JP2018084568A - INSPECTION SUPPORT METHOD FOR SUPPORTING PREDICTION OF PATHOLOGICAL PERFECT RESPONSE (pCR) USING FLUORESCENT NANOPARTICLE - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide means (an inspection support method) for predicting if there will be pathological perfect response (pCR) if chemotherapy before operation using anticancer agents is carried out by using a sample (tissue slice of breast cancer) collected from a breast cancer patient to whom the chemotherapy before operation using anticancer agents is carried out.SOLUTION: An inspection support method includes the steps of: [1] obtaining a fluorescent image of a breast cancer tissue slice displaying luminescent spots of fluorescent nanoparticles labelling one or more types of breast cancer related protein; [2] obtaining one or more types of indexes related to an expression level of the breast cancer related protein on the basis of the luminescent spots of the fluorescent image; and [3] obtaining information for predicting pCR by analysis using the one or more types of indexes.SELECTED DRAWING: None

Description

  The present invention relates to a test support method for supporting prediction of pathological complete response (pCR) of breast cancer preoperative therapy using a sample of breast cancer tissue collected from a breast cancer patient performing preoperative chemotherapy. More specifically, the present invention predicts pCR by fluorescently labeling a breast cancer-related protein on a tissue section using fluorescent nanoparticles and analyzing using an index relating to the expression level of the breast cancer-related protein obtained from the fluorescent image. The present invention relates to an inspection support method including obtaining information for performing the operation.

  Preceding treatment with an anticancer drug before surgery for breast cancer is called “preoperative chemotherapy” or “neoadjuvant chemotherapy”. Preoperative chemotherapy is mainly used in the era of mastectomy in the 1970s, mainly for patients with locally advanced breast cancer whose cancer has spread to surrounding tissues and lymph nodes and cannot be completely removed by surgery alone. It was done for the purpose of enhancing the effect. Some patients were thought to be effective, but their effects were not always positively evaluated, and the main goal of treatment was “improving prognosis (survival)” compared to chemotherapy given after surgery. "It has been thought not to lead to. However, recently, excellent anticancer agents and hormonal therapeutic agents have been developed, and the therapeutic effect can be enhanced by combining with surgery. For this reason, it has also been proposed that preoperative chemotherapy be called PST (primary systemic treatment) in the sense that it is used on an equal footing with surgery.

  The state of cancer cells completely disappearing by preoperative chemotherapy, confirmed by microscopic histopathological methods, is called pathological complete response (pCR). It becomes an index that can be judged that the agent was effective.

  Here, the molecular target therapeutic drug “Trastuzumab” (trade name “Herceptin” (registered trademark), anti-HER2 monoclonal antibody) that specifically targets the HER2 protein expressed on the cell surface is “transposition in which HER2 overexpression has been confirmed. It is an anti-cancer agent that has been confirmed to have certain effects and effects on “fertile breast cancer” and in “postoperative adjuvant chemotherapy in breast cancer in which HER2 overexpression has been confirmed”. The HER2 protein is thought to perform signal transduction by forming a homodimer or a heterodimer bound to activated EGFR (HER1), HER3 or HER4, and is used as a receptor for cancer cell growth factor. Presumed to be functional (to date no endogenous ligand binding to HER2 is known). In human breast cancer cases, HER2 gene amplification and HER2 protein overexpression are observed in 15 to 25%. For example, breast cancer patients with HER2 gene amplification / HER2 protein overexpression have a poor prognosis, and anthracycline system There are also reports of high sensitivity to anticancer drugs (such as doxorubicin) and reports of treatment resistance to hormonal therapy (such as tamoxifen) and CMF therapy (combined with cyclophosphamide, methotrexate, and fluorouracil). is there. From the viewpoint of improving the cure rate and medical economics, the HER2 gene (HER2 / neu, c-erbB-2) is amplified and / or the HER2 protein overexpression is examined and judged in order to select Herceptin target cases. In order to manage its accuracy, the ASCO / CAP HER2 inspection guidelines were established in 2007 and revised in 2013.

  In Japan, the determination of HER2 protein overexpression using the immunohistochemistry (IHC) method and the HER2 gene using the in situ hybridization (ISH) method in accordance with the revised ASCO / CAP HER2 test guidelines Amplification is being determined (HER2 Examination Guide Fourth Edition, Breast Cancer HER2 Examination Pathology Committee, April 2014). For these determinations, a formalin-fixed paraffin-embedded tissue block (specimen) is prepared from the primary or metastatic tissue of breast cancer, and a slide on which the sliced slice is placed is stained according to a predetermined procedure. The In the IHC method, the staining property and the staining intensity of cancer cells in a tissue section are determined according to a predetermined standard (staining pattern), and 3+ (positive:> 10% of cancer cells having a complete circumference that is strong in cancer cells. Membrane staining is observed) 2+ (equivocal:> 10% cancer cells are incomplete and / or weak or moderate circumferential membrane staining is observed, or ≦ 10% cancer cells are completely intact 1+ (negative:> 10% cancer cells have faint or barely partial membrane staining) or 0 (negative: no staining image is observed, ≦ 10% of tumor cells are incomplete and faint or barely membrane staining is observed). In the ISH method, the ratio of the number of HER2 gene signals on a chromosome contained in cancer cells in a tissue section to the number of CEP17 gene signals as a control (HER2 / CEP2 ratio) and 1 cell of HER2 gene copy number Per mean (HER2 gene average copy number), positive (HER2 / CEP2 ratio ≧ 2.0, or HER2 / CEP2 ratio <2.0 and HER2 gene average copy number ≧ 6.0), equal (HER2 / CEP2 Ratio <2.0 and HER2 gene average copy number ≧ 4.0 to <6.0) or negative (HER2 / CEP2 ratio <2.0 and HER2 gene average copy number <4.0). The average HER2 gene copy number is commonly referred to as the ISH score. When the ISH method is performed first, if the result is positive, it is judged that there is an indication for treatment with trastuzumab, and even if equicalcal, the IHC method is performed on the same sample and the result is positive or different. If the specimen is subjected to the IHC method or ISH method and the result is positive, it is determined that treatment with trastuzumab is indicated. When the IHC method is performed first, if the result is positive (3+), it is judged that treatment with trastuzumab is indicated. Even if equivacal (2+), the result is obtained by performing the ISH method on the same specimen. If the result is positive or if the result of IHC or ISH is performed on a different sample and the result is positive, it is determined that treatment with trastuzumab is also applicable.

  Here, in the IHC method, conventionally, an anti-HER2 antibody labeled with an enzyme (peroxidase) is bound to a HER2 protein contained in a tissue section of a tissue slide by a direct method or an indirect method, and then a substrate (diaminobenzidine) is added. The DAB staining method (IHC-DAB method), which develops color by reacting, has been generally performed. However, staining with an enzyme such as DAB staining has a problem in that it is difficult to accurately estimate the actual amount of antigen or the like from the staining concentration because the staining concentration greatly depends on environmental conditions such as temperature and time. .

  Therefore, in recent years, instead of a method of evaluating the expression level of a target protein such as HER2 using a dye (generated from a substrate by an enzyme) as in the IHC-DAB method, nano-sized fluorescent particles such as a fluorescent dye And a method for evaluating the expression level of a target protein (IHC-PID method) using particles (phosphor integrated particles: Phosphor Integrated Dot: PID) in which phosphors such as quantum dots are integrated as a base material. Practical use is in progress. When the target protein is labeled using fluorescent particles and irradiated with excitation light that matches the fluorescent substance, the fluorescent particles should be observed as bright spots with high accuracy that indicate the number and position of the target protein. In addition, since the bright spot is not easily faded, observation and imaging can be performed for a long time. For example, International Publication 2012/029342 pamphlet (Patent Document 1), International Publication 2013/146741 pamphlet (Patent Document 2), etc., may be referred to as phosphor integrated particles (fluorescent aggregates, fluorescent substance integrated particles, etc.). The IHC-PID method for immunostaining the target protein using the

  The above patent document relates to a method for quantifying a breast cancer-related protein such as HER2 or a breast cancer-related gene using phosphor-aggregated particles. However, in the above-mentioned patent document and other patent documents and non-patent documents, there is a pathological complete response (pCR) when preoperative chemotherapy is performed using an anticancer agent by such a quantitative method. It is not described that it can be predicted whether or not it will be, and the test support method based on this prediction.

International Publication 2012/029342 Pamphlet International Publication 2013/146741 Pamphlet

  The present invention predicts whether or not a pathological complete response (pCR) will be obtained when preoperative chemotherapy using an anticancer agent is performed, using a sample collected from a breast cancer patient who performs preoperative chemotherapy. It is an object to provide a means (inspection support method) for doing this.

  Upon completion of the present invention, the inventors collected samples from Tohoku University Hospital in 2007-2014 or JBCRG-16 (Neo-LaTH test) in 2016 at JBCRG (Japan Breast Cancer Research Group). Samples were used. All samples are permitted for use by Tohoku University School of Medicine Ethics Committee and JBCRG. That is, at the completion of the present invention, samples (pCR group) collected before performing preoperative chemotherapy from a plurality of breast cancer patients who finally became pCR, and a plurality of samples that did not finally become pCR. Using a sample (non-pCR group) collected from a breast cancer patient before performing preoperative chemotherapy, the expression level of HER2 contained in each sample was determined using the IHC-PID method, IHC-DAB method, and FISH method. The results of the pCR group were compared with the results of the non-pCR group. Similarly, the expression levels of breast cancer-related proteins other than HER2, such as HER1 and HER3, were similarly quantified by the IHC-PID method, the IHC-DAB method, and the FISH method, and the results of the pCR group and the results of the non-pCR group were compared. . Furthermore, in the IHC-PID method, histograms were created from the quantification results of the expression level of HER2, and the distribution patterns were compared between the pCR group and the non-pCR group.

  The expression level of HER2 was quantified by the IHC-DAB method (in the case where the color development intensity of DAB measured by the apparatus was used as an index instead of the four-stage score according to the HER2 test guide) or the result quantified by the FISH method (described above) With such HER2 gene average copy number (FISH score) as an index), no statistically significant difference was observed between the pCR group and the non-pCR group (FIGS. 13 and 14). In the IHC-DAB method or the FISH method, no such significant difference has been reported so far, and the fact that no significant difference is observed is recognized as a reconfirmation of a well-known fact.

  On the other hand, in the result quantified by the IHC-PID method, when the number of PID particles per unit area of tissue is used as an index of expression (PID score), or the average number of PID particles per cell is used as an index of expression ( In any case where the PID score was used, a statistically significant difference was observed between the pCR group and the non-pCR group (FIGS. 15 and 16). Further, the expression level of HER2 and the expression level of HER1 or HER3 determined by the IHC-PID method are combined. For example, the ratio of the expression level of HER2 to the expression level of HER1 (HER2 expression level / HER1 expression level) or HER3 When the value of the ratio of the expression level of HER2 to the expression level (HER2 expression level / HER3 expression level) was calculated and the results of the pCR group and the non-pCR group were compared, the statistically significant difference was found. It was recognized (FIGS. 21 and 22). Furthermore, the distribution pattern of the histogram showing the expression level of HER2 quantified by the IHC-PID method was also found to have a difference in tendency between the pCR group and the non-pCR group. In addition, the evaluation of the expression level by the IHC-DAB method according to the HER2 test guide is limited to the four-stage non-quantitative score (3+, 2+, 1+ and 0) as described above, and the FISH method is also evaluated in the same stage. (Her2 / CEP2 ratio is 2.0 or more and less than 2.0, and HER2 gene average copy number is 6.0 or more, 4.0 or more and less than 6.0, or less than 4.0) Therefore, even if a histogram can be created based on such an evaluation result, a feature cannot be found in the distribution pattern because the number of classes is small. Moreover, although a histogram can be created from quantitative evaluation using the color development intensity of the IHC-DAB method as an index, no clear difference is seen in the trend between the pCR group and the non-pCR group.

  Here, the conventional FISH method counts the number of signals by the fluorescent dye (although the object is a gene), and the bright spot of the IHC-PID method of the present invention (the object is a protein), that is, the fluorescent nanoparticles. Similar to counting numbers. However, in many cases, in the FISH method, a plurality of fluorescent dyes aggregate (form a cluster) to give a large signal. In such a case, when counting the number of signals, a larger signal has a FISH score of 5 Or a moderate signal is counted as 3 as the FISH score. Under such a rule, it is difficult to say that the exact number of HER2 genes is counted, and in principle, the exact number cannot be counted. Therefore, since the quantitative value of the average copy number of the HER2 gene by the FISH method is inaccurate, it is considered that a clear difference in tendency between the pCR group and the non-pCR group could not be derived.

  On the other hand, since the present invention obtains an accurate number of HER2 proteins according to the principle described below, it is considered that the number of bright spots (PID score) in the histogram also has an accuracy of two digits or more. Therefore, it is considered that the effect of being able to predict whether or not it would be pCR, which could not be found from quantification using the coloring intensity of the IHC-DAB method and the fluorescence intensity of the FISH method as an index, was obtained. In the future, as an improved method of the FISH method, based on the results of the HER2 gene quantification method using fluorescent nanoparticles (ISH-PID method), prediction of pCR will be made by histogramming and typification of its distribution pattern. It may be possible to do this.

  It can be summarized that the principle of quantitativeness of the present invention is to mark one breast cancer-related protein such as HER2 contained in a patient specimen tissue with one fluorescent nanoparticle. HER2 detection by the IHC-DAB method or the FISH method uses an amplification reaction, that is, a plurality of dye molecules are generated or a fluorescent dye is bound to one protein or gene. The size of the middle dot) is not constant, and it is unclear how many HER2 proteins it corresponds to even if the dots overlap. According to the above quantitative principle of the present invention, counting the number of fluorescent nanoparticles is synonymous with counting the number of specific breast cancer-related proteins, and accurately counting the number of breast cancer-related proteins is It is thought that it accurately leads to the prediction of pCR with high accuracy by accurately grasping the characteristics of the patient's breast cancer.

  By the way, the above hypothesis regarding the principle of quantification of the present invention, that is, marking a single breast cancer-related protein with a single fluorescent nanoparticle, has recently been proved from observation results with an atomic force microscope (AFM). It was. As shown in a reference example described later, the inventors measured the binding force between streptavidin bound to the PID surface and biotin immobilized on a solid phase by assembling the evaluation system shown in FIG. 24 and performing a binding assay. As a result, it was concluded that the corresponding binding force was 40 pN as a difference between the measured value of condition I (C in FIG. 25) and the measured value of Condition II (D in FIG. 25). This value was equivalent to the binding force value of one streptavidin molecule and one biotin molecule reported by many researchers so far. That is, as disclosed in the examples described later, even in an embodiment in which PID modified with streptavidin is bound to a biotin-modified secondary antibody that is indirectly bound to HER2, The speculation that one PID is bound per protein is well supported.

  Based on the above findings, the inventor collects specimens from breast cancer patients undergoing preoperative chemotherapy, and quantifies the expression level of HER2 or other breast cancer-related proteins according to the IHC-PID method. It was found that it is possible to predict whether or not the breast cancer patient will have pCR by comparing a converted value such as the calculated ratio value with a predetermined threshold value derived in advance from the above-described findings. In addition, regarding the distribution pattern of the histogram representing the expression level of HER2 by the IHC-PID method, by determining whether the distribution pattern is well applied to the pCR group derived in advance from the above-described knowledge, the breast cancer patient is identified as pCR. We have also found that it is possible to predict whether or not Furthermore, the prediction result when comparing the above quantitative value and the threshold with the prediction result when comparing the distribution pattern of the histogram is combined, and when both are prediction results that become pCR, it is higher. It has also been found that pCR can be predicted with accuracy.

  In particular, after measuring the expression level of a specific protein contained in a specimen (sliced tissue slice) as the number of bright spots or the number of fluorescent signals of fluorescent nanoparticles using a specimen from a breast cancer patient undergoing preoperative chemotherapy , Characterized by the process of creating a histogram of measured values, that is, the histogram obtained after creating a histogram with the horizontal axis representing the number of bright spots or particles per cell (average expression level) and the vertical axis representing the number of cells. The assessment of breast cancer-related molecules by stratifying the distribution pattern of breast cancer is brand new, and this assessment method can be a useful tool to help predict pathological complete response (pCR) That is an interesting fact.

That is, the present invention includes the following inventions.
[Claim 1]
A test support method that supports the prediction of complete pathological response (pCR) of breast cancer preoperative therapy using a sample of breast cancer tissue collected from a breast cancer patient undergoing preoperative chemotherapy,
[1] A step of acquiring a fluorescent image of a breast cancer tissue section in which bright spots of fluorescent nanoparticles labeled with one or more types of breast cancer-related proteins are represented,
[2] A step of obtaining one or more indicators relating to the expression level of the breast cancer-related protein based on the bright spot of the fluorescent image, and [3] pCR prediction by analysis using the one or more indicators Acquiring information for
Inspection support method including
[Section 2]
The step [1] is a step of acquiring a fluorescent image of a breast cancer tissue section in which bright spots of fluorescent nanoparticles labeled with at least two types of breast cancer-related proteins containing HER2 are represented,
The step [2] acquires, as the index, a numerical value representing the expression level of each of the two or more types of breast cancer-related proteins, or a numerical value calculated from a combination of the numerical values, based on the bright spot of the fluorescent image. Process,
The step [3] is a step of obtaining information for predicting pCR by analysis including comparing the numerical value with a predetermined threshold value.
The inspection support method according to Item 1.
[Section 3]
The step [1] is a step of obtaining a fluorescent image of a breast cancer tissue section in which fluorescent luminescent spots of fluorescent nanoparticles labeled with one or more types of breast cancer-related proteins are represented.
The step [2] is a step of acquiring a histogram based on the expression level of each cell of the breast cancer-related protein based on the bright spot of the fluorescent image and acquiring it as the index,
The step [3] is a step of obtaining information for predicting pCR by an analysis including at least typifying the distribution pattern of the histogram.
The inspection support method according to Item 1.
[Claim 4]
The step [1] is a step of obtaining a fluorescent image of a breast cancer tissue section in which fluorescent luminescent spots of fluorescent nanoparticles labeled with one or more kinds of breast cancer-related proteins containing at least HER2 are represented;
The step [2] is a step of creating a histogram based on at least the expression level of each HER2 cell based on the base point of the fluorescence image and acquiring it as the index,
The step [3] is a step of obtaining information for predicting pCR by an analysis including at least typifying the distribution pattern of the histogram.
The inspection support method according to Item 3.
[Section 5]
The step [1] is a step of acquiring a fluorescence image of a breast cancer tissue section in which the fluorescent bright spots of fluorescent nanoparticles labeled with HER2 and HER1 or HER3 are represented,
The step [2] obtains a numerical value representing each expression level of HER2 and HER1 or HER3 based on the bright spot of the fluorescent image, and (a) a numerical value representing the expression level of HER2 / expression of HER1 A numerical value representing the amount, or (b) a numerical value representing the expression level of HER2 / a numerical value representing the expression level of HER3.
The step [3] is a step of obtaining information for predicting pCR by analysis including comparing the value of the ratio of either (a) or (b) with a predetermined threshold value.
Item 3. The inspection support method according to Item 2.
[Claim 6]
The step [1] is a step of acquiring a fluorescent image of a breast cancer tissue section in which the fluorescent bright spots of fluorescent nanoparticles labeled with HER2 are represented,
In the step [2], based on the bright spot of the fluorescence image, (a) a numerical value representing the expression level of HER2 is acquired as the index, and (b) a histogram based on the expression level of each cell of HER2 is created. And obtaining as the index,
Information for predicting pCR by the analysis including the combination of (a) comparing the numerical value with a predetermined threshold and (b) typifying the distribution pattern of the histogram in the step [3]. Is the process of obtaining
Item 5. The examination support method according to Item 4.
[Claim 7]
Item 2, 4 wherein in step [1], two or more kinds of breast cancer-related proteins including at least HER2 are labeled with two or more kinds of fluorescent nanoparticles corresponding to each on one breast cancer tissue section. 5. The inspection support method according to 5 or 6.

  According to the present invention, it is possible to determine with high accuracy whether or not it can be expected to become pCR, not just determining whether to apply an anticancer drug (trastuzumab or the like) as in the conventional HER2 test. And its clinical significance is extremely large.

