WO2023050642A1 - Application of alpha-fetoprotein or carcinoembryonic antigen combined with gene marker in tumor diagnosis - Google Patents

Abstract

Disclosed are an application of an alpha-fetoprotein or carcinoembryonic antigen combined with a gene marker in tumor diagnosis. In the present invention, the accuracy of colorectal cancer screening is improved by combining the alpha-fetoprotein or the carcinoembryonic antigen with the gene marker, and combats the disadvantage of low accuracy in colorectal cancer screening using alpha-fetoprotein or the carcinoembryonic antigen individually.

Description

Application of alpha-fetoprotein or carcinoembryonic antigen combined gene markers in tumor diagnosis technical field

The invention belongs to the field of disease diagnosis, and in particular relates to the application of alpha-fetoprotein or carcinoembryonic antigen combined with gene markers in tumor diagnosis.

Background technique

Colorectal cancer (CRC) is one of the most common malignant tumors worldwide. It is estimated that the age-standardized incidence rate of CRC in the world in 2020 is 19.5/100,000, and the mortality rate is 9.0/100,000. The incidence of CRC is relatively high in developed countries. In the United States, the age-standardized incidence rate of CRC in the past five years is about 38.7/100,000, and the mortality rate is 13.9/100,000. The practical experience of many countries shows that the adoption of effective colorectal cancer screening strategies can reduce the disease burden of colorectal cancer (Research Status and Reflections on Colorectal Cancer Screening Strategies, Chinese Journal of General Practice, September 2021).

As one of the screening indicators for CRC, carcinoembryonic antigen (CEA) is a tumor-associated antigen first extracted from colon cancer and embryonic tissues by Gold and Freedman in 1965. It is an acidic human embryonic antigen characteristic. Glycoprotein, present on the surface of cancer cells differentiated from endoderm cells, is a structural protein of the cell membrane. Formed in the cytoplasm, secreted out of the cell through the cell membrane, and then into the surrounding body fluids. Therefore, it can be detected from various body fluids and excreta such as serum, cerebrospinal fluid, breast milk, gastric juice, pleural effusion, urine, and feces. CEA has played an important clinical role in the differential diagnosis, condition monitoring, and curative effect evaluation of colorectal cancer.

Alpha-fetoprotein (AFP) is a tumor marker commonly used in tumor screening, and is widely used in the diagnosis of liver cancer and other tumors.

However, the accuracy of CEA or AFP for the diagnosis of colorectal cancer is not high. In order to improve the accuracy of CEA or AFP in the diagnosis of colorectal cancer, the present invention is proposed.

Contents of the invention

In order to overcome the deficiencies of the prior art, the present invention provides the application of alpha-fetoprotein or carcinoembryonic antigen combined with gene markers in tumor diagnosis.

Technical scheme of the present invention is as follows:

Application of a gene marker combined with alpha-fetoprotein or carcinoembryonic antigen in the preparation of a tumor diagnostic kit; specifically, the gene marker combined with alpha-fetoprotein is miR-3934-5p, and the gene marker combined with carcinoembryonic antigen is miR- 609.

A serum detection kit for early diagnosis of colorectal cancer, containing reagents for detecting alpha-fetoprotein or carcinoembryonic antigen in serum and their combined detection gene markers, specifically, the combined detection gene marker of alpha-fetoprotein is miR-3934 The combined detection gene marker of -5p and carcinoembryonic antigen is miR-609.

Beneficial technical effects:

The present invention improves the accuracy of colorectal cancer screening by combining miR-609 with carcinoembryonic antigen or miR-3934-5p with alpha-fetoprotein, and overcomes the accuracy of colorectal cancer screening when carcinoembryonic antigen or alpha-fetoprotein is used alone Not high enough.

Description of drawings

Figure 1 is a comparison of the serum levels of CEA, AFP, miR-609 and miR-3934-5p in colorectal cancer and healthy people; among them, miR-609 and miR-3934-5p were determined by agarose gel electrophoresis, and the internal reference was β -Actin, randomly divide 40 rectal cancer samples or healthy population samples in the training set into four parts, and mix 10 samples in each group into one part. In the electrophoresis results, A, C, E, and G correspond to the mixed samples of healthy people, respectively, and B and D , F, H respectively correspond to mixed samples of rectal cancer;

Figure 2 is the ROC curve of CEA alone in the training set to distinguish colorectal cancer from healthy people;

Figure 3 is the ROC curve of AFP alone in the training set to diagnose and distinguish colorectal cancer and healthy people;

Figure 4 is the ROC curve of CEA combined with miR-609 in the training set to diagnose and distinguish colorectal cancer and healthy people;

Figure 5 is the ROC curve of CEA combined with miR-3934-5p in the training set to diagnose and distinguish colorectal cancer and healthy people;

Figure 6 is the ROC curve of AFP combined with miR-609 in the training set to diagnose and distinguish colorectal cancer and healthy people;

Figure 7 is the ROC curve of AFP combined with miR-3934-5p in the training set to diagnose and distinguish colorectal cancer and healthy people.

Detailed ways

The substantive content of the present invention will be described in detail below through specific examples, but the protection scope of the present invention cannot be limited thereto.

1. Test materials

Total RNA extraction kit was purchased from Invitrogen, USA. The reverse transcription kit was purchased from Thermo Fisher Scientific. RT-PCR measuring instrument was purchased from Qiagen, Germany. RT-PCR primers were synthesized by Jiman Biotechnology (Shanghai) Co., Ltd.

2. Test method

1. General information

Colorectal cancer samples: select 120 patients with pathologically diagnosed colorectal cancer from the First Affiliated Hospital of Nanjing Medical University from 2018 to 2020; healthy population samples: select 120 healthy people from the First Affiliated Hospital of Nanjing Medical University from 2018 to 2020 . The age distribution of the two groups of samples is highly similar, P>0.05, no statistical significance.

Inclusion criteria: ①Confirmed by imaging examinations such as computed tomography (CT) or pathological examination; ②No anti-tumor treatment such as radiotherapy and chemotherapy before the test; ③Age ≥ 18 years old. Exclusion criteria: ①combined with malignant tumors in other parts; ②pregnant or lactating women; ③combined with immune system diseases, blood system diseases, etc.

2. Sample grouping

Training set: 40 samples were randomly selected from colorectal cancer samples and healthy population samples respectively to form a training set, with a total sample size of 80 cases; validation set: the remaining colorectal cancer samples and healthy population samples constituted a validation set, with a total sample size of 160 cases.

3. Determination of serum CEA and AFP

Take 5mL of venous blood on an empty stomach, centrifuge at 2500r/min for 5min, separate the serum, use a fully automatic biochemical analyzer and supporting original reagents, and measure the concentrations of CEA and AFP in strict accordance with the instructions.

4. Determination of expression levels of serum miR-609 and miR-3934-5p

5 mL of venous blood was drawn on an empty stomach, centrifuged at 2500 r/min for 5 min, serum was separated, and total RNA was extracted with a total RNA extraction kit. 2 μg of total RNA was used to synthesize cDNA in a reverse transcription kit. The cDNA was taken and amplified in a PCR amplification instrument. The reaction conditions were 94°C for 15 minutes for pre-denaturation, 60°C for 30 s annealing, and 72°C for 30 s for 40 cycles. The relative quantitative method was used to measure the Ct value of the PCR product of the target gene and GAPDH, and the relative expression of the target gene was calculated by 2 ^-ΔΔCt . Three replicate wells were set up for each experiment, and the experiment was repeated three times.

miR-609 forward primer sequence: 5'-CGACGTGCACTGCACCAGC-3';

miR-609 reverse primer sequence: 5'-AGTCACTGCACAGTCAC-3';

miR-3934-5p forward primer sequence: 5'-GCCAGCTCCTACATCTCAGC-3';

miR-3934-5p reverse primer sequence: 5'-TGACTACCAGGTTTGAAGA-3';

GAPDH forward primer sequence: 5'-TGATGACATCAAGAAGGTGGTGAAG-3';

GAPDH reverse primer sequence: 5'-TCCTTGGAGGCCCAGTGGGCCAT-3'.

5. Statistical processing

SPSS 19.0 was used to process the data. All measurement data were tested for normality and homogeneity of variance. The data that conformed to the normal distribution were expressed as mean ± deviation. Pairwise comparisons were made using the t test. SPSS 19.0 was used to draw receiver operating characteristic (ROC) curves of serum CEA or AFP alone and combined with serum miR-609 or miR-3934-5p to distinguish colorectal cancer from healthy people, and calculate the area under the curve (AUC), and AUC was used to evaluate the diagnostic value of CEA or AFP alone and combined with serum miR-609 or miR-3934-5p for colorectal cancer and healthy subjects. AUC≤0.5 means no diagnostic value, 0.5<AUC≤0.7 means low diagnostic accuracy, 0.7<AUC≤0.9 means better diagnostic accuracy, AUC≥0.9 means highest diagnostic accuracy, P<0.05 means statistically significant difference .

