Comprehensive analysis of the association between tumor glycolysis and immune/inflammation function in breast cancer

Li, Wenhui; Xu, Ming; Liu, Yü; Huang, Ziwei; Zhou, Jun; Zhao, Qiu; Le, Kehao; Fang, Dong; Wan, Cheng; Yi, Pengfei

doi:10.1186/s12967-020-02267-2

Cited by 85 publications

(59 citation statements)

References 64 publications

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“…Li et al explored the association between glycolysis and the immune cells. They concluded that most of the immune cell type enrichment scores were remarkably higher in the high glycolysis group, including CD8 + naive T cells, Th1 cells, Th2 cells, NK cells, Monocytes, Macrophages M1, DC, and so on [ 43 ]. Taken together, glycolysis activity was closely related to immune activity, and immune function was activated as glycolysis was elevated in bladder cancer.…”

Section: Discussionmentioning

confidence: 99%

Correlations between glycolysis with clinical traits and immune function in bladder urothelial carcinoma

Che

Han

et al. 2021

Bioscience Reports

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Background: Glycolysis was a representative hallmark in the tumor microenvironment, and we aimed to explore the correlations between glycolysis with immune activity and clinical traits in bladder urothelial carcinoma (BLCA). Method: Our study obtained glycolysis scores for each BLCA samples from TCGA by a single-sample gene-set enrichment analysis(ssGSEA) algorithm, based on a glycolytic gene set. The relationship between glycolysis with prognosis, clinical characteristics, and immune activity were investigated. Results: We found that enhanced glycolysis was associated with poor prognosis and metastasis in BLCA. Moreover, glycolysis had a close correlation with immune function, and enhanced glycolysis increased immune activities. In other words, glycolysis had a positive correlation with immune activities. Immune checkpoints such as IDO1, CD274, were up-regulated in high-glycolysis group as well. Conclusion: We speculated that in BLCA, elevated glycolysis enhanced immune function, which caused tumor cells to overexpress immune checkpoints to evade immune surveillance. Inhibition of glycolysis might be a promising assistant for immunotherapy in bladder cancer.

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Section: Discussionmentioning

confidence: 99%

Correlations between glycolysis with clinical traits and immune function in bladder urothelial carcinoma

Che

Han

et al. 2021

Bioscience Reports

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“…Cascone et al found that in patients with melanoma and NSCLC, high glycolytic activity will be accompanied by poor immune cell infiltration, such as cytoxic T cells, T helper cells, memory T cells, macrophases, or natural killer (NK) cells reduction [ 46 ]. Li et al found that high glycolysis group had a higher immunescore and higher TIL percentage in breast cancer, however, the immune cells with anti-tumor effect were not enriched, and concluded that high glycolysis was associated with immunosuppression of tumor microenvironment [ 47 ]. In our study, the expression levels of CD8 T cells and resting mast cells were significantly higher in the low-risk group.…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer

Cai

et al. 2020

BMC Cancer

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Background Cervical cancer (CC) is one of the most common gynaecological cancers. The gene signature is believed to be reliable for predicting cancer patient survival. However, there is no relevant study on the relationship between the glycolysis-related gene (GRG) signature and overall survival (OS) of patients with CC. Methods We extracted the mRNA expression profiles of 306 tumour and 13 normal tissues from the University of California Santa Cruz (UCSC) Database. Then, we screened out differentially expressed glycolysis-related genes (DEGRGs) among these mRNAs. All patients were randomly divided into training cohort and validation cohort according to the ratio of 7: 3. Next, univariate and multivariate Cox regression analyses were carried out to select the GRG with predictive ability for the prognosis of the training cohort. Additionally, risk score model was constructed and validated it in the validation cohort. Results Six mRNAs were obtained that were associated with patient survival. The filtered mRNAs were classified into the protective type (GOT1) and the risk type (HSPA5, ANGPTL4, PFKM, IER3 and PFKFB4). Additionally, by constructing the prognostic risk score model, we found that the OS of the high-risk group was notably poorer, which showed good predictive ability both in training cohort and validation cohort. And the six-gene signature is a prognostic indicator independent of clinicopathological features. Through the verification of PCR, the results showed that compared with the normal cervial tissuses, the expression level of six mRNAs were significantly higher in the CC tissue, which was consistent with our findings. Conclusions We constructed a glycolysis-related six-gene signature to predict the prognosis of patients with CC using bioinformatics methods. We provide a thorough comprehension of the effect of glycolysis in patients with CC and provide new targets and ideas for individualized treatment.

