Prediction and prognosis methods for breast cancer

Abstract

The present invention relates to a method for predicting the possibility of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy, to a method for selecting breast cancer treatment, to a method for breast cancer treatment, and to a method for prognosis of breast cancer after breast cancer treatment.

Description

Technical Field

[0001] The present invention relates to a method for predicting the possibility of pathological complete response (pCR) in a breast cancer patient after neoadjuvant chemotherapy, a method for selecting breast cancer treatment, a method for breast cancer treatment, and a method for prognosis of breast cancer after breast cancer treatment. Background Art

[0002] Neoadjuvant chemotherapy is an increasingly common chemotherapy modality in clinical practice and has been included as a standard treatment approach to make unresectable breast tumors operable and to assess in vivo responses to drugs. Excluding patients who do not benefit from neoadjuvant chemotherapy regimens is the most important first step in planning treatment; therefore, predicting the response to this neoadjuvant therapy is of high clinical value.

[0003] Furthermore, achievement of pathological complete response (pCR) is a very important predictor of improved disease-free survival (DFS) and overall survival (OS), regardless of treatment type (see, e.g., Broglio KR et al., 2016, JAMA Oncology 2(6): 751-760).

[0004] Although some methods and parameters that allow prediction of pCR have been described, no method has been widely accepted as a standard and is routinely used. This is mainly due to the fact that the implementation of many methods, especially Ki67 IHC (IHC refers to ImmunoHistoChemistry; Olfatbakhsh A. et al., 2018, Int J Cancer Manag. 11(5): e60098) and IHC4 (Elsamany S. et al., 2015, APJCP 16(17): 7975-7979), is difficult to standardize and therefore produces significantly different results when routinely applied in different laboratories.

[0005] Therefore, the object of the present invention is to provide an objective, quantitative, reproducible, reliable and routinely applicable method for predicting pCR in breast cancer patients after neoadjuvant chemotherapy, for selecting breast cancer treatment for a given breast cancer patient and for the prognosis of breast cancer in breast cancer patients after breast cancer treatment.

[0006] These and other objects are solved by the present invention, which will be described below. Summary of the invention

[0007] In one aspect, the present invention relates to a method for predicting the likelihood of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy, the method comprising:

[0008] The unscaled score (su) was calculated based on the relative expression levels of ERBB2, ESR1, PGR, and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients determined by reverse transcription quantitative PCR (RT-qPCR), where

[0009] a) a higher score su indicates a higher probability of pCR, wherein a higher relative expression level of ERBB2 mRNA is associated with a higher su, a higher relative expression level of ESR1 mRNA is associated with a lower su, a higher relative expression level of PGR mRNA is associated with a lower su, and a higher relative expression level of MKI67 mRNA is associated with a higher su; or

[0010] b) A lower score su indicates a higher probability of pCR, where a higher relative expression level of ERBB2 mRNA is associated with a lower su, a higher relative expression level of ESR1 mRNA is associated with a higher su, a higher relative expression level of PGR mRNA is associated with a higher su, and a higher relative expression level of MKI67 mRNA is associated with a lower su.

[0011] In one embodiment, the method comprises: determining the relative expression levels of ERBB2, ESR1, PGR and MKI67 mRNA in a pre-treatment breast tumor sample by RT-qPCR before calculating su.

[0012] In one embodiment, the neoadjuvant chemotherapy comprises administration of a taxane.

[0013] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy is accompanied by the administration of an anti-ERBB2 drug.

[0014] In one embodiment, the breast cancer is i) luminal breast cancer and / or ii) ESR1- and / or PGR-positive breast cancer.

[0015] In one embodiment, in the calculation of su, the relative expression levels (REL) of mRNAs of ERBB2, ESR1, PGR, and MKI67 are weighted as follows:

[0016] REL(ERBB2):REL(ESR1):REL(PGR):REL(MKI67)=0.35(±0.05):1(±0.15):0.39(±0.06):1.53(±0.23); or

[0017] REL(ERBB2):REL(ESR1):REL(PGR):REL(MKI67)=0.41(±0.06):1(±0.15):0.23(±0.03):1.76(±0.26).

[0018] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0019] su=baseline+WF(ERBB2)·REL(ERBB2)-WF(ESRl)·REL(ESRl)-WF(PGR)·REL(PGR)+WF(MKI67)·REL(MKI67),

[0020] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), WF(PGR) is the weight factor of REL(PGR2), and WF(MKI67) is the weight factor of REL(MKI67).

[0021] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0022] su=-6.394+0.099·REL(ERBB2)-0.279·REL(ESR1)-0.108·REL(PGR)+0.426·REL(MKI67); or

[0023] su=-13.413+0.117·REL(ERBB2)-0.288·REL(ESR1)-0.067·REL(PGR)+0.508·REL(MKI67).

[0024] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0025] su=-baseline-WF(ERBB2)·REL(ERBB2)+WF(ESRl)·REL(ESRl)+WF(PGR)·REL(PGR)-WF(MKI67)·REL(MKI67),

[0026] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), WF(PGR) is the weight factor of REL(PGR2), and WF(MKI67) is the weight factor of REL(MKI67).

[0027] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0028] su=6.394-0.099·REL(ERBB2)+0.279·REL(ESR1)+0.108·REL(PGR)-0.426·REL(MKI67); or

[0029] su=13.413-0.117·REL(ERBB2)+0.288·REL(ESR1)+0.067·REL(PGR)-0.508·REL(MKI67).

[0030] In one embodiment, the method further comprises:

[0031] The predicted probability q of pCR was calculated, where

[0032] a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0033] and

[0034] b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0035]

[0036] Among them, preferably, q equal to or greater than a predefined threshold indicates a high pCR possibility, and q less than the predefined threshold indicates a low pCR possibility.

[0037] In one embodiment, the method further comprises: calculating a clinical score s based on su, wherein s ranges from 0 to 100.

[0038] In one embodiment, su is calculated by using the following formula:

[0039] su=-6.394+0.099·REL(ERBB2)-0.279·REL(ESR1)-0.108·REL(PGR)+0.426·REL(MKI67), and

[0040] The method further comprises:

[0041] The clinical score s was calculated based on su, where s was calculated by using the following formula:

[0042] s = (su + 3.960) 18.191 (rounded to 0 decimal places),

[0043] If (su+3.960)·18.191<0, then s=0, and

[0044] If (su+3.960)·18.191>100, then s=100.

[0045] In one embodiment,

[0046] a) if a higher score su indicates a higher likelihood of pCR, a score s or a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score s or a score su less than the predefined threshold indicates a low likelihood of pCR; and

[0047] b) If a lower score su indicates a higher pCR likelihood, a score s or a score su less than a predefined threshold indicates a high pCR likelihood, and a score s or a score su equal to or greater than a predefined threshold indicates a low pCR likelihood.

[0048] In another aspect, the present invention relates to a method for predicting the likelihood of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy, the method comprising:

[0049] The unscaled score (su) was calculated based on the relative expression levels of ERBB2, ESR1, and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients determined by reverse transcription quantitative PCR (RT-qPCR), where

[0050] a) a higher score su indicates a higher probability of pCR, wherein a higher relative expression level of ERBB2 mRNA is associated with a higher su, a higher relative expression level of ESR1 mRNA is associated with a lower su, and a higher relative expression level of MKI67 mRNA is associated with a higher su; or

[0051] b) A lower score su indicates a higher probability of pCR, wherein a higher relative expression level of ERBB2 mRNA is associated with a lower su, a higher relative expression level of ESR1 mRNA is associated with a higher su, and a higher relative expression level of MKI67 mRNA is associated with a lower su.

[0052] In one embodiment, the method comprises: determining the relative expression levels of ERBB2, ESR1, and MKI67 mRNA in a pre-treatment breast tumor sample by RT-qPCR before calculating su.

[0053] In one embodiment, the neoadjuvant chemotherapy comprises administration of a taxane.

[0054] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy is accompanied by the administration of an anti-ERBB2 drug.

[0055] In one embodiment, the breast cancer is i) luminal breast cancer and / or ii) ESR1- and / or PGR-positive breast cancer.

[0056] In one embodiment, in the calculation of su, the relative expression levels (REL) of mRNAs of ERBB2, ESR1, PGR, and MKI67 are weighted as follows:

[0057] REL(ERBB2):REL(ESR1):REL(MKI67)=0.34(±0.05):1(±0.15):1.61(±0.24).

[0058] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0059] su=baseline+WF(ERBB2)·REL(ERBB2)-WF(ESR1)·REL(ESR1)+WF(MKI67)·REL(MKI67),

[0060] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0061] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0062] su=-15.209+0.114·REL(ERBB2)-0.335·REL(ESR1)+0.539·REL(MKI67).

[0063] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0064] su=-baseline-WF(ERBB2)·REL(ERBB2)+WF(ESR1)·REL(ESR1)-WF(MKI67)·REL(MKI67),

[0065] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0066] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0067] su=15.209-0.114·REL(ERBB2)+0.335·REL(ESR1)-0.539·REL(MKI67).

[0068] In one embodiment, the method further comprises:

[0069] The predicted probability q of pCR was calculated, where

[0070] a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0071] and

[0072] b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0073]

[0074] Among them, preferably, q equal to or greater than a predefined threshold indicates a high pCR possibility, and q less than the predefined threshold indicates a low pCR possibility.

[0075] In one embodiment, the method further comprises: calculating a clinical score s based on su, wherein s ranges from 0 to 100.

[0076] In one embodiment,

[0077] a) if a higher score su indicates a higher likelihood of pCR, a score s or a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score s or a score su less than the predefined threshold indicates a low likelihood of pCR; and

[0078] b) If a lower score su indicates a higher pCR likelihood, a score s or a score su less than a predefined threshold indicates a high pCR likelihood, and a score s or a score su equal to or greater than a predefined threshold indicates a low pCR likelihood.

[0079] In another aspect, the present invention relates to a method for predicting the likelihood of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy, the method comprising:

[0080] The unscaled score (su) was calculated based on the relative expression levels of ESR1 and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients measured by reverse transcription quantitative PCR (RT-qPCR), where

[0081] a) a higher score su indicates a higher probability of pCR, wherein a higher relative expression level of ESR1 mRNA is associated with a lower su, and a higher relative expression level of MKI67 mRNA is associated with a higher su; or

[0082] b) A lower score su indicates a higher probability of pCR, wherein a higher relative expression level of ESR1 mRNA is associated with a higher su, and a higher relative expression level of MKI67 mRNA is associated with a lower su.

[0083] In one embodiment, the method comprises: before calculating su, determining the relative expression levels of ESR1 and MKI67 mRNA in a pre-treatment breast tumor sample by RT-qPCR.

[0084] In one embodiment, the neoadjuvant chemotherapy comprises administration of a taxane.

[0085] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy is accompanied by the administration of an anti-ERBB2 drug.

[0086] In one embodiment, the breast cancer is i) luminal breast cancer and / or ii) ESR1- and / or PGR-positive breast cancer.

[0087] In one embodiment, in the calculation of su, the relative expression levels (REL) of the mRNAs of ESR1 and MKI67 are weighted as follows:

[0088] REL(ESR1):REL(MKI67)=1(±0.15):1.63(±0.24).

[0089] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0090] su=baseline-WF(ESR1)·REL(ESR1)+WF(MKI67)·REL(MKI67),

[0091] Where WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0092] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0093] su=-10.625-0.324·REL(ESR1)+0.527·REL(MKI67).

[0094] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0095] su=-baseline+WF(ESR1)·REL(ESR1)-WF(MKI67)·REL(MKI67),

[0096] Where WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0097] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0098] su=10.625+0.324·REL(ESR1)-0.527·REL(MKI67).

[0099] In one embodiment, the method further comprises:

[0100] The predicted probability q of pCR was calculated, where

[0101] a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0102] and

[0103] b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0104]

[0105] Among them, preferably, q equal to or greater than a predefined threshold indicates a high pCR possibility, and q less than the predefined threshold indicates a low pCR possibility.

[0106] In one embodiment, the method further comprises: calculating a clinical score s based on su, wherein s ranges from 0 to 100.

[0107] In one embodiment,

[0108] a) if a higher score su indicates a higher likelihood of pCR, a score s or a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score s or a score su less than the predefined threshold indicates a low likelihood of pCR; and

[0109] b) If a lower score su indicates a higher pCR likelihood, a score s or a score su less than a predefined threshold indicates a high pCR likelihood, and a score s or a score su equal to or greater than the predefined threshold indicates a low pCR likelihood.

[0110] In another aspect, the invention relates to a method for selecting a breast cancer treatment for a breast cancer patient, the method comprising:

[0111] calculating an unscaled score (su) as defined above based on the relative expression levels of mRNA of ERBB2, ESR1, PGR and / or MKI67 in a pre-treatment breast tumor sample of a breast cancer patient, and, optionally, a predicted likelihood of pCR q as defined above, or a clinical score s as defined above; and

[0112] A breast cancer treatment method is selected for a breast cancer patient based on su and, optionally, q or s, wherein

[0113] a) If a higher score su indicates a higher likelihood of pCR, then

[0114] - if su and, optionally, q or s, are equal to or greater than a predefined threshold, selecting neoadjuvant chemotherapy; and / or

[0115] - if su and, optionally, q or s, are less than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy, non-chemotherapy and endocrine therapy; and

[0116] b) If a lower score su indicates a higher likelihood of pCR, then

[0117] - if su and, optionally, s, are less than a predefined threshold, neoadjuvant chemotherapy is selected;

[0118] -If q is equal to or greater than a predefined threshold, neoadjuvant chemotherapy is chosen;

[0119] - if su and, optionally, s, are equal to or greater than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy, non-chemotherapy and endocrine therapy; and / or

[0120] - If q is less than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy, non-chemotherapy and endocrine therapy.

[0121] In one embodiment, the method comprises determining the relative mRNA expression level of ERBB2, ESR1, PGR and / or MKI67 in a pre-treatment breast tumor sample by RT-qPCR prior to calculating su and, optionally, q or s.

[0122] In one embodiment, the neoadjuvant or adjuvant chemotherapy comprises the administration of a taxane.

[0123] In one embodiment, the endocrine therapy is administered in an adjuvant or neo-adjuvant setting.

[0124] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy or endocrine therapy is accompanied by the administration of an anti-ERBB2 drug.

[0125] In one embodiment, the breast cancer is i) luminal breast cancer and / or ii) ESR1- and / or PGR-positive breast cancer.

[0126] In one embodiment, if a higher score su indicates a higher likelihood of pCR, then endocrine therapy is selected if su and, optionally, q or s, are less than a predefined threshold. In another embodiment, if a lower score su indicates a higher likelihood of pCR, then endocrine therapy is selected if su and, optionally, s, are equal to or greater than a predefined threshold, and / or if q is less than a predefined threshold.

[0127] In one embodiment, the endocrine therapy is administered in the neoadjuvant setting. In another embodiment, the endocrine therapy comprises administering an aromatase inhibitor.

[0128] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1- and / or PGR-positive breast cancer (e.g., luminal and ESR1- or PGR-positive), and if the breast cancer is ERBB2-positive breast cancer, the endocrine therapy is accompanied by administration of an anti-ERBB2 drug and / or a tyrosine kinase inhibitor (TKI). In one embodiment, the anti-ERBB2 drug comprises a combination of trastuzumab and pertuzumab. In one embodiment, the TKI is selected from neratinib and lapatinib.

[0129] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1- and / or PGR-positive breast cancer (e.g., luminal and ESR1- or PGR-positive), and if the breast cancer is ERBB2-negative breast cancer, the endocrine therapy is accompanied by administration of a CDK4 / 6 inhibitor and / or a Pi3KCa or mTOR inhibitor. In one embodiment, the CDK4 / 6 inhibitor is selected from ribociclib and palbociclib. In one embodiment, the mTOR inhibitor is everolimus. In one embodiment, the pi3KCa inhibitor is alpelisib.

[0130] In another aspect, the present invention relates to a method for treating breast cancer in a breast cancer patient, the method comprising:

[0131] Selecting breast cancer treatment for a breast cancer patient by using the methods defined above; and

[0132] The breast cancer treatment of choice is given to the breast cancer patient.

[0133] In one embodiment, the breast cancer treatment comprises neoadjuvant chemotherapy, wherein, preferably, the neoadjuvant chemotherapy comprises the administration of a taxane.

[0134] In one embodiment, the breast cancer treatment comprises endocrine therapy, wherein, preferably, the endocrine therapy is administered in the adjuvant or neoadjuvant setting.

[0135] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy or the endocrine therapy is accompanied by the administration of an anti-ERBB2 drug.

[0136] In one embodiment, the breast cancer is i) luminal breast cancer and / or ii) ESR1- and / or PGR-positive breast cancer.

[0137] In one embodiment, the endocrine therapy is administered in the neoadjuvant setting. In one embodiment, the endocrine therapy comprises administering an aromatase inhibitor.

[0138] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1- and / or PGR-positive breast cancer (e.g., luminal and ESR1- or PGR-positive), and if the breast cancer is ERBB2-positive breast cancer, the endocrine therapy is accompanied by administration of an anti-ERBB2 drug and / or a tyrosine kinase inhibitor (TKI). In one embodiment, the anti-ERBB2 drug comprises a combination of trastuzumab and pertuzumab. In one embodiment, the TKI is selected from neratinib and lapatinib.

[0139] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1- and / or PGR-positive breast cancer (e.g., luminal and ESR1- or PGR-positive), and if the breast cancer is ERBB2-negative breast cancer, the endocrine therapy is accompanied by administration of a CDK4 / 6 inhibitor and / or a Pi3KCa or mTOR inhibitor. In one embodiment, the CDK4 / 6 inhibitor is selected from ribociclib and palbociclib. In one embodiment, the mTOR inhibitor is everolimus. In one embodiment, the pi3KCa inhibitor is apellis.

[0140] In another aspect, the invention relates to a chemotherapeutic compound, such as a taxane, for use in a method of treating breast cancer as defined above.

[0141] In another aspect, the present invention relates to an endocrine therapy agent for use in a method of treating breast cancer as defined above.

[0142] In another aspect, the present invention relates to a method for prognosticating breast cancer in a breast cancer patient after treatment of breast cancer, the method comprising:

[0143] Calculating an unscaled score (su) based on the relative expression levels of mRNA of ERBB2, ESR1, PGR and MKI67 in a pre-treatment breast tumor sample of a breast cancer patient as defined above, and, optionally, a predicted likelihood of pCR q as defined above, or a clinical score s as defined above, wherein

[0144] a) if a higher score su indicates a higher likelihood of pCR, su and, optionally, q or s, equal to or greater than a predefined threshold value indicate a poor prognosis, and / or su and, optionally, q or s, less than a predefined threshold value indicate a good prognosis; and

[0145] b) if a lower score su indicates a higher likelihood of pCR, then i) su and, optionally, s, equal to or greater than a predefined threshold indicate a good prognosis, and / or su and, optionally, s, less than a predefined threshold indicate a poor prognosis, and ii) q equal to or greater than a predefined threshold indicates a poor prognosis, and / or q less than a predefined threshold indicates a good prognosis.

[0146] In one embodiment, the method comprises determining the relative mRNA expression level of ERBB2, ESR1, PGR and / or MKI67 in a pre-treatment breast tumor sample by RT-qPCR prior to calculating su and, optionally, q or s.

[0147] In one embodiment, the good prognosis includes an increased / high likelihood of distant recurrence-free survival (DRFS), disease-free survival (DFS), and / or overall survival (OS).

[0148] In one embodiment, the poor prognosis includes a decreased / low likelihood of distant recurrence-free survival (DRFS), disease-free survival (DFS), and / or overall survival (OS).

[0149] In one embodiment, the breast cancer treatment comprises neoadjuvant chemotherapy or adjuvant chemotherapy.

[0150] In one embodiment, the breast cancer treatment comprises adjuvant endocrine therapy.

[0151] In another aspect, the present invention relates to the use of a kit in a method as defined above, wherein the kit comprises:

[0152] at least one pair of ERBB2-specific primers;

[0153] At least one pair of ESR1-specific primers;

[0154] at least one pair of PGR-specific primers; and / or

[0155] At least one pair of MKI67-specific primers.

[0156] In one embodiment, the kit further comprises at least one ERBB2-specific probe, at least one ESR1-specific probe, at least one PGR-specific probe and / or at least one MKI67-specific probe.

[0157] In one embodiment, the kit further comprises at least one pair of reference gene-specific primers and, optionally, at least one reference gene-specific probe.

[0158] In one embodiment, the reference gene is selected from B2M, CAFM2, TBP, PUM1, MRFP19, GUSB, RPF37A and CYFIP1.

[0159] In another aspect, the present invention relates to a method for predicting the likelihood of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy as defined above, a method for selecting breast cancer treatment for a breast cancer patient as defined above, or a method for prognosis of breast cancer in a breast cancer patient after breast cancer treatment as defined above, wherein the method is implemented by a computer or partially implemented by a computer.

[0160] In another aspect, the invention relates to a data processing apparatus / apparatus / system comprising means for performing a computer-implemented or partly computer-implemented method as defined above.

[0161] In another aspect, the invention relates to a computer program comprising instructions which, when the program is executed by a computer, cause the computer to perform a computer-implemented or partly computer-implemented method as defined above.

[0162] In another aspect, the invention relates to a transitory or non-transitory computer-readable data carrier having stored thereon a computer program as defined above. BRIEF DESCRIPTION OF THE DRAWINGS

[0163] Figure 1 Shown are the predicted likelihood of pCR (A) and the distribution of clinical score values ​​(B) in a complete sample set of the training cohort.

[0164] Figure 2 Shown are the predicted likelihood of pCR (A) and the distribution of clinical score values ​​(B) in samples from the neoadjuvant chemotherapy study S080.

[0165] Figure 3 Shown 1 st Distribution of the predicted probability of pCR (A) and clinical score values ​​(B) in a complete sample set of the endocrine study.

[0166] Figure 4 The results show that the training group was divided into four quartiles according to the clinical scores. Subtype (l3 th St Gallen Guide). (A), (B), (C) and (D): Quartiles 1, 2, 3 and 4, respectively. The proportion of subtypes.

[0167] Figure 5 Shown by Subtype separated 3rd Distribution of score 1 for each sample in the adjuvant therapy cohort.

[0168] Figure 6 Shown is the ROC analysis of the prediction of pCR using clinical scores in samples from the S080 study.

[0169] Figure 7 An x / y plot comparing the predicted likelihood of pCR based on the model generated by the Techno / Prepare cohort (x-axis) with the predicted likelihood of pCR by the predefined model (y-axis) is shown. The predefined score is constrained to values ​​between 0 and 100, whereas the Techno / Prepare model is not.

[0170] Figure 8 The pCR rate in the Techno / Prepare cohort according to clinical score is shown. Quartiles (Q1-4) were predefined based on the training cohort. Small tumors (cT1 or cT2) had higher pCR rates.

[0171] Fig. 9 Shows the Techno / Prepare group sample according to (l3 th Distribution of clinical scores for subtypes defined by the StGallen guidelines. The mean pCR rate for samples with scores below the predefined threshold of 42 was ∼3%, whereas the mean pCR rate for samples with high scores (>42) was -25%.

[0172] Fig.10 Shows the Techno / Prepare group sample according to Clinical score distribution for sample groups defined by the combination of ESR1 and PGR (hormone receptor = HR) and ERBB2 (HER2). The mean pCR rate for samples with scores below the predefined threshold of 42 was ~3%, while the mean pCR rate for samples with high scores (>42) was -25%.

[0173] Fig.11 The ROC curve of the continuous prediction score 1 for predicting pCR in the Techno / Prepare cohort samples is shown. The arrow starting at 80% on the x-axis indicates a specificity of 80%, the arrow ending at -70% on the x-axis indicates a sensitivity of 80%, and the arrow ending at -60% on the x-axis indicates the predefined Q2 threshold (CLASS 1_42).

[0174] Fig.12The regression model estimating the likelihood of pCR as a function of the continuous score 1 is shown; the thick curve represents the estimated value and the thin curve represents the 95% confidence interval (fixed score value point by point). The two arrows mark the thresholds corresponding to 10% and 20% predicted likelihood of pCR.

[0175] Fig.13 Shown is a Kaplan Meier analysis of the Techno / Prepare cohort divided by high / low scores (threshold 42) for cT1-T2 tumors with 0-3 positive lymph nodes in patients who did not achieve pCR. DFS = disease-free survival, DDFS = distant disease-free survival (also referred to herein as distant recurrence-free survival DRFS), OS = overall survival. In the three Kaplan Meier graphs, the upper line represents a patient with a low score result, and the lower line represents a patient with a high score result (threshold ≥ 42). HR = hazard ratio.

[0176] Fig.14 Shown is a correlation analysis of the continuous pCR score (score 1) of the reduction in tumor size after neoadjuvant chemotherapy (A) and residual tumor (B) in patients of the second validation cohort (Neo-Italy) who did not achieve pCR (residual tumor remaining).

[0177] Other objects, advantages and features of the present invention will become apparent from the following detailed description, particularly when considered in conjunction with the accompanying drawings. DETAILED DESCRIPTION

[0178] Although the present invention is described in detail below, it should be understood that the present invention is not limited to the specific methods, protocols and reagents described herein, as they may vary. It should also be understood that the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the scope of the present invention, which is limited only by the appended claims. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those of ordinary skill in the art.

[0179] Hereinafter, some elements of the present invention will be described. These elements can be listed together with specific embodiments, but it should be understood that they can be combined in any way and in any number to produce other embodiments. The various described embodiments and preferred embodiments should not be interpreted as limiting the present invention to only the embodiments clearly described. Such description should be understood to support and include embodiments, which combine the embodiments clearly described with any number of disclosed and / or preferred elements. In addition, unless the context otherwise indicates, it should be considered that the specification of the application discloses any arrangement and combination of all description elements in the application.

[0180] Preferably, the terms used herein are defined as described in "A multilingual glossary of biotechnological terms (IUPAC recommendations)", HGW Leuenberger, B. Nagel, and H. Kolbl, eds., Helvetica Chimica Acta, CH-4010 Basel, Switzerland, (1995).

[0181] The practice of the present invention will employ, unless otherwise indicated, conventional methods of chemistry, biochemistry, cell biology, immunology and recombinant DNA techniques, which are explained in the literature in the field (see, e.g., Molecular Cloning: A Laboratory Manual, 3rd edition, J. Sambrook et al., eds., Cold Spring Harbor Laboratory Press, Cold Spring Harbor 2000).

[0182] Throughout this specification and the claims that follow, unless the context requires otherwise, the word "comprise" and variations such as "comprises" and "comprising" should be understood to imply the inclusion of the member, integer or step or group of members, integers or steps, but not to exclude any other member, integer or step or group of members, integers or steps, although in some embodiments the other member, integer or step or group of members, integers or steps may be excluded, i.e., the subject matter is the inclusion of the member, integer or step or group of members, integers or steps. Unless otherwise specified herein or clearly contradictory to the context, the terms "a or an" and "the" and similar references used in the context of describing the present invention (particularly in the context of the claims) should be interpreted as covering the singular and the plural. The recitation of numerical ranges herein is intended only to be used as a shorthand method of referring to each individual value falling within the range, respectively. Unless otherwise specified herein, each individual value is incorporated into the specification as if it were individually cited herein. Unless otherwise specified herein or clearly contradicted by the context, all methods described herein can be performed in any suitable order. The use of any and all examples or exemplary language (e.g., "such as") provided herein is intended only to better illustrate the present invention and is not intended to limit the scope of the present invention otherwise claimed. No language in this specification should be interpreted as indicating any unclaimed element essential to practicing the present invention.

[0183] Some documents are cited throughout this specification. Each document cited herein (including all patents, patent applications, scientific publications, manufacturer's specifications, instructions, etc.), whether above or below, is incorporated herein by reference in its entirety. Nothing herein should be construed as admitting that the present invention is not entitled to preempt the disclosure of prior inventions.

[0184] In one aspect, the present invention relates to a method for predicting the likelihood of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy, the method comprising:

[0185] Based on the expression levels, preferably relative expression levels, of ERBB2, ESR1, PGR and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients determined by reverse transcription quantitative PCR (RT-qPCR), an unscaled score (scoreunscaled, su) is calculated, where

[0186] a) a higher score su indicates a higher probability of pCR, wherein a higher expression level of ERBB2 mRNA is associated with a higher su, a higher expression level of ESR1 mRNA is associated with a lower su, a higher expression level of PGR mRNA is associated with a lower su, and a higher expression level of MKI67 mRNA is associated with a higher su; or

[0187] b) A lower score su indicates a higher probability of pCR, where a higher expression level of ERBB2 mRNA is associated with a lower su, a higher expression level of ESR1 mRNA is associated with a higher su, a higher expression level of PGR mRNA is associated with a higher su, and a higher expression level of MKI67 mRNA is associated with a lower su.

[0188] The term "breast cancer" refers to a cancer that originates from breast tissue, most commonly from the lining of the milk ducts or the lobules that supply milk to the ducts. Cancers that originate from the ducts are called ductal carcinomas, while cancers that originate from the lobules are called lobular carcinomas. Breast cancer sometimes manifests as metastatic disease. Common metastatic sites include bones, liver, lungs, and brain. Breast cancer occurs in humans and other mammals. Although the vast majority of human cases occur in women, male breast cancer may also occur. In one embodiment of the invention, breast cancer is primary breast cancer (also called early breast cancer). Primary breast cancer refers to breast cancer that has not yet spread beyond the breast or axillary lymph nodes.

[0189] As used herein, the term "tumor" refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all precancerous and cancerous cells and tissues. The terms "tumor" and "cancer" can be used interchangeably herein. In one embodiment of the invention, the tumor is a solid tumor.

[0190] Several molecular subtypes of breast cancer / tumors are known to the skilled person. As used herein, the term "molecular subtype of a tumor" (or "molecular subtype of a cancer") refers to a subtype of a tumor / cancer that is characterized by a different molecular profile (eg, gene expression profile).

[0191] In one embodiment, the molecular subtype is selected from the group comprising ERBB2 / HER2-positive, triple negative (also called "basal-like"), luminal A(-like) and luminal B(-like), preferably consisting of the group. The term "basal-like" refers to the fact that the gene expression of such a tumor has certain similarities with the gene expression of basal epithelial cells. The term "luminal" is derived from the similarity of gene expression between tumors and luminal epithelial cells. In one embodiment, the molecular subtype is selected from the group comprising, preferably consisting of, the molecular subtypes according to the 13th St Gallen guidelines (the 13th StGallen guidelines) (Goldhirsch A. et al., 2013, Ann Oncol. 24(9): 2206-2223), which are shown in Table 1 below.

[0192] In one embodiment, the molecular subtype is determined by immunohistochemistry (IHC) at the protein level and / or by RT-qPCR at the mRNA level, preferably only at the mRNA level, for example as described in WO 2015 / 024942 A1, which is incorporated herein by reference. In one embodiment, the molecular subtype, for example according to the 13th StGallen guidelines, is determined by Kit determination (BioNTech Diagnostics GmbH, Mainz, Germany; see also Laible M. et al., 2016, BMC Cancer 16:398), e.g., essentially as described in Example 2.

[0193] The term "ERBB2-positive breast cancer" (also referred to as "HER2-positive breast cancer") refers to breast cancer with high expression levels of ERBB2 as determined by methods known in the art, such as by IHC and / or RT-qPCR.

[0194] The term "ESR1-positive and / or PGR-positive breast cancer" refers to a breast cancer that expresses at least one of ESR1 and PGR, as determined by methods known in the art (e.g., by IHC and / or RT-qPCR). The breast cancer may also be referred to as "hormone receptor-positive breast cancer."

[0195] As used herein, the term "patient" refers to a human or another mammal. Preferably, the patient is a human. Preferably, the patient is a female patient.

[0196] Pathological complete response (pCR; also called pathological complete remission) is usually defined as

[0197] 1. Absence of residual invasive cancer based on hematoxylin and eosin assessment of the complete resected breast specimen and all sampled regional lymph nodes after completion of neoadjuvant systemic therapy (i.e., ypT0 / Tis ypN0 in the current AJCC staging system);

[0198] or

[0199] 2. Absence of residual invasive cancer and carcinoma in situ based on hematoxylin and eosin evaluation of the complete resected breast specimen and all sampled regional lymph nodes after completion of neoadjuvant systemic therapy (ie, ypT0 ypN0 in the current AJCC staging system).

[0200] As used herein, the term "treatment", particularly in relation to the treatment of cancer, refers to any treatment that improves health and / or prolongs (increases) the life span of a patient. The treatment may eliminate cancer, reduce the size or number of tumors in a patient, prevent or slow the development of cancer in a patient, inhibit or slow the development of new cancers in a patient, reduce the frequency or severity of symptoms in a patient, and / or reduce recurrence in a patient currently suffering from cancer or who has previously suffered from cancer.

[0201] As used herein, the term "breast cancer treatment" may include surgery, drug therapy (antihormonal / endocrine therapy and chemotherapy), radiation, immunotherapy / targeted therapy, and any combination of the foregoing.

[0202] As used herein, endocrine therapy (also referred to as "anti-hormone therapy" or "anti-hormone" therapy) refers to treatment that blocks or removes hormones. Endocrine therapy is accomplished by administering drugs that block / downregulate estrogen and / or progesterone receptors (e.g., tamoxifen). or fulvestrant ) or alternatively with an aromatase inhibitor (e.g. anastrozole or letrozole ) Drugs that block the production of estrogen target cancers that require estrogen to continue to grow. However, aromatase inhibitors are only suitable for postmenopausal patients. This is because the active aromatase in postmenopausal women is different from the prevalent form in premenopausal women, so these agents are ineffective in inhibiting the main aromatase in premenopausal women. In one embodiment, endocrine therapy includes administering aromatase inhibitors. Aromatase inhibitors are particularly suitable for neoadjuvant endocrine therapy in postmenopausal patients for downstaging of tumors to achieve breast conservation therapy.

[0203] Chemotherapy includes the administration of chemotherapeutic agents. The chemotherapeutic agents or compounds of the present invention include compounds that inhibit cell growth and cytotoxic compounds. Traditional chemotherapeutic agents work by killing cells that divide rapidly (one of the main characteristics of most cancer cells). According to the present invention, the term "chemotherapeutic agent" or "chemotherapeutic compound" includes taxanes, platinum compounds, nucleoside analogs, camptothecin analogs, anthracyclines and anthracycline analogs, etoposide, bleomycin, vinorelbine, cyclophosphamide, antimetabolites, anti-mitotics and alkylating agents, including the above-disclosed agents related to antibody conjugates, and combinations thereof. In one embodiment, chemotherapy is platinum-based, i.e., includes the administration of platinum-based compounds, such as cisplatin. According to the present invention, any prodrug, such as esters, salts or derivatives (such as conjugates of the agent) is included when referring to the chemotherapeutic agent. Examples are conjugates of the agent with a carrier substance, such as protein-bound paclitaxel, such as albumin-bound paclitaxel. Preferably, the salt of the agent is pharmaceutically acceptable. Chemotherapeutic agents are usually administered in combination, usually for 3-6 months. One of the most common treatments is cyclophosphamide plus doxorubicin (adriamycin; belonging to the group of anthracyclines and anthracycline analogs), known as AC. Sometimes, a taxane drug (e.g., docetaxel) is added, and the regime is then called CAT; taxanes attack microtubules in cancer cells. Therefore, in one embodiment, chemotherapy (e.g., neoadjuvant chemotherapy) includes administering cyclophosphamide, anthracyclines, and taxanes. Another common treatment that produces equivalent results is cyclophosphamide, methotrexate (an anti-metabolite), and fluorouracil (a nucleoside analog (CMF)). Another standard chemotherapy regimen includes fluorouracil, epirubicin, and cyclophosphamide (FEC), which may be supplemented with a taxane (eg, docetaxel) or vinorelbine.

[0204] In one embodiment, as used herein, the term "anti-ERBB2 drug" refers to an anti-ERBB2 / HER2 antibody, particularly a monoclonal anti-ERBB2 / HER2 antibody. Monoclonal anti-ERBB2 / HER2 antibodies include trastuzumab and pertuzumab They can be given alone or in combination. The combination of trastuzumab and pertuzumab is also called a "double blockade" of ERBB2 / HER2. Trastuzumab is only effective in cancers where ERBB2 / HER2 is overexpressed. Other monoclonal antibodies, such as ertumaxomab Clinical trials are currently underway. Anti-ERBB2 / HER2 antibodies may be further modified to include a therapeutic moiety / agent, such as a cytotoxic agent, a drug (e.g., an immunosuppressant), a chemotherapeutic agent, or a radionuclide or radioisotope. Thus, if the tumor treatment regimen includes (a combination of) anti-ERBB2 / HER2 therapy and chemotherapy, an anti-ERBB2 / HER2 antibody conjugated to a chemotherapeutic agent may be used. Cytotoxins or cytotoxic agents include any agent that is harmful to cells and particularly kills cells. Examples include mertansine or emtansine (DM1), paclitaxel, cytochalasin B, gramicidin D, ethidium bromide, emetine, mitomycin, etoposide, tenoposide, vincristine, vinblastine, colchicin, doxorubicin, daunorubicin, dihydroxy anthracin, diketone, mitoxantrone, mithramycin, actinomycin D, D), amanitin, 1-dehydrotestosterone, glucocorticoids, procaine, tetracaine, lidocaine, propranolol and puromycin and their analogs or homologues. In one embodiment, the antibody conjugate is trastuzumab (T)-DM1, such as trastuzumab emtansine.Other suitable therapeutic agents for forming antibody conjugates include, but are not limited to, antimetabolites (e.g., methotrexate, 6-mercaptopurine, 6-thioguanine, cytarabine, fludarabin, 5-fluorouracil dacarbazine, In some embodiments, the therapeutic agent is a cytotoxic agent or a radiotoxic agent. In another embodiment, the therapeutic agent is an immunosuppressant. In yet another embodiment, the therapeutic agent is GM-CSF. In another preferred embodiment, the therapeutic agent is doxorubicin, cisplatin, bleomycin, sulfate, carmustine, chlorambucil, cyclophosphamide or ricin A. Other therapeutic moieties include therapeutic moieties that act on mRNA and / or protein synthesis. Several transcription inhibitors are known. For example, actinomycin D, which is both a transcription inhibitor and a DNA damaging agent, inserts into DNA, thereby inhibiting the initiation phase of transcription. Flavopiridol targets the elongation phase of transcription. α-Arnanitin directly binds to RNA polymerase II, thereby causing both the initiation phase and the elongation phase to be inhibited. Anti-ERBB2 / HER2 antibodies can also be conjugated to radioactive isotopes (e.g., iodine-131, yttrium-90 or indium-111) to produce cytotoxic radiopharmaceuticals. In another embodiment, as used herein, the term "anti-ERBB2 drug" refers to a small compound that targets ERBB2 / HER2, such as lapatinib (. or ), afatinib, or neratinib.

[0205] Adjuvant therapy is treatment given in addition to (i.e., after) the primary, main, or initial treatment. An example of adjuvant therapy is additional treatment (e.g., by chemotherapy) given post-surgically, where, preferably, all detectable disease has been removed, but there is still a statistical risk of recurrence due to occult disease. Neoadjuvant therapy is treatment given before primary treatment, such as pre-surgical chemotherapy.

[0206] The term "mRNA" refers to "messenger RNA" and to a "transcript" encoding a peptide or protein. mRNA generally comprises a 5' untranslated region (5'-UTR), a protein or peptide coding region and a 3' untranslated region (3'-UTR). mRNA has a limited half-life in cells and in vitro.

[0207] According to the present invention, the expression level of mRNA is measured by reverse transcription quantitative PCR (RT-qPCR). Since RNA cannot be directly amplified in PCR, it must be reverse transcribed into cDNA using reverse transcriptase. For this reason, one-step RT-qPCR can be utilized, which combines the reverse transcription reaction with the DNA amplification performed by PCR in the same reaction. In one-step RT-qPCR, the RNA template is mixed in a reaction mixture containing reverse transcriptase, DNA polymerase, primers and probes, dNTPs, salts and detergents. In the first step, the target RNA is reversely transcribed by reverse transcriptase using a target-specific reverse primer. Then, cDNA is amplified in a PCR reaction using primers / probes and DNA polymerase.

[0208] In one embodiment, quantitative PCR is fluorescence-based quantitative real-time PCR, in particular fluorescence-based quantitative real-time PCR. Fluorescence-based quantitative real-time PCR includes the use of fluorescently labeled probes. Preferably, the fluorescently labeled probe consists of an oligonucleotide labeled with both a fluorescent reporter dye and a quencher dye (= double-labeled probe). Suitable fluorescent reporters and quencher dyes / parts are known to those skilled in the art, including but not limited to the reporter dye / part 6-FAM. TM , JOE TM , and quencher dye / moiety dabcyl, TAMRA TM , BHQ TM -l, BHQ TM -2 or BHQ TM-3. Amplification of the probe-specific product causes cleavage of the probe (=amplification-mediated probe displacement), resulting in an increase in reporter fluorescence. The increase in fluorescence in the reaction is proportional to the increase in target amplification. By using 480II system (Roche Diagnostics) or Versant kPCR system (Siemens) or Mx3005P system (Agilent Technologies) or equivalent real-time instrument to detect the fluorescence from the probe, one can measure the increase in fluorescence in real time. In one embodiment, RT-qPCR is performed using 480II system (Roche Diagnostics). In another embodiment, RT-qPCR is performed using 480II system, and the results obtained with the system were arithmetically converted to those obtained with The results obtained with the 480II system correspond to the results obtained with the 480II system. The output of the analysis is the Cq value (Cq = quantitative cycle) for each target gene / sequence. The Cq value (also called the cycle threshold (CT) value) is determined by the number of PCR amplification cycles after which the fluorescent signal of the probe exceeds a certain background signal, where the Cq value is a measure of the amount of target molecules in the sample before PCR amplification. Preferably, the Cq value is calculated using suitable software (e.g., Microsoft Excel TM ) or statistical packages (e.g. 9.0.0,GraphPadPrism4,Genedata Expressionist TM) is further analyzed by Cq values. Based on the Cq results of a standard curve with known target concentrations, the Cq values ​​can be converted to absolute target molecular weights (e.g., ng / μl or molecules / μl). Alternatively, the target amount can be reported as an amount that is x-fold reduced or increased based on a reference value (=ΔCq). A low ΔCq value (small difference) indicates a higher target amount relative to a reference value compared to a high ΔCq (large difference). It is appropriate to recalculate ΔCq by subtracting ΔCq from a fixed value (e.g., the number of PCR cycles, e.g., 40). The result is a value that is directly related to the target amount (high value=high amount) and is expressed as 40-ΔCq value, where one integer refers to twice the target amount (e.g., a value of 34 represents twice the amount of a value of 33). Depending on the desired reproducibility and accuracy of the system, multiple reference assays can be combined (panel) or the ΔCq of the sample can be recalculated / standardized with the ΔCq of the calibrator to obtain a ΔΔCq value (1-point calibration; Pfaffl, 2001, Nucleic Acid Res. 29 (9): e45). Preferably, the Cq value is not converted by any other mathematical operation that may distort the ratio of the Cq value. By using different fluorescent groups for specific probes, different target assays can also be multiplexed in the same reaction. During PCR, each target in the multiplex is amplified in parallel, but detected separately using different fluorescence emissions.

[0209] In one embodiment, as used herein, the term "mRNA expression level" refers to the absolute expression level of the mRNA, preferably given as a Cq value. In one embodiment, the Cq value is directly used for calculation (e.g., subtracted from other Cq values) without prior standardization with one or more reference genes.

[0210] In another embodiment, as used herein, the term "expression level of mRNA" refers to the relative expression level of mRNA.

[0211] In one embodiment, the amplification efficiency of qPCR is between 90% and 110%. Preferably, if the amplification efficiency of qPCR is lower than 90% or higher than 110%, the corresponding Cq value is corrected to conform to 100% amplification efficiency.

[0212] Preferably, the primers used according to the invention have a length of 15 to 30 nucleotides, in particular deoxyribonucleotides. In one embodiment, the primers are designed so that (1) they are specific for the target mRNA sequence (e.g., ERBB2, ESR1, PGR or MKI67), (2) they provide an amplicon size of less than 150 bp (preferably less than 100 bp), (3) they detect all known splice variants of the encoded protein, (4) they exclude known polymorphisms (e.g., single nucleotide polymorphisms, SNPs), (5) they are mRNA specific (taking into account exons / introns; preferably, no amplification of DNA is performed), (6) they have no tendency to dimerize and / or (7) they have a melting temperature T m 58°C to 62°C (preferably, T m is about 60°C).

[0213] As used herein, the term "nucleotide" includes natural (naturally occurring) nucleotides, including nitrogenous bases selected from adenine (A), thymine (T), cytosine (C), guanine (G) and uracil (U), sugars selected from ribose, arabinose, xylose and pyranose, and deoxyribose (a combination of base and sugar, commonly referred to as "nucleoside"), and one to three phosphate groups, and it can form a phosphodiester internucleosidyl linkage. In addition, as used herein, "nucleotide" refers to nucleotide analogs. As used herein, "nucleotide analogs" means analogs of A, G, C, T or U that are recognized by DNA or RNA polymerase (whichever is applicable) and incorporated into DNA or RNA chains (whichever is appropriate) (i.e., analogs of nucleotides comprising bases A, G, C, T or U). Examples of the nucleotide analogs include, but are not limited to, 5-propynylpyrimidine (i.e., 5-propynyl-dTTP and 5-propynyl-dCTP), 7-deazapurine (i.e., 7-deazapurine) (i.e., 7-deaza-dATP and 7-deaza-dGTP), aminoallyl-dNTP, biotin-AA-dNTP, 2-amino-dATP, 5-methyl-dCTP, 5-iodo-dUTP, 5-bromo-dUTP, 5-fluoro-dUTP, N4-methyl-dCTP, 2-thio-dTTP, 4-thio-dTTP, and α-thio-dNTP. Also included are labeled analogs (e.g., fluorescent analogs, such as DEAC-propylenediamine (PDA)-ATP), analogs based on morpholino nucleoside analogs, and locked nucleic acid (LNA) analogs.

[0214] The phrase "specific to the target mRNA sequence" used in conjunction with the primers used according to the present invention means the ability of the primer to hybridize (i.e. anneal) with the cDNA of the target mRNA sequence under the conditions of appropriate temperature and solution ionic strength, particularly under PCR conditions. The conditions of temperature and solution ionic strength determine the stringency of hybridization. Hybridization requires that the two nucleic acids (i.e. primers and cDNA) contain complementary sequences, although mismatches may exist between bases depending on the stringency of hybridization. In one embodiment, "appropriate temperature and solution ionic strength conditions" refer to a temperature in the range of 58°C to 62°C (preferably a temperature of about 60°C) and a solution ionic strength commonly used in a PCR reaction mixture. In one embodiment, the sequence of the primer is 80%, preferably 85%, more preferably 90%, even more preferably 95%, 96%, 97%, 98%, 99% or 100% complementary to the corresponding sequence of the cDNA of the target mRNA sequence, as determined by a sequence comparison algorithm known in the art.

[0215] In one embodiment, primers are hybridized with the cDNA of target mRNA sequence under stringent or medium stringent hybridization conditions. As defined herein, "stringent hybridization conditions" relate to hybridization in 5x SSC / 5x Denhardt solution / 1.0% SDS at 68°C, and washed in 0.2x SSC / 0.1% SDS at room temperature, or relate to its equivalents recognized in the art (e.g., conditions for hybridization in 2.5x SSC buffer at 60°C, then several washing steps at low buffer concentrations at 37°C, and remain stable). As defined herein, "medium stringent hybridization conditions" relate to washing in 3x SSC at 42°C, or its equivalents recognized in the art. The parameters of salt concentration and temperature can be changed to achieve the optimal identity level between primer and target nucleic acid. Guidance on such conditions is available in the art, for example, by J. Sambrook et al., eds., 2000, Molecular Cloning: A Laboratory Manual, 3rd ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor; and Ausubel et al., eds., 1995, Current Protocols in Molecular Biology, John Wiley and Sons, NY.

