Yudong Zhou, Shibo Yu, Lizhe Zhu, Yalong Wang, Chenglong Duan, Danni Li, Jinsui Du, Jiaqi Zhang, Jianing Zhang, Ruichao Ma, Jianjun He, Yu Ren, Bin Wang
{"title":"乳腺癌预后的分子生物标志物：氨基酸代谢基因的作用。","authors":"Yudong Zhou, Shibo Yu, Lizhe Zhu, Yalong Wang, Chenglong Duan, Danni Li, Jinsui Du, Jiaqi Zhang, Jianing Zhang, Ruichao Ma, Jianjun He, Yu Ren, Bin Wang","doi":"10.1007/s13105-025-01088-5","DOIUrl":null,"url":null,"abstract":"<p><p>The development of precise molecular biomarkers for breast cancer prognosis holds immense potential to improve treatment outcomes. This study aimed to investigate the role of amino acid metabolism genes as predictive markers for breast cancer prognosis and their association with the immune-tumour microenvironment. By employing advanced machine learning algorithms and bioinformatics analysis techniques, the impact of amino acid metabolism-related genes (AAMRGs) on the immune status and overall survival of patients with breast cancer was examined. An AAMRG-based risk model was established to assess the prognostic significance. Validated risk models (AIMP2, IYD, and QARS1) accurately predicted patient outcomes [1 y: 0.87 (0.96-0.78); 3 y: 0.82 (0.87-0.76); 5 y: 0.80 (0.86-0.75)]. Furthermore, this study revealed evidence suggesting that QARS1 may influence breast cancer cell proliferation through methionine metabolism. This analysis provides valuable insights into the mechanisms of breast cancer, emphasizing the significance of AAMRGs as prognostic biomarkers and potential therapeutic targets for optimizing personalized treatment strategies.</p>","PeriodicalId":16779,"journal":{"name":"Journal of physiology and biochemistry","volume":" ","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Molecular biomarkers for the prognosis of breast cancer: role of amino acid metabolism genes.\",\"authors\":\"Yudong Zhou, Shibo Yu, Lizhe Zhu, Yalong Wang, Chenglong Duan, Danni Li, Jinsui Du, Jiaqi Zhang, Jianing Zhang, Ruichao Ma, Jianjun He, Yu Ren, Bin Wang\",\"doi\":\"10.1007/s13105-025-01088-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The development of precise molecular biomarkers for breast cancer prognosis holds immense potential to improve treatment outcomes. This study aimed to investigate the role of amino acid metabolism genes as predictive markers for breast cancer prognosis and their association with the immune-tumour microenvironment. By employing advanced machine learning algorithms and bioinformatics analysis techniques, the impact of amino acid metabolism-related genes (AAMRGs) on the immune status and overall survival of patients with breast cancer was examined. An AAMRG-based risk model was established to assess the prognostic significance. Validated risk models (AIMP2, IYD, and QARS1) accurately predicted patient outcomes [1 y: 0.87 (0.96-0.78); 3 y: 0.82 (0.87-0.76); 5 y: 0.80 (0.86-0.75)]. Furthermore, this study revealed evidence suggesting that QARS1 may influence breast cancer cell proliferation through methionine metabolism. This analysis provides valuable insights into the mechanisms of breast cancer, emphasizing the significance of AAMRGs as prognostic biomarkers and potential therapeutic targets for optimizing personalized treatment strategies.</p>\",\"PeriodicalId\":16779,\"journal\":{\"name\":\"Journal of physiology and biochemistry\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of physiology and biochemistry\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1007/s13105-025-01088-5\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of physiology and biochemistry","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s13105-025-01088-5","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Molecular biomarkers for the prognosis of breast cancer: role of amino acid metabolism genes.
The development of precise molecular biomarkers for breast cancer prognosis holds immense potential to improve treatment outcomes. This study aimed to investigate the role of amino acid metabolism genes as predictive markers for breast cancer prognosis and their association with the immune-tumour microenvironment. By employing advanced machine learning algorithms and bioinformatics analysis techniques, the impact of amino acid metabolism-related genes (AAMRGs) on the immune status and overall survival of patients with breast cancer was examined. An AAMRG-based risk model was established to assess the prognostic significance. Validated risk models (AIMP2, IYD, and QARS1) accurately predicted patient outcomes [1 y: 0.87 (0.96-0.78); 3 y: 0.82 (0.87-0.76); 5 y: 0.80 (0.86-0.75)]. Furthermore, this study revealed evidence suggesting that QARS1 may influence breast cancer cell proliferation through methionine metabolism. This analysis provides valuable insights into the mechanisms of breast cancer, emphasizing the significance of AAMRGs as prognostic biomarkers and potential therapeutic targets for optimizing personalized treatment strategies.
期刊介绍：
The Journal of Physiology and Biochemistry publishes original research articles and reviews describing relevant new observations on molecular, biochemical and cellular mechanisms involved in human physiology. All areas of the physiology are covered. Special emphasis is placed on the integration of those levels in the whole-organism. The Journal of Physiology and Biochemistry also welcomes articles on molecular nutrition and metabolism studies, and works related to the genomic or proteomic bases of the physiological functions. Descriptive manuscripts about physiological/biochemical processes or clinical manuscripts will not be considered. The journal will not accept manuscripts testing effects of animal or plant extracts.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
