CN115902222A - Breast cancer chemotherapy risk scoring model and construction method and system thereof - Google Patents
Breast cancer chemotherapy risk scoring model and construction method and system thereof Download PDFInfo
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Abstract
The invention relates to the technical field of breast cancer treatment, in particular to a breast cancer chemotherapy risk scoring model and a construction method and a system thereof; the method comprises the following steps: obtaining a breast cancer tissue specimen; selecting the breast cancer tissue specimen which accords with hormone receptor positive and epidermal growth factor receptor 2 negative for detection; calculating the percentage of Ki 67-positive stained cells in the breast cancer cell nucleus; respectively calculating the molecular marker expression quantification of Aurora A, survivin, cyclin B1, cathepsin L2 and MMP 11; establishing a breast cancer chemotherapy risk scoring model by taking a risk function as the weight of each protein expression based on the linear combination of the regression coefficient of the multiple Cox regression model multiplied by the regression coefficient of the expression level; provides a reference basis for treating breast cancer patients by adopting a chemotherapy method, and avoids blind chemotherapy of the breast cancer patients.
Description
Technical Field
The invention relates to the technical field of breast cancer treatment, in particular to a breast cancer chemotherapy risk scoring model and a construction method and a system thereof.
Background
The incidence of breast cancer worldwide has been on the rise since the end of the 20 th century 70 s. 1 of 8 women in the United states suffered from breast cancer in their lifetime. China is not a high-incidence country of breast cancer, but is not optimistic, and the growth rate of the incidence of breast cancer in China is 1-2% higher than that of the high-incidence country in recent years. According to 2009 breast cancer onset data published by the disease prevention and control agency of the national cancer center and the ministry of health in 2012, it is shown that: the incidence of breast cancer of women in tumor registration areas in the whole country is 1 st of malignant tumors of women, the incidence (thickness) of breast cancer of women is 42.55/10 ten thousand in total in the whole country, 51.91/10 ten thousand in cities and 23.12/10 ten thousand in rural areas.
While treatment of breast cancer involves chemotherapy treatment, chemotherapy helps to reduce the recurrence rate and mortality rate of early breast cancer patients, but not all patients can benefit the chemotherapy, and chemotherapy may also cause over-treatment of some breast cancer patients, so certain evaluation measures are still required for whether the breast cancer patients are treated by chemotherapy.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention aims to provide a breast cancer chemotherapy risk scoring model, and a method and a system for constructing the same, so as to provide an evaluation mode for whether a breast cancer patient is treated by chemotherapy.
In order to solve the problems, the invention adopts the following technical scheme:
in a first aspect, the invention provides a method for constructing a hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk score model, comprising the following steps:
obtaining a breast cancer tissue specimen;
selecting the breast cancer tissue specimen which accords with hormone receptor positive and epidermal growth factor receptor 2 negative for detection;
calculating the percentage of Ki67 positive staining cells in the breast cancer cell nucleus;
respectively calculating the expression quantification of the molecular markers of Aurora A, survivin, cyclin B1, cathepsin L2 and MMP 11;
and (3) establishing a breast cancer chemotherapy risk scoring model by taking the risk function as the weight of each protein expression based on the linear combination of the regression coefficient of the multiple Cox regression model multiplied by the regression coefficient of the expression level.
Further, the obtaining a breast cancer tissue specimen comprises:
obtaining a breast cancer tissue specimen, pretreating, and then, dipping wax and slicing;
dewaxing the section, staining a nucleus by hematoxylin, staining cytoplasm by eosin, dehydrating and sealing the section, and determining a chip collection point on the section to prepare an immunoassay specimen;
dewaxing an immunity test sample, repairing antigen, sealing goat serum, then dropwise adding primary antibody, secondary antibody and streptavidin peroxidase, performing DAB color development, counterstaining with hematoxylin, and performing microscope image acquisition.
Furthermore, the proportion of tumor cells with positive hormone receptors, which are expressed by estrogen and progestogen receptor proteins in nuclei and have brown particles, in all the tumor cells is more than or equal to 1 percent.
Further, the epidermal growth factor receptor 2 negative detects the expression level of the epidermal growth factor receptor 2 protein by an immunohistochemical method, detects the amplification level of the epidermal growth factor receptor 2 gene by an in situ hybridization method, and defines IHC0/1+ as negative.
