Method for determining prognosis of breast cancer

Abstract

To provide a novel method for determining breast cancer prognosis.SOLUTION: Provided is a method for determining breast cancer prognosis using all of the following 27 gene groups as indicators: ASPM (SEQ ID NO: 1), BCL11A (SEQ ID NO: 2), BF930764 (SEQ ID NO: 3), BIRC5 (SEQ ID NO: 4), C10orf3 (SEQ ID NO: 5), CCNB2 (SEQ ID NO: 6), CDC45 L (SEQ ID NO: 7), CDCA8 (SEQ ID NO: 8), CENPF (SEQ ID NO: 9), FLJ10719 (SEQ ID NO: 10), FLJ11280 (SEQ ID NO: 11) ), FLJ14399 (SEQ ID NO: 12), HIS1 (SEQ ID NO: 13), HSPC150 (SEQ ID NO: 14), KIF2C (SEQ ID NO: 15), LOC51161 (SEQ ID NO: 16), MGC7036 (SEQ ID NO: 17), MKNK2 (SEQ ID NO: 18), PKMYT1 (SEQ ID NO: 19), PLK (SEQ ID NO: 20), PRC1 (SEQ ID NO: 21), PTP4A2 (SEQ ID NO: 22), RPS27 L (SEQ ID NO: 23), STMN1 (SEQ ID NO: 24), SULF2 (SEQ ID NO: 25), TGS (SEQ ID NO: 26), and UBE2C (SEQ ID NO: 27).SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to a method for determining the prognosis of breast cancer. [Background technology]

[0002] Structural mutations in the TP53 gene are known to be an independent prognostic factor for breast cancer, but due to the lack of a simple and reliable diagnostic method, they have not been introduced clinically. The present inventors developed a gene expression profile (TP53 signature) that can predict the presence or absence of loss-of-function mutations in the TP53 gene through comprehensive gene expression analysis and obtained a patent (Patent Document 1). The method described in Patent Document 1 determines the TP53 signature status of a tumor by calculating the correlation coefficient between the gene expression profiles of the TP53 gene mutant and wild-type. Calculating the correlation coefficient requires standardization of tumor gene expression data, which requires expression data from a large number of breast cancer cases for comparison. Due to the need for a large number of cases for comparison, the complexity of the standardization algorithm, and the possibility of excessive data correction due to standardization, we sought to develop a diagnostic method that addresses these issues. As a result, we reported a method that calculates the ratio of the sum of the expression levels of genes whose expression is elevated in TP53 mutants to the sum of the expression levels of genes whose expression is decreased. If the ratio is equal to or above a cutoff value, the tumor is diagnosed as TP53 signature mutant, and if it is below a cutoff value, the tumor is diagnosed as TP53 signature wild-type (Non-Patent Document 1).

[0003] However, this method had issues with diagnostic accuracy in ER-positive patients, Stage I patients, lymph node-negative patients, Grade 1 patients, patients over 50 years of age, and patients with Ki-67≧10%. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 4370409 [Non-patent literature]

[0005] [Non-Patent Document 1] Oncotarget 9: 14193-14206. 2018 Summary of the Invention [Problem to be solved by the invention]

[0006] An objective of the present invention is to provide a new method for determining the prognosis of breast cancer, and a method capable of diagnosing the prognosis with high accuracy, particularly in a group of breast cancer patients with a relatively low risk of recurrence. [Means for solving the problem]

[0007] Under these circumstances, the present inventors have discovered that the above-mentioned problems can be solved in a very simple manner by focusing on a specific gene among the wide variety of genes whose expression levels are affected by the presence or absence of a pathogenic mutation in the TP53 gene, and have thus completed the present invention. Item 1. A method for determining the prognosis of breast cancer using all of the following 27 gene groups as indicators: ASPM (SEQ ID NO: 1) BCL11A (SEQ ID NO: 2) BF930764 (SEQ ID NO: 3) BIRC5 (SEQ ID NO: 4) C10orf3 (SEQ ID NO: 5) CCNB2 (SEQ ID NO: 6) CDC45L (SEQ ID NO: 7) CDCA8 (SEQ ID NO: 8) CENPF (SEQ ID NO: 9) FLJ10719 (SEQ ID NO: 10) FLJ11280 (SEQ ID NO: 11) FLJ14399 (SEQ ID NO: 12) HIS1 (SEQ ID NO: 13) HSPC150 (SEQ ID NO: 14) KIF2C (SEQ ID NO: 15) LOC51161 (SEQ ID NO: 16) MGC7036 (SEQ ID NO: 17) MKNK2 (SEQ ID NO: 18) PKMYT1 (SEQ ID NO: 19) PLK (SEQ ID NO: 20) PRC1 (SEQ ID NO: 21) PTP4A2 (SEQ ID NO: 22) RPS27L (SEQ ID NO: 23) STMN1 (SEQ ID NO: 24) SULF2 (SEQ ID NO: 25) TGS (SEQ ID NO: 26) UBE2C (SEQ ID NO: 27) Item 2. The method according to Item 1, wherein the prognosis is determined to be good when the TP53 signature score calculated by the following formula is less than a cutoff value: TP53 signature score = [sum of logarithms of expression values ​​of gene group A below] / [sum of logarithms of expression values ​​of gene group B below] Genogroup A ASPM (SEQ ID NO: 1) BCL11A (SEQ ID NO: 2) BF930764 (SEQ ID NO: 3) BIRC5 (SEQ ID NO: 4) C10orf3 (SEQ ID NO: 5) CCNB2 (SEQ ID NO: 6) CDC45L (SEQ ID NO: 7) CDCA8 (SEQ ID NO: 8) CENPF (SEQ ID NO: 9) FLJ10719 (SEQ ID NO: 10) HSPC150 (SEQ ID NO: 14) KIF2C (SEQ ID NO: 15) PKMYT1 (SEQ ID NO: 19) PLK (SEQ ID NO: 20) PRC1 (SEQ ID NO: 21) STMN1 (SEQ ID NO: 24) TGS (SEQ ID NO: 26) UBE2C (SEQ ID NO: 27) Genogroup B FLJ11280 (SEQ ID NO: 11) FLJ14399 (SEQ ID NO: 12) HIS1 (SEQ ID NO: 13) LOC51161 (SEQ ID NO: 16) MGC7036 (SEQ ID NO: 17) MKNK2 (SEQ ID NO: 18) PTP4A2 (SEQ ID NO: 22) RPS27L (SEQ ID NO: 23) SULF2 (SEQ ID NO: 25) Item 3. The method according to Item 1 or 2, wherein the group of genes is derived from a sample prepared from breast cancer tissue or breast cancer cells collected from a breast cancer patient. [Effects of the Invention]

[0008] According to the present invention, a novel method for determining the prognosis of breast cancer can be provided. The present invention also provides a method capable of diagnosing the prognosis with high accuracy in a patient group with a relatively low risk of recurrence. [Brief explanation of the drawings]

[0009] [Figure 1] Upper left: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 216 cases of Stage I-II breast cancer. Upper right: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 216 cases of Stage I-II breast cancer. Lower left: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 148 cases of ER-positive breast cancer. Lower right: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 148 cases of ER-positive breast cancer. [Figure 2]Upper left: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 115 Stage I cases. Upper right: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 115 Stage I cases. Lower left: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 154 lymph node-negative cases. Lower right: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 154 lymph node-negative cases. [Figure 3] Upper left: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 55 cases of grade 1. Upper right: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 55 cases of grade 1. Lower left: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 149 cases aged 51 years or older. Lower right: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant type (mt group) in 149 cases aged 51 years or older. [Figure 4]Left: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant group (mt group) in 152 patients with Ki-67 levels of 10% or higher. Right: Graph summarizing the recurrence-free survival rate and survival period for the TP53 signature wild-type group (wt group) and TP53 signature mutant group (mt group) in 152 patients with Ki-67 levels of 10% or higher. DETAILED DESCRIPTION OF THE INVENTION

[0010] The present invention relates to a method for determining the prognosis of breast cancer using a specific group of genes as an index. In the present invention, unless otherwise specified, the term "gene" includes not only structural genes that define the primary structure of proteins, tRNA, rRNA, etc., but also regions on nucleic acids that have specific control functions, such as promoters and operators. Therefore, in the present invention, unless otherwise specified, the term "gene" refers to regulatory regions, coding regions, exons, and introns without distinction. In addition, "structural genes" include genes in which silent mutations have been introduced into the original DNA sequence. In the present invention, the term "gene" also includes nucleic acid molecules such as siRNA that interfere with gene expression.

[0011] As used herein, "nucleic acid" is synonymous with nucleotide, oligonucleotide, and polynucleotide, and may be DNA, RNA, or a DNA-RNA hybrid. These may be double-stranded or single-stranded, and unless otherwise specified, a reference to a nucleic acid molecule having a certain sequence also comprehensively refers to nucleic acid molecules (or nucleotides, oligonucleotides, and polynucleotides) having a complementary sequence. These nucleic acid molecules may be circular or linear, and may be synthetic or of biological origin.

[0012] Method for determining prognosis of breast cancer The present invention provides a method for determining the prognosis of breast cancer using all of the following 27 genes as indicators: ASPM (SEQ ID NO: 1), BCL11A (SEQ ID NO: 2), BF930764 (SEQ ID NO: 3), BIRC5 (SEQ ID NO: 4), and IFN-γ (SEQ ID NO: 5). Sequence number 4), C10orf3 (SEQ ID NO: 5), CCNB2 (SEQ ID NO: 6), CDC45L (SEQ ID NO: 7), CDCA8 (SEQ ID NO: 8), CENPF (SEQ ID NO: 9), FLJ10719 (SEQ ID NO: 10), FLJ11280 (SEQ ID NO: 11), FLJ14399 (SEQ ID NO: 12), HIS1 (SEQ ID NO: 13), HSPC150 (SEQ ID NO: 14) 4), KIF2C (SEQ ID NO: 15), LOC51161 (SEQ ID NO: 16), MGC7036 (SEQ ID NO: 17), MKNK2 (SEQ ID NO: 18), PKMYT1 (SEQ ID NO: 19), PLK (SEQ ID NO: 20), PRC1 (SEQ ID NO: 21), PTP4A2 (SEQ ID NO: 22), RPS27L (SEQ ID NO: 23), STMN1 (SEQ ID NO: 24) , SULF2 (SEQ ID NO: 25), TGS (SEQ ID NO: 26), UBE2C (SEQ ID NO: 27).

[0013] In a typical embodiment of the present invention, the expression level of each of the above genes in a sample collected from a breast cancer patient is measured. Such a biological sample is not particularly limited as long as it contains nucleic acid derived from tumor cells of the breast cancer patient, and examples thereof include breast cancer tumor tissue and breast cancer tumor cells collected from the breast cancer patient. Other examples include breast tissue, nipple secretions, blood, serum, and plasma collected from the breast cancer patient. The method for extracting DNA from these samples is also not particularly limited and can be performed using or based on known methods. The expression level of each gene can be obtained by measuring the mRNA, protein, etc. of each gene, for example, by measuring mRNA as described in the Examples below. The method for measuring mRNA levels is not particularly limited, and examples include RT-quantitative PCR and RNA-Seq. The method for measuring protein levels is not particularly limited, and examples include ELISA and protein arrays. The expression level can also be measured using a reporter gene assay.

[0014] In the present invention, the genes used as prognostic indicators include known genes assigned Genbank Accession Nos. as shown below. More specifically, the base sequences of the cDNA sequences of the genes include those shown in SEQ ID NOs: 1 to 27. The name of each gene, and the correspondence between the Genbank Accession No. and the SEQ ID NO in a typical embodiment are shown in the table below.

[0015] [Table 1]

[0016] In a preferred embodiment, according to the method of the present invention, the 27 genes are divided into two groups, and a TP53 signature score, represented by the following formula, is calculated from the expression level of each gene. When the score is less than the cutoff value, the prognosis can be determined to be good: TP53 signature score = [sum of logarithms of expression values ​​of gene group A below] / [sum of logarithms of expression values ​​of gene group B below] Genogroup A: ASPM, BCL11A, BF930764, BIRC5, C10orf3, CCNB2, CDC45L, CDCA8, CENPF, FLJ10719, HSPC150, KIF2C, PKMYT1, PLK, PRC1, STMN1, TGS, UBE2C Genogroup B: FLJ11280, FLJ14399, HIS1, LOC51161, MGC7036, MKNK2, PTP4A2, RPS27L, SULF2.

[0017] In such an embodiment, the logarithm of the expression value may be, for example, log n [Expression value] can be increased, where n is a preset value, and can be set, for example, within the range of 8≦n≦12, preferably within the range of 9≦n≦11, and typically n=10. In this embodiment, the cutoff value T can be set, for example, in the range of 1.50≦T≦1.80, preferably 1.60≦T≦1.70, and more preferably 1.65≦T≦1.70. In a typical embodiment of the present invention, the cutoff value T can be set to 1.67.