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“…Breast IDC is the most common pathological type of breast tumor, and morbidity and mortality from this cancer continue to increase ( Harbeck et al, 2019 ; Badve & Gokmen-Polar, 2019 ). There is evidence that changes in glycolysis-related genes have multiple effects on the prognosis of these patients ( Li et al., 2020a ; Li et al., 2020b ; Chen et al, 2019 ). In particular, tumor cells reprogram the glycolysis pathway to accommodate the increased energy required for malignant transformations, including invasion and metastasis ( Shen et al, 2020 ; Abbaszadeh, Cesmeli & Biray, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…The prognosis of women with breast IDC is related to the activation or silencing of various biological functions in tumor tissues and signaling pathways. There are prognostic models based on tumor immunity and autophagy, but no models have exclusively focused on IDC ( Li et al., 2020a ; Li et al., 2020b ; Zhang, Zhang & Yu, 2019 ; Hu et al, 2020 ) and few models examined genes that function in basic metabolism.…”

Section: Introductionmentioning

confidence: 99%

Prognostic model of invasive ductal carcinoma of the breast based on differentially expressed glycolysis-related genes

Chen

et al. 2020

PeerJ

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Background Invasive ductal carcinoma (IDC) is a common pathological type of breast cancer that is characterized by high malignancy and rapid progression. Upregulation of glycolysis is a hallmark of tumor growth, and correlates with the progression of breast cancer. We aimed to establish a model to predict the prognosis of patients with breast IDC based on differentially expressed glycolysis-related genes (DEGRGs). Methods Transcriptome data and clinical data of patients with breast IDC were from The Cancer Genome Atlas (TCGA). Glycolysis-related gene sets and pathways were from the Molecular Signatures Database (MSigDB). DEGRGs were identified by comparison of tumor tissues and adjacent normal tissues. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to screen for DEGRGs with prognostic value. A risk-scoring model based on DEGRGs related to prognosis was constructed. Receiver operating characteristic (ROC) analysis and calculation of the area under the curve (AUC) were used to evaluate the performance of the model. The model was verified in different clinical subgroups using an external dataset (GSE131769). A nomogram that included clinical indicators and risk scores was established. Gene function enrichment analysis was performed, and a protein-protein interaction network was developed. Results We analyzed data from 772 tumors and 88 adjacent normal tissues from the TCGA database and identified 286 glycolysis-related genes from the MSigDB. There were 185 DEGRGs. Univariate Cox regression and LASSO regression indicated that 13 of these genes were related to prognosis. A risk-scoring model based on these 13 DEGRGs allowed classification of patients as high-risk or low-risk according to median score. The duration of overall survival (OS) was longer in the low-risk group (P < 0.001), and the AUC was 0.755 for 3-year OS and 0.726 for 5-year OS. The results were similar when using the GEO data set for external validation (AUC for 3-year OS: 0.731, AUC for 5-year OS: 0.728). Subgroup analysis showed there were significant differences in OS among high-risk and low-risk patients in different subgroups (T1-2, T3-4, N0, N1-3, M0, TNBC, non-TNBC; all P < 0.01). The C-index was 0.824, and the AUC was 0.842 for 3-year OS and 0.808 for 5-year OS from the nomogram. Functional enrichment analysis demonstrated the DEGRGs were mainly involved in regulating biological functions. Conclusions Our prognostic model, based on 13 DEGRGs, had excellent performance in predicting the survival of patients with IDC of the breast. These DEGRGs appear to have important biological functions in the progression of this cancer.

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Comprehensive analysis of the association between tumor glycolysis and immune/inflammation function in breast cancer

Cited by 85 publications

References 64 publications

Correlations between glycolysis with clinical traits and immune function in bladder urothelial carcinoma

Correlations between glycolysis with clinical traits and immune function in bladder urothelial carcinoma

Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer

Prognostic model of invasive ductal carcinoma of the breast based on differentially expressed glycolysis-related genes

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