the present invention is:
[0081] logit(P)=9.992+2.898×EZH2-3.170×ENOSF1-2.613×PGM5
[0082] Among them, the P value is the probability of the event, which is the probability of ESCC patients having high or low sensitivity to radiotherapy and recurrence after radiotherapy. When P>=0.661, ESCC patients have low sensitivity to radiotherapy and high probability of recurrence after radiotherapy; when P<=0.661, ESCC patients have high sensitivity to radiotherapy and low probability of recurrence after radiotherapy. EAH2, ENOSF1 and PGM5 represent the expression scores of EZH2, ENOSF1 and PGM5, respectively. The scores are based on the results of immunohistochemistry experiments and are quantified using the IRS scoring system (scoring range: 0-12).
[0083] Clinicians use the P value calculated by the model for evaluation. First, they can accurately predict the efficacy of radiotherapy for ESCC patients, optimize their clinical treatment strategies and programs, and provide more targeted and personalized solutions for patients with different radiotherapy sensitivities. For example: for patients with high P values: standard radiotherapy programs can be adopted to improve treatment efficiency; for patients with low P values: combined chemotherapy, immunotherapy or targeted therapy and other therapies are recommended to reduce the risk of recurrence, and pay attention to continuous monitoring of the prognosis of such patients. Secondly, it also shows that the prediction model of the present invention can also stratify and classify patients, help clinicians manage patients with different risks, and formulate different follow-up treatments and follow-up plans. At the same time, it also avoids unnecessary treatments and reduces waste of resources.
[0084] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the present invention itself. Various changes may be made to the form and details without departing from the spirit and scope of the present invention.
Claims
1. A biomarker for predicting radiotherapy sensitivity of esophageal squamous cell carcinoma, characterized in that: The biomarkers include EZH2, ENOSF1 and PGM5.
2. The biomarker according to claim 1, characterized in that: The higher the expression level of EZH2 in the tumor tissue of patients with esophageal squamous cell carcinoma, the lower the sensitivity of the patients to radiotherapy; the higher the expression levels of ENOSF1 and PGM5 in the tumor tissue of patients with esophageal squamous cell carcinoma, the higher the sensitivity of the patients to radiotherapy.
3. A prediction model for predicting the radiotherapy sensitivity of esophageal squamous cell carcinoma, characterized in that: The prediction model is constructed based on the biological combination markers described in claim 1.
4. The prediction model according to claim 3, characterized in that The calculation formula of the prediction model is: logit(P)=9.992+2.898×EZH2-3.170×ENOSF1-2.613×PGM5 Among them, P is the probability of event occurrence, that is, the probability of judging the sensitivity of patients with esophageal squamous cell carcinoma to radiotherapy and whether they will relapse after radiotherapy. EAH2, ENOSF1 and PGM5 represent the expression scores of EZH2, ENOSF1 and PGM5, respectively. The scores are based on the results of immunohistochemistry experiments and are quantified using the IRS scoring system.
5. The prediction model according to claim 4, characterized in that The expression scores of EAH2, ENOSF1 and PGM5 were determined by immunohistochemical staining and IRS score according to the staining intensity and the percentage of positively stained cells. The specific score calculation method is as follows: 1) The staining intensity is divided into four levels: 0 point: no positive staining; 1 point: light yellow; 2 points: brownish yellow, 3 points: brownish brown; 2) Divide the percentage of positively stained cells into four intervals: 1 point: <5% of cells are positive; 2 points: 5%-25% of cells are positive; 3 points: 25%-75% of cells are positive; 4 points: >75% of cells are positive; 3) Scoring formula: IRS = staining intensity × percentage of positive cells, the score range is 0-12 points; 4) For EZH2 expressed in the nucleus, the protein expression score was calculated according to the scoring formula; for ENOSF1 and PGM5 expressed in the cytoplasm, if they could be detected in the immunohistochemical staining, that is, as long as there were cells with positive staining, the proportion of positive cells was 100%, that is, 4 points, and the expression scores of ENOSF1 and PGM5 were calculated according to the above scoring formula.
6. The prediction model according to claim 5, characterized in that The immunohistochemical staining method comprises the following specific steps: Step 1: Tissue dewaxing and antigen retrieval: Paraffin-embedded ESCC tumor tissue samples were sliced at 4 μm thickness and baked at 60°C for 40 min. The slices were then deparaffinized with xylene and dehydrated with gradient ethanol. The slices were heated in ethylenediaminetetraacetic acid buffer in a microwave oven for 10 min, cooled for 5 min, and then heated for another 5 min. Step 2: Immunohistochemical staining using streptavidin-peroxidase: 1) The activity of endogenous peroxidase was blocked with 3% hydrogen peroxide, and the sections were then incubated with primary antibodies against EZH2, ENOSF1, and PGM5 at 4°C overnight; 2) Then, incubate with horseradish peroxidase-conjugated anti-mouse or anti-rabbit secondary antibody at room temperature for 1 hour; 3) Treat with 3,3'-diaminobenzidine tetrahydrochloride for 1-5 minutes, and optimize according to the staining intensity; 4) After staining, rinse the sections with water; 5) Counterstain the sections with hematoxylin for about 0.5-1 minute, and rinse with water for about 15 minutes to reverse the blue color; 6) Then, use an oven to dry the slices and mount them with neutral gum; 7) Finally, the staining results were observed using a white light microscope. The nuclei of cells stained with hematoxylin appeared blue, and the nuclei of cells stained positively with 3,3'-diaminobenzidine tetrahydrochloride appeared yellow.