Identification of a novel glycolysis-related signature to predict the prognosis of patients with breast cancer

He, Menglin; Hu, Cheng; Deng, Jianzhi; Ji, Hui; Tian, Weiqian

doi:10.1186/s12957-021-02409-w

Cited by 9 publications

(8 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both glycolysis and oxidative stress are demonstrated to be activated in BC tissues [ 20 , 25 ]. Herein, the result of GSEA implied that both glycolysis and response to oxidative stress were regulated by LINC00092 in BC tissues ( Figure 4(a) ).…”

Section: Resultsmentioning

confidence: 99%

“…As the main manner for BC cells to produce ATP, glycolysis is essential for BC growth [ 20 ]. Earlier literature reported that even in aerobic environment, BC cells still will choose glycolysis as the main manner for energy supplement [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

“…Lots of literatures reported that glycolysis was promoted in many human cancer cells, including BC cells [ 18 ]. Actually, glycolysis is the main manner for BC cells to produce ATP, which is one of the important characteristics of malignant progression for BC [ 19 , 20 ]. As key regulators of gene expressions in cells, many lncRNAs are discovered to take part in the modulation of glycolysis, including in BC cells [ 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

LINC00092 Modulates Oxidative Stress and Glycolysis of Breast Cancer Cells via Pyruvate Carboxylase-Mediated AKT/mTOR Pathway

Chen

Liu

Kang

et al. 2022

Oxidative Medicine and Cellular Longevity

View full text Add to dashboard Cite

Background. The discovery of noncoding RNAs (ncRNAs) offers new options for cancer-targeted therapy. This study is aimed at exploring the regulatory function of LINC00092 on breast cancer (BC) oxidative stress and glycolysis, along with internal mechanism concerning pyruvate carboxylase (PC). Methods. Bioinformatics analysis was used to explore LINC00092 (or friend leukemia virus integration 1 (FLI1)) expression on BC progression, as well as oxidative stress and glycolysis in BC. After LINC00092 overexpression or silence, BC cell viability, proliferation, migration, invasion, oxidative stress, glycolysis, and AKT/mTOR pathway were detected. Following 2-DG, SC79, or MK2206 treatment, effects of LINC00092 on BC cells were measured. Moreover, regulatory activity of LINC00092 in PC expression was analyzed. Whether PC participated in the modulation of LINC00092 on BC cell functions was explored. Results. LINC00092 was lowly expressed in BC and negatively related to BC progression. FLI1 bound to LINC00092 promoter to positively modulate LINC00092. LINC00092 overexpression inhibited BC cell proliferation, migration, invasion, oxidative stress, glycolysis, and AKT/mTOR pathway and likewise suppressed BC growth in vivo. Silence of LINC00092 had opposite influences. 2-DG partially reversed the LINC00092 silence-resulted increase of BC cell proliferation. SC79 alleviated the function of LINC00092 overexpression on BC cell functions. MK2206 had the contrary influence of SC79. Besides, LINC00092 bound to PC to modulate ubiquitination degradation of PC protein. PC took part in the influences of LINC00092 on BC cell functions. Conclusions. LINC0092 modulates oxidative stress and glycolysis of BC cells via the PC-mediated AKT/mTOR pathway, which is possibly a target for BC diagnosis and therapy.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

LINC00092 Modulates Oxidative Stress and Glycolysis of Breast Cancer Cells via Pyruvate Carboxylase-Mediated AKT/mTOR Pathway

Chen

Liu

Kang

et al. 2022

Oxidative Medicine and Cellular Longevity

View full text Add to dashboard Cite

show abstract

“…2F). To comprehensively analyze the prognostic ability of IL score, four risk models [36][37][38][39] from previous studies were collected to compare with the prognostic prediction capacity. The landscape of clinicopathological features in the risk model.…”

Section: Validation and Comparison Of Il Scorementioning

confidence: 99%

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Bai

Wang³

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Breast cancer (BRCA) is the most prevalent malignancy and the leading cause of death in women. Interleukin (IL) genes are critical in tumor initiation and control. Nevertheless, the prognosis value of the IL in BRCA remains unclear. We collected data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and 94 IL genes were identified from GeneCard. Based on the random forest (RF), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression analysis, we constructed an IL signature. GSE22219, GSE25065, and GSE21653 were derived as validation sets. The expression differences in the tumor microenvironment (TME), immunotherapy, and chemosensitivity of BRCA between the high- and low-risk groups were evaluated. Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA. IL score could distinguish BRCA patients with inferior outcomes, and AUC of it was 0.70, 0.76, and 0.72 for 1-,3- and 5- years, respectively, which was also verified in GSE22219, GSE25065, and GSE21653 cohorts. Meanwhile, compared to luminal A and luminal B, HER2-positive and TNBC had significantly higher IL score. Besides, the high-risk group had a significantly higher prevalence of TP53 and TTN but a lower prevalence of PIK3CA, as well as higher tumor mutation burden (TMB) and neoantigen level. High- and low-risk groups exhibited notable differences in immunomodulators and tumor infiltrates immune cells (TIICs), and the high-risk group had significantly lower Tumor Immune Dysfunction and Exclusion (TIDE) score. Additionally, the high-risk group has more responders to immune or anti-HER2 combination therapy, whereas the low-risk group has higher sensitivity to docetaxel and paclitaxel. Consequently, we constructed a reliable risk model based on the IL genes, which can provide more information on both the risk stratification and personalizing management strategies for BRCA.

show abstract

“…A gene expression signature consisting with several genetic markers might improve the specificity and sensitivity of prediction for GC. Some studies using data from public databases have also shown that glycolysis-related genes can predict the prognosis of cancer patients, including those with clear cell renal cell carcinoma ( 11 ), lung adenocarcinoma ( 12 ), hepatocellular carcinoma ( 13 ), breast cancer ( 14 , 15 ), ovarian cancer ( 16 ), and colorectal cancer ( 17 ). Additionally, recent research has shown that glycolysis-related genes might be used to effectively assess the prognosis of GC patients ( 18 , 19 ).…”

Section: Introductionmentioning

confidence: 99%

Identification and verification of a glycolysis-related gene signature for gastric cancer

Liu¹,

Wu²,

Cao³

et al. 2022

Ann Transl Med

View full text Add to dashboard Cite

Background: Glycolysis is a central metabolic pathway for tumor cells. However, the relationship between glycolysis and the prognosis of gastric cancer (GC) patients is not well established. In this study, we sought to construct a glycolysis-related gene signature for GC. Methods:The messenger ribonucleic acid (mRNA) expression profiles were analyzed using data from The Cancer Genome Atlas (TCGA) database. Glycolysis-related gene sets and pathways were obtained from the Molecular Signatures Database (MSigDB). Subsequently, a prognosis prediction model of the glycolysisrelated genes was constructed using Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. An external validation was conducted using data from the Gene Expression Omnibus (GEO) database. Risk scores were also calculated based on the signature. Finally, the correlations between the risk score and overall survival (OS), mutation, immune cell infiltration, immune score, and stromal score were examined in 22 types of infiltrating immune cells.Results: Fifty-five glycolysis-related genes were identified from TCGA database and MSigDB. Using the LASSO and Cox models, 4 novel genes (i.e., VCAN, EFNA3, ADH4, and CLDN9) were identified to construct a gene signature for GC prognosis prediction. The GC patients with low-risk scores had significantly better OS than those with high-risk scores in the training set. Similar results were also found in the independent GEO GSE84437 testing set. Additionally, the degree of cell infiltration in the low-risk group was significantly higher than that in the high-risk group in terms of naive B cells, plasma cells, and T follicular helper cells. In monocytes, M2 macrophages, resting dendritic cells, and resting Mast cells, the degree of infiltration in the high-risk group was significantly higher than that in the low-risk group. The immune score and stromal score of the high-risk group were also significantly higher than those of the lowrisk group. Finally, the univariate and multivariate Cox regression analyses showed that 4 glycolysis-related genes were independent prognostic factors for GC. Conclusions:The established 4 glycolysis-related gene signature may serve as a reliable tool for the prognosis of GC patients and provide a potential glycolysis therapeutic target for GC.

show abstract

Identification of a novel glycolysis-related signature to predict the prognosis of patients with breast cancer

Cited by 9 publications

References 52 publications

LINC00092 Modulates Oxidative Stress and Glycolysis of Breast Cancer Cells via Pyruvate Carboxylase-Mediated AKT/mTOR Pathway

LINC00092 Modulates Oxidative Stress and Glycolysis of Breast Cancer Cells via Pyruvate Carboxylase-Mediated AKT/mTOR Pathway

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Identification and verification of a glycolysis-related gene signature for gastric cancer

Contact Info

Product

Resources

About