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Integrated analysis of patients with bladder cancer from prospective transcription factor activity: Implications for personalized treatment approaches.
Wei, Haodong; Luo, Xu; Lan, Rifang; Xiong, Yuqiang; Yang, Siru; Wang, Shiyuan; Yang, Lei; Lv, Yingli.
Afiliación
  • Wei H; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
  • Luo X; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
  • Lan R; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
  • Xiong Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
  • Yang S; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
  • Wang S; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
  • Yang L; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China. Electronic address: leiyang@hrbmu.edu.cn.
  • Lv Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China. Electronic address: lyl@ems.hrbmu.edu.cn.
Methods ; 230: 32-43, 2024 Oct.
Article en En | MEDLINE | ID: mdl-39079653
ABSTRACT
Transcription factors are a specialized group of proteins that play important roles in regulating gene expression in human. These proteins control the transcription and translation of genes by binding to specific sites on DNA, thereby regulating key biological processes such as cell differentiation, proliferation, immune response, and neural development. Moreover, transcription factors are also involved in apoptosis and the pathogenesis of various diseases. By investigating transcription factors, researchers can uncover the mechanisms of gene regulation in organisms and develop more effective methods for preventing and treating human diseases. In the present study, the Virtual Inference of Protein-activity by Enriched Regulon algorithm was utilized to calculate the protein activity of transcription factors, and the metabolic-related protein activity were used for classifying bladder cancer patients into different subtype. To identify chemotherapy drugs with clinical benefits, the differences in prognosis and drug sensitivity between two distinct subtypes of bladder cancer patients were investigated. Simultaneously, the master regulators that display varying levels of transcription factor activity between two different bladder cancer subtypes were explored. Additionally, the potential transcriptional regulatory mechanisms and targets of these factors were investigated, thereby generating novel insights into bladder cancer research at the transcriptional regulation level.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Factores de Transcripción / Neoplasias de la Vejiga Urinaria / Regulación Neoplásica de la Expresión Génica / Medicina de Precisión Límite: Humans Idioma: En Revista: Methods Asunto de la revista: BIOQUIMICA 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: Factores de Transcripción / Neoplasias de la Vejiga Urinaria / Regulación Neoplásica de la Expresión Génica / Medicina de Precisión Límite: Humans Idioma: En Revista: Methods Asunto de la revista: BIOQUIMICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos