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Establishment of a prognostic model based on m(6)A regulatory factors and stemness of hepatocellular carcinoma using RNA-seq data and scRNA-seq data

BACKGROUND: Hepatocellular carcinoma (HCC) with high incidence and mortality is one of the most common malignant cancers worldwide. Increasing evidence has reported that N6-methyladenosine (m(6)A) modification has been considered as a major contribution to the occurrence and development of tumors. M...

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Detalles Bibliográficos
Autores principales: Liang, Yan, Chen, Sen, Xie, Jinghe, Yan, Guanrong, Guo, Tingting, Li, Tianyang, Liu, Shoupei, Zeng, Weiping, Zhang, Shuai, Ma, Keqiang, Chen, Honglin, Ou, Yimeng, Wang, Bailin, Gu, Weili, Duan, Yuyou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10587019/
https://www.ncbi.nlm.nih.gov/pubmed/37466793
http://dx.doi.org/10.1007/s00432-023-05045-x
Descripción
Sumario:BACKGROUND: Hepatocellular carcinoma (HCC) with high incidence and mortality is one of the most common malignant cancers worldwide. Increasing evidence has reported that N6-methyladenosine (m(6)A) modification has been considered as a major contribution to the occurrence and development of tumors. METHOD: In our study, we comprehensively analyzed the connection between m(6)A regulatory factors and cancer stem cells (CSCs) of HCC to establish a clinical tool for predicting its outcome. First, we concluded that the expression level of m(6)A regulatory factors was related with the stemness of hepatocellular carcinoma. Subsequently, we gained a ten hub regulatory factors that were associated with prognosis of hepatocellular carcinoma by overall survival (OS) analysis using ICGC and TCGA datasets, and these regulatory factors included YTHDF1, IGF2BP1, METTL3, IGF2BP3, HNRNPA2B1, IGF2BP2, RBM15B, HNRNPC, RBMX, and LRPPR. Next, we found that these ten hub m(6)A regulatory factors were highly expressed in CSCs, and CSCs related pathways were also enriched by the gene set variation analysis (GSVA). Then, correlation, consensus clustering and PCA analysis were performed to reveal potential therapeutic benefits of HCC. Moreover, univariate Cox regression (UNICOX), LASSON and multivariate Cox regression (MULTICOX) analyses were adopted to establish HCC prognosis prediction signature. RESULTS: Four regulatory factors RBM15B, LRPPRC, IGF2BP1, and IGF2BP3 were picked as valuable prognostic indicators. CONCLUSION: In summary, these ten hub regulatory factors would be useful therapeutic targets for HCC treatment, and RBM15B/LRPPRC/IGF2BP1/IGF2BP3 prognostic indicators can be used to guide therapy for HCC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00432-023-05045-x.