m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer

• Published in: Journal of translational medicine Vol. 20; no. 1; pp. 1 - 11
• Main Authors: Feng, Zi-Hao, Liang, Yan-Ping, Cen, Jun-Jie, Yao, Hao-Hua, Lin, Hai-Shan, Li, Jia-Ying, Liang, Hui, Wang, Zhu, Deng, Qiong, Cao, Jia-Zheng, Huang, Yong, Wei, Jin-Huan, Luo, Jun-Hang, Chen, Wei, Chen, Zhen-Hua
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 29.10.2022; BioMed Central; BMC
• Subjects: Biomarkers; Bladder cancer; Bladder cancer (BLCA); Cancer; Care and treatment; Chemotherapy; Correlation analysis; Datasets; Development and progression; Gene expression; Genomes; Health aspects; Immune cell infiltration; Immune microenvironment; Immune response; Infiltration; Innate immunity; Long noncoding RNA (lncRNA); m6A (N6-methyladenosine); Malignancy; Medical prognosis; Metabolism; Metastases; Metastasis; Mutation; N6-methyladenosine; Nomograms; Non-coding RNA; Patients; Prognosis; Prognosis prediction; Regression analysis; Risk groups; Software; Statistical analysis; Transcriptomes; Tumorigenesis; Tumors; China
• ISSN: 1479-5876; 1479-5876
• DOI: 10.1186/s12967-022-03711-1

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. Keywords: m6A (N6-methyladenosine), Long noncoding RNA (lncRNA), Bladder cancer (BLCA), Immune microenvironment, Immune cell infiltration, Prognosis prediction