FIG. 1 shows a DAB-stained image (A), a PID-stained image (B), a hematoxylin-stained image (C), and a PID-stained image and a hematoxylin-stained image of an example of a breast cancer patient in the pCR group disclosed by Example 1 (D) and a DAB-stained image (E), a PID-stained image (F), a hematoxylin-stained image (G), and a PID-stained image and a hematoxylin-stained image (H) of an example of a breast cancer patient in the non-pCR group. FIG. 2 is a box plot showing the IHC-DAB color development intensity (color development intensity per unit area of tissue) of the HER2 protein of each of the pCR group and the non-pCR group disclosed by Example 1. FIG. 3 is a box plot showing the FISH score of the HER2 gene of each of the pCR group and the non-pCR group disclosed by Example 1. FIG. 4 is a box plot showing the PID score (number of PID particles per unit area of tissue) of the HER2 protein of each of the pCR group and the non-pCR group disclosed by Example 1. FIG. 5 shows IHC-DAB of HER2 protein disclosed in Example 2 in a survival group of 100 months or more after surgery (corresponding to a pCR group) and a survival group of less than 100 months after surgery (corresponding to a non-pCR group). It is a box plot showing coloring intensity (coloring intensity per unit area of tissue). FIG. 6 is a box plot showing the FISH score of the HER2 gene of each of the survival group of 100 months or more after surgery and the survival group of less than 100 months after surgery, disclosed in Example 2. FIG. 7 is a box showing the PID score (number of PID particles per unit area of tissue) of the HER2 protein in the survival group of 100 months or more after surgery and the survival group of less than 100 months after surgery, disclosed in Example 2. It is a plot. FIG. 8 is a ROC curve (receiver operating characteristic curve) for the PID score of the HER2 protein disclosed by Example 2. FIG. 9 is a box that represents the PID score (number of PID particles per unit area of tissue) of the HER1 protein survival group disclosed in Example 2 for the survival group of 100 months or more after surgery and the survival group of less than 100 months after surgery. It is a plot. FIG. 10 is a box plot showing the PID score ratio of HER2 / HER1 of the survival group of 100 months or more after surgery and the survival group of less than 100 months after surgery, disclosed in Example 2. FIG. 11 is an explanatory diagram for explaining a process of creating a histogram created from the PID score of the HER2 protein disclosed in Example 3 and Example 4. FIG. 12 (FIGS. 12-1 and 12-2) is a histogram created from the PID score of the HER2 protein disclosed by Example 3. FIG. 13 is a box plot showing the IHC-DAB color intensity (color intensity per cell) of the HER2 protein of the pCR group and the non-pCR group disclosed in Example 4. FIG. 14 is a box plot showing the FISH score (HER2 gene average copy number) of the HER2 gene of each of the pCR group and the non-pCR group disclosed by Example 4. FIG. 15 is a box representing the PID score (number of PID particles per unit area of tissue) of the HER2 protein of each of the pCR group (n = 48) and the non-pCR group (n = 33) disclosed by Example 4 It is a plot. FIG. 16 is a box plot showing the PID score (number of PID particles per cell) of the HER2 protein of each of the pCR group and the non-pCR group disclosed by Example 4. FIG. 17 is a ROC curve (receiver operating characteristic curve) for the PID score (number of PID particles per cell) of the HER2 protein disclosed by Example 4. FIG. 18 is a box plot representing the PID score (number of PID particles per cell) of the HER1 protein disclosed by Example 4. FIG. 19 is a box plot showing the PID score ratio (number of PID particles per cell) of HER2 / HER1 for each of the pCR group and the non-pCR group disclosed by Example 4. FIG. 20 is a box plot representing the PID score (number of PID particles per cell) of the HER3 protein disclosed by Example 4. FIG. 21 is a box plot showing the HER2 / HER3 PID score ratio (number of PID particles per cell) for each of the pCR group and the non-pCR group disclosed in Example 4. FIG. 22 is a box plot showing the PID score ratio (number of PID particles per cell) of HER3 / HER2 for each of the pCR group and the non-pCR group disclosed by Example 4. FIG. 23 is a flowchart of an inspection support method according to an embodiment of the present invention. FIG. 24 is a schematic diagram of the evaluation system shown in the reference example. FIG. 25 is a diagram relating to the evaluation of the binding force between one PID particle and a specific density of biotin shown in the reference example. (A) A schematic diagram of AFM measurement. (B) SEM image of an AFM cantilever coated with PID. The binding force of PID particles (arrows) located at the tip of the AFM cantilever was measured. (C) Histogram based on measured value of binding force-distance under condition I. (D) Histogram based on measured value of binding force-distance in condition II. (E) Histogram based on measured value of binding force-distance in condition III.

The test support method of the present invention is a test support method that supports the prediction of pathological complete response (pCR) of breast cancer preoperative therapy using a sample of breast cancer tissue collected from a breast cancer patient who is undergoing preoperative chemotherapy. Basically, the following steps [1], [2] and [3] are included:
Step [1] A step of obtaining a fluorescent image of a breast cancer tissue section in which bright spots of fluorescent nanoparticles labeled with one or more types of breast cancer-related proteins are represented;
Step [2] obtaining one or more types of indices relating to the expression level of the breast cancer-related protein based on the bright spot of the fluorescence image; and Step [3] pCR by analysis using the one or more types of indices. The process of acquiring information for predicting.

  Breast cancer patients who take a sample of breast cancer tissue may be in the state before starting preoperative chemotherapy or before the end of preoperative chemotherapy (ie during preoperative chemotherapy) It may be in a state.

The inspection support method of the present invention can be roughly divided into two according to the characteristics of the preferred embodiment.
In the first embodiment of the test support method, in step [1], two or more types of breast cancer-related proteins including at least HER2, that is, HER2 and one or more other types of breast cancer-related proteins are labeled with fluorescent nanoparticles. And In step [2], a numerical value representing the expression level of each of the two or more types of breast cancer-related proteins, that is, a numerical value representing the expression level of HER2 and a numerical value representing the expression level of one or more other breast cancer-related proteins. A numerical value obtained by dividing or by dividing a numerical value calculated from a combination of those numerical values, for example, a numerical value representing the expression level of HER2, by a numerical value representing the expression level of other breast cancer-related protein is acquired. In step [3], an analysis including comparing the numerical value as the index with a predetermined threshold is performed.

That is, the first embodiment of the inspection support method of the present invention includes the following steps [1], [2] and [3].
Step [1] A step of acquiring a fluorescent image of a breast cancer tissue section in which bright spots of fluorescent nanoparticles labeled with two or more kinds of breast cancer-related proteins containing at least HER2 are represented;
Step [2] obtaining, as the index, a numerical value representing the expression level of each of the two or more types of breast cancer-related proteins, or a numerical value calculated from a combination of the numerical values, based on the bright spot of the fluorescent image; and Step [3] A step of obtaining information for predicting pCR by analysis including comparing the numerical value with a predetermined threshold value.

  In the second embodiment of the test support method, in step [2], a histogram based on at least the expression level of each cell of the breast cancer-related protein is created, and in step [3], at least the distribution pattern of the histogram is classified. To perform an analysis that includes

That is, the second embodiment of the inspection support method of the present invention includes the following steps [1], [2] and [3]:
Step [1] A step of obtaining a fluorescent image of a breast cancer tissue section in which fluorescent luminescent spots of fluorescent nanoparticles labeled with one or more types of breast cancer-related proteins are represented;
Step [2] creating a histogram based on the expression level of each cell of the breast cancer-related protein based on the bright spot of the fluorescence image and obtaining it as the index; and step [3] at least the distribution pattern of the histogram Obtaining information for predicting pCR by analysis including typifying.

Further, the test support method of the present invention performs an analysis using a histogram based on an expression level of each cell of HER2 at least in an embodiment in which the first embodiment and the second embodiment are combined. There may be embodiments including the following steps [1], [2] and [3]:
Step [1] A step of obtaining a fluorescent image of a breast cancer tissue section in which fluorescent luminescent spots of fluorescent nanoparticles labeled with at least one or two or more types of breast cancer-related proteins containing HER2 are represented;
Step [2] A step of acquiring, as the index, a histogram based on at least the expression level of each HER2 cell based on the base point of the fluorescence image;
Step [3] A step of obtaining information for predicting pCR by an analysis including at least typifying the distribution pattern of the histogram.

Step [1]: Fluorescence image acquisition step Step [1] included in the test support method of the present invention includes one or more types of breast cancer-related proteins, for example, two or more types of breast cancer-related proteins including at least HER2 (first embodiment). ) Is a step of obtaining a fluorescent image of a breast cancer tissue section in which the bright spots of fluorescent nanoparticles labeled are represented.

(Breast cancer-related protein)
The breast cancer-related protein in the test support method of the present invention is a protein expressed by a cell contained in a breast cancer tissue or a protein existing around such a cell, and is used in preoperative chemotherapy for breast cancer. It is related to the effect of the agent. The breast cancer tissue includes not only breast cancer cells but also cells other than breast cancer cells, for example, cells such as immune cells that interact with tumor cells such as breast cancer cells. The breast cancer-related protein is not limited to a protein expressed by breast cancer cells as long as it is related to the action effect of the anticancer agent, and may be a protein expressed by cells other than breast cancer cells.

  Breast cancer-related proteins include, for example, cancer cell growth factor, cancer cell growth factor receptor, cell surface antigen, vascular growth factor, vascular growth factor receptor, cytokine, cytokine receptor, immune checkpoint protein, cancer growth Among the markers that indicate the ability, these are related to the effects of anticancer agents on breast cancer. Specific examples of the cancer cell growth factor and the cancer cell growth factor receptor include HER1 (EGFR), HER2, HER3, HER4, IGFR, HGFR and the like. Specific examples of the cell surface antigen, vascular growth factor and vascular growth factor receptor include VEGF-A, VEGF-B, VEGF-C, VEGF-D, VEGF-E, PlGF-1, and PlGF-2. . Specific examples of cytokines and cytokine receptors include interferon, interleukin, G-CSF, M-CSF, EPO, SCF, EGF, FGF, IGF, NGF, PDGF, TGF and the like. Specific examples of immune checkpoint proteins include CD40, TL1A, GITR-L, 4-188-L, CX4D-L, CD70, HHLA2, ICOS-L, CD85, CD80, MHC-II, PDL1, PDL2, VISTA, BTNL2, B7-H3, B7-H4, CD48, HVEM, CD40L, TNFRSF25, GITR, 4-188, OX40, CD27, TMIGD2, ICOS, CD28, TCR, LAG3, CTLA4, PD1, CD244, TIM3, BTLA, CD160, LIGHT etc. are mentioned. As a specific example of a marker representing cancer growth ability, Ki67 and the like can be mentioned. Ki67 is a protein that is expressed in the nucleus during cell division, and is used to evaluate the proliferative and malignant grades of breast cancer and other various tumors. For example, Ki67-expressing cell number or expression in breast cancer tissue A method for determining the risk of cancer recurrence by combining the amount and other information has also been proposed (Japanese Patent Laid-Open No. 2011-209220).

  In an example of a preferred embodiment of the present invention, the breast cancer-related protein is a protein that is a target of a molecular target drug effective against breast cancer, for example, HER1 (EGFR), HER2, HER3, VEGFR, PD-L1, PD -1, CTLA-4, Ki67 and the like. For example, a combination of HER2 and HER1 or HER3 is particularly preferable because highly reliable information can be obtained in predicting pCR by the analysis in step [3].

  In an example of a preferred embodiment of the present invention, the breast cancer-related protein is a phosphorylated protein, and examples thereof include HER1 (EGFR), HER2, HER3, and VEGFR. The phosphorylated protein can be quantified by using an antibody that specifically recognizes only a phosphorylated protein among breast cancer-related proteins during immunostaining. If it is desired to quantify the whole breast cancer-related protein regardless of whether it is phosphorylated or non-phosphorylated, an antibody that recognizes them without distinguishing them may be used.

  Anticancer agents used in preoperative chemotherapy for breast cancer are typically molecular targeted drugs that target specific breast cancer-related proteins. For example, trastuzumab (registered trademark “Herceptin”), pertuzumab (registered trademark “ Anti-HER2 humanized monoclonal antibody that specifically binds to the extracellular region domain of HER2 such as “Pergeta”); anti-HER2 humanized monoclonal antibody such as trastuzumab emtandin (registered trademark “cadadoira”) and tubulin polymerization inhibitor And a tyrosine kinase inhibitor targeting the intracellular kinase domain of HER1 (EGFR) and HER2, such as lapatinib tosylate hydrate (registered trademark “Tykerb”). These molecular target drugs may be used singly or in combination, and drugs other than molecular target drugs such as taxane drugs (docetaxel, paclitaxel, etc.) and anthracyclines (doxorubicin, Epirubicin etc.) may be used in combination.

(Fluorescent nanoparticles)
The fluorescent nanoparticles may be non-integrated particles (inorganic phosphors) such as quantum dots and silica dots as long as they can represent bright spots indicating the presence of breast cancer-related proteins in fluorescent images. Alternatively, particles (phosphor integrated particles: PID) in which fluorescent materials such as fluorescent dyes and quantum dots are integrated using a resin or the like as a base material may be used. Examples of PID include fluorescent dye-integrated resin particles prepared using a fluorescent dye as a phosphor and a resin as a matrix; fluorescent dye-integrated silica prepared using a fluorescent dye as a phosphor and silica as a matrix Particles: Inorganic phosphor integrated resin particles prepared using an inorganic phosphor as a phosphor and a resin as a matrix; Inorganic phosphor integrated silica prepared using an inorganic phosphor as a phosphor and silica as a matrix And particles. Among them, fluorescent dyes prepared using fluorescent dyes such as perylene diimide, pyromethene, sulforhodamine 101 or its hydrochloride (Texas Red) as phosphors, and resins such as melamine resins and styrene resins as mother substances. The integrated resin particles are preferable as the fluorescent nanoparticles in the present invention because of excellent labeling performance and the like.

  In the present invention, when phosphor-aggregated particles (PID) are used as the fluorescent nanoparticles, a brightness representing PID for labeling a breast cancer-related protein in a fluorescent image is obtained by adjusting the particle diameter of the fluorescent nanoparticles to a predetermined range. The size of the dots can be a certain size that is preferable for quantifying the expression level. From such a viewpoint, it is preferable that the average particle diameter of PID is 40 nm or more and 160 nm or less. The particle diameter of the PID is the diameter (area circle) when an image is taken using a scanning electron microscope (SEM), the cross-sectional area of the fluorescent labeling resin particles is measured, and the measured value is the area of the corresponding circle. Equivalent diameter). The average particle size and coefficient of variation for a population of PIDs can be calculated as the arithmetic average after measuring the particle size for each of a sufficient number (eg 1000) of PIDs as described above.

  To such fluorescent nanoparticles, an antibody against a breast cancer-related protein (primary antibody, eg, anti-HER2 rabbit monoclonal antibody), an antibody against the primary antibody (secondary antibody, eg, anti-rabbit IgG antibody), primary antibody, or secondary antibody Breast cancer-related proteins can be directly obtained by using a modified form of avidin or an anti-hapten antibody (anti-dicoxygenin antibody, anti-FITC antibody, etc.) that reacts with biotin or a hapten (such as dicoxygenin or FITC) modified with Or it can be indirectly labeled. Fluorescent nanoparticle modification conditions or a substance to which the modified fluorescent nanoparticle binds so that the binding number (average value) of the modified fluorescent nanoparticle as described above to one breast cancer-related protein is as close to 1 as possible. It is preferable to adjust the conditions.

  In the first embodiment of the present invention, two or more kinds of breast cancer-related proteins including at least HER2, for example, HER2 and HER1, or HER2 and HER3 are labeled. In such a case, it is preferable to simultaneously stain each breast cancer-related protein on a single breast cancer tissue section by using two or more kinds of fluorescent nanoparticles having different colors (maximum emission wavelength). is there. The fluorescence image showing the luminescent spots of each breast cancer-related protein irradiates the excitation wavelength corresponding to each fluorescent nanoparticle, and transmits the emission wavelength corresponding to each fluorescent nanoparticle (does not transmit other emission wavelengths) By using a filter, it can be acquired as separate fluorescent images. In the case of not using such an embodiment, for example, in each of two or more adjacent sliced sections prepared from one formalin-fixed paraffin-embedded tissue block, each breast cancer-related protein is stained with fluorescent nanoparticles. Thus, it is also possible to acquire each fluorescence image.

  A basic embodiment of a method for labeling a target protein (a breast cancer-related protein in the present invention) directly or indirectly using fluorescent nanoparticles (in particular, IHC-PID method using PID as a fluorescent label) Known from International Publication No. 2012/029342 (Patent Document 1), International Publication No. 2013/146741 (Patent Document 2), or other patent documents or non-patent documents. It can implement by embodiment according to the case where a pathological diagnosis is performed.

  In the present invention, since fluorescent nanoparticles are used to label a breast cancer-related protein, there is no problem that a dye produced by an enzyme reaction is mixed with a staining agent for morphology observation as in the conventional IHC method. Therefore, on one tissue section, a staining process for breast cancer-related protein using fluorescent nanoparticles can be performed, and a staining process for observing cell morphology can be performed. Such an embodiment is preferable because, for example, in step [2] described below, the expression level for each cell of the breast cancer-related protein can be obtained as the measurement value (i). It is described in the publication 2013/035688 pamphlet.

  Also, instead of using a staining agent for morphological observation, a membrane protein other than a breast cancer-related protein that is constantly expressed in the cell membrane (reference biological substance, for example, ATPase, cadherin, cytokeratin, EpCAM) is fluorescent. By labeling with nanoparticles, a fluorescent image in which the region of the cell membrane is represented by fluorescent bright spots may be acquired. In this case, the breast cancer-related protein and the above-mentioned reference biological substance are stained on one tissue section with two kinds of fluorescent nanoparticles having different excitation maximum wavelengths and emission maximum wavelengths, and each bright spot Can be acquired as another fluorescent image. The basic matters of such an embodiment are described in, for example, the pamphlet of International Publication No. 2015/146896.

(Breast cancer tissue section)
The breast cancer tissue section may be prepared using a specimen collected from a human (breast cancer patient) -derived breast cancer tissue, or a human breast cancer tissue or a breast cancer tissue of an experimental animal transplanted with breast cancer cells. Alternatively, it may be prepared using a specimen collected from a site containing breast cancer cells.

  The above “experimental animals” are generally called tumor-bearing animals and are derived from humans established as tumor (breast cancer) tissues or tumor cells or cultured cell lines collected from humans (breast cancer patients). Of 0th generation experimental animals transplanted with tumor cells, and tumor tissue or tumor cells transplanted into such 0th generation, and grown in the body of n-1 generation experimental animals Or includes an nth generation (n ≧ 1) experimental animal transplanted with expanded tumor cells. Such experimental animals can be prepared using known techniques. For example, in the case of mice, in addition to CDX (Cell-line derived xenograft) model mice and PDX (Patient derived xenograft) model mice, human xenograft model mice, Immuno-avatar model mice, hematopoietic lymphoid humanization Various tumor-bearing model mice such as model mice (Hemato-lymphoid humanized mice) and Immune-PDX model mice can be produced, and an environment in which a prepared tumor-bearing mouse model can be purchased is also prepared. On the other hand, tumor-bearing model mice transplanted with cultured cells derived from tumor cells removed from patients are more classic and easy to produce.

Step [2]: Index acquisition step Step [2] included in the examination support method of the present invention includes each of the two or more types of breast cancer-related proteins based on the bright spot of the fluorescent image acquired in the step [1]. This is a step of acquiring, as the index, a numerical value (the first embodiment) representing the expression level of at least one or at least a histogram (second embodiment) based on the expression level of each cell of the breast cancer-related protein.

(index)
Examples of indexes relating to the expression level of breast cancer-related protein include (I) expression level per cell (average value) of breast cancer-related protein, and (II) expression level per unit area of tissue of breast cancer-related protein (average value). (III) A histogram based on the expression level of each cell of the breast cancer-related protein, (IV) A distribution curve based on the expression level of each cell of the breast cancer-related protein, and the like.

  In order to obtain the above-mentioned index, specifically, based on the bright spot of the fluorescence image, (i) the expression level for each cell of the breast cancer-related protein, (ii) the total number of cells for which the expression level was measured (Iii) The expression level of a breast cancer-related protein in cells contained in a predetermined region of a breast cancer tissue, (iv) the area of the region where the expression level is measured, and the like may be measured. By using the above measured values (i) and (ii), the expression level (average value) per cell of the breast cancer-related protein mentioned as the index (I) can be calculated. By using the above measured values (iii) and (iv), the expression level (average value) per unit area of the breast cancer tissue of the breast cancer-related protein mentioned as the index (II) can be calculated. Further, by using the measured value (i), the histogram cited as the index (III) or the distribution curve cited as the index (IV) can be created.

  The expression level of the breast cancer-related protein (i) for each cell is, for example, in the step [1], the tissue section (specimen slide) is immunostained with fluorescent nanoparticles, and the morphological observation stains (hematoxylin, eosin, etc.) It can measure by dyeing so that the shape of a cell can be specified. In this case, in step [1], first, fluorescent nanoparticles labeled with a breast cancer-related protein are observed as a bright spot by observing and imaging in the dark field while irradiating excitation light having a predetermined wavelength corresponding to the fluorescent nanoparticles. Get the image that appears as. On the other hand, an image that is stained so as to represent the shape of a cell with a staining agent for morphology observation is also acquired by observation and imaging in a bright field. In step [2], when these two images are overlapped by image processing, individual cells contained in the entire image or in a specific region (for example, only tumor tissue) in the image are expressed. The number of bright spots labeled with a breast cancer-related protein can be measured. Cells that do not have a bright spot or cells that have a bright spot outside the cell are not subject to measurement.

  The number of cells or the area of the region to be measured for the number of bright spots is arbitrary, but the index of (i) and (ii) is calculated, or the histogram or distribution curve as the index of (iii) and (iv) It is appropriate to make the number or area sufficiently large in consideration of the fact that they will be valid (especially statistically). On one specimen slide (tissue section), the number of bright spots may be measured for one visual field or a predetermined number of cells contained therein, or two or more visual fields or a predetermined number of each included in each field. You may measure the number of bright spots about a cell.

  The expression level of the breast cancer-related protein may be represented by the number of bright spots measured as described above, or may be represented by the number of particles constituting the bright spots, which can be converted from the number of bright spots. From the viewpoint of improving the accuracy of analysis in [3], the latter is preferable. Since one luminescent spot may be constituted by fluorescence emitted from a plurality of fluorescent nanoparticles, fluorescent nanoparticles 1 in which the brightness (luminance, fluorescence intensity) of one luminescent spot has been separately measured. By dividing by the brightness per unit, the number of fluorescent nanoparticles constituting the bright spot can be calculated.

  Index (I): expression level (average value) of breast cancer-related protein per cell is measured value (i): expression level for each cell of breast cancer-related protein, and measurement value (ii): cell whose expression level is measured Can be calculated by dividing the total sum of the measurement values (i) by the measurement value (ii).

  Index (II): Expression amount (average value) of breast cancer-related protein per unit area of breast cancer tissue is measured value (iii): Predetermined region of breast cancer tissue (whether the whole or part of the visual field) Expression level of the breast cancer-related protein (present in the cell shape represented by the staining agent for morphological observation) and the measured value (iv): the area of the region where the expression level was measured By using it, that is, it can be calculated by dividing the measured value (iii) by the measured value (iv).

  Index (III): A histogram based on the expression level of each cell of breast cancer-related protein is calculated from a plurality of measured values (i): expression level of each cell of breast cancer-related protein. It can be created by setting a class, then calculating the number of cells (frequency) belonging to each class, expressing the former on the horizontal axis and the latter on the vertical axis. As for the class of the horizontal axis, for example, as in the embodiment described in the present specification, the number of bright spots from 0 to 400 can be divided into 10 widths for a total of 41 classes. .

  Index (IV): The distribution curve based on the expression level of each breast cancer-related protein cell is also represented by the measured value (i): the expression level of each breast cancer-related protein expression level on the horizontal axis (like a histogram). The number of cells (frequency) corresponding to each expression level on the vertical axis.

Step [3]: pCR prediction information acquisition step Step [3] included in the inspection support method of the present invention is an analysis using the one or more types of indicators, for example, the numerical value acquired in the step [2] is predetermined. Obtaining information for predicting pCR by an analysis including comparison with a threshold value (first embodiment) or an analysis including at least categorizing the distribution pattern of the histogram (second embodiment) It is.

  “Analysis using one or more indicators” is not particularly limited as long as it can obtain information with a certain level of reliability and can predict whether or not it will be a pCR. Absent.

  In an example of a preferred embodiment of the present invention, in the step [3], an analysis that classifies the distribution pattern of a histogram created based on at least the expression level of each HER2 cell is performed, and other analysis is performed as necessary. Also do. For this purpose, in step [1], one or more breast cancer-related proteins including at least HER2 may be labeled with fluorescent nanoparticles, and in step [2], a histogram based on the expression level of at least HER2 for each cell. May be acquired as an index, and other numerical values or histograms may be acquired as an index as necessary.

  In one example of a preferred embodiment of the present invention, in step [3], (a) a value of a ratio of a numerical value representing the expression level of HER2 to a numerical value representing the expression level of HER1 (HER2 / HER1), or (b) of HER3 An analysis including comparing the value of any ratio of the numerical value representing the expression level of HER2 to the numerical value representing the expression level (HER2 / HER3) with a predetermined threshold value is performed. To that end, in step [1], HER2 and HER1 or HER3 may be labeled with fluorescent nanoparticles (if necessary, other breast cancer-related proteins may be labeled with fluorescent nanoparticles). In [2], a numerical value representing the expression level of HER2 and HER1 or HER3 may be obtained, and the value of the above ratio may be calculated (even if other indicators related to breast cancer-related proteins are obtained as necessary) Good).

  In an example of a preferred embodiment of the present invention, in the step [3], (a) an analysis for comparing a numerical value representing the expression level of HER2 with a predetermined threshold, and (b) an expression level for each cell of HER2 is prepared. The resulting histogram is analyzed to classify the distribution pattern and combine them. For that purpose, in step [1], HER2 may be labeled with fluorescent nanoparticles (if necessary, other breast cancer-related proteins may be labeled with fluorescent nanoparticles), and in step [2] ( It is only necessary to create a histogram based on a) a numerical value representing the expression level of HER2 and (b) an expression level of HER2 for each cell (an index related to another breast cancer-related protein may be obtained as necessary).

  In the step [3], when an analysis is performed using a numerical value representing the expression level of a breast cancer-related protein as an index, the analysis method is not particularly limited, but typically, as described above, those numerical values are used. Is compared with a predetermined threshold value (cut-off value) set in advance. In this case, the human or experimental animal from which the specimen is collected becomes pCR by performing preoperative chemotherapy when the index value or the like is larger (or higher) than the threshold value or smaller (or lower). Diagnostic information useful for predicting or not to be obtained can be obtained.

  Whether the index value is predicted to be pCR when it is larger than the threshold value, or is predicted to be pCR when it is smaller (in other words, is it predicted not to be pCR when it is smaller than the threshold value)? If it is large, it is predicted that it is not pCR) may change. For example, when the expression level per unit area of breast cancer tissue of HER2 protein is used as a numerical value representing the expression level of HER2, it is predicted that the expression level is pCR if the expression level is larger than a threshold value. In addition, in the case where any one of a numerical value representing the expression level of HER2 / a numerical value representing the expression level of HER1 and a numerical value representing the expression level of HER2 / a numerical value representing the expression level of HER3 is used, the ratio value should be larger than the threshold value. PCR is predicted. This seems to reflect that when an anticancer drug targeting HER2 is used as preoperative chemotherapy, the higher the expression level of HER2, the better the efficacy and the higher the probability of pCR. . In general, when comparing the results of the pCR group and the non-pCR group as described below, if the pCR group is statistically significantly higher (the non-pCR group is statistically significant) PCR is predicted to be greater than the threshold, and conversely if the pCR group is statistically significantly lower (the non-pCR group is statistically significantly higher) Is expected to be pCR.

  The threshold (cut-off value) in such an analysis was finally pCR among the samples collected before or during preoperative chemotherapy. Expression of specific breast cancer-related protein contained in each specimen in specimens collected from multiple breast cancer patients (pCR group) and specimens collected from multiple breast cancer patients that ultimately did not become pCR (non-pCR group) A numerical value representing the quantity can be obtained by the IHC-PID method, and further derived by comparing the results of the pCR group and the non-pCR group. For example, when the expression level per unit area of the HER2 protein tissue is used as an index value, the index value in as many specimens as possible contained in the pCR group is larger than the threshold (that is, the sensitivity is increased) and is included in the non-pCR group Ideally, the threshold value is set so that the index value in as few samples as possible is below the threshold value (that is, the specificity is increased). Since the sensitivity and specificity also change by changing the threshold value, it is desirable to use what is adjusted (optimized) so as to balance both of them as the threshold value of the step [3].

  On the other hand, in the step [3], when an analysis is performed using a histogram created based on the expression level of each breast cancer-related protein as an index, the analysis method is not particularly limited, but typically As described above, the distribution pattern of the histogram is categorized, that is, it is compared with several distribution patterns provided in advance to determine which one corresponds. For example, regarding a histogram created based on the expression level of each HER2 cell, (A) a distribution pattern having a peak (peak) at 0 bright spots and (B) a single peak and the peak is shifted to the right. The pattern can be classified into any one of four types: a distribution pattern, (C) a bimodal or multimodal distribution pattern, and (D) a distribution pattern distributed in a wide class. When the distribution pattern (B), (C), or (D) (that is, a pattern with few cells having 0 bright spots) is satisfied, it is predicted to be pCR, and conversely, it corresponds to the distribution pattern (A). It is predicted that it will not be pCR.

  The distribution pattern in such an analysis is, for example, comparing the histogram of the pCR group with the histogram of the non-pCR group, paying attention to what the distribution peak is, and the average value if necessary Alternatively, referring to numerical values such as median and variance (CV), as many samples as possible are included in the pCR group (that is, high sensitivity) and as few samples as possible are included in the non-pCR group (that is, as high as possible). By finding the distribution pattern (low specificity), it can be typified as described above.

  In addition, instead of the histogram as described above, the expression level of each breast cancer-related protein for each cell is continuously plotted on the horizontal axis (not divided as in the histogram), and the number of cells (frequency) corresponding to each expression level is calculated. A similar analysis may be possible even when a distribution curve taken along the vertical axis is created.

[Preparation Example 1] Preparation of biotin-modified anti-rabbit IgG antibody 50 μg of anti-rabbit IgG antibody (clone: LO-RG-1) used as a secondary antibody was dissolved in a 50 mM Tris solution. To this solution, a DTT (dithiothreitol) solution was added to a final concentration of 3 mM, mixed, and reacted at 37 ° C. for 30 minutes. Thereafter, the reaction solution was passed through a desalting column “Zeba ™ Desalt Spin Columns” (Thermo Scientific, Cat. # 89882) to purify the secondary antibody reduced with DTT. Of the total amount of the purified antibody, 200 μL was dissolved in a 50 mM Tris solution to prepare an antibody solution. On the other hand, the linker reagent “Maleimide-PEG2-Biotin” (Thermo Scientific, 21901BID) was adjusted to 0.4 mM using DMSO. 8.5 μL of this linker reagent solution was added to the antibody solution, mixed, and reacted at 37 ° C. for 30 minutes to bind biotin to the anti-rabbit IgG antibody via the PEG chain. The reaction solution was purified through a desalting column. About the desalted reaction solution, the density | concentration of the protein (biotin modification secondary antibody) in a reaction solution was computed by measuring the light absorbency in wavelength 300nm using a spectrophotometer (Hitachi High-Technologies "F-7000"). . A solution in which the concentration of the biotin-modified secondary antibody was adjusted to 250 μg / mL using a 50 mM Tris solution was used as a biotin-modified secondary antibody solution.

[Preparation Example 2] Preparation of streptavidin-modified Texas Red-integrated melamine resin particles 20.3 mg of Texas Red, which is a red fluorescent dye, was added as a fluorescent dye to 22 mL of water and dissolved. Thereafter, 2 mL of a 5% aqueous solution of an emulsifier for emulsion polymerization “Emulgen” (registered trademark) 430 (polyoxyethylene oleyl ether, manufactured by Kao Corporation) was added thereto. The solution was heated to 70 ° C. while stirring on a hot stirrer, and then 0.81 g of a melamine resin raw material “Nicalak MX-035” (manufactured by Nippon Carbide Industries Co., Ltd.) was added to the solution. Furthermore, 1000 μL of a 10% aqueous solution of dodecylbenzenesulfonic acid (manufactured by Kanto Chemical Co., Inc.) was added to this solution as a reaction initiator, and the mixture was heated and stirred at 70 ° C. for 50 minutes. Then, it heated up at 90 degreeC and heat-stirred for 20 minutes.

  In order to remove impurities such as excess resin raw materials and fluorescent dyes from the resulting dispersion of Texas Red-integrated melamine resin particles, washing was performed with pure water. Specifically, centrifuge “Micro Cooling Centrifuge 3740” (manufactured by Kubota Shoji Co., Ltd.) is centrifuged at 20000 G for 15 minutes, the supernatant is removed, ultrapure water is added, and ultrasonic dispersion is applied for redispersion. did. Centrifugation, supernatant removal, and washing by redispersion in ultrapure water were repeated 5 times. Through the above steps, Texas Red integrated melamine resin particles (excitation wavelength 590 nm, emission wavelength 620 nm) were produced.

  By dispersing 0.1 mg of the above Texas Red-integrated melamine resin particles in 1.5 mL of ethanol, adding 2 μL of aminopropyltrimethoxysilane (“LS-3150”, manufactured by Shin-Etsu Chemical Co., Ltd.), and reacting for 8 hours, A surface amination treatment was performed to convert hydroxyl groups present on the surface of the resin particles into amino groups.

The concentration of the Texas Red integrated melamine resin particles was adjusted to 3 nM using phosphate buffered saline (PBS) containing 2 mM ethylenediaminetetraacetic acid (EDTA). SM (PEG) ₁₂ (succinimidyl-[(N-maleimidopropionamide) -dodecaethylene glycol] ester, Thermo Fisher Sien, so as to have a final concentration of 10 mM with respect to the dispersion of the concentration-adjusted Texas Red-integrated melamine resin particles. Manufactured by Tefic Co., Ltd.) and reacted at 20 ° C. for 1 hour to obtain a mixed solution containing Texas Red integrated melamine resin particles whose particle surfaces were modified with maleimide groups.

  The mixture was centrifuged at 10,000 G for 20 minutes, the supernatant was removed, PBS containing 2 mM EDTA was added to disperse the precipitate, and the mixture was centrifuged again. After the above washing by the same procedure three times, Texas red-integrated melamine resin particles modified with maleimide groups were collected.

  On the other hand, by reacting streptavidin (manufactured by Wako Pure Chemical Industries, Ltd.) with N-succinimidyl-S-acetylthioacetic acid (SATA), deprotecting the S-acetyl group by performing known hydroxylamine treatment A thiol group was introduced into streptavidin. Thereafter, gel filtration was performed to separately prepare streptavidin capable of binding to the fluorescent dye-aggregated particles.

  The maleimide-modified Texas Red-integrated melamine resin particles and streptavidin into which thiol groups have been introduced are mixed in PBS containing 2 mM EDTA and reacted at room temperature for 1 hour, and both (maleimide group and thiol group) are mixed. Combined. Thereafter, 10 mM mercaptoethanol was added to stop the reaction. After concentrating the obtained solution with a centrifugal filter of φ = 0.65 μm, unreacted streptavidin and the like were removed using a gel filtration column for purification to obtain streptavidin-modified Texas red integrated melamine resin particles.

