Literature DB >> 30777332

Prognostic significance of high metabolic activity in breast cancer: PET signature in breast cancer.

Sanghee Kang1, Eui Hyun Kim2, Jun-Eul Hwang3, Ji-Hyun Shin4, Yun Seong Jeong4, Sun Young Yim5, Eun Wook Joo6, Young Gyu Eun7, Dong Jin Lee8, Bo Hwa Sohn4, Sung Hwan Lee4, Bora Lim9, Ju-Seog Lee10.   

Abstract

High metabolic activity, reflected in increased glucose uptake, is one of the hallmarks of many cancers including breast cancer. However, not all cancers avidly take up glucose, suggesting heterogeneity in their metabolic demand. Thus, we aim to generate a genomic signature of glucose hypermetabolism in breast cancer and examine its clinical relevance. To identify genes significantly associated with glucose uptake, gene expression data were analyzed together with the standardized uptake values (SUVmax) of 18F-fluorodeoxy-glucose on positron emission tomography (PET) for 11 breast cancers. The resulting PET signature was evaluated for prognostic significance in four large independent patient cohorts (n = 5417). Potential upstream regulators accountable for the high glucose uptake were identified by gene network analysis. A PET signature of 242 genes was significantly correlated with SUVmax in breast cancer. In all four cohorts, high PET signature was significantly associated with poorer prognosis. The prognostic value of this PET signature was further supported by Cox regression analyses (hazard ratio 1.7, confidential interval 1.48-2.02; P < 0.001). The PET signature was also strongly correlated with previously established prognostic genomic signatures such as PAM50, Oncotype DX, and NKI. Gene network analyses suggested that MYC and TBX2 were the most significant upstream transcription factors in the breast cancers with high glucose uptake. A PET signature reflecting high glucose uptake is a novel independent prognostic factor in breast cancer. MYC and TBX2 are potential regulators of glucose uptake.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  (18)F-fluorodeoxy-glucose; Breast cancer; MYC; Positron emission tomography; TBX2

Year:  2019        PMID: 30777332     DOI: 10.1016/j.bbrc.2019.02.035

Source DB:  PubMed          Journal:  Biochem Biophys Res Commun        ISSN: 0006-291X            Impact factor:   3.575


  4 in total

1.  Conventional Nanosized Drug Delivery Systems for Cancer Applications.

Authors:  Cristian Vergallo; Muhammad Nadeem Hafeez; Dalila Iannotta; Hélder A Santos; Nicola D'Avanzo; Luciana Dini; Felisa Cilurzo; Massimo Fresta; Luisa Di Marzio; Celia Christian
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

2.  Diagnostic and prognostic significance of SLC50A1 expression in patients with primary early breast cancer.

Authors:  Qunchen Zhang; Yutong Fang; Chuanghong She; Rongji Zheng; Chaoqun Hong; Chunfa Chen; Jundong Wu
Journal:  Exp Ther Med       Date:  2022-08-05       Impact factor: 2.751

3.  Prediction of Overall Survival Among Female Patients With Breast Cancer Using a Prognostic Signature Based on 8 DNA Repair-Related Genes.

Authors:  Dai Zhang; Si Yang; Yiche Li; Jia Yao; Jian Ruan; Yi Zheng; Yujiao Deng; Na Li; Bajin Wei; Ying Wu; Zhen Zhai; Jun Lyu; Zhijun Dai
Journal:  JAMA Netw Open       Date:  2020-10-01

4.  Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.

Authors:  Dai Zhang; Yiche Li; Si Yang; Meng Wang; Jia Yao; Yi Zheng; Yujiao Deng; Na Li; Bajin Wei; Ying Wu; Zhen Zhai; Zhijun Dai; Huafeng Kang
Journal:  Cancer Med       Date:  2021-10-05       Impact factor: 4.452

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.