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Identification of a signature of histone modifiers in kidney renal clear cell carcinoma.
Huang, Yongming; Yang, Zhongsheng; Tang, Ying; Chen, Hua; Liu, Tairong; Peng, Guanghua; Huang, Xin; He, Xiaolong; Mei, Ming; Du, Chuance.
Afiliación
  • Huang Y; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
  • Yang Z; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
  • Tang Y; Department of Day Ward, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, China.
  • Chen H; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
  • Liu T; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
  • Peng G; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
  • Huang X; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
  • He X; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
  • Mei M; Department of Day Ward, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, China.
  • Du C; Department of Urology, Ganzhou People's Hospital, Ganzhou, Jiangxi 341000, China.
Aging (Albany NY) ; 16(12): 10489-10511, 2024 06 17.
Article en En | MEDLINE | ID: mdl-38888515
ABSTRACT
Kidney renal clear cell carcinoma (KIRC) is a cancer that is closely associated with epigenetic alterations, and histone modifiers (HMs) are closely related to epigenetic regulation. Therefore, this study aimed to comprehensively explore the function and prognostic value of HMs-based signature in KIRC. HMs were first obtained from top journal. Then, the mRNA expression profiles and clinical information in KIRC samples were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Cox regression analysis and least absolute shrinkage and selection operator (Lasso) analysis were implemented to find prognosis-related HMs and construct a risk model related to the prognosis in KIRC. Kaplan-Meier analysis was used to determine prognostic differences between high- and low-risk groups. Immune infiltration and drug sensitivity analysis were also performed between high- and low-risk groups. Eventually, 8 HMs were successfully identified for the construction of a risk model in KIRC. The results of the correlation analysis between risk signature and the prognosis showed HMs-based signature has good prognostic value in KIRC. Results of immune analysis of risk models showed there were significant differences in the level of immune cell infiltration and expression of immune checkpoints between high- and low-risk groups. The results of the drug sensitivity analysis showed that the high-risk group was more sensitive to several chemotherapeutic agents such as Sunitinib, Tipifarnib, Nilotinib and Bosutinib than the low-risk group. In conclusion, we successfully constructed HMs-based prognostic signature that can predict the prognosis of KIRC.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carcinoma de Células Renales / Neoplasias Renales Límite: Humans Idioma: En Revista: Aging (Albany NY) Asunto de la revista: GERIATRIA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carcinoma de Células Renales / Neoplasias Renales Límite: Humans Idioma: En Revista: Aging (Albany NY) Asunto de la revista: GERIATRIA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos