Amino Acid Metabolism-Related lncRNA Signature Predicts the Prognosis of Breast Cancer

Abstract

Background and Purpose: Breast cancer (BRCA) is the most frequent female malignancy and is potentially life threatening. The amino acid metabolism (AAM) has been shown to be strongly associated with the development and progression of human malignancies. In turn, long noncoding RNAs (lncRNAs) exert an important influence on the regulation of metabolism. Therefore, we attempted to build an AAM-related lncRNA prognostic model for BRCA and illustrate its immune characteristics and molecular mechanism.Experimental Design: The RNA-seq data for BRCA from the TCGA-BRCA datasets were stochastically split into training and validation cohorts at a 3:1 ratio, to construct and validate the model, respectively. The amino acid metabolism-related genes were obtained from the Molecular Signature Database. A univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression, and a multivariate Cox analysis were applied to create a predictive risk signature. Subsequently, the immune and molecular characteristics and the benefits of chemotherapeutic drugs in the high-risk and low-risk subgroups were examined.Results: The prognostic model was developed based on the lncRNA group including LIPE-AS1, AC124067.4, LINC01655, AP005131.3, AC015802.3, USP30-AS1, SNHG26, and AL589765.4. Low-risk patients had a more favorable overall survival than did high-risk patients, in accordance with the results obtained for the validation cohort and the complete TCGA cohort. The elaborate results illustrated that a low-risk index was correlated with DNA-repair–associated pathways; a low TP53 and PIK3CA mutation rate; high infiltration of CD4+ T cells, CD8+ T cells, and M1 macrophages; active immunity; and less-aggressive phenotypes. In contrast, a high-risk index was correlated with cancer and metastasis-related pathways; a high PIK3CA and TP53 mutation rate; high infiltration of M0 macrophages, fibroblasts, and M2 macrophages; inhibition of the immune response; and more invasive phenotypes.Conclusion: In conclusion, we attempted to shed light on the importance of AAM-associated lncRNAs in BRCA. The prognostic model built here might be acknowledged as an indispensable reference for predicting the outcome of patients with BRCA and help identify immune and molecular characteristics.

Construction and validation of a novel cuproptosis-related long noncoding RNA signature for predicting the outcome of prostate cancer

“…Previous studies have found that lncRNA LIPE-AS1 is overexpressed in a variety of tumor types, including cervical cancer and breast cancer, compared with normal tissues. Several studies have also shown that high expression of LIPE-AS1 is associated with better prognosis ( Liu et al, 2021a ; Xu et al, 2021 ; Dai et al, 2022 ), consistent with our results. Xu et al showed that the expression of LIPE-AS1 was significantly correlated with that of the PD-L1 gene ( Xu et al, 2021 ).…”

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

“…We also listed the other signatures that focus more on short-term (3- and 5-year survival) survival. We found our signature usually have better short-term survival prognostic value compared with them, such as the necroptosis-related lncRNA signature ( Zhang et al, 2022 ), hypoxia-related lncRNA signature ( Zhao et al, 2021 ), autophagy-related lncRNA signature ( Li et al, 2021 ), ferroptosis-related lncRNA signature ( Jia et al, 2021 ), N6-methyladenosine-related lncRNA signature ( Lv et al, 2021 ), acid metabolism-related lncRNA signature ( Dai et al, 2022 ), and CD4 + conventional T cells-related lncRNA signature ( Ning et al, 2022 ) and pyroptosis-related lncRNA signature ( Yang et al, 2021 ). In addition, our model only involves 7 lncRNAs, while other models (6/11) tend to have more, which is more convenient to use to a certain extent.…”

T2DB: A Web Database for Long Non-Coding RNA Genes in Type II Diabetes

“…In this study, we have found that USP30-AS1 influences the activation of macrophage-like cells. Interestingly, USP30-AS1 has been implicated to be a potential prognostic risk factor for cancer and to play a role in cell death (e.g., apoptosis, autophagy, ferroptosis, and necroptosis) [ 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 ]. Furthermore, USP30-AS1 promotes cell viability and inhibits apoptosis in acute myeloid leukemia cell lines, including THP-1 [ 100 ].…”