IMPORTANCE There is a lack of studies exploring whether the survival of patients with distant lymph node metastases (DLNM) is different from that of patients with ipsilateral supraclavicular lymph node metastases (ISLM) and other stage IV breast cancer. OBJECTIVE To assess the survival of patients with DLNM from breast cancer vs ISLM and other stage IV breast cancer.
Background Lipid metabolism is closely related to the occurrence and development of breast cancer. Our purpose was to establish a novel model based on lipid metabolism‐related long noncoding RNAs (lncRNAs) and evaluate the potential clinical value in predicting prognosis for patients suffering from breast cancer. Methods RNA data and clinical information for breast cancer were obtained from the cancer genome atlas (TCGA) database. Lipid metabolism‐related lncRNAs were identified via the criteria of correlation coefficient | R 2 | > 0.4 and p < 0.001, and prognostic lncRNAs were identified to establish model through Cox regression analysis. The training set and validation set were established to certify the feasibility, and all samples were separated into high‐risk group or low‐risk group. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were conducted to evaluate the potential biological functions, and the immune infiltration levels were explored through Cibersortx database. Results A total of 14 lncRNAs were identified as protective genes (AC022150.4, AC061992.1, AC090948.3, AC092794.1, AC107464.3, AL021707.8, AL451085.2, AL606834.2, FLJ42351, LINC00926, LINC01871, TNFRSF14−AS1, U73166.1 and USP30−AS1) with HRs < 1 while 10 lncRNAs (AC022150.2, AC090948.1, AC243960.1, AL021707.6, ITGB2−AS1, OTUD6B−AS1, SP2−AS1, TOLLIP−AS1, Z68871.1 and ZNF337−AS1) were associated with increased risk with HRs >1. A total of 24 prognostic lncRNAs were selected to construct the model. The patients in low‐risk group were associated with better prognosis in both training set ( p < 0.001) and validation set ( p < 0.001). The univariate and multivariate Cox regression analyses revealed that risk score was an independent prognostic factors in both training set ( p < 0.001) and validation set ( p < 0.001). GO and GSEA analyses revealed that these lncRNAs were related to metabolism‐related signal pathway and immune cells signal pathway. Risk score was negatively correlated with B cells ( r = −0.097, p = 0.002), NK cells ( r = −0.097, p = 0.002), Plasma cells ( r = −0.111, p = 3.329e‐04), T‐cells CD4 ( r = −0.064, p = 0.039) and T‐cells CD8 ( r = −0.322, p = 2.357e‐26) and positively correlated with Dendritic cells ( r = 0.077, p = 0.013) and Monocytes ( r = 0.228, p = 1.107e‐13). Conclusion The prognostic model based on lipid metabolism lncRNAs possessed an impo...
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