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Exploring Trastuzumab Resistance Biomarkers for HER2-positive Breast Cancer Based on Targeted Metabolomics of TCA-Related Metabolites
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WEI Bangbang1, CAO Yiwei1, DONG Chuntao1, LI Debang1, XU Feifei2, SI Xinxin1, *, CHEN Yun2
Chinese Pharmaceutical Journal | 2024, 59(4) : 302 - 310
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Chinese Pharmaceutical Journal | 2024, 59(4): 302-310
Exploring Trastuzumab Resistance Biomarkers for HER2-positive Breast Cancer Based on Targeted Metabolomics of TCA-Related Metabolites
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WEI Bangbang1, CAO Yiwei1, DONG Chuntao1, LI Debang1, XU Feifei2, SI Xinxin1, *, CHEN Yun2
Affiliations
  • 1 School of Pharmacy, Jiangsu Ocean University, Lianyungang 222005, China
  • 2 School of Pharmacy, Nanjing Medical University, Nanjing 211100, China
Published: 2024-02-22 doi: 10.11669/cpj.2024.04.003
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OBJECTIVE To investigate the levels of tricarboxylic acid cycle (TCA)-related metabolites in human epidermal growth factor receptor 2 (HER2)-positive breast cancer trastuzumab-resistant and trastuzumab-sensitive cells, as well as to screen potential biomarkers of trastuzumab resistance. METHODS Targeted metabolomics was adopted to detect TCA-related metabolite levels including citrate, cis-aconitate, isocitrate, alpha-ketoglutarate, succinic acid,fumaric acid,malic acid and oxaloacetic acid based on ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) in trastuzumab-resistant and trastuzumab-sensitive cells. The linearity, accuracy and precision of the method were validated. Then, orthogonal partial least-squares discrimination analysis (OPLS-DA) was used to compare the relative differential expression in trastuzumab-resistant and trastuzumab-sensitive cells. Differentially expressed metabolites were screened according to P<0.05, fold change (FC)>1.5 or FC<0.67. Finally, a multivariable model based on SVM and receiver operating characteristic (ROC) curve analysis was used to assess the classification accuracy of each metabolite. RESULTS For all TCA-related metabolites, the standard curves were linear, the correlation coefficients (r) were greater than 0.994, the established method accuracy was 94%-105% and the precision coefficient of variation (CV, %) was less than 15%. Trastuzumab-resistant and trastuzumab-sensitive cells were clearly separated from each other in the OPLS-DA model. Malic acid, succinic acid and fumaric acid were significantly upregulated in trastuzumab-resistant cells (P<0.05) compared to trastuzumab-sensitive cells. The areas under the curves (AUCs) of malic acid, succinic acid and fumaric acid were greater than 0.9 and the SVM model yielded the highest AUC of 1.000. CONCLUSION TCA-related metabolites are differentially expressed in trastuzumab-resistant and trastuzumab-sensitive cells. Succinic acid, fumaric acid and malic acid can serve as biomarkers that may provide potential value for the diagnosis of trastuzumab resistance in HER2-positive breast cancer.

HER2-positive breast cancer  /  trastuzumab-resistance  /  TCA-related metabolity  /  targeted metabolomic  /  biomarker
WEI Bangbang, CAO Yiwei, DONG Chuntao, LI Debang, XU Feifei, SI Xinxin, CHEN Yun. Exploring Trastuzumab Resistance Biomarkers for HER2-positive Breast Cancer Based on Targeted Metabolomics of TCA-Related Metabolites[J]. Chinese Pharmaceutical Journal, 2024 , 59 (4) : 302 -310 . DOI: 10.11669/cpj.2024.04.003
Year 2024 volume 59 Issue 4
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doi: 10.11669/cpj.2024.04.003
  • Receive Date:2023-08-03
  • Online Date:2025-11-13
  • Published:2024-02-22
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  • Received:2023-08-03
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    1 School of Pharmacy, Jiangsu Ocean University, Lianyungang 222005, China
    2 School of Pharmacy, Nanjing Medical University, Nanjing 211100, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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