WO2019095541A1 - 一种诊断预示乳腺癌骨转移的组合物及诊断预示方法 - Google Patents

一种诊断预示乳腺癌骨转移的组合物及诊断预示方法 Download PDF

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WO2019095541A1
WO2019095541A1 PCT/CN2018/072269 CN2018072269W WO2019095541A1 WO 2019095541 A1 WO2019095541 A1 WO 2019095541A1 CN 2018072269 W CN2018072269 W CN 2018072269W WO 2019095541 A1 WO2019095541 A1 WO 2019095541A1
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breast cancer
lncrna
methylated
bone metastasis
luminal
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French (fr)
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李宜健
薛守海
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李宜健
薛守海
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Priority claimed from CN201711142657.1A external-priority patent/CN107746887B/zh
Priority claimed from CN201711142665.6A external-priority patent/CN107699619B/zh
Priority claimed from CN201711142695.7A external-priority patent/CN107746888B/zh
Priority claimed from CN201711153105.0A external-priority patent/CN107858430B/zh
Priority claimed from CN201711200315.0A external-priority patent/CN107904309B/zh
Priority claimed from CN201711153104.6A external-priority patent/CN107881235B/zh
Priority claimed from CN201711153220.8A external-priority patent/CN107699620B/zh
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    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer

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  • the invention belongs to the field of biochemistry, relates to a disease diagnosis composition and a diagnosis method, and particularly relates to a composition for diagnosing bone metastasis of breast cancer and a diagnostic prediction method.
  • Breast cancer is one of the malignant tumors that threaten women's life and health. About 400-45 million people die of breast cancer every year. (Reference: Clinical characteristics and prognosis of patients with different molecular subtypes of breast cancer with bone metastases, Journal of Xi'an Jiaotong University ⁇ Medical Edition, September 2017, Vol. 38, No. 5). Breast cancer is very prone to distant metastasis. Bone is the most common distant metastasis site for breast cancer. More than 50% of patients have a metastatic tissue at the first metastatic site (Reference: Genes associated with breast cancer metastatic to bone, J Clin Oncol, 2006).
  • ECT radionuclide bone scan
  • CT computed tomography
  • MRI nuclear magnetic resonance
  • PET-CT positron emission tomography
  • bone biopsy is the gold for the discovery and diagnosis of breast cancer bone metastasis. standard.
  • these methods have different deficiencies, such as high inspection costs, and interventional diagnosis increases the burden on patients. This increases the pressure for routine testing of bone metastases in breast cancer patients.
  • the findings and validations can be used as a genetic marker for the diagnosis and prediction of bone metastases in different molecular subtypes of breast cancer to provide a Kits and methods for rapidly diagnosing and predicting bone metastasis of different molecular subtypes of breast cancer by blood.
  • the object of the present invention is to overcome the deficiencies of the prior art and provide a lncRNA diagnostic composition, which is prepared as a diagnostic kit for detecting low-cost, non-invasive, convenient and rapid diagnosis of bone metastasis of different molecular subtypes of breast cancer.
  • a lncRNA diagnostic composition consisting of lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of Luminal A breast cancer.
  • a diagnostic kit for the diagnosis of bone metastases in Luminal type A breast cancer including qPCR primers for lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1.
  • the diagnostic kit further comprises a qPCR primer of the internal reference GAPDH.
  • An enzyme required for qRT-PCR is also included in the diagnostic kit of any of the above.
  • a method for diagnosing bone metastasis of Luminal A breast cancer comprising the following steps:
  • Step S1 collecting fasting venous blood of Luminal type A breast cancer patient, and separating the serum by centrifugation after natural coagulation;
  • step S2 serum total RNA is extracted, and the relative expression levels of lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1 in total RNA relative to the internal reference GAPDH are determined by qRT-PCR, and are sequentially expressed by X 3 , X 1 , X 2 ;
  • a lncRNA diagnostic composition consisting of lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of Luminal B breast cancer.
  • a diagnostic kit for the diagnosis of bone metastases predicting Luminal B breast cancer including qPCR primers for lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452.
  • the diagnostic kit further comprises a qPCR primer of the internal reference GAPDH.
  • the diagnostic kit of any of the above includes the enzyme required for qRT-PCR.
  • a method for diagnosing bone metastasis of Luminal B breast cancer comprising the following steps:
  • Step S1 collecting fasting venous blood of Luminal B type breast cancer patient, and separating the serum by centrifugation after natural coagulation;
  • Step S2 extracting total serum RNA, and determining the relative expression levels of lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452 in total RNA relative to the internal reference GAPDH by qRT-PCR, represented by X 3 , X 1 , X 2 ;
  • a lncRNA diagnostic composition consisting of lncRNA AK043773 and lncRNA EXOC7.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of Her-2 overexpressing breast cancer.
  • a diagnostic kit for the diagnosis of bone metastases in Her-2 overexpressing breast cancer including qPCR primers for lncRNA AK043773 and lncRNA EXOC7.
  • the diagnostic kit further comprises a qPCR primer of the internal reference GAPDH.
  • the diagnostic kit of any of the above includes the enzyme required for qRT-PCR.
  • a method for diagnosing bone metastasis of Her-2 overexpressing breast cancer comprises the following steps:
  • step S1 the fasting venous blood of the Her-2 overexpressing breast cancer patient is collected, and the serum is separated by centrifugation after natural coagulation;
  • step S2 serum total RNA is extracted, and the relative expression levels of lncRNA AK043773 and lncRNA EXOC7 in total RNA relative to the internal reference GAPDH are determined by qRT-PCR, and are sequentially expressed by X 1 and X 2 ;
  • a lncRNA diagnostic composition consisting of lncRNA Lnc01089 and lncRNA HOTAIR.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of triple negative breast cancer.
  • a diagnostic kit for diagnosing bone metastasis predicting triple-negative breast cancer including qPCR primers for lncRNA Lnc01089 and lncRNA HOTAIR.
  • the diagnostic kit further comprises a qPCR primer of the internal reference GAPDH.
  • the diagnostic kit of any of the above includes the enzyme required for qRT-PCR.
  • a method for diagnosing bone metastasis of a triple negative breast cancer comprising the following steps:
  • Step S1 collecting fasting venous blood of a triple-negative breast cancer patient, and separating the serum by centrifugation after natural coagulation;
  • step S2 serum total RNA is extracted, and the relative expression levels of lncRNA Lnc01089 and lncRNA HOTAIR in total RNA relative to the internal reference GAPDH are determined by qRT-PCR, and are sequentially expressed by X 1 and X 2 ;
  • a methylation gene diagnostic composition consisting of methylated PITX1 and methylated AMOT.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of Luminal A breast cancer.
  • a diagnostic kit for the diagnosis of bone metastases in Luminal A breast cancer including PCR amplification primers for methylated PITX1 and methylated AMOT.
  • the diagnostic kit further comprises a pyrosequencing primer for methylated PITX1 and methylated AMOT.
  • the diagnostic kit further includes enzymes and reagents required for PCR amplification and pyrosequencing.
  • a method for diagnosing bone metastasis of Luminal A breast cancer comprising the following steps:
  • Step S1 collecting fasting venous blood of Luminal type A breast cancer patient, and separating the serum by centrifugation after natural coagulation;
  • Step S2 extracting total serum DNA, and determining methylation index of methylated PITX1 and methylated AMOT in total DNA by PCR amplification, DNA sulfite modification and pyrosequencing, and sequentially expressed by X 1 and X 2 ;
  • a methylation gene diagnostic composition consisting of methylated PTPN1 and methylated SLIT2.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of Luminal B breast cancer.
  • a diagnostic kit for the diagnosis of bone metastases in Luminal B breast cancer including PCR amplification primers for methylated PTPN1 and methylated SLIT2.
  • the diagnostic kit further comprises a pyrosequencing primer for methylated PTPN1 and methylated SLIT2.
  • the diagnostic kit further includes enzymes and reagents required for PCR amplification and pyrosequencing.
  • a method for diagnosing bone metastasis of Luminal B breast cancer comprising the following steps:
  • Step S1 collecting fasting venous blood of Luminal B type breast cancer patient, and separating the serum by centrifugation after natural coagulation;
  • Step S2 extracting total serum DNA, and determining methylation index of methylated PTPN1 and methylated SLIT2 in total DNA by PCR amplification, DNA sulfite modification and pyrosequencing, and sequentially expressed by X 1 and X 2 ;
  • a methylation gene composition consisting of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of Her-2 overexpressing breast cancer.
  • a diagnostic kit for the diagnosis of bone metastases in Her-2 overexpressing breast cancer comprising PCR amplification primers and pyrosequencing primers for methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1.
  • the diagnostic kit further includes enzymes and reagents required for PCR amplification and pyrosequencing.
  • a method for diagnosing bone metastasis of Her-2 overexpressing breast cancer comprises the following steps:
  • step S1 the fasting venous blood of the Her-2 overexpressing breast cancer patient is collected, and the serum is separated by centrifugation after natural coagulation;
  • Step S2 extracting total serum DNA, and determining methylation index of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 in total DNA by PCR amplification, DNA sulfite modification and pyrosequencing, in turn X 1 , X 2 , X 3 ;
  • a methylation gene diagnostic composition consisting of methylated MYLK3 and methylated SCARA5.
  • the above diagnostic composition is useful in the preparation of a diagnostic kit for predicting bone metastasis of triple negative breast cancer.
  • a diagnostic kit for diagnosing bone metastasis predicting triple-negative breast cancer including PCR amplification primers for methylated MYLK3 and methylated SCARA5.
  • the diagnostic kit further comprises a pyrosequencing primer for methylated MYLK3 and methylated SCARA5.
  • the diagnostic kit further includes enzymes and reagents required for PCR amplification and pyrosequencing.
  • a method for diagnosing bone metastasis of a triple negative breast cancer comprising the following steps:
  • Step S1 collecting fasting venous blood of a triple-negative breast cancer patient, and separating the serum by centrifugation after natural coagulation;
  • Step S2 extracting total serum DNA, and determining methylation index of methylated MYLK3 and methylated SCARA5 in total DNA by PCR amplification, DNA sulfite modification and pyrosequencing, and sequentially expressed by X 1 and X 2 ;
  • Figure 1 shows the ROC curve of the combination of lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1 for the diagnosis of bone metastases in Luminal A breast cancer unmetastatic and Luminal A breast cancer;
  • Figure 2 shows the accuracy of the combination of lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1 in the diagnosis of bone metastases in Luminal A breast cancer unmetastatic and Luminal A breast cancer;
  • Figure 3 is a ROC curve of the combination of lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452 in the test set for the diagnosis of bone metastases in Luminal B breast cancer unmetastatic and Luminal B breast cancer;
  • Figure 4 shows the accuracy of the combination of lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452 in the diagnosis of bone metastases in Luminal B breast cancer unmetastatic and Luminal B breast cancer;
  • Figure 5 is a ROC curve of the combination of lncRNA AK043773 and lncRNA EXOC7 in the test set for the diagnosis of bone metastases in Her-2 overexpressing breast cancer unmetastatic and Her-2 overexpressing breast cancer;
  • Figure 6 shows the accuracy of the combination of lncRNA AK043773 and lncRNA EXOC7 in the diagnosis of bone metastases in Her-2 overexpressing breast cancer unmetastatic and Her-2 overexpressing breast cancer;
  • Figure 7 is a ROC curve for the diagnosis of bone metastases in triple-negative breast cancer unmetastatic and triple-negative breast cancer using a combination of lncRNA Lnc01089 and lncRNA HOTAIR in the test set;
  • Figure 8 shows the accuracy of the combined diagnosis of lncRNA Lnc01089 and lncRNA HOTAIR in the diagnosis of triple-negative breast cancer unmetastatic and triple-negative breast cancer bone metastases;
  • Figure 9 is a ROC curve of the combination of methylated PITX1 and methylated AMOT in the test for the differential diagnosis of Luminal A breast cancer unmetastatic and Luminal A breast cancer bone metastases;
  • Figure 10 is a graph showing the accuracy of the combination of focused methylated PITX1 and methylated AMOT for the diagnosis of bone metastases in Luminal type A breast cancer without metastasis and Luminal type A breast cancer;
  • Figure 11 shows the ROC curve of the combination of methylated PTPN1 and methylated SLIT2 in the test for the differential diagnosis of Luminal B breast cancer unmetastatic and Luminal B breast cancer bone metastases;
  • Figure 12 is a graph showing the accuracy of the combination of methylated PTPN1 and methylated SLIT2 for the diagnosis of bone metastases in Luminal B breast cancer without metastasis and Luminal B breast cancer;
  • Figure 13 is a ROC curve of the combination of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 in the test for differential diagnosis of bone metastases in Her-2 overexpressing breast cancer unmetastatic and Her-2 overexpressing breast cancer;
  • Figure 14 is a graph showing the accuracy of the combination of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 in the diagnosis of bone metastases in Her-2 overexpressing breast cancer unmetastatic and Her-2 overexpressing breast cancer;
  • Figure 15 is a ROC curve of the combination of methylated MYLK3 and methylated SCARA5 in the test combination for the diagnosis of bone metastases in triple-negative breast cancer unmetastatic and triple-negative breast cancer;
  • Figure 16 is a graph showing the accuracy of the combination of methylated MYLK3 and methylated SCARA5 in the diagnosis of triple-negative breast cancer unmetastatic and triple-negative breast cancer.
