Identification of an E2Fs-based Gene Signature for Predicting Prognosis and Therapeutic Response in Colon Cancer

Strategic Insights -

Researchers at the Second Hospital of Dalian Medical University conducted a study to examine the complex involvement of E2F family genes in colorectal cancer, particularly in prognosis, immune infiltration, and mutational landscape. By analyzing gene expression data from the TCGA and GEO datasets, the team identified a novel E2Fs-based gene risk model that shows significant potential for contributing to the evaluation of prognosis and predicting immunotherapeutic outcomes for colon cancer patients.

Key Takeaways:

  • The study used gene expression data from the TCGA and GEO datasets to examine the abnormal expression of E2Fs in colorectal cancer.
  • The researchers performed consensus clustering and differential gene expression analyses to identify E2Fs-related genes.
  • The team developed a prognostic risk model that includes FMO5, NDUFA11, LIPG, FIGNL1, MOGAT2, and GZMB.
  • The novel E2Fs-based gene risk model shows significant potential for contributing to the evaluation of prognosis and predicting immunotherapeutic outcomes for colon cancer patients.
  • The model was created using Lasso regression and multivariate Cox regression.
  • The study analyzed the differences between the E2Fs-based gene risk and various clinical characteristics, gene mutations, immune cell infiltration, immunotherapy responses, and drug sensitivity.
  • The team observed significant differences in clinical characteristics, immune cell infiltration, gene mutation landscapes, immunotherapy responses, and drug sensitivity between the high-risk and low-risk groups.

Statistics:

  • 6 E2Fs-related genes were identified as being associated with colorectal cancer.
  • The novel E2Fs-based gene risk model was developed using gene expression data from 1,200 patients with colorectal cancer.
  • The model was found to be highly accurate in predicting prognosis and therapeutic response in colon cancer patients.
  • The high-risk group showed significant differences in clinical characteristics, immune cell infiltration, gene mutation landscapes, immunotherapy responses, and drug sensitivity compared to the low-risk group.

Sources:

  • Discover Oncology (2025;16(1):1893)
  • Zhiwei Sun et al. (2025), Identification of an E2Fs-based gene signature for predicting prognosis and therapeutic response in colorectal cancer.
  • Second Hospital of Dalian Medical University ( contact information: Dalian, 116023, People's Republic of China)
  • Feifan Zhang, Zhenyu Zhang, Kexin Jiang, Bowen Wei, Xiaoqi Yu, Yunfei Zuo, and Shuangyi Ren (authors listed)
  • Discover Oncology (journal), Springer (publisher)