{"title":"基于转录组分析和实验验证的结直肠癌坏死相关预后模型","authors":"Yuying Huang, Licheng Li, Zhongmin Kang, Huali Luo, Xiaojing Lin, Shuli Zhao, Qizhu Zhang, Qinshan Li, Honglin Liu, Meng-Ting Li","doi":"10.31083/j.fbl2903098","DOIUrl":null,"url":null,"abstract":"Purpose : Numerous studies have emphasised the importance of necroptosis in the malignant progression of colorectal cancer (CRC). However, whether necroptosis-related genes (NRGs) can be used to predict the prognosis of CRC remains to be revealed. Methods : Patients with CRC were divided into two clusters based on the expression of NRGs, and prognosis was compared between the two clusters. A prognostic model was established based on NRGs, and its predictive efficiency was validated using Kaplan-Meier (K-M) curves, receiver operating characteristic (ROC) curves and a nomogram. Immune infiltration, single-cell and drug sensitivity analyses were used to examine the effects of NRGs on the prognosis of CRC. Results : The prognostic model served as a valid and independent predictor of CRC prognosis. Immune infiltration and single-cell analyses revealed that the unique immune microenvironment of CRC was regulated by NRGs. Drug sensitivity analysis showed that patients in the high-and low-risk groups were sensitive to different drugs. In addition, H2BC18 was found to play an important role in regulating the malignant progression of CRC. Conclusion : This study provides novel insights into precision immunotherapy based on NRGs in CRC. The NRG-based prognostic model may help to identify targeted drugs and develop more effective and individualised treatment strategies for patients with CRC.","PeriodicalId":503756,"journal":{"name":"Frontiers in Bioscience-Landmark","volume":"52 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prognostic Model Associated with Necroptosis in Colorectal Cancer based on Transcriptomic Analysis and Experimental Validation\",\"authors\":\"Yuying Huang, Licheng Li, Zhongmin Kang, Huali Luo, Xiaojing Lin, Shuli Zhao, Qizhu Zhang, Qinshan Li, Honglin Liu, Meng-Ting Li\",\"doi\":\"10.31083/j.fbl2903098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose : Numerous studies have emphasised the importance of necroptosis in the malignant progression of colorectal cancer (CRC). However, whether necroptosis-related genes (NRGs) can be used to predict the prognosis of CRC remains to be revealed. Methods : Patients with CRC were divided into two clusters based on the expression of NRGs, and prognosis was compared between the two clusters. A prognostic model was established based on NRGs, and its predictive efficiency was validated using Kaplan-Meier (K-M) curves, receiver operating characteristic (ROC) curves and a nomogram. Immune infiltration, single-cell and drug sensitivity analyses were used to examine the effects of NRGs on the prognosis of CRC. Results : The prognostic model served as a valid and independent predictor of CRC prognosis. Immune infiltration and single-cell analyses revealed that the unique immune microenvironment of CRC was regulated by NRGs. Drug sensitivity analysis showed that patients in the high-and low-risk groups were sensitive to different drugs. In addition, H2BC18 was found to play an important role in regulating the malignant progression of CRC. Conclusion : This study provides novel insights into precision immunotherapy based on NRGs in CRC. The NRG-based prognostic model may help to identify targeted drugs and develop more effective and individualised treatment strategies for patients with CRC.\",\"PeriodicalId\":503756,\"journal\":{\"name\":\"Frontiers in Bioscience-Landmark\",\"volume\":\"52 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Bioscience-Landmark\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31083/j.fbl2903098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Bioscience-Landmark","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31083/j.fbl2903098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prognostic Model Associated with Necroptosis in Colorectal Cancer based on Transcriptomic Analysis and Experimental Validation
Purpose : Numerous studies have emphasised the importance of necroptosis in the malignant progression of colorectal cancer (CRC). However, whether necroptosis-related genes (NRGs) can be used to predict the prognosis of CRC remains to be revealed. Methods : Patients with CRC were divided into two clusters based on the expression of NRGs, and prognosis was compared between the two clusters. A prognostic model was established based on NRGs, and its predictive efficiency was validated using Kaplan-Meier (K-M) curves, receiver operating characteristic (ROC) curves and a nomogram. Immune infiltration, single-cell and drug sensitivity analyses were used to examine the effects of NRGs on the prognosis of CRC. Results : The prognostic model served as a valid and independent predictor of CRC prognosis. Immune infiltration and single-cell analyses revealed that the unique immune microenvironment of CRC was regulated by NRGs. Drug sensitivity analysis showed that patients in the high-and low-risk groups were sensitive to different drugs. In addition, H2BC18 was found to play an important role in regulating the malignant progression of CRC. Conclusion : This study provides novel insights into precision immunotherapy based on NRGs in CRC. The NRG-based prognostic model may help to identify targeted drugs and develop more effective and individualised treatment strategies for patients with CRC.