[Production Example 3] Preparation of streptavidin-modified perylenediimide-integrated melamine resin particles Streptavidin-modified perylenediimide-integrated melamine resin particles (excitation wavelength: 590 nm, light emission) in the same manner as in Production Example 2 except that perylenediimide is used instead of Texas Red. Wavelength 620 nm).

[Production Example 4] Production of anti-HER1 antibody-modified pyromethene-integrated melamine resin particles (green fluorescent nanoparticles) Pyrromethene 556 and 14.4 mg, which is a green fluorescent dye, were added to 22 mL of water and dissolved. Thereafter, 2 mL of a 5% aqueous solution of an emulsifier for emulsion polymerization “Emulgen” (registered trademark) 430 (polyoxyethylene oleyl ether, manufactured by Kao Corporation) was added thereto. The solution was heated to 70 ° C. while stirring on a hot stirrer, and then 0.65 g of a melamine resin raw material “Nicalak MX-035” (manufactured by Nippon Carbide Industries, Ltd.) was added to the solution. Furthermore, 1000 μL of a 10% aqueous solution of dodecylbenzenesulfonic acid (manufactured by Kanto Chemical Co., Inc.) was added to this solution as a reaction initiator, and the mixture was heated and stirred at 70 ° C. for 50 minutes. Then, it heated up at 90 degreeC and heat-stirred for 20 minutes.

  In order to remove impurities such as excess resin raw materials and fluorescent dyes from the obtained dispersion of pyromethene-integrated melamine resin particles, washing with pure water was performed. Specifically, centrifuge “Micro Cooling Centrifuge 3740” (manufactured by Kubota Shoji Co., Ltd.) is centrifuged at 20000 G for 15 minutes, the supernatant is removed, ultrapure water is added, and ultrasonic dispersion is applied for redispersion. did. Centrifugation, supernatant removal, and washing by redispersion in ultrapure water were repeated 5 times. Through the above process, pyromethene-integrated melamine resin particles (excitation wavelength: 490 nm, emission wavelength: 520 nm) were produced.

  Maleimide was introduced into the above-mentioned pyromethene-integrated melamine resin particles using NHS-PEG-maleimide reagent, and thiolated anti-HER1 antibody was bound thereto to obtain anti-HER1 antibody-modified pyromethene-integrated melamine resin particles.

[Example 1] Analysis using numerical values representing the expression levels of HER1, HER2 and HER3 (corresponding to the first embodiment of the present invention)
A formalin-fixed paraffin-embedded tissue block (specimen) was prepared from a breast cancer tissue collected by a needle biopsy from a breast cancer patient at Tohoku University Hospital in 2011-2014, and sliced by a microtome to prepare a specimen slide. . Using this specimen slide, DAB staining for HER2 protein was performed using “HercepTest kit” (Dako).

  As a result of IHC-DAB score determination, patients diagnosed as HER2-positive are administered anthracycline drugs (topoisomerase inhibitors) daunorubicin or doxorubicin for 3 months, followed by trastuzumab (trade name: Herceptin) In addition, preoperative chemotherapy was performed in which paclitaxel or docetaxel, which is a taxane drug (microtubule inhibitor), was administered for 3 months. Thereafter, the breast cancer tissue was removed by surgery, and whether or not it was pCR was determined based on whether or not invasion in the primary lesion of cancer cells and metastasis to lymph nodes were observed using a microscope.

  Among the 8 breast cancer patients who received preoperative chemotherapy as described above, there were 6 patients who were pCR (pCR group) and 2 patients who were not pCR (non-pCR group). Using the specimen (formalin-fixed paraffin-embedded tissue block) collected and stored before preoperative chemotherapy of these breast cancer patients, PID staining for each of HER2, HER1, and HER3 by the following procedure To obtain a PID score.

In parallel with the acquisition of the PID score, DAB staining of the HER2 protein and FISH of the HER2 gene were also performed using the above samples. For DAB staining, “HercepTest kit” (Dako) was used as described above, and the DAB score (0 to 3+) in four stages according to the conventional HER2 inspection guide was determined, and per unit area (0.1 mm ² ) of the tissue. The DAB color intensity (IHC-DAB color intensity) was measured with Aperio (Leica Biosystems). FISH used “PathVysion HWE2 DNA probe kit” (Abbott), and the observed number of bright spots was obtained as the FISH score (HER2 gene average copy number).

(1-1) PID staining for HER2 and acquisition of PID score (1-1-1) Sample pretreatment step The above-described formalin-fixed paraffin-embedded tissue block derived from a breast cancer patient's tissue is sliced with a microtome and a sample slide is obtained. Produced. The specimen slide was deparaffinized and then washed with water. The washed specimen slide was autoclaved at 121 ° C. for 15 minutes in 10 mM citrate buffer (pH 6.0) to carry out antigen activation treatment. The specimen slide after the activation treatment was washed with PBS, and the washed specimen slide was subjected to blocking treatment with PBS containing 1% BSA for 1 hour.

(1-1-2) Immunostaining step (1-1-2-1) Primary reaction treatment of immunostaining Anti-HER2 rabbit monoclonal antibody “4B5” using PBS containing 1% (w / w) of BSA A primary reaction treatment solution containing Ventana at a concentration of 0.05 nM was prepared. The specimen slide which passed through the process (1-1-1) was immersed in this primary reaction processing liquid, and it was made to react at 4 degreeC overnight.

(1-1-2-2) Secondary reaction treatment of immunostaining The biotin-modified anti-rabbit IgG antibody solution prepared in Preparation Example 1 was further treated with 6 μg / kg of PBS containing 1% (w / w) of BSA. A secondary reaction treatment solution diluted to mL was prepared. The specimen slide after the primary reaction treatment was washed with PBS, then immersed in this secondary reaction treatment solution, and reacted at room temperature for 30 minutes.

(1-1-2-3) Fluorescent labeling treatment for immunostaining The streptavidin-modified Texas Red-integrated melamine resin particles prepared in Preparation Example 2 were prepared using a dilution solution for fluorescent nanoparticles containing casein and BSA. A fluorescent labeling reaction solution diluted to 02 nM was prepared. The specimen slide after the secondary reaction treatment was immersed in this fluorescent labeling treatment solution and reacted at room temperature for 3 hours in a neutral pH environment (pH 6.9 to 7.4).

(1-1-2-4) Morphological Observation Staining Treatment The specimen slide subjected to the fluorescence labeling treatment was stained with Mayer's hematoxylin solution for 5 minutes and stained with hematoxylin, and then washed with running water at 45 ° C. for 3 minutes.

(1-1-3) Specimen post-treatment step The specimen slide (stained slide) after immunostaining was subjected to immobilization / dehydration treatment in which the operation of immersing in pure ethanol for 5 minutes was performed four times. Subsequently, a penetration treatment was performed in which the operation of immersing in xylene for 5 minutes was performed four times. Finally, an encapsulating agent “Enteran New” (Merck) was placed on the staining slide, and the encapsulating process of covering with a cover glass was performed to obtain a staining slide used for observation.

(1-1-4) Evaluation Step (1-1-4-1) Observation / Photographing Step For the irradiation of excitation light and the observation of fluorescence emission in this step, a fluorescence microscope “BX-53” (Olympus Corporation) is used. A digital camera “DP73” (Olympus Corporation) attached to the fluorescence microscope was used for taking an immunostained image (400 times).

First, the staining slide was irradiated with excitation light corresponding to Texas Red used for fluorescent labeling of the target protein HER2 to emit fluorescence, and an immunostained image of the state was taken (“fluorescence image in the examination support method of the present invention”). Corresponding to “acquisition process”). At this time, the wavelength of excitation light was set to 575 to 600 nm using an optical filter for excitation light provided in the fluorescence microscope, and the wavelength of fluorescence to be observed was set to 612 to 692 nm using an optical filter for fluorescence. The intensity of the excitation light at the time of observation and image photographing with a fluorescence microscope was such that the irradiation energy near the center of the visual field was 900 W / cm ² . The exposure time at the time of image shooting was adjusted within a range in which the luminance of the image was not saturated, and was set to, for example, 4000 μsec.

Next, a stained image by hematoxylin staining for cell morphology observation was photographed by observation and image photographing in a bright field of a fluorescence microscope.
Such immunostained images and morphological observation stained images were taken in the same visual field, and then the same operation was repeated while changing the visual field, and 5 visual fields were performed for each stained slide.

(1-1-4-2) Image Processing / Measurement Step Image processing software “ImageJ” (open source) was used for the image processing in this step.
Streptavidin-modified Texas Red accumulation labeled with the HER2 protein expressed on the cell membrane by specifying the shape of the cell (position of the cell membrane) by image processing using the stained image for morphology observation and overlaying it with the immunostained image The bright spots representing melamine resin particles were extracted and measured as the number of PID particles. Among the bright spots on the cell membrane, those having a luminance of a predetermined value or more were converted into the number of particles by dividing the luminance by the luminance per Texas Red integrated particle (PID). Since HER2 is not expressed in the stromal cell region, the bright spot located in the stromal cell was treated as a nonspecific signal, that is, noise. Then, the number of bright spots derived from HER2 in 5 visual fields per stained slide was measured, converted to the number of fluorescent nanoparticles per unit area (100 μm ² ) as described above, and the average value was calculated. Then, the “PID score” of the specimen slide was used (corresponding to the “index acquisition step” in the examination support method of the present invention).

(1-2) Acquisition of PID staining and PID score for HER1 In the step (1-1-2-1), the primary containing anti-HER2 rabbit monoclonal antibody “4B5” (Ventana) at a concentration of 0.05 nM PID staining for HER2 except that a primary reaction treatment solution containing anti-HER1 rabbit monoclonal antibody “5B7” (Roche, production number 790-4347) at a concentration of 0.05 nM was used instead of the reaction treatment solution. In the same manner as the acquisition of the PID score, PID staining for HER1 and acquisition of the PID score were performed.

(1-3) Acquisition of PID staining and PID score for HER3 In the step (1-1-2-1), the primary containing anti-HER2 rabbit monoclonal antibody “4B5” (Ventana) at a concentration of 0.05 nM Instead of the reaction treatment solution, the HER2 was used except that a primary reaction treatment solution containing an anti-HER3 rabbit monoclonal antibody “clone: RTJ2” (ABR, product number MA1-860) at a concentration of 0.05 nM was used. The PID staining and PID score for HER3 were obtained in the same manner as the PID staining and PID score for.

(1-4) Analysis Results FIG. 1 shows a DAB-stained image (A), a PID-stained image (B), a hematoxylin-stained image (C), and a PID-stained image and a hematoxylin-stained image of an example of a breast cancer patient in the pCR group ( D), and a DAB-stained image (E), a PID-stained image (F), a hematoxylin-stained image (G), and a PID-stained image and a hematoxylin-stained image (H) of an example of a breast cancer patient in the non-pCR group. Both have an IHC-DAB score of 3+ and a FISH score of about 6, but preoperative chemotherapy has resulted in different results, the former being pCR and the latter being non-pCR. Both PID scores were 61.5 and 24.3, respectively.

