A novel lactate metabolism-related signature predicts prognosis and tumor immune microenvironment of breast cancer

Abstract

Background: Lactate, an intermediate product of glycolysis, has become an essential regulator of tumor maintenance, development, and metastasis. Lactate can drive tumors by changing the microenvironment of tumor cells. Because of lactate’s important role in cancer, we aim to find a novel prognostic signature based on lactate metabolism-related genes (LMRGs) of breast cancer (BC).Methods: RNA-sequencing data and clinical information of BC were enrolled from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We obtained LMRGs from the Molecular Signature Database v7.4 and articles, and then we compared candidate genes with TCGA data to get differential genes. Univariate analysis and most minor absolute shrinkage and selector operator (LASSO) Cox regression were employed to filter prognostic genes. A novel lactate metabolism-related risk signature was constructed using a multivariate Cox regression analysis. The signature was validated by time-dependent ROC curve analyses and Kaplan–Meier analyses in TCGA and GEO cohorts. Then, we further investigated in depth the function of the model’s immune microenvironment.Results: We constructed a 3-LMRG-based risk signature. Kaplan–Meier curves confirmed that high-risk score subgroups had a worse prognosis in TCGA and GEO cohorts. Then a nomogram to predict the probability of survival for BC was constructed. We also performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function analysis. The function analysis showed that the lactate metabolism-related signature was significantly related to immune response. A significant correlation was observed between prognostic LMRGs and tumor mutation burden, checkpoints, and immune cell infiltration. An mRNA–miRNA network was built to identify an miR-203a-3p/LDHD/LYRM7 regulatory axis in BC.Conclusion: In conclusion, we constructed a novel 3-LMRG signature and nomogram that can be used to predict the prognosis of BC patients. In addition, the signature is closely related to the immune microenvironment, which may provide new insight into future anticancer therapies.

Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer

“…Construction and validation of the NMRS. some existing BC biomarkers, our gene signature had better predictive performance with higher AUC and c-index values (Figures 4F-I) (48)(49)(50). Using a BC cohort from the ICGC database, we performed external validation to further confirm the predictive capacity of the NMRS.…”

A breast cancer classification and immune landscape analysis based on cancer stem-cell-related risk panel

“…In order to avoid genes involved in the same biological process that might be linked or even screened for duplicate genes, we deliberately chose three models in different directions. The three signatures we selected were associated with breast cancer prognosis; these were a macrophage marker gene signature (Li et al) 11 , a lactate metabolism-related gene signature (Zhang et al) 12 , and a ferroptosis-related gene signature (Wang et al) 13 . The risk score for each breast cancer patient was calculated as per the original method, and all patients in TCGA were divided into high- and low-risk groups according to the median for further survival analysis.…”

Molecular and serological biomarkers to predict trastuzumab responsiveness in HER-2 positive breast cancer

“…Such stimulation is triggered by different molecules, such as kinases, phosphatases, and phospholipases, which account for the expression of immune checkpoint molecules in these effector cells (CD8, CD4, and T-Reg) [ 25 ]. The finding implies that in response to trastuzumab, expression of CTLA-4 in peripheral cells may be important in modulating patients' immune responses and cancer defenses.…”