{"title":"乳腺癌中糖基化蛋白相关微环境特征与患者预后相关。","authors":"Xiaoxiao Zhong, Jiaxuan Han, Huan Li, Xiangyu Shen, Bowen Yu, Ting Chen, Haobing Li, Jun Li, Jin Pang, Liyuan Qian, Wei Wu, Xiaoliang Tong, Boni Ding","doi":"10.1007/s00335-025-10137-9","DOIUrl":null,"url":null,"abstract":"<p><p>The tumor microenvironment (TME) and aberrant glycosylation have been suggested to play key roles in cancer. This study integrated differentially expressed genes (DEGs) and weighted gene coexpression network analysis (WGCNA) to identify tumor microenvironment-related genes and construct a TME-risk prognostic signature (TMERS) through LASSO Cox regression. After batch effect removal, 44 TME-prognosis-related genes (TMEPGs) were identified and classified into three molecular subtypes via K-means clustering. The finalized 22-gene TMERS model demonstrated robust prognostic predictive capacity in GEO datasets. The results revealed distinct immune profiles and prognostic stratifications among genetic subtypes and risk groups, confirming that the TMERS is an independent prognostic indicator for breast cancer (BRCA). Glycosyltransferase genes (GTs) have potential therapeutic relevance through immune regulation, with TMEPG member killer cell lectin like receptor B1 (KLRB1) significantly correlated with BRCA prognosis. Cellular experiments demonstrated that KLRB1 overexpression suppressed BRCA cell proliferation and migration. This work establishes a novel prognostic model for BRCA while highlighting KLRB1 as a potential biomarker, providing new insights into TME-targeted therapeutic strategies.</p>","PeriodicalId":18259,"journal":{"name":"Mammalian Genome","volume":" ","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Glycosylated protein-related microenvironmental features in breast cancer are associated with patient prognosis.\",\"authors\":\"Xiaoxiao Zhong, Jiaxuan Han, Huan Li, Xiangyu Shen, Bowen Yu, Ting Chen, Haobing Li, Jun Li, Jin Pang, Liyuan Qian, Wei Wu, Xiaoliang Tong, Boni Ding\",\"doi\":\"10.1007/s00335-025-10137-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The tumor microenvironment (TME) and aberrant glycosylation have been suggested to play key roles in cancer. This study integrated differentially expressed genes (DEGs) and weighted gene coexpression network analysis (WGCNA) to identify tumor microenvironment-related genes and construct a TME-risk prognostic signature (TMERS) through LASSO Cox regression. After batch effect removal, 44 TME-prognosis-related genes (TMEPGs) were identified and classified into three molecular subtypes via K-means clustering. The finalized 22-gene TMERS model demonstrated robust prognostic predictive capacity in GEO datasets. The results revealed distinct immune profiles and prognostic stratifications among genetic subtypes and risk groups, confirming that the TMERS is an independent prognostic indicator for breast cancer (BRCA). Glycosyltransferase genes (GTs) have potential therapeutic relevance through immune regulation, with TMEPG member killer cell lectin like receptor B1 (KLRB1) significantly correlated with BRCA prognosis. Cellular experiments demonstrated that KLRB1 overexpression suppressed BRCA cell proliferation and migration. This work establishes a novel prognostic model for BRCA while highlighting KLRB1 as a potential biomarker, providing new insights into TME-targeted therapeutic strategies.</p>\",\"PeriodicalId\":18259,\"journal\":{\"name\":\"Mammalian Genome\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mammalian Genome\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1007/s00335-025-10137-9\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mammalian Genome","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s00335-025-10137-9","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Glycosylated protein-related microenvironmental features in breast cancer are associated with patient prognosis.
The tumor microenvironment (TME) and aberrant glycosylation have been suggested to play key roles in cancer. This study integrated differentially expressed genes (DEGs) and weighted gene coexpression network analysis (WGCNA) to identify tumor microenvironment-related genes and construct a TME-risk prognostic signature (TMERS) through LASSO Cox regression. After batch effect removal, 44 TME-prognosis-related genes (TMEPGs) were identified and classified into three molecular subtypes via K-means clustering. The finalized 22-gene TMERS model demonstrated robust prognostic predictive capacity in GEO datasets. The results revealed distinct immune profiles and prognostic stratifications among genetic subtypes and risk groups, confirming that the TMERS is an independent prognostic indicator for breast cancer (BRCA). Glycosyltransferase genes (GTs) have potential therapeutic relevance through immune regulation, with TMEPG member killer cell lectin like receptor B1 (KLRB1) significantly correlated with BRCA prognosis. Cellular experiments demonstrated that KLRB1 overexpression suppressed BRCA cell proliferation and migration. This work establishes a novel prognostic model for BRCA while highlighting KLRB1 as a potential biomarker, providing new insights into TME-targeted therapeutic strategies.
期刊介绍：
Mammalian Genome focuses on the experimental, theoretical and technical aspects of genetics, genomics, epigenetics and systems biology in mouse, human and other mammalian species, with an emphasis on the relationship between genotype and phenotype, elucidation of biological and disease pathways as well as experimental aspects of interventions, therapeutics, and precision medicine. The journal aims to publish high quality original papers that present novel findings in all areas of mammalian genetic research as well as review articles on areas of topical interest. The journal will also feature commentaries and editorials to inform readers of breakthrough discoveries as well as issues of research standards, policies and ethics.
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