(1-4-1) Relationship between IHC-DAB color intensity and FISH score and pCR Color intensity per unit area (100 μm ² ) of tissue by IHC-DAB staining in each of pCR group and non-pCR group (measured by AQUA) ) (FIG. 2) and FISH score (FIG. 3). These are all for HER2. There was no difference in tendency between the pCR group and the non-pCR group in both the IHC-DAB color intensity and the FISH score.

(1-4-2) Relationship between PID score of HER2 and pCR FIG. 4 shows the PID score of HER2 protein in each of the pCR group and the non-pCR group (average number of PID particles per unit area (100 μm ² ) calculated). Value). In the PID score, a difference in tendency was observed between the pCR group and the non-pCR group.
Based on the above results, it is easy to create an ROC curve (receiver operating characteristic curve) for the PID score and set an optimal cutoff value.

  From these results, it is not possible to predict whether or not pCR will occur before preoperative chemotherapy using the IHC-DAB color intensity and the FISH score, but using the PID score for the HER2 protein, HER2 It can be seen that even a single result can be predicted with a certain degree of accuracy.

[Example 2] Embodiment in which numerical values representing the expression levels of HER1 and HER2 are obtained from one specimen slide (first embodiment by double staining)
PID staining of HER2 protein with a fluorescent labeling reaction solution prepared using the streptavidin-modified Texas Red integrated melamine resin particles (excitation wavelength 590 nm, emission wavelength 620 nm) prepared in Preparation Example 2, and anti-HER1 prepared in Preparation Example 3 PID staining of HER1 protein was performed on the same slide with a fluorescent labeling reaction solution prepared using antibody-modified pyromethene-integrated melamine resin particles (excitation wavelength: 490 nm, emission wavelength: 520 nm).

  The tissue slide is the same as that of Example 1 except that the specimen (pCR group) collected before performing preoperative chemotherapy from a plurality of breast cancer patients who finally became pCR, and finally the pCR. Instead of using specimens (non-pCR group) collected prior to preoperative chemotherapy from multiple breast cancer patients who were not present, commercially available slides with clinical information (BioMax code. HBre-Duc150Sur-01, 150 tissue specimens) Array and Asterand Breast Cancer Tissue Specimen Slide) were purchased, and specimens from the surviving group (corresponding to pCR group) for 100 months or more after surgery and specimens surviving for less than 100 months (corresponding to non-pCR group) after surgery were purchased. Using.

  IHC-DAB color intensity of HER2 protein and FISH score of HER2 gene of 49 commercial slides described above (25 specimen spots of patients surviving 100 months or more after surgery and 24 specimen spots of patients surviving less than 100 months after surgery) The PID score of HER2 protein was measured in the same manner as in Example 1. Box plots for these results are shown in FIGS. 5, 6 and 7, respectively. In the Mann-Whitney U test, a significant difference was observed between the pCR group and the non-pCR group in the PID score of the HER2 protein (p <0.05). FIG. 8 shows an ROC curve (receiver operating characteristic curve) for the PID score created based on the above result. The optimum cutoff value is 51.3, the sensitivity (sensitivity: vertical axis) at this time is 68%, the specificity is 60% (specificity: horizontal axis), that is, the false positive rate (1-specificity). Is 40%.

  Next, double staining with streptavidin-modified Texas Red-integrated melamine resin particles and anti-HER1 antibody-modified pyromethene-integrated melamine resin particles was performed as follows. First, in accordance with the procedure up to (1-1-2-3) in Example 1, the HER2 protein was fluorescently labeled with streptavidin-modified Texas Red-integrated melamine resin particles. After fluorescent labeling treatment for HER2 protein, fluorescent labeling of anti-HER1 antibody-modified pyromethene-integrated melamine resin particles diluted to 0.02 nM using a fluorescent nanoparticle diluent as in (1-1-2-3) Used as a reaction treatment solution, HER1 protein was fluorescently labeled. Thereafter, the staining process for morphological observation similar to (1-1-2-4) was performed, and the specimen post-treatment process similar to (1-1-3) was further performed to prepare a staining slide.

  The number of bright spots on the stained slide double-stained as described above was measured as follows. First, according to the procedure of the observation / photographing process of (1-1-4-1) of Example 1, a fluorescence image was photographed using excitation light of streptavidin-modified Texas red integrated melamine resin particles labeled with HER2. Next, anti-HER1 antibody-modified pyromethene labeled with HER1 using a filter set made by Semrock (optical filter for excitation light: 470 nm (30 nm width), beam splitter: 495 nm, optical filter for fluorescence: 525 nm (50 nm width)). A fluorescence image of the accumulated melamine resin particles was taken. After that, in the same manner as in (1-1-4-2), the number of bright spots of HER2 and the number of bright spots of HER1 are measured, and the PID score ratio of HER2 / HER1 is calculated. The results were compared between.

  FIG. 9 shows a box plot for the PID score of the HER1 protein. FIG. 10 shows a box plot of the HER2 / HER1 PID score ratio created based on the above result. In the Mann-Whitney U test, a significant difference at a high significance level was observed between the pCR group and the non-pCR group (p <0.001).

  From these results, it is more accurate to use the HER2 / HER1 PID score ratio (p <0.001) as an index than to use the HER2 PID score alone (p <0.05) as an index. It is considered that it can be predicted whether or not it will be pCR.

[Example 3] Analysis using a distribution pattern of a histogram created based on the expression level of each HER2 cell (corresponding to the second embodiment of the present invention)
In Tohoku University Hospital in 2011-2014, HER2 protein PID score (per unit area) was obtained in the same manner as in Example 1-1 (1-1) for 8 specimens derived from breast cancer tissue collected from breast cancer patients by needle biopsy. PID bright spot number) was obtained. Based on the results, a histogram was created in which the horizontal axis represents the PID score (10 widths, a total of 41 classes) and the vertical axis represents the number of cells (total number of 5 fields in one stained slide). FIG. 11 is an explanatory diagram of the histogram creation process, and FIG. 12 (FIGS. 12-1 and 12-2) shows the actually created histogram.

  The created histogram consists of (A) a pattern with a peak at 0 bright spots, (B) a pattern that is unimodal and the peak is shifted to the right, (C) a bimodal or multimodal pattern, and ( D) It was found that the pattern can be classified into any one of four patterns, which are distributed in a wide class. The number of samples of the pCR group and the non-pCR group included in each pattern of (A) to (D) is as follows. Pattern (A): pCR group = 1, non-pCR group = 2. Pattern (B): pCR group = 3, non-pCR group = 0. Pattern (C): pCR group = 1, non-pCR group 0. Pattern (D): pCR group = 1, non-pCR group = 0.

  From such a result, when a histogram created based on the PID score of HER2 for a certain breast cancer patient has a high ratio of cells having a pattern as in (B) above, particularly a PID score of about 10 to 100, Breast cancer patients become pCR by preoperative chemotherapy, and conversely, in the case of the pattern (A) above, the breast cancer patient can be predicted with a certain degree of accuracy if it does not become pCR by preoperative chemotherapy. I understand.

[Example 4] Analysis using numerical values representing the expression levels of HER1, HER2 and HER3 (corresponding to the first embodiment of the present invention)
A formalin-fixed paraffin-embedded tissue block (specimen) was prepared from a breast cancer tissue collected by a needle biopsy from a breast cancer patient, which was collected for the purpose of a prospective study at JBCRG (Japan Breast Cancer Research Group) in 2016. A specimen slide was prepared by slicing. Using this specimen slide, DAB staining for HER2 protein was performed using “HercepTest kit” (Dako).

  As a result of DAB score determination, an anthracycline drug (topoisomerase inhibitor) daunorubicin or doxorubicin is administered to patients diagnosed as HER2 positive for 3 months, followed by trastuzumab (trade name: Herceptin) and taxane Preoperative chemotherapy was administered for 3 months with paclitaxel or docetaxel, a systemic drug (microtubule inhibitor). Thereafter, the breast cancer tissue was removed by surgery, and whether or not it was pCR was determined based on whether or not invasion in the primary lesion of cancer cells and metastasis to lymph nodes were observed using a microscope.

  Of the 81 breast cancer patients who received preoperative chemotherapy as described above, 48 patients became pCR (pCR group), and 33 patients did not become pCR (non-pCR group). Using specimen slides prepared from specimens (formalin-fixed paraffin-embedded tissue blocks) collected and stored prior to preoperative chemotherapy for these breast cancer patients, HER2, HER1, HER3 PID staining was performed on each of the samples, and PID scores were obtained (see Tables 1-1 and 1-2).

  In parallel with the acquisition of the PID score, DAB staining of the HER2 protein and FISH of the HER2 gene were also carried out in the same manner as in Example 1 using the specimen slide prepared from the above specimen.

(4-1) Acquisition of PID staining and PID score for HER2 The streptavidin-modified perylenediimide-integrated melamine resin particles prepared in Preparation Example 3 are used in place of the streptavidin-modified Texas red-integrated melamine resin particles in the fluorescence labeling treatment of immunostaining. Except for the above, PID staining for HER2 was performed in the same manner as in Example 1, and further, morphological observation staining processing and specimen post-processing steps were performed.

(4-2) Evaluation process The observation / photographing process and image processing were performed in the same manner as in Example 1, and the bright spot representing the perylene diimide dye-integrated melamine resin particles labeled with the HER2 protein expressed on the cell membrane was PID. The number of particles was extracted and measured. Of the luminescent spots on the cell membrane, those having a luminance of a predetermined value or more were converted to the number of PID particles by dividing the luminance of the luminescent spot by the luminance per one perylene diimide dye-integrated melamine resin particle. The number of HER2 bright spots was measured in 5 fields per stained slide.

The average value of the number of PID particles per unit area (100 μm ² ), or the average value of the number of PID particles per cell in each of 100 selected cells in 5 fields per staining slide was measured (each Corresponding to the “index acquisition step” in the inspection support method of the invention).

(4-3) Acquisition of PID staining and PID score for HER1 In the same manner as the acquisition of PID staining and PID score for HER1 in the step (1-2), acquisition of PID staining and PID score for HER1 was performed.

(4-4) Acquisition of PID staining and PID score for HER3 In the same manner as the acquisition of PID staining and PID score for HER3 in the step (1-3), acquisition of PID staining and PID score for HER3 was performed.

(4-5) Analysis Results (4-5-1) Relationship between IHC-DAB Coloring Intensity and FISH Score and pCR FIG. 13 shows the unit area of tissues by IHC-DAB staining of pCR group and non-pCR group ( The color intensity per 100 μm ² ) is shown. FIG. 14 shows the FISH scores of the pCR group and the non-pCR group. These are all for HER2. In the Mann-Whitney U test, neither DAB color intensity nor FISH score was significantly different between the pCR group and the non-pCR group (both p> 0.05).

(4-5-2) Relationship between PID score of HER2 and pCR FIG. 15 and FIG. 16 show PID scores of HER2 protein in pCR group and non-pCR group (FIG. 15 shows PID per unit area of tissue (100 μm ² )). The average value of the number of particles, FIG. 16 shows the average value of the number of PID particles per cell as the PID score). In the Mann-Whitney U test, a significant difference was observed in the PID score between the pCR group and the non-pCR group (both p <0.05). Here, it was confirmed that an equivalent p value can be obtained for any PID value. The PID score calculated below is an average value of the number of PID particles per cell.

