m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer
Abstract Background N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. Methods Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome A...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-10-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-022-03711-1 |
| _version_ | 1811335269472796672 |
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| author | Zi-Hao Feng Yan-Ping Liang Jun-Jie Cen Hao-Hua Yao Hai-Shan Lin Jia-Ying Li Hui Liang Zhu Wang Qiong Deng Jia-Zheng Cao Yong Huang Jin-Huan Wei Jun-Hang Luo Wei Chen Zhen-Hua Chen |
| author_facet | Zi-Hao Feng Yan-Ping Liang Jun-Jie Cen Hao-Hua Yao Hai-Shan Lin Jia-Ying Li Hui Liang Zhu Wang Qiong Deng Jia-Zheng Cao Yong Huang Jin-Huan Wei Jun-Hang Luo Wei Chen Zhen-Hua Chen |
| author_sort | Zi-Hao Feng |
| collection | DOAJ |
| description | Abstract Background N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. Methods Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan–Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated. Results Totally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan–Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib. Conclusions An m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer. |
| first_indexed | 2024-04-13T17:22:37Z |
| format | Article |
| id | doaj.art-c174050369a44a65a5b1c412ae34f42a |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-04-13T17:22:37Z |
| publishDate | 2022-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-c174050369a44a65a5b1c412ae34f42a2022-12-22T02:37:56ZengBMCJournal of Translational Medicine1479-58762022-10-0120111110.1186/s12967-022-03711-1m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancerZi-Hao Feng0Yan-Ping Liang1Jun-Jie Cen2Hao-Hua Yao3Hai-Shan Lin4Jia-Ying Li5Hui Liang6Zhu Wang7Qiong Deng8Jia-Zheng Cao9Yong Huang10Jin-Huan Wei11Jun-Hang Luo12Wei Chen13Zhen-Hua Chen14Department of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, Affiliated Longhua People’s Hospital, Southern Medical UniversityDepartment of Urology, Affiliated Longhua People’s Hospital, Southern Medical UniversityDepartment of Urology, Affiliated Longhua People’s Hospital, Southern Medical UniversityDepartment of Urology, Jiangmen Central HospitalDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityDepartment of Urology, The First Affiliated Hospital, Sun Yat-sen UniversityAbstract Background N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. Methods Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan–Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated. Results Totally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan–Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib. Conclusions An m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer.https://doi.org/10.1186/s12967-022-03711-1m6A (N6-methyladenosine)Long noncoding RNA (lncRNA)Bladder cancer (BLCA)Immune microenvironmentImmune cell infiltrationPrognosis prediction |
| spellingShingle | Zi-Hao Feng Yan-Ping Liang Jun-Jie Cen Hao-Hua Yao Hai-Shan Lin Jia-Ying Li Hui Liang Zhu Wang Qiong Deng Jia-Zheng Cao Yong Huang Jin-Huan Wei Jun-Hang Luo Wei Chen Zhen-Hua Chen m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer Journal of Translational Medicine m6A (N6-methyladenosine) Long noncoding RNA (lncRNA) Bladder cancer (BLCA) Immune microenvironment Immune cell infiltration Prognosis prediction |
| title | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
| title_full | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
| title_fullStr | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
| title_full_unstemmed | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
| title_short | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
| title_sort | m6a immune related lncrna prognostic signature for predicting immune landscape and prognosis of bladder cancer |
| topic | m6A (N6-methyladenosine) Long noncoding RNA (lncRNA) Bladder cancer (BLCA) Immune microenvironment Immune cell infiltration Prognosis prediction |
| url | https://doi.org/10.1186/s12967-022-03711-1 |
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