[0216] Preferably, the probe used according to the present invention has a length of 20 to 35 nucleotides, in particular deoxyribonucleotides. In one embodiment, the probe is designed so that (1) it is specific for the target mRNA sequence (e.g., ERBB2, ESR1, PGR or MKI67), (2) it does not include known polymorphisms (e.g., single nucleotide polymorphisms, SNPs) and / or (3) the melting temperature Tm T m About 5℃ to 8℃ higher.

[0217] The phrase "specific for the target mRNA sequence" used in conjunction with the probe used according to the present invention means the ability of the probe to hybridize (i.e., anneal) with the (amplified) cDNA of the target mRNA sequence under conditions of appropriate temperature and solution ionic strength, particularly under PCR conditions. The conditions of temperature and solution ionic strength determine the stringency of hybridization. Hybridization requires that the two nucleic acids (i.e., the probe and the cDNA) contain complementary sequences, although mismatches may exist between bases depending on the stringency of hybridization. In one embodiment, "conditions of appropriate temperature and solution ionic strength" refer to temperatures in the range of 63°C to 70°C and solution ionic strengths commonly used in PCR reaction mixtures. In one embodiment, the sequence of the probe is 80%, preferably 85%, more preferably 90%, even more preferably 95%, 96%, 97%, 98%, 99% or 100% complementary to the corresponding sequence of the (amplified) cDNA of the target mRNA sequence, as determined by sequence comparison algorithms known in the art.

[0218] In one embodiment, the probe hybridizes to the (amplified) cDNA of the target mRNA sequence under stringent or moderately stringent hybridization conditions as defined above.

[0219] The probe as defined above is preferably labeled, for example, with a label selected from the group consisting of fluorescent labels, fluorescence quenching labels, luminescent labels, radioactive labels, enzyme labels and combinations thereof.Preferably, the probe as defined above is a dual-labeled probe comprising a fluorescent reporter moiety and a fluorescent quencher moiety.

[0220] In one embodiment, the expression level is normalized relative to the (average) expression level of one or more reference genes in the tumor sample. As used herein, the term "reference gene" means a gene with a relatively constant expression level at the RNA transcript / mRNA level in the system being tested (i.e., cancer). The gene may be referred to as a housekeeping gene. In one embodiment, one or more reference genes are selected from B2M, CALM2, TBP, PUM1, MRLP19, GUSB, RPL37A, and CYFIP1. Other suitable reference genes are known to those skilled in the art.

[0221] B2M refers to the gene for beta-2 microglobulin (UniProt: P61769), CALM2 refers to the gene for calmodulin-2 (UniProt: P0DP24), TBP refers to the gene for TATA-box binding protein (UniProt: P20226), PUM1 refers to the gene for pumilio homolog 1 (UniProt: Q14671), MRLP19 refers to the gene for mitochondrial 39S ribosomal protein L19 (UniProt: P49406), GUSB refers to the gene for beta-glucuronidase (UniProt: P08236), RPL37A refers to the gene for ribosomal protein L37a (UniProt: P61513), and CYFIP1 refers to the gene for cytoplasmic FMR1-interacting protein 1 (UniProt: Q7L576).

[0222] In one embodiment, the primers used according to the present invention are selected from the primers described in WO 2015 / 024942 A1 and / or WO 2016 / 131875 A1, which are incorporated herein by reference. In one embodiment, RT-qPCR is performed by Kit (BioNTech Diagnostics GmbH, Mainz, Germany; see also Laible M. et al., 2016, BMC Cancer 16:398), for example, essentially as described in Example 2.

[0223] As used herein, the term "relative expression level (REL)" refers to the expression level of a given marker gene (e.g., ERBB2, ESR1, PGR or MKI67) relative to the expression level of one or more reference genes (e.g., one or more reference genes defined herein). According to the present invention, expression levels are measured at the mRNA level (transcription level) by RT-qPCR.

[0224] In one embodiment, the relative expression level (REL) is given as a ΔCq value, which is calculated by subtracting the Cq value or mean / median Cq value of one or more reference genes from the Cq value or mean / median Cq value of the marker gene. In one embodiment, the ΔCq value is further standardized by subtracting the ΔCq value of a calibrator (e.g., a positive control, e.g., an in vitro transcribed RNA of a marker gene) from the ΔCq value to obtain a ΔΔCq value.

[0225] In one embodiment, the relative expression level (REL) of a given marker gene (i.e., REL (ERBB2), REL (ESR1), REL (PGR), or REL (MKI67)) is given as a value selected from the following: a ΔCq value, a ΔΔCq value, an X-ΔCq value, and an X-ΔΔCq value, wherein, preferably, X is an integer, wherein, preferably, the integer is the number of PCR cycles for RT-qPCR, such as 40. In one embodiment, REL is given as an X-ΔΔCq value, such as a 40-ΔΔCq value.

[0226] In one embodiment, the ΔCq value is calculated as follows: Cq of each marker of the patient sample (e.g., ERBB2, ESR1, PGR and / or MKI67) - Cq of the reference gene of the patient sample (e.g., B2M and / or CALM2) (= calculation method 1). In one embodiment, Cq is the median / mean Cq. If more than one reference gene is used, the ΔCq value is calculated as follows: Cq of each marker of the patient sample - mean / median Cq of the selected reference gene of the patient sample (= calculation method 2).

[0227] In one embodiment, ΔΔCq is calculated as follows: ΔΔCq=(marker Cq of patient sample-marker Cq of reference sample)-(reference gene Cq of patient sample-reference gene Cq of reference sample) (=calculation method 3).

[0228] In another embodiment, the ΔΔCq value is calculated as follows: (marker Cq of patient sample-reference gene Cq of patient sample)-(marker Cq of control sample-reference gene Cq of control sample)] (= calculation method 4). In one embodiment, Cq is the median / average Cq. The Cq of the reference gene can be the Cq of a single reference gene, or the average Cq of two or more reference genes (referred to as the average / median CombRef). Preferably, the same control sample (also referred to as calibrator) is used in all analyses and produces the same RT-qPCR or qPCR results. In one embodiment, the calibrator is a positive control (PC). In one embodiment, the control sample is an equimolar mixture of cell line RNA, in vitro transcribed RNA, or DNA oligonucleotides, representing a labeled mRNA or cDNA or a marker amplicon or a portion of a marker amplicon at a constant ratio. In one embodiment, CALM2 and / or B2M are used as reference genes, and a positive control (e.g., in vitro transcribed RNA) is used as a control sample (calibrator).

[0229] The gene ERBB2 (also known as HER2; location: 17q12, annotation: chromosome: 17; NC_000017.10; UniProt: P04626) encodes a member of the epidermal growth factor (EGF) receptor family of receptor tyrosine kinases. Amplification and / or overexpression of this gene have been reported in many cancers, including breast and ovarian tumors. In the NCBI database, two mRNA variants of ERBB2 are listed, which encode two protein versions. Protein and mRNA sequences can be found under accession numbers NM_001005862.1 (receptor tyrosine-protein kinase erbB-2 isoform b) and NM_004448.2 (receptor tyrosine-protein kinase erbB-2 isoform precursor).

[0230] The gene ESR1 (position: 6q25, annotation: chromosome 6, NC_000006.11; UniProt: P03372) encodes the estrogen receptor (ER), which is a ligand-activated transcription factor consisting of several domains important for hormone binding, DNA binding, and activation of transcription. Estrogen receptors are known to be involved in pathological processes including breast cancer, endometrial cancer, and osteoporosis. Four ESR1 mRNA variants are known, in which the transcript variants differ in the 5'UTR and / or use different promoters, but each variant encodes the same protein.

[0231] The gene PGR (also known as PR; location: 11q22-q23, annotation: chromosome: 11; NC_000011.9; UniProt: P06401) encodes the progesterone receptor. Steroid hormones (such as progesterone) and their receptors are involved in the regulation of eukaryotic gene expression and affect cell proliferation and differentiation in target tissues. This gene uses two different promoters and translation start sites in the first exon to produce two mRNA isoforms, A and B. These two isoforms are identical except for an additional 165 amino acids found in the N-terminus of isoform B.

[0232] The gene MKI67 (also known as Ki67; location: 10q26.2, annotation: chromosome: 10; NC_000010.10; UniProt: P46013) encodes a nuclear protein that is involved in and may be required for cell proliferation. Two mRNA variants have been described. A related pseudogene is present on chromosome 10.

[0233] In one embodiment of the present invention, the term "breast tumor sample" refers to a breast tumor tissue sample (e.g., a biopsy or resection tissue of a breast tumor) isolated from a cancer patient. In a preferred embodiment, the breast tumor tissue sample is a frozen section (cryo-section) of a breast tumor tissue sample or a chemically fixed breast tumor tissue sample. In a more preferred embodiment, the breast tumor tissue sample is a formalin-fixed and paraffin-embedded (FFPE) breast tumor tissue sample. In one embodiment, the breast tumor sample is (total) RNA extracted from a breast tumor tissue sample. In a particularly preferred embodiment, the breast tumor sample is (total) RNA extracted from a FFPE breast tumor tissue sample. In another embodiment, the breast tumor sample is a sample of one or more circulating tumor cells (CTCs) or (total) RNA extracted from one or more CTCs. Those skilled in the art are able to perform an RNA extraction step. For example, a high-purity RNA paraffin kit (Roche, Basel, Switzerland), an XTRAKT RNA extraction kit XL (Stratifyer Molecular Pathology, Cologne, Germany) or Extraction kit (BioNTech Diagnostics GmbH, Mainz, Germany) extracts total RNA from 5 to 10 μm curls of FFPE tumor tissue. The sample material to be used / tested can also be stored in a refrigerator and the method of the present invention is performed at an appropriate time point after thawing each sample material. Before starting / giving breast cancer treatment, a "pre-treatment" breast cancer sample is obtained from a breast cancer patient.

[0234] In one embodiment, the method comprises, prior to calculating su:

[0235] The expression levels of mRNA of ERBB2, ESR1, PGR and MKI67 are measured in breast tumor samples before treatment by RT-qPCR, preferably the relative expression levels.

[0236] In one embodiment, the expression level of mRNA of genes other than ERBB2, ESR1, PGR and MKI67 and optionally one or more reference genes is not determined, preferably the relative expression level is not determined.

[0237] In one embodiment, neoadjuvant chemotherapy comprises administration of a taxane.

[0238] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, neoadjuvant chemotherapy is accompanied by administration of an anti-ERBB2 drug.

[0239] In one embodiment, the breast cancer is i) luminal breast cancer, and / or ii) ESR1 -positive and / or PGR-positive breast cancer.

[0240] In one embodiment, in the calculation of su, the relative expression levels (REL) of mRNAs of ERBB2, ESR1, PGR, and MKI67 are weighted as follows:

[0241] REL(ERBB2):REL(ESR1):REL(PGR):REL(MKI67)=0.35(±0.05):1(±0.15):0.39(±0.06):1.53(±0.23); or

[0242] REL(ERBB2):REL(ESR1):REL(PGR):REL(MKI67)=0.41(±0.06):1(±0.15):0.23(±0.03):1.76(±0.26).

[0243] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the formula:

[0244] su=baseline+WF(ERBB2)·REL(ERBB2)-WF(ESR1)·REL(ESR1)-WF(PGR)·REL(PGR)+WF(MKI67)·REL(MKI67),

[0245] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), WF(PGR) is the weight factor of REL(PGR2), and WF(MKI67) is the weight factor of REL(MKI67).

[0246] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the formula:

[0247] su=-6.394+0.099·REL(ERBB2)-0.279·REL(ESR1)-0.108·REL(PGR)+0.426·REL(MKI67); or

[0248] su=-13.413+0.117·REL(ERBB2)-0.288·REL(ESR1)-0.067·REL(PGR)+0.508·REL(MKI67).

[0249] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0250] su=-baseline-WF(ERBB2)·REL(ERBB2)+WF(ESR1)·REL(ESR1)+WF(PGR)·REL(PGR)-WF(MKI67)·REL(MKI67),

[0251] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), WF(PGR) is the weight factor of REL(PGR2), and WF(MKI67) is the weight factor of REL(MKI67).

[0252] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0253] su=6.394-0.099·REL(ERBB2)+0.279·REL(ESR1)+0.108·REL(PGR)-0.426·REL(MKI67); or

[0254] su=13.413-0.117·REL(ERBB2)+0.288·REL(ESR1)+0.067·REL(PGR)-0.508·REL(MKI67).

[0255] In one embodiment, the method further comprises:

[0256] The predicted probability q of pCR was calculated, where

[0257] a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0258] and

[0259] b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0260]

[0261] Preferably, q equal to or greater than a predefined threshold indicates a high pCR possibility, while q less than the predefined threshold indicates a low pCR possibility.

[0262] In one embodiment, the method further comprises:

[0263] A clinical score s was calculated based on su, where s ranged from 0 to 100.

[0264] In one embodiment, su is calculated by using the formula:

[0265] su = -6.394 + 0.099 · REL (ERBB2) - 0.279 · REL (ESR1) - 0.108 · REL (PGR) + 0.426 · REL (MKI67), and

[0266] Wherein, the method further comprises:

[0267] The clinical score s was calculated based on su, where s was calculated by using the following formula:

[0268] s = (su + 3.960) 18.191 (rounded to 0 decimal places),

[0269] where if (su+3.960)·18.191<0 s=0, and

[0270] If (su+3.960)·18.191>100 s=100.

[0271] In one embodiment,

[0272] a) if a higher score su indicates a higher likelihood of pCR, a score s or a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score s or a score su less than the predefined threshold indicates a low likelihood of pCR; and

[0273] b) If a lower score su indicates a higher pCR likelihood, a score s or a score su less than a predefined threshold indicates a high pCR likelihood, while a score s or a score su equal to or greater than the predefined threshold indicates a low pCR likelihood.

[0274] Suitable baselines and predefined thresholds / cut-offs for formulas described herein, for example, thresholds / cut-offs for dichotomizing pCR scores in "low pCR likelihood" or "high pCR likelihood" or prognostic thresholds / cut-offs, can be easily determined by a technician based on his or her common sense and the technical guidance provided herein (see Examples). For example, a consistency study in a training-testing setting can be used to define and verify a suitable threshold / cut-off. In one embodiment, the threshold / cut-off is defined based on one or more previous clinical studies. In addition, additional clinical studies can be conducted to establish and verify the threshold / cut-off. The threshold / cut-off can be determined / defined by techniques known in the art. In one embodiment, in a training cohort by partitioning test, ROC analysis or other statistical methods, the threshold / cut-off is determined / defined based on data of pCR, overall survival (OS), disease-free survival (DFS) and / or distant recurrence-free survival (DRFS), and preferably depends on a specific clinical utility (e.g., by using SAS software 9.0.0).

[0275] In another aspect, the present invention relates to a method for predicting the likelihood of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy, the method comprising:

[0276] An unscaled score (su) is calculated based on the expression level, preferably relative expression level, of ERBB2, ESR1 and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients determined by reverse transcription quantitative PCR (RT-qPCR), where

[0277] a) a higher score su indicates a higher probability of pCR, wherein a higher expression level of ERBB2 mRNA is associated with a higher su, a higher expression level of ESR1 mRNA is associated with a lower su, and a higher expression level of MKI67 mRNA is associated with a higher su; or

[0278] b) A lower score su indicates a higher probability of pCR, wherein a higher expression level of ERBB2 mRNA is associated with a lower su, a higher expression level of ESR1 mRNA is associated with a higher su, and a higher expression level of MKI67 mRNA is associated with a lower su.

[0279] In one embodiment, wherein the method comprises, prior to calculating su:

[0280] The expression levels of ERBB2, ESR1 and MKI67 mRNA are measured in pre-treatment breast tumor samples by RT-qPCR, preferably relative expression levels.

[0281] In one embodiment, the expression level of mRNA of genes other than ERBB2, ESR1 and MKI67 and optionally one or more reference genes is not determined, preferably the relative expression level is not determined.

[0282] In one embodiment, neoadjuvant chemotherapy comprises administration of a taxane.

[0283] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, neoadjuvant chemotherapy is accompanied by administration of an anti-ERBB2 drug.

[0284] In one embodiment, the breast cancer is i) luminal breast cancer, and / or ii) ESR1 -positive and / or PGR-positive breast cancer.

[0285] In one embodiment, in the calculation of su, the relative expression levels (REL) of mRNAs of ERBB2, ESR1, PGR, and MKI67 are weighted as follows:

[0286] REL(ERBB2):REL(ESR1):REL(MKI67)=0.34(±0.05):1(±0.15):1.61(±0.24).

