JP7587251B2 - Method for determining prognosis of breast cancer - Google Patents

Description

The present invention relates to a method for determining the prognosis of breast cancer.

Although structural mutations in the TP53 gene are known as an independent prognostic factor for breast cancer, they have not been introduced into clinical practice due to the lack of a simple and reliable diagnostic method. The present inventors have developed a gene expression profile (TP53 signature) that can predict the presence or absence of loss-of-function mutations in the TP53 gene by comprehensive gene expression analysis, and obtained a patent for it (Patent Document 1). In the method described in Patent Document 1, the TP53 signature status of a tumor is determined by calculating a correlation coefficient between the gene expression profiles of the TP53 gene mutant and wild type. In order to calculate the correlation coefficient, it is necessary to standardize the gene expression data of the tumor, and expression data of a large number of breast cancer cases to be compared are required for standardization. Since a large number of cases to be compared are required, the standardization algorithm is complicated, and there is a possibility that excessive data correction may occur due to standardization, a diagnostic method that improves these points was investigated. As a result, a method was reported in which the ratio of the sum of the expression levels of genes whose expression is increased in the TP53 gene mutant type to the sum of the expression levels of genes whose expression is decreased is calculated, and a diagnosis of TP53 signature mutant type is made when the ratio is equal to or greater than the cutoff value, and TP53 signature wild type is made when the ratio is equal to or less than the cutoff value (Non-Patent Document 1).

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%.

Patent No. 4370409

Oncotarget 9: 14193-14206. 2018

The present invention aims to provide a new method for determining the prognosis of breast cancer. In addition, the present invention aims to provide a method that can diagnose the prognosis with high accuracy, particularly in a group of breast cancer patients with a relatively low risk of recurrence.

Under such circumstances, the present inventors have found 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 pathological mutation in the TP53 gene, and have thus completed the present invention. Accordingly, the present invention provides the following:
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 judged 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]
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)
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.

The present invention provides a new method for determining the prognosis of breast cancer. The present invention also provides a method for diagnosing the prognosis with high accuracy in a patient group with a relatively low risk of recurrence.

Top left: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature wild type group (wt group) and the TP53 signature mutant type (mt group) for 216 cases of Stage I-II breast cancer. Top right: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature' wild type group (wt group) and the TP53 signature' mutant type (mt group) for 216 cases of Stage I-II breast cancer. Bottom left: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature wild type group (wt group) and the TP53 signature' mutant type (mt group) for 148 cases of ER positive. Bottom right: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature' wild type group (wt group) and the TP53 signature' mutant type (mt group) for 148 cases of ER positive. Upper left: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature wild type group (wt group) and the TP53 signature mutant type (mt group) for 115 Stage I cases. Upper right: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature' wild type group (wt group) and the TP53 signature' mutant type (mt group) for 115 Stage I cases. Lower left: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature wild type group (wt group) and the TP53 signature' mutant type (mt group) for 154 cases with negative lymph node metastasis. Lower right: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature' wild type group (wt group) and the TP53 signature' mutant type (mt group) for 154 cases with negative lymph node metastasis. Upper left: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature wild type group (wt group) and the TP53 signature mutant type (mt group) for 55 cases of grade 1. Upper right: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature' wild type group (wt group) and the TP53 signature' mutant type (mt group) for 55 cases of grade 1. Lower left: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature wild type group (wt group) and the TP53 signature' mutant type (mt group) for 149 cases aged 51 years or older. Lower right: A graph summarizing the recurrence-free survival rate and survival time of the TP53 signature' wild type group (wt group) and the TP53 signature' mutant type (mt group) for 149 cases aged 51 years or older. Left: A graph summarizing the recurrence-free survival rate and survival time for the TP53 signature wild type group (wt group) and the TP53 signature mutant type (mt group) in 152 patients with Ki-67 of 10% or more. Right: A graph summarizing the recurrence-free survival rate and survival time for the TP53 signature' wild type group (wt group) and the TP53 signature' mutant type (mt group) in 152 patients with Ki-67 of 10% or more.

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, 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, unless otherwise specified. Therefore, in the present invention, the term "gene" refers to regulatory regions, coding regions, exons, and introns without distinction, unless otherwise specified. In addition, "structural genes" also include silent DNA in which silent mutations have been made in the original DNA sequence. In addition, in the present invention, nucleic acid molecules such as siRNA that interfere with gene expression are also included in "genes".

In this specification, "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 is intended to comprehensively refer to a nucleic acid molecule (or nucleotide, oligonucleotide, and polynucleotide) having a complementary sequence. These nucleic acid molecules may be circular or linear, and may be synthetic or of biological origin.

The present invention provides a method for determining the prognosis of breast cancer , which uses 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), and FLJ14399 (SEQ ID NO: 12). No. 12), HIS1 (sequence number 13), HSPC150 (sequence number 14), KIF2C (sequence number 15), LOC51161 (sequence number 16), MGC7036 (sequence number 17), MKNK2 (sequence number 18), PKMYT1 (sequence number 19), PLK (sequence number 20), PRC1 (sequence number 21), PTP4A2 (sequence number 22), RPS27L (sequence number 23), STMN1 (sequence number 24), SULF2 (sequence number 25), TGS (sequence number 26), UBE2C (sequence number 27).

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 the tumor cells of a breast cancer patient, and examples thereof include breast cancer tumor tissue and breast cancer tumor cells collected from the breast cancer patient. Examples of the biological sample include breast tissue, nipple secretions, blood, serum, plasma, and the like collected from the breast cancer patient. The method of extracting DNA from these samples is also not particularly limited, and can be performed using or based on a known method. The expression level of each gene can be obtained by measuring the mRNA, protein, and the like of each gene, and can be obtained, for example, by measuring the mRNA as in the examples described below. The method of measuring the amount of mRNA is not particularly limited, and examples of the method include RT-quantitative PCR, RNA-Seq, and the like. The method of measuring protein is not particularly limited, and examples of the method include ELISA, protein array, and the like. The expression level can also be measured using a reporter gene assay.

In the present invention, the genes used as prognostic indicators include known genes to which a Genbank Accession No. is assigned, 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.

In a preferred embodiment, according to the method of the present invention, the 27 genes are divided into two groups, and the 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 is judged 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]
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.

In such an embodiment, the logarithm of the expression value can be, for example, log _n [expression value], where n is a preset value, for example, set 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 may be set, for example, in the range of 1.50≦T≦1.80, preferably in the range of 1.60≦T≦1.70, and more preferably in the range of 1.65≦T≦1.70. In a typical embodiment of the present invention, the cutoff value T may be set to 1.67.

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

According to the present invention, the prognosis of breast cancer patients can be predicted using a method based on the extremely simplified calculation formula as described above, and therefore using a very easy method. In a typical embodiment of the present invention, examples of breast cancer patients that are the subject of the present invention include Stage I-II breast cancer patients. Furthermore, the method of the present invention makes it possible to accurately predict the prognosis of 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%, whose prognosis was difficult to predict using conventional methods.

ER (estrogen receptor) positive patients refer to patients in whom staining is observed by immunohistochemistry using anti-ER antibodies in breast cancer tissue. ER positive patients have a better prognosis than ER negative patients, and there are relatively few cases of recurrence. However, recurrence occurs at a certain frequency, so a method to predict the prognosis of these patients has been eagerly awaited. Stage I patients refer to patients who are judged to be Stage I according to the criteria described 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, but recurrence occurs at a certain frequency. However, it is difficult to predict the prognosis of patients with a low risk of recurrence, so a method to predict the prognosis of these patients has been eagerly awaited. Lymph node metastasis negative patients refer to patients in whom swelling of the regional lymph nodes of breast cancer is not observed by imaging diagnosis such as CT, MRI, and ultrasound, or patients in whom lymph node metastasis is not observed in pathological diagnosis of the regional lymph nodes. Although the risk of recurrence is relatively low in patients with negative lymph node metastasis, recurrence occurs at a certain frequency, and therefore a method for predicting the prognosis of such patients has been desired. Grade 1 patients refer to patients who are judged to be Grade 1 according to the criteria described in the Nottingham histological grading classification, the classification by Black et al., the classification by Le Doussal et al., and the nuclear grading classification in the "Breast Cancer Treatment Guidelines." Grade 1 patients also have a relatively low risk of recurrence, but recurrence occurs at a certain frequency. However, it is difficult to predict the prognosis of patients with a low risk of recurrence, and therefore a method for predicting the prognosis of such patients has been desired. In addition, 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 occurs at a certain frequency, and therefore a method for predicting the prognosis of such patients has been desired. Group, Ki-67 ≧ 10% refers to patients in whom the ratio of positive cells to the number of cells evaluated by immunohistochemistry using an antibody against KI67 (MKI67) protein in breast cancer tissue is 10% or more. Patients with Ki-67≧10% are a group of patients with a relatively high risk of recurrence, and therefore a method capable of predicting the prognosis of such patients has been desired. Therefore, the method of the present invention meets such a 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 determining the prognosis of breast cancer in Stage I breast cancer patients, a method for determining the prognosis of breast cancer in patients with negative lymph node metastasis, a method for determining the prognosis of breast cancer in Grade 1 breast cancer patients, 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%. As described above, the method of the present invention can diagnose the prognosis with high accuracy in patient groups with a relatively low risk of recurrence, such as ER-positive patient groups, Stage I patient groups, lymph node-negative patient groups, Grade 1 patient groups, and patient groups over 50 years of age. Since it was 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 that were difficult to predict.

Also, as described above, according to the present invention, the prognosis of a breast cancer patient can be predicted. In general, in cancer, the higher the cell proliferation ability (the easier the cells grow), the more likely the prognosis is to be poor. Therefore, it is expected that the cancer cells of a patient whose prognosis is determined to be poor by the method of the present invention have a relatively high cell proliferation ability. On the other hand, anticancer drugs generally cause cell death by inhibiting DNA replication that occurs during cell proliferation or by suppressing proteins that work on cell division. Therefore, cells with high cell proliferation ability have the property that anticancer drugs are more effective against them. Therefore, according to the method of the present invention, it is also possible to determine the sensitivity of a breast cancer patient to treatment with an anticancer drug that has a site of action related to cell proliferation or cell division. A specific method can be performed in accordance with the method for predicting the prognosis of a breast cancer patient, and for example, when 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 above-mentioned anticancer drug treatment. Also, for example, when the TP53 signature score is less than the cutoff value, the breast cancer patient can be determined to be less sensitive to the above-mentioned anticancer drug treatment.
When the TP53 signature score is equal to or higher than the cutoff value, the disease progresses quickly and the prognosis is generally poor. However, when chemotherapy, especially treatment with anticancer drugs that act on cell proliferation or cell division, is performed, 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 equal to or higher than the cutoff value, it is possible to select a treatment strategy in which preoperative chemotherapy is actively performed to obtain pCR. On the other hand, when the TP53 signature score is below the cutoff value, it is possible to select a treatment strategy in which surgery is performed early without preoperative chemotherapy.

In the present invention, examples of breast cancer treatment include surgical therapy, drug therapy, and radiation therapy. In the present invention, drug therapy for breast cancer is not particularly limited, and examples include hormone therapy, chemotherapy, therapy using molecular targeted drugs, and combinations thereof. Drugs used in hormone therapy are not particularly limited, and examples include anti-estrogens 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.

In the present invention, the "method of determining the prognosis of breast cancer using all 27 types of 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 does not change).

According to the present invention, by using the above 27 genes as indicators, it is possible to detect 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), MAPREL1 (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: 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: 65), 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 to determine the prognosis of breast cancer without using them as indicators.

The present invention provides a kit for use in the method of the present invention, which contains a nucleic acid consisting of at least a part of the base sequence of any of the genes in Table 1. The kit of the present invention can be appropriately configured depending on the method, means, etc. for measuring the expression level of each of the above genes. For example, the length of the nucleic acid consisting of at least a part of the base sequence of any of the genes in Table 1 contained in the kit of the present invention can be several tens of base pairs, and the specific part (base sequence) can be appropriately prepared by a person skilled in the art based on information that can be easily obtained from various databases such as the database (Genbank) listed in Table 1. In addition, they can be used in the form of a DNA chip or a probe in Northern blotting, a primer in PCR, etc., depending on the method for measuring the expression level of each gene. Furthermore, if necessary, the polynucleotide or oligonucleotide may be labeled with an appropriate labeling substance such as a radioactive substance, a fluorescent substance, or a dye.

The above kit may optionally contain other elements or components, such as various reagents, enzymes, buffer solutions, reaction plates (containers), etc.

Prognostic prediction of TP53 signature in 216 cases of stage I-II breast cancer
Total RNA was extracted from formalin-fixed, paraffin-embedded (FFPE) tissues of breast cancer tumors surgically removed from 216 cases of stage I-II breast cancer, and gene expression analysis was performed using nCounter (NanoString).

The expression values 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 value. That is, in this embodiment, 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]

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

As a result, there were 99 cases of TP53 signature mutation and 117 cases of wild type, respectively. The upper left of Figure 1 shows a graph summarizing the recurrence-free survival rate and survival period of the TP53 signature wild type group (wt group) and the TP53 signature mutation type (mt group). As shown in the upper left of Figure 1, the TP53 signature mutation type had a significantly poorer prognosis (recurrence-free survival period) compared to the wild type (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."

A univariate analysis was performed using the Cox proportional hazards model for recurrence-free survival with respect to clinical pathological patient background factors and TP53 signature for breast cancer. The results showed that stage, the presence or absence of lymph node metastasis, and TP53 signature were significantly associated with recurrence-free survival. Ki-67 showed a tendency to be associated with recurrence-free survival. A multivariate analysis was performed using the Cox proportional hazards model using only factors that were associated with recurrence-free survival in the univariate analysis. The results showed that TP53 signature alone was significantly associated with recurrence-free survival (hazard ratio 3.44, P=0.047). These results demonstrated that TP53 signature is a predictor of recurrence-free survival.

Next, the above 216 cases were diagnosed using the method described in non-patent literature 1. Specifically, the ratio of the sum of the expression levels of the genes whose expression is increased in the TP53 gene mutant type (gene group C: ANAPC, ASPM, BCL11A, BF930764, BIRC5, C10orf3, CCNB2, CDC45L, CDCA8, CENPE, CENPF, FLJ10719, HSPC150, KIF2C, MAPREL1, MGC45866, MUTYH, PKMYT1, PLK, PRC1, STMN1, TGS, UBE2C, gene group D: FLJ11280, FLJ14399, HIS1, LOC51161, MGC7036, MKNK2, PTP4A2, RPS27L, SULF2) to the sum of the expression levels of the genes whose expression is decreased ([sum of the expression values of the above gene group C] / [sum of the expression values of the above gene group D]) was calculated. In this specification, [the sum of the expression values of the above gene group C] / [the sum of the expression values of the above gene group D] is referred to as TP53 signature'. In this method, when the ratio of the sum of the expression levels of the above gene group C and gene group D is 0.78 or more, the cutoff value is diagnosed as TP53 signature' mutant type, and when it is below 0.78, the TP53 signature' wild type is diagnosed. In this embodiment, the above method using TP53 signature' as an index may be simply referred to as "Oncotarget diagnostic method". As shown in the upper right of Figure 1, the TP53 signature' mutant type also had a significantly poorer prognosis (recurrence-free survival period) than the wild type (P = 0.033), but as described above, the predictability of prognosis was poorer than that of the method of the embodiment using TP53 signature (Figure 1, upper left, P = 0.0044).

Next, of the 216 cases of Stage I-II breast cancer, 148 ER-positive cases were compared for the recurrence-free survival period between the TP53 signature mutation group and the wild type group. There were 53 TP53 signature mutations and 108 wild type cases, respectively. The results are shown in Figure 1, bottom left. The TP53 signature mutation type had a significantly poorer prognosis (recurrence-free survival period) than the wild type (P = 0.0239). In contrast, the results of performing the Oncotarget diagnostic method on 148 ER-positive cases showed no significant difference in prognosis (recurrence-free survival period) between the TP53 signature mutation type and the wild type (Figure 1, bottom right, P = 0.073)

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

Of 216 cases of stage I-II breast cancer, 154 cases with negative lymph node metastasis were compared for recurrence-free survival 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) than the wild type (P = 0.018). In contrast, when the Oncotarget diagnostic method was performed on 154 cases with negative lymph node metastasis, there was no significant difference in prognosis (recurrence-free survival) between the TP53 signature mutation type and the wild type (Figure 2, bottom right, P = 0.17).

Of 216 cases of stage I-II breast cancer, 55 grade 1 cases were targeted and the recurrence-free survival time was compared between the TP53 signature mutation group and the wild type group. There were 11 TP53 signature mutations and 44 wild type cases, respectively. The results are shown in Figure 3, upper left. The TP53 signature mutation type had a significantly poorer prognosis (recurrence-free survival time) than the wild type (P = 0.0002). In contrast, when the Oncotarget diagnostic method was performed on 55 grade 1 cases, there was no significant difference in prognosis (recurrence-free survival time) between the TP53 signature' mutation type and the wild type (Figure 3, upper right, P = 0.091).

Of 216 cases of stage I-II breast cancer, 149 cases aged 51 years or older were included, and the recurrence-free survival time 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 the lower left of Figure 3. The TP53 signature mutation type had a significantly worse prognosis (recurrence-free survival time) than the wild type (P=0.018).

Of 216 cases of stage I-II breast cancer, 152 cases with Ki-67 of 10% or more were included, and the recurrence-free survival time was compared between the TP53 signature mutation group and the wild type group. There were 92 TP53 signature mutations and 60 wild type cases, respectively. The results are shown in Figure 4, left. The TP53 signature mutations had a significantly poorer prognosis (recurrence-free survival time) than the wild type (P = 0.017). In contrast, when the Oncotarget diagnostic method was performed on 152 cases with Ki-67 of 10% or more, there was no significant difference in prognosis (recurrence-free survival time) between the TP53 signature mutations and the wild type (Figure 4, right, P = 0.059).

Claims (2)

A method for determining 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)
Measuring the expression levels of the following gene group A and gene group B in a sample collected from a breast cancer patient;
The method includes a step of determining that the prognosis is 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]
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)
In the above step, "determining that the prognosis is good" means determining that the recurrence-free survival rate is high. 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 taken from a breast cancer patient.

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