3. Test results

1. Comparison of serum levels of CEA, AFP, miR-609 and miR-3934-5p in colorectal cancer and healthy people

In the training set, the levels of CEA, AFP, miR-609 and miR-3934-5p were significantly up-regulated in the serum of colorectal cancer and healthy people, and the up-regulation folds are shown in Table 1 and Figure 1.

Table 1 The target markers are up-regulated in colorectal cancer serum relative to healthy people

the	CEA	AFP	miR-609	miR-3934-5p
Colorectal Cancer/Healthy People	4.59±1.82	5.17±2.35	6.25±2.18	5.87±1.94

2. ROC curve analysis in the training set

In the training set, the CEA content of each sample was taken as the independent variable X, and the group colorectal cancer and healthy people were used as the dependent variable, and SPSS software was used to perform binary logistic regression on the content of CEA in colorectal cancer and healthy people samples, and the binary logistic regression was obtained. Logistic regression equation: Ln ^[p/(1-p)] = 4.38X-3.95, then substitute the CEA content in each sample into the binary logistic regression equation to obtain the p value of each serum sample, and use the possible p value as the diagnostic point , calculate the sensitivity and specificity, and draw the ROC curve, as shown in Figure 2 and Table 2, AUC=0.783, the sensitivity is 71.2%, and the specificity is 67.4%.

In the training set, the AFP content of each sample was used as the independent variable X, and the group colorectal cancer and healthy people were used as the dependent variable, and SPSS software was used to perform binary logistic regression on the content of AFP in colorectal cancer and healthy people samples, and the binary logistic regression was obtained. Logistic regression equation: Ln ^[p/(1-p)] = 5.15X-3.46, and then substitute the AFP content in each sample into the binary logistic regression equation to obtain the p value of each serum sample, and use the possible p value as the diagnostic point , calculate the sensitivity and specificity, and draw the ROC curve, as shown in Figure 3 and Table 2, AUC=0.749, the sensitivity is 77.5%, and the specificity is 64.1%.

In the training set, the CEA content of each sample was used as the independent variable X ₁ , the relative content of miR-609 was used as the independent variable X ₂ , and the groups of colorectal cancer and healthy individuals were used as the dependent variables. Binary logistic regression was carried out with the content in the samples of healthy people, and the binary logistic regression equation was obtained: Ln ^[p/(1-p)] =3.02X ₁ +2.77X ₂ -5.93, and then CEA, miR- The 609 content was substituted into the binary logistic regression equation to obtain the p-value of each serum sample, and the possible p-value was used as a diagnostic point to calculate the sensitivity and specificity and draw the ROC curve, as shown in Figure 4 and Table 2, AUC=0.912, sensitivity was 83.6%, and the specificity was 80.2%.

In the training set, the CEA content of each sample was used as the independent variable X ₁ , the relative content of miR-3934-5p was used as the independent variable X ₂ , and the groups of colorectal cancer and healthy people were used as the dependent variable. The content in colorectal cancer and healthy person samples is subjected to binary logistic regression, and the binary logistic regression equation is obtained: Ln ^[p/(1-p)] = 2.86X ₁ +2.39X ₂ -3.70, and then each sample The contents of CEA and miR-3934-5p were substituted into the binary logistic regression equation to obtain the p value of each serum sample, and the possible p value was used as the diagnostic point to calculate the sensitivity and specificity and draw the ROC curve, as shown in Figure 5 and Table 2 , AUC=0.805, the sensitivity was 70.5%, and the specificity was 75.7%.

In the training set, the AFP content of each sample was used as the independent variable X ₁ , the relative content of miR-609 was used as the independent variable X ₂ , and the groups of colorectal cancer and healthy people were used as the dependent variable. Binary logistic regression was carried out with the content in the samples of healthy people, and the binary logistic regression equation was obtained: Ln ^[p/(1-p)] = 4.13X ₁ +2.06X ₂ -4.32, and then AFP, miR- The 609 content was substituted into the binary logistic regression equation to obtain the p value of each serum sample, and the possible p value was used as a diagnostic point to calculate the sensitivity and specificity, and draw the ROC curve, as shown in Figure 6 and Table 2, AUC=0.692, sensitivity was 66.8%, and the specificity was 67.5%.