[0018] Furthermore, in a preferred embodiment of the present invention, when the TP53 signature score is equal to or greater than the cutoff value, the prognosis can be determined to be poor.

[0019] According to the present invention, the prognosis of breast cancer patients can be predicted using a method based on the extremely simplified calculation formula described above, and therefore using a very simple method. In a typical embodiment of the present invention, breast cancer patients to be targeted include Stage I-II breast cancer patients. Furthermore, the method of the present invention can be used to predict the prognosis of ER-positive patients and Stage I patients, whose prognosis has been difficult to predict using conventional methods. group, lymph node metastasis negative patient group, Grade 1 patient group, patient group over 50 years old, Ki-67 ≥ 10% This makes it possible to accurately predict the prognosis for this patient group.

[0020] ER (estrogen receptor) positive patients refer to patients in whom staining is observed in the breast cancer tissue by immunohistochemistry using anti-ER antibodies. ER-positive patients have a better prognosis than ER-negative patients, and there are relatively few cases of recurrence. However, as recurrence occurs at a certain frequency, a method that can predict the prognosis of these patients has been eagerly awaited. Stage I patients refer to patients who are judged to be at Stage I according to the criteria set out in the Clinical and Pathological Guidelines for Breast Cancer (Japan Breast Cancer Society) or the TNM classification of the Union for International Cancer Control (UICC). Stage I patients also have a relatively low risk of recurrence, Recurrence is observed at a certain frequency. However, it is difficult to predict the prognosis in patients with a low risk of recurrence, and a method to predict the prognosis for such patients has been desired. Lymph node-negative patients are those in whom swelling of the lymph nodes associated with breast cancer is not found in diagnostic imaging such as CT, MRI, or ultrasound. This refers to patients who do not have lymph node metastasis or patients who have not had lymph node metastasis in the pathological diagnosis of the regional lymph nodes. Although lymph node metastasis-negative patients have a relatively low risk of recurrence, recurrence occurs at a certain frequency, so a method to predict the prognosis of these patients was desired. Grade 1 patients are those who do not meet the criteria for the Nottingham histological grading classification, the classification by Black et al., the classification by Le Doussal et al., and This refers to patients who are judged to be Grade 1 according to the criteria set forth in the nuclear grading classification in the "Guidelines for the Treatment of Breast Cancer." Grade 1 patients also have a relatively low risk of recurrence, but recurrence is observed at a certain frequency. However, it is difficult to predict the prognosis in patients with a low risk of recurrence, and a method for predicting the prognosis for these patients has been desired. Patients over 50 years of age also have a good prognosis compared to patients under 50 years of age, and there are relatively few cases of recurrence. However, recurrence is observed at a certain frequency, and therefore a method for predicting the prognosis for these patients has been desired. Ki-67 ≥ 10% refers to the number of positive cells in breast cancer tissue evaluated by immunohistochemistry using an antibody against the KI67 (MKI67) protein. Patients with Ki-67 ≥ 10% are at a relatively high risk of recurrence. Since this is a high-risk patient group, a method for predicting the prognosis of these patients has been desired. Therefore, the method of the present invention meets this demand and is very useful. Therefore, the present invention provides a method for determining the prognosis of breast cancer in ER-positive patients, a method for predicting the prognosis of breast cancer in Stage I breast cancer patients, and a method for predicting the prognosis of breast cancer in ER-positive patients. The present invention provides a method for determining the prognosis of breast cancer in patients with lymph node metastasis negative, a method for determining the prognosis of breast cancer in patients with Grade 1 breast cancer, a method for determining the prognosis of breast cancer in patients over 50 years of age, and a method for determining the prognosis of breast cancer in patients with Ki-67≧10%. The method of the present invention is applicable to ER-positive patients, Stage I patients, lymph node-negative patients, and Grade 1 patients. It is possible to diagnose the prognosis with high accuracy in patient groups with a relatively low risk of recurrence, such as patient groups with a low risk of recurrence, such as those with a high risk of recurrence, or those over 50 years of age. Since it has been difficult to predict the prognosis in patient groups with a low risk of recurrence, the present invention is effective because it can predict the prognosis of such patient groups, which has been difficult to predict.

[0021] Furthermore, as mentioned above, the present invention makes it possible to predict the prognosis of breast cancer patients. Generally, in cancers, those with high cell proliferation capacity (cells that are more likely to grow) tend to have a poor prognosis. Therefore, it is expected that cancer cells of patients judged to have a poor prognosis by the method of the present invention have a relatively high cell proliferation capacity. On the other hand, anticancer drugs generally inhibit DNA damage that occurs during cell proliferation. It inhibits replication of the virus and suppresses proteins that affect cell division, causing cell death. This causes the TP53 signature score to increase. Therefore, cells with high cell proliferation ability have the property that anticancer drugs are more effective against them. Therefore, the method of the present invention can also determine the sensitivity of breast cancer patients to treatment with anticancer drugs that act particularly on cell proliferation or cell division. A specific method can be performed in accordance with the prognosis prediction method for breast cancer patients. For example, if the TP53 signature score is equal to or greater than the cutoff value, the breast cancer patient can be determined to be sensitive to the anticancer drug treatment. Alternatively, for example, if the TP53 signature score is less than the cutoff value, the breast cancer patient can be determined to have low sensitivity to the anticancer drug treatment. If the TP53 signature score is above the cutoff value, the disease progresses rapidly and the prognosis is generally poor. However, when chemotherapy is administered, especially with anticancer drugs that act on cell proliferation or cell division, the rate of pathological complete response (pCR) is expected to be significantly higher than when the score is below the cutoff value. Therefore, when the TP53 signature score is above the cutoff value, the rate of achieving pCR is expected to be significantly higher. On the other hand, if the TP53 signature score is below the cutoff value, a treatment strategy of early surgery without preoperative chemotherapy can be selected.

[0022] In the present invention, breast cancer treatments include surgical therapy, drug therapy, radiation therapy, etc. Drug therapies for breast cancer are not particularly limited, and include hormone therapy, chemotherapy, molecular targeted drug therapy, and combinations thereof. Drugs used in hormone therapy are not particularly limited, and examples include antiestrogens such as tamoxifen, toremifene, fulvestrant, and raloxifene, and aromatase inhibitors such as anastrozole, letrozole, and exemestane. Drugs used in chemotherapy are not particularly limited, and examples include doxorubicin, cyclophosphamide, paclitaxel, and docetaxel. Molecular targeted drugs are also not particularly limited, and examples include anti-HER2 agents such as trastuzumab, pertuzumab, and lapatinib, CDK4 / 6 inhibitors such as palbociclib and abemaciclib, PARP inhibitors such as olaparib, and immune checkpoint inhibitors such as atezolizumab.

[0023] In the present invention, the "method for determining the prognosis of breast cancer using all 27 gene groups as indicators" includes not only methods that use only the above 27 genes as indicators, but also methods that use a gene group that adds one or several genes (e.g., 1 gene, 2 genes, 3 genes, 4 genes) to the 27 genes as indicators, as long as the effects of the present invention are obtained (as long as the conclusion is not changed).

[0024] According to the present invention, by using the above 27 genes as indicators, ANAPC7 (SEQ ID NO: 28), PTTG1 (SEQ ID NO: 29), CENPE (SEQ ID NO: 30), MUTYH (SEQ ID NO: 31), MGC45866 ( SEQ ID NO: 32), MAPREL (SEQ ID NO: 33), TMSNB (SEQ ID NO: 34), TTC12 (SEQ ID NO: 35), HCAP-G (SEQ ID NO: 36), CEAL1 (SEQ ID NO: 37), FLJ33962 (SEQ ID NO: 38), GMNN (SEQ ID NO: 39), ENST00000332343 (SEQ ID NO: 40), HEC (SEQ ID NO: 41), GMPR2 (SEQ ID NO: 42), TncRNA (SEQ ID NO: 43), SMOC2 (SEQ ID NO: 44), DNAJC9 (SEQ ID NO: No. 45), RAD54B (SEQ ID NO: 46), CKS2 (SEQ ID NO: 47), I_960269 (SEQ ID NO: 48), BAG1 (SEQ ID NO: 49), AL137566 (SEQ ID NO: 50), BRRN1 (SEQ ID NO: 51), CDC2 ( SEQ ID NO: 52), ZF (SEQ ID NO: 53), THC1577090 (SEQ ID NO: 54), CDKN2C (SEQ ID NO: 55), I_1842252 (SEQ ID NO: 56), SDOS (SEQ ID NO: 57), SNAPC2 (SEQ ID NO: 58) , EVI2A (SEQ ID NO: 59), V4b (SEQ ID NO: 60), BC007934 (SEQ ID NO: 61), ECT2 (SEQ ID NO: 62), RAD21 (SEQ ID NO: 63), MCM7 (SEQ ID NO: 64), AK097469 (SEQ ID NO: 6 5), MGC39900 (SEQ ID NO: 66), FLJ21439 (SEQ ID NO: 67), STATIP1 (SEQ ID NO: 68 ), DKFZp434L142 (SEQ ID NO: 69), and PLAT (SEQ ID NO: 70) can be used as indicators to determine the prognosis of breast cancer.

[0025] Breast cancer prognosis kit The present invention relates to a nucleic acid comprising at least a part of the base sequence of any of the genes in Table 1. The kit of the present invention can be configured appropriately depending on the method, means, etc. for measuring the expression level of each of the above-mentioned genes. For example, the length of a nucleic acid consisting of at least a part of the base sequence of any gene in Table 1 included in the kit of the present invention can be several tens of base pairs, and the specific part (base sequence) can be easily obtained from various databases, such as the database listed in Table 1 (Genbank). Those skilled in the art can prepare them appropriately based on the above. Furthermore, they can be used in the form of probes for DNA chips or Northern blotting, primers for PCR, etc., depending on the method for measuring the expression level of each gene. Furthermore, if necessary, the polynucleotides or oligonucleotides may be labeled with an appropriate labeling substance such as a radioactive substance, a fluorescent substance, or a dye.

[0026] The kit may optionally contain other elements or components, such as various reagents, enzymes, buffer solutions, reaction plates (containers), and the like. [Example]

[0027] Prognostic prediction of TP53 signature in 216 cases of stage I-II breast cancer Formalin-fixed paraformaldehyde-treated breast cancer tissues from 216 patients with Stage I-II breast cancer were analyzed. Total RNA was extracted from FFPE tissues and analyzed using nCounter (NanoString). Gene expression analysis was performed.

[0028] The expression levels of 27 genes constituting the TP53 signature (gene group A: ASPM, BCL11A, BF930764, BIRC5, C10orf3, CCNB2, CDC45L, CDCA8, CENPF, FLJ10719, HSPC150, KIF2C, PKMYT1, PLK, PRC1, STMN1, TGS, UBE2C; gene group B: FLJ11280, FLJ14399, HIS1, LOC51161, MGC7036, MKNK2, PTP4A2, RPS27L, SULF2) were measured, and the TP53 signature score was calculated from the log10 value of the obtained expression values. That is, in this example, the TP53 signature score was calculated as follows: TP53 signature score = [log10 sum of expression values ​​of gene group A below] / [log10 sum of expression values ​​of gene group B below]

[0029] Of the 216 cases, those with a TP53 signature score of 1.67 or higher were classified as TP53 signature mutant, and those with a score of less than 1.67 were classified as TP53 signature wild type.

[0030] As a result, 99 cases were TP53 signature mutation type and 117 cases were wild type, respectively. The graph above shows the recurrence-free survival rate and survival time for the TP53 signature wild-type group (wt group) and the TP53 signature mutant group (mt group). As shown in the upper left of Figure 1, the TP53 signature mutant group had a significantly poorer prognosis (recurrence-free survival time) than the wild-type group (P = 0.0044). In this example, the above method using TP53 signature as an index may be simply referred to as the "method of the example."

[0031] Univariate analysis of recurrence-free survival time using a Cox proportional hazards model for clinicopathological patient background factors and TP53 signature for breast cancer revealed that stage, presence or absence of lymph node metastasis, and TP53 signature were significantly associated with recurrence-free survival time. A multivariate analysis was performed using the Cox proportional hazards model using only the factors that were found to be associated with recurrence-free survival in the univariate analysis. The TP53 signature was significantly associated with recurrence-free survival (hazard ratio 3.44, P=0.047). These results demonstrate that the TP53 signature is a predictor of recurrence-free survival.

[0032] [Table 2]

[0033] Next, the above 216 cases were diagnosed using the method described in Non-Patent Document 1. The gene groups whose expression levels are elevated in TP53 gene mutants (gene group C: ANAPC, ASPM, BCL11A, BF930764, BIRC5, C10orf3, CCNB2, CDC45L, CDCA8, CENPE, CENPF, FLJ10719, HSPC150, KIF2C, MAPR1, MGC45866, MUTYH, PKMYT1, PLK, PRC1, STMN1, TGS, UBE2C; gene group D: FLJ11280, FLJ14399, HIS1, LOC51161, MGC7036, MKNK2, PTP4A2, RPS27L, SULF2) were identified. The ratio of the sum of expression levels of the genes whose expression levels are decreased to the sum of expression levels of the genes whose expression levels are decreased ([sum of expression values ​​of gene group C] / [sum of expression values ​​of gene group D]) was calculated. In the present specification, [sum of expression values ​​of gene group C] / [sum of expression values ​​of gene group D] is referred to as TP53 signature'. In this method, when the ratio of the sum of expression levels of gene group C to gene group D was equal to or greater than the cutoff value of 0.78, the patient was diagnosed as TP53 signature' mutant, and when it was less than 0.78, the patient was diagnosed as TP53 signature' wild type. In this example, the above method using TP53 signature' as an index may be simply referred to as "Oncotarget diagnostic method." As shown in Figure 1, upper right, the TP53 signature' mutant also had a significantly poorer prognosis (recurrence-free survival period) compared to the wild type (P=0.033), but as mentioned above, the predictability of prognosis was poorer compared to the method of the example using TP53 signature (Figure 1, upper left, P=0.0044). Ta.

[0034] Next, we compared the recurrence-free survival time between the TP53 signature mutation group and the wild-type group for 148 ER-positive cases out of 216 cases of Stage I-II breast cancer. There were 53 cases of TP53 signature mutation and 108 cases of wild-type, respectively. The results are shown in Figure 1, bottom left. The TP53 signature mutation group showed a significantly longer recurrence-free survival time compared to the wild-type group. The prognosis (recurrence-free survival) was significantly worse in 148 patients with ER-positive tumors (P = 0.0239). Oncotarget diagnostics was performed on these cases, and no significant difference in prognosis (recurrence-free survival) was found between TP53 signature mutations and wild-type (Figure 1, bottom right, P=0.073).

[0035] Of the 216 cases of Stage I-II breast cancer, 115 cases of Stage I were classified as TP53 signature mutation group and The recurrence-free survival period was compared between the TP53 signature mutation and wild-type groups. The results are shown in Figure 2, upper left. There were 48 and 67 cases of TP53 signature mutation and wild-type, respectively. The TP53 signature mutation had a significantly poorer prognosis (recurrence-free survival period) than the wild-type (P = 0.0239). In contrast, when the Oncotarget diagnostic method was used on 115 Stage I cases, there was no significant difference in prognosis (recurrence-free survival period) between the TP53 signature mutation and wild-type (Figure 2, upper right, P = 0.44).

[0036] Of 216 cases of stage I-II breast cancer, 154 cases with negative lymph node metastasis were targeted, and the recurrence-free survival time was compared between the TP53 signature mutation group and the wild-type group. There were 66 cases of TP53 signature mutation and 88 cases of wild-type, respectively. The results are shown in Figure 2, bottom left. The TP53 signature mutation type had a significantly poorer prognosis (recurrence-free survival time) than the wild-type (P=0.018). In contrast, the prognosis of the TP53 signature mutation type was significantly poorer than that of the wild-type (P=0.018). Oncotarget diagnostics was performed on 154 metastasis-negative cases, and TP53 signature mutations were identified. There was no significant difference in prognosis (recurrence-free survival period) between the wild-type and control groups (Figure 2, bottom right, P=0.17).

[0037] Of 216 cases of Stage I-II breast cancer, 55 cases of Grade 1 were included in the TP53 signature mutation group. The recurrence-free survival period was compared between the TP53 signature mutation and wild-type groups. There were 11 and 44 cases of TP53 signature mutation, respectively. The results are shown in Figure 3, upper left. The TP53 signature mutation had a significantly worse prognosis (recurrence-free survival period) than the wild-type (P = 0.0002). In contrast, when the Oncotarget diagnostic method was used on 55 grade 1 cases, there was no significant difference in prognosis (recurrence-free survival period) between the TP53 signature mutation and wild-type (Figure 3, upper right, P = 0.091).

[0038] Of 216 cases of stage I-II breast cancer, 149 patients aged 51 years or older were included, and the recurrence-free survival period was compared between the TP53 signature mutation group and the wild-type group. There were 74 and 75 TP53 signature mutation and wild-type cases, respectively. The results are shown in Figure 3, bottom left. The TP53 signature mutation group had a significantly worse prognosis (recurrence-free survival period) than the wild-type group (P = 0.018).

[0039] Of 216 cases of stage I-II breast cancer, 152 cases with Ki-67 of 10% or higher were screened for TP53 signature mutations. The recurrence-free survival period was compared between the variant group and the wild-type group. There were 92 cases of TP53 signature mutation and 60 cases of wild-type, respectively. The results are shown in Figure 4, left. The TP53 signature mutation had a significantly poorer prognosis (recurrence-free survival period) compared with the wild-type (P = 0.017). In contrast, the Oncotarget diagnostic method was performed on 152 cases with Ki-67 of 10% or higher, and the results showed that the TP53 signature mutation and wild-type There was no significant difference in prognosis (recurrence-free survival) between the two types (Figure 4, right, P = 0.059).

Claims

1. A method for determining the sensitivity of a breast cancer patient to treatment with an anticancer drug having an action point related to cell proliferation or cell division, using all of the following 27 gene groups as indicators: ASPM (SEQ ID NO: 1) BCL11A (SEQ ID NO: 2) BF930764 (SEQ ID NO: 3) BIRC5 (SEQ ID NO: 4) C10orf3 (SEQ ID NO: 5) CCNB2 (SEQ ID NO: 6) CDC45L (SEQ ID NO: 7) CDCA8 (SEQ ID NO: 8) CENPF (SEQ ID NO: 9) FLJ10719 (SEQ ID NO: 10) FLJ11280 (SEQ ID NO: 11) FLJ14399 (SEQ ID NO: 12) HIS1 (SEQ ID NO: 13) HSPC150 (SEQ ID NO: 14) KIF2C (SEQ ID NO: 15) LOC51161 (SEQ ID NO: 16) MGC7036 (SEQ ID NO: 17) MKNK2 (SEQ ID NO: 18) PKMYT1 (SEQ ID NO: 19) PLK (SEQ ID NO: 20) PRC1 (SEQ ID NO: 21) PTP4A2 (SEQ ID NO: 22) RPS27L (SEQ ID NO: 23) STMN1 (SEQ ID NO: 24) SULF2 (SEQ ID NO: 25) TGS (SEQ ID NO: 26) UBE2C (SEQ ID NO: 27) Measuring the expression levels of the following gene group A and gene group B in a sample collected from a breast cancer patient; A method comprising a step of determining that a breast cancer patient is sensitive to an anticancer drug treatment having an action point related to cell proliferation or cell division when the TP53 signature score calculated by the following formula is equal to or greater than a cutoff value: TP53 signature score = [sum of logarithms of expression values ​​of gene group A below] / [sum of logarithms of expression values ​​of gene group B below] Gene group A ASPM (SEQ ID NO: 1) BCL11A (SEQ ID NO: 2) BF930764 (SEQ ID NO: 3) BIRC5 (SEQ ID NO: 4) C10orf3 (SEQ ID NO: 5) CCNB2 (SEQ ID NO: 6) CDC45L (SEQ ID NO: 7) CDCA8 (SEQ ID NO: 8) CENPF (SEQ ID NO: 9) FLJ10719 (SEQ ID NO: 10) HSPC150 (SEQ ID NO: 14) KIF2C (SEQ ID NO: 15) PKMYT1 (SEQ ID NO: 19) PLK (SEQ ID NO: 20) PRC1 (SEQ ID NO: 21) STMN1 (SEQ ID NO: 24) TGS (SEQ ID NO: 26) UBE2C (SEQ ID NO: 27) Gene group B FLJ11280 (SEQ ID NO: 11) FLJ14399 (SEQ ID NO: 12) HIS1 (SEQ ID NO: 13) LOC51161 (SEQ ID NO: 16) MGC7036 (SEQ ID NO: 17) MKNK2 (SEQ ID NO: 18) PTP4A2 (SEQ ID NO: 22) RPS27L (SEQ ID NO: 23) SULF2 (SEQ ID NO: 25).

2. The method according to claim 1, wherein the group of genes is derived from a sample prepared from breast cancer tissue or breast cancer cells collected from a breast cancer patient.

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