Scholarlink

Background <p>The expression of angiogenesis-associated genes affects the development of colorectal cancer (CRC). In this study, we aimed to develop and evaluate a method to predict survival outcomes in patients with CRC.</p> Methods <p>We investigated the expression of CRC angiogenesis-associated genes using various public databases and identified diverse molecular subtypes. We built an angiogenesis-associated prediction model to forecast patient survival in CRC using the least absolute shrinkage and selection operator and multifactorial COX regression and confirmed its reliable predictive ability.</p> Results <p>The model accurately reflected tumor microsatellite status, immune cell infiltration, and mutation burden. In addition, the model was significantly correlated with drug sensitivity; thus, it can guide the personalized treatment of tumors. Finally, the status of some prognosis-related genes was verified in clinical samples.</p> Conclusions <p>This study identified angiogenesis-associated molecular subtypes of CRC and constructed a prognostic model. This signature may provide a new basis for clinical judgment of patient prognosis and personalized therapy.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development of a novel angiogenesis-associated gene model for prognosis prediction in colorectal cancer

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月22日

查看全文
  • Yuguang Shen,
  • Tianshang Bao,
  • Tianli Yuan,
  • Yuanruohan Zhang,
  • Jian Tang,
  • Cheng Zhang

摘要

Background

The expression of angiogenesis-associated genes affects the development of colorectal cancer (CRC). In this study, we aimed to develop and evaluate a method to predict survival outcomes in patients with CRC.

Methods

We investigated the expression of CRC angiogenesis-associated genes using various public databases and identified diverse molecular subtypes. We built an angiogenesis-associated prediction model to forecast patient survival in CRC using the least absolute shrinkage and selection operator and multifactorial COX regression and confirmed its reliable predictive ability.

Results

The model accurately reflected tumor microsatellite status, immune cell infiltration, and mutation burden. In addition, the model was significantly correlated with drug sensitivity; thus, it can guide the personalized treatment of tumors. Finally, the status of some prognosis-related genes was verified in clinical samples.

Conclusions

This study identified angiogenesis-associated molecular subtypes of CRC and constructed a prognostic model. This signature may provide a new basis for clinical judgment of patient prognosis and personalized therapy.