In the training set, the AFP content of each sample was used as the independent variable X ₁ , the relative content of miR-3934-5p was used as the independent variable X ₂ , and the groups of colorectal cancer and healthy people were used as the dependent variable, and the AFP and miR-3934-5p levels were analyzed using SPSS software. The contents in colorectal cancer and healthy person samples were subjected to binary logistic regression, and the binary logistic regression equation was obtained: Ln ^[p/(1-p)] = 3.45X ₁ +3.18X ₂ -4.03, and then each sample The contents of AFP and miR-3934-5p were substituted into the binary logistic regression equation to obtain the p value of each serum sample, and the possible p value was used as the diagnostic point to calculate the sensitivity and specificity and draw the ROC curve, as shown in Figure 7 and Table 2 , AUC=0.923, the sensitivity was 87.6%, and the specificity was 82.4%.

Table 2 The diagnostic efficacy of different markers for colorectal cancer

the	AUC	Sensitivity %	specificity%
CEA	0.783	71.2	67.4
AFP	0.749	77.5	64.1
CEA combined with miR-609	0.912	83.6	80.2
CEA combined with miR-3934-5p	0.805	70.5	75.7
AFP combined with miR-609	0.692	66.8	67.5
AFP combined with miR-3934-5p	0.923	87.6	82.4

Those skilled in the art know that AUC≤0.5 has no diagnostic value, 0.5<AUC≤0.7 has lower diagnostic accuracy, 0.7<AUC≤0.9 has better diagnostic accuracy, and AUC≥0.9 has the highest diagnostic accuracy. The above results indicated that the diagnostic efficacy of CEA or AFP alone in diagnosing colorectal cancer was average, the combination of miR-609 and CEA could significantly improve the diagnostic efficacy of CEA in diagnosing colorectal cancer, and the combination of miR-3934-5p and AFP could significantly improve Diagnostic performance of AFP in the diagnosis of colorectal cancer. miR-609 did not significantly increase the diagnostic efficiency of AFP in the diagnosis of colorectal cancer, and miR-3934-5p did not significantly increase the diagnostic efficiency of CEA in the diagnosis of colorectal cancer.

3. Verify the diagnostic accuracy of the optimal combination in the verification set

In the verification set, the CEA content (X ₁ ) and the relative content of miR-609 (X ₂ ) in each sample were substituted into the above binary logistic regression equation Ln ^[p/(1-p)] =3.02X ₁ +2.77X ₂ -5.93 , the regression prediction probability p of each serum sample was obtained, the prediction higher than the optimal cut-off value of 0.524 was colorectal cancer, otherwise the prediction was healthy, and the diagnostic accuracy was 89.4% (143/160).

In the verification set, the AFP content (X ₁ ) and the relative content of miR-3934-5p (X ₂ ) in each sample were substituted into the above binary logistic regression equation Ln ^[p/(1-p)] =3.45X ₁ +3.18X ₂ -4.03, the regression prediction probability p of each serum sample was obtained, and the prediction higher than the optimal cut-off value of 0.561 was colorectal cancer, otherwise it was predicted as a healthy person, and the diagnostic accuracy was 91.3% (146/160).

In conclusion, miR-609 can be combined with CEA to prepare a serum detection kit for early diagnosis of colorectal cancer, and miR-3934-5p can be combined with AFP to prepare a serum detection kit for early diagnosis of colorectal cancer.

Claims (2)

1. Application of a gene marker combined with alpha-fetoprotein or carcinoembryonic antigen in the preparation of a tumor diagnostic kit; specifically, the gene marker combined with alpha-fetoprotein is miR-3934-5p, and the gene marker combined with carcinoembryonic antigen is miR- 609.
2. A serum detection kit for early diagnosis of colorectal cancer, characterized in that: it contains reagents for detecting alpha-fetoprotein or carcinoembryonic antigen and its joint detection gene markers in serum, specifically, the joint detection gene markers of alpha-fetoprotein The combined detection gene marker for carcinoembryonic antigen is miR-3934-5p and miR-609.

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