Xiao-Li Wu, Di Hu, Guo-Fa Xu, Mei-Yu Zhou, Bin Li, Xiao-Qiao Hu, Gen-Dou Zhou, Ya Fu, Rui Huang, Shou-Yan Xiang, Miao-Miao Tao, Hong-Bo Ma
{"title":"中性粒细胞胞外陷阱（NETs）评分：结直肠癌患者的一种新的预后指标。","authors":"Xiao-Li Wu, Di Hu, Guo-Fa Xu, Mei-Yu Zhou, Bin Li, Xiao-Qiao Hu, Gen-Dou Zhou, Ya Fu, Rui Huang, Shou-Yan Xiang, Miao-Miao Tao, Hong-Bo Ma","doi":"10.1007/s12672-025-03708-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, displaying significant tendencies towards recurrence and metastasis. Advanced CRC typically necessitates systemic treatments such as chemotherapy, targeted therapy, and immunotherapy, yet the development of primary and acquired drug resistance remains a significant challenge. Neutrophil extracellular traps (NETs) represent a complex network structure comprising DNA, histones, and antimicrobial peptides generated by activated neutrophils, which have been implicated in promoting cancer progression. However, the precise mechanisms underlying the interaction between NETs-related gene signatures and cancer cells remain poorly understood.</p><p><strong>Methods: </strong>The gene expression profile of TCGA-CRC was obtained from the Xena database. Using the expression levels of 69 initial NETs biomarkers, a LASSO Cox regression model was used to develop a 10-gene NETs score. This score was then comprehensively analyzed, focusing on various aspects such as the tumor microenvironment (TME), drug resistance, tumor mutations, and immunotherapy response.</p><p><strong>Results: </strong>A prognostic model for NETs was developed using multivariate Cox regression and LASSO regression analysis. A customized nomogram was developed to improve the forecast precision of the NETs-score. The NETs-score is involved in the TME and clinicopathological characteristics, where a lower score is associated with a more favorable prognosis. Further examination indicated that the NETs-score can predict how well a patient will respond to chemotherapy and identify those who could potentially gain advantages from anti-CTLA4 and PD-L1 treatments.</p><p><strong>Conclusion: </strong>The NETs-score introduces a new, effective, and precise prognostic model for CRC, enhancing the prediction of responses to chemotherapy and immunotherapy. This advancement also propels personalized cancer treatment strategies in the realms of chemotherapy and immunotherapy.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1896"},"PeriodicalIF":2.9000,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12528602/pdf/","citationCount":"0","resultStr":"{\"title\":\"Neutrophil extracellular traps (NETs)-score: a novel prognostic marker for colorectal cancer patients.\",\"authors\":\"Xiao-Li Wu, Di Hu, Guo-Fa Xu, Mei-Yu Zhou, Bin Li, Xiao-Qiao Hu, Gen-Dou Zhou, Ya Fu, Rui Huang, Shou-Yan Xiang, Miao-Miao Tao, Hong-Bo Ma\",\"doi\":\"10.1007/s12672-025-03708-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, displaying significant tendencies towards recurrence and metastasis. Advanced CRC typically necessitates systemic treatments such as chemotherapy, targeted therapy, and immunotherapy, yet the development of primary and acquired drug resistance remains a significant challenge. Neutrophil extracellular traps (NETs) represent a complex network structure comprising DNA, histones, and antimicrobial peptides generated by activated neutrophils, which have been implicated in promoting cancer progression. However, the precise mechanisms underlying the interaction between NETs-related gene signatures and cancer cells remain poorly understood.</p><p><strong>Methods: </strong>The gene expression profile of TCGA-CRC was obtained from the Xena database. Using the expression levels of 69 initial NETs biomarkers, a LASSO Cox regression model was used to develop a 10-gene NETs score. This score was then comprehensively analyzed, focusing on various aspects such as the tumor microenvironment (TME), drug resistance, tumor mutations, and immunotherapy response.</p><p><strong>Results: </strong>A prognostic model for NETs was developed using multivariate Cox regression and LASSO regression analysis. A customized nomogram was developed to improve the forecast precision of the NETs-score. The NETs-score is involved in the TME and clinicopathological characteristics, where a lower score is associated with a more favorable prognosis. Further examination indicated that the NETs-score can predict how well a patient will respond to chemotherapy and identify those who could potentially gain advantages from anti-CTLA4 and PD-L1 treatments.</p><p><strong>Conclusion: </strong>The NETs-score introduces a new, effective, and precise prognostic model for CRC, enhancing the prediction of responses to chemotherapy and immunotherapy. This advancement also propels personalized cancer treatment strategies in the realms of chemotherapy and immunotherapy.</p>\",\"PeriodicalId\":11148,\"journal\":{\"name\":\"Discover. Oncology\",\"volume\":\"16 1\",\"pages\":\"1896\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12528602/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Discover. Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12672-025-03708-4\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discover. Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12672-025-03708-4","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Neutrophil extracellular traps (NETs)-score: a novel prognostic marker for colorectal cancer patients.
Background: Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, displaying significant tendencies towards recurrence and metastasis. Advanced CRC typically necessitates systemic treatments such as chemotherapy, targeted therapy, and immunotherapy, yet the development of primary and acquired drug resistance remains a significant challenge. Neutrophil extracellular traps (NETs) represent a complex network structure comprising DNA, histones, and antimicrobial peptides generated by activated neutrophils, which have been implicated in promoting cancer progression. However, the precise mechanisms underlying the interaction between NETs-related gene signatures and cancer cells remain poorly understood.
Methods: The gene expression profile of TCGA-CRC was obtained from the Xena database. Using the expression levels of 69 initial NETs biomarkers, a LASSO Cox regression model was used to develop a 10-gene NETs score. This score was then comprehensively analyzed, focusing on various aspects such as the tumor microenvironment (TME), drug resistance, tumor mutations, and immunotherapy response.
Results: A prognostic model for NETs was developed using multivariate Cox regression and LASSO regression analysis. A customized nomogram was developed to improve the forecast precision of the NETs-score. The NETs-score is involved in the TME and clinicopathological characteristics, where a lower score is associated with a more favorable prognosis. Further examination indicated that the NETs-score can predict how well a patient will respond to chemotherapy and identify those who could potentially gain advantages from anti-CTLA4 and PD-L1 treatments.
Conclusion: The NETs-score introduces a new, effective, and precise prognostic model for CRC, enhancing the prediction of responses to chemotherapy and immunotherapy. This advancement also propels personalized cancer treatment strategies in the realms of chemotherapy and immunotherapy.
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