A lactate-related LncRNA model for predicting prognosis, immune landscape and therapeutic response in breast cancer

Abstract

Breast cancer (BC) has the highest incidence rate of all cancers globally, with high heterogeneity. Increasing evidence shows that lactate and long non-coding RNA (lncRNA) play a critical role in tumor occurrence, maintenance, therapeutic response, and immune microenvironment. We aimed to construct a lactate-related lncRNAs prognostic signature (LRLPS) for BC patients to predict prognosis, tumor microenvironment, and treatment responses. The BC data download from the Cancer Genome Atlas (TCGA) database was the entire cohort, and it was randomly assigned to the training and test cohorts at a 1:1 ratio. Difference analysis and Pearson correlation analysis identified 196 differentially expressed lactate-related lncRNAs (LRLs). The univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to construct the LRLPS, which consisted of 7 LRLs. Patients could be assigned into high-risk and low-risk groups based on the medium-risk sore in the training cohort. Then, we performed the Kaplan–Meier survival analysis, time-dependent receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. The results indicated that the prognosis prediction ability of the LRLPS was excellent, robust, and independent. Furthermore, a nomogram was constructed based on the LRLPS risk score and clinical factors to predict the 3-, 5-, and 10-year survival probability. The GO/KEGG and GSEA indicated that immune-related pathways differed between the two-risk group. CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore (IPS) showed that low-risk patients had higher levels of immune infiltration and better immunotherapeutic response. The pRRophetic and CellMiner databases indicated that many common chemotherapeutic drugs were more effective for low-risk patients. In conclusion, we developed a novel LRLPS for BC that could predict the prognosis, immune landscape, and treatment response.

Dissecting the role of lactate metabolism LncRNAs in the progression and immune microenvironment of osteosarcoma

“…Numerous studies have previously demonstrated that lactate metabolism-associated lncRNAs significantly affect the evolution of various tumors. Li et al [32] successfully developed a lactate metabolism-associated lncRNAs signature for predicting the prognosis of breast cancer; Xia et al [50] developed a signature to assess the prognosis of patients with hepatocellular carcinoma using lactate metabolism-associated lncRNAs which was found to be significantly relevant to immune infiltration; Mai et al [51] generated a lactate metabolism-associated lncRNAs marker that accurately predicted lung cancer prognosis and had a significant impact on the tumor immune microenvironment. However, studies on genes related to lactate metabolism are still relatively scarce in the progression of osteosarcoma.…”

“…Nowadays LncRNA expression levels have been widely used in the diagnosis and prognosis prediction of osteosarcoma, for example, Wang et al [28] found that LINC00629 promotes osteosarcoma progression through activation of the KLF4-LAMA4 axis; Yang et al [29] identified six copper death-associated lncRNAs that regulate the immune microenvironment in osteosarcoma and influence survival outcomes in osteosarcoma patients. Notably, recent studies have found that LncRNAs may target lactate metabolism to influence tumor progression [30] , [31] , [32] , but the mechanics of the role of LRLs in osteosarcoma are unclear. Therefore, our study focused on finding a new signature of LRLs that can predict the prognosis of osteosarcoma.…”