Hui Ye, Xiabo Shen, Yaohan Li, Weibin Zou, Syed Shams ul Hassan, Yue Feng, Xiaojia Wang, Jingkui Tian, Xiying Shao, Yi Tao, Wei Zhu
{"title":"Proteomic and metabolomic characterization of bone, liver, and lung metastases in plasma of breast cancer patients","authors":"Hui Ye, Xiabo Shen, Yaohan Li, Weibin Zou, Syed Shams ul Hassan, Yue Feng, Xiaojia Wang, Jingkui Tian, Xiying Shao, Yi Tao, Wei Zhu","doi":"10.1002/prca.202300136","DOIUrl":null,"url":null,"abstract":"BackgroundBreast cancer (BC) is the second leading cause of cancer‐related deaths among women, primarily due to metastases to other organs rather than the primary tumor.MethodsIn this study, a comprehensive analysis of plasma proteomics and metabolomics was conducted on a cohort of 51 BC patients. Potential biomarkers were screened by the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest algorithm. Additionally, enzyme‐linked immunosorbent assay (ELISA) kits and untargeted metabolomics were utilized to validate the prognostic biomarkers in an independent cohort.ResultsIn the study, extracellular matrix (ECM)‐related functional enrichments were observed to be enriched in BC cases with bone metastases. Proteins dysregulated in retinol metabolism in liver metastases and leukocyte transendothelial migration in lung metastases were also identified. Machine learning models identified specific biomarker panels for each metastasis type, achieving high diagnostic accuracy with area under the curve (AUC) of 0.955 for bone, 0.941 for liver, and 0.989 for lung metastases.ConclusionsFor bone metastasis, biomarkers such as leucyl‐tryptophan, LysoPC(P‐16:0/0:0), FN1, and HSPG2 have been validated. dUDP, LPE(18:1/0:0), and aspartylphenylalanine have been confirmed for liver metastasis. For lung metastasis, dUDP, testosterone sulfate, and PE(14:0/20:5) have been established.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/prca.202300136","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
BackgroundBreast cancer (BC) is the second leading cause of cancer‐related deaths among women, primarily due to metastases to other organs rather than the primary tumor.MethodsIn this study, a comprehensive analysis of plasma proteomics and metabolomics was conducted on a cohort of 51 BC patients. Potential biomarkers were screened by the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest algorithm. Additionally, enzyme‐linked immunosorbent assay (ELISA) kits and untargeted metabolomics were utilized to validate the prognostic biomarkers in an independent cohort.ResultsIn the study, extracellular matrix (ECM)‐related functional enrichments were observed to be enriched in BC cases with bone metastases. Proteins dysregulated in retinol metabolism in liver metastases and leukocyte transendothelial migration in lung metastases were also identified. Machine learning models identified specific biomarker panels for each metastasis type, achieving high diagnostic accuracy with area under the curve (AUC) of 0.955 for bone, 0.941 for liver, and 0.989 for lung metastases.ConclusionsFor bone metastasis, biomarkers such as leucyl‐tryptophan, LysoPC(P‐16:0/0:0), FN1, and HSPG2 have been validated. dUDP, LPE(18:1/0:0), and aspartylphenylalanine have been confirmed for liver metastasis. For lung metastasis, dUDP, testosterone sulfate, and PE(14:0/20:5) have been established.