  • Part I lncRNA diagnostic composition and diagnostic method
  • the breast cancer non-metastasis group and the breast cancer bone metastasis group were subjected to radionuclide bone scan (ECT), computed tomography (CT), nuclear magnetic resonance (MRI), positron emission computed tomography (PET-CT) and/or tissue.
  • ECT radionuclide bone scan
  • CT computed tomography
  • MRI nuclear magnetic resonance
  • PET-CT positron emission computed tomography
  • Collection of serum samples Collecting 5.0 mL of fasting venous blood of the patient, centrifugation (4000 r/min, 2860 ⁇ g) after natural coagulation, and separating the serum for 7 min, and storing at -80 °C for detecting the relative expression of target lncRNA in serum. .
  • Example 1 Luminal type A breast cancer bone metastasis
  • the primer was synthesized by Beauchamps (Shanghai, China), lncRNA XLOC_004122 primer sequence: upstream 5'-CTGGCAGGAACACCGGGTACTT-3', downstream 5'-TGACTTTTACTTAGGAGCCACTTCTTG-3'; lncRNA SUMO1P3 primer sequence: upstream 5'-CTGGAACTGGGAATGGAGGAAGA-3', downstream 5 '-GATTGAGAAAGGATTGAGGGAAA-3'; lncRNANBAT-1 Primer sequence: upstream 5'-CTGGGAAAGCCTGTGCTCTTGGA-3', downstream 5'-GCTTCACAGTGCTGCTCAATCGT-3'; GAPDH primer sequence: upstream 5'-CGCTCTCTGCTCCTCCTGTTC-3', downstream 5'-ATCCGTTGACTCCGACCTTCAC- 3'. LncRNA SUMO1P3 NBAT-1 and the relative expression of lncRNA average of 3 measurements was calculated by method 2
  • the data was analyzed using SPSS 19.0.
  • the measurement data were expressed as mean ⁇ deviation, using t test, the count data was expressed as a percentage, using ⁇ 2 test, P ⁇ 0.05 was considered statistically significant, and the ROC curve was established to calculate the area under the curve (area under the curve, AUC). ) and 95% confidence interval.
  • Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the relative expression levels of lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1 in each sample were determined.
  • the relative expression levels of lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1 were significantly up-regulated in the Luminal A breast cancer bone metastasis group.
  • the bone metastasis group lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT- 1 The relative expression levels were (1.9 ⁇ 0.4) times, (2.3 ⁇ 0.5) times, and (2.5 ⁇ 0.4) times the relative expression levels of the untransferred group, respectively.
  • lncRNA XLOC_004122, lncRNA SUMO1P3 or lncRNA NBAT-1 relative expression level alone for diagnosis and differentiation of Luminal A breast cancer without metastasis and Luminal A breast cancer bone transfer ROC curve analysis
  • the basic evaluation indicators of the diagnostic test are sensitivity and specificity, and the comprehensive evaluation indicators include Youden index, ROC, AUC, and the like.
  • the results of the diagnostic test can be classified into the following cases:
  • the ROC curve is a curve based on the above sensitivity and specificity. Using the possible diagnostic thresholds in the diagnostic test as the diagnostic point, the corresponding sensitivity and specificity are calculated according to the above table. Then, with the sensitivity as the ordinate and the 1-specificity as the abscissa, the sensitivity and specific points of each point in each diagnostic point are marked in the coordinate map, and the coordinate points are connected to obtain a smooth curve, which is the ROC curve. . The more dense the diagnostic points are set, the smoother the resulting ROC curve will be.
  • the ROC curve uses each test result as a possible diagnostic threshold.
  • the size of the area under the curve AUC indicates the accuracy of the diagnostic test.
  • the area under the ROC curve AUC has been widely recognized as an intrinsic accuracy index for the authenticity evaluation of diagnostic tests.
  • the AUC is 0.5, there is no diagnostic significance; when the AUC is 0.5-0.7, the diagnostic accuracy is low; the AUC is 0.7-0.9. Time indicates that the diagnostic accuracy is medium; when AUC>0.9, the diagnosis has higher accuracy.
  • lncRNA XLOC_004122, lncRNA SUMO1P3 or lncRNA NBAT-1 were mapped in SPSS 19.0 alone to diagnose the ROC curves of Luminal A breast cancer unmetastatic and Luminal A breast cancer bone metastases, AUC were 0.601, 0.697, 0.729, respectively. , with low or medium accuracy.
  • lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1 combined expression model construction and ROC curve analysis for diagnosis of Luminal A breast cancer non-metastasis and Luminal A breast cancer bone metastasis
  • AUC is 0.921, with high accuracy.
  • the Verdon index specificity + sensitivity-1, and the corresponding Y value of the maximum value of the Verdon's index can be diagnosed to distinguish the best cut-off between the Luminal A breast cancer non-metastasis group and the bone metastasis group.
  • the value is 0.598 (the diagnostic threshold).
  • Example 2 Luminal B breast cancer bone metastasis
  • Test set and validation set of Luminal B type breast cancer non-metastasis group and Luminal B type breast cancer bone metastasis group are included in Test set and validation set of Luminal B type breast cancer non-metastasis group and Luminal B type breast cancer bone metastasis group.
  • the primer was synthesized by Beauchamps (Shanghai, China), lncRNA XLOC_004122 Primer sequence: upstream 5'-CTGGCAGGAACACCGGGTACTT-3', downstream 5'-TGACTTTTACTTAGGAGCCACTTCTTG-3'; lncRNA Linc00467 Primer sequence: upstream 5'-GCCTG GTTGTTCAGCACCTTCG-3', downstream 5'-TCGGATCGGTGCTGGTTTTGGT-3'; lncRNA Al049452 Primer sequence: upstream 5'-CAGTTAAACCCACAGGTGGTAGCATGAC-3', downstream 5'-TAGTGGGAAAA CCTAGTTTCCGACAGTT-3'; GAPDH primer sequence: upstream 5'-CGCTCTCTGCTCCTCCTGTTC-3', downstream 5'-ATCCGTTGACTCCGACCTTCAC -3'.
  • the data was analyzed using SPSS 19.0.
  • the measurement data were expressed as mean ⁇ deviation, using t test, the count data was expressed as a percentage, using ⁇ 2 test, P ⁇ 0.05 was considered statistically significant, and the ROC curve was established to calculate the area under the curve (area under the curve, AUC). ) and 95% confidence interval.
  • Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the relative expression levels of lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452 were determined for each sample. Compared with the Luminal B breast cancer non-metastasis group, the relative expression levels of lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452 were significantly up-regulated in the Luminal B breast cancer bone metastasis group. The relative expression levels of lncRNA XLOC_004122, lncRNA Linc00467 and lncRNA Al049452 in the bone metastasis group. They were (2.2 ⁇ 0.4) times, (2.7 ⁇ 0.3) times, and (2.3 ⁇ 0.3) times the relative expression levels of the untransferred group, respectively.
  • lncRNA XLOC_004122, lncRNA Linc00467 or lncRNA Al049452 were mapped in SPSS 19.0 alone to diagnose the ROC curves of Luminal B breast cancer unmetastatic and Luminal B breast cancer bone metastases, AUC were 0.687, 0.744, 0.706, respectively. Lower or medium accuracy.
  • the regression value Y of each sample can be obtained, and the possible regression value Y is used as a diagnosis point, and the sensitivity and specificity are calculated, and the ROC curve is drawn accordingly (as shown in FIG. 3), and the AUC is 0.935, with high accuracy.
  • the Verdon index specificity + sensitivity-1
  • the corresponding Y value of the maximum value of the Verdon's index can be diagnosed to distinguish the best cut-off between the Luminal B type breast cancer non-metastasis group and the bone metastasis group.
  • the value is 0.607 (the diagnostic threshold).
  • Test set and validation set of Her-2 overexpressing breast cancer non-metastasis group and Her-2 overexpressing breast cancer bone metastasis group are listed.
  • the primer was synthesized by Beauchamps (Shanghai, China), lncRNA AK043773 primer sequence: upstream 5'-GTGACGCCAGGGATGGCATTA-3', downstream 5'-CAG AGCCTTGCATTGGTCAGT-3'; lncRNA EXOC7 primer sequence: upstream 5'-GAGTCTGGGATCAGAGA GCAAAGG-3', Downstream 5'-GGTACTGTAGAAAGGCCCCGTAGG-3'; GAPDH primer sequence: upstream 5'-C GCTCTCTGCTCCTCCTGTTC-3', downstream 5'-ATCCGTTGACTCCGACCTTCAC-3'. Relative expression lncRNA AK043773 lncRNA EXOC7 and an average value of 3 measurements 2 - ⁇ Ct calculation method.
  • the data was analyzed using SPSS 19.0.
  • the measurement data were expressed as mean ⁇ deviation, using t test, the count data was expressed as a percentage, using ⁇ 2 test, P ⁇ 0.05 was considered statistically significant, and the ROC curve was established to calculate the area under the curve (area under the curve, AUC). ) and 95% confidence interval.
  • Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the relative expression levels of lncRNA AK043773 and lncRNA EXOC7 were determined for each sample. Compared with the Her-2 overexpressing breast cancer non-metastasis group, the relative expression levels of lncRNA AK043773 and lncRNA EXOC7 in the Her-2 overexpressing breast cancer bone metastasis group were significantly up-regulated, and the relative expression levels of lncRNA AK043773 and lncRNA EXOC7 in the bone metastasis group. They were (3.3 ⁇ 0.5) times and (2.6 ⁇ 0.3) times of the untransferred group, respectively.
  • the relative expression level of lncRNA AK043773 or lncRNA EXOC7 was used to diagnose the ROC curve of Her-2 overexpressing breast cancer without metastasis and Her-2 overexpressing breast cancer.
  • the relative expression levels of lncRNA AK043773 or lncRNA EXOC7 were mapped in SPSS 19.0 alone to diagnose the ROC curves of bone metastases in Her-2 overexpressing breast cancer and meta-2 overexpressing breast cancer, with AUC of 0.762 and 0.717, respectively. Has moderate accuracy.
  • Binary Logistic Regression of Relative Expression Levels of lncRNA AK043773 and lncRNA EXOC7 in Her-2 Overexpressing Breast Cancer Unmetastatic and Her-2 Overexpressing Breast Cancer Bone Metastasis Samples as a Dependent Variable , the binary logistic regression equation is obtained: Y -2.918+2.618X 1 +2.115X 2 ; and the relative expression levels of lncRNA AK043773 and lncRNA EXOC7 in each sample are substituted into the binary logistic regression equation to obtain the regression of each sample.
  • the cut-off value is 0.495 (ie, the diagnostic threshold).
  • the relative expression levels of each sample lncRNA AK043773 and EXOC7 were substituted into the above regression model, and the regression values Y, Y of each sample were higher than the diagnostic threshold of 0.495.
  • the prediction was Her-2 overexpressing breast cancer bone metastasis, lower than diagnosis.
  • the threshold of 0.495 was predicted to be non-metastatic in Her-2 overexpressing breast cancer with an accuracy of 91.1% (51/56), as shown in Figure 6.
  • the primer was synthesized by Beauchamps (Shanghai, China), lncRNA Lnc01089 Primer sequence: upstream 5'-TCGCTGGGTTGCTCTGCTTC-3', downstream 5'-GTCAGGAGGTCACAGTCTTAGGG-3'; lncRNA HOTAIR primer sequence: upstream 5'-CGTGGAAAGATCCAAATGGGACCA-3', downstream 5 '-AGCCTAGGAATCAGCACGAAGCAAA-3'; GAPDH primer sequence: upstream 5'-CGCTCTCTGCTCCTCCTGTTC-3', downstream 5'-ATCCGTTGACTCCGACCTTCAC-3'. Relative expression lncRNA Lnc01089 lncRNA HOTAIR and an average value of 3 measurements 2 - ⁇ Ct calculation method.
  • the data was analyzed using SPSS 19.0.
  • the measurement data were expressed as mean ⁇ deviation, using t test, the count data was expressed as a percentage, using ⁇ 2 test, P ⁇ 0.05 was considered statistically significant, and the ROC curve was established to calculate the area under the curve (area under the curve, AUC). ) and 95% confidence interval.
  • Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the relative expression levels of lncRNA Lnc01089 and lncRNA HOTAIR were determined for each sample. Compared with the triple-negative breast cancer non-metastasis group, the relative expression levels of lncRNA Lnc01089 and lncRNA HOTAIR were significantly up-regulated in the triple-negative breast cancer bone metastasis group. The relative expression levels of lncRNA Lnc01089 and lncRNA HOTAIR in the bone metastasis group were untransferred group, respectively. (3.5 ⁇ 0.6) times, (3.2 ⁇ 0.5) times.
  • Binary logistic regression was performed as a dependent variable for the relative expression levels of lncRNA Lnc01089 and lncRNA HOTAIR in triple-negative breast cancer unmetastatic and triple-negative breast cancer bone metastasis samples, resulting in binary logistic regression.
  • Equation: Y -2.537+2.793X 1 +2.181X 2 ; Substituting the relative expression levels of lncRNA Lnc01089 and lncRNA HOTAIR in each sample into the binary logistic regression equation, the regression value Y of each sample can be obtained, possibly The regression value Y is used as a diagnostic point to calculate the sensitivity and specificity, and the ROC curve is plotted accordingly (as shown in Fig. 7), and the AUC is 0.948, which has high accuracy.
  • the Verdon index specificity + sensitivity-1
  • the corresponding Y value of the maximum value of the Verdon's index can be diagnosed to distinguish the best cut of the triple-negative breast cancer non-metastasis group and the bone metastasis group.
  • the off value is 0.633 (ie the diagnostic threshold).
  • serum lncRNA XLOC_004122, lncRNA SUMO1P3 and lncRNA NBAT-1 can be used in combination to diagnose the bone metastasis of Luminal A breast cancer, and the accuracy of the independent verification is more than 90%; serum lncRNA XLOC_004122 , lncRNA Linc00467 and lncRNA Al049452 can be used in combination to diagnose the bone metastasis of Luminal B breast cancer. The accuracy of the independent diagnosis is more than 90%.
  • the serum lncRNA AK043773 and lncRNA EXOC7 can be used together for the diagnosis of Her-2.
  • the accuracy of independent diagnosis in the independent verification predicts more than 90%; lncRNA Lnc01089 and lncRNA HOTAIR can be used together to diagnose the bone metastasis of triple-negative breast cancer, and the accuracy of the independent diagnosis is predictive. More than 90.
  • the use of the above-mentioned serum lncRNA diagnosis indicates that the bone metastasis of different molecular subtypes of breast cancer is not only highly accurate, but also has low detection cost, non-invasiveness, convenience, and greatly reduces the pain and burden of the patient.
  • the experimental sample is the same as the first part.
  • Serum specimen collection 5.0 mL of fasting venous blood of the patient was collected, and the serum was isolated after centrifugation (4000 r/min, 2860 ⁇ g) for 7 min after natural coagulation, and stored at -80 ° C for detection of the target methylation gene in serum.
  • Example 5 Luminal type A breast cancer bone metastasis
  • Serum DNA extraction was performed according to the DNA Blood Midi Kit instructions, using 0.8 mL of serum per sample. The purity of the extracted DNA was detected by an ultraviolet spectrophotometer, and the ratio of the absorbance A260/A280 was between 1.7 and 2.0 for subsequent operations. Calculate the DNA content and store at -70 °C for later use.
  • PCR was used to amplify the methylation region of the PITX1 and AMOT gene promoters in the sample.
  • the reaction system includes sulfite-treated template 2 ⁇ l, 10 ⁇ PCR buffer, 0.25 U/ ⁇ l Hot star Taq enzyme, 0.5 mmol/L dNTP, 1 ⁇ l of each of the upstream and downstream primers, and a total volume of 50 ⁇ l. Double distilled water was used as a blank control.
  • the PCR amplification primers and sequencing primers are as follows:
  • methylation index of the promoter region of each gene was calculated according to the following formula, which reflects the degree of methylation of the promoter region of the gene:
  • the data was analyzed using SPSS 19.0. The measurement data were expressed as mean ⁇ deviation. The t test was used. The count data was expressed as a percentage. The ⁇ 2 test was used. The difference was statistically significant at P ⁇ 0.05.
  • the ROC curve was established and the area under the curve (areaunderthecurve, AUC) and 95 were calculated. % confidence interval. Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the methylation index of methylated PITX1 and methylated AMOT in each sample was determined. Compared with the Luminal type A breast cancer non-metastasis group, the methylation index of methylated PITX1 and methylated AMOT was significantly increased in the Luminal type A breast cancer bone metastasis group.
  • the bone metastasis group methylated PITX1 and methyl group.
  • the methylation index of AMOT was (3.5 ⁇ 0.4) times and (3.3 ⁇ 0.5) times of the methylation index of the untransferred group, respectively.
  • the methylation index of methylated PITX1 and methylated AMOT was used to diagnose the ROC curve of Luminal A breast cancer without metastasis and Luminal A breast cancer.
  • the methylation index of methylated PITX1 and methylated AMOT was plotted in SPSS 19.0 alone to diagnose the ROC curve for the differential metastasis of Luminal A breast cancer and Luminal A breast cancer.
  • the AUC was 0.715 and 0.707, respectively. Has moderate accuracy.
  • X 1 methylation index of methylated PITX1
  • X 2 methylation index of methylated AMOT
  • Y 1/[1+EXP(1.499X 1 +2.302X 2 -0.258)];
  • the regression value Y of each sample can be obtained, and the possible regression value Y is used as a diagnostic point to calculate the sensitivity and Specificity, according to which the ROC curve is plotted (as shown in Figure 9), the AUC is 0.935, with high accuracy.
  • the Verdon index specificity + sensitivity-1
  • the corresponding Y value of the maximum value of the Verdon's index can be diagnosed to distinguish the best cut-off between the Luminal A breast cancer non-metastasis group and the bone metastasis group.
  • the value is 0.238 (the diagnostic threshold).
  • the methylation index of each sample methylated PITX1 and methylated AMOT was substituted into the above regression model, and the regression value Y of each sample was obtained.
  • Y is lower than the diagnostic threshold of 0.238.
  • the prediction is Luminal type A breast cancer bone metastasis.
  • the prediction above the diagnostic threshold of 0.238 is Luminal type A breast cancer without metastasis, with an accuracy of 95.5% (105/110), as shown in Figure 10.
  • Example 6 Luminal B breast cancer bone metastasis
  • Test set and validation set of Luminal B type breast cancer non-metastasis group and Luminal B type breast cancer bone metastasis group are included in Test set and validation set of Luminal B type breast cancer non-metastasis group and Luminal B type breast cancer bone metastasis group.
  • Serum DNA extraction was performed according to the DNA Blood Midi Kit instructions, using 0.8 mL of serum per sample. The purity of the extracted DNA was detected by an ultraviolet spectrophotometer, and the ratio of the absorbance A260/A280 was between 1.7 and 2.0 for subsequent operations. Calculate the DNA content and store at -70 °C for later use.
  • the methylation region of the PTPN1 and SLIT2 gene promoters in the sample was amplified by PCR.
  • the reaction system includes sulfite-treated template 2 ⁇ l, 10 ⁇ PCR buffer, 0.25 U/ ⁇ l Hot star Taq enzyme, 0.5 mmol/L dNTP, 1 ⁇ l of each of the upstream and downstream primers, and a total volume of 50 ⁇ l. Double distilled water was used as a blank control.
  • the PCR amplification primers and sequencing primers are as follows:
  • methylation index of the promoter region of each gene was calculated according to the following formula, which reflects the degree of methylation of the promoter region of the gene:
  • the data was analyzed using SPSS 19.0.
  • the measurement data were expressed as mean ⁇ deviation, using t test, the count data was expressed as a percentage, using ⁇ 2 test, P ⁇ 0.05 was considered statistically significant, and the ROC curve was established to calculate the area under the curve (area under the curve, AUC). ) and 95% confidence interval.
  • Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the methylation index of methylated PTPN1 and methylated SLIT2 in each sample was determined. Compared with the Luminal B breast cancer non-metastasis group, the methylation index of methylated PTPN1 and methylated SLIT2 was significantly increased in the Luminal B breast cancer bone metastasis group.
  • the bone metastasis group methylated PTPN1 and methyl group.
  • the methylation index of SLIT2 was (2.9 ⁇ 0.5) times and (3.4 ⁇ 0.5) times that of the untransformed group methylation index, respectively.
  • the methylation index of methylated PTPN1 and methylated SLIT2 was used to diagnose the ROC curve of Luminal B breast cancer without metastasis and Luminal B breast cancer.
  • the methylation index of methylated PTPN1 and methylated SLIT2 was mapped in SPSS 19.0 alone to diagnose the ROC curve of Luminal B breast cancer unmetastatic and Luminal B breast cancer bone metastases, with AUC of 0.723 and 0.741, respectively. Has moderate accuracy.
  • X 1 methylation index of methylated PTPN1
  • X 2 methylation index of methylated SLIT2
  • Y 1/[1+EXP(2.016X 1 +1.898X 2 -0.455)];
  • the regression value Y of each sample can be obtained, and the possible regression value Y is used as a diagnostic point to calculate the sensitivity and Specificity, according to which the ROC curve is plotted (as shown in Figure 11), the AUC is 0.942, with high accuracy.
  • the Verdon index specificity + sensitivity-1
  • the corresponding Y value of the maximum value of the Verdon's index can be diagnosed to distinguish the best cut-off between the Luminal B type breast cancer non-metastasis group and the bone metastasis group.
  • the value is 0.310 (the diagnostic threshold).
  • the methylation index of each sample methylated PTPN1 and methylated SLIT2 was substituted into the above regression model, and the regression value Y of each sample was obtained.
  • Y is lower than the diagnostic threshold of 0.310.
  • the prediction is Luminal B type breast cancer bone metastasis.
  • the prediction above the diagnostic threshold of 0.310 was that Luminal B breast cancer was not metastatic, with an accuracy of 93.7% (59/63), as shown in Figure 12.
  • Example 7 Her-2 overexpressing breast cancer bone metastasis
  • Test set and validation set of Her-2 overexpressing breast cancer non-metastasis group and Her-2 overexpressing breast cancer bone metastasis group are listed.
  • Serum DNA extraction was performed according to the DNA Blood Midi Kit instructions, using 0.8 mL of serum per sample. The purity of the extracted DNA was detected by an ultraviolet spectrophotometer, and the ratio of the absorbance A260/A280 was between 1.7 and 2.0 for subsequent operations. Calculate the DNA content and store at -70 °C for later use.
  • PCR was used to amplify the methylation region of the MYLK2, EFEMP1 and SOSTDC1 gene promoters in the sample.
  • the reaction system includes sulfite-treated template 2 ⁇ l, 10 ⁇ PCRbuffer, 0.25 U/ ⁇ l Hot star Taq enzyme, 0.5 mmol/L dNTP, 1 ⁇ l of each of the upstream and downstream primers, and a total volume of 50 ⁇ l.
  • the PCR amplification primers and sequencing primers are as follows:
  • methylation index of the promoter region of each gene was calculated according to the following formula, which reflects the degree of methylation of the promoter region of the gene:
  • the data was analyzed using SPSS 19.0.
  • the measurement data were expressed as mean ⁇ deviation, using t test, the count data was expressed as a percentage, using ⁇ 2 test, P ⁇ 0.05 was considered statistically significant, and the ROC curve was established to calculate the area under the curve (area under the curve, AUC). ) and 95% confidence interval.
  • Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the methylation index of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 in each sample was determined.
  • the methylation index of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 was significantly increased in the Her-2 overexpressing breast cancer bone metastasis group. , (3.7 ⁇ 0.6) times, (2.6 ⁇ 0.4), (3.1 ⁇ 0.5) times of the methylation index of the untransferred group, respectively.
  • Methylation index of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 was used to diagnose ROC curve of bone metastasis of Her-2 overexpressing breast cancer without metastasis and Her-2 overexpressing breast cancer. analysis
  • the methylation index of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 was mapped in SPSS 19.0 alone to diagnose the differentiation of Her-2 overexpressing breast cancer without metastasis and Her-2 overexpressing breast cancer.
  • the ROC curve, AUC, is 0.794, 0.688, 0.738, respectively, with low or medium accuracy.
  • the binary logistic regression of the methylation index of EFEMP1 and methylated SOSTDC1 in Her-2 overexpressing breast cancer unmetastatic and Her-2 overexpressing breast cancer bone metastasis samples, and the binary logistic regression equation was obtained: Y 1/[1+EXP(1.342X 1 +1.401X 2 +1.345X 3 -2.035)];
  • the methylation index of methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 in each sample was substituted into the binary logistic regression equation to obtain the regression value Y of each sample, and the possible regression value Y was used as a diagnosis.
  • Point calculate the sensitivity and specificity, and draw the ROC curve (as shown in Figure 13), with an AUC of 0.950, with high accuracy.
  • the Verdon index specificity + sensitivity-1
  • the cut-off value is 0.308 (diagnostic threshold).
  • the methylation index of each sample methylated MYLK2, methylated EFEMP1 and methylated SOSTDC1 was substituted into the above regression model to obtain the regression value Y of each sample, and the prediction of the sample below the diagnostic threshold of 0.308 was Her- 2 Over-expression breast cancer bone metastasis, higher than the diagnostic threshold of 0.308 predicted that Her-2 overexpressing breast cancer did not metastasize, the accuracy was 96.4% (54/56), as shown in Figure 14.
  • Example 8 Three-negative breast cancer bone metastasis
  • Serum DNA extraction was performed according to the DNA Blood Midi Kit instructions, using 0.8 mL of serum per sample. The purity of the extracted DNA was detected by an ultraviolet spectrophotometer, and the ratio of the absorbance A260/A280 was between 1.7 and 2.0 for subsequent operations. Calculate the DNA content and store at -70 °C for later use.
  • PCR was used to amplify the methylation region of the MYLK3 and SCARA5 gene promoters in the sample.
  • the reaction system includes sulfite-treated template 2 ⁇ l, 10 ⁇ PCR buffer, 0.25 U/ ⁇ l Hot star Taq enzyme, 0.5 mmol/L dNTP, 1 ⁇ l of each of the upstream and downstream primers, and a total volume of 50 ⁇ l. Double distilled water was used as a blank control.
  • the PCR amplification primers and sequencing primers are as follows:
  • methylation index of the promoter region of each gene was calculated according to the following formula, which reflects the degree of methylation of the promoter region of the gene:
  • the data was analyzed using SPSS 19.0.
  • the measurement data were expressed as mean ⁇ deviation, using t test, the count data was expressed as a percentage, using ⁇ 2 test, P ⁇ 0.05 was considered statistically significant, and the ROC curve was established to calculate the area under the curve (area under the curve, AUC). ) and 95% confidence interval.
  • Logistic regression was used to screen the variables, and regression equations were established to generate a new set of variables Y. The ROC curve analysis was performed on the new variables and each individual indicator.
  • the methylation index of methylated MYLK3 and methylated SCARA5 in each sample was determined. Compared with the triple-negative breast cancer non-metastasis group, the methylation index of methylated MYLK3 and methylated SCARA5 was significantly increased in the triple-negative breast cancer bone metastasis group, and the bone metastasis group methylated MYLK3 and methyl group.
  • the methylation index of SCARA5 was (2.1 ⁇ 0.3) times and (3.6 ⁇ 0.7) times that of the untransformed group methylation index, respectively.
  • the methylation index of methylated MYLK3 and methylated SCARA5 was used to diagnose the ROC curve of triple-negative breast cancer without metastasis and triple-negative breast cancer.
  • the methylation index of methylated MYLK3 and methylated SCARA5 was mapped in SPSS 19.0 alone to diagnose the ROC curve of three-negative breast cancer unmetastatic and triple-negative breast cancer bone metastases, AUC were 0.644, 0.809, respectively. Has low or medium accuracy.
  • Y 1/[1+EXP(1.775X 1 +1.236X 2 -0.398)];
  • the regression value Y of each sample can be obtained, and the possible regression value Y is used as a diagnostic point to calculate the sensitivity and Specificity, according to which the ROC curve is plotted (as shown in Figure 15), the AUC is 0.954, with high accuracy.
  • the Verdon index specificity + sensitivity-1
  • the corresponding Y value of the maximum value of the Verdon's index is the best cut-off for the diagnosis of the triple-negative breast cancer non-metastasis group and the bone metastasis group.
  • the value is 0.366 (the diagnostic threshold).
  • the methylation index of each sample methylated MYLK3 and methylated SCARA5 was substituted into the above regression model, and the regression value Y of each sample was obtained.
  • Y is lower than the diagnostic threshold of 0.366 and is predicted to be triple negative breast cancer bone metastasis.
  • the prediction above the diagnostic threshold of 0.366 was that triple-negative breast cancer did not metastasize with an accuracy of 94.6% (53/56), as shown in Figure 16.
  • serum methylated PITX1 and methylated AMOT can be used in combination to diagnose the bone metastasis of Luminal A breast cancer, and the accuracy of the independent verification is more than 90%; serum methylation PTPN1 and methylated SLIT2 can be used in combination to diagnose the bone metastasis of Luminal B breast cancer.
  • the independent diagnosis has a predictive accuracy of more than 90%.
  • Serum methylation of MYLK2, methylated EFEMP1 and methylated SOSTDC1 can be Combined use in the diagnosis of bone metastases in Her-2 overexpressing breast cancer, the accuracy of independent diagnosis in the independent validation predicts more than 90%; serum methylation of MYLK3 and methylated SCARA5 can be used in combination to predict the diagnosis of triple negative mammary gland Whether the cancer is bone metastasis or not, the accuracy of the independent verification indicates that the accuracy rate is over 90%.
  • the use of the above-mentioned serum methylation gene diagnosis indicates that the bone metastasis of different molecular subtypes of breast cancer is not only highly accurate, but also has low detection cost, non-invasiveness, convenience, and greatly reduces the pain and burden of the patient.

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Abstract

提供了一种诊断预示乳腺癌骨转移的组合物及诊断预示方法。目前，放射性核素骨扫描(ECT)、电子计算机断层扫描(CT)、核磁共振(MRI)、正电子发射计算机断层扫描(PET-CT)和骨组织活检是发现和确诊乳腺癌骨转移的金标准。但是，这些方法均存在不同的不足，比如检查费用高，介入诊断增加了患者的负担，增加了乳腺癌患者骨转移常规检测的压力。通过研究比较发生骨转移与未发生骨转移的乳腺癌患者血清中基因表达的差异，发现并验证了可以用作诊断、预示不同分子亚型乳腺癌骨转移的基因标志物，可以提供一种通过血液即可快速诊断、预示不同分子亚型乳腺癌骨转移的组合物和方法。

Description

一种诊断预示乳腺癌骨转移的组合物及诊断预示方法 技术领域
本发明属于生物化学领域，涉及疾病诊断组合物及诊断方法，具体涉及一种诊断预示乳腺癌骨转移的组合物及诊断预示方法。
背景技术
乳腺癌是威胁女性生命健康的恶性肿瘤之一，每年约有40-45万人死于乳腺癌(参考文献：不同分子亚型乳腺癌骨转移患者的临床特征和预后分析，西安交通大学学报·医学版，2017年9月第38卷第5期)。乳腺癌非常容易发生远处转移，骨是乳腺癌最常见的远处转移部位，大于50％的患者首发转移部位是骨组织(参考文献：Genes associated with breast cancer metastatic to bone,J Clin Oncol,2006；Implications of Bone-Only Metastases in Breast Cancer:Favorable Preference with Excellent Outcomes of Hormone Receptor Positive Breast Cancer,Cancer Res Treat,2011)。根据***受体(estrogen receptor,ER)、孕激素受体(progesterone receptor,PR)、人表皮生长因子受体-2(human epidermal growth factor receptor-2,HER-2)的表达情况，可将乳腺癌分为4个亚型，分别为：Luminal A型、Luminal B型、Her-2过表达型和三阴性乳腺癌(参考文献：Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications,PNAS,2001)。研究表明，乳腺癌骨转移的预后与其分子分型、临床分期、***状态等密切相关(参考文献：Prevalence and risk factors of bone metastasis and skeletal related events in patients with primary breast cancer in Japan,Int J Clin Onco,2014)。不同分子亚型乳腺癌特定的分子生物学和临床病理特征，决定了其治疗方式及预后的差异。不同分子亚型乳腺癌骨转移的基因表达水平也存在差异。
早期诊断乳腺癌骨转移是挽救患者生命的关键。目前，放射性核素骨扫描(ECT)、电子计算机断层扫描(CT)、核磁共振(MRI)、正电子发射计算机断层扫描(PET-CT)和骨组织活检是发现和确诊乳腺癌骨转移的金标准。但是，这些方法均存在不同的不足，比如检查费用高，介入诊断增加了患者的负担。这增加了乳腺癌患者骨转移常规检测的压力。
申请人旨在研究比较发生骨转移与未发生骨转移的乳腺癌患者血清中基因表达的差异，发现、验证可以用作诊断、预示不同分子亚型乳腺癌骨转移的基因标志物，以提供一种通过血液即可快速诊断、预示不同分子亚型乳腺癌骨转移的试剂盒和方法。
发明内容
本发明的目的在于克服现有技术的不足，提供一种lncRNA诊断组合物，制备成一种检测成本低、非介入性、方便快捷诊断预示不同分子亚型乳腺癌骨转移的诊断试剂盒。
本发明的上述目的是通过下面的技术方案得以实现的(lncRNA组合物部分)：
一、Luminal A型乳腺癌骨转移
一种lncRNA诊断组合物，由lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1组成。
上述诊断组合物在制备诊断预示Luminal A型乳腺癌骨转移的诊断试剂盒方面的应用。
用于诊断预示Luminal A型乳腺癌骨转移的诊断试剂盒，包括lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1的qPCR引物。
优选地，所述的诊断试剂盒中还包括内参GAPDH的qPCR引物。
上述任一所述的诊断试剂盒中还包括qRT-PCR所需的酶。
一种诊断预示Luminal A型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集Luminal A型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对于内参GAPDH的相对表达水平，依次用X 3、X 1、X 2表示；
步骤S3，将X 3、X 1、X 2值代入二元逻辑回归方程Y＝-2.577+2.045X 1+1.956X 2+1.676X 3得到Y值，Y值大于0.598预示该乳腺癌患者发生骨转移，小于0.598预示未发生骨转移。
二、Luminal B型乳腺癌骨转移
一种lncRNA诊断组合物，由lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452组成。
上述诊断组合物在制备诊断预示Luminal B型乳腺癌骨转移的诊断试剂盒方面的应用。
用于诊断预示Luminal B型乳腺癌骨转移的诊断试剂盒，包括lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452的qPCR引物。
优选地，所述的诊断试剂盒中，还包括内参GAPDH的qPCR引物。
上述任一所述的诊断试剂盒还包括qRT-PCR所需的酶。
一种诊断预示Luminal B型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集Luminal B型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对于内参GAPDH的相对表达水平，用X 3、X 1、X 2表示；
步骤S3，将X 3、X 1、X 2值代入二元逻辑回归方程Y＝Y＝-2.241+1.883X 1+2.275X 2+1.975X 3得到Y值，Y值大于0.607预示该乳腺癌患者发生骨转移，小于0.607预示未发生骨转移。
三、Her-2过表达型乳腺癌骨转移
一种lncRNA诊断组合物，由lncRNA AK043773和lncRNA EXOC7组成。
上述诊断组合物在制备诊断预示Her-2过表达型乳腺癌骨转移的诊断试剂盒方面的应用。
一种用于诊断预示Her-2过表达型乳腺癌骨转移的诊断试剂盒，包括lncRNA AK043773和lncRNA EXOC7的qPCR引物。
优选地，所述的诊断试剂盒中，还包括内参GAPDH的qPCR引物。
上述任一所述的诊断试剂盒还包括qRT-PCR所需的酶。
一种诊断预示Her-2过表达型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集Her-2过表达型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA AK043773和lncRNA EXOC7相对于内参GAPDH的相对表达水平，依次用X 1、X 2表示；
步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝-2.918+2.618X 1+2.115X 2得到Y值，Y值大于0.495预示该乳腺癌患者发生骨转移，小于0.495预示未发生骨转移。
四、三阴性乳腺癌骨转移
一种lncRNA诊断组合物，由lncRNA Lnc01089和lncRNA HOTAIR组成。
上述诊断组合物在制备诊断预示三阴性型乳腺癌骨转移的诊断试剂盒方面的应用。
一种用于诊断预示三阴性型乳腺癌骨转移的诊断试剂盒，包括lncRNA Lnc01089和lncRNA HOTAIR的qPCR引物。
优选地，所述的诊断试剂盒中，还包括内参GAPDH的qPCR引物。
上述任一所述的诊断试剂盒还包括qRT-PCR所需的酶。
一种诊断预示三阴性型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集三阴性型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA Lnc01089和lncRNA HOTAIR相对于内参GAPDH的相对表达水平，依次用X 1、X 2表示；
步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝-2.537+2.793X 1+2.181X 2得到Y值，Y值大于0.633预示该乳腺癌患者发生骨转移，小于0.633预示未发生骨转移。
本发明的上述目的是通过下面的技术方案得以实现的(甲基化基因组合物部分)：
一、 Luminal A型乳腺癌骨转移
一种甲基化基因诊断组合物，由甲基化PITX1和甲基化AMOT组成。
上述诊断组合物在制备诊断预示Luminal A型乳腺癌骨转移的诊断试剂盒方面的应用。
一种用于诊断预示Luminal A型乳腺癌骨转移的诊断试剂盒，包括甲基化PITX1和甲基化AMOT的PCR扩增引物。
优选地，所述的诊断试剂盒中还包括甲基化PITX1和甲基化AMOT的焦磷酸测序引物。
优选地，所述的诊断试剂盒中，还包括PCR扩增和焦磷酸测序所需的酶和试剂。
一种诊断预示Luminal A型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集Luminal A型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化PITX1和甲基化AMOT的甲基化指数，依次用X 1、X 2表示；
步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝1/[1+EXP(1.499X 1+2.302X 2-0.258)]得到Y值，Y值小于0.238预示该乳腺癌患者发生骨转移，大于0.238预示未发生骨转移。
二、Luminal B型乳腺癌骨转移
一种甲基化基因诊断组合物，由甲基化PTPN1和甲基化SLIT2组成。
上述诊断组合物在制备诊断预示Luminal B型乳腺癌骨转移的诊断试剂盒方面的应用。
一种用于诊断预示Luminal B型乳腺癌骨转移的诊断试剂盒，包括甲基化PTPN1和甲基化SLIT2的PCR扩增引物。
优选地，所述的诊断试剂盒中，还包括甲基化PTPN1和甲基化SLIT2的焦磷酸测序引物。
优选地，所述的诊断试剂盒中，还包括PCR扩增和焦磷酸测序所需的酶和试剂。
一种诊断预示Luminal B型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集Luminal B型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化PTPN1和甲基化SLIT2的甲基化指数，依次用X 1、X 2表示；
步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝1/[1+EXP(2.016X 1+1.898X 2-0.455)]得到Y值，Y值小于0.310预示该乳腺癌患者发生骨转移，大于0.310预示未发生骨转移。
三、 Her-2过表达型乳腺癌骨转移
一种甲基化基因组合物，由甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1组成。
上述诊断组合物在制备诊断预示Her-2过表达型乳腺癌骨转移的诊断试剂盒方面的应用。
一种用于诊断预示Her-2过表达型乳腺癌骨转移的诊断试剂盒，包括甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的PCR扩增引物和焦磷酸测序引物。
优选地，所述的诊断试剂盒中，还包括PCR扩增和焦磷酸测序所需的酶和试剂。
一种诊断预示Her-2过表达型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集Her-2过表达型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数，依次为X 1、X 2、X 3；
步骤S3，将X 1、X 2、X 3代入方程Y＝1/[1+EXP(1.342X 1+1.401X 2+1.345X 3-2.035)]得到Y值，Y值小于0.308预示该乳腺癌患者发生骨转移，大于0.308预示未发生骨转移。
四、 三阴性乳腺癌骨转移
一种甲基化基因诊断组合物，由甲基化MYLK3和甲基化SCARA5组成。
上述诊断组合物在制备诊断预示三阴性型乳腺癌骨转移的诊断试剂盒方面的应用。
一种用于诊断预示三阴性型乳腺癌骨转移的诊断试剂盒，包括甲基化MYLK3和甲基化SCARA5的PCR扩增引物。
优选地，所述诊断试剂盒中还包括甲基化MYLK3和甲基化SCARA5的焦磷酸测序引物。
优选地，所述的诊断试剂盒中，还包括PCR扩增和焦磷酸测序所需的酶和试剂。
一种诊断预示三阴性型乳腺癌骨转移的方法，包括如下步骤：
步骤S1，采集三阴性型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化MYLK3和甲基化SCARA5的甲基化指数，依次用X 1、X 2表示；
步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝1/[1+EXP(1.775X 1+1.236X 2-0.398)]得到Y值，Y值小于0.366预示该乳腺癌患者发生骨转移，大于0.366预示未发生骨转移。
附图说明
图1为测试集中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1联合用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线；
图2为验证集中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1联合用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的准确率；
图3为测试集中lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452联合用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线；
图4为验证集中lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452联合用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的准确率；
图5为测试集中lncRNA AK043773和lncRNA EXOC7联合用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线；
图6为验证集中lncRNA AK043773和lncRNA EXOC7联合用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的准确率；
图7为测试集中lncRNA Lnc01089和lncRNA HOTAIR联合用于诊断区分三阴性型乳腺 癌未转移和三阴性型乳腺癌骨转移的ROC曲线；
图8为验证集中lncRNA Lnc01089和lncRNA HOTAIR联合诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的准确率；
图9为测试集中甲基化PITX1和甲基化AMOT联合用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线；
图10为验证集中甲基化PITX1和甲基化AMOT联合用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的准确率；
图11为测试集中甲基化PTPN1和甲基化SLIT2联合用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线；
图12为验证集中甲基化PTPN1和甲基化SLIT2联合用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的准确率；
图13为测试集中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1联合用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线；
图14为验证集中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1联合用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的准确率；
图15为测试集中甲基化MYLK3和甲基化SCARA5联合用于诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的ROC曲线；
图16为验证集中甲基化MYLK3和甲基化SCARA5联合诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的准确率。
具体实施方式
下面结合附图和实施例具体介绍本发明实质性内容，但并不以此限定本发明的保护范围。
第一部分：lncRNA诊断组合物及诊断方法
本项目所有乳腺癌样本均取自2014年9月至2017年9月来南通大学附属医院或南通市第一人民医院或南京鼓楼医院检查确诊为乳腺癌且不合并其他恶性肿瘤的患者。所有样本根据免疫组化检测分为Luminal A型、Luminal B型、Her-2过表达型和三阴性型，各种分子亚型根据是否转移分为乳腺癌未转移组和乳腺癌骨转移组，且乳腺癌骨转移组各病例均属于骨为首发远处转移部位。乳腺癌未转移组和乳腺癌骨转移组经过放射性核素骨扫描(ECT)、电子计算机断层扫描(CT)、核磁共振(MRI)、正电子发射计算机断层扫描(PET-CT)和/或组织活检等检查证实。各分子亚型中乳腺癌未转移组和骨转移组患者年龄比较无明显差异，具有可比性。最后将各组样本随机对半均分为测试集和验证集。
所有样本分组信息及样本数经上述金标准诊断后如下表所示：
Figure PCTCN2018072269-appb-000001
血清标本的收集：采集患者空腹静脉血5.0mL，自然凝固后离心(4000r/min，2860×g) 7min后分离出血清，置于-80℃保存，用于检测血清中目标lncRNA的相对表达量。
实施例1：Luminal A型乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
Luminal A型中乳腺癌未转移组、Luminal A型乳腺癌骨转移组的测试集和验证集。
2、RNA抽提与qRT-PCR
应用Trizol试剂(Invitrogen，中国上海)从血清样本中提取总RNA。用NanoDrop ND-2000分光光度计(Thermo Scientific)在260nm处测定总RNA的浓度和纯度，电泳检测显示，提纯的RNA质量良好后进行后续操作。应用反转录试剂盒(Takara，中国大连)将总RNA转化为cDNA。采用SYBR Green法进行荧光定量PCR(Takara，中国大连)，并应用ABI Prism7000荧光定量PCR***(Agilent Technologies)进行数据收集。引物由博尚生物(中国上海)合成，lncRNA XLOC_004122引物序列：上游5’-CTGGCAGGAACACCGGGTACTT-3’，下游5’-TGACTTTTACTTAGGAGCCACTTCTTG-3’；lncRNA SUMO1P3引物序列：上游5’-CTGGAACTGGGAATGGAGGAAGA-3’，下游5’-GATTGAGAAAGGATTGAGGGAAA-3’；lncRNANBAT-1引物序列：上游5’-CTGGGAAAGCCTGTGCTCTTGGA-3’，下游5’-GCTTCACAGTGCTGCTCAATCGT-3’；GAPDH引物序列：上游5’-CGCTCTCTGCTCCTCCTGTTC-3’，下游5’-ATCCGTTGACTCCGACCTTCAC-3’。取3次测量的平均值用2 -ΔΔCt法计算lncRNAXLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1的相对表达量。
3、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(area under the curve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、Luminal A型乳腺癌未转移和骨转移组lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对表达水平
在测试集中，分别测定各样本中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对表达水平。与Luminal A型乳腺癌未转移组相比，Luminal A型乳腺癌骨转移组样本中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对表达水平显著上调，骨转移组lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对表达水平分别为未转移组相对表达水平的(1.9±0.4)倍、(2.3±0.5)倍、(2.5±0.4)倍。
2、lncRNA XLOC_004122、lncRNA SUMO1P3或lncRNA NBAT-1相对表达水平单独用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线分析
ROC曲线评价法的原理：
诊断试验的基本评价指标有敏感度、特异性等，综合评价指标有Youden指数、ROC、AUC等。对于诊断试验的评价，首先需要通过金标准知道待测样本的真实组别。对于按金标准确定的疾病组(相当于本发明中的乳腺癌骨转移组)和健康组(相当于本发明中的乳腺癌未转移组)，采用诊断试验检测的结果可以分为如下情况：
阳性(True Positive,TP)；诊断试验检测为阳性(与金标准结果一致)；
阴性(True Negative,TN)；诊断试验检测为阴性(与金标准结果一致)；
假阳性(False Positive,FP)：诊断试验检测为阳性(与金标准结果不一致)；
假阴性(False Negative,FN)：诊断试验检测为阴性(与金标准结果不一致)。
可以用下表表示：
Figure PCTCN2018072269-appb-000002
诊断试验的敏感度＝A/(A+C)；诊断试验的特异性＝D/(B+D)。通过敏感度和特异性可以得出诊断试验相对于金标准的诊断灵敏程度和特异程度。敏感度高代表将疾病例诊断为阴性的个数少，漏诊率低；特异性高代表将健康例诊断为阳性的个数少，误诊率低。
ROC曲线正是基于上述敏感度和特异性绘制出的曲线。以诊断试验中可能的诊断界值作为诊断点，根据上述表格计算出相应的敏感度和特异性。然后，以敏感度为纵坐标，1-特异性为横坐标，将各诊断点时各点的敏感度和特异性点在坐标图中标出，连接坐标点得到平滑曲线，该曲线即为ROC曲线。诊断点设置的越多越密，得到的ROC曲线就越平滑。
ROC曲线是以每一个检测结果作为可能的诊断界值，其曲线下面积AUC的大小表明了诊断试验准确度的大小。ROC曲线下面积AUC作为诊断试验真实性评价的固有准确度指标已被普遍认可，AUC为0.5时，即无诊断意义；AUC在0.5～0.7时，表示诊断准确率较低；AUC在0.7～0.9时，表示诊断准确性中等；AUC＞0.9时，表示诊断有较高的准确性。
在SPSS 19.0中绘制lncRNA XLOC_004122、lncRNA SUMO1P3或lncRNA NBAT-1相对表达水平单独用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线，AUC分别为0.601、0.697、0.729，具有较低或中等的准确性。
3、lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对表达水平联合诊断模型的构建及用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线分析
以测试集样本中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1的相对表达水平作为自变量(设X 1＝lncRNA SUMO1P3相对表达水平，X 2＝lncRNA NBAT-1相对表达水平，X 3＝lncRNA XLOC_004122相对表达水平)，以组别(即根据金标准该样本属于骨转移组还是未转移组)作为应变量，对lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1在Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移样本中的相对表达水平进行二元逻辑回归，得到二元逻辑回归方程：Y＝-2.577+2.045X 1+1.956X 2+1.676X 3；再将各样本中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1的相对表达水平代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算灵敏度和特异性，据此绘制ROC曲线(如图1所示)，AUC为0.921，具有较高的准确性。根据ROC曲线的坐标计算维登指数＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能进行诊 断区分Luminal A型乳腺癌未转移组和骨转移组的最佳cut-off值0.598(即诊断阈值)。
4、验证集中验证lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对表达水平联合诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的准确程度
在验证集中，将各样本lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对表达水平代入上述回归模型，得到各样本的回归值Y，Y高于诊断阈值0.598的预测为Luminal A型乳腺癌骨转移，低于诊断阈值0.598的预测为Luminal A型乳腺癌未转移，准确度为98.2％(108/110)，如图2所示。
实施例2：Luminal B型乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
Luminal B型中乳腺癌未转移组、Luminal B型乳腺癌骨转移组的测试集和验证集。
2、RNA抽提与qRT-PCR
应用Trizol试剂(Invitrogen，中国上海)从血清样本中提取总RNA。用NanoDrop ND-2000分光光度计(Thermo Scientific)在260nm处测定总RNA的浓度和纯度，电泳检测显示，提纯的RNA质量良好后进行后续操作。应用反转录试剂盒(Takara，中国大连)将总RNA转化为cDNA。采用SYBR Green法进行荧光定量PCR(Takara，中国大连)，并应用ABI Prism7000荧光定量PCR***(Agilent Technologies)进行数据收集。引物由博尚生物(中国上海)合成，lncRNA XLOC_004122引物序列：上游5’-CTGGCAGGAACACCGGGTACTT-3’，下游5’-TGACTTTTACTTAGGAGCCACTTCTTG-3’；lncRNA Linc00467引物序列：上游5’-GCCTG GTTGTTCAGCACCTTCG-3’，下游5’-TCGGATCGGTGCTGGTTTTGGT-3’；lncRNA Al049452引物序列：上游5’-CAGTTAAACCCACAGGTGGTAGCATGAC-3’，下游5’-TAGTGGGAAAA CCTAGTTTCCGACAGTT-3’；GAPDH引物序列：上游5’-CGCTCTCTGCTCCTCCTGTTC-3’，下游5’-ATCCGTTGACTCCGACCTTCAC-3’。取3次测量的平均值用2 -ΔΔCt法计算lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452的相对表达量。
3、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(area under the curve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、Luminal B型乳腺癌未转移和骨转移组lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对表达水平
在测试集中，分别测定各样本的lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对表达水平。与Luminal B型乳腺癌未转移组相比，Luminal B型乳腺癌骨转移组样本中lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对表达水平显著上调，骨转移组lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对表达水平分别为未转移组相对表达水平的(2.2±0.4)倍、(2.7±0.3)倍、(2.3±0.3)倍。
2、lncRNA XLOC_004122、lncRNA Linc00467或lncRNA Al049452相对表达水平单独用 于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线分析
在SPSS 19.0中绘制lncRNA XLOC_004122、lncRNA Linc00467或lncRNA Al049452相对表达水平单独用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线，AUC分别为0.687、0.744、0.706，具有较低或中等的准确性。
3、lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对表达水平联合诊断模型的构建及用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线分析
以测试集样本中lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452的相对表达水平作为自变量(设X 1＝lncRNA Linc00467相对表达水平，X 2＝lncRNA Al049452相对表达水平，X 3＝lncRNA XLOC_004122相对表达水平)，以组别(即根据金标准该样本属于骨转移组还是未转移组)作为应变量，对lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452在Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移样本中的相对表达水平进行二元逻辑回归，得到二元逻辑回归方程：Y＝-2.241+1.883X 1+2.275X 2+1.975X 3；再将各样本中lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452的相对表达水平代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算灵敏度和特异性，据此绘制ROC曲线(如图3所示)，AUC为0.935，具有较高的准确性。根据ROC曲线的坐标计算维登指数＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能进行诊断区分Luminal B型乳腺癌未转移组和骨转移组的最佳cut-off值0.607(即诊断阈值)。
4、验证集中验证lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对表达水平联合诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的准确程度
在验证集中，将各样本lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对表达水平代入上述回归模型，得到各样本的回归值Y，Y高于诊断阈值0.607的预测为Luminal B型乳腺癌骨转移，低于诊断阈值0.607的预测为Luminal B型乳腺癌未转移，准确度为95.2％(60/63)，如图4所示。
实施例3：Her-2过表达型乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
Her-2过表达型中乳腺癌未转移组、Her-2过表达型乳腺癌骨转移组的测试集和验证集。
2、RNA抽提与qRT-PCR
应用Trizol试剂(Invitrogen，中国上海)从血清样本中提取总RNA。用NanoDrop ND-2000分光光度计(Thermo Scientific)在260nm处测定总RNA的浓度和纯度，电泳检测显示，提纯的RNA质量良好后进行后续操作。应用反转录试剂盒(Takara，中国大连)将总RNA转化为cDNA。采用SYBR Green法进行荧光定量PCR(Takara，中国大连)，并应用ABI Prism7000荧光定量PCR***(Agilent Technologies)进行数据收集。引物由博尚生物(中国上海)合成，lncRNA AK043773引物序列：上游5’-GTGACGCCAGGGATGGCATTA-3’，下游5’-CAG AGCCTTGCATTGGTCAGT-3’；lncRNA EXOC7引物序列：上游5’-GAGTCTGGGATCAGAGA GCAAAGG-3’，下游5’-GGTACTGTAGAAAGGCCCCGTAGG-3’；GAPDH引物序列：上游5’-C GCTCTCTGCTCCTCCTGTTC-3’，下游5’-ATCCGTTGACTCCGACCTTCAC-3’。取3次测量 的平均值用2 -ΔΔCt法计算lncRNA AK043773和lncRNA EXOC7的相对表达量。
3、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(area under the curve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、Her-2过表达型乳腺癌未转移组和骨转移组lncRNA AK043773和lncRNA EXOC7相对表达水平
在测试集中，分别测定各样本的lncRNA AK043773和lncRNA EXOC7相对表达水平。与Her-2过表达型乳腺癌未转移组相比，Her-2过表达型乳腺癌骨转移组样本中lncRNA AK043773和lncRNA EXOC7相对表达水平显著上调，骨转移组lncRNA AK043773和lncRNA EXOC7相对表达水平分别为未转移组的(3.3±0.5)倍、(2.6±0.3)倍。
2、lncRNA AK043773或lncRNA EXOC7相对表达水平单独用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线分析
在SPSS 19.0中绘制lncRNA AK043773或lncRNA EXOC7相对表达水平单独用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线，AUC分别为0.762、0.717，具有中等的准确性。
3、lncRNA AK043773和lncRNA EXOC7相对表达水平联合诊断模型的构建及用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线分析
以测试集样本中lncRNA AK043773和lncRNA EXOC7的相对表达水平作为自变量(设X 1＝lncRNA AK043773相对表达水平，X 2＝lncRNA EXOC7相对表达水平)，以组别(即根据金标准该样本属于骨转移组还是未转移组)作为应变量，对lncRNA AK043773和lncRNA EXOC7在Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移样本中的相对表达水平进行二元逻辑回归，得到二元逻辑回归方程：Y＝-2.918+2.618X 1+2.115X 2；再将各样本中lncRNA AK043773和lncRNA EXOC7的相对表达水平代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算灵敏度和特异性，据此绘制ROC曲线(如图5所示)，AUC为0.939，具有较高的准确性。进一步根据ROC曲线的坐标计算维登指数＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能诊断区分Her-2过表达型乳腺癌未转移组和骨转移组的最佳cut-off值0.495(即诊断阈值)。
4、验证集中验证lncRNA AK043773和lncRNA EXOC7相对表达水平联合诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的准确程度
在验证集中，将各样本lncRNA AK043773和EXOC7相对表达水平代入上述回归模型，得到各样本的回归值Y，Y高于诊断阈值0.495的预测为Her-2过表达型乳腺癌骨转移，低于诊断阈值0.495的预测为Her-2过表达型乳腺癌未转移，准确度为91.1％(51/56)，如图6。
实施例4：三阴性乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
三阴性型中乳腺癌未转移组、三阴性型乳腺癌骨转移组的测试集和验证集。
2、RNA抽提与qRT-PCR
应用Trizol试剂(Invitrogen，中国上海)从血清样本中提取总RNA。用NanoDrop ND-2000分光光度计(Thermo Scientific)在260nm处测定总RNA的浓度和纯度，电泳检测显示，提纯的RNA质量良好后进行后续操作。应用反转录试剂盒(Takara，中国大连)将总RNA转化为cDNA。采用SYBR Green法进行荧光定量PCR(Takara，中国大连)，并应用ABI Prism 7000荧光定量PCR***(Agilent Technologies)进行数据收集。引物由博尚生物(中国上海)合成，lncRNA Lnc01089引物序列：上游5’-TCGCTGGGTTGCTCTGCTTC-3’，下游5’-GTCAGGAGGTCACAGTCTTAGGG-3’；lncRNA HOTAIR引物序列：上游5’-CGTGGAAAGATCCAAATGGGACCA-3’，下游5’-AGCCTAGGAATCAGCACGAAGCAAA-3’；GAPDH引物序列：上游5’-CGCTCTCTGCTCCTCCTGTTC-3’，下游5’-ATCCGTTGACTCCGACCTTCAC-3’。取3次测量的平均值用2 -ΔΔCt法计算lncRNA Lnc01089和lncRNA HOTAIR的相对表达量。
3、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(area under the curve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、三阴性型乳腺癌未转移组和骨转移组lncRNA Lnc01089和HOTAIR相对表达水平
在测试集中，分别测定各样本的lncRNA Lnc01089和lncRNA HOTAIR相对表达水平。与三阴性型乳腺癌未转移组相比，三阴性型乳腺癌骨转移组样本中lncRNA Lnc01089和lncRNA HOTAIR相对表达水平显著上调，骨转移组lncRNA Lnc01089和lncRNA HOTAIR相对表达水平分别为未转移组的(3.5±0.6)倍、(3.2±0.5)倍。
2、lncRNA Lnc01089或lncRNA HOTAIR相对表达水平单独用于诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的ROC曲线分析
在SPSS 19.0中绘制lncRNA Lnc01089或lncRNA HOTAIR相对表达水平单独用于诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的ROC曲线，AUC分别为0.755、0.732，均具有中等的准确性。
3、lncRNA Lnc01089和lncRNA HOTAIR相对表达水平联合诊断模型的构建及用于诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的ROC曲线分析
以测试集样本中lncRNA Lnc01089和lncRNA HOTAIR的相对表达水平作为自变量(设X 1＝lncRNA Lnc01089相对表达水平，X 2＝lncRNA HOTAIR相对表达水平)，以组别(即根据金标准该样本属于骨转移组还是未转移组)作为应变量，对lncRNA Lnc01089和lncRNA HOTAIR在三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移样本中的相对表达水平进行二元逻辑回归，得到二元逻辑回归方程：Y＝-2.537+2.793X 1+2.181X 2；再将各样本中lncRNA Lnc01089和lncRNA HOTAIR的相对表达水平代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算灵敏度和特异性，据此绘制ROC曲线(如图7所示)，AUC为0.948，具有较高的准确性。进一步根据ROC曲线的坐标计算维登指数 ＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能进行诊断区分三阴性型乳腺癌未转移组和骨转移组的最佳cut-off值0.633(即诊断阈值)。
4、验证集中验证lncRNA Lnc01089和lncRNA HOTAIR相对表达水平联合诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的准确程度
在验证集中，将各样本lncRNA Lnc01089和lncRNA HOTAIR相对表达水平代入上述回归模型，得到各样本的回归值Y，Y高于诊断阈值0.633的预测为三阴性型乳腺癌骨转移，低于诊断阈值0.633的预测为三阴性型乳腺癌未转移，准确度为92.9％(52/56)，如图8。
综上可知，本发明发现，血清lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1可以联合用于诊断预示Luminal A型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上；血清lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452可以联合用于诊断预示Luminal B型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上；血清lncRNA AK043773和lncRNA EXOC7可以联合用于诊断预示Her-2过表达型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上；lncRNA Lnc01089和lncRNA HOTAIR可以联合用于诊断预示三阴性型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上。使用上述血清lncRNA诊断预示不同分子亚型乳腺癌骨转移不仅准确度高，而且检测成本低、非介入性、方便快捷，极大降低患者痛苦和负担。
第二部分：甲基化基因诊断组合物及诊断方法
实验样本同第一部分。血清标本收集：采集患者空腹静脉血5.0mL，自然凝固后离心(4000r/min，2860×g)7min后分离出血清，置-80℃保存，用于检测血清中目标甲基化基因。
实施例5：Luminal A型乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
Luminal A型中乳腺癌未转移组、Luminal A型乳腺癌骨转移组的测试集和验证集。
2、血清总DNA提取
血清DNA提取按照DNA Blood Midi Kit说明书进行，每份样本采用0.8mL血清。提取的DNA纯度用紫外分光光度计检测，吸光度A260/A280比值在1.7-2.0之间进行后续操作。计算DNA含量，-70℃保存备用。
3、DNA亚硫酸盐修饰和焦磷酸测序检测
DNA亚硫酸盐修饰：
取1μg DNA，按照DNA Methylation-Goldkit说明书对基因组DNA进行甲基化修饰后，-70℃保存备用。多聚酶链式反应：采用PCR对样品中PITX1和AMOT基因启动子甲基化区域进行扩增。反应体系包括亚硫酸盐处理后模板2μl，10×PCR buffer，0.25U/μl Hot star Taq酶，0.5mmol/L dNTP，上下游引物各1μl，总体积50μl。以双蒸水作为空白对照。
焦磷酸测序检测：
(1)分别取45μl PCR扩增产物至PSQ 96Plate Low样品制备板A中，各加入45μl结合缓冲液和8μl包被有链亲和素的磁珠，43℃振荡25min。将结合PCR产物的磁珠转移至变性缓冲液的板B中，使双链DNA充分变性。转移结合有单链PCR产物的磁珠至150μl退火缓冲液的板C涡旋振荡洗涤3min。
(2)测序引物杂交：将结合单链PCR产物的磁珠转入50μl复性缓冲液中，加入10μl测序引物，75℃杂交7min。
(3)使用PSQ96焦磷酸测序仪和测序反应试剂盒(PyroGoldReagents)，分别检测PITX1和AMOT启动子区域内甲基化位点的碱基频率。
其中PCR扩增引物和测序引物如下：
PITX1
上游5’-GGAAGGTATTTAGTATAGGTGAGTTTGA-3’
下游5’-AAACCTTAATATTCACTACACTTTATC-3’
测序5’-GTGTTTATTTTGGATTGTTTAATT-3’
AMOT
上游5’-TGAGTTAATATGAAAGAAGATAGTA-3’
下游5’-TGATCTCTACATCTCAACTAATATAC-3’
测序5’-GTAGGTTTATTTAGGTT-3’
通过使用焦磷酸测序仪中等位基因频率分析功能对各甲基化位点进行分析。按照如下公式计算各基因启动子区域的甲基化指数，该指数可以反映该基因启动子区域的甲基化程度：
Figure PCTCN2018072269-appb-000003
4、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(areaunderthecurve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、Luminal A型乳腺癌未转移和骨转移组甲基化PITX1和甲基化AMOT的甲基化程度
在测试集中，分别测定各样本中甲基化PITX1和甲基化AMOT的甲基化指数。与Luminal A型乳腺癌未转移组相比，Luminal A型乳腺癌骨转移组样本中甲基化PITX1和甲基化AMOT的甲基化指数显著升高，骨转移组甲基化PITX1和甲基化AMOT的甲基化指数分别为未转移组甲基化指数的(3.5±0.4)倍、(3.3±0.5)倍。
2、甲基化PITX1和甲基化AMOT的甲基化指数单独用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线分析
在SPSS 19.0中绘制甲基化PITX1和甲基化AMOT的甲基化指数单独用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线，AUC分别为0.715、0.707，具有中等的准确性。
3、甲基化PITX1和甲基化AMOT的甲基化指数联合诊断模型的构建及用于诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的ROC曲线分析
以测试集样本中甲基化PITX1和甲基化AMOT的甲基化指数作为自变量(设X 1＝甲基化PITX1的甲基化指数，X 2＝甲基化AMOT的甲基化指数)，以组别(即根据金标准该样本属 于骨转移组还是未转移组)作为应变量，对甲基化PITX1和甲基化AMOT在Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移样本中的甲基化指数进行二元逻辑回归，得到二元逻辑回归方程：Y＝1/[1+EXP(1.499X 1+2.302X 2-0.258)]；
再将各样本中甲基化PITX1和甲基化AMOT的甲基化指数代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算灵敏度和特异性，据此绘制ROC曲线(如图9所示)，AUC为0.935，具有较高的准确性。根据ROC曲线的坐标计算维登指数＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能进行诊断区分Luminal A型乳腺癌未转移组和骨转移组的最佳cut-off值0.238(即诊断阈值)。
4、验证集中验证甲基化PITX1和甲基化AMOT的甲基化指数联合诊断区分Luminal A型乳腺癌未转移和Luminal A型乳腺癌骨转移的准确程度
在验证集中，将各样本甲基化PITX1和甲基化AMOT的甲基化指数代入上述回归模型，得到各样本的回归值Y，Y低于诊断阈值0.238的预测为Luminal A型乳腺癌骨转移，高于诊断阈值0.238的预测为Luminal A型乳腺癌未转移，准确度为95.5％(105/110)，如图10。
实施例6：Luminal B型乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
Luminal B型中乳腺癌未转移组、Luminal B型乳腺癌骨转移组的测试集和验证集。
2、血清总DNA提取
血清DNA提取按照DNA Blood Midi Kit说明书进行，每份样本采用0.8mL血清。提取的DNA纯度用紫外分光光度计检测，吸光度A260/A280比值在1.7-2.0之间进行后续操作。计算DNA含量，-70℃保存备用。
3、DNA亚硫酸盐修饰和焦磷酸测序检测
DNA亚硫酸盐修饰：
取1μg DNA，按照DNA Methylation-Goldkit说明书对基因组DNA进行甲基化修饰后，-70℃保存备用。多聚酶链式反应：采用PCR对样品中PTPN1和SLIT2基因启动子甲基化区域进行扩增。反应体系包括亚硫酸盐处理后模板2μl，10×PCR buffer，0.25U/μl Hot star Taq酶，0.5mmol/L dNTP，上下游引物各1μl，总体积50μl。以双蒸水作为空白对照。
焦磷酸测序检测：
(1)分别取45μl PCR扩增产物至PSQ 96Plate Low样品制备板A中，各加入45μl结合缓冲液和8μl包被有链亲和素的磁珠，43℃振荡25min。将结合PCR产物的磁珠转移至变性缓冲液的板B中，使双链DNA充分变性。转移结合有单链PCR产物的磁珠至150μl退火缓冲液的板C涡旋振荡洗涤3min。
(2)测序引物杂交：将结合单链PCR产物的磁珠转入50μl复性缓冲液中，加入10μl测序引物，75℃杂交7min。
(3)使用PSQ96焦磷酸测序仪和测序反应试剂盒(Pyro Gold Reagents)，分别检测PTPN1和SLIT2启动子区域内甲基化位点的碱基频率。
其中PCR扩增引物和测序引物如下：
PTPN1
上游5’-AGCGGGTTAGAGGGTAGATGT-3’
下游5’-TAGGTTTCTCCTCTCCCACATAT-3’
测序5’-TTTCCATTCATCCTAA-3’
SLIT2
上游5’-TGAAGTTTTATTAGGTTGTGGAGGAGTA-3’
下游5’-ATACCAAATATCCTATCCTTATCTTC-3’
测序5’-GTTTAAGGTTTATGATA-3’
通过使用焦磷酸测序仪中等位基因频率分析功能对各甲基化位点进行分析。按照如下公式计算各基因启动子区域的甲基化指数，该指数可以反映该基因启动子区域的甲基化程度：
Figure PCTCN2018072269-appb-000004
4、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(area under the curve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、Luminal B型乳腺癌未转移和骨转移组甲基化PTPN1和甲基化SLIT2的甲基化程度
在测试集中，分别测定各样本中甲基化PTPN1和甲基化SLIT2的甲基化指数。与Luminal B型乳腺癌未转移组相比，Luminal B型乳腺癌骨转移组样本中甲基化PTPN1和甲基化SLIT2的甲基化指数显著升高，骨转移组甲基化PTPN1和甲基化SLIT2的甲基化指数分别为未转移组甲基化指数的(2.9±0.5)倍、(3.4±0.5)倍。
2、甲基化PTPN1和甲基化SLIT2的甲基化指数单独用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线分析
在SPSS 19.0中绘制甲基化PTPN1和甲基化SLIT2的甲基化指数单独用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线，AUC分别为0.723、0.741，具有中等的准确性。
3、甲基化PTPN1和甲基化SLIT2的甲基化指数联合诊断模型的构建及用于诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的ROC曲线分析
以测试集样本中甲基化PTPN1和甲基化SLIT2的甲基化指数作为自变量(设X 1＝甲基化PTPN1的甲基化指数，X 2＝甲基化SLIT2的甲基化指数)，以组别(即根据金标准该样本属于骨转移组还是未转移组)作为应变量，对甲基化PTPN1和甲基化SLIT2在Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移样本中的甲基化指数进行二元逻辑回归，得到二元逻辑回归方程：Y＝1/[1+EXP(2.016X 1+1.898X 2-0.455)]；
再将各样本中甲基化PTPN1和甲基化SLIT2的甲基化指数代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算灵敏度和特异性，据此绘制ROC曲线(如图11所示)，AUC为0.942，具有较高的准确性。根据ROC曲线的坐标计 算维登指数＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能进行诊断区分Luminal B型乳腺癌未转移组和骨转移组的最佳cut-off值0.310(即诊断阈值)。
4、验证集中验证甲基化PTPN1和甲基化SLIT2的甲基化指数联合诊断区分Luminal B型乳腺癌未转移和Luminal B型乳腺癌骨转移的准确程度
在验证集中，将各样本甲基化PTPN1和甲基化SLIT2的甲基化指数代入上述回归模型，得到各样本的回归值Y，Y低于诊断阈值0.310的预测为Luminal B型乳腺癌骨转移，高于诊断阈值0.310的预测为Luminal B型乳腺癌未转移，准确度为93.7％(59/63)，如图12所示。
实施例7：Her-2过表达型乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
Her-2过表达型中乳腺癌未转移组、Her-2过表达型乳腺癌骨转移组的测试集和验证集。
2、血清总DNA提取
血清DNA提取按照DNA Blood Midi Kit说明书进行，每份样本采用0.8mL血清。提取的DNA纯度用紫外分光光度计检测，吸光度A260/A280比值在1.7-2.0之间进行后续操作。计算DNA含量，-70℃保存备用。
3、DNA亚硫酸盐修饰和焦磷酸测序检测
DNA亚硫酸盐修饰：
取1μg DNA，按照DNA Methylation-Goldkit说明书对基因组DNA进行甲基化修饰后，-70℃保存备用。多聚酶链式反应：采用PCR对样品中MYLK2、EFEMP1和SOSTDC1基因启动子甲基化区域进行扩增。反应体系包括亚硫酸盐处理后模板2μl，10×PCRbuffer，0.25U/μl Hot star Taq酶，0.5mmol/L dNTP，上下游引物各1μl，总体积50μl。
焦磷酸测序检测：
(1)分别取45μl PCR扩增产物至PSQ 96Plate Low样品制备板A中，各加入45μl结合缓冲液和8μl包被有链亲和素的磁珠，43℃振荡25min。将结合PCR产物的磁珠转移至变性缓冲液的板B中，使双链DNA充分变性。转移结合有单链PCR产物的磁珠至150μl退火缓冲液的板C涡旋振荡洗涤3min。
(2)测序引物杂交：将结合单链PCR产物的磁珠转入50μl复性缓冲液中，加入10μl测序引物，75℃杂交7min。
(3)使用PSQ96焦磷酸测序仪和测序反应试剂盒(Pyro Gold Reagents)，分别检测MYLK2、EFEMP1和SOSTDC1启动子区域内甲基化位点的碱基频率。
其中PCR扩增引物和测序引物如下：
MYLK2
上游5’-GAGGGAAAGGATATGGTTGATT-3’
下游5’-AACTCCACTCCATTCTCCC-3’
测序5’-AGTAAGTTATTTATTTGTTATTTG-3’
EFEMP1
上游5’-GGTTTAGGTGGGGAGTATGATAG-3’
下游5’-ACCAACAACCCAACTTTAACATAACC-3’
测序5’-TAATGAGGGGTTGAG-3’
SOSTDC1
上游5’-GTAAAGGAGAAAGTTTGGTATATGG-3’
下游5’-CAAAACTATACAAAAGTATCTCTCTCAAT-3’
测序5’-ATAATTTAATTGTTAGAGTTGAATA-3’
通过使用焦磷酸测序仪中等位基因频率分析功能对各甲基化位点进行分析。按照如下公式计算各基因启动子区域的甲基化指数，该指数可以反映该基因启动子区域的甲基化程度：
Figure PCTCN2018072269-appb-000005