[0287] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the formula:

[0288] su=baseline+WF(ERBB2)·REL(ERBB2)-WF(ESR1)·REL(ESR1)+WF(MKI67)·REL(MKI67),

[0289] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0290] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the formula:

[0291] su=-15.209+0.114·REL(ERBB2)-0.335·REL(ESR1)+0.539·REL(MKI67).

[0292] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0293] su=-baseline-WF(ERBB2)·REL(ERBB2)+WF(ESR1)·REL(ESR1)-WF(MKI67)·REL(MKI67),

[0294] Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0295] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0296] su=15.209-0.114·REL(ERBB2)+0.335·REL(ESR1)-0.539·REL(MKI67).

[0297] In one embodiment, the method further comprises:

[0298] The predicted probability q of pCR was calculated, where

[0299] a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0300] and

[0301] b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0302]

[0303] Preferably, q equal to or greater than a predefined threshold indicates a high pCR possibility, while q less than the predefined threshold indicates a low pCR possibility.

[0304] In one embodiment, the method further comprises:

[0305] A clinical score s was calculated based on su, where s ranged from 0 to 100.

[0306] In one embodiment,

[0307] a) if a higher score su indicates a higher likelihood of pCR, a score s or a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score s or a score su less than the predefined threshold indicates a low likelihood of pCR; and

[0308] b) If a lower score su indicates a higher pCR likelihood, a score s or a score su less than a predefined threshold indicates a high pCR likelihood, while a score s or a score su equal to or greater than the predefined threshold indicates a low pCR likelihood.

[0309] In another aspect, the present invention relates to a method for predicting the likelihood of pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy, the method comprising:

[0310] An unscaled score (su) is calculated based on the expression level, preferably relative expression level, of ESR1 and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients determined by reverse transcription quantitative PCR (RT-qPCR), where

[0311] (i) a higher score su indicates a higher probability of pCR, wherein a higher expression level of ESR1 mRNA is associated with a lower su, and a higher expression level of MKI67 mRNA is associated with a higher su; or

[0312] (ii) A lower score su indicates a higher probability of pCR, where a higher expression level of ESR1 mRNA is associated with a higher su, and a higher expression level of MKI67 mRNA is associated with a lower su.

[0313] In one embodiment, the method comprises, prior to calculating su:

[0314] The expression levels of ESR1 and MKI67 mRNA are measured in pre-treatment breast tumor samples by RT-qPCR, preferably relative expression levels.

[0315] In one embodiment, the relative expression level of mRNA of genes other than ESR1 and MKI67 and optionally one or more reference genes is not determined, preferably the relative expression level is not determined.

[0316] In one embodiment, neoadjuvant chemotherapy comprises administration of a taxane.

[0317] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, neoadjuvant chemotherapy is accompanied by administration of an anti-ERBB2 drug.

[0318] In one embodiment, the breast cancer is i) luminal breast cancer, and / or ii) ESR1 -positive and / or PGR-positive breast cancer.

[0319] In one embodiment, in the calculation of su, the relative expression levels (REL) of the mRNAs of ESR1 and MKI67 are weighted as follows:

[0320] REL(ESR1):REL(MKI67)=1(±0.15):1.63(±0.24).

[0321] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the formula:

[0322] su=baseline-WF(ESR1)·REL(ESR1)+WF(MKI67)·REL(MKI67),

[0323] Where WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0324] In one embodiment, a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the formula:

[0325] su=-10.625-0.324·REL(ESR1)+0.527·REL(MKI67).

[0326] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0327] su=-baseline+WF(ESR1)·REL(ESR1)-WF(MKI67)·REL(MKI67),

[0328] Where WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

[0329] In one embodiment, a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula:

[0330] su=10.625+0.324·REL(ESR1)-0.527·REL(MKI67).

[0331] In one embodiment, the method further comprises:

[0332] The predicted probability q of pCR was calculated, where

[0333] a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0334] and

[0335] b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula:

[0336]

[0337] Preferably, q equal to or greater than a predefined threshold indicates a high pCR possibility, while q less than the predefined threshold indicates a low pCR possibility.

[0338] In one embodiment, the method further comprises:

[0339] A clinical score s was calculated based on su, where s ranged from 0 to 100.

[0340] In one embodiment,

[0341] a) if a higher score su indicates a higher likelihood of pCR, a score s or a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score s or a score su less than the predefined threshold indicates a low likelihood of pCR; and

[0342] b) If a lower score su indicates a higher pCR likelihood, a score s or a score su less than a predefined threshold indicates a high pCR likelihood, while a score s or a score su equal to or greater than the predefined threshold indicates a low pCR likelihood.

[0343] In another aspect, the present invention relates to a method for selecting a breast cancer treatment for a breast cancer patient, the method comprising:

[0344] Calculating an unscaled score (su) based on the expression level (preferably relative expression level) of mRNA of ERBB2, ESR1, PGR and / or MKI67 in a pre-treatment breast tumor sample of a breast cancer patient as defined above, and optionally, a predicted likelihood q of pCR as defined above, or a clinical score s as defined above; and

[0345] A breast cancer treatment is selected for a breast cancer patient based on su and optionally q or s, wherein

[0346] a) If a higher score su indicates a higher likelihood of pCR, then

[0347] - if su, and optionally q or s, are equal to or greater than a predefined threshold, neoadjuvant chemotherapy is selected; and / or

[0348] - if su, and optionally q or s, are less than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy, a non-chemotherapeutic treatment and endocrine therapy; and

[0349] b) If a lower score su indicates a higher likelihood of pCR, then

[0350] - if su, and optionally s, are less than a predefined threshold, neoadjuvant chemotherapy is selected;

[0351] - If q is equal to or greater than a predefined threshold, neoadjuvant chemotherapy is selected;

[0352] - if su, and optionally s, is equal to or greater than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy, a non-chemotherapeutic treatment and an endocrine therapy; and / or

[0353] - If q is less than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy, non-chemotherapy treatment and endocrine therapy.

[0354] In one embodiment, if a higher score su indicates a higher likelihood of pCR, then the breast cancer patient is excluded from neoadjuvant chemotherapy if su and optionally q or s are less than a predefined threshold.

[0355] In one embodiment, if a lower score su indicates a higher likelihood of pCR, the breast cancer patient is excluded from neoadjuvant chemotherapy if su and optionally s are equal to or greater than a predefined threshold and / or if q is less than a predefined threshold.

[0356] In one embodiment, the method comprises, prior to calculating su and optionally q or s:

[0357] The expression level, preferably the relative expression level, of mRNA of ERBB2, ESR1, PGR and / or MKI67 is determined in breast tumor samples before treatment by RT-qPCR.

[0358] In one embodiment, neoadjuvant chemotherapy or adjuvant chemotherapy comprises administration of a taxane.

[0359] In one embodiment, endocrine therapy is administered in the adjuvant or neoadjuvant setting.

[0360] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, neoadjuvant chemotherapy or endocrine therapy is accompanied by administration of an anti-ERBB2 drug.

[0361] In one embodiment, the breast cancer is i) luminal breast cancer, and / or ii) ESR1 -positive and / or PGR-positive breast cancer.

[0362] In one embodiment, if a higher score su indicates a higher likelihood of pCR, endocrine therapy is selected if su and optionally q or s are less than a predefined threshold. In another embodiment, if a lower score su indicates a higher likelihood of pCR, endocrine therapy is selected if su and optionally s are equal to or greater than a predefined threshold and / or if q is less than a predefined threshold.

[0363] In one embodiment, endocrine therapy is administered in the neoadjuvant setting. In one embodiment, endocrine therapy comprises administering an aromatase inhibitor.

[0364] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1-positive and / or PGR-positive breast cancer (e.g., luminal and ESR1-positive or PGR-positive), and if the breast cancer is ERBB2-positive breast cancer, endocrine therapy is accompanied by administration of anti-ERBB2 drugs and / or tyrosine kinase inhibitors (TKIs). In one embodiment, the anti-ERBB2 drug comprises a combination of trastuzumab and pertuzumab. In one embodiment, the TKI is selected from neratinib and lapatinib.

[0365] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1-positive and / or PGR-positive breast cancer (e.g., luminal and ESR1-positive or PGR-positive), and if the breast cancer is ERBB2-negative breast cancer, endocrine therapy is accompanied by administration of a CDK4 / 6 inhibitor and / or a Pi3KCa or mTOR inhibitor. In one embodiment, the CDK4 / 6 inhibitor is selected from ribociclib and palbociclib. In one embodiment, the mTOR inhibitor is everolimus. In one embodiment, the pi3KCa inhibitor is apellis.

[0366] In another aspect, the present invention relates to a method of treating breast cancer in a breast cancer patient, the method comprising:

[0367] selecting a breast cancer treatment for a breast cancer patient by using the method as defined above; and

[0368] The breast cancer treatment of choice is given to the breast cancer patient.

[0369] In one embodiment, the breast cancer treatment comprises neoadjuvant chemotherapy, wherein, preferably, the neoadjuvant chemotherapy comprises the administration of a taxane.

[0370] In one embodiment, the breast cancer treatment comprises endocrine therapy, wherein, preferably, the endocrine therapy is administered in the adjuvant or neoadjuvant setting.

[0371] In one embodiment, if the breast cancer is ERBB2-positive breast cancer, neoadjuvant chemotherapy or endocrine therapy is accompanied by administration of an anti-ERBB2 drug.

[0372] In one embodiment, the breast cancer is i) luminal breast cancer, and / or ii) ESR1 -positive and / or PGR-positive breast cancer.

[0373] In one embodiment, endocrine therapy is administered in the neoadjuvant setting. In one embodiment, endocrine therapy comprises administering an aromatase inhibitor.

[0374] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1-positive and / or PGR-positive breast cancer (e.g., luminal and ESR1-positive or PGR-positive), and if the breast cancer is ERBB2-positive breast cancer, endocrine therapy is accompanied by administration of anti-ERBB2 drugs and / or tyrosine kinase inhibitors (TKIs). In one embodiment, the anti-ERBB2 drug comprises a combination of trastuzumab and pertuzumab. In one embodiment, the TKI is selected from neratinib and lapatinib.

[0375] In one embodiment, the breast cancer is i) luminal breast cancer, and ii) ESR1-positive and / or PGR-positive breast cancer (e.g., luminal and ESR1-positive or PGR-positive), and if the breast cancer is ERBB2-negative breast cancer, endocrine therapy is accompanied by administration of a CDK4 / 6 inhibitor and / or a Pi3KCa or mTOR inhibitor. In one embodiment, the CDK4 / 6 inhibitor is selected from ribociclib and palbociclib. In one embodiment, the mTOR inhibitor is everolimus. In one embodiment, the pi3KCa inhibitor is apellis.

[0376] In another aspect, the invention relates to chemotherapeutic compounds, such as taxanes, for use in a method of treatment of breast cancer as defined above.

[0377] In another aspect, the present invention relates to an endocrine therapy agent for use in a method of treating breast cancer as defined above.

[0378] In another aspect, the present invention relates to a method for prognosing breast cancer in a breast cancer patient after treatment of breast cancer, the method comprising:

[0379] Calculating an unscaled score (su) based on the expression level (preferably relative expression level) of mRNA of ERBB2, ESR1, PGR and / or MKI67 in a pre-treatment breast tumor sample of a breast cancer patient as defined above, and optionally, a predicted likelihood q of pCR as defined above, or a clinical score s as defined above, wherein

[0380] a) if a higher score su indicates a higher likelihood of pCR, then a su, and optionally q or s, equal to or greater than a predefined threshold, indicates a poor prognosis (negative prognosis), and / or a su, and optionally q or s, less than a predefined threshold, indicates a good prognosis (positive prognosis); and

[0381] b) if a lower score su indicates a higher likelihood of pCR, then i) su, and optionally s, equal to or greater than a predefined threshold, indicates a good prognosis, and / or su, and optionally s, less than a predefined threshold, indicates a poor prognosis, and ii) q, equal to or greater than a predefined threshold, indicates a poor prognosis, and / or q, less than a predefined threshold, indicates a good prognosis.

[0382] In one embodiment, the method comprises, prior to calculating su and optionally q or s:

[0383] The relative expression level, preferably the relative expression level, of mRNA of ERBB2, ESR1, PGR and / or MKI67 is determined in breast tumor samples before treatment by RT-qPCR.

[0384] In one embodiment, a good prognosis includes an increased / high likelihood of achieving distant recurrence-free survival (DRFS), disease-free survival (DFS), and / or overall survival (OS).

[0385] In one embodiment, a poor prognosis includes a decreased / low likelihood of distant recurrence-free survival (DRFS), disease-free survival (DFS), and / or overall survival (OS).

[0386] The term "recurrence" with respect to cancer includes the reoccurrence of tumor cells at the same site and organ where the disease originated, metastasis, which may occur even many years after the initial diagnosis and treatment of the cancer, or local events such as infiltration of tumor cells into local lymph nodes. "Distant recurrence" refers to situations in which cancer cells have spread (metastasized) to distant sites (i.e., another organ) beyond the local lymph nodes of the body. Relapse-free survival is usually defined as the time from randomization to first recurrence, relapse, secondary cancer, or death.

[0387] The term "metastasis" means the spread of cancer cells from their original site to another part of the body. The formation of metastasis is a very complex process and depends on the detachment of malignant cells from the primary tumor, invasion of the extracellular matrix, penetration of the endothelial basement membrane into body cavities and blood vessels, and then infiltration of target organs after transport through the blood. Finally, the growth of new tumors at the target site depends on angiogenesis. Tumor metastasis often occurs even after the removal of the primary tumor, because tumor cells or components may retain and develop metastatic potential.

[0388] In one embodiment, breast cancer treatment comprises neoadjuvant or adjuvant chemotherapy.

[0389] In one embodiment, breast cancer treatment comprises adjuvant endocrine therapy.

[0390] In one embodiment, the method of the invention as defined above does not comprise any other diagnostic step, such as histological tumor grading or determining (axillary) lymph node status. In one embodiment, the method does not comprise any step involving immunohistochemistry (IHC).

[0391] In one embodiment, the method of the invention further comprises taking into account one or more clinical factors, such as histological tumor grade, (axillary) lymph node status, tumor size, patient age, etc.

[0392] In another aspect, the present invention relates to the use of a kit in a method as defined above, wherein the kit comprises:

[0393] at least one pair of ERBB2-specific primers;

[0394] at least one pair of ESR1-specific primers;

[0395] at least one pair of PGR-specific primers; and / or

[0396] At least one pair of MKI67-specific primers.

[0397] In one embodiment, the kit comprises:

[0398] at least one pair of ESR1-specific primers; and

[0399] At least one pair of MKI67-specific primers.

[0400] In one embodiment, the kit comprises:

[0401] at least one pair of ERBB2-specific primers;

[0402] at least one pair of ESR1-specific primers; and

[0403] At least one pair of MKI67-specific primers.

[0404] In one embodiment, the kit comprises:

[0405] at least one pair of ERBB2-specific primers;

[0406] at least one pair of ESR1-specific primers;

[0407] at least one pair of PGR-specific primers; and

[0408] At least one pair of MKI67-specific primers.

[0409] In one embodiment, the kit further comprises at least one ERBB2-specific probe, at least one ESR1-specific probe, at least one PGR-specific probe and / or at least one MKI67-specific probe. In one embodiment, the kit further comprises at least one ESR1-specific probe and at least one MKI67-specific probe. In one embodiment, the kit further comprises at least one ERBB2-specific probe, at least one ESR1-specific probe and at least one MKI67-specific probe. In one embodiment, the kit further comprises at least one ERBB2-specific probe, at least one ESR1-specific probe, at least one PGR-specific probe and at least one MKI67-specific probe.

[0410] In one embodiment, the kit further comprises at least one pair of reference gene-specific primers, and optionally at least one reference gene-specific probe. In one embodiment, the reference gene is selected from B2M, CALM2, TBP, PUM1, MRLP19, GUSB, RPL37A and CYFIP1. In one embodiment, B2M and / or CALM2 are used as reference genes.