Further, the calculation of the expression of the molecular markers of Aurora a, survivin, cyclin B1, cathepsin L2 and MMP11, respectively, was quantified as the average percentage of positively stained cells of the Aurora a, survivin, cyclin B1, cathepsin L2 and MMP11, respectively, to the total number of malignant cells.
Further, the risk score calculation formula of the risk score model is as follows: risk score =1.2 × expression of cathepsin L2 +1.3 × expression of mmp11 + expression of 1.4 × cyclin B1 + expression of 1.3 × aurora a + expression of 1.2 × expression of surfvin + expression of 1.4 × ki67.
In a second aspect, the present invention provides a system for constructing a risk score model of breast cancer chemotherapy with hormone receptor positive and epidermal growth factor receptor 2 negative, comprising:
the specimen preparation module is used for obtaining a breast cancer tissue specimen;
the breast cancer tissue specimen screening module is used for selecting the breast cancer tissue specimen which accords with hormone receptor positive and epidermal growth factor receptor 2 negative for detection;
the percentage calculation module of the Ki67 positive staining cells is used for calculating the percentage of the Ki67 positive staining cells in the cell nucleus of the breast cancer;
a molecular marker expression quantification calculation module for calculating molecular marker expression quantification of Aurora A, survivin, cyclin B1, cathepsin L2 and MMP11, respectively;
and the risk scoring model establishing module is used for establishing a breast cancer chemotherapy risk scoring model by taking the risk function as the weight of each protein expression based on the linear combination of the regression coefficient of the multiple Cox regression model multiplied by the regression coefficient of the expression level.
In a third aspect, the invention provides a breast cancer chemotherapy risk score model constructed by the method for constructing the hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk score model.
Further, drawing a working curve of the subject through SP 33.0, calculating a john index, taking a corresponding value of an interception point corresponding to the maximum john index as a risk score critical value, and if the risk score calculated by the breast cancer chemotherapy risk score model is greater than the risk score critical value, judging the breast cancer chemotherapy risk score model to be high-risk; otherwise, the risk is low.
Further, the risk score cutoff is 2.16.
The invention has the beneficial effects that: the invention provides a breast cancer chemotherapy risk scoring model and a construction method and a system thereof, wherein the breast cancer chemotherapy risk scoring model is established by calculating the expression quantities of breast cancer cells Ki67, aurora A, survivin, cyclin B1, cathepsin L2 and MMP11 and based on a multivariate Cox regression model, so that a reference basis is provided for whether a breast cancer patient adopts a chemotherapy means for treatment, and the condition that the breast cancer patient is blind in chemotherapy and is unfavorable to the body is avoided.
Drawings
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is a schematic flow chart of a method for constructing a risk score model of breast cancer chemotherapy with hormone receptor positive and epidermal growth factor receptor 2 negative according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a system for constructing a risk score model of breast cancer chemotherapy with hormone receptor positive and epidermal growth factor receptor 2 negative according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples.
It should be noted that these examples are only for illustrating the present invention, and not for limiting the present invention, and the simple modification of the method based on the idea of the present invention is within the protection scope of the present invention.
Referring to fig. 1, a method for constructing a risk score model of breast cancer chemotherapy with hormone receptor positive and epidermal growth factor receptor 2 negative includes:
s100, obtaining a breast cancer tissue specimen;
s200, selecting the breast cancer tissue specimen which accords with hormone receptor positive and epidermal growth factor receptor 2 negative for detection;
s300, calculating the percentage of Ki67 positive staining cells in the breast cancer cell nucleus;
s400, respectively calculating the expression quantification of the molecular markers of Aurora A, survivin, cyclin B1, cathepsin L2 and MMP 11;
s500, based on the linear combination of the regression coefficients of the multiple Cox regression model and the regression coefficients of the expression level of the multiple Cox regression model, taking the risk function as the weight of each protein expression, and establishing a breast cancer chemotherapy risk scoring model.
Wherein S100 comprises:
s101, obtaining a breast cancer tissue specimen, pretreating, and then, dipping wax and slicing.
The method specifically comprises the following steps:
fresh tissue from the surgically excised specimens was immersed in 4% paraformaldehyde fixing solution and fixing continued for at least 24 hours. After fixation, the tissue was removed from the fixative, the site of evidence of necrosis and hemorrhage was removed with a scalpel in a fume hood, the target tissue was trimmed, the repaired tissue was marked, and placed in a dehydration box. Dewaxing and soaking: and (4) placing the dewatering box in a hanging basket, and then placing the box in a dewatering machine for dewatering according to the gradient of the alcohol concentration. 75% alcohol for 4 hours, 85% alcohol for 2 hours, 90% alcohol for 2 hours, 95% alcohol for 1 hour, absolute ethanol I for 30 minutes, absolute ethanol II for 30 minutes, xylene I for 10 minutes, xylene II for 10 minutes.
Wax dipping: paraffin wax was melted and the temperature was maintained at about 57 ℃. A total of three passes of waxing are required, the first time of waxing is about 15 minutes, and the next two passes of waxing can be properly extended to 30min-1h. Embedding: the melted wax was poured into the mold, the tissue was placed in, paraffin was then solidified, and then placed in the embedding frame for labeling. It was cooled on a-20 ℃ freezer table. After the wax solidified, it was removed from the embedding frame and the wax block was trimmed. Slicing: the wax block was sliced on a paraffin slicer to a thickness of 4 μm. The sections were then floated on a paraffin slicer, flattened in warm water at 40 ℃, scooped up with a glass slide, and then baked in an oven at 60 ℃. After baking the water and wax, it was removed and stored at room temperature for later use.
S102, dewaxing the section, staining nuclei with hematoxylin, staining cytoplasm with eosin, dehydrating and sealing the section, and determining a chip collection point on the section to obtain an immune test specimen.
The method specifically comprises the following steps:
placing the slices into dimethylbenzene I for 15 minutes, dimethylbenzene II for 15 minutes, dimethylbenzene III for 15 minutes, absolute ethyl alcohol I for 10 minutes, absolute ethyl alcohol II for 10 minutes, 90% alcohol for 5 minutes, 80% alcohol for 5 minutes, and 70% alcohol for washing for 5 minutes. And (3) hematoxylin nuclear staining: hematoxylin staining for 5 minutes, washing with tap water, distinguishing 1% hydrochloric acid from alcohol, washing with tap water, recovering blue, and washing with tap water. Eosin staining of cytoplasm: the slices were dehydrated in 70%, 80%, 90% ethanol for 3 min, and placed in eosin staining solution for 5 min. And (4) dewatering and sealing the sheet: the slices are sequentially made into absolute ethyl alcohol I for 5 minutes, absolute ethyl alcohol II for 5 minutes, absolute ethyl alcohol III for 5 minutes, xylene I for 5 minutes, xylene II for 5 minutes, and the slices are transparent, neutral and rubber-sealed for 5 minutes. And selecting a representative area on the section for microscopic examination, and determining the chip acquisition point.
S103, dewaxing an immunoassay sample, repairing antigen, sealing goat serum, then dripping primary antibody, secondary antibody and streptavidin peroxidase to perform DAB color development, performing hematoxylin counterstain, and performing microscope image acquisition.
The method specifically comprises the following steps:
paraffin section and dewaxing, placing the baked tissue chips in the following sequence: xylene I, II each 15 minutes, xylene III 15 minutes, absolute ethanol I, II each 10 minutes, 90%, 80%, 70% ethanol each 5 minutes, and finally 3 washes with PBS each 3 minutes.
Putting the chips into 3% 2 O 2 Incubated in the dark at room temperature for 10 minutes, then washed 3 times with PBS for 3 minutes each.
Antigen retrieval: immersing the tissue slices into a repairing box with EDTA antigen repairing buffer solution, and placing the repairing box in an autoclave for high-pressure water bath. After boiling, heating was continued for 5 minutes. In this process, the buffer should be prevented from excessive evaporation, and the sections should not be dried. After cooling, the slides were placed in PBS (pH 7.4) and washed 3 times with PBS on a destaining shaker for 3 minutes each.
Sealing goat serum: a circle was drawn around the tissue with a pen to prevent antibody run-off, goat serum was added dropwise to the circle and incubated at room temperature for 20 min.
A proportion of primary antibody was added dropwise, the sections were kept flat in a moist box to prevent evaporation of antibody, and incubated overnight at 4 ℃.
And (4) dropwise adding a secondary antibody: the tissue chips were removed and washed 3 times with PBS for 3 minutes each. After the sections were slightly dried, the corresponding secondary antibody was added dropwise and incubated at room temperature for 30 minutes. The PBS was washed 3 times with shaking for 3 minutes each.
Dropping streptavidin peroxidase: streptavidin peroxidase was added dropwise, incubated at room temperature for 15 minutes and then washed 3 times with PBS, 3 minutes each.
DAB color development: DAB color reagent 1. The brown-yellow color is a positive stain, and the sections are rinsed with tap water to stop the reaction when the color deepens.
Counterstaining with hematoxylin for 5 minutes, washing in tap water, differentiation in 1% ethanol hydrochloride for several seconds, then washing in tap water, reduction to blue with saturated lithium carbonate for 2 minutes, and then washing with tap water.
Dewatering and fixing: the slices were placed in 70%, 80%, 90% ethanol for 3 minutes each, and in absolute ethanol I, II for 5 minutes each, until dehydrated and became transparent, and the slices were taken out and sealed with neutral gum.
Image acquisition and analysis was performed under a microscope.
In step S200, the proportion of the tumor cells with positive hormone receptors, which are expressed by estrogen and progestogen receptor proteins in nuclei and have brown particles, in all the tumor cells is more than or equal to 1%.
The epidermal growth factor receptor 2 negative characteristic is that the expression level of epidermal growth factor receptor 2 protein is detected by an immunohistochemical method, the amplification level of epidermal growth factor receptor 2 gene is detected by an in-situ hybridization method, and IHC0/1+ is defined as negative.
In step S400, the molecular marker expression quantities of Aurora a, survivin, cyclin B1, cathepsin L2, and MMP11 are calculated as the average percentage of the total number of malignant cells in which the positively stained cells account for Aurora a, survivin, cyclin B1, cathepsin L2, and MMP11, respectively.
In step S500, the risk score calculation formula of the risk score model is as follows: risk score =1.2 × expression of cathepsin L2 +1.3 × expression of mmp11 + expression of 1.4 × cyclin B1 + expression of 1.3 × aurora a + expression of 1.2 × expression of surfvin + expression of 1.4 × ki67.
Referring to fig. 2, a system for constructing a risk score model of breast cancer chemotherapy with hormone receptor positive and epidermal growth factor receptor 2 negative includes:
the specimen preparation module is used for obtaining a breast cancer tissue specimen;
the breast cancer tissue specimen screening module is used for selecting the breast cancer tissue specimen which accords with hormone receptor positive and epidermal growth factor receptor 2 negative for detection;
the percentage calculation module of the Ki67 positive staining cells is used for calculating the percentage of the Ki67 positive staining cells in the cell nucleus of the breast cancer;
the molecular marker expression quantitative calculation module is used for respectively calculating the molecular marker expression quantitative of Aurora A, survivin, cyclin B1, cathepsin L2 and MMP 11;
and the risk scoring model establishing module is used for establishing a breast cancer chemotherapy risk scoring model by taking the risk function as the weight of each protein expression based on the linear combination of the regression coefficients of the multiple Cox regression model multiplied by the regression coefficients of the expression level.
A breast cancer chemotherapy risk scoring model constructed by the method for constructing the hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk scoring model.
Drawing a working curve of a subject through SP 33.0, calculating a john index, taking a corresponding value of an interception point corresponding to the maximum john index as a risk score critical value, and if the risk score calculated by the breast cancer chemotherapy risk score model is greater than the risk score critical value, judging that the risk is high; otherwise, the risk is low.
Wherein the subject's criteria are as follows:
postmenopausal or premenopausal/perimenopausal female patients;
pathologically confirmed early primary invasive breast cancer with positive hormone receptor and negative HER 2;
before operation, radiotherapy, new auxiliary chemotherapy, endocrine treatment or targeted treatment is not carried out;
the patients receive systemic endocrine therapy.
The risk score cutoff value was calculated to be 2.16.
Finally, it is noted that the above-mentioned embodiments illustrate rather than limit the invention, and that, while the invention has been described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for constructing a hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk score model is characterized by comprising the following steps:
obtaining a breast cancer tissue specimen;
selecting the breast cancer tissue specimen which accords with hormone receptor positive and epidermal growth factor receptor 2 negative for detection;
calculating the percentage of Ki 67-positive stained cells in the breast cancer cell nucleus;
respectively calculating the molecular marker expression quantification of Aurora A, survivin, cyclin B1, cathepsin L2 and MMP 11;
and (3) establishing a breast cancer chemotherapy risk scoring model by taking the risk function as the weight of each protein expression based on the linear combination of the regression coefficient of the multiple Cox regression model multiplied by the regression coefficient of the expression level.