4、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(area under the curve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、Her-2过表达型乳腺癌未转移和骨转移组甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化程度
在测试集中，分别测定各样本中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数。与Her-2过表达型乳腺癌未转移组相比，Her-2过表达型乳腺癌骨转移组样本中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数显著升高，分别为未转移组甲基化指数的(3.7±0.6)倍、(2.6±0.4)、(3.1±0.5)倍。
2、甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数单独用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线分析
在SPSS 19.0中绘制甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数单独用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线，AUC分别为0.794、0.688、0.738，具有较低或中等的准确性。
3、甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数联合诊断模型的构建及用于诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的ROC曲线分析
以测试集样本中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数作为自变量(设X 1＝甲基化MYLK2的甲基化指数，X 2＝甲基化EFEMP1的甲基化指数，X 3＝甲基化SOSTDC1的甲基化指数)，以组别(即根据金标准该样本属于骨转移组还是未转移组)作为应变量，对甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1在Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移样本中的甲基化指数进行二元逻辑回归，得到二元逻辑回归方程：Y＝1/[1+EXP(1.342X 1+1.401X 2+1.345X 3-2.035)]；
再将各样本中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算 灵敏度和特异性，据此绘制ROC曲线(如图13所示)，AUC为0.950，具有较高的准确性。根据ROC曲线的坐标计算维登指数＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能进行诊断区分Her-2过表达型乳腺癌未转移组和骨转移组的最佳cut-off值0.308(诊断阈值)。
4、验证集中验证甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数联合诊断区分Her-2过表达型乳腺癌未转移和Her-2过表达型乳腺癌骨转移的准确程度
在验证集中，将各样本甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数代入上述回归模型，得到各样本的回归值Y，Y低于诊断阈值0.308的预测为Her-2过表达型乳腺癌骨转移，高于诊断阈值0.308的预测为Her-2过表达型乳腺癌未转移，准确度为96.4％(54/56)，如图14所示。
实施例8：三阴性型乳腺癌骨转移
一、实验样本和实验方法
1、实验样本
三阴性型中乳腺癌未转移组、三阴性型乳腺癌骨转移组的测试集和验证集。
2、血清总DNA提取
血清DNA提取按照DNA Blood Midi Kit说明书进行，每份样本采用0.8mL血清。提取的DNA纯度用紫外分光光度计检测，吸光度A260/A280比值在1.7-2.0之间进行后续操作。计算DNA含量，-70℃保存备用。
3、DNA亚硫酸盐修饰和焦磷酸测序检测
DNA亚硫酸盐修饰：
取1μg DNA，按照DNA Methylation-Gold kit说明书对基因组DNA进行甲基化修饰后，-70℃保存备用。多聚酶链式反应：采用PCR对样品中MYLK3和SCARA5基因启动子甲基化区域进行扩增。反应体系包括亚硫酸盐处理后模板2μl，10×PCR buffer，0.25U/μl Hot star Taq酶，0.5mmol/L dNTP，上下游引物各1μl，总体积50μl。以双蒸水作为空白对照。
焦磷酸测序检测：
(1)分别取45μl PCR扩增产物至PSQ 96 Plate Low样品制备板A中，各加入45μl结合缓冲液和8μl包被有链亲和素的磁珠，43℃振荡25min。将结合PCR产物的磁珠转移至变性缓冲液的板B中，使双链DNA充分变性。转移结合有单链PCR产物的磁珠至150μl退火缓冲液的板C涡旋振荡洗涤3min。
(2)测序引物杂交：将结合单链PCR产物的磁珠转入50μl复性缓冲液中，加入10μl测序引物，75℃杂交7min。
(3)使用PSQ96焦磷酸测序仪和测序反应试剂盒(Pyro Gold Reagents)，分别检测MYLK3和SCARA5启动子区域内甲基化位点的碱基频率。
其中PCR扩增引物和测序引物如下：
MYLK3
上游5’-TAGGGGAGGTTAAGAAAGTGTA-3’
下游5’-AACTCCTTATCAATTCCTAACATACAAT-3’
测序5’-GGAGTAATGATGTAATGTGTAT-3’
SCARA5
上游5’-AGGAATTAGGTAAGGTATGTTAGTA-3’
下游5’-AAAACTCCAACCTATTCCAACCATACCTAC-3’
测序5’-GTTTTAAGTTTTGGTGTTTGATAT-3’
通过使用焦磷酸测序仪中等位基因频率分析功能对各甲基化位点进行分析。按照如下公式计算各基因启动子区域的甲基化指数，该指数可以反映该基因启动子区域的甲基化程度：
Figure PCTCN2018072269-appb-000006
4、统计学处理
数据采用SPSS 19.0进行分析。计量资料用均值±偏差表示，采用t检验，计数资料用百分率表示，采用χ 2检验，以P＜0.05为差异有统计学意义，并建立ROC曲线，计算曲线下面积(area under the curve，AUC)及95％可信区间。运用Logistic回归筛选变量，建立回归方程，产生一组新变量Y。对新变量及各单项指标进行ROC曲线分析。
二、实验结果
1、三阴性型乳腺癌未转移和骨转移组甲基化MYLK3和甲基化SCARA5的甲基化程度
在测试集中，分别测定各样本中甲基化MYLK3和甲基化SCARA5的甲基化指数。与三阴性型乳腺癌未转移组相比，三阴性型乳腺癌骨转移组样本中甲基化MYLK3和甲基化SCARA5的甲基化指数显著升高，骨转移组甲基化MYLK3和甲基化SCARA5的甲基化指数分别为未转移组甲基化指数的(2.1±0.3)倍、(3.6±0.7)倍。
2、甲基化MYLK3和甲基化SCARA5的甲基化指数单独用于诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的ROC曲线分析
在SPSS 19.0中绘制甲基化MYLK3和甲基化SCARA5的甲基化指数单独用于诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的ROC曲线，AUC分别为0.644、0.809，具有较低或中等的准确性。
3、甲基化MYLK3和甲基化SCARA5的甲基化指数联合诊断模型的构建及用于诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的ROC曲线分析
以测试集样本中甲基化MYLK3和甲基化SCARA5的甲基化指数作为自变量(设X 1＝甲基化MYLK3的甲基化指数，X 2＝甲基化SCARA5的甲基化指数)，以组别(即根据金标准该样本属于骨转移组还是未转移组)作为应变量，对甲基化MYLK3和甲基化SCARA5在三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移样本中的甲基化指数进行二元逻辑回归，得到二元逻辑回归方程：Y＝1/[1+EXP(1.775X 1+1.236X 2-0.398)]；
再将各样本中甲基化MYLK3和甲基化SCARA5的甲基化指数代入该二元逻辑回归方程，即可得到各个样本的回归值Y，以可能的回归值Y作为诊断点，计算灵敏度和特异性，据此绘制ROC曲线(如图15所示)，AUC为0.954，具有较高的准确性。根据ROC曲线的坐标计算维登指数＝特异性+灵敏度-1，维登指数最大值时对应的Y值为能进行诊断区分三阴性型乳腺癌未转移组和骨转移组的最佳cut-off值0.366(即诊断阈值)。
4、验证集中验证甲基化MYLK3和甲基化SCARA5的甲基化指数联合诊断区分三阴性型乳腺癌未转移和三阴性型乳腺癌骨转移的准确程度
在验证集中，将各样本甲基化MYLK3和甲基化SCARA5的甲基化指数代入上述回归模型，得到各样本的回归值Y，Y低于诊断阈值0.366的预测为三阴性型乳腺癌骨转移，高于诊断阈值0.366的预测为三阴性型乳腺癌未转移，准确度为94.6％(53/56)，如图16所示。
综上可知，本发明发现，血清甲基化PITX1和甲基化AMOT可以联合用于诊断预示Luminal A型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上；血清甲基化PTPN1和甲基化SLIT2可以联合用于诊断预示Luminal B型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上；血清甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1可以联合用于诊断预示Her-2过表达型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上；血清甲基化MYLK3和甲基化SCARA5可以联合用于诊断预示三阴性型乳腺癌是否骨转移，在独立验证集中诊断预示准确率达90％以上。使用上述血清甲基化基因诊断预示不同分子亚型乳腺癌骨转移不仅准确度高，而且检测成本低、非介入性、方便快捷，极大降低患者痛苦和负担。
上述实施例的作用在于具体介绍本发明的实质性内容，但本领域技术人员应当知道，不应将本发明的保护范围局限于该具体实施例。

Claims (16)

  1. 一种用于诊断预示Luminal A型乳腺癌骨转移的lncRNA诊断组合物，其特征在于：由lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1组成。
  2. 一种诊断预示Luminal A型乳腺癌骨转移的方法，其特征在于，包括如下步骤：
    步骤S1，采集Luminal A型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA XLOC_004122、lncRNA SUMO1P3和lncRNA NBAT-1相对于内参GAPDH的相对表达水平，依次用X 3、X 1、X 2表示；
    步骤S3，将X 3、X 1、X 2值代入二元逻辑回归方程Y＝-2.577+2.045X 1+1.956X 2+1.676X 3得到Y值，Y值大于0.598预示该乳腺癌患者发生骨转移，小于0.598预示未发生骨转移。
  3. 一种用于诊断预示Luminal B型乳腺癌骨转移的lncRNA诊断组合物，其特征在于：由lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452组成。
  4. 一种诊断预示Luminal B型乳腺癌骨转移的方法，其特征在于：包括如下步骤：
    步骤S1，采集Luminal B型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA XLOC_004122、lncRNA Linc00467和lncRNA Al049452相对于内参GAPDH的相对表达水平，用X 3、X 1、X 2表示；
    步骤S3，将X 3、X 1、X 2值代入二元逻辑回归方程Y＝Y＝-2.241+1.883X 1+2.275X 2+1.975X 3得到Y值，Y值大于0.607预示该乳腺癌患者发生骨转移，小于0.607预示未发生骨转移。
  5. 一种用于诊断预示Her-2过表达型乳腺癌骨转移lncRNA诊断组合物，其特征在于：由lncRNA AK043773和lncRNA EXOC7组成。
  6. 一种诊断预示Her-2过表达型乳腺癌骨转移的方法，其特征在于：包括如下步骤：
    步骤S1，采集Her-2过表达型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA AK043773和lncRNA EXOC7相对于内参GAPDH的相对表达水平，依次用X 1、X 2表示；
    步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝-2.918+2.618X 1+2.115X 2得到Y值，Y值大于0.495预示该乳腺癌患者发生骨转移，小于0.495预示未发生骨转移。
  7. 一种用于诊断预示三阴性型乳腺癌骨转移lncRNA诊断组合物，其特征在于：由lncRNA Lnc01089和lncRNA HOTAIR组成。
  8. 一种诊断预示三阴性型乳腺癌骨转移的方法，其特征在于：包括如下步骤：
    步骤S1，采集三阴性型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总RNA，用qRT-PCR法测定总RNA中lncRNA Lnc01089和lncRNA HOTAIR相对于内参GAPDH的相对表达水平，依次用X 1、X 2表示；
    步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝-2.537+2.793X 1+2.181X 2得到Y值，Y值大于0.633预示该乳腺癌患者发生骨转移，小于0.633预示未发生骨转移。
  9. 一种用于诊断预示Luminal A型乳腺癌骨转移的甲基化基因诊断组合物，其特征在于：由甲基化PITX1和甲基化AMOT组成。
  10. 一种诊断预示Luminal A型乳腺癌骨转移的方法，其特征在于，包括如下步骤：
    步骤S1，采集Luminal A型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化PITX1和甲基化AMOT的甲基化指数，依次用X 1、X 2表示；
    步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝1/[1+EXP(1.499X 1+2.302X 2-0.258)]得到Y值，Y值小于0.238预示该乳腺癌患者发生骨转移，大于0.238预示未发生骨转移。
  11. 一种用于诊断预示Luminal B型乳腺癌骨转移的甲基化基因诊断组合物，其特征在于：由甲基化PTPN1和甲基化SLIT2组成。
  12. 一种诊断预示Luminal B型乳腺癌骨转移的方法，其特征在于：包括如下步骤：
    步骤S1，采集Luminal B型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化PTPN1和甲基化SLIT2的甲基化指数，依次用X 1、X 2表示；
    步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝1/[1+EXP(2.016X 1+1.898X 2-0.455)]得到Y值，Y值小于0.310预示该乳腺癌患者发生骨转移，大于0.310预示未发生骨转移。
  13. 一种用于诊断预示Her-2过表达型乳腺癌骨转移甲基化基因诊断组合物，其特征在于：由甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1组成。
  14. 一种诊断预示Her-2过表达型乳腺癌骨转移的方法，其特征在于：包括如下步骤：
    步骤S1，采集Her-2过表达型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化MYLK2、甲基化EFEMP1和甲基化SOSTDC1的甲基化指数，依次为X 1、X 2、X 3；
    步骤S3，将X 1、X 2、X 3代入方程Y＝1/[1+EXP(1.342X 1+1.401X 2+1.345X 3-2.035)]得到Y值，Y值小于0.308预示该乳腺癌患者发生骨转移，大于0.308预示未发生骨转移。
  15. 一种用于诊断预示三阴性型乳腺癌骨转移甲基化基因诊断组合物，其特征在于：由甲基化MYLK3和甲基化SCARA5组成。
  16. 一种诊断预示三阴性型乳腺癌骨转移的方法，其特征在于：包括如下步骤：
    步骤S1，采集三阴性型乳腺癌患者空腹静脉血，自然凝固后离心分离出血清；
    步骤S2，提取血清总DNA，经PCR扩增、DNA亚硫酸盐修饰和焦磷酸测序测定总DNA中甲基化MYLK3和甲基化SCARA5的甲基化指数，依次用X 1、X 2表示；
    步骤S3，将X 1、X 2值代入二元逻辑回归方程Y＝1/[1+EXP(1.775X 1+1.236X 2-0.398)]得到Y值，Y值小于0.366预示该乳腺癌患者发生骨转移，大于0.366预示未发生骨转移。
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JP7406278B2 (ja) 2019-12-11 2023-12-27 清華大学 腫瘍マーカー及び治療ターゲットとしての長鎖ノンコーディングｒｎａ ｌｅｔｎ

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