[0411] Preferably, primers and / or probes are further defined as above. In one embodiment, the amplicon size provided by the primer is less than 150bp, preferably less than 100bp. In one embodiment, the detection of the probe is based on amplification-mediated probe displacement. In one embodiment, the probe is a dual-labeled probe comprising a fluorescent reporter portion and a fluorescent quencher portion.

[0412] In one embodiment, the kit does not contain any primers and / or probes that are specific for additional non-reference genes. In other words, the kit does not contain primers and / or probes that are specific for genes other than ERBB2, ESR1, PGR and MKI67 and optionally one or more reference genes. In one embodiment, the kit does not contain primers and / or probes that are specific for genes other than ERBB2, ESR1, MKI67 and optionally one or more reference genes. In another embodiment, the kit does not contain primers and / or probes that are specific for genes other than ESR1 and MKI67 and optionally one or more reference genes.

[0413] In one embodiment, the kit further comprises at least one control RNA sample. In one embodiment, at least one control RNA sample is used as a positive control and / or control sample (calibrator), wherein, preferably, the at least one control RNA sample comprises a synthetic mRNA encoding one or more genes selected from ERBB2, ESR1, PGR, MKI67 and one or more reference genes of one or more gene products (or parts thereof). In one embodiment, one or more reference genes are selected from B2M, CALM2, TBP, PUM1, MRLP19, GUSB, RPL37A and CYFIP1. In one embodiment, B2M and / or CALM2 are used as reference genes.

[0414] In one embodiment, the kit further comprises a reverse transcriptase and a DNA polymerase. In one embodiment, the reverse transcriptase and the DNA polymerase are provided in the form of an enzyme mix that allows for one-step RT-qPCR.

[0415] In one embodiment, the kit may further comprise DNase and a DNase reaction buffer.

[0416] As used herein, the term "kit of parts" (abbreviated as: test kit) refers to a manufactured article comprising one or more containers and optionally a data carrier. The one or more containers may be filled with one or more of the above-mentioned tools or reagents. Additional containers may be included in the test kit, which contain, for example, diluents, buffers and other reagents (e.g., dNTPs). The data carrier may be a non-electronic data carrier, such as a graphic data carrier, such as an information leaflet, an information sheet, a barcode or an access code; or an electronic / computer-readable data carrier, such as a compact disc (CD), a digital versatile disc (DVD), a microchip or other semiconductor-based electronic data carrier. The access code may allow access to a database, such as an Internet database, a centralized database or a decentralized database. The data carrier may include instructions for the test kit used in the method of the present invention. The data carrier may include a threshold or reference level of the (relative) expression level of mRNA or a threshold or reference level of the score calculated according to the method of the present invention. In the case where the data carrier contains an access code allowing access to a database, the threshold or reference level is stored in the database. In addition, the data carrier may contain information or instructions on how to perform the method of the present invention.

[0417] In one embodiment, the kit is Kit (BioNTech Diagnostics GmbH, Mainz, Germany; see also Laible M. et al., 2016, BMC Cancer 16:398).

[0418] In another aspect, the present invention relates to a method for predicting the likelihood of a pathological complete remission (pCR) in a breast cancer patient after neoadjuvant chemotherapy as defined above, a method for selecting a breast cancer treatment for a breast cancer patient as defined above, or a method for prognosing breast cancer in a breast cancer patient after breast cancer treatment as defined above, which is implemented by a computer or partially implemented by a computer.

[0419] The term "partially computer-implemented method" refers to a method wherein only certain steps (eg, calculation steps) are computer-implemented, while other steps of the method are not.

[0420] In another aspect, the invention relates to a data processing apparatus / device / system comprising means for performing a computer-implemented or partly computer-implemented method as defined above.

[0421] In another aspect, the invention relates to a computer program comprising instructions which, when the program is executed by a computer, cause the computer to perform a computer-implemented or partly computer-implemented method as defined above.

[0422] In another aspect, the invention relates to a transitory or non-transitory computer-readable data carrier, on which is stored a computer program as defined above.

[0423] The present invention particularly provides a method for predicting pathological complete remission (pCR) of breast cancer after neoadjuvant chemotherapy (particularly taxane-based chemotherapy), which preferably comprises administering an anti-ERBB2 drug for ERBB2-positive breast cancer. The prediction is made based on a pre-treatment breast tumor sample (e.g., FFPE biopsy material). The present invention provides a gene expression profiling algorithm / score that indicates the likelihood of pCR based on the expression of the mRNA markers ERBB2, ESR1, PGR and / or MKI67.

[0424] The present invention also provides a cut-off (also referred to herein as a "threshold") based on which breast cancer can be classified as having a high or low likelihood of pCR after breast cancer treatment. In addition to using a cut-off for this binary classification, the predicted likelihood of pCR for each sample can also be calculated.

[0425] The method and algorithm / score provided by the present invention can also be used to provide prognostic information for breast cancer patients after breast cancer treatment (e.g., only neoadjuvant chemotherapy or endocrine therapy). The possibility of pCR is a powerful predictor of distant recurrence-free survival (DRFS), disease-free survival (DFS) and / or overall survival (OS). For example, patients who may reach pCR should be treated with neoadjuvant chemotherapy. However, for patients who are very likely to fail to reach pCR, it is necessary to consider whether other benefits of neoadjuvant chemotherapy (e.g., partial remission (partial response)) are important enough to choose this treatment. In the case where the patient is very likely to fail to reach pCR based on the algorithm / score, adjuvant chemotherapy can be considered or the patient is usually excluded from chemotherapy. Although applicable to all types of breast cancer, particularly primary breast cancer, the score provided by the present invention shows special clinical applications (ESR1 or PGR positive; ERBB2 / HER2 positive or negative) in a subgroup (subset) of patients with luminal breast cancer and / or ESR1 and / or PGR positive breast cancer.

[0426] The present invention is further illustrated by the following examples, which should not be construed as limiting the scope of the invention.

[0427] Example

[0428] Example 1: Use Protocol for Isolation of Total RNA from FFPE Samples

[0429] Fixing tumor tissue with formalin and subsequently embedding it in paraffin is a standard method in clinical pathology and allows long-term preservation of samples. Due to the chemical modification of nucleic acids in FFPE samples, special protocols are required to extract amplifiable nucleic acids. This requires three steps: (1) removal of the paraffin, (2) lysis of the tissue and release of RNA (if necessary, de-modification of the nucleic acids), and (3) purification of the RNA through several washing steps.

[0430] The kit (BioNTech Diagnostics GmbH, Maniz, Germany) allows purification without the use of organic solvents, which can be performed in a single reaction vessel.

[0431] In a first step, the paraffin contained in the FFPE sections is liquefied in an optimized lysis buffer. Proteinase K is then added to lyse the tissue and release the nucleic acids (RNA and DNA) of the cells. In a binding buffer optimized for efficient RNA enrichment, the RNA is bound to magnetic particles that are functionalized with germanium and achieve very efficient RNA binding. The RNA bound to the magnetic particles is then washed in several increasingly stringent washing steps to ensure efficient removal of proteins and PCR inhibitors and subsequently eluted in an elution buffer. The eluate can be used directly in suitable molecular biology analyses, such as reverse transcription, RT-qPCR, microarray or NGS applications. Quantification can be performed by RT-qPCR methods or UV / VIS spectrophotometry. In order to Used in RTqPCR The eluate (see below) does not need to digest any remaining RNA.

[0432] Example 2: Use Kits measure gene expression levels of biomarkers

[0433] The kit (BioNTech Diagnostics GmbH, Maniz, Germany) allows the determination of the expression levels of selected biomarkers at the mRNA level by reverse transcription quantitative PCR (RT-qPCR).

[0434] In order to determine the expression level of a biomarker at the transcriptional level by PCR, the RNA must first be transcribed into complementary DNA (cDNA) by reverse transcriptase (so-called first-strand synthesis). The marker-specific cDNA is then amplified by DNA polymerase and the amplification is detected in real time in PCR using a fluorescently labeled hydrolysis probe. The assay is performed as a one-step reaction, i.e. reverse transcription of RNA and subsequent PCR of DNA are performed consecutively in the same reaction mixture. In addition to enzymes (reverse transcriptase and DNA polymerase), the enzyme mixture also contains dNTPs as well as salts and PCR additives. For RT-qPCR, the enzyme mix was supplemented with water, assay mix, and RNA samples.

[0435] In each of the three assay mixtures, two assays (assay = primer pair and probe specific for the respective target sequence) are combined (= duplexed). The simultaneous detection of two targets in a duplex assay has been achieved using hydrolysis probes labeled with different fluorophores; in each assay mixture, FAM is used in one assay and JOE is used in the other assay for detection. The hydrolysis probes have been modified with a fluorescent dye at the 5' end and a quencher at the 3' end, respectively. The quencher can inhibit the fluorescence of the dye as long as it is in the immediate vicinity of the dye. During amplification, the probe binds to the target sequence. Due to the exonuclease activity of the DNA polymerase, the bound probe is degraded and the dye and quencher are separated. The resulting fluorescence measured at the end of each cycle is proportional to the amount of synthesized product. In real-time PCR assays using hydrolysis probes, the number of PCR cycles required to obtain a fluorescent signal greater than the background signal is used as a measure of the number of target molecules present at the start of the reaction. The PCR cycle in which a signal above the background signal can be detected is called a quantitative cycle (Cq). In relative expression analysis, the difference between the Cq values ​​of the target and reference assays is determined (=ΔCq) to compensate for variations in the amount of RNA starting material. In addition, the ΔCq values ​​are offset relative to a calibrator to correct for run-to-run and instrument-to-instrument variations of different instruments from one manufacturer (ΔΔCq).

[0436] The marker-specific primers and probes are selected in such a way that amplification and / or detection does not occur in the absence of target gene RNA or in the presence of undesired sequences or analytes (e.g., genomic DNA), while the target gene of interest is sensitively detected. Suitable primers are described, for example, in WO 2015 / 024942 A1 and / or WO 2016 / 131875 A1.

[0437] use Kits, at least one patient sample is analyzed for each RT-qPCR run. In addition, external controls are analyzed in each run to determine the validity / invalidity of the run. To this end, A positive control RNA (positive control = PC) and water (for preparing the reactants and negative control = NC) which can also be used as a calibrator are provided in the kit. Each patient sample / control is analyzed with each assay mixture (1, 2 and 3). The analysis is performed in triplicate, so 3x3 = 9 reactions are performed for each sample / control. Assay mixture 1 contains assays for the biomarkers ERBB2 (FAM) and ESR1 (JOE), assay mixture 2 contains the biomarker assay MKI67 (FAM) and the reference assay B2M (JOE), and assay mixture 3 contains the biomarker assay PGR (FAM) and the reference assay CALM2 (JOE). The two reference assays are used to determine whether there is enough analyte (RNA) to analyze the patient sample. Invalid samples must not be used to calculate the results. For valid samples (sufficient RNA), the analysis is started with the calculation of the combined reference (CombRefSample, the geometric mean of the median Cq values ​​of B2M and CALM2). Marker-specific ΔCqSample values ​​were then determined by subtracting CombRefSample from the four median Cq values ​​for the biomarkers ERBB2, ESR1, PGR, and MKI67.

[0438] The resulting marker-specific ΔCq values ​​were then corrected using the calibrator by subtracting the correction value ΔCqPC. CombRefPC (CombRefPC, the geometric mean of the median Cq values ​​of B2M and CALM2 of the positive control PCs) was subtracted from each marker Cq value of the positive control to calculate marker-specific correction values.

[0439] In use

[0440] ΔCqSample=(median Cq[MarkerSample]-[CombRefSample]),

[0441] and

[0442] Under the condition of ΔCqPC=(median Cq[MarkerPC]-[CombRefPC]),

[0443] Get ΔΔCq value

[0444] ΔΔCq=ΔCqSample-ΔCqPC.

[0445] The final result (40-ΔΔCq value) is obtained by subtracting the ΔΔCq value from the total number of PCR cycles (40), thereby allowing the test results to be positively correlated with marker expression, a format that is helpful for interpretation in clinical decision making.

[0446] For tumor subtypes, marker-specific 40-ΔΔCq values ​​were dichotomized as "positive" or "negative" based on clinically validated thresholds (cutoff values). In addition, continuous values ​​for each quantitative marker assay were reported. The combination of these four marker results (positive / negative) can then be used to determine the molecular subtype of the tumor sample (Table 1). Therefore, to determine the subtype, all three assay mixtures must be analyzed in one run to obtain four 40-ΔΔCq values ​​for the sample.

[0447] Table 1: According to the 13th St Gallen guidelines (Goldhirsch A. et al., 2013, Ann Oncol. 24(9):2206-2223), Translation of single markers into molecular subtypes

[0448] ERBB2 ESR1 PGR MK167 St Gallen subtype Positive Positive Positive Positive Luminal B-like (HER2 positive) Positive Positive Positive Negative Luminal B-like (HER2 positive) Positive Positive Negative Positive Luminal B-like (HER2 positive) Positive Positive Negative Negative Luminal B-like (HER2 positive) Positive Negative Positive Positive Undefined Positive Negative Positive Negative Undefined Positive Negative Negative Positive HER2 positive (non-luminal) Positive Negative Negative Negative HER2 positive (non-luminal) Negative Positive Positive Positive Luminal B-like (HER2 negative) Negative Positive Positive Negative Luminal A-type Negative Positive Negative Positive Luminal B-like (HER2 negative) Negative Positive Negative Negative Luminal B-like (HER2 negative) Negative Negative Positive Positive Undefined Negative Negative Positive Negative Undefined Negative Negative Negative Positive Triple Negative (ductal) Negative Negative Negative Negative Triple Negative (ductal)

[0449] Example 3: Training of unscaled scores (score 1)

[0450] The unscaled score was trained on a set of routine FFPE biopsy samples from patients who underwent neoadjuvant chemotherapy at the University Clinic Erlangen (Germany) between 2000 and 2015. After selecting samples with sufficient tissue for sectioning (20% minimum tumor cell content and sufficient for A total of 598 samples were included in the study. RNA was extracted from a 10 μm curl of each sample according to the manufacturer's instructions. Test (BioNTech Diagnostics GmbH, Maniz, Germany). The measurement is The samples in the cohort also met these inclusion / exclusion criteria.

[0451] Inclusion criteria

[0452] -Female patient at the Department of Gynecology, University Clinic Erlangen (Germany)

[0453] -Age: At least 18 years old

[0454] - Diagnosed with invasive breast cancer and treated with neoadjuvant chemotherapy between January 2008 and December 2014

[0455] -Transfer status: M0

[0456] -If the patient is hormone receptor positive, follow guideline recommendations with neoadjuvant chemotherapy consisting of anthracycline plus cyclophosphamide and taxane (plus trastuzumab for patients with ERBB2 / HER2-positive disease), followed by surgery and then antihormonal therapy.

[0457] - Informed Consent Form (ICF) signed by the patient

[0458] - Information on the following parameters must be obtained from the pre-treatment evaluation:

[0459] The patient's age

[0460] Tumor size

[0461] ■ER status (positive / negative and % of positively stained cells)

[0462] ■PR status (positive / negative and % of positively stained cells)

[0463] HER2 status (IHC score / chromogenic in situ hybridization (CISH) amplification ratio)

[0464] ■Ki-67 status (positive / negative and % of positively stained cells)

[0465] Histological tumor grading

[0466] Axillary lymph node status

[0467] ■Follow-up information is available for up to ten years after the initial diagnosis regarding:

[0468] ■pCR(ypT0ypN0)

[0469] ■According to the regression classification of Sinn (22)

[0470] Local recurrence

[0471] Distant metastasis

[0472] ■Disease-specific survival (DSS) (if determined)

[0473] ■DDFS (or DRFS)

[0474] ■DFS

[0475] ■OS

[0476] Exclusion criteria

[0477] - Insufficient organizational materials

[0478] -Secondary malignancies

[0479] - Metastatic disease suspected at initial diagnosis

[0480] To generate the prediction score, the sample set was limited to samples with complete clinical information on age, body mass index (BMI), clinically determined tumor size (cT), clinically determined nodal status (cN), and tumor grade according to Elston and Ellis (N = 462). The integration of the four biomarkers was accomplished in the following way: two genes that confer tumor aggressiveness, ERBB2 and MKI67, resulted in higher scores when expressed at higher levels, while the two genes, ESR1 and PGR, resulted in lower scores when expressed at higher levels.

[0481] Using multivariate logistic regression, we used four The 40-ΔΔCq value was used as a predictor and the presence of pCR (yes / no) was used as a response to construct an unscaled score. pCR was defined as (ypT0ypN0). The unscaled score obtained by logistic regression was (su = unscaled score; REL(ERBB2), REL(ESR1), REL(PGR), REL(MKI67) = the number of pCRs in 40-ΔΔCq using Relative expression level determined by the kit):

[0482] su=-6.394+0.099·REL(ERBB2)-0.279·REL(ESR1)-0.108·REL

[0483] (PGR)+0.426·REL(MKI67) (= "score 1")

[0484] The signs (+ / -) can be swapped throughout the formula to obtain a score that is associated with non-pCR rather than pCR.

[0485] The results obtained from the unscaled scores can be interpreted in the following way, where su = unscaled score:

[0486]

[0487] The above ratings are based on The scoring was performed on data obtained from the 480II qPCR instrument. For data obtained from qPCR platforms other than 480II, the 40-ΔΔCq value obtained from the platform can be converted to the Expected 40-ΔΔCq values ​​on the 480II system. This conversion of 40-ΔΔCq values ​​can be accomplished by using a linear equation or by adding or subtracting a predefined Cq value to each 40-ΔΔCq value, thereby simulating 480II expression values. Another possible approach is to transfer the scores to another platform. In a dataset where the same samples were measured on the 480II system and another platform, the 40-ΔΔCq value from the other platform was used as a predictor to determine whether the 40-ΔΔCq value was derived from the 480II system using linear regression analysis. pCR score calculated based on the 40-ΔΔCq value of the same sample measured on the 480II system.

[0488] Example 4: Development of clinical scores and thresholds

[0489] To make the established score (Score 1; see Example 3) applicable to clinical routine, the unscaled score was transformed to fit within the 0 to 100 range. This format may allow for better interpretability in daily practice. The upper and lower bounds of the score (0 and 100) were set using the distribution of the unscaled score values ​​in the full sample set with valid MammaTyper results from the training cohort ( Figure 1 ), where the 0.5% and 99.5% percentiles are used as the minimum (0) and maximum (100), respectively. Using this approach, the formula for the rescaled score / clinical routine score "s" is (su = unscaled score):

[0490] If {su+3.960)·18.191<0 s=0

[0491] If {su+3.960)·18.191>100 s=100

[0492] Otherwise s = (su + 3.960) 18.191 (rounded to 0 decimal places)

[0493] The clinical significance of the score is also reflected in the use of The distribution of the other two groups analyzed was determined, Assays: S080 study (ClinicalTrials.gov identifier: NCT00149214) and the 1st Endocrine Research—See respectively Figure 2 and Figure 3 The S080 study represents a high-risk cohort of patients treated with neoadjuvant chemotherapy, the first The endocrine study represents a low-risk cohort of patients who received endocrine therapy alone. Because the predicted likelihood of achieving a pCR is related to the aggressiveness of the tumor, a high pCR score represents an aggressive tumor, while a low pCR score represents a tumor with a lower risk of recurrence.

[0494] Threshold establishment

[0495] Clinical decisions using the scores described herein can be based on the predicted likelihood of pCR for each sample that can be determined, or can be based on a binary output using a decision threshold (predicted likelihood of high / low pCR). Several decision thresholds have been established based on different principles. These thresholds have been validated in the Techno / Prepare cohort (see Example 7 below).

[0496] Table 2. Predicted likelihood of pCR, classifying samples into “low” and “high” based on the cutoff values ​​of the scores shown. The 25% quantile was used for descriptive analysis and marks a group of tumors with a particularly low likelihood of pCR.

[0497]

[0498]

[0499] Using the quartiles from the training study as thresholds, clinically meaningful separation of breast cancer subtypes was seen.

[0500] Table 3. In the third neoadjuvant study, Distribution of luminal B-like samples across all 4 quartiles of clinical scores.

[0501]

[0502] The results are shown in Figure 4 and Figure 5 .

[0503] Example 5: Validation of Scoring Score 1 in an Independent Group (S080)

[0504] The first set of samples used to validate Score 1 (Examples 3 and 4) were routine FFPE biopsies from patients enrolled in the S080 neoadjuvant chemotherapy trial (ClinicalTrials.gov Identifier: NCT00149214). Total RNA was extracted from 10 μm rolls prepared from each sample using a kit (see Example 1). The total RNA was then RT-qPCR test (see Example 2) to On 480II, four breast cancer markers HER2 / ERBB2, ER / ESR1, PgR / PGR, and Ki67 / MKI67 were relatively quantified at the mRNA level.

[0505] Effective Results and information on achievement of pCR (yes / no) were available for 91 of the 105 included samples.

[0506] ROC analysis of the score in this independent cohort yielded a high AUC value, reflecting the high predictive power of the score ( Figure 6 ).

[0507] Table 4. AUC values ​​of ROC analysis of the three scores in samples from the S080 study.

[0508]

[0509] Example 6: Prognostic information for endocrine groups

[0510] To analyze whether score 1 (Examples 3 and 4) also contains prognostic information for patients treated with endocrine therapy alone, a ROC analysis was performed for the clinical score in the 1st endocrine study to predict distant events. For comparison, the best score for predicting distant events was generated on the complete data set (best fit).

[0511] The AUCs obtained in this analysis demonstrate that this score can also predict distant recurrence in the adjuvant endocrine therapy setting. Of note, the clinical score found by an independent approach (logistic fit to pCR (yes / no)) performed almost as well (similar AUC) when applied to prognosis as the score shown by the best fit to the 1st endocrine study data.

[0512] Table 5. AUC values ​​obtained from ROC analysis of clinical scores and reference scores (best fit for the complete data set) for detection of distant events (metastasis) in the 1st endocrine study samples.

[0513]

[0514] Example 7: Second Validation of Score 1 in an Independent Group (Techno / Prepare)

[0515] The pCR prediction score was validated in a retrospective analysis of FFPE biopsy samples from patients treated with neoadjuvant chemotherapy (+ / - anti-ERBB2 / HER2 therapy) during the Techno / Prepare trials (ClinicalTrials.gov identifiers NCT00795899 and NCT00544232, respectively). To verify the generalizability of the actual scoring formula, the predicted likelihood of pCR for each sample determined once using the predefined score was compared to that determined once using the score generated independently in the Techno / Prepare cohort. By plotting these two predicted likelihoods of pCR in an x / y plot, it can be well seen that the best prediction based on the Techno / Prepare cohort closely matches the predicted likelihood of pCR obtained by the predefined score ( Figure 7 ).

[0516] Comparison of the pCR rates in the sample groups divided according to the predefined quartile thresholds in the training cohort showed a clear association between the score and the pCR rate, with lower pCR rates seen in the two low quartiles and higher pCR rates seen in the two high quartiles ( Figure 8 ).

[0517] Table 6. subtype (St Gallen 2013 guidelines), distribution of samples in areas of low and high pCR rates (see also Fig. 9 )

[0518]

[0519] Table 7. According to Fig.10 The distribution of samples in the areas of low and high pCR rates in the sample groups defined in

[0520]

[0521] When analyzing the scores of all samples in the Techno / Prepare cohort using the continuous score, a high AUC could be demonstrated, indicating the high predictive power of the score ( Fig.11 ).

[0522] The clinical score was also applied to patients in the Techno / Prepare cohort in a regression model to obtain a function of the continuous score 1, estimating the probability of pCR and the corresponding 95% confidence interval ( Fig.12 ).

[0523] Table 8. Statistical analysis of the predictive power of continuous clinical scores in the sample from Techno / Prepare.

[0524]

[0525] Likewise, in this cohort, the binary use of the score (high / low) yielded highly significant predictive power, which was maintained even when other known predictors of pCR were taken into account.

[0526] Table 9. Univariate statistical analysis of the predictive power of clinical scores applied in a binary manner in the sample from Techno / Prepare.

[0527]

[0528]

[0529] Table 10. (A) Multivariate statistical analysis of the predictive power of the clinical score applied in a binary manner (high / low) in samples from Techno / Prepare. Including binary IHC results for ER, PR, and HER2, (B) Multivariate analysis of other clinical predictors. In both analyses, the binary pCR score result remained an independent predictor of pCR.

[0530] A

[0531]

[0532] B

[0533]

[0534] As shown in Table 11 , the clinical utility of the other decision thresholds can be illustrated by the clear separation of responders from non-responders.

[0535] Table 11. Validation of other thresholds as described above in the cT1-T2 tumor subgroup. TP = true positive, FP = false positive, FN = false negative, TN = true negative, PPV = positive predictive value, NPV = negative predictive value. PPV corresponds to the pCR rate in the test-positive group and 1-NPV corresponds to the pCR rate in the test-negative group.

[0536] T1-2 TP FP FN TN PPV 1-NPV NPV pWald Odds ratio Notes CLASS1_42 48 111 5 160 30.2％ 3.0％ 97.0％ ＜.0001 13.8 Main Objectives CLASS1_69 28 41 25 230 40.6％ 9.8％ 90.2％ <.0001 6.3 CLASS1_47 47 88 6 183 34.8％ 3.2％ 96.8％ <.0001 16.3 CLASS1_50 42 84 11 187 33.3％ 5.6％ 94.4％ <.0001 8.5 CLASS1_10P 47 91 6 180 34.1％ 3.2％ 96.8％ <0.0001 15.5 CLASS1_20P 34 51 19 220 40.0％ 7.9％ 92.1％ <.0001 7.7 CLASS1_74 7 13 11 8 35.0％ 33.3％ 66.7％ 0.9234 1.1 HER2 positive only (non-luminal) CLASS1_43 11 26 2 36 29.7％ 4.8％ 94.7％ 0.0123 7.6 Luminal B-like only (HER2 positive)

[0537] The predictive power of the score with a cutoff of 42 was particularly high in the ESR1 or PGR-positive patient group, but also in the luminal B ERBB2 / HER2-positive patient group.

[0538] Table 12. Validation threshold 42 in different sample groups. Subtypes defined by (St Gallen 2013 guidelines)

[0539] Subset of CLASS_42 TP FP FN TN PPV 1-NPV NPV pWald Odds ratio all 56 167 6 189 25.1％ 3.1％ 96.9％ <.0001 10.6 T1-2, HER2-positive non-luminal 11 21 0 0 34.4％ NA NA NA NA T1-2, luminal A-like 0 0 0 22 NA NA 100％ NA NA T1-2, triple negative 20 35 0 0 36.4％ NA NA NA NA T1-2, ESR1 and PGR negative 31 56 0 0 35.6％ NA NA NA NA T1-2, luminal B-like (HER2-negative) 3 24 4 104 11.1％ 3.7％ 96.3％ 0.139 3.3 T1-2, luminal B-like (HER2 positive) 12 28 1 34 30.0％ 2.9％ 97.1％ 0.0124 14.6 T1-2, ESR1 and PGR positive 17 55 5 160 23.6％ 3.0％ 97.0％ <.0001 9.9

[0540] The score also carries prognostic information for non-responders, which is very useful for further treatment (manangement) after completion of neoadjuvant chemotherapy.

[0541] Example 8: Evaluation of the appropriate threshold range for score 1

[0542] In initial studies, a master threshold of 42 has been validated for a score of 1. Other thresholds have been systematically evaluated for their suitability for predicting pCR. The following criteria define the clinical utility of the thresholds, however, as with all diagnostic tests, a balance must be struck between the optimal values ​​of different criteria to produce a meaningful test:

[0543] -PPV (Positive Predictive Value): The ratio of true positive results among all positive results. This value should be high;

[0544] -NPV (Negative Predictive Value): The ratio of true negative results among negative results. This value should be high;

[0545] - Sensitivity: The ratio of true positive results among all positive samples (pCR). This value should be high;

[0546] -Specificity: The ratio of true negative results (pCR no) among all negative samples. This value should be high;

[0547] - Youden index: sensitivity + specificity - 100. This value should be high.

[0548] Based on the above criteria, a score 1 threshold of 38 to 49 would yield clinically meaningful results, where nonresponders could be excluded by testing and responders concentrated in a high-scoring group. The same range could be applied particularly to luminal ERBB2 / HER2-positive tumors.

[0549] Table 13. Evaluation of suitable threshold ranges for score 1 (predicted likelihood of pCR).

[0550]

[0551]

[0552]

[0553]

[0554] Regarding the establishment of prognostic thresholds (long-term outcomes) other than those validated in the Techno / Prepare cohort ( Fig.13 ), the following criteria may be applied:

[0555] -HR (hazard ratio): The ratio of the hazard rate corresponding to the condition (e.g., the test result is low / high). The HR of disease-free survival (DFS), distant metastasis-free survival (DDFS) (also referred to as distant recurrence-free survival DRFS in this article) and / or overall survival (OS) can be calculated, where DDFS and OS are the most relevant clinical parameters for primary breast cancer. Whether this value should be high or low depends on the comparison group. In the current analysis, a higher HR should be achieved.

[0556] - Kaplan Meier estimate (percentage of patients event-free (DFS, DDFS, or OS) at a given time point). There is no consensus on acceptable event rates, but in current routine practice with IHC stratification, DDFS rates of 5-10% at 5 years have been observed (Hennigs A. et al., 2016, BMC Cancer 16(1):734).

[0557] Based on the above criteria, a score 1 threshold of 25 to 29 would produce clinically meaningful results, with the low-score group having significantly better survival than the high-score group. Even lower thresholds could be applied, and even lower thresholds would produce even lower risks of recurrence. This could not be seen in this sample set because of the limited sample size.

[0558] Table 14. Assessment of appropriate threshold ranges for score 1 (prognosis)

[0559]

[0560]

[0561] Example 9: Improvement and simplification of scoring

[0562] By restricting the entire group (N=598 samples) to samples with complete IHC and available clinical data, logistic regression was performed for pCR defined as (ypT0 / ypN0) in a subset of 462 samples to find the original 4-marker score 1. After the full data from the training cohort became available, the analysis was refined in the following aspects:

[0563] - All 598 samples were used (instead of 462);

[0564] - Excludes data based on missing measurements 40-ΔΔCq value (Cq 40) (N=21);

[0565] - shrinkage correction (based on 5000 bootstrap samples) was applied to the unscaled scores to correct for overfitting;

[0566] - Normalization of MKI67 only by CALM2 (a more accurate reference gene than B2M);

[0567] - Model settings based on less than 4 markers (3 and 2 markers);

[0568] This identified / determined three scores in addition to score 1 as possible schemes for prediction of the likelihood of pCR, as shown in Tables 15 to 18.

[0569] Table 15. Summary of scoring.

[0570]

[0571] Table 15. Weight of each marker in score 1 to 4

[0572]

[0573] Table 17. AUC values ​​of scores 1-4 for predicting pCR / is in 598 samples

[0574]

[0575] Table 18. Comparison of the AUC (predicted pCR / is) of scores 1-4 to test for equality. p<0.05 was considered significant.

[0576]

[0577] Example 10: Validation of Score 1 in an Independent Group

[0578] In a retrospective analysis of archival samples from a single center, a test score of 1 was used as a predictor of success (measured as pCR) with neoadjuvant chemotherapy (NACT) (+ / - anti-HER2).

[0579] 85 FFPE biopsy samples from 2012-2018 were derived from this archive. Samples with >20% tumor cell content were subjected to RNA extraction. CE-IVD The relative mRNA expression levels of ERBB2, ESR1, PGR, and MKI67 were determined by RT-qPCR. The association of continuous scores with pCR (defined as ypT0 / is) and binary score 1 results with partial response was analyzed.

[0580] The marker positivity of the 75 samples included in the final analysis was ER 62.7%, PR 53.3%, HER2 40.0%, and Ki67 94.7% (≥20% of pos cells). 42.7% of the patients were premenopausal, and all but one sample were grade 3. The pCR rates were only 48.0% and 20.0% in all samples and in hormone receptor (HR)-positive / HER2-negative patients, respectively. The binary score 1 result was significantly associated with pCR in all patients (sensitivity: 88.9%, specificity: 51.3%, PPV: 62.8%, NPV: 83.3%), and only in HR-positive / HER2-negative patients (sensitivity: 83.3%, specificity: 70.8%, PPV: 41.7%, NPV: 94.4%). ROC analysis showed that the continuous score of 1 was well correlated with the achievement of pCR in all patients (AUC = 0.756) and in the subgroup of HR+ / HER2 patients (AUC = 0.774). For the subtypes defined by IHC and RT-qPCR, the pCR rates defined according to the St. Gallen alternative subtypes were similar in triple-negative (80.0% and 78.6%, respectively) and HER2+ non-luminal subtypes (75.0% and 70.0%, respectively). In tumors with incomplete responses, the continuous score of 1 was significantly correlated with the residual tumor size (Spearman rank correlation coefficient (Spearman rs): -0.477 p value: 0.0021) and the % reduction in tumor size (Spearman rank correlation coefficient: 0.388, p value: 0.0147).

[0581] These data confirm that score 1 can be used as a standardized tool to predict response to NACT based on pretreatment biopsy. Neoadjuvant aromatase inhibitors alone or in combination with newer-generation TKIs or CDK4 / 6 inhibitors or Pi3KCa / mTOR inhibitors may be alternative approaches for tumor downstaging in patients with inoperable luminal tumors and a low predicted probability of pCR.

Claims

1. Use of a reagent for detecting the expression level of ERBB2, ESR1, PGR and MKI67 mRNA in the preparation of a kit for predicting the possibility of pathological complete response (pCR) in breast cancer patients after neoadjuvant chemotherapy, wherein the possibility of pCR is predicted by a method comprising the following steps: The unscaled score (su) was calculated based on the relative expression levels of ERBB2, ESR1, PGR, and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients measured by reverse transcription quantitative PCR (RT-qPCR), where a) a higher score su indicates a higher probability of pCR, wherein a higher relative expression level of ERBB2 mRNA is associated with a higher su, a higher relative expression level of ESR1 mRNA is associated with a lower su, a higher relative expression level of PGR mRNA is associated with a lower su, and a higher relative expression level of MKI67 mRNA is associated with a higher su; or b) A lower score su indicates a higher probability of pCR, where a higher relative expression level of ERBB2 mRNA is associated with a lower su, a higher relative expression level of ESR1 mRNA is associated with a higher su, a higher relative expression level of PGR mRNA is associated with a higher su, and a higher relative expression level of MKI67 mRNA is associated with a lower su.

2. The use according to claim 1, wherein the neoadjuvant chemotherapy comprises administration of a taxane.

3. The use according to claim 1 or 2, wherein if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy is accompanied by the administration of an anti-ERBB2 drug.

4. The use according to claim 1 or 2, wherein the breast cancer is ESR1- and / or PGR-positive breast cancer. The use according to claim 1 or 2, wherein the breast cancer is luminal breast cancer.

6. The use according to claim 1, wherein In the calculation of su, the relative expression level (REL) weights of ERBB2, ESR1, PGR, and MKI67 mRNA are as follows: REL(ERBB2) : REL(ESR1) : REL(PGR) : REL(MKI67) = 0.35±0.05 : 1±0.15:0.39±0.06 : 1.53±0.23; or REL(ERBB2) : REL(ESR1) : REL(PGR) : REL(MKI67) = 0.41±0.06 : 1±0.15 : 0.23±0.03 : 1.76±0.

26.

7. The use according to claim 6, wherein a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula: su = baseline + WF(ERBB2)·REL(ERBB2) - WF(ESRl)·REL(ESRl) - WF(PGR)·REL(PGR) + WF(MKI67)·REL(MKI67), Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), WF(PGR) is the weight factor of REL(PGR2), and WF(MKI67) is the weight factor of REL(MKI67).

8. The use according to claim 7, wherein a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula: su = -6.394 + 0.099·REL(ERBB2) - 0.279·REL(ESR1) - 0.108·REL(PGR) +0.426·REL(MKI67); or su = -13.413 + 0.117·REL(ERBB2) - 0.288·REL(ESRl) - 0.067·REL(PGR) +0.508·REL(MKI67).

9. The use according to claim 6, wherein a lower score su indicates a higher probability of pCR, and wherein su is calculated by using the following formula: su = -baseline- WF(ERBB2)·REL(ERBB2) + WF(ESRl)·REL(ESRl) + WF(PGR)·REL(PGR) - WF(MKI67)·REL(MKI67), Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), WF(PGR) is the weight factor of REL(PGR2), and WF(MKI67) is the weight factor of REL(MKI67).

10. The use according to claim 9, wherein a lower score su indicates a higher probability of pCR, and wherein su is calculated by using the following formula: su = 6.394 - 0.099·REL(ERBB2) + 0.279·REL(ESRl) + 0.108·REL(PGR) -0.426·REL(MKI67); or su = 13.413 - 0.117·REL(ERBB2) + 0.288·REL(ESRl) + 0.067·REL(PGR) -0.508·REL(MKI67).

11. The use according to any one of claims 6 to 10, further comprising: The predicted probability q of pCR was calculated, where a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula: ;and b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula: ， Here, q equal to or greater than a predefined threshold indicates a high pCR likelihood, and q less than the predefined threshold indicates a low pCR likelihood.

12. The use according to any one of claims 6 to 10, further comprising: The clinical score s was calculated based on su, where s ranges from 0 to 100, where su was calculated by using the following formula: su = -6.394 + 0.099·REL(ERBB2) - 0.279·REL(ESR1) - 0.108·REL(PGR) +0.426·REL(MKI67), and The method further comprises: The clinical score s was calculated based on su, where s was calculated by using the following formula: s = (su + 3.960) · 18.191, rounded to 0 decimal places, where s = 0 if (su + 3.960)·18.191 < 0, and If (su + 3.960)·18.191 > 100 then s = 100.

13. The use according to claim 12, wherein a) if a higher score su indicates a higher likelihood of pCR, a score s or a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score s or a score su less than the predefined threshold indicates a low likelihood of pCR; and b) If a lower score su indicates a higher pCR likelihood, a score s or a score su less than a predefined threshold indicates a high pCR likelihood, and a score s or a score su equal to or greater than the predefined threshold indicates a low pCR likelihood.

14. Use of a reagent for detecting the expression level of ERBB2, ESR1 and MKI67 mRNA in the preparation of a kit for predicting the possibility of pathological complete response (pCR) in breast cancer patients after neoadjuvant chemotherapy, wherein the possibility of pCR is predicted by a method comprising the following steps: The unscaled score (su) was calculated based on the relative expression levels of ERBB2, ESR1, and MKI67 mRNA in pre-treatment breast tumor samples from breast cancer patients measured by reverse transcription quantitative PCR (RT-qPCR), where a) a higher score su indicates a higher probability of pCR, wherein a higher relative expression level of ERBB2 mRNA is associated with a higher su, a higher relative expression level of ESR1 mRNA is associated with a lower su, and a higher relative expression level of MKI67 mRNA is associated with a higher su; or b) A lower score su indicates a higher probability of pCR, where a higher relative expression level of ERBB2 mRNA is associated with a lower su, a higher relative expression level of ESR1 mRNA is associated with a higher su, and a higher relative expression level of MKI67 mRNA is associated with a lower su.

15. The use according to claim 14, wherein the neoadjuvant chemotherapy comprises administration of a taxane.

16. The use according to claim 14 or 15, wherein if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy is accompanied by the administration of an anti-ERBB2 drug.

17. The use according to claim 14 or 15, wherein the breast cancer is ESR1- and / or PGR-positive breast cancer.

18. The use according to claim 14 or 15, wherein the breast cancer is luminal breast cancer.

19. The use according to claim 14, wherein in the calculation of su, the relative expression level (REL) weights of the mRNAs of ERBB2, ESR1, PGR and MKI67 are as follows: REL(ERBB2) : REL(ESRl) : REL(MKI67) = 0.34 ± 0.05 : 1 ± 0.15 : 1.61 ±0.

24.

20. The use according to claim 19, wherein a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula: su = baseline + WF(ERBB2)·REL(ERBB2) - WF(ESRl)·REL(ESRl) + WF(MKI67)·REL(MKI67), Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

21. The use according to claim 20, wherein a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula: su = -15.209 + 0.114·REL(ERBB2) - 0.335·REL(ESRl) + 0.539·REL(MKI67).

22. The use according to claim 19, wherein a lower score su indicates a higher probability of pCR, and wherein su is calculated by using the following formula: su = -baseline- WF(ERBB2)·REL(ERBB2) + WF(ESR1)·REL(ESR1) - WF(MKI67)·REL(MKI67), Wherein WF(ERBB2) is the weight factor of REL(ERBB2), WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

23. The use according to claim 22, wherein a lower score su indicates a higher probability of pCR, and wherein su is calculated by using the following formula: su = 15.209 - 0.114·REL(ERBB2) + 0.335·REL(ESRl) - 0.539·REL(MKI67).

24. The use according to any one of claims 19 to 23, further comprising: The predicted probability q of pCR was calculated, where a) If a higher score su indicates a higher likelihood of pCR, q is calculated by using the following formula: ;and b) If a lower score su indicates a higher likelihood of pCR, q is calculated by using the following formula: ， Here, q equal to or greater than a predefined threshold indicates a high pCR likelihood, and q less than the predefined threshold indicates a low pCR likelihood.

25. The use according to any one of claims 19 to 23, wherein a) if a higher score su indicates a higher likelihood of pCR, a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score su less than the predefined threshold indicates a low likelihood of pCR; and b) If a lower score su indicates a higher pCR likelihood, a score su less than a predefined threshold indicates a high pCR likelihood, and a score su equal to or greater than the predefined threshold indicates a low pCR likelihood.

26. Use of a reagent for detecting the expression level of ESR1 and MKI67 mRNA in the preparation of a kit for predicting the possibility of pathological complete response (pCR) in breast cancer patients after neoadjuvant chemotherapy, wherein the possibility of pCR is predicted by a method comprising the following steps: The unscaled score (su) was calculated based on the relative expression levels of ESR1 and MKI67 mRNA in pre-treatment breast tumor samples of breast cancer patients measured by reverse transcription quantitative PCR (RT-qPCR), where a) a higher score su indicates a higher probability of pCR, wherein a higher relative expression level of ESR1 mRNA is associated with a lower su, and a higher relative expression level of MKI67 mRNA is associated with a higher su; or b) A lower score su indicates a higher probability of pCR, where a higher relative expression level of ESR1 mRNA is associated with a higher su, and a higher relative expression level of MKI67 mRNA is associated with a lower su.

27. The use according to claim 26, wherein the neoadjuvant chemotherapy comprises administration of a taxane.

28. The use according to claim 26 or 27, wherein if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy is accompanied by the administration of an anti-ERBB2 drug.

29. The use according to claim 26 or 27, wherein the breast cancer is ESR1- and / or PGR-positive breast cancer.

30. The use according to claim 26 or 27, wherein the breast cancer is luminal breast cancer.

31. The use according to claim 26, wherein In the calculation of su, the relative expression level (REL) weights of ESR1 and MKI67 mRNA are as follows: REL(ESRl) : REL(MKI67) = 1 ± 0.15 : 1.63 ± 0.

24.

32. The use according to claim 31, wherein a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula: su = baseline - WF(ESRl)·REL(ESRl) + WF(MKI67)·REL(MKI67), Where WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

33. The use according to claim 32, wherein a higher score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula: su = -10.625 - 0.324·REL(ESRl) + 0.527·REL(MKI67).

34. The use according to claim 31, wherein a lower score su indicates a higher probability of pCR, and wherein su is calculated by using the following formula: su = -baseline + WF(ESRl)·REL(ESRl) - WF(MKI67)·REL(MKI67), Where WF(ESR1) is the weight factor of REL(ESR1), and WF(MKI67) is the weight factor of REL(MKI67).

35. The use according to claim 34, wherein a lower score su indicates a higher likelihood of pCR, and wherein su is calculated by using the following formula: su = 10.625 + 0.324·REL(ESRl) - 0.527·REL(MKI67).

36. The use according to any one of claims 31 to 35, further comprising: The predicted probability q of pCR was calculated, where a) If a higher score su indicates a higher probability of pCR, then q is calculated by using the following formula: ;and b) If a lower score su indicates a higher probability of pCR, then q is calculated by using the following formula: ， Here, q equal to or greater than a predefined threshold indicates a high pCR likelihood, and q less than the predefined threshold indicates a low pCR likelihood.

37. The use according to any one of claims 31 to 35, wherein a) if a higher score su indicates a higher likelihood of pCR, a score su equal to or greater than a predefined threshold indicates a high likelihood of pCR, and a score su less than the predefined threshold indicates a low likelihood of pCR; and b) If a lower score su indicates a higher pCR likelihood, a score su less than a predefined threshold indicates a high pCR likelihood, and a score su equal to or greater than the predefined threshold indicates a low pCR likelihood.

38. Use of an agent for detecting the expression level of mRNA of (i) ERBB2, ESR1, PGR and MKI67, (ii) ERBB2, ESR1 and MKI67, or (iii) ESR1 and MKI67 in the preparation of a kit for selecting a breast cancer treatment for a breast cancer patient, wherein the breast cancer treatment is selected by a method comprising the following steps: Calculating an unscaled score (score unscaled, su) based on the relative expression levels of mRNA of (i) ERBB2, ESR1, PGR and MKI67, (ii) ERBB2, ESR1 and MKI67, or (iii) ESR1 and MKI67 in a pre-treatment breast tumor sample of a breast cancer patient as defined in any one of claims 1 and 6 to 10 and 13 or claims 14 and 18 to 23 and 25 or claims 26 and 31 to 35 and 37, and, optionally, a predicted likelihood of pCR q as defined in claim 11 or claim 24 or claim 36, or a clinical score s as defined in any one of claims 12 to 13; and selecting a breast cancer treatment method for a breast cancer patient based on su and, optionally, q or s, a) If a higher score su indicates a higher likelihood of pCR, then - if su and, optionally, q or s, are equal to or greater than a predefined threshold, selecting neoadjuvant chemotherapy; and / or - if su and, optionally, q or s, are less than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy and non-chemotherapy treatment; and b) If a lower score su indicates a higher likelihood of pCR, then - If su and, optionally, s, are less than a predefined threshold, neoadjuvant chemotherapy is selected; - If q is equal to or greater than a predefined threshold, neoadjuvant chemotherapy is chosen; - if su and, optionally, s, are equal to or greater than a predefined threshold, selecting a breast cancer treatment selected from adjuvant chemotherapy and non-chemotherapy treatment; and / or - If q is less than a predefined threshold, then a breast cancer treatment is selected from adjuvant chemotherapy and non-chemotherapy treatment.

39. The use according to claim 38, wherein the non-chemotherapeutic treatment is endocrine therapy.

40. The use according to claim 38, wherein the method further comprises: Prior to calculating su and, optionally, q or s, the relative mRNA expression levels of (i) ERBB2, ESR1, PGR and MKI67, (ii) ERBB2, ESR1 and MKI67, or (iii) ESR1 and MKI67 in pre-treatment breast tumor samples were determined by RT-qPCR.

41. The use according to claim 38 or 40, wherein the neoadjuvant or adjuvant chemotherapy comprises the administration of a taxane.

42. The use according to claim 39, wherein the endocrine therapy is administered in the adjuvant or neoadjuvant setting.

43. The use according to claim 38 or 39, wherein if the breast cancer is ERBB2-positive breast cancer, the neoadjuvant chemotherapy or endocrine therapy is accompanied by the administration of an anti-ERBB2 drug.

44. The use according to any one of claims 38 to 40, wherein the breast cancer is ESR1- and / or PGR-positive breast cancer.

45. Use according to any one of claims 38 to 40, wherein the breast cancer is luminal breast cancer.

46. ​​The use according to any one of claims 1, 14, 26, and 40, wherein the kit comprises: at least one pair of ERBB2-specific primers; At least one pair of ESR1-specific primers; at least one pair of PGR-specific primers; and / or At least one pair of MKI67-specific primers.

47. The use according to claim 46, wherein the kit further comprises at least one ERBB2-specific probe, at least one ESR1-specific probe, at least one PGR-specific probe and / or at least one MKI67-specific probe.

48. Use according to claim 46 or 47, wherein the kit further comprises at least one pair of reference gene-specific primers and, optionally, at least one reference gene-specific probe.

49. The use according to claim 48, wherein the reference gene is selected from B2M, CAFM2, TBP, PUM1, MRFP19, GUSB, RPF37A and CYFIP1.

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