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Qualitative Transcriptional Signature for Predicting the Pathological Response of Colorectal Cancer to FOLFIRI Therapy

  • 0Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, Institute of Precision Medicine, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou 350122, China.
International Journal of Molecular Sciences +

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December 17, 2024

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December 17, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new predictive signature accurately identifies metastatic colorectal cancer patients who will benefit from FOLFIRI chemotherapy. This discovery improves treatment selection for this common cancer.

Area Of Science

  • Oncology
  • Genomics
  • Translational Medicine

Background

  • First-line chemotherapy for metastatic colorectal cancer (mCRC), FOLFIRI, shows response rates below 50%.
  • Predicting FOLFIRI response is crucial for optimizing treatment strategies in mCRC patients.

Purpose Of The Study

  • To develop and validate a predictive gene signature for FOLFIRI chemotherapy response in mCRC patients.
  • To identify novel biomarkers associated with FOLFIRI efficacy.

Main Methods

  • Utilized Spearman's rank correlation and Wilcoxon rank-sum test for gene selection.
  • Developed a three-gene pair (3-GPS) predictive signature through an optimization procedure.
  • Validated the signature in two independent patient cohorts.

Main Results

  • The 3-GPS signature achieved 0.94 accuracy in the training set.
  • In validation sets, predicted responders demonstrated significantly improved progression-free survival (HR=0.47, p=0.01 and HR=0.06, p=0.02).
  • Signature genes are linked to immunotherapy response pathways and immune cell types.

Conclusions

  • The developed REO-based signature effectively predicts FOLFIRI benefit in mCRC.
  • Signature genes may play a critical role in chemotherapy response and could be therapeutic targets.

Keywords: