CN111735944B - Application of CICs in breast tumor tissue in preparation of product for predicting breast cancer prognosis survival - Google Patents
Application of CICs in breast tumor tissue in preparation of product for predicting breast cancer prognosis survival Download PDFInfo
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Abstract
The invention discloses application of CICs in breast tumor tissues in preparation of a product for predicting breast cancer prognosis survival. The invention provides application of a substance for detecting the number of oCICs in breast cancer tissues of a breast cancer patient in preparing a product for predicting the prognosis survival rate of the breast cancer patient. Also provided is the use of a substance that detects the number of TiT subtypes in breast cancer tissue of a breast cancer patient in the manufacture of a product for predicting the prognosis survival of a breast cancer patient. Also provided is the use of a substance that detects the number of MiT subtypes in breast cancer tissue of a breast cancer patient in the preparation of a product that predicts the prognosis survival of a breast cancer patient. Also provided is the use of a substance that detects the number of TiM subtypes in breast cancer tissue of a breast cancer patient in the preparation of a product that predicts the prognosis survival of a breast cancer patient. The invention predicts the prognosis of the breast cancer patient by CICs subtype analysis and counting method, and has remarkable originality.
Description
Technical Field
The invention belongs to the technical field of biology, and particularly relates to application of CICs in breast tumor tissues in preparation of a product for predicting breast cancer prognosis survival.
Background
Breast cancer is one of the major diseases that currently severely jeopardizes women's health. Breast cancer has significant heterogeneity, particularly in the diversity of tumor biological behaviors, patient prognosis, and significant differences in response to treatment. Most patients are in an early stage of the disease when they first visit, and surgical excision is an important means of disease treatment. The relevant pathological information provided by postoperative pathology is an important basis for judging the prognosis of patients and making subsequent treatment schemes. Although the risk of recurrence in breast cancer patients is significantly reduced with the standardization of surgery and adjuvant therapy, there are still some patients who undergo surgery, adjuvant therapy, and then undergo local recurrence or distant metastasis, resulting in incurable disease and death. Therefore, judging the prognosis of a patient based on only the existing clinical pathology information is insufficient, and further, a new prognostic index needs to be explored for accurately predicting the disease condition and prognosis of the patient.
Currently accepted pathological information related to patient prognosis includes: tumor histological classification, TNM staging, hormone receptor status, HER2 expression status, lymph node status, and the like. However, the above indicators can only make a rough prediction of the prognosis of a patient to some extent. The search of sensitive and effective prediction indexes depends on the deep understanding of the molecular mechanism of tumorigenesis and development, and a plurality of scholars search for effective prognosis markers by taking abnormal gene expression of tumor cells as a starting point, and detect the expression of a plurality of genes simultaneously by using a plurality of gene chips represented by Oncotype, so that the recurrence risk of patients can be estimated, and further, the auxiliary treatment strategy is guided. Although gene chips can provide more accurate prognostic information than histopathological information, commercial gene chips are expensive to detect and are often designated for specific patient populations and are still not widely used in clinical practice.
Peripheral blood circulating tumor cell detection is also an effective means for predicting prognosis of patients, and patients with higher circulating tumor numbers have poorer prognosis, and in the treatment process of patients, the change of the circulating tumor numbers can predict the response of the patients to treatment earlier. However, the predictive value of circulating tumor cell detection also has some limitations in application. First, the detection methods are not identical, affecting the interpretation of the results. The CellSearch platform currently passed by the FDA in the united states can automatically detect the number of circulating tumors, but is expensive. Second, circulating tumor cell detection predicts that patient prognosis has clear evidence in metastatic breast cancer, however, the detection rate of circulating tumor cells in early post-operative breast cancer patients is low, significantly limiting its use in early breast cancer patients.
Given the important role of the immune microenvironment in the progression of tumors, numerous studies have focused on the stromal cells in tumor tissue, and found that the distribution and proportion of infiltrating lymphocytes in tumor tissue is significantly correlated with patient prognosis. Although related studies are at a number of laboratory stages and have not yet been applied to clinical practice, the above results suggest that focusing on interactions of tumor immune microenvironments can provide more, more accurate prognostic information. Focusing on the interaction of different cells in tumor microenvironment is an important direction for finding novel prognosis indexes.
In conclusion, the value of the prognosis index of breast cancer which is conventionally applied to clinic is limited. The search of tumor markers focuses not only on abnormal gene expression of tumor cells, but also on interaction of tumor cells in tumor microenvironment, and the new prognosis related markers are searched at the level of different molecular mechanisms and used together to improve the prediction efficacy and accurately predict the prognosis of patients.
Cell-in-cells (cic) structures refer to the presence of one or more structurally and functionally intact living cells within another Cell, thereby forming a Cell-like structure that can be formed between cells of the same origin (homotyrpic) or between cells of different origins (heterotyrpic), such as between tumor cells and immune cells. The formation of this structure can lead to death of the internalized cells. The common type of cic in tumor tissue is the formation of homogeneous cic structures between tumor cells, which may promote malignant progression of the tumor by screening for more malignant cell clones.
Disclosure of Invention
In order to predict the prognosis survival rate of breast cancer patients, the invention provides the following technical scheme.
The invention provides application of a substance for detecting at least one structural number of A-D in breast cancer tissues of a breast cancer patient in preparing a product for predicting the prognosis survival rate of the breast cancer patient;
A. an oCIC; B. subtype TiT; C. MiT subtype; D. a TiM subtype;
the oCIC is all subtypes of CICs; the subtype of the CICs is TiT subtype, miT subtype, tiM subtype, liM subtype and LiT subtype;
the TiT subtype is a homogenous CICs structure formed by tumor cells phagocytizing tumor cells;
the MiT subtype is a CICs structure formed by phagocytic macrophages of tumor cells;
the TiM subtype is CICs structure formed by phagocytic tumor cells of macrophages;
the LiM subtype is CICs structure formed by phagocytic lymphocyte of macrophage;
the LiT subtype is CICs structure formed by tumor cell phagocytic lymphocyte.
In the application, the substance for detecting the number of at least one structure of A-D in the breast cancer tissue of the breast cancer patient is a substance for detecting the number of any structure of A-D in the breast cancer tissue of the breast cancer patient.
In the above application, the substance for detecting the number of at least one structure A-D in the breast cancer tissue of the breast cancer patient is a substance for detecting the number of structures A and B-D in the breast cancer tissue of the breast cancer patient in any combination.
In practical application, the method can firstly perform preliminary judgment according to oCIC or the number thereof, and then accurately judge by utilizing subtype shown by B-D or any combination of the number thereof; or each subtype can be used for judgment independently; the oCIC determination can also be used alone.
In the above applications, the substance includes an E-cadherein antibody, a CD68 antibody, a CD45 antibody, and a fluorescent antibody or a fluorescent dye capable of binding to the three antibodies, respectively.
In the above application, the fluorescent antibodies or fluorescent dyes capable of binding to the three antibodies respectively have different fluorescent colors or wavelengths.
In the above application, the substance further comprises a fluorescence microscope.
In the above application, the breast cancer patient is a breast cancer patient of the luminalA subgroup, a breast cancer patient of the luminalB (HER 2-) subgroup, a breast cancer patient of the luminalB (her2+) subgroup, a breast cancer patient of the her2+ subgroup and/or a breast cancer patient of the TNBC subgroup.
The invention also provides a product for predicting the prognosis survival rate of breast cancer patients, which comprises at least one of the following 1) -4):
1) Detecting an oscic number of agents in breast cancer tissue of a breast cancer patient;
2) Detecting a number of TiT subtype substances in breast cancer tissue of a breast cancer patient;
3) Detecting a substance of the number of MiT subtypes in breast cancer tissue of a breast cancer patient;
4) Detecting the number of TiM subtypes in breast cancer tissue of a breast cancer patient.
The above product further comprises: readable carrier for recording at least one criterion of the following 1) -4):
1) The prognosis survival rate of the patients to be tested with the oCICs number being more than 15 is more than the prognosis survival rate of the patients to be tested with the oCICs number being less than or equal to 15;
2) A prognosis survival rate of TiT patients to be tested greater than 15 is greater than TiT and less than or equal to 15;
3) The prognosis survival rate of the patients to be tested with the MiT subtype is smaller than the prognosis survival rate of the patients to be tested without the MiT subtype;
4) The prognosis survival rate of the patients tested for the presence of the TiM subtype is greater than the prognosis survival rate of the patients tested for the absence of the TiM subtype.
The use of the above-described readable carrier for detecting the number of individual CIC subtypes in breast cancer tissue of a breast cancer patient and recording at least one criterion as described in 1) -7) for the manufacture of a product for predicting the prognosis survival of a breast cancer patient is also within the scope of the present invention.
The product is a kit.
The invention also provides a method for predicting the prognosis survival rate of breast cancer patients, which comprises the following steps: detecting the number of at least one structure a-D in breast cancer tissue of a breast cancer patient;
A. an oCIC; B. subtype TiT; C. MiT subtype; D. a TiM subtype;
the oCIC is all subtypes of CICs; the subtype of the CICs is TiT subtype, miT subtype, tiM subtype, liM subtype and LiT subtype;
the TiT subtype is a homogenous CICs structure formed by tumor cells phagocytizing tumor cells;
the MiT subtype is a CICs structure formed by phagocytic macrophages of tumor cells;
the TiM subtype is CICs structure formed by phagocytic tumor cells of macrophages;
the LiM subtype is CICs structure formed by phagocytic lymphocyte of macrophage;
the LiT subtype is a CICs structure formed by tumor cell phagocytic lymphocytes;
according to at least one of the following 1) -4):
1) The prognosis survival rate of the patients to be tested with the oCICs number being more than 15 is more than the prognosis survival rate of the patients to be tested with the oCICs number being less than or equal to 15;
2) A prognosis survival rate of TiT patients to be tested greater than 15 is greater than TiT and less than or equal to 15;
3) The prognosis survival rate of the patients to be tested with the MiT subtype is smaller than the prognosis survival rate of the patients to be tested without the MiT subtype;
4) The prognosis survival rate of the patients tested for the presence of the TiM subtype is greater than the prognosis survival rate of the patients tested for the absence of the TiM subtype.
The method of the invention has the following advantages:
1. the prognosis of the breast cancer patient is predicted by CICs subtype analysis and counting method, which has obvious originality;
the research of CICs focuses on the interaction between tumor cells and tumor cells or other cells in the tumor microenvironment, is more similar to the essence of malignant biological behaviors of the tumor cells, and can further reveal the malignant biological behaviors of the tumor. The study finds that the prognosis of the breast cancer general population can be predicted by CICs subtype analysis and counting methods, and the prognosis prediction value is still provided in different breast cancer subtypes, so that the method is a beneficial supplement to the existing classical prediction indexes;
grading and counting of CICs subtype can be carried out on the basis of conventionally obtained pathological sections without additional or special materials;
4. by the multiple fluorescence labeling method, fluorescence labeling of multiple cells is realized on the same tissue section, so that not only can tumor cell boundaries be clearly presented, but also different cell types can be distinguished, and accurate subtype analysis of CICs is realized.
Drawings
FIG. 1 shows different types of CICs in breast cancer tissue.
FIG. 2 shows survival of breast cancer patients with different numbers of CICs.
FIG. 3 shows survival of different MIT numbers of patients in LuminelA subtype and LuminelB (HER 2-) subtype breast cancers.
Figure 4 is survival of different numbers of oscic and TiT patients in luminelb (her2+) subtype breast cancer.
Figure 5 is survival of patients with different numbers of TiM in her2+ or TNBC subtype breast cancer.
Detailed Description
The experimental methods used in the following examples are conventional methods unless otherwise specified.
Materials, reagents and the like used in the examples described below are commercially available unless otherwise specified.
EXAMPLE 1 establishment of methods for predicting prognosis of Breast cancer by subtype CICs in tumor tissue
1. Pretreatment of breast tumor tissue sections to achieve dewaxing and antigen retrieval
1. Obtaining paraffin pathological sections with breast tumor tissues;
2. baking paraffin sections at 65 ℃ for 1.5 hours;
3. dewaxing with xylene I and II for 5-10min, adding into 100%, 95%, 90%, 80%, 70% alcohol solution for 3-5 min, and adding into distilled water for 3 min;
4. placing the slice in antigen retrieval solution (AR 0024) for microwave boiling for 15 min, and naturally cooling to room temperature;
5. the sections were immersed in TBST solution (1 XTBS, 0.1% (vol% Tween 20) for 2 min;
6. the sections were placed in blocking solution (1 XTBS, 0.1% Tween 20 (vol%, wt%, etc.), 5% BSA (wt%, etc.), and allowed to stand at room temperature for 1 hour.
2. Multiple fluorescent labeled cells
The treated tissue sections were subjected to multiple staining with Opal multiple tissue staining kit (Opal 7-color Manual IHC Kit, perkin Elmer, NEL811001 KT) as follows:
1. CD68 molecular marker staining
1) According to the kit instructions, primary antibodies (CD 68 antibody, santa, sc-20060) were prepared according to 1:500 in proportion, diluted with blocking solution (same as before), and tissue sections were incubated with diluted primary antibody (500. Mu.L/Zhang Qiepian) for 1 hour at room temperature;
2) Discarding the primary antibody, and washing the slice with TBST solution (same as above) for 3 times;
3) Adding HRP-labeled secondary Antibody (Cell Signaling Technology,7076, dilution ratio 1:500, dilution TBST solution) 500 μl/Zhang Qiepian, and incubating at room temperature for 1 hr;
4) The secondary antibody was discarded and the sections were washed 3 times with TBST solution (supra);
5) TSA690 (Perkin Elmer, NEL791001KT, dilution ratio 1:50, diluted with 1*Plus Amplification Diluent contained in the kit) 200. Mu.L/Zhang Qiepian was added and incubated for 0.5 hours at room temperature;
6) Washing according to the instructions, removing the bound antibodies, and obtaining sections marked by CD68 molecules.
2. CD45 molecular marker staining
1) According to the kit instructions, primary antibody (CD 45 antibody, boster, BM 0091) was prepared according to 1:500 in proportion, diluting with a blocking solution (the same as before), and incubating the CD68 molecular labeled section obtained in the step 1 with diluted primary antibody (500 mu L/Zhang Qiepian) at room temperature for 1 hour;
2) Discarding the primary antibody, and washing the slice with TBST solution (same as above) for 3 times;
3) Adding HRP-labeled secondary Antibody (Cell Signaling Technology,7076, dilution ratio 1:500, dilution TBST solution) 500 μl/Zhang Qiepian, and incubating at room temperature for 1 hr;
4) The secondary antibody was discarded and the sections were washed 3 times with TBST solution (supra);
5) TSA620 (Perkin Elmer, NEL791001KT, dilution ratio 1:50, diluted with 1*Plus Amplification Diluent contained in the kit) 200. Mu.L/Zhang Qiepian was added and incubated for 0.5 hours at room temperature;
6) Washing according to the instructions removes the bound antibodies, resulting in a section labeled with cd68+cd45 molecules.
3. E-cadherin molecular marker staining
1) According to the kit instructions, primary antibodies (E-cadherein antibody, boster, BM 0091) were prepared according to 1:500 in proportion, diluting with blocking solution (same as before), and incubating the sections marked by CD68+CD45 molecules obtained in the step 2 with diluted primary antibody (500 mu L/Zhang Qiepian) at room temperature for 1 hour;
2) Discarding the primary antibody, and washing the slice with TBST solution (same as above) for 3 times;
3) Adding HRP-labeled secondary Antibody (Cell Signaling Technology,7076, dilution ratio 1:500, dilution TBST solution) 500 μl/Zhang Qiepian, and incubating at room temperature for 1 hr;
4) The secondary antibody was discarded and the sections were washed 3 times with TBST solution (supra);
5) TSA520 (Perkin Elmer, NEL791001KT, dilution ratio 1:50, diluted with 1*Plus Amplification Diluent contained in the kit) 200. Mu.L/Zhang Qiepian was added and incubated for 0.5 hours at room temperature;
6) Washing according to instructions, bound antibodies were removed.
4. DAPI-containing caplets (ZSBB-Bio, ZLI-9557) were used to obtain multi-labeled tissue sections of CD45, E-cadherein and CD68 molecules.
3. Counting CICs number under fluorescence microscope
1. Multispectral imaging (Multispectral imaging) and analysis
1) Using
Automated Imaging System (Perkin Elmer) TMA mode multispectral imaging acquisition (20 x objective);
2) A data set of each single spectrum (DAPI, 488,568 and Cy 5) was constructed using a Nuance system (Perkin Elmer) and spectrally resolved to obtain a clear image for each spectrum;
3) Multispectral imaging data were analyzed in batch using InForm automated image analysis software package (Perkin Elmer).
4) The labeled tissue sections are observed under a fluorescence microscope, the number of cells-in-cells (CICs) is counted, and typical CICs are that one cell not only contains single or multiple cells which enter completely, but also crescent cell nuclei can be observed. The CICs were counted under a microscope in all tissue chips.
2. Subtype of CICs in breast cancer tissue
Multiplex fluorescent markers label cell types: e-cadherein positive (E-cad+) is tumor cell; CD68 positive (cd68+) is macrophage; CD45 positive (cd45+) is a lymphocyte; from the above multiplex fluorescence markers, there are 5 different subtypes of CICs structures in breast cancer tumor tissue (fig. 1), respectively:
TiT (Tumor cell in Tumor cell) the marker is characterized by the E-cad+/CD45-/CD68-in E-cad+/CD45-/CD 68-/subtype which accounts for the vast majority of oCICs, meaning the structure of CICs formed by tumor cells phagocytizing tumor cells.
MiT (Macrophage in Tumor cell) the marker is characterized by the CD68+/E-cad-/CD45-in E-cad+/CD45-/CD 68-subtype, which refers to the structure of CICs formed by phagocytic macrophages of tumor cells.
TiM (Tumor cell in Macrophage) the marker is characterized by the E-cad+/CD45-/CD68-in CD68+/E-cad-/CD 45-subtype, which refers to the structure of CICs formed by phagocytic tumor cells of macrophages.
LiM (Lymphocyte in Tumor cell) the label is characterized by CD45+/CD68-/E-cad-in CD68+/E-cad-/CD 45-subtype, which refers to the structure of CICs formed by phagocytic lymphocytes of macrophages.
LiT (Lymphocyte in Tumor cell0, labeled CD45+/E-cad-/CD68-/in E-cad+/CD45-/CD 68-subtype, refers to the structure of CICs formed by tumor cells phagocytic lymphocytes.
According to the CIC subtype described above, the definition for oCIC (overall CICs) is as follows: the above 5 subtypes are included, the number of which is the sum of the numbers of the above 5 subtypes.
E-cad+ indicates positive and E-cad-indicates negative;
cd45+ means CD45 positive, CD 45-means CD45 negative;
CD68+ indicates CD68 positive, and CD 68-indicates CD68 negative.
4. The subtype of CICs in breast tumor tissue is related to prognosis of patients
1. The number of oCICs in breast tumor tissue is correlated with patient prognosis
The number of CICs in each tumor tissue was measured in a breast cancer tissue chip (available from Shanghai core Biotechnology Co., ltd., HBre-Duc170 Sur-01). The adopted tissue chip comprises 170 cases of breast tumor tissues, clinical information and follow-up information of corresponding patients, and the tumor tissues come from breast cancer operations of the patients. All cases without CICs staining results were deleted due to missed cases or flaking during staining. The final 148 cases of Survival follow-up information were complete and tumor tissue correspondence data with CICs staining results were analyzed, and total Survival (OS) was defined as the time from the patient receiving surgery to the patient's death or last follow-up.
And drawing a survival curve by using a Kaplan-Meier method, dividing the patients into 2 groups according to the number of oCICs in 148 tumor tissues, wherein the number of oCICs is greater than 15 and defined as a High-oCICs group, and the number of oCICs is less than or equal to 15 and defined as a Low-oCICs group.
The Kaplan-Meier analysis results are shown in FIG. 2a, where mOS: median survival (median Overall Survival); low oscics: the number of oCICs is less than or equal to 15; high oCICs: the number of oCICs is more than 15; the median survival times of the Low-oCICs group and the High-oCICs group patients were 147 months and were not yet reached, respectively, and the survival rates were statistically different (P=0.009), showing that the High-oCICs group patients had better prognosis than the Low-oCICs group patients.
Therefore, the prognosis survival condition of the patient to be detected can be predicted according to the number of oCICs detected in the breast tumor tissue, and the prognosis survival rate of the patient to be detected with the number of oCICs being more than 15 is more than the prognosis survival rate of the patient to be detected with the number of oCICs being less than or equal to 15.
The method for detecting the number of oCICs in breast tumor tissue comprises the following steps: firstly, preprocessing a mammary tumor tissue slice to realize dewaxing and antigen restoration, then, performing multiple fluorescent staining on the preprocessed slice, and finally, counting the number of oCICs by a fluorescent microscope.
2. TiT number in breast tumor tissue correlates with patient prognosis
Detecting TiT numbers in the 148 breast cancer tissues, drawing a survival curve by using a Kaplan-Meier method, dividing patients into 2 groups according to TiT numbers in tumor tissues, defining the groups with TiT numbers larger than 15 as High-TiT groups, and defining the groups with TiT numbers smaller than or equal to 15 as Low-TiT groups.
The Kaplan-Meier analysis results are shown in FIG. 2b, where mOS: median survival (median Overall Survival); low TiT: tiT number is less than or equal to 15; high TiT: tiT number is greater than 15; the median survival times for Low-TiT and High-TiT patients were 147 months and as yet, respectively, and the survival rates were statistically different (p=0.038), indicating a better prognosis for High-TiT patients relative to Low-TiT patients.
Therefore, the prognosis survival of the patients to be tested can be predicted according to the TiT number of the breast tumor tissues, and the prognosis survival rate of the patients to be tested with TiT number of more than 15 is more than TiT number of less than or equal to 15.
The method for detecting TiT number in breast tumor tissue comprises the following steps: firstly, pretreatment of breast tumor tissue slices is carried out to achieve dewaxing and antigen restoration, then multiple fluorescent staining is carried out on the pretreated slices, and finally, the number of the breast tumor tissue slices is counted by a fluorescent microscope to TiT.
3. MIT number in breast tumor tissue correlated with patient prognosis
The number of MiTs in the 148 breast cancer tissues was measured, and the patients were divided into 2 groups according to the presence or absence of MiTs in the tumor tissues, wherein the number of MiTs was 1 or more defined as a MiT positive group, and the number of MiTs was 0 defined as a MiT negative group.
The Kaplan-Meier analysis results are shown in FIG. 2d, where mOS: median survival (median Overall Survival); median survival times for the MiT positive and MiT negative groups of patients were (147 months and not yet reached), respectively, with statistical differences in survival (P=0.007), indicating that the MiT positive patients were worse than the MiT negative patients.
Therefore, the prognosis survival condition of the patient to be tested can be predicted according to the number of MiT in the breast tumor tissue, and the prognosis survival rate of the patient to be tested with the MiT subtype is smaller than that of the patient to be tested without the MiT subtype.
The method for detecting the number of MiT in the breast tumor tissue comprises the following steps of preprocessing a breast tumor tissue slice to realize dewaxing and antigen retrieval, then performing multiple fluorescent staining on the preprocessed slice, and finally counting the number of MiT by a fluorescent microscope.
4. The number of TiM in breast tumor tissue correlates with patient prognosis
The number of TiMs in the 148 breast cancer tissues is detected, the patients are divided into 2 groups according to the presence or absence of the TiMs in the tumor tissues, the number of the TiMs is greater than or equal to 1 and is defined as a TiM positive group, and the number of the TiMs is 0 and is defined as a TiM negative group.
The Kaplan-Meier analysis results are shown in FIG. 2c, where mOS: median survival (median Overall Survival); the median survival times for the TiM-negative and TiM-positive patients were (147 months and not yet reached), respectively, with statistical differences in survival (p=0.033), indicating that TiM-positive patients had better prognosis than TiM-negative patients.
Therefore, the prognosis survival condition of the patient to be tested can be predicted according to the number of TiM in the breast tumor tissue, and the prognosis survival rate of the patient to be tested with the TiM subtype is larger than that of the patient to be tested without the TiM subtype.
The method for detecting the number of TiMs in breast tumor tissues comprises the following steps: firstly, preprocessing a mammary tumor tissue slice to realize dewaxing and antigen restoration, then, performing multiple fluorescent staining on the preprocessed slice, and finally, counting the number of TiMs by a fluorescent microscope.
5. The subtype of CICs in different subtype breast cancer tumor tissues is related to the prognosis of patients
Breast cancer can be divided into 5 subtypes based on the expression levels of tumor cytokine receptor (HR), human epidermal growth factor receptor 2 (HER 2, huaman Epidermal Growth Factor-2), and Ki-67:
(1) The luminalA subtype: ER (estrogen receptor) and PR (progestin receptor) positive (> 1%), histologically graded grade 1-2, HER2 negative, ki-67<14%;
(2) Luminel B (HER 2-) subtype: ER (estrogen receptor) and or PR (progestin receptor) positive (> 1%), histologically graded grade 3, HER2 negative; ki-67 is more than or equal to 14%;
(3) Luminel B (her2+) subtype: ER (estrogen receptor) and or PR (progestin receptor) positive (> 1%), histological grading is unlimited, HER2 positive; ki-67 is not limited;
(4) HER2 positive subtype: HER2 positive, HR negative;
(5) TNBC subtype: HR and HER2 were both negative. The treatment and prognosis of breast cancer vary from subtype to subtype. Wherein, the luminalA subtype accounts for most of all breast cancers, and has better prognosis; HER2 positive and TNBC subtype prognosis was poor.
1. The number of MiTs in the luminal subtype breast cancer is prognostic-related
Of the 148 breast cancers, 69 were of the luminal a subtype, and analysis of CIC numbers and survival in this fraction of patients showed that the number of mits correlated with patient prognosis. The specific method comprises the following steps: the number of MiTs in this subtype of tumor tissue was counted and the Kaplan-Meier method was used to draw survival curves. Patients were divided into 2 groups according to the presence or absence of MiT in tumor tissue, with a number of MiT greater than or equal to 1 defined as the MiT positive group (MiT+), and a number of MiT 0 defined as the MiT negative group (MiT-).
The prognosis survival rate of the test patients with MiT subtype is smaller than the prognosis survival rate of the test patients without MiT subtype.
The Kaplan-Meier analysis results are shown in fig. 3a, where the median survival times for the patients in the mix positive and mix negative groups were (147 months and not yet reached), respectively, and the survival rates were statistically different (p=0.017), indicating that the patients with mix positive were worse than the patients with mix negative were predicted.
2. MiT number in Luminal B (HER 2-) subtype breast cancer correlated with prognosis
Of the 148 breast cancers, 16 were of the Luminal B (HER 2-) subtype, and analysis of CIC numbers and survival of this fraction of patients showed that the number of MiTs correlated with patient prognosis. The specific method comprises the following steps: the number of MiTs in this subtype of tumor tissue was counted and the Kaplan-Meier method was used to draw survival curves. Patients were divided into 2 groups according to the presence or absence of MiT in tumor tissue, with a number of MiT greater than or equal to 1 defined as the MiT positive group (MiT+), and a number of MiT 0 defined as the MiT negative group (MiT-).
The prognosis survival rate of the test patients with MiT subtype is smaller than the prognosis survival rate of the test patients without MiT subtype.
The Kaplan-Meier analysis results are shown in fig. 3b, where the median survival times for the patients in the mix positive and mix negative groups were (85 months and not yet reached), respectively, and the survival rates were statistically different (p=0.006), indicating that the mix positive patients were worse than the mix negative patients.
3. The number of oCICs and TiT in Luminal B (HER2+) subtype breast cancer is correlated with prognosis
Of the 148 breast cancers, 19 were of the Luminal B (HER2+) subtype, and analysis of CIC numbers and survival of this patient showed that oCICs and TiT numbers correlated with prognosis. The numbers of oCICs and TiT in the subtype tumor tissues are counted respectively, and a survival curve is drawn by a Kaplan-Meier method.
1)oCICs
Patients were divided into 2 groups according to the number of CICs in tumor tissue, with an oCICs number greater than 15 defined as the High-oCICs group and an oCICs number less than or equal to 15 defined as the Low-oCICs group.
The prognosis survival rate of the patients to be tested with the number of oCICs being more than 15 is more than the prognosis survival rate of the patients to be tested with the number of oCICs being less than or equal to 15.
As shown in FIG. 4a, the Kaplan-Meier analysis results show that the median survival time of the Low-oCICs group and the High-oCICs group patients is 95 months and not yet reached, respectively, and the survival rate has a statistical difference (P=0.008), which shows that the High-oCICs group patients have better prognosis compared with the Low-oCICs group patients.
2)TiT
Patients were divided into 2 groups according to TiT number in tumor tissue, tiT number greater than 15 defined as High-TiT group and TiT number less than or equal to 15 defined as Low-TiT group.
The number of TiT patients to be tested is greater than 15, and the number of TiT patients to be tested is less than or equal to 15.
As shown in FIG. 4b, the results of Kaplan-Meier analysis show that the median survival times of the Low-TiT patients and the High-TiT patients are 87 months and not yet reached, respectively, and the survival rates have statistical differences (P < 0.001), which shows that the High-TiT patients have better prognosis compared with the Low-TiT patients.
4. TiM number in HER2+ or TNBC subtype breast cancer is correlated with prognosis
Of the 148 breast cancers, 19 were HER2+ subtype, 25 were TNBC subtype, and 44 patients were counted in total from HER2+ and TNBC subtypes. Analysis of CIC number and survival in this portion of the patients showed that TiM number correlates with patient prognosis. The specific method comprises the following steps: the number of TiMs in tumor tissues of patients was counted and a survival curve was drawn by the Kaplan-Meier method. Patients were divided into 2 groups according to the presence or absence of TiM in tumor tissue, the number of TiM being 1 or more was defined as TiM positive group (TiM+), and the number of TiM being 0 was defined as TiM negative group (TiM-).
The prognosis survival rate of the patients tested for the presence of the TiM subtype is greater than the prognosis survival rate of the patients tested for the absence of the TiM subtype.
The Kaplan-Meier analysis results are shown in fig. 5, where the median survival times of the patients in the TiM negative group and the TiM positive group were (65 months and not yet reached), respectively, and the survival rates were statistically different (p=0.011), indicating that the patients with TiM negative were worse than the patients with TiM positive were predicted.
6. oCIC, tiT, miT and TiM numbers are independent prognostic factors for breast cancer
To determine whether the CIC numbers described above can be used to predict prognosis of breast cancer patients independently, a Cox regression multifactorial analysis was used, with SPSS software. The numbers of oCIC, tiT, miT and TiM were analyzed for multiple factors with the sex, age, TNM staging and molecular subtype of the patient, respectively.
The results are shown in tables 1 to 4,
oCIC is an independent factor in predicting prognosis of breast cancer, HR is 0.432 (95% CI: 0.227-0.785), P is 0.006, and there is a statistical difference (Table 1).
TiT is an independent factor in predicting prognosis of breast cancer, HR is 0.529 (95% CI: 0.288-0.973), P is 0.04, with statistical differences (Table 2).
MiT is an independent factor in predicting prognosis of breast cancer, HR is 2.608 (95% CI: 1.344-5.063), P is 0.05, and statistical differences are insignificant (Table 3).
TiM is an independent factor in predicting prognosis of breast cancer, with an HR of 0.524 (95% CI: 0.286-0.962), a P value of 0.037, and a statistical difference (Table 4).