  FIG. 17 shows an ROC curve (receiver operating characteristic curve) for the PID score created based on the above result. The optimum cutoff value set is 54.1, the sensitivity (sensitivity: vertical axis) at this time is 71%, the specificity (specificity: horizontal axis) is 60%, that is, the false positive rate (1-specific) Degree) is 40%.

  From these results, it is not possible to predict whether or not pCR will occur before preoperative chemotherapy using the IHC-DAB color intensity and the FISH score, but using the PID score for the HER2 protein, HER2 It can be seen that a single result can be predicted with a certain degree of accuracy.

(4-4-3) Relationship between PID score of HER1 and PID score ratio of HER2 / HER1 and pCR FIG. 18 shows HER1 proteins of pCR group and non-pCR group obtained in (4-2) above. Box plots for the PID scores of are shown.

  Next, from the PID score of the HER2 protein acquired in the above (4-1) and the PID score of the HER1 protein acquired in the above (4-2), the ratio value (HER2 PID score / HER1 PID score) ) Was calculated and compared between the pCR group and the non-pCR group.

  FIG. 19 shows a box plot of the HER2 / HER1 PID score ratio created based on the above results. In the Mann-Whitney U test, a significant difference was observed between the pCR group and the non-pCR group (p <0.001, Mann-Whitney U test).

  From these results, does the HER2 / HER1 PID score ratio (p <0.001) index, rather than the HER2 PID score alone (p <0.05), pCR? It is considered that it can be predicted with higher accuracy.

(4-4-4) Relationship between PID score of HER3, PID score ratio of HER2 / HER3, and pCR FIG. 20 shows HER3 protein of each of pCR group and non-pCR group obtained in (4-3) above. Box plots for the PID scores of are shown.

  Next, from the PID score of the HER2 protein obtained in the above (4-1) and the PID score of the HER3 protein obtained in the above (1-3), the ratio value (HER2 PID score / HER3 PID score) And PID score of HER3 / PID score of HER2) were calculated and compared between the pCR group and the non-pCR group.

  FIG. 21 shows a box plot of the HER2 / HER3 PID score ratio created based on the above result. In the Mann-Whitney U test, a significant difference was observed between the pCR group and the non-pCR group (p <0.001).

  Based on these results, is the HER2 / HER3 PID score ratio (p <0.001) an index rather than the HER2 PID score alone (p <0.05)? It is considered that it can be predicted with higher accuracy.

  In FIG. 22, the box plot about the PID score ratio of HER3 / HER2 created based on said result is shown. In the Mann-Whitney U test, a significant difference was observed between the pCR group and the non-pCR group (p <0.001).

  From these results, it is more accurate to use the HER3 / HER2 PID score ratio (p <0.001) as an index than to use the HER2 PID score alone (p <0.05) as an index. It is thought that it will be able to predict whether it will become pCR.

[Example 5] Analysis using a distribution pattern of a histogram created based on the expression level of each HER2 cell (corresponding to the second embodiment of the present invention)
Among the samples collected by needle biopsy from breast cancer tissue of breast cancer patients in JBCRG in 2011-2014, 81 samples with sufficient amount were analyzed for HER2 protein in the same manner as in (4-1) of Example 1 above. A PID score (number of PID bright spots per unit area) was obtained. Based on the results, a histogram was created in which the horizontal axis represents the PID score (10 widths, a total of 41 classes) and the vertical axis represents the number of cells (total number of 5 fields in one stained slide). All the histograms are not shown, and only the results obtained by patterning the histograms are shown (see Table 2).

  From such a result, when a histogram created based on the PID score of HER2 for a certain breast cancer patient has a high ratio of cells having a pattern as in (B) above, particularly a PID score of about 10 to 100, Breast cancer patients become pCR by preoperative chemotherapy, and conversely, in the case of the pattern (A) above, the breast cancer patient can be predicted with a certain degree of accuracy if it does not become pCR by preoperative chemotherapy. I understand.

[Example 6] Analysis using specimen slide prepared from tissue collected from model animal Using specimen slide prepared using tissue collected from PDX mice (Patient-derived xenograft mice) as a tissue specimen to be examined Except for the above, PID staining for HER2 protein was performed in the same manner as in Example 1, the number of bright spots derived from HER2 was measured, and a PID score was obtained.

  PDX is an abbreviation for Patient-derived tumor xenograft (patient-derived tumor xenograft), and PDX animals are transplanted with tumor tissues derived from patients (humans) into mice or other experimental animals. It is an animal produced by growing in the body. In addition, transplanting human-derived tumor tissue that has grown in the body of a mouse to another mouse is called “passage”, but it is also possible to pass tumor tissue collected from a patient across generations by passage It has become. In recent years, the usefulness of using a mouse transplanted with such a patient's tumor tissue or a mouse whose tumor tissue has been passaged instead of using the patient from whom the tumor was collected as a specimen has been discussed.

The tissue specimen used in this example was prepared by the following procedure.
(1) Specimen acquisition: A breast cancer patient specimen having a size of 1 cm ³ to be transplanted was purchased from Sofia Bio LLC, a clinical specimen supplier company.
(2) Preparation of PDX mice: From 8 breast cancer patients who received preoperative chemotherapy (5 patients who became pCR (pCR group), 3 patients who did not become pCR (non-pCR group)) Each of the collected tumor tissues was transplanted into 3 mm ³ squares subcutaneously of 3 severe combined immunodeficient mice (NOD-SCID mice). Mice were raised in a sterile facility for about 1 month and collected when the tumor tissue grew to 1 cm ³ . The collected cancer tissue was fixed with 10% formalin for 24 hours, and then a paraffin-embedded tissue block was prepared and stored according to a conventional method.
(3) Staining of a paraffin section slide The obtained paraffin block was cut out to a thickness of 4 μm and pasted on a glass slide to prepare a specimen slide. In the same manner as in Example 1, DAB staining for HER2 protein and PID staining was performed for evaluation. As a result, a result showing the same tendency as in Example 1 was obtained.

[Reference Example] Evaluation of binding force between one streptavidin-modified PID particle and a specific density of biotin Amount of binding between biotin immobilized at a constant density on a gold substrate and one PID particle (A in FIG. 25). AFM cantilevers were coated with streptavidin-modified PID particles via PEG chains (A and B in FIG. 25). In order to set the density of biotin on the gold substrate to a predetermined value, biotinylated PEG alkanethiol as a biotin conjugate molecule and (11-mercaptoundecyl) triethylene glycol as a spacer molecule are mixed with 0:10 (condition I) or 3: 7 (condition II) was mixed at the ratio of the number of molecules. When the mixture was added onto the gold substrate, a self-assembled film of each molecule was formed on the gold substrate due to the affinity of the thiol group for gold. From the obtained streptavidin-modified PID particles and the binding force-distance curve of the molecules immobilized on the substrate, a histogram showing the binding force distribution between the two molecules is prepared by the AFM measurement, and the average binding force is calculated. According to this, the average binding force in condition I is 95.7 pN (FIG. 25C), and the binding force mainly acts between the streptavidin that modifies PID and the spacer molecule ethylene glycol.・ It is thought to be due to non-specific interactions such as Del Waals forces. In contrast, the average binding force in condition II is 135.5 pN (D in FIG. 25), and there is a difference of about 40 pN between the binding forces in condition I and II. This difference is the same as the binding force between one streptavidin molecule and one biotin molecule reported so far. In the condition II of the experiment shown in this reference example, 1: 1 of streptavidin and biotin is used. It has been suggested that the binding of can be detected successfully. Furthermore, after streptavidin was locked with a blocking reagent, when the binding force was measured in Condition II (condition III), the average binding force decreased to 94.0 pN (E in FIG. 25). This value is the same as the value of condition I, indicating that the binding between biotin on the gold substrate surface and streptavidin on the PID surface was inhibited by blocking.

Claims (7)

A test support method that supports the prediction of complete pathological response (pCR) of breast cancer preoperative therapy using a sample of breast cancer tissue collected from a breast cancer patient undergoing preoperative chemotherapy,
[1] A step of acquiring a fluorescent image of a breast cancer tissue section in which bright spots of fluorescent nanoparticles labeled with one or more types of breast cancer-related proteins are represented,
[2] A step of obtaining one or more indicators relating to the expression level of the breast cancer-related protein based on the bright spot of the fluorescent image, and [3] pCR prediction by analysis using the one or more indicators Acquiring information for
Inspection support method including The step [1] is a step of acquiring a fluorescent image of a breast cancer tissue section in which bright spots of fluorescent nanoparticles labeled with at least two types of breast cancer-related proteins containing HER2 are represented,
The step [2] acquires, as the index, a numerical value representing the expression level of each of the two or more types of breast cancer-related proteins, or a numerical value calculated from a combination of the numerical values, based on the bright spot of the fluorescent image. Process,
The step [3] is a step of obtaining information for predicting pCR by analysis including comparing the numerical value with a predetermined threshold value.
The inspection support method according to claim 1. The step [1] is a step of obtaining a fluorescent image of a breast cancer tissue section in which fluorescent luminescent spots of fluorescent nanoparticles labeled with one or more types of breast cancer-related proteins are represented.
The step [2] is a step of acquiring a histogram based on the expression level of each cell of the breast cancer-related protein based on the bright spot of the fluorescent image and acquiring it as the index,
The step [3] is a step of obtaining information for predicting pCR by an analysis including at least typifying the distribution pattern of the histogram.
The inspection support method according to claim 1. The step [1] is a step of obtaining a fluorescent image of a breast cancer tissue section in which fluorescent luminescent spots of fluorescent nanoparticles labeled with one or more kinds of breast cancer-related proteins containing at least HER2 are represented;
The step [2] is a step of creating a histogram based on at least the expression level of each HER2 cell based on the base point of the fluorescence image and acquiring it as the index,
The step [3] is a step of obtaining information for predicting pCR by an analysis including at least typifying the distribution pattern of the histogram.
The inspection support method according to claim 3. The step [1] is a step of acquiring a fluorescence image of a breast cancer tissue section in which the fluorescent bright spots of fluorescent nanoparticles labeled with HER2 and HER1 or HER3 are represented,
The step [2] obtains numerical values representing the expression levels of HER2 and HER1 or HER3 based on the bright spot of the fluorescent image, and (a) a numerical value representing the expression level of HER2 / expression of HER1 A numerical value representing the amount, or (b) a numerical value representing the expression level of HER2 / a numerical value representing the expression level of HER3, which is a step of obtaining a value of the ratio,
The step [3] is a step of obtaining information for predicting pCR by analysis including comparing the value of the ratio of either (a) or (b) with a predetermined threshold value.
The inspection support method according to claim 2. The step [1] is a step of acquiring a fluorescent image of a breast cancer tissue section in which the fluorescent bright spots of fluorescent nanoparticles labeled with HER2 are represented,
Step [2] acquires (a) a numerical value representing the expression level of HER2 as the index based on the bright spot of the fluorescent image, and (b) creates a histogram based on the expression level of HER2 for each cell. And obtaining as the index,
Information for predicting pCR by the analysis including the combination of the step [3] (a) comparing the numerical value with a predetermined threshold, and (b) typifying the distribution pattern of the histogram. Is the process of obtaining
The inspection support method according to claim 4.   In the step [1], two or more kinds of breast cancer-related proteins containing at least HER2 are labeled with two or more kinds of fluorescent nanoparticles corresponding to each on one breast cancer tissue section. The inspection support method according to 4, 5 or 6.