2. The method for constructing a risk score model for breast cancer chemotherapy with hormone receptor positive and epidermal growth factor receptor 2 negative according to claim 1, wherein said obtaining a tissue specimen of breast cancer comprises:
obtaining a breast cancer tissue specimen, pretreating, then, dipping wax and slicing;
dewaxing the section, staining a nucleus by hematoxylin, staining cytoplasm by eosin, dehydrating and sealing the section, and determining a chip collection point on the section to prepare an immunoassay specimen;
dewaxing an immunity test sample, repairing antigen, sealing goat serum, then dropwise adding primary antibody, secondary antibody and streptavidin peroxidase, performing DAB color development, counterstaining with hematoxylin, and performing microscope image acquisition.
3. The method for constructing the hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk score model according to claim 1, wherein the proportion of tumor cells with the hormone receptor positive being the nucleus in which the estrogen and progesterone receptor proteins are expressed and brown particles appear is greater than or equal to 1% of all tumor cells.
4. The method for constructing the hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk score model according to claim 1, wherein the epidermal growth factor receptor 2 negative is characterized in that the expression level of epidermal growth factor receptor 2 protein is detected by an immunohistochemical method, the amplification level of epidermal growth factor receptor 2 gene is detected by an in situ hybridization method, and IHC0/1+ is defined as negative.
5. The method for constructing a hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk score model according to claim 1, wherein the molecular marker expression quantities of Aurora a, survivin, cyclin B1, cathepsin L2 and MMP11 are calculated as the average percentage of positively stained cells in the total number of malignant cells.
6. The method for constructing a risk score model of breast cancer chemotherapy, which is positive for hormone receptor and negative for epidermal growth factor receptor 2 according to claim 1, wherein the risk score is calculated by the risk score model according to the following formula: risk score =1.2 × cathepsin L2 expression +1.3 × mmp11 expression +1.4 × cyclin B1 expression +1.3 × aurora a expression +1.2 × survivin expression +1.4 × ki67 expression.
7. A system for constructing a hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk score model is characterized by comprising:
the specimen preparation module is used for obtaining a breast cancer tissue specimen;
the breast cancer tissue specimen screening module is used for selecting the breast cancer tissue specimen which accords with hormone receptor positive and epidermal growth factor receptor 2 negative for detection;
the percentage calculation module of the Ki67 positive staining cells is used for calculating the percentage of the Ki67 positive staining cells in the cell nucleus of the breast cancer;
the molecular marker expression quantitative calculation module is used for respectively calculating the molecular marker expression quantitative of Aurora A, survivin, cyclin B1, cathepsin L2 and MMP 11;
and the risk scoring model establishing module is used for establishing a breast cancer chemotherapy risk scoring model by taking the risk function as the weight of each protein expression based on the linear combination of the regression coefficients of the multiple Cox regression model multiplied by the regression coefficients of the expression level.
8. A breast cancer chemotherapy risk scoring model constructed by a method for constructing a hormone receptor positive and epidermal growth factor receptor 2 negative breast cancer chemotherapy risk scoring model.
9. The breast cancer chemotherapy risk score model according to claim 8, further comprising plotting a subject working curve by SP 33.0, calculating a john index, using the corresponding value of the cut-off point corresponding to the maximum john index as a risk score critical value, and determining as high risk if the risk score calculated by the breast cancer chemotherapy risk score model is greater than the risk score critical value; otherwise, the risk is low.
10. The breast cancer chemotherapy risk score model of claim 9, wherein the risk score cut-off value is 2.16.
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| WO2019077080A1 (en) * | 2017-10-19 | 2019-04-25 | Universite Claude Bernard Lyon 1 | Evaluation of the risk of metastatic relapse in breast cancer patients |
| CN111679072A (en) * | 2020-06-15 | 2020-09-18 | 温州医科大学 | Application of KDM6B protein in breast cancer prognosis assessment kits and diagnostic kits |
| CN114807370A (en) * | 2022-04-29 | 2022-07-29 | 中国医学科学院肿瘤医院 | A Novel Model for Precise Prediction of Breast Cancer Immunotherapy Efficacy and Its Application |
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| WO2019077080A1 (en) * | 2017-10-19 | 2019-04-25 | Universite Claude Bernard Lyon 1 | Evaluation of the risk of metastatic relapse in breast cancer patients |
| CN111679072A (en) * | 2020-06-15 | 2020-09-18 | 温州医科大学 | Application of KDM6B protein in breast cancer prognosis assessment kits and diagnostic kits |
| CN114807370A (en) * | 2022-04-29 | 2022-07-29 | 中国医学科学院肿瘤医院 | A Novel Model for Precise Prediction of Breast Cancer Immunotherapy Efficacy and Its Application |
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