TABLE 1 Cox multifactorial analysis shows that oCICs numbers are independent predictors of prognosis for breast cancer
TABLE 2 Cox multifactor analysis shows that TiT number is an independent predictor of prognosis for breast cancer
TABLE 3 Cox multifactorial analysis shows that the number of MiTs is likely an independent predictor of prognosis for breast cancer
| Variable(s) | Number of examples | HR(95％CI) | P value |
| MiT | 2.608(1.344-5.063) | 0.05 | |
| ＝0 | 122 | ||
| ≥1 | 26 | ||
| Age of | 2.173(1.138-4.147) | 0.019 | |
| ≤60 | 105 | ||
| >60 | 43 | ||
| TNM staging | 2.117(1.192-3.759) | 0.01 | |
| Ⅰ | 13 | ||
| Ⅱ | 91 | ||
| Ⅲ | 44 | ||
| Subtype type | 1.310(1.081-1.588) | 0.006 | |
| Luminal A | 69 | ||
| Luminal B(HER2+) | 19 | ||
| Luminal B(HER2-) | 16 | ||
| HER2+ | 15 | ||
| TNBC | 29 |
TABLE 4 Cox multifactor analysis shows that TiM number is an independent predictor of prognosis for breast cancer
7. MiT is an independent prognostic factor in HR+/HER 2-breast cancer patients
hr+/HER 2-breast cancer patients include the luminal a and luminal b (HER 2-) subtypes, which account for the vast majority of breast cancer patients. To determine whether the above number of mits can independently predict prognosis for this portion of breast cancer patients, a Cox regression multifactor analysis was employed, and the statistical analysis used SPSS software. The number of MiTs was multifactorial analyzed separately from the histological grading, size and TNM grading of the tumors, and the results are shown in Table 5, with MiTs being independent prognostic factors in HR+/HER 2-breast cancer patients, HR being 5.854 (95% CI: 2.239-15.310), P <0.001, with statistical differences (Table 5).
TABLE 5 MIT is an independent prognostic factor in HR+/HER 2-breast cancer patients
Claims (6)
1. Use of a substance that detects the number of at least one structure of a-C in breast cancer tissue of a breast cancer patient in the preparation of a product for predicting the prognosis survival of a breast cancer patient;
A. an oCIC; B. subtype TiT; c. A TiM subtype;
the oCIC is all subtypes of CICs; the CICs are of a Cell-in-Cells structure;
the subtype of the CICs consists of TiT subtype, miT subtype, tiM subtype, liM subtype and LiT subtype;
the TiT subtype is a homogenous CICs structure formed by tumor cells phagocytizing tumor cells;
the MiT subtype is a CICs structure formed by phagocytic macrophages of tumor cells;
the TiM subtype is CICs structure formed by phagocytic tumor cells of macrophages;
the LiM subtype is CICs structure formed by phagocytic lymphocyte of macrophage;
the LiT subtype is a CICs structure formed by tumor cell phagocytic lymphocytes;
the product further comprises: readable carrier for recording at least one criterion of the following 1) -3):
1) The prognosis survival rate of the patients to be tested with the oCIC number being more than 15 is more than the prognosis survival rate of the patients to be tested with the oCIC number being less than or equal to 15;
2) The patients to be tested with the TiT subtype number being more than 15 have a prognosis survival rate of more than TiT subtype number being less than or equal to 15;
3) The prognosis survival rate of the patients tested for the presence of the TiM subtype is greater than the prognosis survival rate of the patients tested for the absence of the TiM subtype.
2. The use according to claim 1, characterized in that: the substance for detecting the number of at least one structure of A-C in the breast cancer tissue of the breast cancer patient is a substance for detecting the number of any structure of A-C in the breast cancer tissue of the breast cancer patient.
3. The use according to claim 1, characterized in that: the substance for detecting the number of at least one structure of A-C in the breast cancer tissue of the breast cancer patient is a substance for detecting the number of structures of any combination of A and B-C in the breast cancer tissue of the breast cancer patient.
4. A use according to any one of claims 1-3, characterized in that:
such substances include E-cadherin antibodies, CD68 antibodies, CD45 antibodies, and fluorescent antibodies or fluorochromes capable of binding to the three antibodies, respectively.
5. The use according to claim 4, characterized in that:
the fluorescent antibodies or fluorescent dyes capable of respectively binding the three antibodies have different fluorescent colors or wavelengths.
6. Use according to any one of claims 1-5, characterized in that: the breast cancer patients are breast cancer patients of a luminalA subgroup, breast cancer patients of a luminalB HER 2-subgroup, breast cancer patients of a luminalB HER2+ subgroup and breast cancer patients of a HER2+ subgroup and/or triple negative breast cancer subgroup.
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