4.4 Article

Characterization of glucose metabolism in breast cancer to guide clinical therapy

Journal

FRONTIERS IN SURGERY
Volume 9, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fsurg.2022.973410

Keywords

breast cancer; glucose metabolism; prognosis; immune infiltration; drug sensitivity

Categories

Funding

  1. Qilu health leader training project
  2. National Natural Science Foundation of China
  3. [81702605]

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A novel glycometabolism-related gene (GRG) signature was constructed to predict overall survival (OS), immune infiltration, and therapeutic response in breast cancer patients. High-risk patients correlated with poorer OS, higher M2 macrophage infiltration, and greater sensitivity to Lapatinib. SDC1 was identified as a candidate target and patients in the low-SDC1 group had a better OS.
Background Breast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients. Materials and methods The mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of rms . Results We constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 x 10(-7)). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8(+) T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS. Conclusions We identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients.

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