JP7818855B2 - Method for determining prognosis of breast cancer - Google Patents

Description

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

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 for this (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 the cutoff value, the tumor is diagnosed as TP53 signature mutant, and if it is below the cutoff value, the tumor is diagnosed as TP53 signature wild-type (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 levels of ≥ 10%.

Patent No. 4370409

Oncotarget 9: 14193-14206. 2018

An objective of the present invention is to provide a new method for determining the prognosis of breast cancer. Another objective of the present invention is to provide a method that can diagnose the prognosis with high accuracy, particularly in breast cancer patients with a relatively low risk of recurrence.

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. 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 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]
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. Furthermore, the present invention provides a method for diagnosing the prognosis with high accuracy in a patient group with a relatively low risk of recurrence.

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. 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. 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. 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.

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 of nucleic acids that have specific control functions, such as promoters and operators. Therefore, in the present invention, "gene" refers to regulatory regions, coding regions, exons, and introns without distinction, unless otherwise specified. Furthermore, "structural genes" also include silent DNAs in which silent mutations have been introduced into the original DNA sequence. Furthermore, in the present invention, nucleic acid molecules such as siRNAs that interfere with gene expression are also included in the term "gene."

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.

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 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), and 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 (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 tumor cells of the breast cancer patient, and examples 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 levels can also be measured using a reporter gene assay.

In the present invention, the genes used as prognostic indicators include known genes assigned Genbank Accession Numbers as shown below. More specifically, the base sequences of the cDNA sequences of each gene include those shown in SEQ ID NOS: 1 to 27. The name of each gene, and the correspondence between the Genbank Accession Number and SEQ ID NOS 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 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]
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, within the range of 8≦n≦12, preferably within the range of 9≦n≦11, and typically n=10.
In such an embodiment, the cutoff value T can 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 can be set to 1.67.

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

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, Stage I patients, lymph node-negative patients, Grade 1 patients, patients over 50 years of age, and patients with Ki-67≧10%, all of which have been difficult to predict using conventional methods.
This makes it possible to accurately predict the prognosis for this patient group.

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 occurs at a certain frequency. However, predicting the prognosis for patients with a low risk of recurrence is difficult, and a method for predicting the prognosis for these patients is needed. Lymph node-negative patients are those in whom imaging diagnostics such as CT, MRI, and ultrasound reveal no enlargement of the regional lymph nodes of breast cancer, or pathological diagnosis of the regional lymph nodes reveals no lymph node metastasis. Although the risk of recurrence is relatively low for lymph node-negative patients, recurrence occurs at a certain frequency, and a method for predicting the prognosis for these patients is needed. Grade 1 patients are those who are classified as Grade 1 according to criteria such as the Nottingham histological grading system, the classification by Black et al., the classification by Le Doussal et al., and the nuclear grading system in the "Breast Cancer Guidelines." Although the risk of recurrence is relatively low for Grade 1 patients, recurrence occurs at a certain frequency. However, predicting the prognosis for these patients is difficult, and a method for predicting the prognosis for these patients is needed. Furthermore, patients over 50 years of age have a better prognosis than patients under 50 years of age, with relatively few cases of recurrence. However, recurrence does occur at a certain frequency, and therefore a method for predicting the prognosis of such patients has been desired. The Ki-67 ≥ 10% group refers to patients in whom the ratio of positive cells to the total number of cells evaluated in breast cancer tissue by immunohistochemistry using an antibody against the KI67 (MKI67) protein is 10% or greater. Patients with Ki-67 ≥ 10% are at a relatively high risk of recurrence, and therefore a method for predicting the prognosis of such patients has been desired. Therefore, the method of the present invention meets this need and is extremely 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 lymph node-negative patients, 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 is applicable to ER-positive patient groups, Stage I patient groups, lymph node-negative patient groups, Grade 1
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, and 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.

Furthermore, as mentioned above, the present invention can 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.
TP53 inhibits the replication of TP53 proteins or suppresses proteins that affect cell division, thereby causing cell death. Therefore, cells with high cell proliferation ability have the property of being more susceptible to anticancer drugs. Therefore, the method of the present invention can also determine the sensitivity of breast cancer patients to treatment with anticancer drugs that act on cell proliferation or cell division. A specific method can be performed in accordance with a method for predicting the prognosis of 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. Furthermore, 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.
When the TP53 signature score is above the cutoff value, the disease progresses rapidly and the prognosis is generally poor. However, chemotherapy, particularly treatment with anticancer drugs that act on cell proliferation or cell division, is expected to result in a significantly higher rate of pathological complete response (pCR) compared with patients with scores below the cutoff value. Therefore, when the TP53 signature score is above the cutoff value, a treatment strategy of aggressive preoperative chemotherapy can be selected to achieve pCR. On the other hand, when the TP53 signature score is below the cutoff value, a treatment strategy of early surgery without preoperative chemotherapy can be selected.

In the present invention, treatments for breast cancer include surgical therapy, drug therapy, and radiation therapy. 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 include, for example, 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 include, for example, doxorubicin, cyclophosphamide, paclitaxel, and docetaxel. Molecularly targeted drugs are also not particularly limited and include, for example, 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 for determining the prognosis of breast cancer using all 27 genes 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 remains unchanged).

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: 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.

The present invention provides a kit for use in the method of the present invention, which comprises a nucleic acid consisting of at least a portion 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 genes. For example, the length of the nucleic acid consisting of at least a portion of the base sequence of any of the genes in Table 1 included in the kit of the present invention can be several tens of base pairs, and the specific portion (base sequence) can be appropriately prepared by those skilled in the art based on information readily available from various databases, such as the database listed in Table 1 (Genbank). Furthermore, these can be used in the form of a probe for DNA chips or Northern blotting, a primer for PCR, or the like, 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 include 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) breast cancer tumor tissues surgically removed from 216 cases of Stage I-II breast cancer, and gene expression analysis was performed using nCounter (NanoString).

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]

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.

As a result, there were 99 cases of TP53 signature mutations 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 for 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 with the wild-type type (P = 0.0044). In this example, the above-mentioned method using TP53 signature as an index may be simply referred to as the "method of the example."

Univariate analysis of recurrence-free survival using a Cox proportional hazards model with breast cancer clinicopathological patient background factors and TP53 signature showed a significant association with recurrence-free survival. Ki-67 showed a tendency to be associated with recurrence-free survival. Multivariate analysis using a Cox proportional hazards model using only factors that showed an association with recurrence-free survival in the univariate analysis 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 Document 1. Specifically, the ratio of the sum of the expression levels of genes whose expression is increased in TP53 gene mutants (gene group C: ANAPC, ASPM, BCL11A, BF930764, BIRC5, C10orf3, CCNB2, CDC45L, CDCA8, CENPE, CENPF, FLJ10719, HSPC150, KIF2C, MAPREL, 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 genes whose expression is decreased ([sum of expression values of the above gene group C] / [sum of expression values of the above gene group D]) was calculated. In this specification, the sum of the expression values of gene group C divided by the sum of the expression values of gene group D is referred to as TP53 signature'. In this method, a TP53 signature' mutant was diagnosed when the ratio of the sum of the expression levels of gene group C to gene group D was 0.78 or higher, and a TP53 signature' wild-type was diagnosed when the ratio was lower than 0.78. In this example, the method using TP53 signature' as an indicator may be simply referred to as the "Oncotarget diagnostic method." As shown in Figure 1, upper right, the TP53 signature' mutant also had a significantly poorer prognosis (recurrence-free survival) than the wild-type (P = 0.033). However, as mentioned above, the predictability of prognosis was poorer than that of the method using TP53 signature (Figure 1, upper left, P = 0.0044) in this example.

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 TP53 signature mutation cases 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 time) than the wild-type type (P=0.0239). In contrast, the 148 ER-positive cases
Oncotarget diagnostics was performed on these cases, and no significant difference in prognosis (recurrence-free survival) was found 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. TP53 signature mutation had a significantly poorer prognosis (recurrence-free survival) than wild-type (P=0.0239). In contrast, when the Oncotarget diagnostic method was used on 115 cases of Stage I, no significant difference in prognosis (recurrence-free survival) was found between the TP53 signature mutation and wild-type (Figure 2, upper right, P=0.44).

Of 216 cases of stage I-II breast cancer, 154 cases with negative lymph nodes were compared for recurrence-free survival between the TP53 signature mutation group and the wild-type group. There were 66 TP53 signature mutations and 88 wild-type cases, respectively. The results are shown in Figure 2, bottom left. The TP53 signature mutations had a significantly worse prognosis (recurrence-free survival) than the wild-type (P=0.018). In contrast, when the Oncotarget diagnostic method was used on 154 cases with negative lymph nodes, there was no significant difference in prognosis (recurrence-free survival) between the TP53 signature mutations 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 included and recurrence-free survival was compared between the TP53 signature mutation group and the wild-type group. There were 11 TP53 signature mutation cases and 44 wild-type cases, respectively. The results are shown in Figure 3, upper left. The TP53 signature mutation case had a significantly worse prognosis (recurrence-free survival) than the wild-type case (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) between the TP53 signature mutation case and the wild-type case (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 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. TP53 signature mutation cases had a significantly worse prognosis (recurrence-free survival period) than wild-type cases (P=0.018).

Of 216 cases of stage I-II breast cancer, 152 cases with Ki-67 levels of 10% or higher were included, and recurrence-free survival 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 worse prognosis (recurrence-free survival) than the wild-type group (P=0.017). In contrast, when the Oncotarget diagnostic method was used on the 152 cases with Ki-67 levels of 10% or higher, no significant difference in prognosis (recurrence-free survival) was found between the TP53 signature mutations and the wild-type group (Figure 4, right, P=0.059).

Claims (2)

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). 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.