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Generation of novel lipid metabolism-based signatures to predict prognosis and immunotherapy response for colorectal adenocarcinoma

  • 0Department of Oncology and Hematology, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou, 215127, China.
Scientific Reports +

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July 26, 2024

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July 26, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Lipid metabolism reprogramming impacts cancer progression. This study developed a lipid metabolism signature to predict colorectal adenocarcinoma prognosis and response to immunotherapy, identifying key genes for potential therapeutic targets.

Area Of Science

  • Oncology
  • Molecular Biology
  • Metabolomics

Background

  • Lipid metabolism reprogramming is crucial in cancer progression, influencing epithelial-mesenchymal transition (EMT), cancer stemness, and immune checkpoints (ICs).
  • Understanding these metabolic alterations is vital for predicting colorectal adenocarcinoma (COAD) patient outcomes and treatment responses.

Purpose Of The Study

  • To develop lipid metabolism-based signatures for predicting prognosis and response to immunotherapy and chemotherapy in COAD.
  • To identify key lipid metabolism-related genes associated with EMT, stemness, and ICs in COAD.

Main Methods

  • Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify gene modules correlated with EMT, stemness, and IC signatures in COAD.
  • Prognostic signatures were generated using hub genes identified from WGCNA, and their expression was validated using single-cell RNA sequencing (scRNA-seq) data.
  • Gene expression and clinical data from TCGA database were analyzed.

Main Results

  • COAD patients showed increased EMT and stemness scores with decreased ICs.
  • Twelve hub genes (e.g., PIK3CG, GGT5, PTGIS) were identified, and a prognostic signature based on PIK3CG, GGT5, and PTGIS was developed.
  • High-risk patients exhibited poor prognosis, elevated tumor microenvironment scores, and higher TIDE scores, while low-risk patients showed increased immunogenicity for immune checkpoint inhibitors (ICIs).
  • PIK3CG was found in B cells, and GGT5/PTGIS in stromal cells.

Conclusions

  • Lipid metabolism-based signatures can predict COAD prognosis and immunotherapy response.
  • The identified genes (PIK3CG, GGT5, PTGIS) represent potential therapeutic targets for COAD immunotherapy.

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