Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer
Abstract Bladder cancer (BLCA) is the tenth most commonly diagnosed cancer and poses a significant challenge due to its complexity and associated high morbidity and mortality rates in the absence of optimal treatment. The tumor microenvironment (TME) is recognized as a critical factor in tumor initi...
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| Format: | Article |
| Language: | English |
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Springer
2025-05-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-025-02292-x |
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| author | Can Liu Chaoyu Liao Bishao Sun Zhen Guo Sihao Chen Shixue Liu Xiaoyu Yuan Zeyu Huang Jingui Liu Min Deng Kui Wang Ruixin Wu Jiang Zhao Xingyou Dong |
| author_facet | Can Liu Chaoyu Liao Bishao Sun Zhen Guo Sihao Chen Shixue Liu Xiaoyu Yuan Zeyu Huang Jingui Liu Min Deng Kui Wang Ruixin Wu Jiang Zhao Xingyou Dong |
| author_sort | Can Liu |
| collection | DOAJ |
| description | Abstract Bladder cancer (BLCA) is the tenth most commonly diagnosed cancer and poses a significant challenge due to its complexity and associated high morbidity and mortality rates in the absence of optimal treatment. The tumor microenvironment (TME) is recognized as a critical factor in tumor initiation, progression and therapeutic response, and offers numerous potential targets for intervention. A comprehensive understanding of immune infiltration patterns in BLCA is essential for the development of effective prevention and treatment strategies. In this study, bioinformatics analysis was used to identify differentially expressed genes (DEGs) and tumor-infiltrating immune cells (TIICs) between BLCA tissues and adjacent normal tissues. Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis were used to identify the top 10 hub genes with the most significant co-expression effects, and their potential relationship with patient prognosis was then predicted. The random survival forest (RSF) model was used to further identify six variables among the hub genes and establish a novel scoring system, defined as the tumor-infiltrating immune score (TIIS) to predict the prognosis of BLCA patients. In addition, the correlation analysis between TIIS and drug sensitivity was investigated using the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) databases. Patients with high TIIS were found to have a poor prognosis but may be more sensitive to Cisplatin and certain novel agents. This study provided a systematic analysis of immune cell infiltration in BLCA and established TIIS to predict patient prognosis and the efficacy of specific drugs in the treatment of BLCA. |
| format | Article |
| id | doaj-art-661150fb3c6e4acab80a1bf4809e115f |
| institution | OA Journals |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-661150fb3c6e4acab80a1bf4809e115f2025-08-20T02:25:15ZengSpringerDiscover Oncology2730-60112025-05-0116111810.1007/s12672-025-02292-xTumour-infiltrating immune cells as a novel prognostic model for bladder cancerCan Liu0Chaoyu Liao1Bishao Sun2Zhen Guo3Sihao Chen4Shixue Liu5Xiaoyu Yuan6Zeyu Huang7Jingui Liu8Min Deng9Kui Wang10Ruixin Wu11Jiang Zhao12Xingyou Dong13Department of Urology, The Second Affiliated Hospital, Army Military Medical UniversityDepartment of Urology, The Second Affiliated Hospital, Army Military Medical UniversityDepartment of Urology, The Second Affiliated Hospital, Army Military Medical UniversityUrology Department, Chongqing Shapingba Hospital, School of Medicine, Chongqing UniversityDepartment of Immunology, School of Basic Medical Sciences, Chongqing Medical UniversityUrology Department, Chongqing Shapingba Hospital, School of Medicine, Chongqing UniversityUrology Department, Chongqing Shapingba Hospital, School of Medicine, Chongqing UniversityDepartment of Urology, The Second Affiliated Hospital, Army Military Medical UniversityDepartment of Urology, The Second Affiliated Hospital, Army Military Medical UniversityDepartment of Urology, The Second Affiliated Hospital, Army Military Medical UniversityDepartment of Urology, The Second Affiliated Hospital, Army Military Medical UniversityDepartment of Immunology, School of Basic Medical Sciences, Chongqing Medical UniversityDepartment of Urology, The Second Affiliated Hospital, Army Military Medical UniversityUrology Department, Chongqing Shapingba Hospital, School of Medicine, Chongqing UniversityAbstract Bladder cancer (BLCA) is the tenth most commonly diagnosed cancer and poses a significant challenge due to its complexity and associated high morbidity and mortality rates in the absence of optimal treatment. The tumor microenvironment (TME) is recognized as a critical factor in tumor initiation, progression and therapeutic response, and offers numerous potential targets for intervention. A comprehensive understanding of immune infiltration patterns in BLCA is essential for the development of effective prevention and treatment strategies. In this study, bioinformatics analysis was used to identify differentially expressed genes (DEGs) and tumor-infiltrating immune cells (TIICs) between BLCA tissues and adjacent normal tissues. Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis were used to identify the top 10 hub genes with the most significant co-expression effects, and their potential relationship with patient prognosis was then predicted. The random survival forest (RSF) model was used to further identify six variables among the hub genes and establish a novel scoring system, defined as the tumor-infiltrating immune score (TIIS) to predict the prognosis of BLCA patients. In addition, the correlation analysis between TIIS and drug sensitivity was investigated using the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) databases. Patients with high TIIS were found to have a poor prognosis but may be more sensitive to Cisplatin and certain novel agents. This study provided a systematic analysis of immune cell infiltration in BLCA and established TIIS to predict patient prognosis and the efficacy of specific drugs in the treatment of BLCA.https://doi.org/10.1007/s12672-025-02292-xBladder cancerSingle cell atlasImmune cell infiltrationDrug sensitivityTumor-infiltrating immune score |
| spellingShingle | Can Liu Chaoyu Liao Bishao Sun Zhen Guo Sihao Chen Shixue Liu Xiaoyu Yuan Zeyu Huang Jingui Liu Min Deng Kui Wang Ruixin Wu Jiang Zhao Xingyou Dong Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer Discover Oncology Bladder cancer Single cell atlas Immune cell infiltration Drug sensitivity Tumor-infiltrating immune score |
| title | Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer |
| title_full | Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer |
| title_fullStr | Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer |
| title_full_unstemmed | Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer |
| title_short | Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer |
| title_sort | tumour infiltrating immune cells as a novel prognostic model for bladder cancer |
| topic | Bladder cancer Single cell atlas Immune cell infiltration Drug sensitivity Tumor-infiltrating immune score |
| url | https://doi.org/10.1007/s12672-025-02292-x |
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