Characterization of glucose metabolism in breast cancer to guide clinical therapy

Yingying Mei; Lantao Zhao; Man Jiang; Fangfang Yang; Xiaochun Zhang; Yizhen Jia; Na Zhou

doi:10.3389/fsurg.2022.973410

Characterization of glucose metabolism in breast cancer to guide clinical therapy

Front Surg. 2022 Sep 19:9:973410. doi: 10.3389/fsurg.2022.973410. eCollection 2022.

Authors

Yingying Mei¹, Lantao Zhao², Man Jiang¹, Fangfang Yang¹, Xiaochun Zhang¹, Yizhen Jia³, Na Zhou¹

Affiliations

¹ Precision Medicine Center of Oncology, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China.
² Department of Anesthesiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
³ Core Laboratory, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.

Abstract

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 × 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.

Keywords: breast cancer; drug sensitivity; glucose metabolism; immune infiltration; prognosis.